<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Haas, Mary</style></author><author><style face="normal" font="default" size="100%">Ajmera, Veeral</style></author><author><style face="normal" font="default" size="100%">Simon, Tracey G</style></author><author><style face="normal" font="default" size="100%">Homburger, Julian</style></author><author><style face="normal" font="default" size="100%">Neben, Cynthia</style></author><author><style face="normal" font="default" size="100%">Jiang, Lan</style></author><author><style face="normal" font="default" size="100%">Wei, Wei-Qi</style></author><author><style face="normal" font="default" size="100%">Feng, Qiping</style></author><author><style face="normal" font="default" size="100%">Zhou, Alicia</style></author><author><style face="normal" font="default" size="100%">Denny, Joshua</style></author><author><style face="normal" font="default" size="100%">Corey, Kathleen</style></author><author><style face="normal" font="default" size="100%">Loomba, Rohit</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association of Genetic Variation With Cirrhosis: A Multi-Trait Genome-Wide Association and Gene-Environment Interaction Study.</style></title><secondary-title><style face="normal" font="default" size="100%">Gastroenterology</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Gastroenterology</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">160</style></volume><pages><style face="normal" font="default" size="100%">1620-1633.e13</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND &amp; AIMS: &lt;/b&gt;In contrast to most other common diseases, few genetic variants have been identified that impact risk of cirrhosis. We aimed to identify new genetic variants that predispose to cirrhosis, to test whether such variants, aggregated into a polygenic score, enable genomic risk stratification, and to test whether alcohol intake or body mass index interacts with polygenic predisposition.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We conducted a multi-trait genome-wide association study combining cirrhosis and alanine aminotransferase levels performed in 5 discovery studies (UK Biobank, Vanderbilt BioVU, Atherosclerosis Risk in Communities study, and 2 case-control studies including 4829 individuals with cirrhosis and 72,705 controls and 362,539 individuals with alanine aminotransferase levels). Identified variants were replicated in 3 studies (Partners HealthCare Biobank, FinnGen, and Biobank Japan including 3554 individuals with cirrhosis and 343,826 controls). A polygenic score was tested in Partners HealthCare Biobank.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Five previously reported and 7 newly identified genetic variants were associated with cirrhosis in both the discovery studies multi-trait genome-wide association study (P &lt; 5 × 10) and the replication studies (P &lt; .05), including a missense variant in the APOE gene and a noncoding variant near EFN1A. These 12 variants were used to generate a polygenic score. Among Partners HealthCare Biobank individuals, high polygenic score-defined as the top quintile of the distribution-was associated with significantly increased risk of cirrhosis (odds ratio, 2.26; P &lt; .001) and related comorbidities compared with the lowest quintile. Risk was even more pronounced among those with extreme polygenic risk (top 1% of the distribution, odds ratio, 3.16; P &lt; .001). The impact of extreme polygenic risk was substantially more pronounced in those with elevated alcohol consumption or body mass index. Modeled as risk by age 75 years, probability of cirrhosis with extreme polygenic risk was 13.7%, 20.1%, and 48.2% among individuals with no or modest, moderate, and increased alcohol consumption, respectively (P &lt; .001). Similarly, probability among those with extreme polygenic risk was 6.5%, 10.3%, and 19.5% among individuals with normal weight, overweight, and obesity, respectively (P &lt; .001).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Twelve independent genetic variants, 7 of which are newly identified in this study, conferred risk for cirrhosis. Aggregated into a polygenic score, these variants identified a subset of the population at substantially increased risk who are most susceptible to the hepatotoxic effects of excess alcohol consumption or obesity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33310085?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chen, Lei</style></author><author><style face="normal" font="default" size="100%">Abel, Haley J</style></author><author><style face="normal" font="default" size="100%">Das, Indraniel</style></author><author><style face="normal" font="default" size="100%">Larson, David E</style></author><author><style face="normal" font="default" size="100%">Ganel, Liron</style></author><author><style face="normal" font="default" size="100%">Kanchi, Krishna L</style></author><author><style face="normal" font="default" size="100%">Regier, Allison A</style></author><author><style face="normal" font="default" size="100%">Young, Erica P</style></author><author><style face="normal" font="default" size="100%">Kang, Chul Joo</style></author><author><style face="normal" font="default" size="100%">Scott, Alexandra J</style></author><author><style face="normal" font="default" size="100%">Chiang, Colby</style></author><author><style face="normal" font="default" size="100%">Wang, Xinxin</style></author><author><style face="normal" font="default" size="100%">Lu, Shuangjia</style></author><author><style face="normal" font="default" size="100%">Christ, Ryan</style></author><author><style face="normal" font="default" size="100%">Service, Susan K</style></author><author><style face="normal" font="default" size="100%">Chiang, Charleston W K</style></author><author><style face="normal" font="default" size="100%">Havulinna, Aki S</style></author><author><style face="normal" font="default" size="100%">Kuusisto, Johanna</style></author><author><style face="normal" font="default" size="100%">Boehnke, Michael</style></author><author><style face="normal" font="default" size="100%">Laakso, Markku</style></author><author><style face="normal" font="default" size="100%">Palotie, Aarno</style></author><author><style face="normal" font="default" size="100%">Ripatti, Samuli</style></author><author><style face="normal" font="default" size="100%">Freimer, Nelson B</style></author><author><style face="normal" font="default" size="100%">Locke, Adam E</style></author><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association of structural variation with cardiometabolic traits in Finns.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Cardiovascular Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Cholesterol</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Finland</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomic Structural Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyruvate Dehydrogenase (Lipoamide)-Phosphatase</style></keyword><keyword><style  face="normal" font="default" size="100%">Pyruvic Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Serum Albumin, Human</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 04 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">108</style></volume><pages><style face="normal" font="default" size="100%">583-596</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The contribution of genome structural variation (SV) to quantitative traits associated with cardiometabolic diseases remains largely unknown. Here, we present the results of a study examining genetic association between SVs and cardiometabolic traits in the Finnish population. We used sensitive methods to identify and genotype 129,166 high-confidence SVs from deep whole-genome sequencing (WGS) data of 4,848 individuals. We tested the 64,572 common and low-frequency SVs for association with 116 quantitative traits and tested candidate associations using exome sequencing and array genotype data from an additional 15,205 individuals. We discovered 31 genome-wide significant associations at 15 loci, including 2 loci at which SVs have strong phenotypic effects: (1) a deletion of the ALB promoter that is greatly enriched in the Finnish population and causes decreased serum albumin level in carriers (p = 1.47 × 10) and is also associated with increased levels of total cholesterol (p = 1.22 × 10) and 14 additional cholesterol-related traits, and (2) a multi-allelic copy number variant (CNV) at PDPR that is strongly associated with pyruvate (p = 4.81 × 10) and alanine (p = 6.14 × 10) levels and resides within a structurally complex genomic region that has accumulated many rearrangements over evolutionary time. We also confirmed six previously reported associations, including five led by stronger signals in single nucleotide variants (SNVs) and one linking recurrent HP gene deletion and cholesterol levels (p = 6.24 × 10), which was also found to be strongly associated with increased glycoprotein level (p = 3.53 × 10). Our study confirms that integrating SVs in trait-mapping studies will expand our knowledge of genetic factors underlying disease risk.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33798444?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Garg, Shilpa</style></author><author><style face="normal" font="default" size="100%">Fungtammasan, Arkarachai</style></author><author><style face="normal" font="default" size="100%">Carroll, Andrew</style></author><author><style face="normal" font="default" size="100%">Chou, Mike</style></author><author><style face="normal" font="default" size="100%">Schmitt, Anthony</style></author><author><style face="normal" font="default" size="100%">Zhou, Xiang</style></author><author><style face="normal" font="default" size="100%">Mac, Stephen</style></author><author><style face="normal" font="default" size="100%">Peluso, Paul</style></author><author><style face="normal" font="default" size="100%">Hatas, Emily</style></author><author><style face="normal" font="default" size="100%">Ghurye, Jay</style></author><author><style face="normal" font="default" size="100%">Maguire, Jared</style></author><author><style face="normal" font="default" size="100%">Mahmoud, Medhat</style></author><author><style face="normal" font="default" size="100%">Cheng, Haoyu</style></author><author><style face="normal" font="default" size="100%">Heller, David</style></author><author><style face="normal" font="default" size="100%">Zook, Justin M</style></author><author><style face="normal" font="default" size="100%">Moemke, Tobias</style></author><author><style face="normal" font="default" size="100%">Marschall, Tobias</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Aach, John</style></author><author><style face="normal" font="default" size="100%">Chin, Chen-Shan</style></author><author><style face="normal" font="default" size="100%">Church, George M</style></author><author><style face="normal" font="default" size="100%">Li, Heng</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Chromosome-scale, haplotype-resolved assembly of human genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Biotechnol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Biotechnol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">Heterozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">309-312</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Haplotype-resolved or phased genome assembly provides a complete picture of genomes and their complex genetic variations. However, current algorithms for phased assembly either do not generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method named diploid assembly (DipAsm) that uses long, accurate reads and long-range conformation data for single individuals to generate a chromosome-scale phased assembly within 1 day. Applied to four public human genomes, PGP1, HG002, NA12878 and HG00733, DipAsm produced haplotype-resolved assemblies with minimum contig length needed to cover 50% of the known genome (NG50) up to 25 Mb and phased ~99.5% of heterozygous sites at 98-99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies for the discovery of structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as the human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) regions. DipAsm will facilitate high-quality precision medicine and studies of individual haplotype variation and population diversity.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33288905?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Akçimen, Fulya</style></author><author><style face="normal" font="default" size="100%">Ross, Jay P</style></author><author><style face="normal" font="default" size="100%">Liao, Calwing</style></author><author><style face="normal" font="default" size="100%">Spiegelman, Dan</style></author><author><style face="normal" font="default" size="100%">Dion, Patrick A</style></author><author><style face="normal" font="default" size="100%">Rouleau, Guy A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Expanded CAG Repeats in ATXN1, ATXN2, ATXN3, and HTT in the 1000 Genomes Project.</style></title><secondary-title><style face="normal" font="default" size="100%">Mov Disord</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mov Disord</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Ataxin-1</style></keyword><keyword><style  face="normal" font="default" size="100%">Ataxin-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Ataxin-3</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Huntingtin Protein</style></keyword><keyword><style  face="normal" font="default" size="100%">Huntington Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Repressor Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Spinocerebellar Ataxias</style></keyword><keyword><style  face="normal" font="default" size="100%">Trinucleotide Repeat Expansion</style></keyword><keyword><style  face="normal" font="default" size="100%">Trinucleotide Repeats</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">514-518</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Spinocerebellar ataxia types 1, 2, 3 and Huntington disease are neurodegenerative disorders caused by expanded CAG repeats.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We performed an in-silico analysis of CAG repeats in ATXN1, ATXN2, ATXN3, and HTT using 30× whole-=genome sequencing data of 2504 samples from the 1000 Genomes Project.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Seven HTT-positive, 3 ATXN2-positive, 1 ATXN3-positive, and 6 possibly ATXN1-positive samples were identified. No correlation was found between the repeat sizes of the different genes. The distribution of CAG alleles varied by ethnicity.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;Our results suggest that there may be asymptomatic small expanded repeats in almost 0.5% of these populations. © 2020 International Parkinson and Movement Disorder Society.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33159825?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kasela, Silva</style></author><author><style face="normal" font="default" size="100%">Ortega, Victor E</style></author><author><style face="normal" font="default" size="100%">Martorella, Molly</style></author><author><style face="normal" font="default" size="100%">Garudadri, Suresh</style></author><author><style face="normal" font="default" size="100%">Nguyen, Jenna</style></author><author><style face="normal" font="default" size="100%">Ampleford, Elizabeth</style></author><author><style face="normal" font="default" size="100%">Pasanen, Anu</style></author><author><style face="normal" font="default" size="100%">Nerella, Srilaxmi</style></author><author><style face="normal" font="default" size="100%">Buschur, Kristina L</style></author><author><style face="normal" font="default" size="100%">Barjaktarevic, Igor Z</style></author><author><style face="normal" font="default" size="100%">Barr, R Graham</style></author><author><style face="normal" font="default" size="100%">Bleecker, Eugene R</style></author><author><style face="normal" font="default" size="100%">Bowler, Russell P</style></author><author><style face="normal" font="default" size="100%">Comellas, Alejandro P</style></author><author><style face="normal" font="default" size="100%">Cooper, Christopher B</style></author><author><style face="normal" font="default" size="100%">Couper, David J</style></author><author><style face="normal" font="default" size="100%">Criner, Gerard J</style></author><author><style face="normal" font="default" size="100%">Curtis, Jeffrey L</style></author><author><style face="normal" font="default" size="100%">Han, MeiLan K</style></author><author><style face="normal" font="default" size="100%">Hansel, Nadia N</style></author><author><style face="normal" font="default" size="100%">Hoffman, Eric A</style></author><author><style face="normal" font="default" size="100%">Kaner, Robert J</style></author><author><style face="normal" font="default" size="100%">Krishnan, Jerry A</style></author><author><style face="normal" font="default" size="100%">Martinez, Fernando J</style></author><author><style face="normal" font="default" size="100%">McDonald, Merry-Lynn N</style></author><author><style face="normal" font="default" size="100%">Meyers, Deborah A</style></author><author><style face="normal" font="default" size="100%">Paine, Robert</style></author><author><style face="normal" font="default" size="100%">Peters, Stephen P</style></author><author><style face="normal" font="default" size="100%">Castro, Mario</style></author><author><style face="normal" font="default" size="100%">Denlinger, Loren C</style></author><author><style face="normal" font="default" size="100%">Erzurum, Serpil C</style></author><author><style face="normal" font="default" size="100%">Fahy, John V</style></author><author><style face="normal" font="default" size="100%">Israel, Elliot</style></author><author><style face="normal" font="default" size="100%">Jarjour, Nizar N</style></author><author><style face="normal" font="default" size="100%">Levy, Bruce D</style></author><author><style face="normal" font="default" size="100%">Li, Xingnan</style></author><author><style face="normal" font="default" size="100%">Moore, Wendy C</style></author><author><style face="normal" font="default" size="100%">Wenzel, Sally E</style></author><author><style face="normal" font="default" size="100%">Zein, Joe</style></author><author><style face="normal" font="default" size="100%">Langelier, Charles</style></author><author><style face="normal" font="default" size="100%">Woodruff, Prescott G</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Christenson, Stephanie A</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NHLBI SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)</style></author><author><style face="normal" font="default" size="100%">NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiotensin-Converting Enzyme 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Asthma</style></keyword><keyword><style  face="normal" font="default" size="100%">Bronchi</style></keyword><keyword><style  face="normal" font="default" size="100%">Cardiovascular Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Obesity</style></keyword><keyword><style  face="normal" font="default" size="100%">Pulmonary Disease, Chronic Obstructive</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Respiratory Mucosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Smoking</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 04 21</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">66</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33883027?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hansen, Adam W</style></author><author><style face="normal" font="default" size="100%">Arora, Payal</style></author><author><style face="normal" font="default" size="100%">Khayat, Michael M</style></author><author><style face="normal" font="default" size="100%">Smith, Leah J</style></author><author><style face="normal" font="default" size="100%">Lewis, Andrea M</style></author><author><style face="normal" font="default" size="100%">Rossetti, Linda Z</style></author><author><style face="normal" font="default" size="100%">Jayaseelan, Joy</style></author><author><style face="normal" font="default" size="100%">Cristian, Ingrid</style></author><author><style face="normal" font="default" size="100%">Haynes, Devon</style></author><author><style face="normal" font="default" size="100%">DiTroia, Stephanie</style></author><author><style face="normal" font="default" size="100%">Meeks, Naomi</style></author><author><style face="normal" font="default" size="100%">Delgado, Mauricio R</style></author><author><style face="normal" font="default" size="100%">Rosenfeld, Jill A</style></author><author><style face="normal" font="default" size="100%">Pais, Lynn</style></author><author><style face="normal" font="default" size="100%">White, Susan M</style></author><author><style face="normal" font="default" size="100%">Meng, Qingchang</style></author><author><style face="normal" font="default" size="100%">Pehlivan, Davut</style></author><author><style face="normal" font="default" size="100%">Liu, Pengfei</style></author><author><style face="normal" font="default" size="100%">Gingras, Marie-Claude</style></author><author><style face="normal" font="default" size="100%">Wangler, Michael F</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author><author><style face="normal" font="default" size="100%">Kaplan, Craig D</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Germline mutation in : a heterogeneous, multi-systemic developmental disorder characterized by transcriptional dysregulation.</style></title><secondary-title><style face="normal" font="default" size="100%">HGG Adv</style></secondary-title><alt-title><style face="normal" font="default" size="100%">HGG Adv</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Jan 14</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">2</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt; germline variation in  was recently reported to associate with a neurodevelopmental disorder. We report twelve individuals harboring putatively pathogenic  or inherited variants in , detail their phenotypes, and map all known variants to the domain structure of  and crystal structure of RNA polymerase II. Affected individuals were ascertained from a local data lake, pediatric genetics clinic, and an online community of families of affected individuals. These include six affected by  missense variants (including one previously reported individual), four clinical laboratory samples affected by missense variation with unknown inheritance-with yeast functional assays further supporting altered function-one affected by a  in-frame deletion, and one affected by a C-terminal frameshift variant inherited from a largely asymptomatic mother. Recurrently observed phenotypes include ataxia, joint hypermobility, short stature, skin abnormalities, congenital cardiac abnormalities, immune system abnormalities, hip dysplasia, and short Achilles tendons. We report a significantly higher occurrence of epilepsy (8/12, 66.7%) than previously reported (3/15, 20%) (p value = 0.014196; chi-square test) and a lower occurrence of hypotonia (8/12, 66.7%) than previously reported (14/15, 93.3%) (p value = 0.076309). -related developmental disorders likely represent a spectrum of related, multi-systemic developmental disorders, driven by distinct mechanisms, converging at a single locus.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33665635?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ebert, Peter</style></author><author><style face="normal" font="default" size="100%">Audano, Peter A</style></author><author><style face="normal" font="default" size="100%">Zhu, Qihui</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Martin, Bernardo</style></author><author><style face="normal" font="default" size="100%">Porubsky, David</style></author><author><style face="normal" font="default" size="100%">Bonder, Marc Jan</style></author><author><style face="normal" font="default" size="100%">Sulovari, Arvis</style></author><author><style face="normal" font="default" size="100%">Ebler, Jana</style></author><author><style face="normal" font="default" size="100%">Zhou, Weichen</style></author><author><style face="normal" font="default" size="100%">Serra Mari, Rebecca</style></author><author><style face="normal" font="default" size="100%">Yilmaz, Feyza</style></author><author><style face="normal" font="default" size="100%">Zhao, Xuefang</style></author><author><style face="normal" font="default" size="100%">Hsieh, PingHsun</style></author><author><style face="normal" font="default" size="100%">Lee, Joyce</style></author><author><style face="normal" font="default" size="100%">Kumar, Sushant</style></author><author><style face="normal" font="default" size="100%">Lin, Jiadong</style></author><author><style face="normal" font="default" size="100%">Rausch, Tobias</style></author><author><style face="normal" font="default" size="100%">Chen, Yu</style></author><author><style face="normal" font="default" size="100%">Ren, Jingwen</style></author><author><style face="normal" font="default" size="100%">Santamarina, Martin</style></author><author><style face="normal" font="default" size="100%">Höps, Wolfram</style></author><author><style face="normal" font="default" size="100%">Ashraf, Hufsah</style></author><author><style face="normal" font="default" size="100%">Chuang, Nelson T</style></author><author><style face="normal" font="default" size="100%">Yang, Xiaofei</style></author><author><style face="normal" font="default" size="100%">Munson, Katherine M</style></author><author><style face="normal" font="default" size="100%">Lewis, Alexandra P</style></author><author><style face="normal" font="default" size="100%">Fairley, Susan</style></author><author><style face="normal" font="default" size="100%">Tallon, Luke J</style></author><author><style face="normal" font="default" size="100%">Clarke, Wayne E</style></author><author><style face="normal" font="default" size="100%">Basile, Anna O</style></author><author><style face="normal" font="default" size="100%">Byrska-Bishop, Marta</style></author><author><style face="normal" font="default" size="100%">Corvelo, André</style></author><author><style face="normal" font="default" size="100%">Evani, Uday S</style></author><author><style face="normal" font="default" size="100%">Lu, Tsung-Yu</style></author><author><style face="normal" font="default" size="100%">Chaisson, Mark J P</style></author><author><style face="normal" font="default" size="100%">Chen, Junjie</style></author><author><style face="normal" font="default" size="100%">Li, Chong</style></author><author><style face="normal" font="default" size="100%">Brand, Harrison</style></author><author><style face="normal" font="default" size="100%">Wenger, Aaron M</style></author><author><style face="normal" font="default" size="100%">Ghareghani, Maryam</style></author><author><style face="normal" font="default" size="100%">Harvey, William T</style></author><author><style face="normal" font="default" size="100%">Raeder, Benjamin</style></author><author><style face="normal" font="default" size="100%">Hasenfeld, Patrick</style></author><author><style face="normal" font="default" size="100%">Regier, Allison A</style></author><author><style face="normal" font="default" size="100%">Abel, Haley J</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author><author><style face="normal" font="default" size="100%">Flicek, Paul</style></author><author><style face="normal" font="default" size="100%">Stegle, Oliver</style></author><author><style face="normal" font="default" size="100%">Gerstein, Mark B</style></author><author><style face="normal" font="default" size="100%">Tubio, Jose M C</style></author><author><style face="normal" font="default" size="100%">Mu, Zepeng</style></author><author><style face="normal" font="default" size="100%">Li, Yang I</style></author><author><style face="normal" font="default" size="100%">Shi, Xinghua</style></author><author><style face="normal" font="default" size="100%">Hastie, Alex R</style></author><author><style face="normal" font="default" size="100%">Ye, Kai</style></author><author><style face="normal" font="default" size="100%">Chong, Zechen</style></author><author><style face="normal" font="default" size="100%">Sanders, Ashley D</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Talkowski, Michael E</style></author><author><style face="normal" font="default" size="100%">Mills, Ryan E</style></author><author><style face="normal" font="default" size="100%">Devine, Scott E</style></author><author><style face="normal" font="default" size="100%">Lee, Charles</style></author><author><style face="normal" font="default" size="100%">Korbel, Jan O</style></author><author><style face="normal" font="default" size="100%">Marschall, Tobias</style></author><author><style face="normal" font="default" size="100%">Eichler, Evan E</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Haplotype-resolved diverse human genomes and integrated analysis of structural variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">INDEL Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Interspersed Repetitive Sequences</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Population Groups</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Retroelements</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Inversion</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 04 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">372</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6537</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33632895?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ranallo-Benavidez, T Rhyker</style></author><author><style face="normal" font="default" size="100%">Lemmon, Zachary</style></author><author><style face="normal" font="default" size="100%">Soyk, Sebastian</style></author><author><style face="normal" font="default" size="100%">Aganezov, Sergey</style></author><author><style face="normal" font="default" size="100%">Salerno, William J</style></author><author><style face="normal" font="default" size="100%">McCoy, Rajiv C</style></author><author><style face="normal" font="default" size="100%">Lippman, Zachary B</style></author><author><style face="normal" font="default" size="100%">Schatz, Michael C</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimized sample selection for cost-efficient long-read population sequencing.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Res</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 May</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">910-918</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;An increasingly important scenario in population genetics is when a large cohort has been genotyped using a low-resolution approach (e.g., microarrays, exome capture, short-read WGS), from which a few individuals are resequenced using a more comprehensive approach, especially long-read sequencing. The subset of individuals selected should ensure that the captured genetic diversity is fully representative and includes variants across all subpopulations. For example, human variation has historically focused on individuals with European ancestry, but this represents a small fraction of the overall diversity. Addressing this, SVCollector identifies the optimal subset of individuals for resequencing by analyzing population-level VCF files from low-resolution genotyping studies. It then computes a ranked list of samples that maximizes the total number of variants present within a subset of a given size. To solve this optimization problem, SVCollector implements a fast, greedy heuristic and an exact algorithm using integer linear programming. We apply SVCollector on simulated data, 2504 human genomes from the 1000 Genomes Project, and 3024 genomes from the 3000 Rice Genomes Project and show the rankings it computes are more representative than alternative naive strategies. When selecting an optimal subset of 100 samples in these cohorts, SVCollector identifies individuals from every subpopulation, whereas naive methods yield an unbalanced selection. Finally, we show the number of variants present in cohorts selected using this approach follows a power-law distribution that is naturally related to the population genetic concept of the allele frequency spectrum, allowing us to estimate the diversity present with increasing numbers of samples.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33811084?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ilumäe, Anne-Mai</style></author><author><style face="normal" font="default" size="100%">Post, Helen</style></author><author><style face="normal" font="default" size="100%">Flores, Rodrigo</style></author><author><style face="normal" font="default" size="100%">Karmin, Monika</style></author><author><style face="normal" font="default" size="100%">Sahakyan, Hovhannes</style></author><author><style face="normal" font="default" size="100%">Mondal, Mayukh</style></author><author><style face="normal" font="default" size="100%">Montinaro, Francesco</style></author><author><style face="normal" font="default" size="100%">Saag, Lauri</style></author><author><style face="normal" font="default" size="100%">Bormans, Concetta</style></author><author><style face="normal" font="default" size="100%">Sanchez, Luisa Fernanda</style></author><author><style face="normal" font="default" size="100%">Ameur, Adam</style></author><author><style face="normal" font="default" size="100%">Gyllensten, Ulf</style></author><author><style face="normal" font="default" size="100%">Kals, Mart</style></author><author><style face="normal" font="default" size="100%">Mägi, Reedik</style></author><author><style face="normal" font="default" size="100%">Pagani, Luca</style></author><author><style face="normal" font="default" size="100%">Behar, Doron M</style></author><author><style face="normal" font="default" size="100%">Rootsi, Siiri</style></author><author><style face="normal" font="default" size="100%">Villems, Richard</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phylogenetic history of patrilineages rare in northern and eastern Europe from large-scale re-sequencing of human Y-chromosomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Eur J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Eur J Hum Genet</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 May 07</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The most frequent Y-chromosomal (chrY) haplogroups in northern and eastern Europe (NEE) are well-known and thoroughly characterised. Yet a considerable number of men in every population carry rare paternal lineages with estimated frequencies around 5%. So far, limited sample-sizes and insufficient resolution of genotyping have obstructed a truly comprehensive look into the variety of rare paternal lineages segregating within populations and potential signals of population history that such lineages might convey. Here we harness the power of massive re-sequencing of human Y chromosomes to identify previously unknown population-specific clusters among rare paternal lineages in NEE. We construct dated phylogenies for haplogroups E2-M215, J2-M172, G-M201 and Q-M242 on the basis of 421 (of them 282 novel) high-coverage chrY sequences collected from large-scale databases focusing on populations of NEE. Within these otherwise rare haplogroups we disclose lineages that began to radiate ~1-3 thousand years ago in Estonia and Sweden and reveal male phylogenetic patterns testifying of comparatively recent local demographic expansions. Conversely, haplogroup Q lineages bear evidence of ancient Siberian influence lingering in the modern paternal gene pool of northern Europe. We assess the possible direction of influx of ancestral carriers for some of these male lineages. In addition, we demonstrate the congruency of paternal haplogroup composition of our dataset with two independent population-based cohorts from Estonia and Sweden.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33958743?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jung, In-Hyuk</style></author><author><style face="normal" font="default" size="100%">Elenbaas, Jared S</style></author><author><style face="normal" font="default" size="100%">Alisio, Arturo</style></author><author><style face="normal" font="default" size="100%">Santana, Katherine</style></author><author><style face="normal" font="default" size="100%">Young, Erica P</style></author><author><style face="normal" font="default" size="100%">Kang, Chul Joo</style></author><author><style face="normal" font="default" size="100%">Kachroo, Puja</style></author><author><style face="normal" font="default" size="100%">Lavine, Kory J</style></author><author><style face="normal" font="default" size="100%">Razani, Babak</style></author><author><style face="normal" font="default" size="100%">Mecham, Robert P</style></author><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">SVEP1 is a human coronary artery disease locus that promotes atherosclerosis.</style></title><secondary-title><style face="normal" font="default" size="100%">Sci Transl Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Sci Transl Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Mar 24</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A low-frequency variant of sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SVEP1), an extracellular matrix protein, is associated with risk of coronary disease in humans independent of plasma lipids. Despite a robust statistical association, if and how SVEP1 might contribute to atherosclerosis remained unclear. Here, using Mendelian randomization and complementary mouse models, we provide evidence that SVEP1 promotes atherosclerosis in humans and mice and is expressed by vascular smooth muscle cells (VSMCs) within the atherosclerotic plaque. VSMCs also interact with SVEP1, causing proliferation and dysregulation of key differentiation pathways, including integrin and Notch signaling. Fibroblast growth factor receptor transcription increases in VSMCs interacting with SVEP1 and is further increased by the coronary disease-associated  variant p.D2702G. These effects ultimately drive inflammation and promote atherosclerosis. Together, our results suggest that VSMC-derived SVEP1 is a proatherogenic factor and support the concept that pharmacological inhibition of SVEP1 should protect against atherosclerosis in humans.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">586</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33762433?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Fahed, Akl C</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna G</style></author><author><style face="normal" font="default" size="100%">Hindy, George</style></author><author><style face="normal" font="default" size="100%">Chen, Yii-Der Ida</style></author><author><style face="normal" font="default" size="100%">Chaudhary, Kumardeep</style></author><author><style face="normal" font="default" size="100%">Dobbyn, Amanda</style></author><author><style face="normal" font="default" size="100%">Krumholz, Harlan M</style></author><author><style face="normal" font="default" size="100%">Sheu, Wayne H H</style></author><author><style face="normal" font="default" size="100%">Rich, Stephen S</style></author><author><style face="normal" font="default" size="100%">Rotter, Jerome I</style></author><author><style face="normal" font="default" size="100%">Chowdhury, Rajiv</style></author><author><style face="normal" font="default" size="100%">Cho, Judy</style></author><author><style face="normal" font="default" size="100%">Do, Ron</style></author><author><style face="normal" font="default" size="100%">Ellinor, Patrick T</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Transethnic Transferability of a Genome-Wide Polygenic Score for Coronary Artery Disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Circ Genom Precis Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Circ Genom Precis Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Feb</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">e003092</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33284643?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Somineni, Hari K</style></author><author><style face="normal" font="default" size="100%">Nagpal, Sini</style></author><author><style face="normal" font="default" size="100%">Venkateswaran, Suresh</style></author><author><style face="normal" font="default" size="100%">Cutler, David J</style></author><author><style face="normal" font="default" size="100%">Okou, David T</style></author><author><style face="normal" font="default" size="100%">Haritunians, Talin</style></author><author><style face="normal" font="default" size="100%">Simpson, Claire L</style></author><author><style face="normal" font="default" size="100%">Begum, Ferdouse</style></author><author><style face="normal" font="default" size="100%">Datta, Lisa W</style></author><author><style face="normal" font="default" size="100%">Quiros, Antonio J</style></author><author><style face="normal" font="default" size="100%">Seminerio, Jenifer</style></author><author><style face="normal" font="default" size="100%">Mengesha, Emebet</style></author><author><style face="normal" font="default" size="100%">Alexander, Jonathan S</style></author><author><style face="normal" font="default" size="100%">Baldassano, Robert N</style></author><author><style face="normal" font="default" size="100%">Dudley-Brown, Sharon</style></author><author><style face="normal" font="default" size="100%">Cross, Raymond K</style></author><author><style face="normal" font="default" size="100%">Dassopoulos, Themistocles</style></author><author><style face="normal" font="default" size="100%">Denson, Lee A</style></author><author><style face="normal" font="default" size="100%">Dhere, Tanvi A</style></author><author><style face="normal" font="default" size="100%">Iskandar, Heba</style></author><author><style face="normal" font="default" size="100%">Dryden, Gerald W</style></author><author><style face="normal" font="default" size="100%">Hou, Jason K</style></author><author><style face="normal" font="default" size="100%">Hussain, Sunny Z</style></author><author><style face="normal" font="default" size="100%">Hyams, Jeffrey S</style></author><author><style face="normal" font="default" size="100%">Isaacs, Kim L</style></author><author><style face="normal" font="default" size="100%">Kader, Howard</style></author><author><style face="normal" font="default" size="100%">Kappelman, Michael D</style></author><author><style face="normal" font="default" size="100%">Katz, Jeffry</style></author><author><style face="normal" font="default" size="100%">Kellermayer, Richard</style></author><author><style face="normal" font="default" size="100%">Kuemmerle, John F</style></author><author><style face="normal" font="default" size="100%">Lazarev, Mark</style></author><author><style face="normal" font="default" size="100%">Li, Ellen</style></author><author><style face="normal" font="default" size="100%">Mannon, Peter</style></author><author><style face="normal" font="default" size="100%">Moulton, Dedrick E</style></author><author><style face="normal" font="default" size="100%">Newberry, Rodney D</style></author><author><style face="normal" font="default" size="100%">Patel, Ashish S</style></author><author><style face="normal" font="default" size="100%">Pekow, Joel</style></author><author><style face="normal" font="default" size="100%">Saeed, Shehzad A</style></author><author><style face="normal" font="default" size="100%">Valentine, John F</style></author><author><style face="normal" font="default" size="100%">Wang, Ming-Hsi</style></author><author><style face="normal" font="default" size="100%">McCauley, Jacob L</style></author><author><style face="normal" font="default" size="100%">Abreu, Maria T</style></author><author><style face="normal" font="default" size="100%">Jester, Traci</style></author><author><style face="normal" font="default" size="100%">Molle-Rios, Zarela</style></author><author><style face="normal" font="default" size="100%">Palle, Sirish</style></author><author><style face="normal" font="default" size="100%">Scherl, Ellen J</style></author><author><style face="normal" font="default" size="100%">Kwon, John</style></author><author><style face="normal" font="default" size="100%">Rioux, John D</style></author><author><style face="normal" font="default" size="100%">Duerr, Richard H</style></author><author><style face="normal" font="default" size="100%">Silverberg, Mark S</style></author><author><style face="normal" font="default" size="100%">Zwick, Michael E</style></author><author><style face="normal" font="default" size="100%">Stevens, Christine</style></author><author><style face="normal" font="default" size="100%">Daly, Mark J</style></author><author><style face="normal" font="default" size="100%">Cho, Judy H</style></author><author><style face="normal" font="default" size="100%">Gibson, Greg</style></author><author><style face="normal" font="default" size="100%">McGovern, Dermot P B</style></author><author><style face="normal" font="default" size="100%">Brant, Steven R</style></author><author><style face="normal" font="default" size="100%">Kugathasan, Subra</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole-genome sequencing of African Americans implicates differential genetic architecture in inflammatory bowel disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">African Americans</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">Calbindin 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Colitis, Ulcerative</style></keyword><keyword><style  face="normal" font="default" size="100%">Crohn Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">European Continental Ancestry Group</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Inflammatory Bowel Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Multifactorial Inheritance</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Receptors, Prostaglandin E, EP4 Subtype</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 03 04</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">108</style></volume><pages><style face="normal" font="default" size="100%">431-445</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Whether or not populations diverge with respect to the genetic contribution to risk of specific complex diseases is relevant to understanding the evolution of susceptibility and origins of health disparities. Here, we describe a large-scale whole-genome sequencing study of inflammatory bowel disease encompassing 1,774 affected individuals and 1,644 healthy control Americans with African ancestry (African Americans). Although no new loci for inflammatory bowel disease are discovered at genome-wide significance levels, we identify numerous instances of differential effect sizes in combination with divergent allele frequencies. For example, the major effect at PTGER4 fine maps to a single credible interval of 22 SNPs corresponding to one of four independent associations at the locus in European ancestry individuals but with an elevated odds ratio for Crohn disease in African Americans. A rare variant aggregate analysis implicates Ca-binding neuro-immunomodulator CALB2 in ulcerative colitis. Highly significant overall overlap of common variant risk for inflammatory bowel disease susceptibility between individuals with African and European ancestries was observed, with 41 of 241 previously known lead variants replicated and overall correlations in effect sizes of 0.68 for combined inflammatory bowel disease. Nevertheless, subtle differences influence the performance of polygenic risk scores, and we show that ancestry-appropriate weights significantly improve polygenic prediction in the highest percentiles of risk. The median amount of variance explained per locus remains the same in African and European cohorts, providing evidence for compensation of effect sizes as allele frequencies diverge, as expected under a highly polygenic model of disease.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33600772?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pirruccello, James P</style></author><author><style face="normal" font="default" size="100%">Bick, Alexander</style></author><author><style face="normal" font="default" size="100%">Wang, Minxian</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Friedman, Samuel</style></author><author><style face="normal" font="default" size="100%">Yao, Jie</style></author><author><style face="normal" font="default" size="100%">Guo, Xiuqing</style></author><author><style face="normal" font="default" size="100%">Venkatesh, Bharath Ambale</style></author><author><style face="normal" font="default" size="100%">Taylor, Kent D</style></author><author><style face="normal" font="default" size="100%">Post, Wendy S</style></author><author><style face="normal" font="default" size="100%">Rich, Stephen</style></author><author><style face="normal" font="default" size="100%">Lima, Joao A C</style></author><author><style face="normal" font="default" size="100%">Rotter, Jerome I</style></author><author><style face="normal" font="default" size="100%">Philippakis, Anthony</style></author><author><style face="normal" font="default" size="100%">Lubitz, Steven A</style></author><author><style face="normal" font="default" size="100%">Ellinor, Patrick T</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cardiomyopathy, Dilated</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Heart</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Myocardium</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 05 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">2254</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32382064?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Patel, Aniruddh P</style></author><author><style face="normal" font="default" size="100%">Wang, Minxian</style></author><author><style face="normal" font="default" size="100%">Fahed, Akl C</style></author><author><style face="normal" font="default" size="100%">Mason-Suares, Heather</style></author><author><style face="normal" font="default" size="100%">Brockman, Deanna</style></author><author><style face="normal" font="default" size="100%">Pelletier, Renee</style></author><author><style face="normal" font="default" size="100%">Amr, Sami</style></author><author><style face="normal" font="default" size="100%">Machini, Kalotina</style></author><author><style face="normal" font="default" size="100%">Hawley, Megan</style></author><author><style face="normal" font="default" size="100%">Witkowski, Leora</style></author><author><style face="normal" font="default" size="100%">Koch, Christopher</style></author><author><style face="normal" font="default" size="100%">Philippakis, Anthony</style></author><author><style face="normal" font="default" size="100%">Cassa, Christopher A</style></author><author><style face="normal" font="default" size="100%">Ellinor, Patrick T</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Ng, Kenney</style></author><author><style face="normal" font="default" size="100%">Lebo, Matthew</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association of Rare Pathogenic DNA Variants for Familial Hypercholesterolemia, Hereditary Breast and Ovarian Cancer Syndrome, and Lynch Syndrome With Disease Risk in Adults According to Family History.</style></title><secondary-title><style face="normal" font="default" size="100%">JAMA Netw Open</style></secondary-title><alt-title><style face="normal" font="default" size="100%">JAMA Netw Open</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Colorectal Neoplasms, Hereditary Nonpolyposis</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Hereditary Breast and Ovarian Cancer Syndrome</style></keyword><keyword><style  face="normal" font="default" size="100%">Heterozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Hyperlipoproteinemia Type II</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Pedigree</style></keyword><keyword><style  face="normal" font="default" size="100%">Proportional Hazards Models</style></keyword><keyword><style  face="normal" font="default" size="100%">United Kingdom</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Exome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 04 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">e203959</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;Importance: &lt;/b&gt;Pathogenic DNA variants associated with familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and Lynch syndrome are widely recognized as clinically important and actionable when identified, leading some clinicians to recommend population-wide genomic screening.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Objectives: &lt;/b&gt;To assess the prevalence and clinical importance of pathogenic or likely pathogenic variants associated with each of 3 genomic conditions (familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and Lynch syndrome) within the context of contemporary clinical care.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Design, Setting, and Participants: &lt;/b&gt;This cohort study used gene-sequencing data from 49 738 participants in the UK Biobank who were recruited from 22 sites across the UK between March 21, 2006, and October 1, 2010. Inpatient hospital data date back to 1977; cancer registry data, to 1957; and death registry data, to 2006. Statistical analysis was performed from July 22, 2019, to November 15, 2019.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Exposures: &lt;/b&gt;Pathogenic or likely pathogenic DNA variants classified by a clinical laboratory geneticist.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Main Outcomes and Measures: &lt;/b&gt;Composite end point specific to each genomic condition based on atherosclerotic cardiovascular disease events for familial hypercholesterolemia, breast or ovarian cancer for hereditary breast and ovarian cancer syndrome, and colorectal or uterine cancer for Lynch syndrome.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Results: &lt;/b&gt;Among 49 738 participants (mean [SD] age, 57 [8] years; 27 144 female [55%]), 441 (0.9%) harbored a pathogenic or likely pathogenic variant associated with any of 3 genomic conditions, including 131 (0.3%) for familial hypercholesterolemia, 235 (0.5%) for hereditary breast and ovarian cancer syndrome, and 76 (0.2%) for Lynch syndrome. Presence of these variants was associated with increased risk of disease: for familial hypercholesterolemia, 28 of 131 carriers (21.4%) vs 4663 of 49 607 noncarriers (9.4%) developed atherosclerotic cardiovascular disease; for hereditary breast and ovarian cancer syndrome, 32 of 116 female carriers (27.6%) vs 2080 of 27 028 female noncarriers (7.7%) developed associated cancers; and for Lynch syndrome, 17 of 76 carriers (22.4%) vs 929 of 49 662 noncarriers (1.9%) developed colorectal or uterine cancer. The predicted probability of disease at age 75 years despite contemporary clinical care was 45.3% for carriers of familial hypercholesterolemia, 41.1% for hereditary breast and ovarian cancer syndrome, and 38.3% for Lynch syndrome. Across the 3 conditions, 39.7% (175 of 441) of the carriers reported a family history of disease vs 23.2% (34 517 of 148 772) of noncarriers.&lt;/p&gt;&lt;p&gt;&lt;b&gt;Conclusions and Relevance: &lt;/b&gt;The findings suggest that approximately 1% of the middle-aged adult population in the UK Biobank harbored a pathogenic variant associated with any of 3 genomic conditions. These variants were associated with an increased risk of disease despite contemporary clinical care and were not reliably detected by family history.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32347951?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Oliva, Meritxell</style></author><author><style face="normal" font="default" size="100%">Muñoz-Aguirre, Manuel</style></author><author><style face="normal" font="default" size="100%">Kasela, Silva</style></author><author><style face="normal" font="default" size="100%">Wucher, Valentin</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Hamel, Andrew R</style></author><author><style face="normal" font="default" size="100%">Viñuela, Ana</style></author><author><style face="normal" font="default" size="100%">Roberts, Amy L</style></author><author><style face="normal" font="default" size="100%">Mangul, Serghei</style></author><author><style face="normal" font="default" size="100%">Wen, Xiaoquan</style></author><author><style face="normal" font="default" size="100%">Wang, Gao</style></author><author><style face="normal" font="default" size="100%">Barbeira, Alvaro N</style></author><author><style face="normal" font="default" size="100%">Garrido-Martín, Diego</style></author><author><style face="normal" font="default" size="100%">Nadel, Brian B</style></author><author><style face="normal" font="default" size="100%">Zou, Yuxin</style></author><author><style face="normal" font="default" size="100%">Bonazzola, Rodrigo</style></author><author><style face="normal" font="default" size="100%">Quan, Jie</style></author><author><style face="normal" font="default" size="100%">Brown, Andrew</style></author><author><style face="normal" font="default" size="100%">Martinez-Perez, Angel</style></author><author><style face="normal" font="default" size="100%">Soria, José Manuel</style></author><author><style face="normal" font="default" size="100%">Getz, Gad</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, Emmanouil T</style></author><author><style face="normal" font="default" size="100%">Small, Kerrin S</style></author><author><style face="normal" font="default" size="100%">Stephens, Matthew</style></author><author><style face="normal" font="default" size="100%">Xi, Hualin S</style></author><author><style face="normal" font="default" size="100%">Im, Hae Kyung</style></author><author><style face="normal" font="default" size="100%">Guigo, Roderic</style></author><author><style face="normal" font="default" size="100%">Segrè, Ayellet V</style></author><author><style face="normal" font="default" size="100%">Stranger, Barbara E</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Cell type-specific genetic regulation of gene expression across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Long Noncoding</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913075?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Biffi, Alessandro</style></author><author><style face="normal" font="default" size="100%">Urday, Sebastian</style></author><author><style face="normal" font="default" size="100%">Kubiszewski, Patryk</style></author><author><style face="normal" font="default" size="100%">Gilkerson, Lee</style></author><author><style face="normal" font="default" size="100%">Sekar, Padmini</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Torres, Axana</style></author><author><style face="normal" font="default" size="100%">Bettin, Margaret</style></author><author><style face="normal" font="default" size="100%">Charidimou, Andreas</style></author><author><style face="normal" font="default" size="100%">Pasi, Marco</style></author><author><style face="normal" font="default" size="100%">Kourkoulis, Christina</style></author><author><style face="normal" font="default" size="100%">Schwab, Kristin</style></author><author><style face="normal" font="default" size="100%">DiPucchio, Zora</style></author><author><style face="normal" font="default" size="100%">Behymer, Tyler</style></author><author><style face="normal" font="default" size="100%">Osborne, Jennifer</style></author><author><style face="normal" font="default" size="100%">Morgan, Misty</style></author><author><style face="normal" font="default" size="100%">Moomaw, Charles J</style></author><author><style face="normal" font="default" size="100%">James, Michael L</style></author><author><style face="normal" font="default" size="100%">Greenberg, Steven M</style></author><author><style face="normal" font="default" size="100%">Viswanathan, Anand</style></author><author><style face="normal" font="default" size="100%">Gurol, M Edip</style></author><author><style face="normal" font="default" size="100%">Worrall, Bradford B</style></author><author><style face="normal" font="default" size="100%">Testai, Fernando D</style></author><author><style face="normal" font="default" size="100%">McCauley, Jacob L</style></author><author><style face="normal" font="default" size="100%">Falcone, Guido J</style></author><author><style face="normal" font="default" size="100%">Langefeld, Carl D</style></author><author><style face="normal" font="default" size="100%">Anderson, Christopher D</style></author><author><style face="normal" font="default" size="100%">Kamel, Hooman</style></author><author><style face="normal" font="default" size="100%">Woo, Daniel</style></author><author><style face="normal" font="default" size="100%">Sheth, Kevin N</style></author><author><style face="normal" font="default" size="100%">Rosand, Jonathan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Combining Imaging and Genetics to Predict Recurrence of Anticoagulation-Associated Intracerebral Hemorrhage.</style></title><secondary-title><style face="normal" font="default" size="100%">Stroke</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Stroke</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Anticoagulants</style></keyword><keyword><style  face="normal" font="default" size="100%">Apolipoprotein E4</style></keyword><keyword><style  face="normal" font="default" size="100%">Cerebral Hemorrhage</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Magnetic Resonance Imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Neuroimaging</style></keyword><keyword><style  face="normal" font="default" size="100%">Recurrence</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">51</style></volume><pages><style face="normal" font="default" size="100%">2153-2160</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND AND PURPOSE: &lt;/b&gt;For survivors of oral anticoagulation therapy (OAT)-associated intracerebral hemorrhage (OAT-ICH) who are at high risk for thromboembolism, the benefits of OAT resumption must be weighed against increased risk of recurrent hemorrhagic stroke. The ε2/ε4 alleles of the  () gene, MRI-defined cortical superficial siderosis, and cerebral microbleeds are the most potent risk factors for recurrent ICH. We sought to determine whether combining MRI markers and  genotype could have clinical impact by identifying ICH survivors in whom the risks of OAT resumption are highest.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Joint analysis of data from 2 longitudinal cohort studies of OAT-ICH survivors: (1) MGH-ICH study (Massachusetts General Hospital ICH) and (2) longitudinal component of the ERICH study (Ethnic/Racial Variations of Intracerebral Hemorrhage). We evaluated whether MRI markers and  genotype predict ICH recurrence. We then developed and validated a combined -MRI classification scheme to predict ICH recurrence, using Classification and Regression Tree analysis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Cortical superficial siderosis, cerebral microbleed, and  ε2/ε4 variants were independently associated with ICH recurrence after OAT-ICH (all &lt;0.05). Combining  genotype and MRI data resulted in improved prediction of ICH recurrence (Harrell C: 0.79 versus 0.55 for clinical data alone, =0.033). In the MGH (training) data set, CSS, cerebral microbleed, and  ε2/ε4 stratified likelihood of ICH recurrence into high-, medium-, and low-risk categories. In the ERICH (validation) data set, yearly ICH recurrence rates for high-, medium-, and low-risk individuals were 6.6%, 2.5%, and 0.9%, respectively, with overall area under the curve of 0.91 for prediction of recurrent ICH.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Combining MRI and  genotype stratifies likelihood of ICH recurrence into high, medium, and low risk. If confirmed in prospective studies, this combined -MRI classification scheme may prove useful for selecting individuals for OAT resumption after ICH.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32517581?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Walker, Ryan W</style></author><author><style face="normal" font="default" size="100%">Belbin, Gillian M</style></author><author><style face="normal" font="default" size="100%">Sorokin, Elena P</style></author><author><style face="normal" font="default" size="100%">Van Vleck, Tielman</style></author><author><style face="normal" font="default" size="100%">Wojcik, Genevieve L</style></author><author><style face="normal" font="default" size="100%">Moscati, Arden</style></author><author><style face="normal" font="default" size="100%">Gignoux, Christopher R</style></author><author><style face="normal" font="default" size="100%">Cho, Judy</style></author><author><style face="normal" font="default" size="100%">Abul-Husn, Noura S</style></author><author><style face="normal" font="default" size="100%">Nadkarni, Girish</style></author><author><style face="normal" font="default" size="100%">Kenny, Eimear E</style></author><author><style face="normal" font="default" size="100%">Loos, Ruth J F</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A common variant in PNPLA3 is associated with age at diagnosis of NAFLD in patients from a multi-ethnic biobank.</style></title><secondary-title><style face="normal" font="default" size="100%">J Hepatol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Hepatol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">72</style></volume><pages><style face="normal" font="default" size="100%">1070-1081</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND &amp; AIMS: &lt;/b&gt;The Ile138Met variant (rs738409) in the PNPLA3 gene has the largest effect on non-alcoholic fatty liver disease (NAFLD), increasing the risk of progression to severe forms of liver disease. It remains unknown if the variant plays a role in age of NAFLD onset. We aimed to determine if rs738409 impacts on the age of NAFLD diagnosis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We applied a novel natural language processing (NLP) algorithm to a longitudinal electronic health records (EHR) dataset of &gt;27,000 individuals with genetic data from a multi-ethnic biobank, defining NAFLD cases (n = 1,703) and confirming controls (n = 8,119). We conducted i) a survival analysis to determine if age at diagnosis differed by rs738409 genotype, ii) a receiver operating characteristics analysis to assess the utility of the rs738409 genotype in discriminating NAFLD cases from controls, and iii) a phenome-wide association study (PheWAS) between rs738409 and 10,095 EHR-derived disease diagnoses.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The PNPLA3 G risk allele was associated with: i) earlier age of NAFLD diagnosis, with the strongest effect in Hispanics (hazard ratio 1.33; 95% CI 1.15-1.53; p &lt;0.0001) among whom a NAFLD diagnosis was 15% more likely in risk allele carriers vs. non-carriers; ii) increased NAFLD risk (odds ratio 1.61; 95% CI 1.349-1.73; p &lt;0.0001), with the strongest effect among Hispanics (odds ratio 1.43; 95% CI 1.28-1.59; p &lt;0.0001); iii) additional liver diseases in a PheWAS (p &lt;4.95 × 10) where the risk variant also associated with earlier age of diagnosis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;Given the role of the rs738409 in NAFLD diagnosis age, our results suggest that stratifying risk within populations known to have an enhanced risk of liver disease, such as Hispanic carriers of the rs738409 variant, would be effective in earlier identification of those who would benefit most from early NAFLD prevention and treatment strategies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;LAY SUMMARY: &lt;/b&gt;Despite clear associations between the PNPLA3 rs738409 variant and elevated risk of progression from non-alcoholic fatty liver disease (NAFLD) to more severe forms of liver disease, it remains unknown if PNPLA3 rs738409 plays a role in the age of NAFLD onset. Herein, we found that this risk variant is associated with an earlier age of NAFLD and other liver disease diagnoses; an observation most pronounced in Hispanic Americans. We conclude that PNPLA3 rs738409 could be used to better understand liver disease risk within vulnerable populations and identify patients that may benefit from early prevention strategies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32145261?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sekar, Shobana</style></author><author><style face="normal" font="default" size="100%">Tomasini, Livia</style></author><author><style face="normal" font="default" size="100%">Proukakis, Christos</style></author><author><style face="normal" font="default" size="100%">Bae, Taejeong</style></author><author><style face="normal" font="default" size="100%">Manlove, Logan</style></author><author><style face="normal" font="default" size="100%">Jang, Yeongjun</style></author><author><style face="normal" font="default" size="100%">Scuderi, Soraya</style></author><author><style face="normal" font="default" size="100%">Zhou, Bo</style></author><author><style face="normal" font="default" size="100%">Kalyva, Maria</style></author><author><style face="normal" font="default" size="100%">Amiri, Anahita</style></author><author><style face="normal" font="default" size="100%">Mariani, Jessica</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Urban, Alexander E</style></author><author><style face="normal" font="default" size="100%">Vaccarino, Flora M</style></author><author><style face="normal" font="default" size="100%">Abyzov, Alexej</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Complex mosaic structural variations in human fetal brains.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Res</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 12</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">1695-1704</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Somatic mosaicism, manifesting as single nucleotide variants (SNVs), mobile element insertions, and structural changes in the DNA, is a common phenomenon in human brain cells, with potential functional consequences. Using a clonal approach, we previously detected 200-400 mosaic SNVs per cell in three human fetal brains (15-21 wk postconception). However, structural variation in the human fetal brain has not yet been investigated. Here, we discover and validate four mosaic structural variants (SVs) in the same brains and resolve their precise breakpoints. The SVs were of kilobase scale and complex, consisting of deletion(s) and rearranged genomic fragments, which sometimes originated from different chromosomes. Sequences at the breakpoints of these rearrangements had microhomologies, suggesting their origin from replication errors. One SV was found in two clones, and we timed its origin to ∼14 wk postconception. No large scale mosaic copy number variants (CNVs) were detectable in normal fetal human brains, suggesting that previously reported megabase-scale CNVs in neurons arise at later stages of development. By reanalysis of public single nuclei data from adult brain neurons, we detected an extrachromosomal circular DNA event. Our study reveals the existence of mosaic SVs in the developing human brain, likely arising from cell proliferation during mid-neurogenesis. Although relatively rare compared to SNVs and present in ∼10% of neurons, SVs in developing human brain affect a comparable number of bases in the genome (∼6200 vs. ∼4000 bp), implying that they may have similar functional consequences.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33122304?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Demanelis, Kathryn</style></author><author><style face="normal" font="default" size="100%">Jasmine, Farzana</style></author><author><style face="normal" font="default" size="100%">Chen, Lin S</style></author><author><style face="normal" font="default" size="100%">Chernoff, Meytal</style></author><author><style face="normal" font="default" size="100%">Tong, Lin</style></author><author><style face="normal" font="default" size="100%">Delgado, Dayana</style></author><author><style face="normal" font="default" size="100%">Zhang, Chenan</style></author><author><style face="normal" font="default" size="100%">Shinkle, Justin</style></author><author><style face="normal" font="default" size="100%">Sabarinathan, Mekala</style></author><author><style face="normal" font="default" size="100%">Lin, Hannah</style></author><author><style face="normal" font="default" size="100%">Ramirez, Eduardo</style></author><author><style face="normal" font="default" size="100%">Oliva, Meritxell</style></author><author><style face="normal" font="default" size="100%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Stranger, Barbara E</style></author><author><style face="normal" font="default" size="100%">Lai, Tsung-Po</style></author><author><style face="normal" font="default" size="100%">Aviv, Abraham</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Ahsan, Habibul</style></author><author><style face="normal" font="default" size="100%">Doherty, Jennifer A</style></author><author><style face="normal" font="default" size="100%">Kibriya, Muhammad G</style></author><author><style face="normal" font="default" size="100%">Pierce, Brandon L</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Determinants of telomere length across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Aging</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Telomere</style></keyword><keyword><style  face="normal" font="default" size="100%">Telomere Homeostasis</style></keyword><keyword><style  face="normal" font="default" size="100%">Telomere Shortening</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in nonblood, disease-relevant tissue types. Here, we characterize variability in TLs from 6391 tissue samples, representing &gt;20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation affects TL in multiple tissue types and that TL may mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913074?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Xavier, Catarina</style></author><author><style face="normal" font="default" size="100%">de la Puente, María</style></author><author><style face="normal" font="default" size="100%">Mosquera-Miguel, Ana</style></author><author><style face="normal" font="default" size="100%">Freire-Aradas, Ana</style></author><author><style face="normal" font="default" size="100%">Kalamara, Vivian</style></author><author><style face="normal" font="default" size="100%">Vidaki, Athina</style></author><author><style face="normal" font="default" size="100%">E Gross, Theresa</style></author><author><style face="normal" font="default" size="100%">Revoir, Andrew</style></author><author><style face="normal" font="default" size="100%">Pośpiech, Ewelina</style></author><author><style face="normal" font="default" size="100%">Kartasińska, Ewa</style></author><author><style face="normal" font="default" size="100%">Spólnicka, Magdalena</style></author><author><style face="normal" font="default" size="100%">Branicki, Wojciech</style></author><author><style face="normal" font="default" size="100%">E Ames, Carole</style></author><author><style face="normal" font="default" size="100%">M Schneider, Peter</style></author><author><style face="normal" font="default" size="100%">Hohoff, Carsten</style></author><author><style face="normal" font="default" size="100%">Kayser, Manfred</style></author><author><style face="normal" font="default" size="100%">Phillips, Christopher</style></author><author><style face="normal" font="default" size="100%">Parson, Walther</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">VISAGE Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Development and validation of the VISAGE AmpliSeq basic tool to predict appearance and ancestry from DNA.</style></title><secondary-title><style face="normal" font="default" size="100%">Forensic Sci Int Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Forensic Sci Int Genet</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">102336</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Forensic DNA phenotyping is gaining interest as the number of applications increases within the forensic genetics community. The possibility of providing investigative leads in addition to conventional DNA profiling for human identification provides new insights into otherwise &quot;cold&quot; police investigations. The ability of reporting on the bio-geographical ancestry (BGA), appearance characteristics and age based on DNA obtained from a crime scene sample of an unknown donor makes the exploration of such markers and the development of new methods meaningful for criminal investigations. The VISible Attributes through GEnomics (VISAGE) Consortium aims to disseminate and broaden the use of predictive markers and develop fully optimized and validated prototypes for forensic casework implementation. Here, the first VISAGE appearance and ancestry tool development, performance and validation is reported. A total of 153 SNPs (96.84 % assay conversion rate) were successfully incorporated into a single multiplex reaction using the AmpliSeq™ design pipeline, and applied for massively parallel sequencing with the Ion S5 platform. A collaborative effort involving six VISAGE laboratory partners was devised to perform all validation tests. An extensive validation plan was carefully organized to explore the assay's overall performance with optimum and low-input samples, as well as with challenging and casework mock samples. In addition, forensic validation studies such as concordance and mixture tests recurring to the Coriell sample set with known genotypes were performed. Finally, inhibitor tolerance and specificity were also evaluated. Results showed a robust, highly sensitive assay with good overall concordance between laboratories.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32619960?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rochtus, Anne</style></author><author><style face="normal" font="default" size="100%">Olson, Heather E</style></author><author><style face="normal" font="default" size="100%">Smith, Lacey</style></author><author><style face="normal" font="default" size="100%">Keith, Louisa G</style></author><author><style face="normal" font="default" size="100%">El Achkar, Christelle</style></author><author><style face="normal" font="default" size="100%">Taylor, Alan</style></author><author><style face="normal" font="default" size="100%">Mahida, Sonal</style></author><author><style face="normal" font="default" size="100%">Park, Meredith</style></author><author><style face="normal" font="default" size="100%">Kelly, McKenna</style></author><author><style face="normal" font="default" size="100%">Shain, Catherine</style></author><author><style face="normal" font="default" size="100%">Rockowitz, Shira</style></author><author><style face="normal" font="default" size="100%">Rosen Sheidley, Beth</style></author><author><style face="normal" font="default" size="100%">Poduri, Annapurna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort.</style></title><secondary-title><style face="normal" font="default" size="100%">Epilepsia</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Epilepsia</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Age of Onset</style></keyword><keyword><style  face="normal" font="default" size="100%">Brain Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Child, Preschool</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy, Generalized</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Microarray Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Exome Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">61</style></volume><pages><style face="normal" font="default" size="100%">249-258</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVE: &lt;/b&gt;We evaluated the yield of systematic analysis and/or reanalysis of whole exome sequencing (WES) data from a cohort of well-phenotyped pediatric patients with epilepsy and suspected but previously undetermined genetic etiology.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We identified and phenotyped 125 participants with pediatric epilepsy. Etiology was unexplained at the time of enrollment despite clinical testing, which included chromosomal microarray (57 patients), epilepsy gene panel (n = 48), both (n = 28), or WES (n = 8). Clinical epilepsy diagnoses included developmental and epileptic encephalopathy (DEE), febrile infection-related epilepsy syndrome, Rasmussen encephalitis, and other focal and generalized epilepsies. We analyzed WES data and compared the yield in participants with and without prior clinical genetic testing.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Overall, we identified pathogenic or likely pathogenic variants in 40% (50/125) of our study participants. Nine patients with DEE had genetic variants in recently published genes that had not been recognized as epilepsy-related at the time of clinical testing (FGF12, GABBR1, GABBR2, ITPA, KAT6A, PTPN23, RHOBTB2, SATB2), and eight patients had genetic variants in candidate epilepsy genes (CAMTA1, FAT3, GABRA6, HUWE1, PTCHD1). Ninety participants had concomitant or subsequent clinical genetic testing, which was ultimately explanatory for 26% (23/90). Of the 67 participants whose molecular diagnoses were &quot;unsolved&quot; through clinical genetic testing, we identified pathogenic or likely pathogenic variants in 17 (25%).&lt;/p&gt;&lt;p&gt;&lt;b&gt;SIGNIFICANCE: &lt;/b&gt;Our data argue for early consideration of WES with iterative reanalysis for patients with epilepsy, particularly those with DEE or epilepsy with intellectual disability. Rigorous analysis of WES data of well-phenotyped patients with epilepsy leads to a broader understanding of gene-specific phenotypic spectra as well as candidate disease gene identification. We illustrate the dynamic nature of genetic diagnosis over time, with analysis and in some cases reanalysis of exome data leading to the identification of disease-associated variants among participants with previously nondiagnostic results from a variety of clinical testing strategies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31957018?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gulsuner, S</style></author><author><style face="normal" font="default" size="100%">Stein, D J</style></author><author><style face="normal" font="default" size="100%">Susser, E S</style></author><author><style face="normal" font="default" size="100%">Sibeko, G</style></author><author><style face="normal" font="default" size="100%">Pretorius, A</style></author><author><style face="normal" font="default" size="100%">Walsh, T</style></author><author><style face="normal" font="default" size="100%">Majara, L</style></author><author><style face="normal" font="default" size="100%">Mndini, M M</style></author><author><style face="normal" font="default" size="100%">Mqulwana, S G</style></author><author><style face="normal" font="default" size="100%">Ntola, O A</style></author><author><style face="normal" font="default" size="100%">Casadei, S</style></author><author><style face="normal" font="default" size="100%">Ngqengelele, L L</style></author><author><style face="normal" font="default" size="100%">Korchina, V</style></author><author><style face="normal" font="default" size="100%">van der Merwe, C</style></author><author><style face="normal" font="default" size="100%">Malan, M</style></author><author><style face="normal" font="default" size="100%">Fader, K M</style></author><author><style face="normal" font="default" size="100%">Feng, M</style></author><author><style face="normal" font="default" size="100%">Willoughby, E</style></author><author><style face="normal" font="default" size="100%">Muzny, D</style></author><author><style face="normal" font="default" size="100%">Baldinger, A</style></author><author><style face="normal" font="default" size="100%">Andrews, H F</style></author><author><style face="normal" font="default" size="100%">Gur, R C</style></author><author><style face="normal" font="default" size="100%">Gibbs, R A</style></author><author><style face="normal" font="default" size="100%">Zingela, Z</style></author><author><style face="normal" font="default" size="100%">Nagdee, M</style></author><author><style face="normal" font="default" size="100%">Ramesar, R S</style></author><author><style face="normal" font="default" size="100%">King, M-C</style></author><author><style face="normal" font="default" size="100%">McClellan, J M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetics of schizophrenia in the South African Xhosa.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Age Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Autistic Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Bipolar Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Dopamine</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">gamma-Aminobutyric Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Glutamine</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Neural Pathways</style></keyword><keyword><style  face="normal" font="default" size="100%">Schizophrenia</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">South Africa</style></keyword><keyword><style  face="normal" font="default" size="100%">Synapses</style></keyword><keyword><style  face="normal" font="default" size="100%">Synaptic Transmission</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 01 31</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">367</style></volume><pages><style face="normal" font="default" size="100%">569-573</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Africa, the ancestral home of all modern humans, is the most informative continent for understanding the human genome and its contribution to complex disease. To better understand the genetics of schizophrenia, we studied the illness in the Xhosa population of South Africa, recruiting 909 cases and 917 age-, gender-, and residence-matched controls. Individuals with schizophrenia were significantly more likely than controls to harbor private, severely damaging mutations in genes that are critical to synaptic function, including neural circuitry mediated by the neurotransmitters glutamine, γ-aminobutyric acid, and dopamine. Schizophrenia is genetically highly heterogeneous, involving severe ultrarare mutations in genes that are critical to synaptic plasticity. The depth of genetic variation in Africa revealed this relationship with a moderate sample size and informed our understanding of the genetics of schizophrenia worldwide.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6477</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32001654?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hindy, George</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna G</style></author><author><style face="normal" font="default" size="100%">Ng, Kenney</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Lotta, Luca A</style></author><author><style face="normal" font="default" size="100%">Baras, Aris</style></author><author><style face="normal" font="default" size="100%">Drake, Isabel</style></author><author><style face="normal" font="default" size="100%">Orho-Melander, Marju</style></author><author><style face="normal" font="default" size="100%">Melander, Olle</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Regeneron Genetics Center</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-Wide Polygenic Score, Clinical Risk Factors, and Long-Term Trajectories of Coronary Artery Disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Arterioscler Thromb Vasc Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Arterioscler Thromb Vasc Biol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Artery Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Heart Disease Risk Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Heredity</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Incidence</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Multifactorial Inheritance</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sweden</style></keyword><keyword><style  face="normal" font="default" size="100%">Time Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">United Kingdom</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">2738-2746</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVE: &lt;/b&gt;To determine the relationship of a genome-wide polygenic score for coronary artery disease (GPS) with lifetime trajectories of CAD risk, directly compare its predictive capacity to traditional risk factors, and assess its interplay with the Pooled Cohort Equations (PCE) clinical risk estimator. Approach and Results: We studied GPS in 28 556 middle-aged participants of the Malmö Diet and Cancer Study, of whom 4122 (14.4%) developed CAD over a median follow-up of 21.3 years. A pronounced gradient in lifetime risk of CAD was observed-16% for those in the lowest GPS decile to 48% in the highest. We evaluated the discriminative capacity of the GPS-as assessed by change in the C-statistic from a baseline model including age and sex-among 5685 individuals with PCE risk estimates available. The increment for the GPS (+0.045, &lt;0.001) was higher than for any of 11 traditional risk factors (range +0.007 to +0.032). Minimal correlation was observed between GPS and 10-year risk defined by the PCE (=0.03), and addition of GPS improved the C-statistic of the PCE model by 0.026. A significant gradient in lifetime risk was observed for the GPS, even among individuals within a given PCE clinical risk stratum. We replicated key findings-noting strikingly consistent results-in 325 003 participants of the UK Biobank.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;GPS-a risk estimator available from birth-stratifies individuals into varying trajectories of clinical risk for CAD. Implementation of GPS may enable identification of high-risk individuals early in life, decades in advance of manifest risk factors or disease.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32957805?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nomura, Akihiro</style></author><author><style face="normal" font="default" size="100%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Won, Hong Hee</style></author><author><style face="normal" font="default" size="100%">Peloso, Gina M</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Ardissino, Diego</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Schunkert, Heribert</style></author><author><style face="normal" font="default" size="100%">Correa, Adolfo</style></author><author><style face="normal" font="default" size="100%">Bown, Matthew J</style></author><author><style face="normal" font="default" size="100%">Samani, Nilesh J</style></author><author><style face="normal" font="default" size="100%">Erdmann, Jeanette</style></author><author><style face="normal" font="default" size="100%">McPherson, Ruth</style></author><author><style face="normal" font="default" size="100%">Watkins, Hugh</style></author><author><style face="normal" font="default" size="100%">Saleheen, Danish</style></author><author><style face="normal" font="default" size="100%">Elosua, Roberto</style></author><author><style face="normal" font="default" size="100%">Kawashiri, Masa-Aki</style></author><author><style face="normal" font="default" size="100%">Tada, Hayato</style></author><author><style face="normal" font="default" size="100%">Gupta, Namrata</style></author><author><style face="normal" font="default" size="100%">Shah, Svati H</style></author><author><style face="normal" font="default" size="100%">Rader, Daniel J</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Heterozygous  Gene Deficiency and Risk of Coronary Artery Disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Circ Genom Precis Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Circ Genom Precis Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 10</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">417-423</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Familial sitosterolemia is a rare Mendelian disorder characterized by hyperabsorption and decreased biliary excretion of dietary sterols. Affected individuals typically have complete genetic deficiency-homozygous loss-of-function (LoF) variants-in the  or  genes and have substantially elevated plasma sitosterol and LDL (low-density lipoprotein) cholesterol (LDL-C) levels. The impact of partial genetic deficiency of  or -as occurs in heterozygous carriers of LoF variants-on LDL-C and risk of coronary artery disease (CAD) has remained uncertain.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We first recruited 9 sitosterolemia families, identified causative LoF variants in  or , and evaluated the associations of these  or  LoF variants with plasma phytosterols and lipid levels. We next assessed for LoF variants in  or  in CAD cases (n=29 321) versus controls (n=357 326). We tested the association of rare LoF variants in  or  with blood lipids and risk for CAD. Rare LoF variants were defined as protein-truncating variants with minor allele frequency &lt;0.1% in  or .&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;In sitosterolemia families, 7 pedigrees harbored causative LoF variants in  and 2 pedigrees in . Homozygous LoF variants in either  or  led to marked elevations in sitosterol and LDL-C. Of those sitosterolemia families, heterozygous carriers of  LoF variants exhibited increased sitosterol and LDL-C levels compared with noncarriers. Within large-scale CAD case-control cohorts, prevalence of rare LoF variants in  and in  was ≈0.1% each.  heterozygous LoF variant carriers had significantly elevated LDL-C levels (25 mg/dL [95% CI, 14-35]; =1.1×10) and were at 2-fold increased risk of CAD (odds ratio, 2.06 [95% CI, 1.27-3.35]; =0.004). By contrast,  heterozygous LoF carrier status was not associated with increased LDL-C or risk of CAD.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Although familial sitosterolemia is traditionally considered as a recessive disorder, we observed that heterozygous carriers of an LoF variant in  had significantly increased sitosterol and LDL-C levels and a 2-fold increase in risk of CAD.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32862661?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Oliva, Meritxell</style></author><author><style face="normal" font="default" size="100%">Muñoz-Aguirre, Manuel</style></author><author><style face="normal" font="default" size="100%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Wucher, Valentin</style></author><author><style face="normal" font="default" size="100%">Gewirtz, Ariel D H</style></author><author><style face="normal" font="default" size="100%">Cotter, Daniel J</style></author><author><style face="normal" font="default" size="100%">Parsana, Princy</style></author><author><style face="normal" font="default" size="100%">Kasela, Silva</style></author><author><style face="normal" font="default" size="100%">Balliu, Brunilda</style></author><author><style face="normal" font="default" size="100%">Viñuela, Ana</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Zou, Yuxin</style></author><author><style face="normal" font="default" size="100%">Khramtsova, Ekaterina A</style></author><author><style face="normal" font="default" size="100%">Skol, Andrew D</style></author><author><style face="normal" font="default" size="100%">Garrido-Martín, Diego</style></author><author><style face="normal" font="default" size="100%">Reverter, Ferran</style></author><author><style face="normal" font="default" size="100%">Brown, Andrew</style></author><author><style face="normal" font="default" size="100%">Evans, Patrick</style></author><author><style face="normal" font="default" size="100%">Gamazon, Eric R</style></author><author><style face="normal" font="default" size="100%">Payne, Anthony</style></author><author><style face="normal" font="default" size="100%">Bonazzola, Rodrigo</style></author><author><style face="normal" font="default" size="100%">Barbeira, Alvaro N</style></author><author><style face="normal" font="default" size="100%">Hamel, Andrew R</style></author><author><style face="normal" font="default" size="100%">Martinez-Perez, Angel</style></author><author><style face="normal" font="default" size="100%">Soria, José Manuel</style></author><author><style face="normal" font="default" size="100%">Pierce, Brandon L</style></author><author><style face="normal" font="default" size="100%">Stephens, Matthew</style></author><author><style face="normal" font="default" size="100%">Eskin, Eleazar</style></author><author><style face="normal" font="default" size="100%">Dermitzakis, Emmanouil T</style></author><author><style face="normal" font="default" size="100%">Segrè, Ayellet V</style></author><author><style face="normal" font="default" size="100%">Im, Hae Kyung</style></author><author><style face="normal" font="default" size="100%">Engelhardt, Barbara E</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Montgomery, Stephen B</style></author><author><style face="normal" font="default" size="100%">Battle, Alexis J</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Guigo, Roderic</style></author><author><style face="normal" font="default" size="100%">Stranger, Barbara E</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">The impact of sex on gene expression across human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human, X</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Epigenesis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Promoter Regions, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Characteristics</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913072?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bick, Alexander G</style></author><author><style face="normal" font="default" size="100%">Weinstock, Joshua S</style></author><author><style face="normal" font="default" size="100%">Nandakumar, Satish K</style></author><author><style face="normal" font="default" size="100%">Fulco, Charles P</style></author><author><style face="normal" font="default" size="100%">Bao, Erik L</style></author><author><style face="normal" font="default" size="100%">Zekavat, Seyedeh M</style></author><author><style face="normal" font="default" size="100%">Szeto, Mindy D</style></author><author><style face="normal" font="default" size="100%">Liao, Xiaotian</style></author><author><style face="normal" font="default" size="100%">Leventhal, Matthew J</style></author><author><style face="normal" font="default" size="100%">Nasser, Joseph</style></author><author><style face="normal" font="default" size="100%">Chang, Kyle</style></author><author><style face="normal" font="default" size="100%">Laurie, Cecelia</style></author><author><style face="normal" font="default" size="100%">Burugula, Bala Bharathi</style></author><author><style face="normal" font="default" size="100%">Gibson, Christopher J</style></author><author><style face="normal" font="default" size="100%">Lin, Amy E</style></author><author><style face="normal" font="default" size="100%">Taub, Margaret A</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin</style></author><author><style face="normal" font="default" size="100%">Mitchell, Braxton D</style></author><author><style face="normal" font="default" size="100%">Barnes, Kathleen C</style></author><author><style face="normal" font="default" size="100%">Moscati, Arden</style></author><author><style face="normal" font="default" size="100%">Fornage, Myriam</style></author><author><style face="normal" font="default" size="100%">Redline, Susan</style></author><author><style face="normal" font="default" size="100%">Psaty, Bruce M</style></author><author><style face="normal" font="default" size="100%">Silverman, Edwin K</style></author><author><style face="normal" font="default" size="100%">Weiss, Scott T</style></author><author><style face="normal" font="default" size="100%">Palmer, Nicholette D</style></author><author><style face="normal" font="default" size="100%">Vasan, Ramachandran S</style></author><author><style face="normal" font="default" size="100%">Burchard, Esteban G</style></author><author><style face="normal" font="default" size="100%">Kardia, Sharon L R</style></author><author><style face="normal" font="default" size="100%">He, Jiang</style></author><author><style face="normal" font="default" size="100%">Kaplan, Robert C</style></author><author><style face="normal" font="default" size="100%">Smith, Nicholas L</style></author><author><style face="normal" font="default" size="100%">Arnett, Donna K</style></author><author><style face="normal" font="default" size="100%">Schwartz, David A</style></author><author><style face="normal" font="default" size="100%">Correa, Adolfo</style></author><author><style face="normal" font="default" size="100%">de Andrade, Mariza</style></author><author><style face="normal" font="default" size="100%">Guo, Xiuqing</style></author><author><style face="normal" font="default" size="100%">Konkle, Barbara A</style></author><author><style face="normal" font="default" size="100%">Custer, Brian</style></author><author><style face="normal" font="default" size="100%">Peralta, Juan M</style></author><author><style face="normal" font="default" size="100%">Gui, Hongsheng</style></author><author><style face="normal" font="default" size="100%">Meyers, Deborah A</style></author><author><style face="normal" font="default" size="100%">McGarvey, Stephen T</style></author><author><style face="normal" font="default" size="100%">Chen, Ida Yii-Der</style></author><author><style face="normal" font="default" size="100%">Shoemaker, M Benjamin</style></author><author><style face="normal" font="default" size="100%">Peyser, Patricia A</style></author><author><style face="normal" font="default" size="100%">Broome, Jai G</style></author><author><style face="normal" font="default" size="100%">Gogarten, Stephanie M</style></author><author><style face="normal" font="default" size="100%">Wang, Fei Fei</style></author><author><style face="normal" font="default" size="100%">Wong, Quenna</style></author><author><style face="normal" font="default" size="100%">Montasser, May E</style></author><author><style face="normal" font="default" size="100%">Daya, Michelle</style></author><author><style face="normal" font="default" size="100%">Kenny, Eimear E</style></author><author><style face="normal" font="default" size="100%">North, Kari E</style></author><author><style face="normal" font="default" size="100%">Launer, Lenore J</style></author><author><style face="normal" font="default" size="100%">Cade, Brian E</style></author><author><style face="normal" font="default" size="100%">Bis, Joshua C</style></author><author><style face="normal" font="default" size="100%">Cho, Michael H</style></author><author><style face="normal" font="default" size="100%">Lasky-Su, Jessica</style></author><author><style face="normal" font="default" size="100%">Bowden, Donald W</style></author><author><style face="normal" font="default" size="100%">Cupples, L Adrienne</style></author><author><style face="normal" font="default" size="100%">Mak, Angel C Y</style></author><author><style face="normal" font="default" size="100%">Becker, Lewis C</style></author><author><style face="normal" font="default" size="100%">Smith, Jennifer A</style></author><author><style face="normal" font="default" size="100%">Kelly, Tanika N</style></author><author><style face="normal" font="default" size="100%">Aslibekyan, Stella</style></author><author><style face="normal" font="default" size="100%">Heckbert, Susan R</style></author><author><style face="normal" font="default" size="100%">Tiwari, Hemant K</style></author><author><style face="normal" font="default" size="100%">Yang, Ivana V</style></author><author><style face="normal" font="default" size="100%">Heit, John A</style></author><author><style face="normal" font="default" size="100%">Lubitz, Steven A</style></author><author><style face="normal" font="default" size="100%">Johnsen, Jill M</style></author><author><style face="normal" font="default" size="100%">Curran, Joanne E</style></author><author><style face="normal" font="default" size="100%">Wenzel, Sally E</style></author><author><style face="normal" font="default" size="100%">Weeks, Daniel E</style></author><author><style face="normal" font="default" size="100%">Rao, Dabeeru C</style></author><author><style face="normal" font="default" size="100%">Darbar, Dawood</style></author><author><style face="normal" font="default" size="100%">Moon, Jee-Young</style></author><author><style face="normal" font="default" size="100%">Tracy, Russell P</style></author><author><style face="normal" font="default" size="100%">Buth, Erin J</style></author><author><style face="normal" font="default" size="100%">Rafaels, Nicholas</style></author><author><style face="normal" font="default" size="100%">Loos, Ruth J F</style></author><author><style face="normal" font="default" size="100%">Durda, Peter</style></author><author><style face="normal" font="default" size="100%">Liu, Yongmei</style></author><author><style face="normal" font="default" size="100%">Hou, Lifang</style></author><author><style face="normal" font="default" size="100%">Lee, Jiwon</style></author><author><style face="normal" font="default" size="100%">Kachroo, Priyadarshini</style></author><author><style face="normal" font="default" size="100%">Freedman, Barry I</style></author><author><style face="normal" font="default" size="100%">Levy, Daniel</style></author><author><style face="normal" font="default" size="100%">Bielak, Lawrence F</style></author><author><style face="normal" font="default" size="100%">Hixson, James E</style></author><author><style face="normal" font="default" size="100%">Floyd, James S</style></author><author><style face="normal" font="default" size="100%">Whitsel, Eric A</style></author><author><style face="normal" font="default" size="100%">Ellinor, Patrick T</style></author><author><style face="normal" font="default" size="100%">Irvin, Marguerite R</style></author><author><style face="normal" font="default" size="100%">Fingerlin, Tasha E</style></author><author><style face="normal" font="default" size="100%">Raffield, Laura M</style></author><author><style face="normal" font="default" size="100%">Armasu, Sebastian M</style></author><author><style face="normal" font="default" size="100%">Wheeler, Marsha M</style></author><author><style face="normal" font="default" size="100%">Sabino, Ester C</style></author><author><style face="normal" font="default" size="100%">Blangero, John</style></author><author><style face="normal" font="default" size="100%">Williams, L Keoki</style></author><author><style face="normal" font="default" size="100%">Levy, Bruce D</style></author><author><style face="normal" font="default" size="100%">Sheu, Wayne Huey-Herng</style></author><author><style face="normal" font="default" size="100%">Roden, Dan M</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Manson, JoAnn E</style></author><author><style face="normal" font="default" size="100%">Mathias, Rasika A</style></author><author><style face="normal" font="default" size="100%">Desai, Pinkal</style></author><author><style face="normal" font="default" size="100%">Taylor, Kent D</style></author><author><style face="normal" font="default" size="100%">Johnson, Andrew D</style></author><author><style face="normal" font="default" size="100%">Auer, Paul L</style></author><author><style face="normal" font="default" size="100%">Kooperberg, Charles</style></author><author><style face="normal" font="default" size="100%">Laurie, Cathy C</style></author><author><style face="normal" font="default" size="100%">Blackwell, Thomas W</style></author><author><style face="normal" font="default" size="100%">Smith, Albert V</style></author><author><style face="normal" font="default" size="100%">Zhao, Hongyu</style></author><author><style face="normal" font="default" size="100%">Lange, Ethan</style></author><author><style face="normal" font="default" size="100%">Lange, Leslie</style></author><author><style face="normal" font="default" size="100%">Rich, Stephen S</style></author><author><style face="normal" font="default" size="100%">Rotter, Jerome I</style></author><author><style face="normal" font="default" size="100%">Wilson, James G</style></author><author><style face="normal" font="default" size="100%">Scheet, Paul</style></author><author><style face="normal" font="default" size="100%">Kitzman, Jacob O</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author><author><style face="normal" font="default" size="100%">Engreitz, Jesse M</style></author><author><style face="normal" font="default" size="100%">Ebert, Benjamin L</style></author><author><style face="normal" font="default" size="100%">Reiner, Alexander P</style></author><author><style face="normal" font="default" size="100%">Jaiswal, Siddhartha</style></author><author><style face="normal" font="default" size="100%">Abecasis, Gonçalo</style></author><author><style face="normal" font="default" size="100%">Sankaran, Vijay G</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NHLBI Trans-Omics for Precision Medicine Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Inherited causes of clonal haematopoiesis in 97,691 whole genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nature</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Africa</style></keyword><keyword><style  face="normal" font="default" size="100%">African Continental Ancestry Group</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">alpha Karyopherins</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Self Renewal</style></keyword><keyword><style  face="normal" font="default" size="100%">Clonal Hematopoiesis</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Germ-Line Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Hematopoietic Stem Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Intracellular Signaling Peptides and Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">National Heart, Lung, and Blood Institute (U.S.)</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Precision Medicine</style></keyword><keyword><style  face="normal" font="default" size="100%">Proto-Oncogene Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Tripartite Motif Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">United States</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 10</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">586</style></volume><pages><style face="normal" font="default" size="100%">763-768</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7831</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33057201?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Satterstrom, F Kyle</style></author><author><style face="normal" font="default" size="100%">Kosmicki, Jack A</style></author><author><style face="normal" font="default" size="100%">Wang, Jiebiao</style></author><author><style face="normal" font="default" size="100%">Breen, Michael S</style></author><author><style face="normal" font="default" size="100%">De Rubeis, Silvia</style></author><author><style face="normal" font="default" size="100%">An, Joon-Yong</style></author><author><style face="normal" font="default" size="100%">Peng, Minshi</style></author><author><style face="normal" font="default" size="100%">Collins, Ryan</style></author><author><style face="normal" font="default" size="100%">Grove, Jakob</style></author><author><style face="normal" font="default" size="100%">Klei, Lambertus</style></author><author><style face="normal" font="default" size="100%">Stevens, Christine</style></author><author><style face="normal" font="default" size="100%">Reichert, Jennifer</style></author><author><style face="normal" font="default" size="100%">Mulhern, Maureen S</style></author><author><style face="normal" font="default" size="100%">Artomov, Mykyta</style></author><author><style face="normal" font="default" size="100%">Gerges, Sherif</style></author><author><style face="normal" font="default" size="100%">Sheppard, Brooke</style></author><author><style face="normal" font="default" size="100%">Xu, Xinyi</style></author><author><style face="normal" font="default" size="100%">Bhaduri, Aparna</style></author><author><style face="normal" font="default" size="100%">Norman, Utku</style></author><author><style face="normal" font="default" size="100%">Brand, Harrison</style></author><author><style face="normal" font="default" size="100%">Schwartz, Grace</style></author><author><style face="normal" font="default" size="100%">Nguyen, Rachel</style></author><author><style face="normal" font="default" size="100%">Guerrero, Elizabeth E</style></author><author><style face="normal" font="default" size="100%">Dias, Caroline</style></author><author><style face="normal" font="default" size="100%">Betancur, Catalina</style></author><author><style face="normal" font="default" size="100%">Cook, Edwin H</style></author><author><style face="normal" font="default" size="100%">Gallagher, Louise</style></author><author><style face="normal" font="default" size="100%">Gill, Michael</style></author><author><style face="normal" font="default" size="100%">Sutcliffe, James S</style></author><author><style face="normal" font="default" size="100%">Thurm, Audrey</style></author><author><style face="normal" font="default" size="100%">Zwick, Michael E</style></author><author><style face="normal" font="default" size="100%">Børglum, Anders D</style></author><author><style face="normal" font="default" size="100%">State, Matthew W</style></author><author><style face="normal" font="default" size="100%">Cicek, A Ercument</style></author><author><style face="normal" font="default" size="100%">Talkowski, Michael E</style></author><author><style face="normal" font="default" size="100%">Cutler, David J</style></author><author><style face="normal" font="default" size="100%">Devlin, Bernie</style></author><author><style face="normal" font="default" size="100%">Sanders, Stephan J</style></author><author><style face="normal" font="default" size="100%">Roeder, Kathryn</style></author><author><style face="normal" font="default" size="100%">Daly, Mark J</style></author><author><style face="normal" font="default" size="100%">Buxbaum, Joseph D</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Autism Sequencing Consortium</style></author><author><style face="normal" font="default" size="100%">iPSYCH-Broad Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Autistic Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Lineage</style></keyword><keyword><style  face="normal" font="default" size="100%">Cerebral Cortex</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Developmental</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurobiology</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurons</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Sex Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Single-Cell Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Exome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 02 06</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">180</style></volume><pages><style face="normal" font="default" size="100%">568-584.e23</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31981491?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mak, Angel C Y</style></author><author><style face="normal" font="default" size="100%">Sajuthi, Satria</style></author><author><style face="normal" font="default" size="100%">Joo, Jaehyun</style></author><author><style face="normal" font="default" size="100%">Xiao, Shujie</style></author><author><style face="normal" font="default" size="100%">Sleiman, Patrick M</style></author><author><style face="normal" font="default" size="100%">White, Marquitta J</style></author><author><style face="normal" font="default" size="100%">Lee, Eunice Y</style></author><author><style face="normal" font="default" size="100%">Saef, Benjamin</style></author><author><style face="normal" font="default" size="100%">Hu, Donglei</style></author><author><style face="normal" font="default" size="100%">Gui, Hongsheng</style></author><author><style face="normal" font="default" size="100%">Keys, Kevin L</style></author><author><style face="normal" font="default" size="100%">Lurmann, Fred</style></author><author><style face="normal" font="default" size="100%">Jain, Deepti</style></author><author><style face="normal" font="default" size="100%">Abecasis, Gonçalo</style></author><author><style face="normal" font="default" size="100%">Kang, Hyun Min</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Germer, Soren</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Winterkorn, Lara</style></author><author><style face="normal" font="default" size="100%">Reeves, Catherine</style></author><author><style face="normal" font="default" size="100%">Huntsman, Scott</style></author><author><style face="normal" font="default" size="100%">Eng, Celeste</style></author><author><style face="normal" font="default" size="100%">Salazar, Sandra</style></author><author><style face="normal" font="default" size="100%">Oh, Sam S</style></author><author><style face="normal" font="default" size="100%">Gilliland, Frank D</style></author><author><style face="normal" font="default" size="100%">Chen, Zhanghua</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajesh</style></author><author><style face="normal" font="default" size="100%">Martínez, Fernando D</style></author><author><style face="normal" font="default" size="100%">Wu, Ann Chen</style></author><author><style face="normal" font="default" size="100%">Ziv, Elad</style></author><author><style face="normal" font="default" size="100%">Hakonarson, Hakon</style></author><author><style face="normal" font="default" size="100%">Himes, Blanca E</style></author><author><style face="normal" font="default" size="100%">Williams, L Keoki</style></author><author><style face="normal" font="default" size="100%">Seibold, Max A</style></author><author><style face="normal" font="default" size="100%">Burchard, Esteban G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Lung Function in African American Children with Asthma Is Associated with Novel Regulatory Variants of the KIT Ligand  and Gene-By-Air-Pollution Interaction.</style></title><secondary-title><style face="normal" font="default" size="100%">Genetics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genetics</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">215</style></volume><pages><style face="normal" font="default" size="100%">869-886</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Baseline lung function, quantified as forced expiratory volume in the first second of exhalation (FEV), is a standard diagnostic criterion used by clinicians to identify and classify lung diseases. Using whole-genome sequencing data from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine project, we identified a novel genetic association with FEV on chromosome 12 in 867 African American children with asthma ( = 1.26 × 10, β = 0.302). Conditional analysis within 1 Mb of the tag signal (rs73429450) yielded one major and two other weaker independent signals within this peak. We explored statistical and functional evidence for all variants in linkage disequilibrium with the three independent signals and yielded nine variants as the most likely candidates responsible for the association with FEV Hi-C data and expression QTL analysis demonstrated that these variants physically interacted with  (KIT ligand, also known as ), and their minor alleles were associated with increased expression of the  gene in nasal epithelial cells. Gene-by-air-pollution interaction analysis found that the candidate variant rs58475486 interacted with past-year ambient sulfur dioxide exposure ( = 0.003, β = 0.32). This study identified a novel protective genetic association with FEV, possibly mediated through , in African American children with asthma. This is the first study that has identified a genetic association between lung function and , which has established a role in orchestrating allergic inflammation in asthma.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32327564?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alonge, Michael</style></author><author><style face="normal" font="default" size="100%">Wang, Xingang</style></author><author><style face="normal" font="default" size="100%">Benoit, Matthias</style></author><author><style face="normal" font="default" size="100%">Soyk, Sebastian</style></author><author><style face="normal" font="default" size="100%">Pereira, Lara</style></author><author><style face="normal" font="default" size="100%">Zhang, Lei</style></author><author><style face="normal" font="default" size="100%">Suresh, Hamsini</style></author><author><style face="normal" font="default" size="100%">Ramakrishnan, Srividya</style></author><author><style face="normal" font="default" size="100%">Maumus, Florian</style></author><author><style face="normal" font="default" size="100%">Ciren, Danielle</style></author><author><style face="normal" font="default" size="100%">Levy, Yuval</style></author><author><style face="normal" font="default" size="100%">Harel, Tom Hai</style></author><author><style face="normal" font="default" size="100%">Shalev-Schlosser, Gili</style></author><author><style face="normal" font="default" size="100%">Amsellem, Ziva</style></author><author><style face="normal" font="default" size="100%">Razifard, Hamid</style></author><author><style face="normal" font="default" size="100%">Caicedo, Ana L</style></author><author><style face="normal" font="default" size="100%">Tieman, Denise M</style></author><author><style face="normal" font="default" size="100%">Klee, Harry</style></author><author><style face="normal" font="default" size="100%">Kirsche, Melanie</style></author><author><style face="normal" font="default" size="100%">Aganezov, Sergey</style></author><author><style face="normal" font="default" size="100%">Ranallo-Benavidez, T Rhyker</style></author><author><style face="normal" font="default" size="100%">Lemmon, Zachary H</style></author><author><style face="normal" font="default" size="100%">Kim, Jennifer</style></author><author><style face="normal" font="default" size="100%">Robitaille, Gina</style></author><author><style face="normal" font="default" size="100%">Kramer, Melissa</style></author><author><style face="normal" font="default" size="100%">Goodwin, Sara</style></author><author><style face="normal" font="default" size="100%">McCombie, W Richard</style></author><author><style face="normal" font="default" size="100%">Hutton, Samuel</style></author><author><style face="normal" font="default" size="100%">Van Eck, Joyce</style></author><author><style face="normal" font="default" size="100%">Gillis, Jesse</style></author><author><style face="normal" font="default" size="100%">Eshed, Yuval</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">van der Knaap, Esther</style></author><author><style face="normal" font="default" size="100%">Schatz, Michael C</style></author><author><style face="normal" font="default" size="100%">Lippman, Zachary B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Crops, Agricultural</style></keyword><keyword><style  face="normal" font="default" size="100%">Cytochrome P-450 Enzyme System</style></keyword><keyword><style  face="normal" font="default" size="100%">Ecotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Epistasis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Fruit</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Duplication</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Plant</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomic Structural Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Inbreeding</style></keyword><keyword><style  face="normal" font="default" size="100%">Lycopersicon esculentum</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Annotation</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Plant Breeding</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07 09</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">182</style></volume><pages><style face="normal" font="default" size="100%">145-161.e23</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32553272?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Abel, Haley J</style></author><author><style face="normal" font="default" size="100%">Larson, David E</style></author><author><style face="normal" font="default" size="100%">Regier, Allison A</style></author><author><style face="normal" font="default" size="100%">Chiang, Colby</style></author><author><style face="normal" font="default" size="100%">Das, Indraniel</style></author><author><style face="normal" font="default" size="100%">Kanchi, Krishna L</style></author><author><style face="normal" font="default" size="100%">Layer, Ryan M</style></author><author><style face="normal" font="default" size="100%">Neale, Benjamin M</style></author><author><style face="normal" font="default" size="100%">Salerno, William J</style></author><author><style face="normal" font="default" size="100%">Reeves, Catherine</style></author><author><style face="normal" font="default" size="100%">Buyske, Steven</style></author><author><style face="normal" font="default" size="100%">Matise, Tara C</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author><author><style face="normal" font="default" size="100%">Dutcher, Susan K</style></author><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NHGRI Centers for Common Disease Genomics</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Mapping and characterization of structural variation in 17,795 human genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nature</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Continental Population Groups</style></keyword><keyword><style  face="normal" font="default" size="100%">Epigenesis, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Dosage</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Sequence Annotation</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">583</style></volume><pages><style face="normal" font="default" size="100%">83-89</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7814</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32460305?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Haas, Mary E</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Klarin, Derek</style></author><author><style face="normal" font="default" size="100%">Hindy, George</style></author><author><style face="normal" font="default" size="100%">Jiang, Lan</style></author><author><style face="normal" font="default" size="100%">Wei, Wei-Qi</style></author><author><style face="normal" font="default" size="100%">Feng, Qiping</style></author><author><style face="normal" font="default" size="100%">Karjalainen, Juha</style></author><author><style face="normal" font="default" size="100%">Havulinna, Aki</style></author><author><style face="normal" font="default" size="100%">Kiiskinen, Tuomo</style></author><author><style face="normal" font="default" size="100%">Bick, Alexander</style></author><author><style face="normal" font="default" size="100%">Ardissino, Diego</style></author><author><style face="normal" font="default" size="100%">Wilson, James G</style></author><author><style face="normal" font="default" size="100%">Schunkert, Heribert</style></author><author><style face="normal" font="default" size="100%">McPherson, Ruth</style></author><author><style face="normal" font="default" size="100%">Watkins, Hugh</style></author><author><style face="normal" font="default" size="100%">Elosua, Roberto</style></author><author><style face="normal" font="default" size="100%">Bown, Matthew J</style></author><author><style face="normal" font="default" size="100%">Samani, Nilesh J</style></author><author><style face="normal" font="default" size="100%">Baber, Usman</style></author><author><style face="normal" font="default" size="100%">Erdmann, Jeanette</style></author><author><style face="normal" font="default" size="100%">Gupta, Namrata</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Saleheen, Danish</style></author><author><style face="normal" font="default" size="100%">Chang, Kyong-Mi</style></author><author><style face="normal" font="default" size="100%">Vujkovic, Marijana</style></author><author><style face="normal" font="default" size="100%">Voight, Ben</style></author><author><style face="normal" font="default" size="100%">Damrauer, Scott</style></author><author><style face="normal" font="default" size="100%">Lynch, Julie</style></author><author><style face="normal" font="default" size="100%">Kaplan, David</style></author><author><style face="normal" font="default" size="100%">Serper, Marina</style></author><author><style face="normal" font="default" size="100%">Tsao, Philip</style></author><author><style face="normal" font="default" size="100%">Mercader, Josep</style></author><author><style face="normal" font="default" size="100%">Hanis, Craig</style></author><author><style face="normal" font="default" size="100%">Daly, Mark</style></author><author><style face="normal" font="default" size="100%">Denny, Joshua</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Million Veteran Program</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alleles</style></keyword><keyword><style  face="normal" font="default" size="100%">Cholesterol, LDL</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Artery Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Datasets as Topic</style></keyword><keyword><style  face="normal" font="default" size="100%">Fatty Liver</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Homozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Liver</style></keyword><keyword><style  face="normal" font="default" size="100%">Liver Cirrhosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Liver Cirrhosis, Alcoholic</style></keyword><keyword><style  face="normal" font="default" size="100%">Loss of Function Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Mitochondrial Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Oxidoreductases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 04</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">e1008629</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.91, p = 2.3*10-11). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.025 SD, 3.7*10-43), alkaline phosphatase (-0.025 SD, 1.2*10-37), total cholesterol (-0.030 SD, p = 1.9*10-36) and LDL cholesterol (-0.027 SD, p = 5.1*10-30) levels. We identified a series of additional MARC1 alleles (low-frequency missense p.M187K and rare protein-truncating p.R200Ter) that also associated with lower cholesterol levels, liver enzyme levels and reduced risk of cirrhosis (0 cirrhosis cases for 238 R200Ter carriers versus 17,046 cases of cirrhosis among 759,027 non-carriers, p = 0.04) suggesting that deficiency of the MARC1 enzyme may lower blood cholesterol levels and protect against cirrhosis.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32282858?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Montenegro-Garreaud, Ximena</style></author><author><style face="normal" font="default" size="100%">Hansen, Adam W</style></author><author><style face="normal" font="default" size="100%">Khayat, Michael M</style></author><author><style face="normal" font="default" size="100%">Chander, Varuna</style></author><author><style face="normal" font="default" size="100%">Grochowski, Christopher M</style></author><author><style face="normal" font="default" size="100%">Jiang, Yunyun</style></author><author><style face="normal" font="default" size="100%">Li, He</style></author><author><style face="normal" font="default" size="100%">Mitani, Tadahiro</style></author><author><style face="normal" font="default" size="100%">Kessler, Elena</style></author><author><style face="normal" font="default" size="100%">Jayaseelan, Joy</style></author><author><style face="normal" font="default" size="100%">Shen, Hua</style></author><author><style face="normal" font="default" size="100%">Gezdirici, Alper</style></author><author><style face="normal" font="default" size="100%">Pehlivan, Davut</style></author><author><style face="normal" font="default" size="100%">Meng, Qingchang</style></author><author><style face="normal" font="default" size="100%">Rosenfeld, Jill A</style></author><author><style face="normal" font="default" size="100%">Jhangiani, Shalini N</style></author><author><style face="normal" font="default" size="100%">Madan-Khetarpal, Suneeta</style></author><author><style face="normal" font="default" size="100%">Scott, Daryl A</style></author><author><style face="normal" font="default" size="100%">Abarca-Barriga, Hugo</style></author><author><style face="normal" font="default" size="100%">Trubnykova, Milana</style></author><author><style face="normal" font="default" size="100%">Gingras, Marie-Claude</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Posey, Jennifer E</style></author><author><style face="normal" font="default" size="100%">Liu, Pengfei</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phenotypic expansion in KIF1A-related dominant disorders: A description of novel variants and review of published cases.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Mutat</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Mutat</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 12</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">2094-2104</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;KIF1A is a molecular motor for membrane-bound cargo important to the development and survival of sensory neurons. KIF1A dysfunction has been associated with several Mendelian disorders with a spectrum of overlapping phenotypes, ranging from spastic paraplegia to intellectual disability. We present a novel pathogenic in-frame deletion in the KIF1A molecular motor domain inherited by two affected siblings from an unaffected mother with apparent germline mosaicism. We identified eight additional cases with heterozygous, pathogenic KIF1A variants ascertained from a local data lake. Our data provide evidence for the expansion of KIF1A-associated phenotypes to include hip subluxation and dystonia as well as phenotypes observed in only a single case: gelastic cataplexy, coxa valga, and double collecting system. We review the literature and suggest that KIF1A dysfunction is better understood as a single neuromuscular disorder with variable involvement of other organ systems than a set of discrete disorders converging at a single locus.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32935419?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Collins, Ryan L</style></author><author><style face="normal" font="default" size="100%">Brand, Harrison</style></author><author><style face="normal" font="default" size="100%">Karczewski, Konrad J</style></author><author><style face="normal" font="default" size="100%">Zhao, Xuefang</style></author><author><style face="normal" font="default" size="100%">Alföldi, Jessica</style></author><author><style face="normal" font="default" size="100%">Francioli, Laurent C</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Lowther, Chelsea</style></author><author><style face="normal" font="default" size="100%">Gauthier, Laura D</style></author><author><style face="normal" font="default" size="100%">Wang, Harold</style></author><author><style face="normal" font="default" size="100%">Watts, Nicholas A</style></author><author><style face="normal" font="default" size="100%">Solomonson, Matthew</style></author><author><style face="normal" font="default" size="100%">O'Donnell-Luria, Anne</style></author><author><style face="normal" font="default" size="100%">Baumann, Alexander</style></author><author><style face="normal" font="default" size="100%">Munshi, Ruchi</style></author><author><style face="normal" font="default" size="100%">Walker, Mark</style></author><author><style face="normal" font="default" size="100%">Whelan, Christopher W</style></author><author><style face="normal" font="default" size="100%">Huang, Yongqing</style></author><author><style face="normal" font="default" size="100%">Brookings, Ted</style></author><author><style face="normal" font="default" size="100%">Sharpe, Ted</style></author><author><style face="normal" font="default" size="100%">Stone, Matthew R</style></author><author><style face="normal" font="default" size="100%">Valkanas, Elise</style></author><author><style face="normal" font="default" size="100%">Fu, Jack</style></author><author><style face="normal" font="default" size="100%">Tiao, Grace</style></author><author><style face="normal" font="default" size="100%">Laricchia, Kristen M</style></author><author><style face="normal" font="default" size="100%">Ruano-Rubio, Valentin</style></author><author><style face="normal" font="default" size="100%">Stevens, Christine</style></author><author><style face="normal" font="default" size="100%">Gupta, Namrata</style></author><author><style face="normal" font="default" size="100%">Cusick, Caroline</style></author><author><style face="normal" font="default" size="100%">Margolin, Lauren</style></author><author><style face="normal" font="default" size="100%">Taylor, Kent D</style></author><author><style face="normal" font="default" size="100%">Lin, Henry J</style></author><author><style face="normal" font="default" size="100%">Rich, Stephen S</style></author><author><style face="normal" font="default" size="100%">Post, Wendy S</style></author><author><style face="normal" font="default" size="100%">Chen, Yii-Der Ida</style></author><author><style face="normal" font="default" size="100%">Rotter, Jerome I</style></author><author><style face="normal" font="default" size="100%">Nusbaum, Chad</style></author><author><style face="normal" font="default" size="100%">Philippakis, Anthony</style></author><author><style face="normal" font="default" size="100%">Lander, Eric</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author><author><style face="normal" font="default" size="100%">Neale, Benjamin M</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Daly, Mark J</style></author><author><style face="normal" font="default" size="100%">Banks, Eric</style></author><author><style face="normal" font="default" size="100%">MacArthur, Daniel G</style></author><author><style face="normal" font="default" size="100%">Talkowski, Michael E</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Genome Aggregation Database Production Team</style></author><author><style face="normal" font="default" size="100%">Genome Aggregation Database Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">A structural variation reference for medical and population genetics.</style></title><secondary-title><style face="normal" font="default" size="100%">Nature</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nature</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Continental Population Groups</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Medical</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetics, Population</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotyping Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Reference Standards</style></keyword><keyword><style  face="normal" font="default" size="100%">Selection, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">581</style></volume><pages><style face="normal" font="default" size="100%">444-451</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Structural variants (SVs) rearrange large segments of DNA and can have profound consequences in evolution and human disease. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral in the interpretation of single-nucleotide variants (SNVs). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings. This SV resource is freely distributed via the gnomAD browser and will have broad utility in population genetics, disease-association studies, and diagnostic screening.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7809</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32461652?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pirruccello, James P</style></author><author><style face="normal" font="default" size="100%">Bick, Alexander</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna G</style></author><author><style face="normal" font="default" size="100%">Choi, Seung Hoan</style></author><author><style face="normal" font="default" size="100%">Lubitz, Steven A</style></author><author><style face="normal" font="default" size="100%">Ho, Carolyn Y</style></author><author><style face="normal" font="default" size="100%">Ng, Kenney</style></author><author><style face="normal" font="default" size="100%">Philippakis, Anthony</style></author><author><style face="normal" font="default" size="100%">Ellinor, Patrick T</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Titin Truncating Variants in Adults Without Known Congestive Heart Failure.</style></title><secondary-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Asymptomatic Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Connectin</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Heart Failure</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 03 17</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">75</style></volume><pages><style face="normal" font="default" size="100%">1239-1241</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32164899?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ferraro, Nicole M</style></author><author><style face="normal" font="default" size="100%">Strober, Benjamin J</style></author><author><style face="normal" font="default" size="100%">Einson, Jonah</style></author><author><style face="normal" font="default" size="100%">Abell, Nathan S</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Barbeira, Alvaro N</style></author><author><style face="normal" font="default" size="100%">Brandt, Margot</style></author><author><style face="normal" font="default" size="100%">Bucan, Maja</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Davis, Joe R</style></author><author><style face="normal" font="default" size="100%">Greenwald, Emily</style></author><author><style face="normal" font="default" size="100%">Hess, Gaelen T</style></author><author><style face="normal" font="default" size="100%">Hilliard, Austin T</style></author><author><style face="normal" font="default" size="100%">Kember, Rachel L</style></author><author><style face="normal" font="default" size="100%">Kotis, Bence</style></author><author><style face="normal" font="default" size="100%">Park, YoSon</style></author><author><style face="normal" font="default" size="100%">Peloso, Gina</style></author><author><style face="normal" font="default" size="100%">Ramdas, Shweta</style></author><author><style face="normal" font="default" size="100%">Scott, Alexandra J</style></author><author><style face="normal" font="default" size="100%">Smail, Craig</style></author><author><style face="normal" font="default" size="100%">Tsang, Emily K</style></author><author><style face="normal" font="default" size="100%">Zekavat, Seyedeh M</style></author><author><style face="normal" font="default" size="100%">Ziosi, Marcello</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Assimes, Themistocles L</style></author><author><style face="normal" font="default" size="100%">Bassik, Michael C</style></author><author><style face="normal" font="default" size="100%">Brown, Christopher D</style></author><author><style face="normal" font="default" size="100%">Correa, Adolfo</style></author><author><style face="normal" font="default" size="100%">Hall, Ira</style></author><author><style face="normal" font="default" size="100%">Im, Hae Kyung</style></author><author><style face="normal" font="default" size="100%">Li, Xin</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Montgomery, Stephen B</style></author><author><style face="normal" font="default" size="100%">Battle, Alexis</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">TOPMed Lipids Working Group</style></author><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcriptomic signatures across human tissues identify functional rare genetic variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Multifactorial Inheritance</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913073?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sajuthi, Satria P</style></author><author><style face="normal" font="default" size="100%">DeFord, Peter</style></author><author><style face="normal" font="default" size="100%">Li, Yingchun</style></author><author><style face="normal" font="default" size="100%">Jackson, Nathan D</style></author><author><style face="normal" font="default" size="100%">Montgomery, Michael T</style></author><author><style face="normal" font="default" size="100%">Everman, Jamie L</style></author><author><style face="normal" font="default" size="100%">Rios, Cydney L</style></author><author><style face="normal" font="default" size="100%">Pruesse, Elmar</style></author><author><style face="normal" font="default" size="100%">Nolin, James D</style></author><author><style face="normal" font="default" size="100%">Plender, Elizabeth G</style></author><author><style face="normal" font="default" size="100%">Wechsler, Michael E</style></author><author><style face="normal" font="default" size="100%">Mak, Angel C Y</style></author><author><style face="normal" font="default" size="100%">Eng, Celeste</style></author><author><style face="normal" font="default" size="100%">Salazar, Sandra</style></author><author><style face="normal" font="default" size="100%">Medina, Vivian</style></author><author><style face="normal" font="default" size="100%">Wohlford, Eric M</style></author><author><style face="normal" font="default" size="100%">Huntsman, Scott</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Germer, Soren</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Abecasis, Gonçalo</style></author><author><style face="normal" font="default" size="100%">Kang, Hyun Min</style></author><author><style face="normal" font="default" size="100%">Rice, Kenneth M</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajesh</style></author><author><style face="normal" font="default" size="100%">Oh, Sam</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Santana, Jose</style></author><author><style face="normal" font="default" size="100%">Burchard, Esteban G</style></author><author><style face="normal" font="default" size="100%">Seibold, Max A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Type 2 and interferon inflammation regulate SARS-CoV-2 entry factor expression in the airway epithelium.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Angiotensin-Converting Enzyme 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Betacoronavirus</style></keyword><keyword><style  face="normal" font="default" size="100%">Child</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronavirus Infections</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Epithelial Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Host-Pathogen Interactions</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Inflammation</style></keyword><keyword><style  face="normal" font="default" size="100%">Interferons</style></keyword><keyword><style  face="normal" font="default" size="100%">Interleukin-13</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Nasal Mucosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Pandemics</style></keyword><keyword><style  face="normal" font="default" size="100%">Peptidyl-Dipeptidase A</style></keyword><keyword><style  face="normal" font="default" size="100%">Pneumonia, Viral</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Serine Endopeptidases</style></keyword><keyword><style  face="normal" font="default" size="100%">Virus Internalization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 10 12</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">5139</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2, an emerging virus that utilizes host proteins ACE2 and TMPRSS2 as entry factors. Understanding the factors affecting the pattern and levels of expression of these genes is important for deeper understanding of SARS-CoV-2 tropism and pathogenesis. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci for both ACE2 and TMPRSS2, that vary in frequency across world populations. We find TMPRSS2 is part of a mucus secretory network, highly upregulated by type 2 (T2) inflammation through the action of interleukin-13, and that the interferon response to respiratory viruses highly upregulates ACE2 expression. IL-13 and virus infection mediated effects on ACE2 expression were also observed at the protein level in the airway epithelium. Finally, we define airway responses to common coronavirus infections in children, finding that these infections generate host responses similar to other viral species, including upregulation of IL6 and ACE2. Our results reveal possible mechanisms influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33046696?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sajuthi, Satria P</style></author><author><style face="normal" font="default" size="100%">DeFord, Peter</style></author><author><style face="normal" font="default" size="100%">Jackson, Nathan D</style></author><author><style face="normal" font="default" size="100%">Montgomery, Michael T</style></author><author><style face="normal" font="default" size="100%">Everman, Jamie L</style></author><author><style face="normal" font="default" size="100%">Rios, Cydney L</style></author><author><style face="normal" font="default" size="100%">Pruesse, Elmar</style></author><author><style face="normal" font="default" size="100%">Nolin, James D</style></author><author><style face="normal" font="default" size="100%">Plender, Elizabeth G</style></author><author><style face="normal" font="default" size="100%">Wechsler, Michael E</style></author><author><style face="normal" font="default" size="100%">Mak, Angel Cy</style></author><author><style face="normal" font="default" size="100%">Eng, Celeste</style></author><author><style face="normal" font="default" size="100%">Salazar, Sandra</style></author><author><style face="normal" font="default" size="100%">Medina, Vivian</style></author><author><style face="normal" font="default" size="100%">Wohlford, Eric M</style></author><author><style face="normal" font="default" size="100%">Huntsman, Scott</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Germer, Soren</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Abecasis, Gonçalo</style></author><author><style face="normal" font="default" size="100%">Kang, Hyun Min</style></author><author><style face="normal" font="default" size="100%">Rice, Kenneth M</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajesh</style></author><author><style face="normal" font="default" size="100%">Oh, Sam</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Santana, Jose</style></author><author><style face="normal" font="default" size="100%">Burchard, Esteban G</style></author><author><style face="normal" font="default" size="100%">Seibold, Max A</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium.</style></title><secondary-title><style face="normal" font="default" size="100%">bioRxiv</style></secondary-title><alt-title><style face="normal" font="default" size="100%">bioRxiv</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 Apr 10</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Coronavirus disease 2019 (COVID-19) outcomes vary from asymptomatic infection to death. This disparity may reflect different airway levels of the SARS-CoV-2 receptor, ACE2, and the spike protein activator, TMPRSS2. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci (eQTL) for both  and , that vary in frequency across world populations. Importantly, we find  is part of a mucus secretory network, highly upregulated by T2 inflammation through the action of interleukin-13, and that interferon response to respiratory viruses highly upregulates  expression. Finally, we define airway responses to coronavirus infections in children, finding that these infections upregulate  while also stimulating a more pronounced cytotoxic immune response relative to other respiratory viruses. Our results reveal mechanisms likely influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.&lt;/p&gt;</style></abstract><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32511326?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wang, Minxian</style></author><author><style face="normal" font="default" size="100%">Menon, Ramesh</style></author><author><style face="normal" font="default" size="100%">Mishra, Sanghamitra</style></author><author><style face="normal" font="default" size="100%">Patel, Aniruddh P</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Tanneeru, Deepak</style></author><author><style face="normal" font="default" size="100%">Deshmukh, Manjari</style></author><author><style face="normal" font="default" size="100%">Mathew, Oshin</style></author><author><style face="normal" font="default" size="100%">Apte, Sanika</style></author><author><style face="normal" font="default" size="100%">Devanboo, Christina S</style></author><author><style face="normal" font="default" size="100%">Sundaram, Sumathi</style></author><author><style face="normal" font="default" size="100%">Lakshmipathy, Praveena</style></author><author><style face="normal" font="default" size="100%">Murugan, Sakthivel</style></author><author><style face="normal" font="default" size="100%">Sharma, Krishna Kumar</style></author><author><style face="normal" font="default" size="100%">Rajendran, Karthikeyan</style></author><author><style face="normal" font="default" size="100%">Santhosh, Sam</style></author><author><style face="normal" font="default" size="100%">Thachathodiyl, Rajesh</style></author><author><style face="normal" font="default" size="100%">Ahamed, Hisham</style></author><author><style face="normal" font="default" size="100%">Balegadde, Aniketh Vijay</style></author><author><style face="normal" font="default" size="100%">Alexander, Thomas</style></author><author><style face="normal" font="default" size="100%">Swaminathan, Krishnan</style></author><author><style face="normal" font="default" size="100%">Gupta, Rajeev</style></author><author><style face="normal" font="default" size="100%">Mullasari, Ajit S</style></author><author><style face="normal" font="default" size="100%">Sigamani, Alben</style></author><author><style face="normal" font="default" size="100%">Kanchi, Muralidhar</style></author><author><style face="normal" font="default" size="100%">Peterson, Andrew S</style></author><author><style face="normal" font="default" size="100%">Butterworth, Adam S</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Di Angelantonio, Emanuele</style></author><author><style face="normal" font="default" size="100%">Naheed, Aliya</style></author><author><style face="normal" font="default" size="100%">Inouye, Michael</style></author><author><style face="normal" font="default" size="100%">Chowdhury, Rajiv</style></author><author><style face="normal" font="default" size="100%">Vedam, Ramprasad L</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Gupta, Ravi</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians.</style></title><secondary-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Bangladesh</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Artery Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">India</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Multifactorial Inheritance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 08 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">76</style></volume><pages><style face="normal" font="default" size="100%">703-714</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;This analysis used summary statistics from a prior genome-wide association study to derive a new GPS for South Asians.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;This GPS was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPS reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPS reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The GPS, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p &lt; 0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p &lt; 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPS distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p &lt; 0.05 for each).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;The new GPS has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32762905?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">A vast resource of allelic expression data spanning human tissues.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Biol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">234</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32912332?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Flex, Elisabetta</style></author><author><style face="normal" font="default" size="100%">Martinelli, Simone</style></author><author><style face="normal" font="default" size="100%">Van Dijck, Anke</style></author><author><style face="normal" font="default" size="100%">Ciolfi, Andrea</style></author><author><style face="normal" font="default" size="100%">Cecchetti, Serena</style></author><author><style face="normal" font="default" size="100%">Coluzzi, Elisa</style></author><author><style face="normal" font="default" size="100%">Pannone, Luca</style></author><author><style face="normal" font="default" size="100%">Andreoli, Cristina</style></author><author><style face="normal" font="default" size="100%">Radio, Francesca Clementina</style></author><author><style face="normal" font="default" size="100%">Pizzi, Simone</style></author><author><style face="normal" font="default" size="100%">Carpentieri, Giovanna</style></author><author><style face="normal" font="default" size="100%">Bruselles, Alessandro</style></author><author><style face="normal" font="default" size="100%">Catanzaro, Giuseppina</style></author><author><style face="normal" font="default" size="100%">Pedace, Lucia</style></author><author><style face="normal" font="default" size="100%">Miele, Evelina</style></author><author><style face="normal" font="default" size="100%">Carcarino, Elena</style></author><author><style face="normal" font="default" size="100%">Ge, Xiaoyan</style></author><author><style face="normal" font="default" size="100%">Chijiwa, Chieko</style></author><author><style face="normal" font="default" size="100%">Lewis, M E Suzanne</style></author><author><style face="normal" font="default" size="100%">Meuwissen, Marije</style></author><author><style face="normal" font="default" size="100%">Kenis, Sandra</style></author><author><style face="normal" font="default" size="100%">Van der Aa, Nathalie</style></author><author><style face="normal" font="default" size="100%">Larson, Austin</style></author><author><style face="normal" font="default" size="100%">Brown, Kathleen</style></author><author><style face="normal" font="default" size="100%">Wasserstein, Melissa P</style></author><author><style face="normal" font="default" size="100%">Skotko, Brian G</style></author><author><style face="normal" font="default" size="100%">Begtrup, Amber</style></author><author><style face="normal" font="default" size="100%">Person, Richard</style></author><author><style face="normal" font="default" size="100%">Karayiorgou, Maria</style></author><author><style face="normal" font="default" size="100%">Roos, J Louw</style></author><author><style face="normal" font="default" size="100%">Van Gassen, Koen L</style></author><author><style face="normal" font="default" size="100%">Koopmans, Marije</style></author><author><style face="normal" font="default" size="100%">Bijlsma, Emilia K</style></author><author><style face="normal" font="default" size="100%">Santen, Gijs W E</style></author><author><style face="normal" font="default" size="100%">Barge-Schaapveld, Daniela Q C M</style></author><author><style face="normal" font="default" size="100%">Ruivenkamp, Claudia A L</style></author><author><style face="normal" font="default" size="100%">Hoffer, Mariette J V</style></author><author><style face="normal" font="default" size="100%">Lalani, Seema R</style></author><author><style face="normal" font="default" size="100%">Streff, Haley</style></author><author><style face="normal" font="default" size="100%">Craigen, William J</style></author><author><style face="normal" font="default" size="100%">Graham, Brett H</style></author><author><style face="normal" font="default" size="100%">van den Elzen, Annette P M</style></author><author><style face="normal" font="default" size="100%">Kamphuis, Daan J</style></author><author><style face="normal" font="default" size="100%">Õunap, Katrin</style></author><author><style face="normal" font="default" size="100%">Reinson, Karit</style></author><author><style face="normal" font="default" size="100%">Pajusalu, Sander</style></author><author><style face="normal" font="default" size="100%">Wojcik, Monica H</style></author><author><style face="normal" font="default" size="100%">Viberti, Clara</style></author><author><style face="normal" font="default" size="100%">Di Gaetano, Cornelia</style></author><author><style face="normal" font="default" size="100%">Bertini, Enrico</style></author><author><style face="normal" font="default" size="100%">Petrucci, Simona</style></author><author><style face="normal" font="default" size="100%">De Luca, Alessandro</style></author><author><style face="normal" font="default" size="100%">Rota, Rossella</style></author><author><style face="normal" font="default" size="100%">Ferretti, Elisabetta</style></author><author><style face="normal" font="default" size="100%">Matullo, Giuseppe</style></author><author><style face="normal" font="default" size="100%">Dallapiccola, Bruno</style></author><author><style face="normal" font="default" size="100%">Sgura, Antonella</style></author><author><style face="normal" font="default" size="100%">Walkiewicz, Magdalena</style></author><author><style face="normal" font="default" size="100%">Kooy, R Frank</style></author><author><style face="normal" font="default" size="100%">Tartaglia, Marco</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Aberrant Function of the C-Terminal Tail of HIST1H1E Accelerates Cellular Senescence and Causes Premature Aging.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am. J. Hum. Genet.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Sep 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">105</style></volume><pages><style face="normal" font="default" size="100%">493-508</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Histones mediate dynamic packaging of nuclear DNA in chromatin, a process that is precisely controlled to guarantee efficient compaction of the genome and proper chromosomal segregation during cell division and to accomplish DNA replication, transcription, and repair. Due to the important structural and regulatory roles played by histones, it is not surprising that histone functional dysregulation or aberrant levels of histones can have severe consequences for multiple cellular processes and ultimately might affect development or contribute to cell transformation. Recently, germline frameshift mutations involving the C-terminal tail of HIST1H1E, which is a widely expressed member of the linker histone family and facilitates higher-order chromatin folding, have been causally linked to an as-yet poorly defined syndrome that includes intellectual disability. We report that these mutations result in stable proteins that reside in the nucleus, bind to chromatin, disrupt proper compaction of DNA, and are associated with a specific methylation pattern. Cells expressing these mutant proteins have a dramatically reduced proliferation rate and competence, hardly enter into the S phase, and undergo accelerated senescence. Remarkably, clinical assessment of a relatively large cohort of subjects sharing these mutations revealed a premature aging phenotype as a previously unrecognized feature of the disorder. Our findings identify a direct link between aberrant chromatin remodeling, cellular senescence, and accelerated aging.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31447100?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wenger, Aaron M</style></author><author><style face="normal" font="default" size="100%">Peluso, Paul</style></author><author><style face="normal" font="default" size="100%">Rowell, William J</style></author><author><style face="normal" font="default" size="100%">Chang, Pi-Chuan</style></author><author><style face="normal" font="default" size="100%">Hall, Richard J</style></author><author><style face="normal" font="default" size="100%">Concepcion, Gregory T</style></author><author><style face="normal" font="default" size="100%">Ebler, Jana</style></author><author><style face="normal" font="default" size="100%">Fungtammasan, Arkarachai</style></author><author><style face="normal" font="default" size="100%">Kolesnikov, Alexey</style></author><author><style face="normal" font="default" size="100%">Olson, Nathan D</style></author><author><style face="normal" font="default" size="100%">Töpfer, Armin</style></author><author><style face="normal" font="default" size="100%">Alonge, Michael</style></author><author><style face="normal" font="default" size="100%">Mahmoud, Medhat</style></author><author><style face="normal" font="default" size="100%">Qian, Yufeng</style></author><author><style face="normal" font="default" size="100%">Chin, Chen-Shan</style></author><author><style face="normal" font="default" size="100%">Phillippy, Adam M</style></author><author><style face="normal" font="default" size="100%">Schatz, Michael C</style></author><author><style face="normal" font="default" size="100%">Myers, Gene</style></author><author><style face="normal" font="default" size="100%">DePristo, Mark A</style></author><author><style face="normal" font="default" size="100%">Ruan, Jue</style></author><author><style face="normal" font="default" size="100%">Marschall, Tobias</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Zook, Justin M</style></author><author><style face="normal" font="default" size="100%">Li, Heng</style></author><author><style face="normal" font="default" size="100%">Koren, Sergey</style></author><author><style face="normal" font="default" size="100%">Carroll, Andrew</style></author><author><style face="normal" font="default" size="100%">Rank, David R</style></author><author><style face="normal" font="default" size="100%">Hunkapiller, Michael W</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Biotechnol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat. Biotechnol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">37</style></volume><pages><style face="normal" font="default" size="100%">1155-1162</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions &lt;50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the 'genome in a bottle' (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of &gt;15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31406327?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Karaca, Ender</style></author><author><style face="normal" font="default" size="100%">Posey, Jennifer E</style></author><author><style face="normal" font="default" size="100%">Bostwick, Bret</style></author><author><style face="normal" font="default" size="100%">Liu, Pengfei</style></author><author><style face="normal" font="default" size="100%">Gezdirici, Alper</style></author><author><style face="normal" font="default" size="100%">Yesil, Gozde</style></author><author><style face="normal" font="default" size="100%">Coban Akdemir, Zeynep</style></author><author><style face="normal" font="default" size="100%">Bayram, Yavuz</style></author><author><style face="normal" font="default" size="100%">Harms, Frederike L</style></author><author><style face="normal" font="default" size="100%">Meinecke, Peter</style></author><author><style face="normal" font="default" size="100%">Alawi, Malik</style></author><author><style face="normal" font="default" size="100%">Bacino, Carlos A</style></author><author><style face="normal" font="default" size="100%">Sutton, V Reid</style></author><author><style face="normal" font="default" size="100%">Kortüm, Fanny</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Biallelic and De Novo Variants in DONSON Reveal a Clinical Spectrum of Cell Cycle-opathies with Microcephaly, Dwarfism and Skeletal Abnormalities.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Med Genet A</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am. J. Med. Genet. A</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">179</style></volume><pages><style face="normal" font="default" size="100%">2056-2066</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Co-occurrence of primordial dwarfism and microcephaly together with particular skeletal findings are seen in a wide range of Mendelian syndromes including microcephaly micromelia syndrome (MMS, OMIM 251230), microcephaly, short stature, and limb abnormalities (MISSLA, OMIM 617604), and microcephalic primordial dwarfisms (MPDs). Genes associated with these syndromes encode proteins that have crucial roles in DNA replication or in other critical steps of the cell cycle that link DNA replication to cell division. We identified four unrelated families with five affected individuals having biallelic or de novo variants in DONSON presenting with a core phenotype of severe short stature (z score &lt; -3 SD), additional skeletal abnormalities, and microcephaly. Two apparently unrelated families with identical homozygous c.631C &gt; T p.(Arg211Cys) variant had clinical features typical of Meier-Gorlin syndrome (MGS), while two siblings with compound heterozygous c.346delG p.(Asp116Ile*62) and c.1349A &gt; G p.(Lys450Arg) variants presented with Seckel-like phenotype. We also identified a de novo c.683G &gt; T p.(Trp228Leu) variant in DONSON in a patient with prominent micrognathia, short stature and hypoplastic femur and tibia, clinically diagnosed with Femoral-Facial syndrome (FFS, OMIM 134780). Biallelic variants in DONSON have been recently described in individuals with microcephalic dwarfism. These studies also demonstrated that DONSON has an essential conserved role in the cell cycle. Here we describe novel biallelic and de novo variants that are associated with MGS, Seckel-like phenotype and FFS, the last of which has not been associated with any disease gene to date.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31407851?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Punetha, Jaya</style></author><author><style face="normal" font="default" size="100%">Karaca, Ender</style></author><author><style face="normal" font="default" size="100%">Gezdirici, Alper</style></author><author><style face="normal" font="default" size="100%">Lamont, Ryan E</style></author><author><style face="normal" font="default" size="100%">Pehlivan, Davut</style></author><author><style face="normal" font="default" size="100%">Marafi, Dana</style></author><author><style face="normal" font="default" size="100%">Appendino, Juan P</style></author><author><style face="normal" font="default" size="100%">Hunter, Jill V</style></author><author><style face="normal" font="default" size="100%">Akdemir, Zeynep C</style></author><author><style face="normal" font="default" size="100%">Fatih, Jawid M</style></author><author><style face="normal" font="default" size="100%">Jhangiani, Shalini N</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Innes, A Micheil</style></author><author><style face="normal" font="default" size="100%">Posey, Jennifer E</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Biallelic CACNA2D2 variants in epileptic encephalopathy and cerebellar atrophy.</style></title><secondary-title><style face="normal" font="default" size="100%">Ann Clin Transl Neurol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Ann Clin Transl Neurol</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">1395-1406</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;OBJECTIVE: &lt;/b&gt;To characterize the molecular and clinical phenotypic basis of developmental and epileptic encephalopathies caused by rare biallelic variants in CACNA2D2.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Two affected individuals from a family with clinical features of early onset epileptic encephalopathy were recruited for exome sequencing at the Centers for Mendelian Genomics to identify their molecular diagnosis. GeneMatcher facilitated identification of a second family with a shared candidate disease gene identified through clinical gene panel-based testing.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Rare biallelic CACNA2D2 variants have been previously reported in three families with developmental and epileptic encephalopathy, and one family with congenital ataxia. We identified three individuals in two unrelated families with novel homozygous rare variants in CACNA2D2 with clinical features of developmental and epileptic encephalopathy and cerebellar atrophy. Family 1 includes two affected siblings with a likely damaging homozygous rare missense variant c.1778G&gt;C; p.(Arg593Pro) in CACNA2D2. Family 2 includes a proband with a homozygous rare nonsense variant c.485_486del; p.(Tyr162Ter) in CACNA2D2. We compared clinical and molecular findings from all nine individuals reported to date and note that cerebellar atrophy is shared among all.&lt;/p&gt;&lt;p&gt;&lt;b&gt;INTERPRETATION: &lt;/b&gt;Our study supports the candidacy of CACNA2D2 as a disease gene associated with a phenotypic spectrum of neurological disease that include features of developmental and epileptic encephalopathy, ataxia, and cerebellar atrophy. Age at presentation may affect apparent penetrance of neurogenetic trait manifestations and of a particular clinical neurological endophenotype, for example, seizures or ataxia.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31402629?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Leija-Salazar, Melissa</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Toffoli, Marco</style></author><author><style face="normal" font="default" size="100%">Mullin, Stephen</style></author><author><style face="normal" font="default" size="100%">Mokretar, Katya</style></author><author><style face="normal" font="default" size="100%">Athanasopoulou, Maria</style></author><author><style face="normal" font="default" size="100%">Donald, Aimee</style></author><author><style face="normal" font="default" size="100%">Sharma, Reena</style></author><author><style face="normal" font="default" size="100%">Hughes, Derralynn</style></author><author><style face="normal" font="default" size="100%">Schapira, Anthony H V</style></author><author><style face="normal" font="default" size="100%">Proukakis, Christos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluation of the detection of GBA missense mutations and other variants using the Oxford Nanopore MinION.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Genet Genomic Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol Genet Genomic Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 03</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">e564</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Mutations in GBA cause Gaucher disease when biallelic and are strong risk factors for Parkinson's disease when heterozygous. GBA analysis is complicated by the nearby pseudogene. We aimed to design and validate a method for sequencing GBA using long reads.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We sequenced GBA on the Oxford Nanopore MinION as an 8.9 kb amplicon from 102 individuals, including patients with Parkinson's and Gaucher diseases. We used NanoOK for quality metrics, NGMLR to align data (after comparing with GraphMap), Nanopolish and Sniffles to call variants, and WhatsHap for phasing.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We detected all known missense mutations in these samples, including the common p.N409S (N370S) and p.L483P (L444P) in multiple samples, and nine rarer ones, as well as a splicing and a truncating mutation, and intronic SNPs. We demonstrated the ability to phase mutations, confirm compound heterozygosity, and assign haplotypes. We also detected two known risk variants in some Parkinson's patients. Rare false positives were easily identified and filtered, with the Nanopolish quality score adjusted for the number of reads a very robust discriminator. In two individuals carrying a recombinant allele, we were able to detect and fully define it in one carrier, where it included a 55-base pair deletion, but not in another one, suggesting a limitation of the PCR enrichment method. Missense mutations were detected at the correct zygosity, except for the case where the RecNciI one was missed.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSION: &lt;/b&gt;The Oxford Nanopore MinION can detect missense mutations and an exonic deletion in this difficult gene, with the added advantages of phasing and intronic analysis. It can be used as an efficient research tool, but additional work is required to exclude all recombinants.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30637984?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Li, Alexander H</style></author><author><style face="normal" font="default" size="100%">Hanchard, Neil A</style></author><author><style face="normal" font="default" size="100%">Azamian, Mahshid</style></author><author><style face="normal" font="default" size="100%">D'Alessandro, Lisa C A</style></author><author><style face="normal" font="default" size="100%">Coban-Akdemir, Zeynep</style></author><author><style face="normal" font="default" size="100%">Lopez, Keila N</style></author><author><style face="normal" font="default" size="100%">Hall, Nancy J</style></author><author><style face="normal" font="default" size="100%">Dickerson, Heather</style></author><author><style face="normal" font="default" size="100%">Nicosia, Annarita</style></author><author><style face="normal" font="default" size="100%">Fernbach, Susan</style></author><author><style face="normal" font="default" size="100%">Boone, Philip M</style></author><author><style face="normal" font="default" size="100%">Gambin, Tomaz</style></author><author><style face="normal" font="default" size="100%">Karaca, Ender</style></author><author><style face="normal" font="default" size="100%">Gu, Shen</style></author><author><style face="normal" font="default" size="100%">Yuan, Bo</style></author><author><style face="normal" font="default" size="100%">Jhangiani, Shalini N</style></author><author><style face="normal" font="default" size="100%">Doddapaneni, HarshaVardhan</style></author><author><style face="normal" font="default" size="100%">Hu, Jianhong</style></author><author><style face="normal" font="default" size="100%">Dinh, Huyen</style></author><author><style face="normal" font="default" size="100%">Jayaseelan, Joy</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna</style></author><author><style face="normal" font="default" size="100%">Lalani, Seema</style></author><author><style face="normal" font="default" size="100%">Towbin, Jeffrey</style></author><author><style face="normal" font="default" size="100%">Penny, Daniel</style></author><author><style face="normal" font="default" size="100%">Fraser, Charles</style></author><author><style face="normal" font="default" size="100%">Martin, James</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Ware, Stephanie M</style></author><author><style face="normal" font="default" size="100%">Belmont, John W</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic architecture of laterality defects revealed by whole exome sequencing.</style></title><secondary-title><style face="normal" font="default" size="100%">Eur J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Eur. J. Hum. Genet.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">563-573</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Aberrant left-right patterning in the developing human embryo can lead to a broad spectrum of congenital malformations. The causes of most laterality defects are not known, with variants in established genes accounting for &lt;20% of cases. We sought to characterize the genetic spectrum of these conditions by performing whole-exome sequencing of 323 unrelated laterality cases. We investigated the role of rare, predicted-damaging variation in 1726 putative laterality candidate genes derived from model organisms, pathway analyses, and human phenotypes. We also evaluated the contribution of homo/hemizygous exon deletions and gene-based burden of rare variation. A total of 28 candidate variants (26 rare predicted-damaging variants and 2 hemizygous deletions) were identified, including variants in genes known to cause heterotaxy and primary ciliary dyskinesia (ACVR2B, NODAL, ZIC3, DNAI1, DNAH5, HYDIN, MMP21), and genes without a human phenotype association, but with prior evidence for a role in embryonic laterality or cardiac development. Sanger validation of the latter variants in probands and their parents revealed no de novo variants, but apparent transmitted heterozygous (ROCK2, ISL1, SMAD2), and hemizygous (RAI2, RIPPLY1) variant patterns. Collectively, these variants account for 7.1% of our study subjects. We also observe evidence for an excess burden of rare, predicted loss-of-function variation in PXDNL and BMS1- two genes relevant to the broader laterality phenotype. These findings highlight potential new genes in the development of laterality defects, and suggest extensive locus heterogeneity and complex genetic models in this class of birth defects.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30622330?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dennenmoser, Stefan</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Schatz, Michael C</style></author><author><style face="normal" font="default" size="100%">Altmüller, Janine</style></author><author><style face="normal" font="default" size="100%">Zytnicki, Matthias</style></author><author><style face="normal" font="default" size="100%">Nolte, Arne W</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide patterns of transposon proliferation in an evolutionary young hybrid fish.</style></title><secondary-title><style face="normal" font="default" size="100%">Mol Ecol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Mol. Ecol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Mar</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">1491-1505</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Hybridization can induce transposons to jump into new genomic positions, which may result in their accumulation across the genome. Alternatively, transposon copy numbers may increase through nonallelic (ectopic) homologous recombination in highly repetitive regions of the genome. The relative contribution of transposition bursts versus recombination-based mechanisms to evolutionary processes remains unclear because studies on transposon dynamics in natural systems are rare. We assessed the genomewide distribution of transposon insertions in a young hybrid lineage (&quot;invasive Cottus&quot;, n = 11) and its parental species Cottus rhenanus (n = 17) and Cottus perifretum(n = 9) using a reference genome assembled from long single molecule pacbio reads. An inventory of transposable elements was reconstructed from the same data and annotated. Transposon copy numbers in the hybrid lineage increased in 120 (15.9%) out of 757 transposons studied here. The copy number increased on average by 69% (range: 10%-197%). Given the age of the hybrid lineage, this suggests that they have proliferated within a few hundred generations since admixture began. However, frequency spectra of transposon insertions revealed no increase in novel and rare insertions across assembled parts of the genome. This implies that transposons were added to repetitive regions of the genome that remain difficult to assemble. Future studies will need to evaluate whether recombination-based mechanisms rather than genomewide transposition may explain the majority of the recent transposon proliferation in the hybrid lineage. Irrespectively of the underlying mechanism, the observed overabundance in repetitive parts of the genome suggests that gene-rich regions are unlikely to be directly affected.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30520198?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Leasure, Audrey C</style></author><author><style face="normal" font="default" size="100%">Sheth, Kevin N</style></author><author><style face="normal" font="default" size="100%">Comeau, Mary</style></author><author><style face="normal" font="default" size="100%">Aldridge, Chad</style></author><author><style face="normal" font="default" size="100%">Worrall, Bradford B</style></author><author><style face="normal" font="default" size="100%">Vashkevich, Anastasia</style></author><author><style face="normal" font="default" size="100%">Rosand, Jonathan</style></author><author><style face="normal" font="default" size="100%">Langefeld, Carl</style></author><author><style face="normal" font="default" size="100%">Moomaw, Charles J</style></author><author><style face="normal" font="default" size="100%">Woo, Daniel</style></author><author><style face="normal" font="default" size="100%">Falcone, Guido J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Identification and Validation of Hematoma Volume Cutoffs in Spontaneous, Supratentorial Deep Intracerebral Hemorrhage.</style></title><secondary-title><style face="normal" font="default" size="100%">Stroke</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Stroke</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">2044-2049</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Background and Purpose- Clinical trials in spontaneous intracerebral hemorrhage (ICH) have used volume cutoffs as inclusion criteria to select populations in which the effects of interventions are likely to be the greatest. However, optimal volume cutoffs for predicting poor outcome in deep locations (thalamus versus basal ganglia) are unknown. Methods- We conducted a 2-phase study to determine ICH volume cutoffs for poor outcome (modified Rankin Scale score of 4-6) in the thalamus and basal ganglia. Cutoffs with optimal sensitivity and specificity for poor outcome were identified in the ERICH ([Ethnic/Racial Variations of ICH] study; derivation cohort) using receiver operating characteristic curves. The cutoffs were then validated in the ATACH-2 trial (Antihypertensive Treatment of Acute Cerebral Hemorrhage-2) by comparing the c-statistic of regression models for outcome (including dichotomized volume) in the validation cohort. Results- Of the 3000 patients enrolled in ERICH, 1564 (52%) had deep ICH, of whom 1305 (84%) had complete neuroimaging and outcome data (660 thalamic and 645 basal ganglia hemorrhages). Receiver operating characteristic curve analysis identified 8 mL in thalamic (area under the curve, 0.79; sensitivity, 73%; specificity, 78%) and 18 mL in basal ganglia ICH (area under the curve, 0.79; sensitivity, 70%; specificity, 83%) as optimal cutoffs for predicting poor outcome. The validation cohort included 834 (84%) patients with deep ICH and complete neuroimaging data enrolled in ATACH-2 (353 thalamic and 431 basal ganglia hemorrhages). In thalamic ICH, the c-statistic of the multivariable outcome model including dichotomized ICH volume was 0.80 (95% CI, 0.75-0.85) in the validation cohort. For basal ganglia ICH, the c-statistic was 0.81 (95% CI, 0.76-0.85) in the validation cohort. Conclusions- Optimal hematoma volume cutoffs for predicting poor outcome in deep ICH vary by the specific deep brain nucleus involved. Utilization of location-specific volume cutoffs may improve clinical trial design by targeting deep ICH patients that will obtain maximal benefit from candidate therapies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31238829?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Posey, Jennifer E</style></author><author><style face="normal" font="default" size="100%">O'Donnell-Luria, Anne H</style></author><author><style face="normal" font="default" size="100%">Chong, Jessica X</style></author><author><style face="normal" font="default" size="100%">Harel, Tamar</style></author><author><style face="normal" font="default" size="100%">Jhangiani, Shalini N</style></author><author><style face="normal" font="default" size="100%">Coban Akdemir, Zeynep H</style></author><author><style face="normal" font="default" size="100%">Buyske, Steven</style></author><author><style face="normal" font="default" size="100%">Pehlivan, Davut</style></author><author><style face="normal" font="default" size="100%">Carvalho, Claudia M B</style></author><author><style face="normal" font="default" size="100%">Baxter, Samantha</style></author><author><style face="normal" font="default" size="100%">Sobreira, Nara</style></author><author><style face="normal" font="default" size="100%">Liu, Pengfei</style></author><author><style face="normal" font="default" size="100%">Wu, Nan</style></author><author><style face="normal" font="default" size="100%">Rosenfeld, Jill A</style></author><author><style face="normal" font="default" size="100%">Kumar, Sushant</style></author><author><style face="normal" font="default" size="100%">Avramopoulos, Dimitri</style></author><author><style face="normal" font="default" size="100%">White, Janson J</style></author><author><style face="normal" font="default" size="100%">Doheny, Kimberly F</style></author><author><style face="normal" font="default" size="100%">Witmer, P Dane</style></author><author><style face="normal" font="default" size="100%">Boehm, Corinne</style></author><author><style face="normal" font="default" size="100%">Sutton, V Reid</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Günel, Murat</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Mane, Shrikant</style></author><author><style face="normal" font="default" size="100%">MacArthur, Daniel G</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Hamosh, Ada</style></author><author><style face="normal" font="default" size="100%">Lifton, Richard P</style></author><author><style face="normal" font="default" size="100%">Matise, Tara C</style></author><author><style face="normal" font="default" size="100%">Rehm, Heidi L</style></author><author><style face="normal" font="default" size="100%">Gerstein, Mark</style></author><author><style face="normal" font="default" size="100%">Bamshad, Michael J</style></author><author><style face="normal" font="default" size="100%">Valle, David</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Centers for Mendelian Genomics</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Insights into genetics, human biology and disease gleaned from family based genomic studies.</style></title><secondary-title><style face="normal" font="default" size="100%">Genet Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genet. Med.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 04</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><pages><style face="normal" font="default" size="100%">798-812</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of &gt;75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel &quot;disease gene&quot; discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30655598?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Connaughton, Dervla M</style></author><author><style face="normal" font="default" size="100%">Kennedy, Claire</style></author><author><style face="normal" font="default" size="100%">Shril, Shirlee</style></author><author><style face="normal" font="default" size="100%">Mann, Nina</style></author><author><style face="normal" font="default" size="100%">Murray, Susan L</style></author><author><style face="normal" font="default" size="100%">Williams, Patrick A</style></author><author><style face="normal" font="default" size="100%">Conlon, Eoin</style></author><author><style face="normal" font="default" size="100%">Nakayama, Makiko</style></author><author><style face="normal" font="default" size="100%">van der Ven, Amelie T</style></author><author><style face="normal" font="default" size="100%">Ityel, Hadas</style></author><author><style face="normal" font="default" size="100%">Kause, Franziska</style></author><author><style face="normal" font="default" size="100%">Kolvenbach, Caroline M</style></author><author><style face="normal" font="default" size="100%">Dai, Rufeng</style></author><author><style face="normal" font="default" size="100%">Vivante, Asaf</style></author><author><style face="normal" font="default" size="100%">Braun, Daniela A</style></author><author><style face="normal" font="default" size="100%">Schneider, Ronen</style></author><author><style face="normal" font="default" size="100%">Kitzler, Thomas M</style></author><author><style face="normal" font="default" size="100%">Moloney, Brona</style></author><author><style face="normal" font="default" size="100%">Moran, Conor P</style></author><author><style face="normal" font="default" size="100%">Smyth, John S</style></author><author><style face="normal" font="default" size="100%">Kennedy, Alan</style></author><author><style face="normal" font="default" size="100%">Benson, Katherine</style></author><author><style face="normal" font="default" size="100%">Stapleton, Caragh</style></author><author><style face="normal" font="default" size="100%">Denton, Mark</style></author><author><style face="normal" font="default" size="100%">Magee, Colm</style></author><author><style face="normal" font="default" size="100%">O'Seaghdha, Conall M</style></author><author><style face="normal" font="default" size="100%">Plant, William D</style></author><author><style face="normal" font="default" size="100%">Griffin, Matthew D</style></author><author><style face="normal" font="default" size="100%">Awan, Atif</style></author><author><style face="normal" font="default" size="100%">Sweeney, Clodagh</style></author><author><style face="normal" font="default" size="100%">Mane, Shrikant M</style></author><author><style face="normal" font="default" size="100%">Lifton, Richard P</style></author><author><style face="normal" font="default" size="100%">Griffin, Brenda</style></author><author><style face="normal" font="default" size="100%">Leavey, Sean</style></author><author><style face="normal" font="default" size="100%">Casserly, Liam</style></author><author><style face="normal" font="default" size="100%">de Freitas, Declan G</style></author><author><style face="normal" font="default" size="100%">Holian, John</style></author><author><style face="normal" font="default" size="100%">Dorman, Anthony</style></author><author><style face="normal" font="default" size="100%">Doyle, Brendan</style></author><author><style face="normal" font="default" size="100%">Lavin, Peter J</style></author><author><style face="normal" font="default" size="100%">Little, Mark A</style></author><author><style face="normal" font="default" size="100%">Conlon, Peter J</style></author><author><style face="normal" font="default" size="100%">Hildebrandt, Friedhelm</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Monogenic causes of chronic kidney disease in adults.</style></title><secondary-title><style face="normal" font="default" size="100%">Kidney Int</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Kidney Int.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">95</style></volume><pages><style face="normal" font="default" size="100%">914-928</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Approximately 500 monogenic causes of chronic kidney disease (CKD) have been identified, mainly in pediatric populations. The frequency of monogenic causes among adults with CKD has been less extensively studied. To determine the likelihood of detecting monogenic causes of CKD in adults presenting to nephrology services in Ireland, we conducted whole exome sequencing (WES) in a multi-centre cohort of 114 families including 138 affected individuals with CKD. Affected adults were recruited from 78 families with a positive family history, 16 families with extra-renal features, and 20 families with neither a family history nor extra-renal features. We detected a pathogenic mutation in a known CKD gene in 42 of 114 families (37%). A monogenic cause was identified in 36% of affected families with a positive family history of CKD, 69% of those with extra-renal features, and only 15% of those without a family history or extra-renal features. There was no difference in the rate of genetic diagnosis in individuals with childhood versus adult onset CKD. Among the 42 families in whom a monogenic cause was identified, WES confirmed the clinical diagnosis in 17 (40%), corrected the clinical diagnosis in 9 (22%), and established a diagnosis for the first time in 16 families referred with CKD of unknown etiology (38%). In this multi-centre study of adults with CKD, a molecular genetic diagnosis was established in over one-third of families. In the evolving era of precision medicine, WES may be an important tool to identify the cause of CKD in adults.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30773290?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Staretz-Chacham, Orna</style></author><author><style face="normal" font="default" size="100%">Shukrun, Rachel</style></author><author><style face="normal" font="default" size="100%">Barel, Ortal</style></author><author><style face="normal" font="default" size="100%">Pode-Shakked, Ben</style></author><author><style face="normal" font="default" size="100%">Pleniceanu, Oren</style></author><author><style face="normal" font="default" size="100%">Anikster, Yair</style></author><author><style face="normal" font="default" size="100%">Shalva, Nechama</style></author><author><style face="normal" font="default" size="100%">Ferreira, Carlos R</style></author><author><style face="normal" font="default" size="100%">Ben-Haim Kadosh, Admit</style></author><author><style face="normal" font="default" size="100%">Richardson, Justin</style></author><author><style face="normal" font="default" size="100%">Mane, Shrikant M</style></author><author><style face="normal" font="default" size="100%">Hildebrandt, Friedhelm</style></author><author><style face="normal" font="default" size="100%">Vivante, Asaf</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Novel homozygous ENPP1 mutation causes generalized arterial calcifications of infancy, thrombocytopenia, and cardiovascular and central nervous system syndrome.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Med Genet A</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am. J. Med. Genet. A</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Oct</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">179</style></volume><pages><style face="normal" font="default" size="100%">2112-2118</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Generalized arterial calcifications of infancy (GACI) is caused by mutations in ENPP1. Other ENPP1-related phenotypes include pseudoxanthoma elasticum, hypophosphatemic rickets, and Cole disease. We studied four children from two Bedouin consanguineous families who presented with severe clinical phenotype including thrombocytopenia, hypoglycemia, hepatic, and neurologic manifestations. Initial working diagnosis included congenital infection; however, patients remained without a definitive diagnosis despite extensive workup. Consequently, we investigated a potential genetic etiology. Whole exome sequencing (WES) was performed for affected children and their parents. Following the identification of a novel mutation in the ENPP1 gene, we characterized this novel multisystemic presentation and revised relevant imaging studies. Using WES, we identified a novel homozygous mutation (c.556G &gt; C; p.Gly186Arg) in ENPP1 which affects a highly conserved protein domain (somatomedin B2). ENPP1-associated genetic diseases exhibit phenotypic heterogeneity depending on mutation type and location. Follow-up clinical characterization of these families allowed us to revise and detect new features of systemic calcifications, which established the diagnosis of GACI, expanding the phenotypic spectrum associated with ENPP1 mutations. Our findings demonstrate that this novel ENPP1 founder mutation can cause a fatal multisystemic phenotype, mimicking severe congenital infection. This also represents the first reported mutation affecting the SMB2 domain, associated with GACI.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31444901?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bryen, Samantha J</style></author><author><style face="normal" font="default" size="100%">Joshi, Himanshu</style></author><author><style face="normal" font="default" size="100%">Evesson, Frances J</style></author><author><style face="normal" font="default" size="100%">Girard, Cyrille</style></author><author><style face="normal" font="default" size="100%">Ghaoui, Roula</style></author><author><style face="normal" font="default" size="100%">Waddell, Leigh B</style></author><author><style face="normal" font="default" size="100%">Testa, Alison C</style></author><author><style face="normal" font="default" size="100%">Cummings, Beryl</style></author><author><style face="normal" font="default" size="100%">Arbuckle, Susan</style></author><author><style face="normal" font="default" size="100%">Graf, Nicole</style></author><author><style face="normal" font="default" size="100%">Webster, Richard</style></author><author><style face="normal" font="default" size="100%">MacArthur, Daniel G</style></author><author><style face="normal" font="default" size="100%">Laing, Nigel G</style></author><author><style face="normal" font="default" size="100%">Davis, Mark R</style></author><author><style face="normal" font="default" size="100%">Lührmann, Reinhard</style></author><author><style face="normal" font="default" size="100%">Cooper, Sandra T</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pathogenic Abnormal Splicing Due to Intronic Deletions that Induce Biophysical Space Constraint for Spliceosome Assembly.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am. J. Hum. Genet.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Sep 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">105</style></volume><pages><style face="normal" font="default" size="100%">573-587</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A precise genetic diagnosis is the single most important step for families with genetic disorders to enable personalized and preventative medicine. In addition to genetic variants in coding regions (exons) that can change a protein sequence, abnormal pre-mRNA splicing can be devastating for the encoded protein, inducing a frameshift or in-frame deletion/insertion of multiple residues. Non-coding variants that disrupt splicing are extremely challenging to identify. Stemming from an initial clinical discovery in two index Australian families, we define 25 families with genetic disorders caused by a class of pathogenic non-coding splice variant due to intronic deletions. These pathogenic intronic deletions spare all consensus splice motifs, though they critically shorten the minimal distance between the 5' splice-site (5'SS) and branchpoint. The mechanistic basis for abnormal splicing is due to biophysical constraint precluding U1/U2 spliceosome assembly, which stalls in A-complexes (that bridge the 5'SS and branchpoint). Substitution of deleted nucleotides with non-specific sequences restores spliceosome assembly and normal splicing, arguing against loss of an intronic element as the primary causal basis. Incremental lengthening of 5'SS-branchpoint length in our index EMD case subject defines 45-47 nt as the critical elongation enabling (inefficient) spliceosome assembly for EMD intron 5. The 5'SS-branchpoint space constraint mechanism, not currently factored by genomic informatics pipelines, is relevant to diagnosis and precision medicine across the breadth of Mendelian disorders and cancer genomics.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31447096?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Alonge, Michael</style></author><author><style face="normal" font="default" size="100%">Soyk, Sebastian</style></author><author><style face="normal" font="default" size="100%">Ramakrishnan, Srividya</style></author><author><style face="normal" font="default" size="100%">Wang, Xingang</style></author><author><style face="normal" font="default" size="100%">Goodwin, Sara</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Lippman, Zachary B</style></author><author><style face="normal" font="default" size="100%">Schatz, Michael C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">RaGOO: fast and accurate reference-guided scaffolding of draft genomes.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Biol.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Oct 28</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">20</style></volume><pages><style face="normal" font="default" size="100%">224</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present RaGOO, a reference-guided contig ordering and orienting tool that leverages the speed and sensitivity of Minimap2 to accurately achieve chromosome-scale assemblies in minutes. After the pseudomolecules are constructed, RaGOO identifies structural variants, including those spanning sequencing gaps. We show that RaGOO accurately orders and orients 3 de novo tomato genome assemblies, including the widely used M82 reference cultivar. We then demonstrate the scalability and utility of RaGOO with a pan-genome analysis of 103 Arabidopsis thaliana accessions by examining the structural variants detected in the newly assembled pseudomolecules. RaGOO is available open source at https://github.com/malonge/RaGOO .&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31661016?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aldinger, Kimberly A</style></author><author><style face="normal" font="default" size="100%">Timms, Andrew E</style></author><author><style face="normal" font="default" size="100%">Thomson, Zachary</style></author><author><style face="normal" font="default" size="100%">Mirzaa, Ghayda M</style></author><author><style face="normal" font="default" size="100%">Bennett, James T</style></author><author><style face="normal" font="default" size="100%">Rosenberg, Alexander B</style></author><author><style face="normal" font="default" size="100%">Roco, Charles M</style></author><author><style face="normal" font="default" size="100%">Hirano, Matthew</style></author><author><style face="normal" font="default" size="100%">Abidi, Fatima</style></author><author><style face="normal" font="default" size="100%">Haldipur, Parthiv</style></author><author><style face="normal" font="default" size="100%">Cheng, Chi V</style></author><author><style face="normal" font="default" size="100%">Collins, Sarah</style></author><author><style face="normal" font="default" size="100%">Park, Kaylee</style></author><author><style face="normal" font="default" size="100%">Zeiger, Jordan</style></author><author><style face="normal" font="default" size="100%">Overmann, Lynne M</style></author><author><style face="normal" font="default" size="100%">Alkuraya, Fowzan S</style></author><author><style face="normal" font="default" size="100%">Biesecker, Leslie G</style></author><author><style face="normal" font="default" size="100%">Braddock, Stephen R</style></author><author><style face="normal" font="default" size="100%">Cathey, Sara</style></author><author><style face="normal" font="default" size="100%">Cho, Megan T</style></author><author><style face="normal" font="default" size="100%">Chung, Brian H Y</style></author><author><style face="normal" font="default" size="100%">Everman, David B</style></author><author><style face="normal" font="default" size="100%">Zarate, Yuri A</style></author><author><style face="normal" font="default" size="100%">Jones, Julie R</style></author><author><style face="normal" font="default" size="100%">Schwartz, Charles E</style></author><author><style face="normal" font="default" size="100%">Goldstein, Amy</style></author><author><style face="normal" font="default" size="100%">Hopkin, Robert J</style></author><author><style face="normal" font="default" size="100%">Krantz, Ian D</style></author><author><style face="normal" font="default" size="100%">Ladda, Roger L</style></author><author><style face="normal" font="default" size="100%">Leppig, Kathleen A</style></author><author><style face="normal" font="default" size="100%">McGillivray, Barbara C</style></author><author><style face="normal" font="default" size="100%">Sell, Susan</style></author><author><style face="normal" font="default" size="100%">Wusik, Katherine</style></author><author><style face="normal" font="default" size="100%">Gleeson, Joseph G</style></author><author><style face="normal" font="default" size="100%">Nickerson, Deborah A</style></author><author><style face="normal" font="default" size="100%">Bamshad, Michael J</style></author><author><style face="normal" font="default" size="100%">Gerrelli, Dianne</style></author><author><style face="normal" font="default" size="100%">Lisgo, Steven N</style></author><author><style face="normal" font="default" size="100%">Seelig, Georg</style></author><author><style face="normal" font="default" size="100%">Ishak, Gisele E</style></author><author><style face="normal" font="default" size="100%">Barkovich, A James</style></author><author><style face="normal" font="default" size="100%">Curry, Cynthia J</style></author><author><style face="normal" font="default" size="100%">Glass, Ian A</style></author><author><style face="normal" font="default" size="100%">Millen, Kathleen J</style></author><author><style face="normal" font="default" size="100%">Doherty, Dan</style></author><author><style face="normal" font="default" size="100%">Dobyns, William B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Redefining the Etiologic Landscape of Cerebellar Malformations.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am. J. Hum. Genet.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Sep 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">105</style></volume><pages><style face="normal" font="default" size="100%">606-615</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Cerebellar malformations are diverse congenital anomalies frequently associated with developmental disability. Although genetic and prenatal non-genetic causes have been described, no systematic analysis has been performed. Here, we present a large-exome sequencing study of Dandy-Walker malformation (DWM) and cerebellar hypoplasia (CBLH). We performed exome sequencing in 282 individuals from 100 families with DWM or CBLH, and we established a molecular diagnosis in 36 of 100 families, with a significantly higher yield for CBLH (51%) than for DWM (16%). The 41 variants impact 27 neurodevelopmental-disorder-associated genes, thus demonstrating that CBLH and DWM are often features of monogenic neurodevelopmental disorders. Though only seven monogenic causes (19%) were identified in more than one individual, neuroimaging review of 131 additional individuals confirmed cerebellar abnormalities in 23 of 27 genetic disorders (85%). Prenatal risk factors were frequently found among individuals without a genetic diagnosis (30 of 64 individuals [47%]). Single-cell RNA sequencing of prenatal human cerebellar tissue revealed gene enrichment in neuronal and vascular cell types; this suggests that defective vasculogenesis may disrupt cerebellar development. Further, de novo gain-of-function variants in PDGFRB, a tyrosine kinase receptor essential for vascular progenitor signaling, were associated with CBLH, and this discovery links genetic and non-genetic etiologies. Our results suggest that genetic defects impact specific cerebellar cell types and implicate abnormal vascular development as a mechanism for cerebellar malformations. We also confirmed a major contribution for non-genetic prenatal factors in individuals with cerebellar abnormalities, substantially influencing diagnostic evaluation and counseling regarding recurrence risk and prognosis.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31474318?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Larson, David E</style></author><author><style face="normal" font="default" size="100%">Abel, Haley J</style></author><author><style face="normal" font="default" size="100%">Chiang, Colby</style></author><author><style face="normal" font="default" size="100%">Badve, Abhijit</style></author><author><style face="normal" font="default" size="100%">Das, Indraniel</style></author><author><style face="normal" font="default" size="100%">Eldred, James M</style></author><author><style face="normal" font="default" size="100%">Layer, Ryan M</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">svtools: population-scale analysis of structural variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Bioinformatics</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Nov 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">4782-4787</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;SUMMARY: &lt;/b&gt;Large-scale human genetics studies are now employing whole genome sequencing with the goal of conducting comprehensive trait mapping analyses of all forms of genome variation. However, methods for structural variation (SV) analysis have lagged far behind those for smaller scale variants, and there is an urgent need to develop more efficient tools that scale to the size of human populations. Here, we present a fast and highly scalable software toolkit (svtools) and cloud-based pipeline for assembling high quality SV maps-including deletions, duplications, mobile element insertions, inversions and other rearrangements-in many thousands of human genomes. We show that this pipeline achieves similar variant detection performance to established per-sample methods (e.g. LUMPY), while providing fast and affordable joint analysis at the scale of ≥100 000 genomes. These tools will help enable the next generation of human genetics studies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;AVAILABILITY AND IMPLEMENTATION: &lt;/b&gt;svtools is implemented in Python and freely available (MIT) from https://github.com/hall-lab/svtools.&lt;/p&gt;&lt;p&gt;&lt;b&gt;SUPPLEMENTARY INFORMATION: &lt;/b&gt;Supplementary data are available at Bioinformatics online.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">22</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/31218349?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Klarin, Derek</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna</style></author><author><style face="normal" font="default" size="100%">Haas, Mary</style></author><author><style face="normal" font="default" size="100%">Bick, Alexander</style></author><author><style face="normal" font="default" size="100%">Zekavat, Seyedeh M</style></author><author><style face="normal" font="default" size="100%">Nomura, Akihiro</style></author><author><style face="normal" font="default" size="100%">Ardissino, Diego</style></author><author><style face="normal" font="default" size="100%">Wilson, James G</style></author><author><style face="normal" font="default" size="100%">Schunkert, Heribert</style></author><author><style face="normal" font="default" size="100%">McPherson, Ruth</style></author><author><style face="normal" font="default" size="100%">Watkins, Hugh</style></author><author><style face="normal" font="default" size="100%">Elosua, Roberto</style></author><author><style face="normal" font="default" size="100%">Bown, Matthew J</style></author><author><style face="normal" font="default" size="100%">Samani, Nilesh J</style></author><author><style face="normal" font="default" size="100%">Baber, Usman</style></author><author><style face="normal" font="default" size="100%">Erdmann, Jeanette</style></author><author><style face="normal" font="default" size="100%">Gupta, Namrata</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Chasman, Daniel</style></author><author><style face="normal" font="default" size="100%">Ridker, Paul</style></author><author><style face="normal" font="default" size="100%">Denny, Joshua</style></author><author><style face="normal" font="default" size="100%">Bastarache, Lisa</style></author><author><style face="normal" font="default" size="100%">Lichtman, Judith H</style></author><author><style face="normal" font="default" size="100%">D'Onofrio, Gail</style></author><author><style face="normal" font="default" size="100%">Mattera, Jennifer</style></author><author><style face="normal" font="default" size="100%">Spertus, John A</style></author><author><style face="normal" font="default" size="100%">Sheu, Wayne H-H</style></author><author><style face="normal" font="default" size="100%">Taylor, Kent D</style></author><author><style face="normal" font="default" size="100%">Psaty, Bruce M</style></author><author><style face="normal" font="default" size="100%">Rich, Stephen S</style></author><author><style face="normal" font="default" size="100%">Post, Wendy</style></author><author><style face="normal" font="default" size="100%">Rotter, Jerome I</style></author><author><style face="normal" font="default" size="100%">Chen, Yii-Der Ida</style></author><author><style face="normal" font="default" size="100%">Krumholz, Harlan</style></author><author><style face="normal" font="default" size="100%">Saleheen, Danish</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Databases, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes Mellitus, Type 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Testing</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Obesity</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Respiratory Hypersensitivity</style></keyword><keyword><style  face="normal" font="default" size="100%">United Kingdom</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Apr 24</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">1613</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Less than 3% of protein-coding genetic variants are predicted to result in loss of protein function through the introduction of a stop codon, frameshift, or the disruption of an essential splice site; however, such predicted loss-of-function (pLOF) variants provide insight into effector transcript and direction of biological effect. In &gt;400,000 UK Biobank participants, we conduct association analyses of 3759 pLOF variants with six metabolic traits, six cardiometabolic diseases, and twelve additional diseases. We identified 18 new low-frequency or rare (allele frequency &lt; 5%) pLOF variant-phenotype associations. pLOF variants in the gene GPR151 protect against obesity and type 2 diabetes, in the gene IL33 against asthma and allergic disease, and in the gene IFIH1 against hypothyroidism. In the gene PDE3B, pLOF variants associate with elevated height, improved body fat distribution and protection from coronary artery disease. Our findings prioritize genes for which pharmacologic mimics of pLOF variants may lower risk for disease.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29691411?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Murphy, Meredith P</style></author><author><style face="normal" font="default" size="100%">Kuramatsu, Joji B</style></author><author><style face="normal" font="default" size="100%">Leasure, Audrey</style></author><author><style face="normal" font="default" size="100%">Falcone, Guido J</style></author><author><style face="normal" font="default" size="100%">Kamel, Hooman</style></author><author><style face="normal" font="default" size="100%">Sansing, Lauren H</style></author><author><style face="normal" font="default" size="100%">Kourkoulis, Christina</style></author><author><style face="normal" font="default" size="100%">Schwab, Kristin</style></author><author><style face="normal" font="default" size="100%">Elm, Jordan J</style></author><author><style face="normal" font="default" size="100%">Gurol, M Edip</style></author><author><style face="normal" font="default" size="100%">Tran, Huy</style></author><author><style face="normal" font="default" size="100%">Greenberg, Steven M</style></author><author><style face="normal" font="default" size="100%">Viswanathan, Anand</style></author><author><style face="normal" font="default" size="100%">Anderson, Christopher D</style></author><author><style face="normal" font="default" size="100%">Schwab, Stefan</style></author><author><style face="normal" font="default" size="100%">Rosand, Jonathan</style></author><author><style face="normal" font="default" size="100%">Shi, Fu-Dong</style></author><author><style face="normal" font="default" size="100%">Kittner, Steven J</style></author><author><style face="normal" font="default" size="100%">Testai, Fernando D</style></author><author><style face="normal" font="default" size="100%">Woo, Daniel</style></author><author><style face="normal" font="default" size="100%">Langefeld, Carl D</style></author><author><style face="normal" font="default" size="100%">James, Michael L</style></author><author><style face="normal" font="default" size="100%">Koch, Sebastian</style></author><author><style face="normal" font="default" size="100%">Huttner, Hagen B</style></author><author><style face="normal" font="default" size="100%">Biffi, Alessandro</style></author><author><style face="normal" font="default" size="100%">Sheth, Kevin N</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Cardioembolic Stroke Risk and Recovery After Anticoagulation-Related Intracerebral Hemorrhage.</style></title><secondary-title><style face="normal" font="default" size="100%">Stroke</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Stroke</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Nov</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">2652-2658</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Background and Purpose- Whether to resume oral anticoagulation treatment after intracerebral hemorrhage (ICH) remains an unresolved question. Previous studies focused primarily on recurrent stroke after ICH. We sought to investigate the association between cardioembolic stroke risk, oral anticoagulation therapy resumption, and functional recovery among ICH survivors in the absence of recurrent stroke. Methods- We conducted a joint analysis of 3 observational studies: (1) the multicenter RETRACE study (German-Wide Multicenter Analysis of Oral Anticoagulation Associated Intracerebral Hemorrhage); (2) the Massachusetts General Hospital ICH study (n=166); and (3) the ERICH study (Ethnic/Racial Variations of Intracerebral Hemorrhage; n=131). We included 941 survivors of ICH in the setting of active oral anticoagulation therapy for prevention of cardioembolic stroke because of nonvalvular atrial fibrillation and without evidence of ischemic stroke and recurrent ICH at 1 year from the index event. We created univariable and multivariable models to explore associations between cardioembolic stroke risk (based on CHADS-VASc scores) and functional recovery after ICH, defined as achieving modified Rankin Scale score of ≤3 at 1 year for participants with modified Rankin Scale score of &gt;3 at discharge. Results- In multivariable analyses, the CHADS-VASc score was associated with a decreased likelihood of functional recovery (odds ratio, 0.83 per 1 point increase; 95% CI, 0.79-0.86) at 1 year. Anticoagulation resumption was independently associated with a higher likelihood of recovery, regardless of CHADS-VASc score (odds ratio, 1.89; 95% CI, 1.32-2.70). We found an interaction between CHADS-VASc score and anticoagulation resumption in terms of association with increased likelihood of functional recovery (interaction P=0.011). Conclusions- Increasing cardioembolic stroke risk is associated with a decreased likelihood of functional recovery at 1 year after ICH, but this association was weaker among participants resuming oral anticoagulation therapy. These findings support, including recovery metrics, in future studies of anticoagulation resumption after ICH.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/30355194?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Costello, Maura</style></author><author><style face="normal" font="default" size="100%">Fleharty, Mark</style></author><author><style face="normal" font="default" size="100%">Abreu, Justin</style></author><author><style face="normal" font="default" size="100%">Farjoun, Yossi</style></author><author><style face="normal" font="default" size="100%">Ferriera, Steven</style></author><author><style face="normal" font="default" size="100%">Holmes, Laurie</style></author><author><style face="normal" font="default" size="100%">Granger, Brian</style></author><author><style face="normal" font="default" size="100%">Green, Lisa</style></author><author><style face="normal" font="default" size="100%">Howd, Tom</style></author><author><style face="normal" font="default" size="100%">Mason, Tamara</style></author><author><style face="normal" font="default" size="100%">Vicente, Gina</style></author><author><style face="normal" font="default" size="100%">Dasilva, Michael</style></author><author><style face="normal" font="default" size="100%">Brodeur, Wendy</style></author><author><style face="normal" font="default" size="100%">DeSmet, Timothy</style></author><author><style face="normal" font="default" size="100%">Dodge, Sheila</style></author><author><style face="normal" font="default" size="100%">Lennon, Niall J</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Genomics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Library</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 May 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">332</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/29739332?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Nattestad, Maria</style></author><author><style face="normal" font="default" size="100%">Goodwin, Sara</style></author><author><style face="normal" font="default" size="100%">Ng, Karen</style></author><author><style face="normal" font="default" size="100%">Baslan, Timour</style></author><author><style face="normal" font="default" size="100%">Sedlazeck, Fritz J</style></author><author><style face="normal" font="default" size="100%">Rescheneder, Philipp</style></author><author><style face="normal" font="default" size="100%">Garvin, Tyler</style></author><author><style face="normal" font="default" size="100%">Fang, Han</style></author><author><style face="normal" font="default" size="100%">Gurtowski, James</style></author><author><style face="normal" font="default" size="100%">Hutton, Elizabeth</style></author><author><style face="normal" font="default" size="100%">Tseng, Elizabeth</style></author><author><style face="normal" font="default" size="100%">Chin, Chen-Shan</style></author><author><style face="normal" font="default" size="100%">Beck, Timothy</style></author><author><style face="normal" font="default" size="100%">Sundaravadanam, Yogi</style></author><author><style face="normal" font="default" size="100%">Kramer, Melissa</style></author><author><style face="normal" font="default" size="100%">Antoniou, Eric</style></author><author><style face="normal" font="default" size="100%">McPherson, John D</style></author><author><style face="normal" font="default" size="100%">Hicks, James</style></author><author><style face="normal" font="default" size="100%">McCombie, W Richard</style></author><author><style face="normal" font="default" size="100%">Schatz, Michael C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Complex rearrangements and oncogene amplifications revealed by long-read DNA and RNA sequencing of a breast cancer cell line.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Res.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Breast Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Amplification</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Rearrangement</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomic Structural Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">MCF-7 Cells</style></keyword><keyword><style  face="normal" font="default" size="100%">Oncogenes</style></keyword><keyword><style  face="normal" font="default" size="100%">Receptor, ErbB-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Repetitive Sequences, Nucleic Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 08</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">1126-1135</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important  oncogene (also known as ), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/29954844?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Regier, Allison A</style></author><author><style face="normal" font="default" size="100%">Farjoun, Yossi</style></author><author><style face="normal" font="default" size="100%">Larson, David E</style></author><author><style face="normal" font="default" size="100%">Krasheninina, Olga</style></author><author><style face="normal" font="default" size="100%">Kang, Hyun Min</style></author><author><style face="normal" font="default" size="100%">Howrigan, Daniel P</style></author><author><style face="normal" font="default" size="100%">Chen, Bo-Juen</style></author><author><style face="normal" font="default" size="100%">Kher, Manisha</style></author><author><style face="normal" font="default" size="100%">Banks, Eric</style></author><author><style face="normal" font="default" size="100%">Ames, Darren C</style></author><author><style face="normal" font="default" size="100%">English, Adam C</style></author><author><style face="normal" font="default" size="100%">Li, Heng</style></author><author><style face="normal" font="default" size="100%">Xing, Jinchuan</style></author><author><style face="normal" font="default" size="100%">Zhang, Yeting</style></author><author><style face="normal" font="default" size="100%">Matise, Tara</style></author><author><style face="normal" font="default" size="100%">Abecasis, Goncalo R</style></author><author><style face="normal" font="default" size="100%">Salerno, Will</style></author><author><style face="normal" font="default" size="100%">Zody, Michael C</style></author><author><style face="normal" font="default" size="100%">Neale, Benjamin M</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Commun</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Commun</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole Genome Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 10 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">9</style></volume><pages><style face="normal" font="default" size="100%">4038</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power. A central challenge for joint analysis is that different WGS data processing pipelines cause substantial differences in variant calling in combined datasets, necessitating computationally expensive reprocessing. This approach is no longer tenable given the scale of current studies and data volumes. Here, we define WGS data processing standards that allow different groups to produce functionally equivalent (FE) results, yet still innovate on data processing pipelines. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results and produce significantly less variability than sequencing replicates. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for community-wide human genetics studies.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/30279509?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Aragam, Krishna G</style></author><author><style face="normal" font="default" size="100%">Haas, Mary E</style></author><author><style face="normal" font="default" size="100%">Roselli, Carolina</style></author><author><style face="normal" font="default" size="100%">Choi, Seung Hoan</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author><author><style face="normal" font="default" size="100%">Lubitz, Steven A</style></author><author><style face="normal" font="default" size="100%">Ellinor, Patrick T</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat. Genet.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Sep</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">1219-1224</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation. Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature, it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For coronary artery disease, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk. We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/30104762?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Cervera, Alejandra</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Reverter, Ferran</style></author><author><style face="normal" font="default" size="100%">Wolman, Aaron</style></author><author><style face="normal" font="default" size="100%">Guigo, Roderic</style></author><author><style face="normal" font="default" size="100%">Iossifov, Ivan</style></author><author><style face="normal" font="default" size="100%">Vasileva, Ana</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modified penetrance of coding variants by cis-regulatory variation contributes to disease risk.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat. Genet.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Sep</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">50</style></volume><pages><style face="normal" font="default" size="100%">1327-1334</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Coding variants represent many of the strongest associations between genotype and phenotype; however, they exhibit inter-individual differences in effect, termed 'variable penetrance'. Here, we study how cis-regulatory variation modifies the penetrance of coding variants. Using functional genomic and genetic data from the Genotype-Tissue Expression Project (GTEx), we observed that in the general population, purifying selection has depleted haplotype combinations predicted to increase pathogenic coding variant penetrance. Conversely, in cancer and autism patients, we observed an enrichment of penetrance increasing haplotype configurations for pathogenic variants in disease-implicated genes, providing evidence that regulatory haplotype configuration of coding variants affects disease risk. Finally, we experimentally validated this model by editing a Mendelian single-nucleotide polymorphism (SNP) using CRISPR/Cas9 on distinct expression haplotypes with the transcriptome as a phenotypic readout. Our results demonstrate that joint regulatory and coding variant effects are an important part of the genetic architecture of human traits and contribute to modified penetrance of disease-causing variants.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/30127527?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mak, Angel C Y</style></author><author><style face="normal" font="default" size="100%">White, Marquitta J</style></author><author><style face="normal" font="default" size="100%">Eckalbar, Walter L</style></author><author><style face="normal" font="default" size="100%">Szpiech, Zachary A</style></author><author><style face="normal" font="default" size="100%">Oh, Sam S</style></author><author><style face="normal" font="default" size="100%">Pino-Yanes, Maria</style></author><author><style face="normal" font="default" size="100%">Hu, Donglei</style></author><author><style face="normal" font="default" size="100%">Goddard, Pagé</style></author><author><style face="normal" font="default" size="100%">Huntsman, Scott</style></author><author><style face="normal" font="default" size="100%">Galanter, Joshua</style></author><author><style face="normal" font="default" size="100%">Wu, Ann Chen</style></author><author><style face="normal" font="default" size="100%">Himes, Blanca E</style></author><author><style face="normal" font="default" size="100%">Germer, Soren</style></author><author><style face="normal" font="default" size="100%">Vogel, Julia M</style></author><author><style face="normal" font="default" size="100%">Bunting, Karen L</style></author><author><style face="normal" font="default" size="100%">Eng, Celeste</style></author><author><style face="normal" font="default" size="100%">Salazar, Sandra</style></author><author><style face="normal" font="default" size="100%">Keys, Kevin L</style></author><author><style face="normal" font="default" size="100%">Liberto, Jennifer</style></author><author><style face="normal" font="default" size="100%">Nuckton, Thomas J</style></author><author><style face="normal" font="default" size="100%">Nguyen, Thomas A</style></author><author><style face="normal" font="default" size="100%">Torgerson, Dara G</style></author><author><style face="normal" font="default" size="100%">Kwok, Pui-Yan</style></author><author><style face="normal" font="default" size="100%">Levin, Albert M</style></author><author><style face="normal" font="default" size="100%">Celedón, Juan C</style></author><author><style face="normal" font="default" size="100%">Forno, Erick</style></author><author><style face="normal" font="default" size="100%">Hakonarson, Hakon</style></author><author><style face="normal" font="default" size="100%">Sleiman, Patrick M</style></author><author><style face="normal" font="default" size="100%">Dahlin, Amber</style></author><author><style face="normal" font="default" size="100%">Tantisira, Kelan G</style></author><author><style face="normal" font="default" size="100%">Weiss, Scott T</style></author><author><style face="normal" font="default" size="100%">Serebrisky, Denise</style></author><author><style face="normal" font="default" size="100%">Brigino-Buenaventura, Emerita</style></author><author><style face="normal" font="default" size="100%">Farber, Harold J</style></author><author><style face="normal" font="default" size="100%">Meade, Kelley</style></author><author><style face="normal" font="default" size="100%">Lenoir, Michael A</style></author><author><style face="normal" font="default" size="100%">Avila, Pedro C</style></author><author><style face="normal" font="default" size="100%">Sen, Saunak</style></author><author><style face="normal" font="default" size="100%">Thyne, Shannon M</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Cintron, William</style></author><author><style face="normal" font="default" size="100%">Winkler, Cheryl A</style></author><author><style face="normal" font="default" size="100%">Moreno-Estrada, Andrés</style></author><author><style face="normal" font="default" size="100%">Sandoval, Karla</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Santana, Jose R</style></author><author><style face="normal" font="default" size="100%">Kumar, Rajesh</style></author><author><style face="normal" font="default" size="100%">Williams, L Keoki</style></author><author><style face="normal" font="default" size="100%">Ahituv, Nadav</style></author><author><style face="normal" font="default" size="100%">Ziv, Elad</style></author><author><style face="normal" font="default" size="100%">Seibold, Max A</style></author><author><style face="normal" font="default" size="100%">Darnell, Robert B</style></author><author><style face="normal" font="default" size="100%">Zaitlen, Noah</style></author><author><style face="normal" font="default" size="100%">Hernandez, Ryan D</style></author><author><style face="normal" font="default" size="100%">Burchard, Esteban G</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma.</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Respir Crit Care Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am. J. Respir. Crit. Care Med.</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2018 Jun 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">197</style></volume><pages><style face="normal" font="default" size="100%">1552-1564</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;RATIONALE: &lt;/b&gt;Albuterol, a bronchodilator medication, is the first-line therapy for asthma worldwide. There are significant racial/ethnic differences in albuterol drug response.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;To identify genetic variants important for bronchodilator drug response (BDR) in racially diverse children.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We performed the first whole-genome sequencing pharmacogenetics study from 1,441 children with asthma from the tails of the BDR distribution to identify genetic association with BDR.&lt;/p&gt;&lt;p&gt;&lt;b&gt;MEASUREMENTS AND MAIN RESULTS: &lt;/b&gt;We identified population-specific and shared genetic variants associated with BDR, including genome-wide significant (P &lt; 3.53 × 10) and suggestive (P &lt; 7.06 × 10) loci near genes previously associated with lung capacity (DNAH5), immunity (NFKB1 and PLCB1), and β-adrenergic signaling (ADAMTS3 and COX18). Functional analyses of the BDR-associated SNP in NFKB1 revealed potential regulatory function in bronchial smooth muscle cells. The SNP is also an expression quantitative trait locus for a neighboring gene, SLC39A8. The lack of other asthma study populations with BDR and whole-genome sequencing data on minority children makes it impossible to perform replication of our rare variant associations. Minority underrepresentation also poses significant challenges to identify age-matched and population-matched cohorts of sufficient sample size for replication of our common variant findings.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;The lack of minority data, despite a collaboration of eight universities and 13 individual laboratories, highlights the urgent need for a dedicated national effort to prioritize diversity in research. Our study expands the understanding of pharmacogenetic analyses in racially/ethnically diverse populations and advances the foundation for precision medicine in at-risk and understudied minority populations.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">12</style></issue><custom1><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/29509491?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lu, Hsiang-Chih</style></author><author><style face="normal" font="default" size="100%">Tan, Qiumin</style></author><author><style face="normal" font="default" size="100%">Rousseaux, Maxime W C</style></author><author><style face="normal" font="default" size="100%">Wang, Wei</style></author><author><style face="normal" font="default" size="100%">Kim, Ji-Yoen</style></author><author><style face="normal" font="default" size="100%">Richman, Ronald</style></author><author><style face="normal" font="default" size="100%">Wan, Ying-Wooi</style></author><author><style face="normal" font="default" size="100%">Yeh, Szu-Ying</style></author><author><style face="normal" font="default" size="100%">Patel, Jay M</style></author><author><style face="normal" font="default" size="100%">Liu, Xiuyun</style></author><author><style face="normal" font="default" size="100%">Lin, Tao</style></author><author><style face="normal" font="default" size="100%">Lee, Yoontae</style></author><author><style face="normal" font="default" size="100%">Fryer, John D</style></author><author><style face="normal" font="default" size="100%">Han, Jing</style></author><author><style face="normal" font="default" size="100%">Chahrour, Maria</style></author><author><style face="normal" font="default" size="100%">Finnell, Richard H</style></author><author><style face="normal" font="default" size="100%">Lei, Yunping</style></author><author><style face="normal" font="default" size="100%">Zurita-Jimenez, Maria E</style></author><author><style face="normal" font="default" size="100%">Ahimaz, Priyanka</style></author><author><style face="normal" font="default" size="100%">Anyane-Yeboa, Kwame</style></author><author><style face="normal" font="default" size="100%">Van Maldergem, Lionel</style></author><author><style face="normal" font="default" size="100%">Lehalle, Daphne</style></author><author><style face="normal" font="default" size="100%">Jean-Marcais, Nolwenn</style></author><author><style face="normal" font="default" size="100%">Mosca-Boidron, Anne-Laure</style></author><author><style face="normal" font="default" size="100%">Thevenon, Julien</style></author><author><style face="normal" font="default" size="100%">Cousin, Margot A</style></author><author><style face="normal" font="default" size="100%">Bro, Della E</style></author><author><style face="normal" font="default" size="100%">Lanpher, Brendan C</style></author><author><style face="normal" font="default" size="100%">Klee, Eric W</style></author><author><style face="normal" font="default" size="100%">Alexander, Nora</style></author><author><style face="normal" font="default" size="100%">Bainbridge, Matthew N</style></author><author><style face="normal" font="default" size="100%">Orr, Harry T</style></author><author><style face="normal" font="default" size="100%">Sillitoe, Roy V</style></author><author><style face="normal" font="default" size="100%">Ljungberg, M Cecilia</style></author><author><style face="normal" font="default" size="100%">Liu, Zhandong</style></author><author><style face="normal" font="default" size="100%">Schaaf, Christian P</style></author><author><style face="normal" font="default" size="100%">Zoghbi, Huda Y</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Disruption of the ATXN1-CIC complex causes a spectrum of neurobehavioral phenotypes in mice and humans.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Ataxin-1</style></keyword><keyword><style  face="normal" font="default" size="100%">Autism Spectrum Disorder</style></keyword><keyword><style  face="normal" font="default" size="100%">Cerebellum</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Intellectual Disability</style></keyword><keyword><style  face="normal" font="default" size="100%">Interpersonal Relations</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Nerve Tissue Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Neurodegenerative Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Nuclear Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Repressor Proteins</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">49</style></volume><pages><style face="normal" font="default" size="100%">527-536</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Gain-of-function mutations in some genes underlie neurodegenerative conditions, whereas loss-of-function mutations in the same genes have distinct phenotypes. This appears to be the case with the protein ataxin 1 (ATXN1), which forms a transcriptional repressor complex with capicua (CIC). Gain of function of the complex leads to neurodegeneration, but ATXN1-CIC is also essential for survival. We set out to understand the functions of the ATXN1-CIC complex in the developing forebrain and found that losing this complex results in hyperactivity, impaired learning and memory, and abnormal maturation and maintenance of upper-layer cortical neurons. We also found that CIC activity in the hypothalamus and medial amygdala modulates social interactions. Informed by these neurobehavioral features in mouse mutants, we identified five individuals with de novo heterozygous truncating mutations in CIC who share similar clinical features, including intellectual disability, attention deficit/hyperactivity disorder (ADHD), and autism spectrum disorder. Our study demonstrates that loss of ATXN1-CIC complexes causes a spectrum of neurobehavioral phenotypes.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28288114?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Auer, Paul L</style></author><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic association studies in cardiovascular diseases: Do we have enough power?</style></title><secondary-title><style face="normal" font="default" size="100%">Trends Cardiovasc Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Trends Cardiovasc Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cardiovascular Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Accuracy</style></keyword><keyword><style  face="normal" font="default" size="100%">Data Interpretation, Statistical</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Association Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Reproducibility of Results</style></keyword><keyword><style  face="normal" font="default" size="100%">Research Design</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Assessment</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Aug</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">397-404</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Genetic association studies have a long history of delivering insightful results for cardiovascular disease (CVD) research. Beginning with early candidate gene studies, to genome-wide association studies, and now on to newer whole-genome sequencing studies, research in human genetics has enriched our understanding of the pathobiology of CVD. As these studies continue to expand, the issue of statistical power plays an important role in study design as well as the interpretation of results. We provide an overview of the component parts that determine statistical power and preview the future of CVD genetic association studies through this lens.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28456354?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Posey, Jennifer E</style></author><author><style face="normal" font="default" size="100%">Harel, Tamar</style></author><author><style face="normal" font="default" size="100%">Liu, Pengfei</style></author><author><style face="normal" font="default" size="100%">Rosenfeld, Jill A</style></author><author><style face="normal" font="default" size="100%">James, Regis A</style></author><author><style face="normal" font="default" size="100%">Coban Akdemir, Zeynep H</style></author><author><style face="normal" font="default" size="100%">Walkiewicz, Magdalena</style></author><author><style face="normal" font="default" size="100%">Bi, Weimin</style></author><author><style face="normal" font="default" size="100%">Xiao, Rui</style></author><author><style face="normal" font="default" size="100%">Ding, Yan</style></author><author><style face="normal" font="default" size="100%">Xia, Fan</style></author><author><style face="normal" font="default" size="100%">Beaudet, Arthur L</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Eng, Christine M</style></author><author><style face="normal" font="default" size="100%">Sutton, V Reid</style></author><author><style face="normal" font="default" size="100%">Shaw, Chad A</style></author><author><style face="normal" font="default" size="100%">Plon, Sharon E</style></author><author><style face="normal" font="default" size="100%">Yang, Yaping</style></author><author><style face="normal" font="default" size="100%">Lupski, James R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.</style></title><secondary-title><style face="normal" font="default" size="100%">N Engl J Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">N Engl J Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Diseases, Inborn</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotyping Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Phenotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Retrospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jan 05</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">376</style></volume><pages><style face="normal" font="default" size="100%">21-31</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;A molecular diagnosis was rendered for 2076 of 7374 patients (28.2%); among these patients, 101 (4.9%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77×10).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;In our study, we found multiple molecular diagnoses in 4.9% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27959697?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ganel, Liron</style></author><author><style face="normal" font="default" size="100%">Abel, Haley J</style></author><author><style face="normal" font="default" size="100%">Hall, Ira M</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">FinMetSeq Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">SVScore: an impact prediction tool for structural variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Bioinformatics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Bioinformatics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Gene Frequency</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomic Structural Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Deletion</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Apr 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">33</style></volume><pages><style face="normal" font="default" size="100%">1083-1085</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;SUMMARY: &lt;/b&gt;Here we present SVScore, a tool for in silico structural variation (SV) impact prediction. SVScore aggregates per-base single nucleotide polymorphism (SNP) pathogenicity scores across relevant genomic intervals for each SV in a manner that considers variant type, gene features and positional uncertainty. We show that the allele frequency spectrum of high-scoring SVs is strongly skewed toward lower frequencies, suggesting that they are under purifying selection, and that SVScore identifies deleterious variants more effectively than alternative methods. Notably, our results also suggest that duplications are under surprisingly strong selection relative to deletions, and that there are a similar number of strongly pathogenic SVs and SNPs in the human population.&lt;/p&gt;&lt;p&gt;&lt;b&gt;AVAILABILITY AND IMPLEMENTATION: &lt;/b&gt;SVScore is implemented in Perl and available freely at {{ http://www.github.com/lganel/SVScore }} for use under the MIT license.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONTACT: &lt;/b&gt;ihall@wustl.edu.&lt;/p&gt;&lt;p&gt;&lt;b&gt;SUPPLEMENTARY INFORMATION: &lt;/b&gt;Supplementary data are available at Bioinformatics online.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">7</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28031184?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rusu, Victor</style></author><author><style face="normal" font="default" size="100%">Hoch, Eitan</style></author><author><style face="normal" font="default" size="100%">Mercader, Josep M</style></author><author><style face="normal" font="default" size="100%">Tenen, Danielle E</style></author><author><style face="normal" font="default" size="100%">Gymrek, Melissa</style></author><author><style face="normal" font="default" size="100%">Hartigan, Christina R</style></author><author><style face="normal" font="default" size="100%">DeRan, Michael</style></author><author><style face="normal" font="default" size="100%">von Grotthuss, Marcin</style></author><author><style face="normal" font="default" size="100%">Fontanillas, Pierre</style></author><author><style face="normal" font="default" size="100%">Spooner, Alexandra</style></author><author><style face="normal" font="default" size="100%">Guzman, Gaelen</style></author><author><style face="normal" font="default" size="100%">Deik, Amy A</style></author><author><style face="normal" font="default" size="100%">Pierce, Kerry A</style></author><author><style face="normal" font="default" size="100%">Dennis, Courtney</style></author><author><style face="normal" font="default" size="100%">Clish, Clary B</style></author><author><style face="normal" font="default" size="100%">Carr, Steven A</style></author><author><style face="normal" font="default" size="100%">Wagner, Bridget K</style></author><author><style face="normal" font="default" size="100%">Schenone, Monica</style></author><author><style face="normal" font="default" size="100%">Ng, Maggie C Y</style></author><author><style face="normal" font="default" size="100%">Chen, Brian H</style></author><author><style face="normal" font="default" size="100%">Centeno-Cruz, Federico</style></author><author><style face="normal" font="default" size="100%">Zerrweck, Carlos</style></author><author><style face="normal" font="default" size="100%">Orozco, Lorena</style></author><author><style face="normal" font="default" size="100%">Altshuler, David M</style></author><author><style face="normal" font="default" size="100%">Schreiber, Stuart L</style></author><author><style face="normal" font="default" size="100%">Florez, Jose C</style></author><author><style face="normal" font="default" size="100%">Jacobs, Suzanne B R</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">MEDIA Consortium</style></author><author><style face="normal" font="default" size="100%">SIGMA T2D Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Basigin</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Membrane</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosomes, Human, Pair 17</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes Mellitus, Type 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Knockdown Techniques</style></keyword><keyword><style  face="normal" font="default" size="100%">Haplotypes</style></keyword><keyword><style  face="normal" font="default" size="100%">Hepatocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Heterozygote</style></keyword><keyword><style  face="normal" font="default" size="100%">Histone Code</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Liver</style></keyword><keyword><style  face="normal" font="default" size="100%">Models, Molecular</style></keyword><keyword><style  face="normal" font="default" size="100%">Monocarboxylic Acid Transporters</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Jun 29</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">170</style></volume><pages><style face="normal" font="default" size="100%">199-212.e20</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. VIDEO ABSTRACT.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28666119?dopt=Abstract</style></custom1></record></records></xml>