<?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%">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%">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%">Niestroj, Lisa-Marie</style></author><author><style face="normal" font="default" size="100%">Perez-Palma, Eduardo</style></author><author><style face="normal" font="default" size="100%">Howrigan, Daniel P</style></author><author><style face="normal" font="default" size="100%">Zhou, Yadi</style></author><author><style face="normal" font="default" size="100%">Cheng, Feixiong</style></author><author><style face="normal" font="default" size="100%">Saarentaus, Elmo</style></author><author><style face="normal" font="default" size="100%">Nürnberg, Peter</style></author><author><style face="normal" font="default" size="100%">Stevelink, Remi</style></author><author><style face="normal" font="default" size="100%">Daly, Mark J</style></author><author><style face="normal" font="default" size="100%">Palotie, Aarno</style></author><author><style face="normal" font="default" size="100%">Lal, Dennis</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">Epi25 Collaborative</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Epilepsy subtype-specific copy number burden observed in a genome-wide study of 17 458 subjects.</style></title><secondary-title><style face="normal" font="default" size="100%">Brain</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Brain</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DNA Copy Number Variations</style></keyword><keyword><style  face="normal" font="default" size="100%">Epilepsy</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%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</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 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">143</style></volume><pages><style face="normal" font="default" size="100%">2106-2118</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Cytogenic testing is routinely applied in most neurological centres for severe paediatric epilepsies. However, which characteristics of copy number variants (CNVs) confer most epilepsy risk and which epilepsy subtypes carry the most CNV burden, have not been explored on a genome-wide scale. Here, we present the largest CNV investigation in epilepsy to date with 10 712 European epilepsy cases and 6746 ancestry-matched controls. Patients with genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, and developmental and epileptic encephalopathy were included. All samples were processed with the same technology and analysis pipeline. All investigated epilepsy types, including lesional focal epilepsy patients, showed an increase in CNV burden in at least one tested category compared to controls. However, we observed striking differences in CNV burden across epilepsy types and investigated CNV categories. Genetic generalized epilepsy patients have the highest CNV burden in all categories tested, followed by developmental and epileptic encephalopathy patients. Both epilepsy types also show association for deletions covering genes intolerant for truncating variants. Genome-wide CNV breakpoint association showed not only significant loci for genetic generalized and developmental and epileptic encephalopathy patients but also for lesional focal epilepsy patients. With a 34-fold risk for developing genetic generalized epilepsy, we show for the first time that the established epilepsy-associated 15q13.3 deletion represents the strongest risk CNV for genetic generalized epilepsy across the whole genome. Using the human interactome, we examined the largest connected component of the genes overlapped by CNVs in the four epilepsy types. We observed that genetic generalized epilepsy and non-acquired focal epilepsy formed disease modules. In summary, we show that in all common epilepsy types, 1.5-3% of patients carry epilepsy-associated CNVs. The characteristics of risk CNVs vary tremendously across and within epilepsy types. Thus, we advocate genome-wide genomic testing to identify all disease-associated types of CNVs.&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/32568404?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%">Winkler, Thomas W</style></author><author><style face="normal" font="default" size="100%">Grassmann, Felix</style></author><author><style face="normal" font="default" size="100%">Brandl, Caroline</style></author><author><style face="normal" font="default" size="100%">Kiel, Christina</style></author><author><style face="normal" font="default" size="100%">Günther, Felix</style></author><author><style face="normal" font="default" size="100%">Strunz, Tobias</style></author><author><style face="normal" font="default" size="100%">Weidner, Lorraine</style></author><author><style face="normal" font="default" size="100%">Zimmermann, Martina E</style></author><author><style face="normal" font="default" size="100%">Korb, Christina A</style></author><author><style face="normal" font="default" size="100%">Poplawski, Alicia</style></author><author><style face="normal" font="default" size="100%">Schuster, Alexander K</style></author><author><style face="normal" font="default" size="100%">Müller-Nurasyid, Martina</style></author><author><style face="normal" font="default" size="100%">Peters, Annette</style></author><author><style face="normal" font="default" size="100%">Rauscher, Franziska G</style></author><author><style face="normal" font="default" size="100%">Elze, Tobias</style></author><author><style face="normal" font="default" size="100%">Horn, Katrin</style></author><author><style face="normal" font="default" size="100%">Scholz, Markus</style></author><author><style face="normal" font="default" size="100%">Cañadas-Garre, Marisa</style></author><author><style face="normal" font="default" size="100%">McKnight, Amy Jayne</style></author><author><style face="normal" font="default" size="100%">Quinn, Nicola</style></author><author><style face="normal" font="default" size="100%">Hogg, Ruth E</style></author><author><style face="normal" font="default" size="100%">Küchenhoff, Helmut</style></author><author><style face="normal" font="default" size="100%">Heid, Iris M</style></author><author><style face="normal" font="default" size="100%">Stark, Klaus J</style></author><author><style face="normal" font="default" size="100%">Weber, Bernhard H F</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Med Genomics</style></secondary-title><alt-title><style face="normal" font="default" size="100%">BMC Med Genomics</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Loci</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%">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%">Macular Degeneration</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 08 26</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">120</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;Advanced age-related macular degeneration (AMD) is a leading cause of blindness. While around half of the genetic contribution to advanced AMD has been uncovered, little is known about the genetic architecture of early AMD.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;To identify genetic factors for early AMD, we conducted a genome-wide association study (GWAS) meta-analysis (14,034 cases, 91,214 controls, 11 sources of data including the International AMD Genomics Consortium, IAMDGC, and UK Biobank, UKBB). We ascertained early AMD via color fundus photographs by manual grading for 10 sources and via an automated machine learning approach for &gt; 170,000 photographs from UKBB. We searched for early AMD loci via GWAS and via a candidate approach based on 14 previously suggested early AMD variants.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Altogether, we identified 10 independent loci with statistical significance for early AMD: (i) 8 from our GWAS with genome-wide significance (P &lt; 5 × 10), (ii) one previously suggested locus with experiment-wise significance (P &lt; 0.05/14) in our non-overlapping data and with genome-wide significance when combining the reported and our non-overlapping data (together 17,539 cases, 105,395 controls), and (iii) one further previously suggested locus with experiment-wise significance in our non-overlapping data. Of these 10 identified loci, 8 were novel and 2 known for early AMD. Most of the 10 loci overlapped with known advanced AMD loci (near ARMS2/HTRA1, CFH, C2, C3, CETP, TNFRSF10A, VEGFA, APOE), except two that have not yet been identified with statistical significance for any AMD. Among the 17 genes within these two loci, in-silico functional annotation suggested CD46 and TYR as the most likely responsible genes. Presence or absence of an early AMD effect distinguished the known pathways of advanced AMD genetics (complement/lipid pathways versus extracellular matrix metabolism).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Our GWAS on early AMD identified novel loci, highlighted shared and distinct genetics between early and advanced AMD and provides insights into AMD etiology. Our data provide a resource comparable in size to the existing IAMDGC data on advanced AMD genetics enabling a joint view. The biological relevance of this joint view is underscored by the ability of early AMD effects to differentiate the major pathways for advanced AMD.&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/32843070?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%">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%">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%">Yin, Jiani</style></author><author><style face="normal" font="default" size="100%">Chun, Chun-An</style></author><author><style face="normal" font="default" size="100%">Zavadenko, Nikolay N</style></author><author><style face="normal" font="default" size="100%">Pechatnikova, Natalia L</style></author><author><style face="normal" font="default" size="100%">Naumova, Oxana Yu</style></author><author><style face="normal" font="default" size="100%">Doddapaneni, Harsha V</style></author><author><style face="normal" font="default" size="100%">Hu, Jianhong</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Schaaf, Christian P</style></author><author><style face="normal" font="default" size="100%">Grigorenko, Elena L</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Next Generation Sequencing of 134 Children with Autism Spectrum Disorder and Regression.</style></title><secondary-title><style face="normal" font="default" size="100%">Genes (Basel)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genes (Basel)</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Autism Spectrum Disorder</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%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Disease Progression</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation</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%">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%">Infant</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation</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 25</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Approximately 30% of individuals with autism spectrum disorder (ASD) experience developmental regression, the etiology of which remains largely unknown. We performed a complete literature search and identified 47 genes that had been implicated in such cases. We sequenced these genes in a preselected cohort of 134 individuals with regressive autism. In total, 16 variants in 12 genes with evidence supportive of pathogenicity were identified. They were classified as variants of uncertain significance based on ACMG standards and guidelines. Among these were recurring variants in  and , variants in genes that were linked to syndromic forms of ASD (, , , , , and ), and variants in the form of oligogenic heterozygosity (, , and ).&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/32722525?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%">Grenn, Francis P</style></author><author><style face="normal" font="default" size="100%">Kim, Jonggeol J</style></author><author><style face="normal" font="default" size="100%">Makarious, Mary B</style></author><author><style face="normal" font="default" size="100%">Iwaki, Hirotaka</style></author><author><style face="normal" font="default" size="100%">Illarionova, Anastasia</style></author><author><style face="normal" font="default" size="100%">Brolin, Kajsa</style></author><author><style face="normal" font="default" size="100%">Kluss, Jillian H</style></author><author><style face="normal" font="default" size="100%">Schumacher-Schuh, Artur F</style></author><author><style face="normal" font="default" size="100%">Leonard, Hampton</style></author><author><style face="normal" font="default" size="100%">Faghri, Faraz</style></author><author><style face="normal" font="default" size="100%">Billingsley, Kimberley</style></author><author><style face="normal" font="default" size="100%">Krohn, Lynne</style></author><author><style face="normal" font="default" size="100%">Hall, Ashley</style></author><author><style face="normal" font="default" size="100%">Diez-Fairen, Monica</style></author><author><style face="normal" font="default" size="100%">Periñán, Maria Teresa</style></author><author><style face="normal" font="default" size="100%">Foo, Jia Nee</style></author><author><style face="normal" font="default" size="100%">Sandor, Cynthia</style></author><author><style face="normal" font="default" size="100%">Webber, Caleb</style></author><author><style face="normal" font="default" size="100%">Fiske, Brian K</style></author><author><style face="normal" font="default" size="100%">Gibbs, J Raphael</style></author><author><style face="normal" font="default" size="100%">Nalls, Mike A</style></author><author><style face="normal" font="default" size="100%">Singleton, Andrew B</style></author><author><style face="normal" font="default" size="100%">Bandres-Ciga, Sara</style></author><author><style face="normal" font="default" size="100%">Reed, Xylena</style></author><author><style face="normal" font="default" size="100%">Blauwendraat, Cornelis</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">International Parkinson's Disease Genomics Consortium (IPDGC)</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">The Parkinson's Disease Genome-Wide Association Study Locus Browser.</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%">Age of Onset</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%">Neurodegenerative Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Parkinson Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk 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 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">35</style></volume><pages><style face="normal" font="default" size="100%">2056-2067</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;Parkinson's disease (PD) is a neurodegenerative disease with an often complex component identifiable by genome-wide association studies. The most recent large-scale PD genome-wide association studies have identified more than 90 independent risk variants for PD risk and progression across more than 80 genomic regions. One major challenge in current genomics is the identification of the causal gene(s) and variant(s) at each genome-wide association study locus. The objective of the current study was to create a tool that would display data for relevant PD risk loci and provide guidance with the prioritization of causal genes and potential mechanisms at each locus.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We included all significant genome-wide signals from multiple recent PD genome-wide association studies including themost recent PD risk genome-wide association study, age-at-onset genome-wide association study, progression genome-wide association study, and Asian population PD risk genome-wide association study. We gathered data for all genes 1 Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Multiple databases were queried for each gene to collect additional causal data.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We created a PD genome-wide association study browser tool (https://pdgenetics.shinyapps.io/GWASBrowser/) to assist the PD research community with the prioritization of genes for follow-up functional studies to identify potential therapeutic targets.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Our PD genome-wide association study browser tool provides users with a useful method of identifying potential causal genes at all known PD risk loci from large-scale PD genome-wide association studies. We plan to update this tool with new relevant data as sample sizes increase and new PD risk loci are discovered. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.&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/32864809?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%">Wang, Minxian</style></author><author><style face="normal" font="default" size="100%">Homburger, Julian R</style></author><author><style face="normal" font="default" size="100%">Patel, Aniruddh P</style></author><author><style face="normal" font="default" size="100%">Bick, Alexander G</style></author><author><style face="normal" font="default" size="100%">Neben, Cynthia L</style></author><author><style face="normal" font="default" size="100%">Lai, Carmen</style></author><author><style face="normal" font="default" size="100%">Brockman, Deanna</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%">Cassa, Christopher A</style></author><author><style face="normal" font="default" size="100%">Lebo, Matthew</style></author><author><style face="normal" font="default" size="100%">Ng, Kenney</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author><author><style face="normal" font="default" size="100%">Zhou, Alicia Y</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%">Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions.</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%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Breast Neoplasms</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Colorectal Neoplasms</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, Human</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%">Multifactorial Inheritance</style></keyword><keyword><style  face="normal" font="default" size="100%">Odds Ratio</style></keyword><keyword><style  face="normal" font="default" size="100%">Penetrance</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk 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 08 20</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">3635</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 variation can predispose to disease both through (i) monogenic risk variants that disrupt a physiologic pathway with large effect on disease and (ii) polygenic risk that involves many variants of small effect in different pathways. Few studies have explored the interplay between monogenic and polygenic risk. Here, we study 80,928 individuals to examine whether polygenic background can modify penetrance of disease in tier 1 genomic conditions - familial hypercholesterolemia, hereditary breast and ovarian cancer, and Lynch syndrome. Among carriers of a monogenic risk variant, we estimate substantial gradients in disease risk based on polygenic background - the probability of disease by age 75 years ranged from 17% to 78% for coronary artery disease, 13% to 76% for breast cancer, and 11% to 80% for colon cancer. We propose that accounting for polygenic background is likely to increase accuracy of risk estimation for individuals who inherit a monogenic risk variant.&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/32820175?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, Chang</style></author><author><style face="normal" font="default" size="100%">Grove, Megan L</style></author><author><style face="normal" font="default" size="100%">Yu, Bing</style></author><author><style face="normal" font="default" size="100%">Jones, Barbara C</style></author><author><style face="normal" font="default" size="100%">Morrison, Alanna</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Liu, Xiaoming</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic variants in microRNA genes and targets associated with cardiovascular disease risk factors in the African-American population.</style></title><secondary-title><style face="normal" font="default" size="100%">Hum Genet</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Hum Genet</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">3' Untranslated Regions</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Black or African American</style></keyword><keyword><style  face="normal" font="default" size="100%">Cardiovascular Diseases</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%">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%">MicroRNAs</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</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 Jan</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">137</style></volume><pages><style face="normal" font="default" size="100%">85-94</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 purpose of this study is to identify microRNA (miRNA) related polymorphism, including single nucleotide variants (SNVs) in mature miRNA-encoding sequences or in miRNA-target sites, and their association with cardiovascular disease (CVD) risk factors in African-American population. To achieve our objective, we examined 1900 African-Americans from the Atherosclerosis Risk in Communities study using SNVs identified from whole-genome sequencing data. A total of 971 SNVs found in 726 different mature miRNA-encoding sequences and 16,057 SNVs found in the three prime untranslated region (3'UTR) of 3647 protein-coding genes were identified and interrogated their associations with 17 CVD risk factors. Using single-variant-based approach, we found 5 SNVs in miRNA-encoding sequences to be associated with serum Lipoprotein(a) [Lp(a)], high-density lipoprotein (HDL) or triglycerides, and 2 SNVs in miRNA-target sites to be associated with Lp(a) and HDL, all with false discovery rates of 5%. Using a gene-based approach, we identified 3 pairs of associations between gene NSD1 and platelet count, gene HSPA4L and cardiac troponin T, and gene AHSA2 and magnesium. We successfully validated the association between a variant specific to African-American population, NR_039880.1:n.18A&gt;C, in mature hsa-miR-4727-5p encoding sequence and serum HDL level in an independent sample of 2135 African-Americans. Our study provided candidate miRNAs and their targets for further investigation of their potential contribution to ethnic disparities in CVD risk factors.&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/29264654?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%">Kim-Hellmuth, Sarah</style></author><author><style face="normal" font="default" size="100%">Bechheim, Matthias</style></author><author><style face="normal" font="default" size="100%">Pütz, Benno</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Nédélec, Yohann</style></author><author><style face="normal" font="default" size="100%">Giangreco, Nicholas</style></author><author><style face="normal" font="default" size="100%">Becker, Jessica</style></author><author><style face="normal" font="default" size="100%">Kaiser, Vera</style></author><author><style face="normal" font="default" size="100%">Fricker, Nadine</style></author><author><style face="normal" font="default" size="100%">Beier, Esther</style></author><author><style face="normal" font="default" size="100%">Boor, Peter</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Nöthen, Markus M</style></author><author><style face="normal" font="default" size="100%">Barreiro, Luis B</style></author><author><style face="normal" font="default" size="100%">Pickrell, Joseph K</style></author><author><style face="normal" font="default" size="100%">Müller-Myhsok, Bertram</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Schumacher, Johannes</style></author><author><style face="normal" font="default" size="100%">Hornung, Veit</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic regulatory effects modified by immune activation contribute to autoimmune disease associations.</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%">Acetylmuramyl-Alanyl-Isoglutamine</style></keyword><keyword><style  face="normal" font="default" size="100%">Adjuvants, Immunologic</style></keyword><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%">Autoimmune Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</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 Predisposition to Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Healthy Volunteers</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Indicators and Reagents</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipopolysaccharides</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Monocytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Regulatory Sequences, Nucleic Acid</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Double-Stranded</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</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 16</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">266</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 immune system plays a major role in human health and disease, and understanding genetic causes of interindividual variability of immune responses is vital. Here, we isolate monocytes from 134 genotyped individuals, stimulate these cells with three defined microbe-associated molecular patterns (LPS, MDP, and 5'-ppp-dsRNA), and profile the transcriptomes at three time points. Mapping expression quantitative trait loci (eQTL), we identify 417 response eQTLs (reQTLs) with varying effects between conditions. We characterize the dynamics of genetic regulation on early and late immune response and observe an enrichment of reQTLs in distal cis-regulatory elements. In addition, reQTLs are enriched for recent positive selection with an evolutionary trend towards enhanced immune response. Finally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response than constant eQTLs in GWAS signals of several autoimmune diseases. This demonstrates the importance of infectious stimuli in modifying genetic predisposition to disease.Insight into the genetic influence on the immune response is important for the understanding of interindividual variability in human pathologies. Here, the authors generate transcriptome data from human blood monocytes stimulated with various immune stimuli and provide a time-resolved response eQTL map.&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/28814792?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%">Willems, Thomas</style></author><author><style face="normal" font="default" size="100%">Zielinski, Dina</style></author><author><style face="normal" font="default" size="100%">Yuan, Jie</style></author><author><style face="normal" font="default" size="100%">Gordon, Assaf</style></author><author><style face="normal" font="default" size="100%">Gymrek, Melissa</style></author><author><style face="normal" font="default" size="100%">Erlich, Yaniv</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome-wide profiling of heritable and de novo STR variations.</style></title><secondary-title><style face="normal" font="default" size="100%">Nat Methods</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Nat Methods</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Algorithms</style></keyword><keyword><style  face="normal" font="default" size="100%">Chromosome Mapping</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA Fingerprinting</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%">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%">Microsatellite Repeats</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Alignment</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, DNA</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 Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">590-592</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Short tandem repeats (STRs) are highly variable elements that play a pivotal role in multiple genetic diseases, population genetics applications, and forensic casework. However, it has proven problematic to genotype STRs from high-throughput sequencing data. Here, we describe HipSTR, a novel haplotype-based method for robustly genotyping and phasing STRs from Illumina sequencing data, and we report a genome-wide analysis and validation of de novo STR mutations. HipSTR is freely available at https://hipstr-tool.github.io/HipSTR.&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/28436466?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%">Stitziel, Nathan O</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Human genetic insights into lipoproteins and risk of cardiometabolic disease.</style></title><secondary-title><style face="normal" font="default" size="100%">Curr Opin Lipidol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Curr Opin Lipidol</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%">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%">Lipoproteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk</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%">28</style></volume><pages><style face="normal" font="default" size="100%">113-119</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;PURPOSE OF REVIEW: &lt;/b&gt;Human genetic studies have been successfully used to identify genes and pathways relevant to human biology. Using genetic instruments composed of loci associated with human lipid traits, recent studies have begun to clarify the causal role of major lipid fractions in risk of cardiometabolic disease.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RECENT FINDINGS: &lt;/b&gt;The causal relationship between LDL cholesterol and coronary disease has been firmly established. Of the remaining two major fractions, recent studies have found that HDL cholesterol is not likely to be a causal particle in atherogenesis, and have instead shifted the causal focus to triglyceride-rich lipoproteins. Subsequent results are refining this view to suggest that triglycerides themselves might not be causal, but instead may be a surrogate for the causal cholesterol content within this fraction. Other studies have used a similar approach to address the association between lipid fractions and risk of type 2 diabetes. Beyond genetic variation in the target of statin medications, reduced LDL cholesterol associated with multiple genes encoding current or prospective drug targets associated with increased diabetic risk. In addition, genetically lower HDL cholesterol and genetically lower triglycerides both appear to increase risk of type 2 diabetes.&lt;/p&gt;&lt;p&gt;&lt;b&gt;SUMMARY: &lt;/b&gt;Results of these and future human genetic studies are positioned to provide substantive insights into the causal relationship between lipids and human disease, and should highlight mechanisms with important implications for our understanding of human biology and future lipid-altering therapeutic development.&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/28059951?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%">Lappalainen, Tuuli</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Concerted Genetic Function in Blood Traits.</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%">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%">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%">Phenotype</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%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Nov 17</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">167</style></volume><pages><style face="normal" font="default" size="100%">1167-1169</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 hematopoietic system plays a major role in human health. Two studies by Astle et al. and Chen et al. published in this issue of Cell use genome-wide association and functional genomics approaches to provide deep insights into the role of genetic variants in hematological traits. We discuss these discoveries and future strategies toward completing our understanding of the genetic basis for variation in human traits.&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/27863238?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%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Drake, Isabel</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Bick, Alexander G</style></author><author><style face="normal" font="default" size="100%">Cook, Nancy R</style></author><author><style face="normal" font="default" size="100%">Chasman, Daniel I</style></author><author><style face="normal" font="default" size="100%">Baber, Usman</style></author><author><style face="normal" font="default" size="100%">Mehran, Roxana</style></author><author><style face="normal" font="default" size="100%">Rader, Daniel J</style></author><author><style face="normal" font="default" size="100%">Fuster, Valentin</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Melander, Olle</style></author><author><style face="normal" font="default" size="100%">Orho-Melander, Marju</style></author><author><style face="normal" font="default" size="100%">Ridker, Paul M</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%">Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease.</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%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Cross-Sectional Studies</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%">Healthy Lifestyle</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%">Patient Compliance</style></keyword><keyword><style  face="normal" font="default" size="100%">Polymorphism, Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Dec 15</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">375</style></volume><pages><style face="normal" font="default" size="100%">2349-2358</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;Both genetic and lifestyle factors contribute to individual-level risk of coronary artery disease. The extent to which increased genetic risk can be offset by a healthy lifestyle is unknown.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Using a polygenic score of DNA sequence polymorphisms, we quantified genetic risk for coronary artery disease in three prospective cohorts - 7814 participants in the Atherosclerosis Risk in Communities (ARIC) study, 21,222 in the Women's Genome Health Study (WGHS), and 22,389 in the Malmö Diet and Cancer Study (MDCS) - and in 4260 participants in the cross-sectional BioImage Study for whom genotype and covariate data were available. We also determined adherence to a healthy lifestyle among the participants using a scoring system consisting of four factors: no current smoking, no obesity, regular physical activity, and a healthy diet.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The relative risk of incident coronary events was 91% higher among participants at high genetic risk (top quintile of polygenic scores) than among those at low genetic risk (bottom quintile of polygenic scores) (hazard ratio, 1.91; 95% confidence interval [CI], 1.75 to 2.09). A favorable lifestyle (defined as at least three of the four healthy lifestyle factors) was associated with a substantially lower risk of coronary events than an unfavorable lifestyle (defined as no or only one healthy lifestyle factor), regardless of the genetic risk category. Among participants at high genetic risk, a favorable lifestyle was associated with a 46% lower relative risk of coronary events than an unfavorable lifestyle (hazard ratio, 0.54; 95% CI, 0.47 to 0.63). This finding corresponded to a reduction in the standardized 10-year incidence of coronary events from 10.7% for an unfavorable lifestyle to 5.1% for a favorable lifestyle in ARIC, from 4.6% to 2.0% in WGHS, and from 8.2% to 5.3% in MDCS. In the BioImage Study, a favorable lifestyle was associated with significantly less coronary-artery calcification within each genetic risk category.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Across four studies involving 55,685 participants, genetic and lifestyle factors were independently associated with susceptibility to coronary artery disease. Among participants at high genetic risk, a favorable lifestyle was associated with a nearly 50% lower relative risk of coronary artery disease than was an unfavorable lifestyle. (Funded by the National Institutes of Health and others.).&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">24</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/27959714?dopt=Abstract</style></custom1></record></records></xml>