<?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%">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%">Chun, Sung</style></author><author><style face="normal" font="default" size="100%">Imakaev, Maxim</style></author><author><style face="normal" font="default" size="100%">Hui, Daniel</style></author><author><style face="normal" font="default" size="100%">Patsopoulos, Nikolaos A</style></author><author><style face="normal" font="default" size="100%">Neale, Benjamin M</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author><author><style face="normal" font="default" size="100%">Sunyaev, Shamil R</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.</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%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Diabetes Mellitus, Type 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Genotype</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Linkage Disequilibrium</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%">Models, Genetic</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%">Polymorphism, Single Nucleotide</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07 02</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">107</style></volume><pages><style face="normal" font="default" size="100%">46-59</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.&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/32470373?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%">Ferraro, Nicole M</style></author><author><style face="normal" font="default" size="100%">Strober, Benjamin J</style></author><author><style face="normal" font="default" size="100%">Einson, Jonah</style></author><author><style face="normal" font="default" size="100%">Abell, Nathan S</style></author><author><style face="normal" font="default" size="100%">Aguet, François</style></author><author><style face="normal" font="default" size="100%">Barbeira, Alvaro N</style></author><author><style face="normal" font="default" size="100%">Brandt, Margot</style></author><author><style face="normal" font="default" size="100%">Bucan, Maja</style></author><author><style face="normal" font="default" size="100%">Castel, Stephane E</style></author><author><style face="normal" font="default" size="100%">Davis, Joe R</style></author><author><style face="normal" font="default" size="100%">Greenwald, Emily</style></author><author><style face="normal" font="default" size="100%">Hess, Gaelen T</style></author><author><style face="normal" font="default" size="100%">Hilliard, Austin T</style></author><author><style face="normal" font="default" size="100%">Kember, Rachel L</style></author><author><style face="normal" font="default" size="100%">Kotis, Bence</style></author><author><style face="normal" font="default" size="100%">Park, YoSon</style></author><author><style face="normal" font="default" size="100%">Peloso, Gina</style></author><author><style face="normal" font="default" size="100%">Ramdas, Shweta</style></author><author><style face="normal" font="default" size="100%">Scott, Alexandra J</style></author><author><style face="normal" font="default" size="100%">Smail, Craig</style></author><author><style face="normal" font="default" size="100%">Tsang, Emily K</style></author><author><style face="normal" font="default" size="100%">Zekavat, Seyedeh M</style></author><author><style face="normal" font="default" size="100%">Ziosi, Marcello</style></author><author><style face="normal" font="default" size="100%">Ardlie, Kristin G</style></author><author><style face="normal" font="default" size="100%">Assimes, Themistocles L</style></author><author><style face="normal" font="default" size="100%">Bassik, Michael C</style></author><author><style face="normal" font="default" size="100%">Brown, Christopher D</style></author><author><style face="normal" font="default" size="100%">Correa, Adolfo</style></author><author><style face="normal" font="default" size="100%">Hall, Ira</style></author><author><style face="normal" font="default" size="100%">Im, Hae Kyung</style></author><author><style face="normal" font="default" size="100%">Li, Xin</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Mohammadi, Pejman</style></author><author><style face="normal" font="default" size="100%">Montgomery, Stephen B</style></author><author><style face="normal" font="default" size="100%">Battle, Alexis</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">TOPMed Lipids Working Group</style></author><author><style face="normal" font="default" size="100%">GTEx Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Transcriptomic signatures across human tissues identify functional rare genetic variation.</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Science</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome, Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Multifactorial Inheritance</style></keyword><keyword><style  face="normal" font="default" size="100%">Organ Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 09 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">369</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Rare genetic variants are abundant across the human genome, and identifying their function and phenotypic impact is a major challenge. Measuring aberrant gene expression has aided in identifying functional, large-effect rare variants (RVs). Here, we expanded detection of genetically driven transcriptome abnormalities by analyzing gene expression, allele-specific expression, and alternative splicing from multitissue RNA-sequencing data, and demonstrate that each signal informs unique classes of RVs. We developed Watershed, a probabilistic model that integrates multiple genomic and transcriptomic signals to predict variant function, validated these predictions in additional cohorts and through experimental assays, and used them to assess RVs in the UK Biobank, the Million Veterans Program, and the Jackson Heart Study. Our results link thousands of RVs to diverse molecular effects and provide evidence to associate RVs affecting the transcriptome with human traits.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6509</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32913073?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Wang, Minxian</style></author><author><style face="normal" font="default" size="100%">Menon, Ramesh</style></author><author><style face="normal" font="default" size="100%">Mishra, Sanghamitra</style></author><author><style face="normal" font="default" size="100%">Patel, Aniruddh P</style></author><author><style face="normal" font="default" size="100%">Chaffin, Mark</style></author><author><style face="normal" font="default" size="100%">Tanneeru, Deepak</style></author><author><style face="normal" font="default" size="100%">Deshmukh, Manjari</style></author><author><style face="normal" font="default" size="100%">Mathew, Oshin</style></author><author><style face="normal" font="default" size="100%">Apte, Sanika</style></author><author><style face="normal" font="default" size="100%">Devanboo, Christina S</style></author><author><style face="normal" font="default" size="100%">Sundaram, Sumathi</style></author><author><style face="normal" font="default" size="100%">Lakshmipathy, Praveena</style></author><author><style face="normal" font="default" size="100%">Murugan, Sakthivel</style></author><author><style face="normal" font="default" size="100%">Sharma, Krishna Kumar</style></author><author><style face="normal" font="default" size="100%">Rajendran, Karthikeyan</style></author><author><style face="normal" font="default" size="100%">Santhosh, Sam</style></author><author><style face="normal" font="default" size="100%">Thachathodiyl, Rajesh</style></author><author><style face="normal" font="default" size="100%">Ahamed, Hisham</style></author><author><style face="normal" font="default" size="100%">Balegadde, Aniketh Vijay</style></author><author><style face="normal" font="default" size="100%">Alexander, Thomas</style></author><author><style face="normal" font="default" size="100%">Swaminathan, Krishnan</style></author><author><style face="normal" font="default" size="100%">Gupta, Rajeev</style></author><author><style face="normal" font="default" size="100%">Mullasari, Ajit S</style></author><author><style face="normal" font="default" size="100%">Sigamani, Alben</style></author><author><style face="normal" font="default" size="100%">Kanchi, Muralidhar</style></author><author><style face="normal" font="default" size="100%">Peterson, Andrew S</style></author><author><style face="normal" font="default" size="100%">Butterworth, Adam S</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Di Angelantonio, Emanuele</style></author><author><style face="normal" font="default" size="100%">Naheed, Aliya</style></author><author><style face="normal" font="default" size="100%">Inouye, Michael</style></author><author><style face="normal" font="default" size="100%">Chowdhury, Rajiv</style></author><author><style face="normal" font="default" size="100%">Vedam, Ramprasad L</style></author><author><style face="normal" font="default" size="100%">Kathiresan, Sekar</style></author><author><style face="normal" font="default" size="100%">Gupta, Ravi</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians.</style></title><secondary-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Am Coll Cardiol</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Bangladesh</style></keyword><keyword><style  face="normal" font="default" size="100%">Case-Control Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Coronary Artery Disease</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">India</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Multifactorial Inheritance</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 08 11</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">76</style></volume><pages><style face="normal" font="default" size="100%">703-714</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;This analysis used summary statistics from a prior genome-wide association study to derive a new GPS for South Asians.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;This GPS was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPS reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPS reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The GPS, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p &lt; 0.001 for each). Next, individuals of the Indian case-control study were projected onto static reference distributions, observing an OR/SD of 1.66 (p &lt; 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPS distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p &lt; 0.05 for each).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;The new GPS has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/32762905?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Young, Robin</style></author><author><style face="normal" font="default" size="100%">Stitziel, Nathan O</style></author><author><style face="normal" font="default" size="100%">Padmanabhan, Sandosh</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%">Sartori, Samantha</style></author><author><style face="normal" font="default" size="100%">Fuster, Valentin</style></author><author><style face="normal" font="default" size="100%">Reilly, Dermot F</style></author><author><style face="normal" font="default" size="100%">Butterworth, Adam</style></author><author><style face="normal" font="default" size="100%">Rader, Daniel J</style></author><author><style face="normal" font="default" size="100%">Ford, Ian</style></author><author><style face="normal" font="default" size="100%">Sattar, Naveed</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%">Polygenic Risk Score Identifies Subgroup With Higher Burden of Atherosclerosis and Greater Relative Benefit From Statin Therapy in the Primary Prevention Setting.</style></title><secondary-title><style face="normal" font="default" size="100%">Circulation</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Circulation</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">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%">Atherosclerosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Cohort Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Cost of Illness</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Hydroxymethylglutaryl-CoA Reductase Inhibitors</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%">Primary Prevention</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</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 May 30</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">135</style></volume><pages><style face="normal" font="default" size="100%">2091-2101</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;Relative risk reduction with statin therapy has been consistent across nearly all subgroups studied to date. However, in analyses of 2 randomized controlled primary prevention trials (ASCOT [Anglo-Scandinavian Cardiac Outcomes Trial-Lipid-Lowering Arm] and JUPITER [Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin]), statin therapy led to a greater relative risk reduction among a subgroup at high genetic risk. Here, we aimed to confirm this observation in a third primary prevention randomized controlled trial. In addition, we assessed whether those at high genetic risk had a greater burden of subclinical coronary atherosclerosis.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We studied participants from a randomized controlled trial of primary prevention with statin therapy (WOSCOPS [West of Scotland Coronary Prevention Study]; n=4910) and 2 observational cohort studies (CARDIA [Coronary Artery Risk Development in Young Adults] and BioImage; n=1154 and 4392, respectively). For each participant, we calculated a polygenic risk score derived from up to 57 common DNA sequence variants previously associated with coronary heart disease. We compared the relative efficacy of statin therapy in those at high genetic risk (top quintile of polygenic risk score) versus all others (WOSCOPS), as well as the association between the polygenic risk score and coronary artery calcification (CARDIA) and carotid artery plaque burden (BioImage).&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;Among WOSCOPS trial participants at high genetic risk, statin therapy was associated with a relative risk reduction of 44% (95% confidence interval [CI], 22-60; &lt;0.001), whereas in all others, the relative risk reduction was 24% (95% CI, 8-37; =0.004) despite similar low-density lipoprotein cholesterol lowering. In a study-level meta-analysis across the WOSCOPS, ASCOT, and JUPITER primary prevention, relative risk reduction in those at high genetic risk was 46% versus 26% in all others ( for heterogeneity=0.05). Across all 3 studies, the absolute risk reduction with statin therapy was 3.6% (95% CI, 2.0-5.1) among those in the high genetic risk group and 1.3% (95% CI, 0.6-1.9) in all others. Each 1-SD increase in the polygenic risk score was associated with 1.32-fold (95% CI, 1.04-1.68) greater likelihood of having coronary artery calcification and 9.7% higher (95% CI, 2.2-17.8) burden of carotid plaque.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Those at high genetic risk have a greater burden of subclinical atherosclerosis and derive greater relative and absolute benefit from statin therapy to prevent a first coronary heart disease event.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CLINICAL TRIAL REGISTRATION: &lt;/b&gt;URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00738725 (BioImage) and NCT00005130 (CARDIA). WOSCOPS was carried out and completed before the requirement for clinical trial registration.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">22</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28223407?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>