<?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%">Kasela, Silva</style></author><author><style face="normal" font="default" size="100%">Ortega, Victor E</style></author><author><style face="normal" font="default" size="100%">Martorella, Molly</style></author><author><style face="normal" font="default" size="100%">Garudadri, Suresh</style></author><author><style face="normal" font="default" size="100%">Nguyen, Jenna</style></author><author><style face="normal" font="default" size="100%">Ampleford, Elizabeth</style></author><author><style face="normal" font="default" size="100%">Pasanen, Anu</style></author><author><style face="normal" font="default" size="100%">Nerella, Srilaxmi</style></author><author><style face="normal" font="default" size="100%">Buschur, Kristina L</style></author><author><style face="normal" font="default" size="100%">Barjaktarevic, Igor Z</style></author><author><style face="normal" font="default" size="100%">Barr, R Graham</style></author><author><style face="normal" font="default" size="100%">Bleecker, Eugene R</style></author><author><style face="normal" font="default" size="100%">Bowler, Russell P</style></author><author><style face="normal" font="default" size="100%">Comellas, Alejandro P</style></author><author><style face="normal" font="default" size="100%">Cooper, Christopher B</style></author><author><style face="normal" font="default" size="100%">Couper, David J</style></author><author><style face="normal" font="default" size="100%">Criner, Gerard J</style></author><author><style face="normal" font="default" size="100%">Curtis, Jeffrey L</style></author><author><style face="normal" font="default" size="100%">Han, MeiLan K</style></author><author><style face="normal" font="default" size="100%">Hansel, Nadia N</style></author><author><style face="normal" font="default" size="100%">Hoffman, Eric A</style></author><author><style face="normal" font="default" size="100%">Kaner, Robert J</style></author><author><style face="normal" font="default" size="100%">Krishnan, Jerry A</style></author><author><style face="normal" font="default" size="100%">Martinez, Fernando J</style></author><author><style face="normal" font="default" size="100%">McDonald, Merry-Lynn N</style></author><author><style face="normal" font="default" size="100%">Meyers, Deborah A</style></author><author><style face="normal" font="default" size="100%">Paine, Robert</style></author><author><style face="normal" font="default" size="100%">Peters, Stephen P</style></author><author><style face="normal" font="default" size="100%">Castro, Mario</style></author><author><style face="normal" font="default" size="100%">Denlinger, Loren C</style></author><author><style face="normal" font="default" size="100%">Erzurum, Serpil C</style></author><author><style face="normal" font="default" size="100%">Fahy, John V</style></author><author><style face="normal" font="default" size="100%">Israel, Elliot</style></author><author><style face="normal" font="default" size="100%">Jarjour, Nizar N</style></author><author><style face="normal" font="default" size="100%">Levy, Bruce D</style></author><author><style face="normal" font="default" size="100%">Li, Xingnan</style></author><author><style face="normal" font="default" size="100%">Moore, Wendy C</style></author><author><style face="normal" font="default" size="100%">Wenzel, Sally E</style></author><author><style face="normal" font="default" size="100%">Zein, Joe</style></author><author><style face="normal" font="default" size="100%">Langelier, Charles</style></author><author><style face="normal" font="default" size="100%">Woodruff, Prescott G</style></author><author><style face="normal" font="default" size="100%">Lappalainen, Tuuli</style></author><author><style face="normal" font="default" size="100%">Christenson, Stephanie A</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">NHLBI SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)</style></author><author><style face="normal" font="default" size="100%">NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">Genetic and non-genetic factors affecting the expression of COVID-19-relevant genes in the large airway epithelium.</style></title><secondary-title><style face="normal" font="default" size="100%">Genome Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Genome Med</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged, 80 and over</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiotensin-Converting Enzyme 2</style></keyword><keyword><style  face="normal" font="default" size="100%">Asthma</style></keyword><keyword><style  face="normal" font="default" size="100%">Bronchi</style></keyword><keyword><style  face="normal" font="default" size="100%">Cardiovascular Diseases</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Variation</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Obesity</style></keyword><keyword><style  face="normal" font="default" size="100%">Pulmonary Disease, Chronic Obstructive</style></keyword><keyword><style  face="normal" font="default" size="100%">Quantitative Trait Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Respiratory Mucosa</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">Smoking</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 04 21</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">66</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;The large airway epithelial barrier provides one of the first lines of defense against respiratory viruses, including SARS-CoV-2 that causes COVID-19. Substantial inter-individual variability in individual disease courses is hypothesized to be partially mediated by the differential regulation of the genes that interact with the SARS-CoV-2 virus or are involved in the subsequent host response. Here, we comprehensively investigated non-genetic and genetic factors influencing COVID-19-relevant bronchial epithelial gene expression.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We analyzed RNA-sequencing data from bronchial epithelial brushings obtained from uninfected individuals. We related ACE2 gene expression to host and environmental factors in the SPIROMICS cohort of smokers with and without chronic obstructive pulmonary disease (COPD) and replicated these associations in two asthma cohorts, SARP and MAST. To identify airway biology beyond ACE2 binding that may contribute to increased susceptibility, we used gene set enrichment analyses to determine if gene expression changes indicative of a suppressed airway immune response observed early in SARS-CoV-2 infection are also observed in association with host factors. To identify host genetic variants affecting COVID-19 susceptibility in SPIROMICS, we performed expression quantitative trait (eQTL) mapping and investigated the phenotypic associations of the eQTL variants.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;We found that ACE2 expression was higher in relation to active smoking, obesity, and hypertension that are known risk factors of COVID-19 severity, while an association with interferon-related inflammation was driven by the truncated, non-binding ACE2 isoform. We discovered that expression patterns of a suppressed airway immune response to early SARS-CoV-2 infection, compared to other viruses, are similar to patterns associated with obesity, hypertension, and cardiovascular disease, which may thus contribute to a COVID-19-susceptible airway environment. eQTL mapping identified regulatory variants for genes implicated in COVID-19, some of which had pheWAS evidence for their potential role in respiratory infections.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;These data provide evidence that clinically relevant variation in the expression of COVID-19-related genes is associated with host factors, environmental exposures, and likely host genetic variation.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/33883027?dopt=Abstract</style></custom1></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">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%">Chen, Guo-Chong</style></author><author><style face="normal" font="default" size="100%">Chai, Jin Choul</style></author><author><style face="normal" font="default" size="100%">Yu, Bing</style></author><author><style face="normal" font="default" size="100%">Michelotti, Gregory A</style></author><author><style face="normal" font="default" size="100%">Grove, Megan L</style></author><author><style face="normal" font="default" size="100%">Fretts, Amanda M</style></author><author><style face="normal" font="default" size="100%">Daviglus, Martha L</style></author><author><style face="normal" font="default" size="100%">Garcia-Bedoya, Olga L</style></author><author><style face="normal" font="default" size="100%">Thyagarajan, Bharat</style></author><author><style face="normal" font="default" size="100%">Schneiderman, Neil</style></author><author><style face="normal" font="default" size="100%">Cai, Jianwen</style></author><author><style face="normal" font="default" size="100%">Kaplan, Robert C</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Qi, Qibin</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Serum sphingolipids and incident diabetes in a US population with high diabetes burden: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).</style></title><secondary-title><style face="normal" font="default" size="100%">Am J Clin Nutr</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Am J Clin Nutr</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%">Diabetes Mellitus</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Hispanic Americans</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%">Prospective Studies</style></keyword><keyword><style  face="normal" font="default" size="100%">Risk Factors</style></keyword><keyword><style  face="normal" font="default" size="100%">Sphingolipids</style></keyword><keyword><style  face="normal" font="default" size="100%">United States</style></keyword><keyword><style  face="normal" font="default" size="100%">Young Adult</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020 07 01</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">112</style></volume><pages><style face="normal" font="default" size="100%">57-65</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;Genetic or pharmacological inhibition of de novo sphingolipid synthases prevented diabetes in animal studies.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;We sought to evaluate prospective associations of serum sphingolipids with incident diabetes in a population-based cohort.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We included 2010 participants of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) aged 18-74 y who were free of diabetes and other major chronic diseases at baseline (2008-2011). Metabolomic profiling of fasting serum was performed using a global, untargeted approach. A total of 43 sphingolipids were quantified and, considering subclasses and chemical structures of individual species, 6 sphingolipid scores were constructed. Diabetes status was assessed using standard procedures including blood tests. Multivariable survey Poisson regressions were applied to estimate RR and 95% CI of incident diabetes associated with individual sphingolipids or sphingolipid scores.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;There were 224 incident cases of diabetes identified during, on average, 6 y of follow-up. After adjustment for socioeconomic and lifestyle factors, a ceramide score (RR Q4 versus Q1 = 2.40; 95% CI: 1.24, 4.65; P-trend = 0.003) and a score of sphingomyelins with fully saturated sphingoid-fatty acid pairs (RR Q4 versus Q1 = 3.15; 95% CI: 1.75, 5.67; P-trend &lt;0.001) both were positively associated with risk of diabetes, whereas scores of glycosylceramides, lactosylceramides, or other unsaturated sphingomyelins (even if having an SFA base) were not associated with risk of diabetes. After additional adjustment for numerous traditional risk factors (especially triglycerides), both associations were attenuated and only the saturated-sphingomyelin score remained associated with risk of diabetes (RR Q4 versus Q1 = 1.98; 95% CI: 1.09, 3.59; P-trend = 0.031).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Our findings suggest that a cluster of saturated sphingomyelins may be associated with elevated risk of diabetes beyond traditional risk factors, which needs to be verified in other population studies. This study was registered at clinicaltrials.gov as NCT02060344.&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/32469399?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%">Stitziel, Nathan O</style></author><author><style face="normal" font="default" size="100%">Khera, Amit V</style></author><author><style face="normal" font="default" size="100%">Wang, Xiao</style></author><author><style face="normal" font="default" size="100%">Bierhals, Andrew J</style></author><author><style face="normal" font="default" size="100%">Vourakis, A Christina</style></author><author><style face="normal" font="default" size="100%">Sperry, Alexandra E</style></author><author><style face="normal" font="default" size="100%">Natarajan, Pradeep</style></author><author><style face="normal" font="default" size="100%">Klarin, Derek</style></author><author><style face="normal" font="default" size="100%">Emdin, Connor A</style></author><author><style face="normal" font="default" size="100%">Zekavat, Seyedeh M</style></author><author><style face="normal" font="default" size="100%">Nomura, Akihiro</style></author><author><style face="normal" font="default" size="100%">Erdmann, Jeanette</style></author><author><style face="normal" font="default" size="100%">Schunkert, Heribert</style></author><author><style face="normal" font="default" size="100%">Samani, Nilesh J</style></author><author><style face="normal" font="default" size="100%">Kraus, William E</style></author><author><style face="normal" font="default" size="100%">Shah, Svati H</style></author><author><style face="normal" font="default" size="100%">Yu, Bing</style></author><author><style face="normal" font="default" size="100%">Boerwinkle, Eric</style></author><author><style face="normal" font="default" size="100%">Rader, Daniel J</style></author><author><style face="normal" font="default" size="100%">Gupta, Namrata</style></author><author><style face="normal" font="default" size="100%">Frossard, Philippe M</style></author><author><style face="normal" font="default" size="100%">Rasheed, Asif</style></author><author><style face="normal" font="default" size="100%">Danesh, John</style></author><author><style face="normal" font="default" size="100%">Lander, Eric S</style></author><author><style face="normal" font="default" size="100%">Gabriel, Stacey</style></author><author><style face="normal" font="default" size="100%">Saleheen, Danish</style></author><author><style face="normal" font="default" size="100%">Musunuru, Kiran</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%">PROMIS and Myocardial Infarction Genetics Consortium Investigators</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">ANGPTL3 Deficiency and Protection Against Coronary Artery Disease.</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%">Angiopoietin-Like Protein 3</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiopoietin-like Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Angiopoietins</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Atherosclerosis</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%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Lipids</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice, Inbred C57BL</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice, Knockout</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Mutation, Missense</style></keyword><keyword><style  face="normal" font="default" size="100%">Myocardial Infarction</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 Apr 25</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">69</style></volume><pages><style face="normal" font="default" size="100%">2054-2063</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;b&gt;BACKGROUND: &lt;/b&gt;Familial combined hypolipidemia, a Mendelian condition characterized by substantial reductions in all 3 major lipid fractions, is caused by mutations that inactivate the gene angiopoietin-like 3 (ANGPTL3). Whether ANGPTL3 deficiency reduces risk of coronary artery disease (CAD) is unknown.&lt;/p&gt;&lt;p&gt;&lt;b&gt;OBJECTIVES: &lt;/b&gt;The study goal was to leverage 3 distinct lines of evidence-a family that included individuals with complete (compound heterozygote) ANGPTL3 deficiency, a population based-study of humans with partial (heterozygote) ANGPTL3 deficiency, and biomarker levels in patients with myocardial infarction (MI)-to test whether ANGPTL3 deficiency is associated with lower risk for CAD.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;We assessed coronary atherosclerotic burden in 3 individuals with complete ANGPTL3 deficiency and 3 wild-type first-degree relatives using computed tomography angiography. In the population, ANGPTL3 loss-of-function (LOF) mutations were ascertained in up to 21,980 people with CAD and 158,200 control subjects. LOF mutations were defined as nonsense, frameshift, and splice-site variants, along with missense variants resulting in &lt;25% of wild-type ANGPTL3 activity in a mouse model. In a biomarker study, circulating ANGPTL3 concentration was measured in 1,493 people who presented with MI and 3,232 control subjects.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;The 3 individuals with complete ANGPTL3 deficiency showed no evidence of coronary atherosclerotic plaque. ANGPTL3 gene sequencing demonstrated that approximately 1 in 309 people was a heterozygous carrier for an LOF mutation. Compared with those without mutation, heterozygous carriers of ANGPTL3 LOF mutations demonstrated a 17% reduction in circulating triglycerides and a 12% reduction in low-density lipoprotein cholesterol. Carrier status was associated with a 34% reduction in odds of CAD (odds ratio: 0.66; 95% confidence interval: 0.44 to 0.98; p = 0.04). Individuals in the lowest tertile of circulating ANGPTL3 concentrations, compared with the highest, had reduced odds of MI (adjusted odds ratio: 0.65; 95% confidence interval: 0.55 to 0.77; p &lt; 0.001).&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;ANGPTL3 deficiency is associated with protection from CAD.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">16</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/28385496?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%">Sabo, Aniko</style></author><author><style face="normal" font="default" size="100%">Mishra, Pamela</style></author><author><style face="normal" font="default" size="100%">Dugan-Perez, Shannon</style></author><author><style face="normal" font="default" size="100%">Voruganti, V Saroja</style></author><author><style face="normal" font="default" size="100%">Kent, Jack W</style></author><author><style face="normal" font="default" size="100%">Kalra, Divya</style></author><author><style face="normal" font="default" size="100%">Cole, Shelley A</style></author><author><style face="normal" font="default" size="100%">Comuzzie, Anthony G</style></author><author><style face="normal" font="default" size="100%">Muzny, Donna M</style></author><author><style face="normal" font="default" size="100%">Gibbs, Richard A</style></author><author><style face="normal" font="default" size="100%">Butte, Nancy F</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children.</style></title><secondary-title><style face="normal" font="default" size="100%">Obesity (Silver Spring)</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Obesity (Silver Spring)</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">ATPases Associated with Diverse Cellular Activities</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Mass Index</style></keyword><keyword><style  face="normal" font="default" size="100%">Body Weight</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%">Exome</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Loci</style></keyword><keyword><style  face="normal" font="default" size="100%">Genome-Wide Association Study</style></keyword><keyword><style  face="normal" font="default" size="100%">Hispanic or Latino</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Membrane Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">Pediatric Obesity</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%">Sequence Analysis, DNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Software</style></keyword><keyword><style  face="normal" font="default" size="100%">Waist Circumference</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 Jul</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">25</style></volume><pages><style face="normal" font="default" size="100%">1270-1276</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 perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.&lt;/p&gt;&lt;p&gt;&lt;b&gt;METHODS: &lt;/b&gt;Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level.&lt;/p&gt;&lt;p&gt;&lt;b&gt;RESULTS: &lt;/b&gt;(1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated.&lt;/p&gt;&lt;p&gt;&lt;b&gt;CONCLUSIONS: &lt;/b&gt;Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.&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/28508493?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%">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></records></xml>