Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians

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. This analysi...

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Published in	Journal of the American College of Cardiology Vol. 76; no. 6; pp. 703 - 714
Main Authors	Wang, Minxian, Menon, Ramesh, Mishra, Sanghamitra, Patel, Aniruddh P., Chaffin, Mark, Tanneeru, Deepak, Deshmukh, Manjari, Mathew, Oshin, Apte, Sanika, Devanboo, Christina S., Sundaram, Sumathi, Lakshmipathy, Praveena, Murugan, Sakthivel, Sharma, Krishna Kumar, Rajendran, Karthikeyan, Santhosh, Sam, Thachathodiyl, Rajesh, Ahamed, Hisham, Balegadde, Aniketh Vijay, Alexander, Thomas, Swaminathan, Krishnan, Gupta, Rajeev, Mullasari, Ajit S., Sigamani, Alben, Kanchi, Muralidhar, Peterson, Andrew S., Butterworth, Adam S., Danesh, John, Di Angelantonio, Emanuele, Naheed, Aliya, Inouye, Michael, Chowdhury, Rajiv, Vedam, Ramprasad L., Kathiresan, Sekar, Gupta, Ravi, Khera, Amit V.
Format	Journal Article
Language	English
Published	United States Elsevier Inc 11.08.2020
Subjects	Adult Aged Bangladesh Cardiovascular Case-Control Studies coronary artery disease Coronary Artery Disease - genetics Female Genome-Wide Association Study genomic medicine Humans India Male Middle Aged Multifactorial Inheritance polygenic score South Asian Bangladesh India coronary artery disease genomic medicine PCs OR/SD CI CAD South Asian GPS polygenic score AUC area under the receiver-operator curve genome-wide polygenic score(s) confidence interval principal components odds ratios per standard deviation
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ISSN	0735-1097 1558-3597 1558-3597
DOI	10.1016/j.jacc.2020.06.024

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Abstract	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. This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. This GPSCAD 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 GPSCAD 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 GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. The GPSCAD, 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 < 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 < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution—ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment. [Display omitted]
AbstractList	AbstractBackgroundGenome-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. ObjectivesThis analysis used summary statistics from a prior genome-wide association study to derive a new GPS CAD for South Asians. MethodsThis GPS CAD 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 CAD 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 CAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. ResultsThe GPS CAD, 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 < 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 < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPS CAD distribution—ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). ConclusionsThe new GPS CAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment. 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.BACKGROUNDGenome-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.This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians.OBJECTIVESThis analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians.This GPSCAD 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 GPSCAD 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 GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India.METHODSThis GPSCAD 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 GPSCAD 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 GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India.The GPSCAD, 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 < 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 < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each).RESULTSThe GPSCAD, 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 < 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 < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution-ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each).The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment.CONCLUSIONSThe new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment. 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. This analysis used summary statistics from a prior genome-wide association study to derive a new GPS for South Asians. 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. 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 < 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 < 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 < 0.05 for each). The new GPS has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment. 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. This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. This GPSCAD 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 GPSCAD 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 GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. The GPSCAD, 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 < 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 < 0.001). Compared with the middle quintile, risk for CAD was most pronounced for those in the top 5% of the GPSCAD distribution—ORs of 4.16, 2.46, and 3.22 in the South Asian UK Biobank, Bangladeshi, and Indian studies, respectively (p < 0.05 for each). The new GPSCAD has been developed and tested using 3 distinct South Asian studies, and provides a generalizable framework for ancestry-specific GPS assessment. [Display omitted]
Author	Swaminathan, Krishnan Gupta, Rajeev Naheed, Aliya Murugan, Sakthivel Khera, Amit V. Rajendran, Karthikeyan Sundaram, Sumathi Mullasari, Ajit S. Inouye, Michael Danesh, John Patel, Aniruddh P. Butterworth, Adam S. Wang, Minxian Devanboo, Christina S. Santhosh, Sam Sigamani, Alben Di Angelantonio, Emanuele Chaffin, Mark Thachathodiyl, Rajesh Mishra, Sanghamitra Apte, Sanika Alexander, Thomas Mathew, Oshin Ahamed, Hisham Chowdhury, Rajiv Tanneeru, Deepak Deshmukh, Manjari Menon, Ramesh Kanchi, Muralidhar Balegadde, Aniketh Vijay Kathiresan, Sekar Gupta, Ravi Lakshmipathy, Praveena Sharma, Krishna Kumar Peterson, Andrew S. Vedam, Ramprasad L.
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Cites_doi	10.1016/j.ajhg.2017.03.004 10.1038/s41467-020-15464-w 10.1002/sim.4085 10.1056/NEJM199404143301503 10.1038/s41586-019-1310-4 10.1016/j.cell.2019.10.004 10.1371/journal.pmed.1001779 10.1093/bioinformatics/btx299 10.1001/jamanetworkopen.2020.3959 10.1093/eurheartj/ehw028 10.1056/NEJMoa1605086 10.1161/CIRCULATIONAHA.119.044434 10.1016/j.jacc.2019.03.009 10.1161/CIR.0000000000000580 10.1038/nature15393 10.1093/eurheartj/eht273 10.1016/j.jacc.2016.03.520 10.1016/j.ajhg.2018.07.015 10.1038/s41588-019-0379-x 10.1186/s13073-019-0682-2 10.1038/s41576-018-0018-x 10.1016/j.jacc.2018.11.003 10.1038/s41586-019-1793-z 10.1038/s41467-019-11112-0 10.1038/s41588-018-0183-z 10.1016/j.jacc.2018.08.1041 10.1126/science.aaf7000 10.1038/ng.3643 10.1007/s10654-015-0037-2 10.1186/1471-2105-12-77 10.1016/j.ajhg.2015.09.001 10.1161/CIRCULATIONAHA.116.024436 10.1016/j.cell.2019.02.048 10.1161/CIRCULATIONAHA.119.043805 10.1038/ng.3396 10.1016/j.jacc.2018.07.079 10.1186/s13742-015-0047-8 10.1161/CIRCULATIONAHA.118.035658 10.1371/journal.pgen.1008500 10.1038/s41586-018-0579-z 10.1590/1678-4685-gmb-2017-0173 10.1161/CIRCULATIONAHA.115.020109
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Copyright	2020 American College of Cardiology Foundation American College of Cardiology Foundation Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
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Keywords	coronary artery disease genomic medicine PCs OR/SD CI CAD South Asian GPS polygenic score AUC area under the receiver-operator curve genome-wide polygenic score(s) confidence interval principal components odds ratios per standard deviation
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References	Kullo, Jouni, Austin (bib43) 2016; 133 Khera, Emdin, Drake (bib39) 2016; 375 Natarajan (bib33) 2018; 72 Gurdasani, Carstensen, Fatumo (bib36) 2019; 179 Abul-Husn, Manickam, Jones (bib8) 2016; 354 Inouye, Abraham, Nelson (bib13) 2018; 72 Abraham, Qiu, Inouye (bib28) 2017; 33 Marston, Kamanu, Nordio (bib42) 2020; 141 Browning, Zhou, Browning (bib27) 2018; 103 Duncan, Shen, Gelaye (bib35) 2019; 10 Nordestgaard, Chapman, Humphries (bib6) 2013; 34 Arnett, Blumenthal, Albert (bib2) 2019; 74 Khera, Chaffin, Aragam (bib11) 2018; 50 Robin, Turck, Hainard (bib30) 2011; 12 Natarajan, Young, Stitziel (bib40) 2017; 135 Vilhjálmsson, Yang, Finucane (bib23) 2015; 97 Chang, Chow, Tellier, Vattikuti, Purcell, Lee (bib25) 2015; 4 Kowalski, Qian, Hou (bib37) 2019; 15 Homburger, Neben, Mishne, Zhou, Kathiresan, Khera (bib18) 2019; 11 Bycroft, Freeman, Petkova (bib20) 2018; 562 Martin, Gignoux, Walters (bib15) 2017; 100 Patel, Wang, Fahed (bib10) 2020; 3 Pereira, Mendonca, Borges (bib32) 2018; 41 Marenberg, Risch, Berkman, Floderus, Faire (bib5) 1994; 330 Khera, Won, Peloso (bib7) 2016; 67 Pencina, D’Agostino, Steyerberg (bib31) 2011; 30 Sudlow, Gallacher, Allen (bib19) 2015; 12 (bib24) 2015; 526 Chowdhury, Alam, Fakir (bib21) 2015; 30 (bib29) 2016; 48 Sirugo, Williams, Tishkoff (bib14) 2019; 177 Torkamani, Wineinger, Topol (bib34) 2018; 19 Wojcik, Graff, Nishimura (bib17) 2019; 570 Gertler (bib4) 1951; 147 Grundy, Stone, Bailey (bib3) 2019; 73 Taliun, Harris, Kessler (bib38) 2019 Marnetto, Pärna, Läll (bib44) 2020; 11 Benn, Watts, Tybjærg-Hansen, Nordestgaard (bib9) 2016; 37 Nikpay, Goel, Won (bib22) 2015; 47 (bib26) 2019; 576 Martin, Kanai, Kamatani, Okada, Neale, Daly (bib16) 2019; 51 Volgman, Palaniappan, Aggarwal (bib1) 2018; 138 Khera, Chaffin, Zekavat (bib12) 2019; 139 Damask, Steg, Schwartz (bib41) 2020; 141 Gertler (10.1016/j.jacc.2020.06.024_bib4) 1951; 147 Chang (10.1016/j.jacc.2020.06.024_bib25) 2015; 4 Grundy (10.1016/j.jacc.2020.06.024_bib3) 2019; 73 Duncan (10.1016/j.jacc.2020.06.024_bib35) 2019; 10 Homburger (10.1016/j.jacc.2020.06.024_bib18) 2019; 11 Volgman (10.1016/j.jacc.2020.06.024_bib1) 2018; 138 Abul-Husn (10.1016/j.jacc.2020.06.024_bib8) 2016; 354 Kowalski (10.1016/j.jacc.2020.06.024_bib37) 2019; 15 Kullo (10.1016/j.jacc.2020.06.024_bib43) 2016; 133 (10.1016/j.jacc.2020.06.024_bib24) 2015; 526 Khera (10.1016/j.jacc.2020.06.024_bib7) 2016; 67 Sudlow (10.1016/j.jacc.2020.06.024_bib19) 2015; 12 Marenberg (10.1016/j.jacc.2020.06.024_bib5) 1994; 330 Wojcik (10.1016/j.jacc.2020.06.024_bib17) 2019; 570 Vilhjálmsson (10.1016/j.jacc.2020.06.024_bib23) 2015; 97 Abraham (10.1016/j.jacc.2020.06.024_bib28) 2017; 33 Khera (10.1016/j.jacc.2020.06.024_bib11) 2018; 50 Robin (10.1016/j.jacc.2020.06.024_bib30) 2011; 12 (10.1016/j.jacc.2020.06.024_bib26) 2019; 576 Benn (10.1016/j.jacc.2020.06.024_bib9) 2016; 37 Damask (10.1016/j.jacc.2020.06.024_bib41) 2020; 141 Patel (10.1016/j.jacc.2020.06.024_bib10) 2020; 3 Torkamani (10.1016/j.jacc.2020.06.024_bib34) 2018; 19 Gurdasani (10.1016/j.jacc.2020.06.024_bib36) 2019; 179 Khera (10.1016/j.jacc.2020.06.024_bib39) 2016; 375 Inouye (10.1016/j.jacc.2020.06.024_bib13) 2018; 72 Pencina (10.1016/j.jacc.2020.06.024_bib31) 2011; 30 Martin (10.1016/j.jacc.2020.06.024_bib15) 2017; 100 Marston (10.1016/j.jacc.2020.06.024_bib42) 2020; 141 Nikpay (10.1016/j.jacc.2020.06.024_bib22) 2015; 47 Natarajan (10.1016/j.jacc.2020.06.024_bib33) 2018; 72 (10.1016/j.jacc.2020.06.024_bib29) 2016; 48 Pereira (10.1016/j.jacc.2020.06.024_bib32) 2018; 41 Chowdhury (10.1016/j.jacc.2020.06.024_bib21) 2015; 30 Arnett (10.1016/j.jacc.2020.06.024_bib2) 2019; 74 Taliun (10.1016/j.jacc.2020.06.024_bib38) 2019 Khera (10.1016/j.jacc.2020.06.024_bib12) 2019; 139 Bycroft (10.1016/j.jacc.2020.06.024_bib20) 2018; 562 Martin (10.1016/j.jacc.2020.06.024_bib16) 2019; 51 Marnetto (10.1016/j.jacc.2020.06.024_bib44) 2020; 11 Nordestgaard (10.1016/j.jacc.2020.06.024_bib6) 2013; 34 Sirugo (10.1016/j.jacc.2020.06.024_bib14) 2019; 177 Browning (10.1016/j.jacc.2020.06.024_bib27) 2018; 103 Natarajan (10.1016/j.jacc.2020.06.024_bib40) 2017; 135 32762906 - J Am Coll Cardiol. 2020 Aug 11;76(6):715-718. doi: 10.1016/j.jacc.2020.06.028.
References_xml	– volume: 33 start-page: 2776 year: 2017 end-page: 2778 ident: bib28 article-title: FlashPCA2: principal component analysis of Biobank-scale genotype datasets Stegle O, editor publication-title: Bioinformatics – volume: 67 start-page: 2578 year: 2016 end-page: 2589 ident: bib7 article-title: Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia publication-title: J Am Coll Cardiol – volume: 34 start-page: 3478 year: 2013 end-page: 3490 ident: bib6 article-title: Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: Consensus Statement of the European Atherosclerosis Society publication-title: Eur Heart J – volume: 179 start-page: 984 year: 2019 end-page: 1002.e36 ident: bib36 article-title: Uganda genome resource enables insights into population history and genomic discovery in Africa publication-title: Cell – volume: 48 start-page: 1279 year: 2016 end-page: 1283 ident: bib29 article-title: A reference panel of 64,976 haplotypes for genotype imputation publication-title: Nat Genet – volume: 139 start-page: 1593 year: 2019 end-page: 1602 ident: bib12 article-title: Whole-genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction publication-title: Circulation – volume: 72 start-page: 1894 year: 2018 end-page: 1897 ident: bib33 article-title: Polygenic risk scoring for coronary heart disease publication-title: J Am Coll Cardiol – volume: 30 start-page: 11 year: 2011 end-page: 21 ident: bib31 article-title: Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers publication-title: Stat Med – volume: 138 start-page: e1 year: 2018 end-page: e34 ident: bib1 article-title: Atherosclerotic cardiovascular disease in South Asians in the United States: epidemiology, risk factors, and treatments: a scientific statement from the American Heart Association publication-title: Circulation – volume: 37 start-page: 1384 year: 2016 end-page: 1394 ident: bib9 article-title: Mutations causative of familial hypercholesterolaemia: screening of 98 098 individuals from the Copenhagen General Population Study estimated a prevalence of 1 in 217 publication-title: Eur Heart J – volume: 11 start-page: 1628 year: 2020 ident: bib44 article-title: Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals publication-title: Nat Commun – volume: 100 start-page: 635 year: 2017 end-page: 649 ident: bib15 article-title: Human demographic history impacts genetic risk prediction across diverse populations publication-title: Am J Hum Genet – volume: 12 year: 2011 ident: bib30 article-title: pROC: an open-source package for R and S+ to analyze and compare ROC curves publication-title: BMC Bioinformatics – volume: 72 start-page: 1883 year: 2018 end-page: 1893 ident: bib13 article-title: Genomic risk prediction of coronary artery disease in 480,000 adults publication-title: J Am Coll Cardiol – volume: 562 start-page: 203 year: 2018 end-page: 209 ident: bib20 article-title: The UK Biobank resource with deep phenotyping and genomic data publication-title: Nature – volume: 135 start-page: 2091 year: 2017 end-page: 2101 ident: bib40 article-title: Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting publication-title: Circulation – year: 2019 ident: bib38 article-title: Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program publication-title: Genomics – volume: 47 start-page: 1121 year: 2015 end-page: 1130 ident: bib22 article-title: A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease publication-title: Nat Genet – volume: 375 start-page: 2349 year: 2016 end-page: 2358 ident: bib39 article-title: Genetic risk, adherence to a healthy lifestyle, and coronary disease publication-title: N Engl J Med – volume: 570 start-page: 514 year: 2019 end-page: 518 ident: bib17 article-title: Genetic analyses of diverse populations improves discovery for complex traits publication-title: Nature – volume: 103 start-page: 338 year: 2018 end-page: 348 ident: bib27 article-title: A one-penny imputed genome from next-generation reference panels publication-title: Am J Hum Genet – volume: 526 start-page: 68 year: 2015 end-page: 74 ident: bib24 article-title: A global reference for human genetic variation publication-title: Nature – volume: 12 year: 2015 ident: bib19 article-title: UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age publication-title: PLOS Med – volume: 133 start-page: 1181 year: 2016 end-page: 1188 ident: bib43 article-title: Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES Clinical Trial) publication-title: Circulation – volume: 30 start-page: 577 year: 2015 end-page: 587 ident: bib21 article-title: for the Cardiology Research Group The Bangladesh Risk of Acute Vascular Events (BRAVE) study: objectives and design publication-title: Eur J Epidemiol – volume: 19 start-page: 581 year: 2018 end-page: 590 ident: bib34 article-title: The personal and clinical utility of polygenic risk scores publication-title: Nat Rev Genet – volume: 141 start-page: 624 year: 2020 end-page: 636 ident: bib41 article-title: Patients with high genome-wide polygenic risk scores for coronary artery disease may receive greater clinical benefit from alirocumab treatment in the Odyssey Outcomes Trial publication-title: Circulation – volume: 50 start-page: 1219 year: 2018 end-page: 1224 ident: bib11 article-title: Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations publication-title: Nat Genet – volume: 11 start-page: 74 year: 2019 ident: bib18 article-title: Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores publication-title: Genome Med – volume: 177 start-page: 26 year: 2019 end-page: 31 ident: bib14 article-title: The missing diversity in human genetic studies publication-title: Cell – volume: 10 start-page: 3328 year: 2019 ident: bib35 article-title: Analysis of polygenic risk score usage and performance in diverse human populations publication-title: Nat Commun – volume: 330 start-page: 1041 year: 1994 end-page: 1046 ident: bib5 article-title: Genetic susceptibility to death from coronary heart disease in a study of twins publication-title: N Engl J Med – volume: 73 start-page: e285 year: 2019 end-page: e350 ident: bib3 article-title: 2018 guideline on the management of blood cholesterol publication-title: J Am Coll Cardiol – volume: 354 year: 2016 ident: bib8 article-title: Genetic identification of familial hypercholesterolemia within a single U.S. health care system publication-title: Science – volume: 3 year: 2020 ident: bib10 article-title: Association of rare pathogenic DNA variants for familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and lynch syndrome with disease risk in adults according to family history publication-title: JAMA Netw Open – volume: 147 start-page: 621 year: 1951 ident: bib4 article-title: Young candidates for coronary heart disease publication-title: J Am Med Assoc – volume: 15 year: 2019 ident: bib37 article-title: Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations publication-title: PLOS Genet – volume: 4 start-page: 7 year: 2015 ident: bib25 article-title: Second-generation PLINK: rising to the challenge of larger and richer datasets publication-title: GigaScience – volume: 74 start-page: 1376 year: 2019 end-page: 1414 ident: bib2 article-title: 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines publication-title: J Am Coll Cardiol – volume: 97 start-page: 576 year: 2015 end-page: 592 ident: bib23 article-title: Modeling linkage disequilibrium increases accuracy of polygenic risk scores publication-title: Am J Hum Genet – volume: 41 start-page: 766 year: 2018 end-page: 774 ident: bib32 article-title: Additional value of a combined genetic risk score to standard cardiovascular stratification publication-title: Genet Mol Biol – volume: 51 start-page: 584 year: 2019 end-page: 591 ident: bib16 article-title: Clinical use of current polygenic risk scores may exacerbate health disparities publication-title: Nat Genet – volume: 141 start-page: 616 year: 2020 end-page: 623 ident: bib42 article-title: Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score: results from the FOURIER Trial publication-title: Circulation – volume: 576 start-page: 106 year: 2019 end-page: 111 ident: bib26 article-title: The GenomeAsia 100K Project enables genetic discoveries across Asia publication-title: Nature – volume: 100 start-page: 635 year: 2017 ident: 10.1016/j.jacc.2020.06.024_bib15 article-title: Human demographic history impacts genetic risk prediction across diverse populations publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2017.03.004 – volume: 11 start-page: 1628 year: 2020 ident: 10.1016/j.jacc.2020.06.024_bib44 article-title: Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals publication-title: Nat Commun doi: 10.1038/s41467-020-15464-w – volume: 30 start-page: 11 year: 2011 ident: 10.1016/j.jacc.2020.06.024_bib31 article-title: Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers publication-title: Stat Med doi: 10.1002/sim.4085 – volume: 330 start-page: 1041 year: 1994 ident: 10.1016/j.jacc.2020.06.024_bib5 article-title: Genetic susceptibility to death from coronary heart disease in a study of twins publication-title: N Engl J Med doi: 10.1056/NEJM199404143301503 – volume: 570 start-page: 514 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib17 article-title: Genetic analyses of diverse populations improves discovery for complex traits publication-title: Nature doi: 10.1038/s41586-019-1310-4 – volume: 179 start-page: 984 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib36 article-title: Uganda genome resource enables insights into population history and genomic discovery in Africa publication-title: Cell doi: 10.1016/j.cell.2019.10.004 – volume: 12 year: 2015 ident: 10.1016/j.jacc.2020.06.024_bib19 article-title: UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age publication-title: PLOS Med doi: 10.1371/journal.pmed.1001779 – volume: 33 start-page: 2776 year: 2017 ident: 10.1016/j.jacc.2020.06.024_bib28 article-title: FlashPCA2: principal component analysis of Biobank-scale genotype datasets Stegle O, editor publication-title: Bioinformatics doi: 10.1093/bioinformatics/btx299 – volume: 3 year: 2020 ident: 10.1016/j.jacc.2020.06.024_bib10 article-title: Association of rare pathogenic DNA variants for familial hypercholesterolemia, hereditary breast and ovarian cancer syndrome, and lynch syndrome with disease risk in adults according to family history publication-title: JAMA Netw Open doi: 10.1001/jamanetworkopen.2020.3959 – volume: 37 start-page: 1384 year: 2016 ident: 10.1016/j.jacc.2020.06.024_bib9 article-title: Mutations causative of familial hypercholesterolaemia: screening of 98 098 individuals from the Copenhagen General Population Study estimated a prevalence of 1 in 217 publication-title: Eur Heart J doi: 10.1093/eurheartj/ehw028 – volume: 375 start-page: 2349 year: 2016 ident: 10.1016/j.jacc.2020.06.024_bib39 article-title: Genetic risk, adherence to a healthy lifestyle, and coronary disease publication-title: N Engl J Med doi: 10.1056/NEJMoa1605086 – volume: 141 start-page: 624 year: 2020 ident: 10.1016/j.jacc.2020.06.024_bib41 article-title: Patients with high genome-wide polygenic risk scores for coronary artery disease may receive greater clinical benefit from alirocumab treatment in the Odyssey Outcomes Trial publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.119.044434 – volume: 74 start-page: 1376 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib2 article-title: 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2019.03.009 – volume: 138 start-page: e1 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib1 article-title: Atherosclerotic cardiovascular disease in South Asians in the United States: epidemiology, risk factors, and treatments: a scientific statement from the American Heart Association publication-title: Circulation doi: 10.1161/CIR.0000000000000580 – volume: 526 start-page: 68 year: 2015 ident: 10.1016/j.jacc.2020.06.024_bib24 article-title: A global reference for human genetic variation publication-title: Nature doi: 10.1038/nature15393 – volume: 34 start-page: 3478 year: 2013 ident: 10.1016/j.jacc.2020.06.024_bib6 article-title: Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: Consensus Statement of the European Atherosclerosis Society publication-title: Eur Heart J doi: 10.1093/eurheartj/eht273 – volume: 67 start-page: 2578 year: 2016 ident: 10.1016/j.jacc.2020.06.024_bib7 article-title: Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2016.03.520 – volume: 103 start-page: 338 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib27 article-title: A one-penny imputed genome from next-generation reference panels publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2018.07.015 – volume: 51 start-page: 584 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib16 article-title: Clinical use of current polygenic risk scores may exacerbate health disparities publication-title: Nat Genet doi: 10.1038/s41588-019-0379-x – volume: 11 start-page: 74 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib18 article-title: Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores publication-title: Genome Med doi: 10.1186/s13073-019-0682-2 – volume: 19 start-page: 581 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib34 article-title: The personal and clinical utility of polygenic risk scores publication-title: Nat Rev Genet doi: 10.1038/s41576-018-0018-x – volume: 73 start-page: e285 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib3 article-title: 2018 guideline on the management of blood cholesterol publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2018.11.003 – volume: 576 start-page: 106 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib26 article-title: The GenomeAsia 100K Project enables genetic discoveries across Asia publication-title: Nature doi: 10.1038/s41586-019-1793-z – volume: 10 start-page: 3328 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib35 article-title: Analysis of polygenic risk score usage and performance in diverse human populations publication-title: Nat Commun doi: 10.1038/s41467-019-11112-0 – volume: 50 start-page: 1219 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib11 article-title: Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations publication-title: Nat Genet doi: 10.1038/s41588-018-0183-z – volume: 72 start-page: 1894 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib33 article-title: Polygenic risk scoring for coronary heart disease publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2018.08.1041 – volume: 147 start-page: 621 year: 1951 ident: 10.1016/j.jacc.2020.06.024_bib4 article-title: Young candidates for coronary heart disease publication-title: J Am Med Assoc – volume: 354 year: 2016 ident: 10.1016/j.jacc.2020.06.024_bib8 article-title: Genetic identification of familial hypercholesterolemia within a single U.S. health care system publication-title: Science doi: 10.1126/science.aaf7000 – volume: 48 start-page: 1279 year: 2016 ident: 10.1016/j.jacc.2020.06.024_bib29 article-title: A reference panel of 64,976 haplotypes for genotype imputation publication-title: Nat Genet doi: 10.1038/ng.3643 – volume: 30 start-page: 577 year: 2015 ident: 10.1016/j.jacc.2020.06.024_bib21 article-title: for the Cardiology Research Group The Bangladesh Risk of Acute Vascular Events (BRAVE) study: objectives and design publication-title: Eur J Epidemiol doi: 10.1007/s10654-015-0037-2 – volume: 12 year: 2011 ident: 10.1016/j.jacc.2020.06.024_bib30 article-title: pROC: an open-source package for R and S+ to analyze and compare ROC curves publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-12-77 – volume: 97 start-page: 576 year: 2015 ident: 10.1016/j.jacc.2020.06.024_bib23 article-title: Modeling linkage disequilibrium increases accuracy of polygenic risk scores publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2015.09.001 – volume: 135 start-page: 2091 year: 2017 ident: 10.1016/j.jacc.2020.06.024_bib40 article-title: Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.116.024436 – volume: 177 start-page: 26 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib14 article-title: The missing diversity in human genetic studies publication-title: Cell doi: 10.1016/j.cell.2019.02.048 – volume: 141 start-page: 616 year: 2020 ident: 10.1016/j.jacc.2020.06.024_bib42 article-title: Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score: results from the FOURIER Trial publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.119.043805 – volume: 47 start-page: 1121 year: 2015 ident: 10.1016/j.jacc.2020.06.024_bib22 article-title: A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease publication-title: Nat Genet doi: 10.1038/ng.3396 – volume: 72 start-page: 1883 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib13 article-title: Genomic risk prediction of coronary artery disease in 480,000 adults publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2018.07.079 – volume: 4 start-page: 7 year: 2015 ident: 10.1016/j.jacc.2020.06.024_bib25 article-title: Second-generation PLINK: rising to the challenge of larger and richer datasets publication-title: GigaScience doi: 10.1186/s13742-015-0047-8 – volume: 139 start-page: 1593 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib12 article-title: Whole-genome sequencing to characterize monogenic and polygenic contributions in patients hospitalized with early-onset myocardial infarction publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.118.035658 – volume: 15 year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib37 article-title: Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations publication-title: PLOS Genet doi: 10.1371/journal.pgen.1008500 – volume: 562 start-page: 203 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib20 article-title: The UK Biobank resource with deep phenotyping and genomic data publication-title: Nature doi: 10.1038/s41586-018-0579-z – volume: 41 start-page: 766 year: 2018 ident: 10.1016/j.jacc.2020.06.024_bib32 article-title: Additional value of a combined genetic risk score to standard cardiovascular stratification publication-title: Genet Mol Biol doi: 10.1590/1678-4685-gmb-2017-0173 – year: 2019 ident: 10.1016/j.jacc.2020.06.024_bib38 article-title: Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program publication-title: Genomics – volume: 133 start-page: 1181 year: 2016 ident: 10.1016/j.jacc.2020.06.024_bib43 article-title: Incorporating a genetic risk score into coronary heart disease risk estimates: effect on low-density lipoprotein cholesterol levels (the MI-GENES Clinical Trial) publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.115.020109 – reference: 32762906 - J Am Coll Cardiol. 2020 Aug 11;76(6):715-718. doi: 10.1016/j.jacc.2020.06.028.
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Snippet	Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are... AbstractBackgroundGenome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery...
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SubjectTerms	Adult Aged Bangladesh Cardiovascular Case-Control Studies coronary artery disease Coronary Artery Disease - genetics Female Genome-Wide Association Study genomic medicine Humans India Male Middle Aged Multifactorial Inheritance polygenic score South Asian
Title	Validation of a Genome-Wide Polygenic Score for Coronary Artery Disease in South Asians
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