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Author Notes:

Minxian Wang, Email: wangmx@big.ac.cn

Concept and design: A.P.P., M.W., Y.R., P.N. and A.V.K. Acquisition, analysis or interpretation of data: A.P.P., M.W., Y.R., S.K., S.L.C., X.Y., C.T., S.A., A.C.F., D.A.v.H., A.S.B., K.G.A., P.N. and A.V.K. Drafting of the manuscript: A.P.P., M.W. and A.V.K. Critical revision of the manuscript for important intellectual content: P.T.E., P.S.T., Y.V.S., K.C., P.W.F.W. and T.L.A.

We thank all of the volunteers participating in Genes & Health.

S.A. has served as a scientific advisor to Third Rock Ventures. A.C.F. is a co-founder of Goodpath and reports a grant from Abbott Vascular. P.T.E. receives sponsored research support from Bayer AG and IBM Research; he has also served on advisory boards or consulted for Bayer AG, MyoKardia and Novartis. A.S.B. reports institutional grants from AstraZeneca, Bayer, Biogen, BioMarin, Bioverativ, Novartis, Regeneron and Sanofi. P.N. reports research grants from Allelica, Apple, Amgen, Boston Scientific, Genentech/Roche and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine and Novartis, scientific advisory board membership of Esperion Therapeutics, Preciseli and TenSixteen Bio, scientific co-founder of TenSixteen Bio, equity in Preciseli and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. A.V.K. is an employee of Verve Therapeutics; has served as a scientific advisor to Amgen, Novartis, Silence Therapeutics, Korro Bio, Veritas International, Color Health, Third Rock Ventures, Illumina, Ambry and Foresite Labs; holds equity in Verve Therapeutics, Color Health and Foresite Labs; and is listed as a co-inventor on patent applications related to assessment and mitigation of risk associated with perturbations in body fat distribution. The remaining authors declare no competing interests.

These authors contributed equally: Aniruddh P. Patel, Minxian Wang. These authors jointly supervised this work: Pradeep Natarajan, Amit V. Khera.

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Research Funding:

This work was supported by the KL2/Catalyst Medical Research Investigator Training award from Harvard Catalyst (to A.P.P. and K.G.A.); the Sarnoff Cardiovascular Research Foundation Fellowship (to S.A.); grants 1K08HL153937 (to K.G.A.), 1K08HL161448 (to A.C.F.), R01HL1427 (to P.N.), R01HL148565 (to P.N.), R01HL148050 (to P.N.), 1RO1HL092577 (to P.T.E.), 1R01HL157635 (to P.T.E.) and 1R01HL157635 (to P.T.E.) from the National Heart, Lung, and Blood Institute; grants RG/18/13/33946 and CH/12/2/29428 from the British Heart Foundation (to A.S.B.) grants BRC-1215-20014 and NIHR203312 from the NIHR Cambridge Biomedical Research Centre (to A.S.B.) grant RE/18/1/34212 from the Cambridge British Heart Foundation Centre of Research Excellence (to A.S.B.); grants 862032 (to K.G.A.) 18SFRN34110082 (to P.T.E.), 17IFUNP3384001 (to K.G.A.) from the American Heart Association; grant MAESTRIA 965286 from the European Union (to P.T.E.); grants 1K08HG010155 (to A.V.K.) and 1U01HG011719 from the National Human Genome Research Institute (to A.P.P., P.N. and A.V.K.); a Hassenfeld Scholar Award from Massachusetts General Hospital (to P.N. and A.V.K.); a Merkin Institute Fellowship from the Broad Institute of MIT and Harvard (to A.V.K.).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Biochemistry & Molecular Biology
  • Cell Biology
  • Medicine, Research & Experimental
  • Research & Experimental Medicine
  • HEART-DISEASE
  • GENETIC RISK
  • CARDIOVASCULAR-DISEASE
  • GENOMIC RISK
  • HEALTH
  • ASSOCIATION
  • VALIDATION
  • BIOBANK
  • VARIANTS
  • ACCURACY

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease

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Journal Title:

NATURE MEDICINE

Volume:

Volume 29, Number 7

Publisher:

, Pages 1793-+

Type of Work:

Article | Final Publisher PDF

Abstract:

Identification of individuals at highest risk of coronary artery disease (CAD)—ideally before onset—remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10–2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70–1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Copyright information:

© The Author(s) 2023

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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