Rare coding alleles play crucial roles in the molecular diagnosis of genetic diseases. However, the systemic identification of these alleles has been challenging due to their scarcity in the general population. Here, we discovered and characterized rare coding alleles contributing to genetic dyslipidemia, a principal risk for coronary artery disease, among over a million individuals combining three large contemporary genetic datasets (Million Veteran Program, n = 634,535, UK Biobank, n = 431,178, and All Of Us Research Program, n = 92,304) totaling 1,158,017 multi-ancestral individuals. Unlike previous rare variant studies in lipids, this study included 238,243 individuals (20.6%) from non-European-like populations. Testing 2,997,401 rare coding variants from diverse backgrounds, we identified 800 exome-wide significant associations across 209 genes including 176 predicted loss of function and 624 missense variants. Among these exome-wide associations, 130 associations were driven by non-European-like populations. Associated alleles are highly enriched in functional variant classes, showed significant additive and recessive associations, exhibited similar effects across populations, and resolved pathogenicity for variants enriched in African or South-Asian populations. Furthermore, we identified 5 lipid-related genes associated with coronary artery disease (RORC, CFAP65, GTF2E2, PLCB3, and ZNF117). Among them, RORC is a potentially novel therapeutic target through the down regulation of LDLC by its silencing. This study provides resources and insights for understanding causal mechanisms, quantifying the expressivity of rare coding alleles, and identifying novel drug targets across diverse populations.

D.K. is a scientific advisor and reports consulting fees from Bitterroot Bio, Inc unrelated to the present work. P.N. reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech / Roche, and Novartis, personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Foresite Labs, Genentech / Roche, GV, HeartFlow, Magnet Biomedicine, Merck, and Novartis, scientific advisory board membership of Esperion Therapeutics, Preciseli, and TenSixteen Bio, scientific co-founder of TenSixteen Bio, equity in MyOme, Preciseli, and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work.

S.K. is supported by Japan Society for the Promotion of Science (202160643), Uehara Memorial Foundation, and National Heart Lung and Blood Institute (NHLBI, K99HL169733). Z.Y. is supported by National Human Genome Research Institute (K99HG012956). S.H.C is supported by NHLBI (R01HL127564). S.J.J. is supported by the Dutch Heart Foundation (grant no. 03-007-2022-0035). M.S.S is supported by TOPMed (2022-6842.02), D.K. is supported by the Department of Veterans Affairs (VA, IK2BX005759-01), the American Heart Association (DOI: https://doi.org/10.58275/AHA.23SCEFIA1153369.pc.gr.173943), and the Baszucki Research Initiative provided to Stanford Vascular Surgery. This work was supported in part via funding from VA Merit Award I01 BX003362 (K.M.C., P.S.T.) from the VA Office of R&D. P.N. and G.M.P are supported by NHLBI (R01HL142711, R01HL127564).

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study received ethics approval from the Veterans Affairs Central Institutional Review Board under Institutional Review Board protocol number 16-06. The study protocols were approved under protocol numbers 2016P002395 and 2021P002228 by the Mass General Brigham Institutional Review Board. The analysis for UK Biobank was performed under application number 7089.

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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Full summary statistics will be publically available after the acceptance of the manuscript through dbGAP. The individual data for AOU, MVP, and UKB is available upon application to the respective organizations. The analysis codes and supplemental data are available at Zenodo (https://zenodo.org/doi/10.5281/zenodo.11092802). The docker/singularity images used in the analysis are publically available through docker hub (https://hub.docker.com/u/skoyamamd).