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Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program

Nature Genetics (2018) | Download Citation


The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of US military veterans. Here we genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least one blood lipid measurement, including 57,332 black and 24,743 Hispanic participants, we tested up to around 32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total n > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes) and PDE3B (triglycerides and coronary disease).

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Data availability

The full summary-level association data from the trans-ancestry meta-analysis for each lipid trait from this report are available through dbGaP, with accession number phs001672.v1.p1.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


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Data on patients with coronary artery disease and myocardial infarctions have been contributed by the CARDIoGRAMplusC4D investigators and the Myocardial Infarction Genetics and CARDIoGRAM Exome investigators. Both datasets were obtained online (see URLs). This research is based on data from the MVP, Office of Research and Development, Veterans Health Administration, and was supported by the Department of Veterans Affairs Cooperative Studies Program award G002. This research was also supported by three additional Department of Veterans Affairs awards (1I0101BX003340, 1I01BX003362, and 1I01CX001025) and the NIH (T32 HL007734, K01HL125751, R01HL127564). The content of this manuscript does not represent the views of the Department of Veterans Affairs or the United States Government.

Author information

Author notes

  1. These authors contributed equally: Derek Klarin, Scott M. Damrauer.

  2. These authors jointly supervised: Christopher J. O’Donnell, Philip S. Tsao, Sekar Kathiresan, Daniel J. Rader, Peter W. F. Wilson, Themistocles L. Assimes.

  3. A list of members and affiliations appears in the Supplementary Note.


  1. Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    • Derek Klarin
    • , Connor A. Emdin
    • , Pradeep Natarajan
    • , Amit V. Khera
    •  & Sekar Kathiresan
  2. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    • Derek Klarin
    • , Mark Chaffin
    • , Connor A. Emdin
    • , Pradeep Natarajan
    • , Benjamin M. Neale
    • , Amit V. Khera
    •  & Sekar Kathiresan
  3. Boston VA Healthcare System, Boston, MA, USA

    • Derek Klarin
  4. Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA

    • Scott M. Damrauer
    • , Aeron M. Small
    • , Danish Saleheen
    • , Marijana Vujkovic
    •  & Kyong-Mi Chang
  5. Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Scott M. Damrauer
  6. Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA

    • Kelly Cho
    • , Jacqueline Honerlaw
    • , David R. Gagnon
    • , Jie Huang
    • , Yuk-Lam Ho
    • , Jennifer E. Huffman
    • , Saiju Pyarajan
    • , J. Michael Gaziano
    •  & Christopher J. O’Donnell
  7. Department of Epidemiology, Rollins School of Public Health, Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, USA

    • Yan V. Sun
  8. Regeneron Genetics Center, Tarrytown, NY, USA

    • Tanya M. Teslovich
    • , Alexander H. Li
    • , Aris Baras
    •  & Frederick E. Dewey
  9. Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

    • David R. Gagnon
    •  & Gina M. Peloso
  10. VA Salt Lake City Health Care System, Salt Lake City, UT, USA

    • Scott L. DuVall
    •  & Julie A. Lynch
  11. Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA

    • Scott L. DuVall
  12. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    • Jin Li
    • , Jennifer S. Lee
    • , Philip S. Tsao
    •  & Themistocles L. Assimes
  13. VA Palo Alto Health Care System, Palo Alto, CA, USA

    • Jin Li
    • , Jennifer S. Lee
    • , Philip S. Tsao
    •  & Themistocles L. Assimes
  14. Department of Medicine, Yale School of Medicine, New Haven, CT, USA

    • Aeron M. Small
    •  & John Concato
  15. Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

    • Hua Tang
  16. University of Massachusetts College of Nursing and Health Sciences, Boston, MA, USA

    • Julie A. Lynch
  17. Department of Public Health Sciences, Institute of Personalized Medicine, Penn State College of Medicine, Hershey, PA, USA

    • Dajiang J. Liu
  18. Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    • Pradeep Natarajan
  19. Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

    • Rajiv Chowdhury
    • , Emanuele Di Angelantonio
    •  & John Danesh
  20. Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Danish Saleheen
    •  & Marijana Vujkovic
  21. Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    • Saiju Pyarajan
    •  & J. Michael Gaziano
  22. Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA

    • Benjamin M. Neale
  23. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    • Benjamin M. Neale
  24. Initiative for Noncommunicable Diseases, Health Systems and Population Studies Division, International Centre for Diarrheal Disease Research, Dhaka, Bangladesh

    • Aliya Naheed
  25. Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Kyong-Mi Chang
    •  & Daniel J. Rader
  26. Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA

    • Gonçalo Abecasis
  27. Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, USA

    • Cristen Willer
  28. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA

    • Cristen Willer
  29. Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA

    • Cristen Willer
  30. Geisinger Health System, Danville, PA, USA

    • David J. Carey
  31. Clinical Epidemiology Research Center, VA Connecticut Healthcare System, West Haven, CT, USA

    • John Concato
  32. Department of Medicine, Harvard Medical School, Boston, MA, USA

    • J. Michael Gaziano
    • , Christopher J. O’Donnell
    •  & Daniel J. Rader
  33. Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Daniel J. Rader
  34. Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Daniel J. Rader
  35. Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    • Daniel J. Rader
  36. Atlanta VA Medical Center, Decatur, GA, USA

    • Peter W. F. Wilson
  37. Emory Clinical Cardiovascular Research Institute, Atlanta, GA, USA

    • Peter W. F. Wilson


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  1. Global Lipids Genetics Consortium

    1. Myocardial Infarction Genetics (MIGen) Consortium

      1. The Geisinger-Regeneron DiscovEHR Collaboration

        1. The VA Million Veteran Program


          Concept and design: D.K., T.L.A., S.M.D., K.C., K.-M.C., P.S.T., S.K., D.J.R., P.W.F.W., J.C. and J.M.G. Acquisition, analysis or interpretation of data: D.K., S.M.D., Y.V.S., K.C., T.M.T., J.Ho., D.R.G., S.L.D., J.L., G.M.P., M.C., A.M.S., J.Hu., H.T., J.S.L., Y.-L.H., D.J.L., C.A.E., A.H.L., J.A.L., R.C., P.N., D.S., M.V., A.B., S.P., E.D.A., B.M.N., A.N., A.V.K., J.D., K.-M.C., G.A., C.W., F.E.D., J.E.H. and D.J.C. Drafting of the manuscript: D.K. and T.L.A. Critical revision of the manuscript for important intellectual content: S.M.D., Y.V.S., K.C., P.N., C.W., J.A.L., F.E.D., S.L.D., K.-M.C., C.J.O., P.S.T., S.K., D.J.R. and P.W.W. Administrative, technical or material support: D.K., Y.V.S., K.C., J.Ho., D.R.G., S.L.D., J.A.L., Y.H., J.C., J.M.G., C.J.O., P.S.T, J.E.H., and P.W.W.

          Competing interests

          S.K. reports grant support from Regeneron and Bayer, grant support and personal fees from Aegerion, personal fees from Regeneron Genetics Center, Merck, Celera, Novartis, Bristol-Myers Squibb, Sanofi, AstraZeneca, Alnylam, Eli Lilly and Leerink Partners, personal fees and other support from Catabasis, and other support from San Therapeutics outside the submitted work. He is also the chair of the scientific advisory board at Genomics Plc. T.M.T., A.H.L., A.B., F.E.D. and D.J.C. are employees of Regeneron Pharmaceuticals. G.A. has received consulting income from Regeneron Genetics Center, 23andMe and Helix. S.L.D. has received research grant support from the following for-profit companies through the University of Utah or the Western Institute for Biomedical Research (VA Salt Lake City’s affiliated non-profit): AbbVie Inc., Anolinx LLC, Astellas Pharma Inc., AstraZeneca Pharmaceuticals LP, Boehringer Ingelheim International GmbH, Celgene Corporation, Eli Lilly and Company, Genentech Inc., Genomic Health Inc., Gilead Sciences Inc., GlaxoSmithKline PLC, Innocrin Pharmaceuticals Inc., Janssen Pharmaceuticals Inc., Kantar Health, Myriad Genetic Laboratories Inc., Novartis International AG and PAREXEL International Corporation.

          Corresponding author

          Correspondence to Themistocles L. Assimes.

          Supplementary information

          1. Supplementary Text and Figures

            Supplementary Figures 1–17 and Supplementary Note

          2. Reporting Summary

          3. Supplementary Tables 1–4

          4. Supplementary Tables 5–8

          5. Supplementary Table 9

            826 independent genome-wide lipid variants (across 1,014 associations) identified with GCTA-COJO software

          6. Supplementary Table 10

            Variance explained for 444 previously mapped independent exome-wide variants, 118 novel loci identified in this study, and 826 independent lipid genome-wide variants identified on conditional analysis in this study

          7. Supplementary Table 11

            223 variants (across 223 distinct loci) used for weighted genetic risk score

          8. Supplementary Table 12

            Increase in variance explained as a function of the number of repeated measures in MVP non-Hispanic whites (for a fixed sample size of 171,314 MVP participants; only individuals with five or more measures were included)

          9. Supplementary Tables 13–16

          10. Supplementary Table 17

            Transcriptome-wide association study

          11. Supplementary Table 18

            Black-specific novel low-frequency protein-altering variants associated with lipids

          12. Supplementary Table 19

            Hispanic-specific novel low-frequency protein-altering variants associated with lipids

          13. Supplementary Table 20

            Genome-wide significant pLOF variants for lipids in the MVP discovery analysis

          14. Supplementary Table 21

            Exemplar list of 47 rare damaging mutations in PDE3B from Myocardial Infarction Genetics Consortium exome sequencing data used for coronary artery disease analysis

          15. Supplementary Table 22

            Statistically significant (P < 4.98 × 10–5) phenome-wide association results for DNA sequence variants within genes targeted by lipid-lowering medicines

          16. Supplementary Table 23

            Association of 223-variant lipid genetic risk score with abdominal aortic aneurysm (AAA) risk

          17. Supplementary Tables 24–29

          18. Supplementary Table 30

            CAD association statistics for 118 novel genome-wide significant loci in the MVP lipids GWAS

          About this article

          Publication history