Abstract

The majority of reported complex disease associations for common genetic variants have been identified through meta-analysis, a powerful approach that enables the use of large sample sizes while protecting against common artifacts due to population structure and repeated small-sample analyses sharing individual-level data. As the focus of genetic association studies shifts to rare variants, genes and other functional units are becoming the focus of analysis. Here we propose and evaluate new approaches for performing meta-analysis of rare variant association tests, including burden tests, weighted burden tests, variable-threshold tests and tests that allow variants with opposite effects to be grouped together. We show that our approach retains useful features from single-variant meta-analysis approaches and demonstrate its use in a study of blood lipid levels in 18,500 individuals genotyped with exome arrays.

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Acknowledgements

The authors would like to thank M. Boehnke, X. Wen and S. Zoellner for helpful discussions. This work was supported by research grants R01HG007022 from the National Human Genome Research Institute, R01EY022005 from the National Eye Institute and R01HL117626 from the National Heart, Lung, and Blood Institute. G.M.P. was supported by award T32HL007208 from the National Heart, Lung, and Blood Institute. S.K. is supported by a Research Scholar award from Massachusetts General Hospital (MGH), the Howard Goodman Fellowship from MGH, the Donovan Family Foundation and grant R01HL107816 from the National Heart, Lung, and Blood Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute or the US National Institutes of Health. The WHI program is funded by the National Heart, Lung, and Blood Institute, US National Institutes of Health, US Department of Health and Human Services through contracts N01WH22110, N01WH24152, N01WH32100-2, N01WH32105-6, N01WH32108-9, N01WH32111-13, N01WH32115, N01WH32118-32119, N01WH32122, N01WH42107-26, N01WH42129-32 and N01WH44221. This manuscript was prepared in collaboration with investigators from the WHI and has been approved by the WHI. WHI investigators are listed at https://cleo.whi.org/researchers/SitePages/WHI%20Investigators.aspx. The full list of PROCARDIS acknowledgments is available at http://www.procardis.org/. The Ottawa Heart Genomics Study was supported by Canadian Institutes of Health Research (CIHR) grants MOP-82810, MOP-77682 and MOP-2380941 and Canada Foundation for Innovation (CFI) grant 11966. The studies for the Malmö Diet and Cancer cohort were supported by grants from the Swedish Research Council, the Swedish Heart and Lung Foundation, the Påhlsson Foundation, the Novo Nordic Foundation and European Research Council starting grant StG-282255.

Author information

Author notes

    • Dajiang J Liu
    • , Gina M Peloso
    • , Xiaowei Zhan
    •  & Oddgeir L Holmen

    These authors contributed equally to this work.

    • Sekar Kathiresan
    •  & Gonçalo R Abecasis

    These authors jointly directed this work.

Affiliations

  1. Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.

    • Dajiang J Liu
    • , Xiaowei Zhan
    • , Matthew Zawistowski
    • , Shuang Feng
    •  & Gonçalo R Abecasis
  2. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.

    • Gina M Peloso
    •  & Sekar Kathiresan
  3. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Gina M Peloso
    •  & Sekar Kathiresan
  4. Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA.

    • Gina M Peloso
    •  & Sekar Kathiresan
  5. HUNT Research Centre, Department of Public Health and General Practice, Norwegian University of Science and Technology, Levanger, Norway.

    • Oddgeir L Holmen
    •  & Kristian Hveem
  6. St. Olav Hospital, Trondheim University Hospital, Trondheim, Norway.

    • Oddgeir L Holmen
  7. University of Ottawa Heart Institute, Ottawa, Ontario, Canada.

    • Majid Nikpay
    •  & Ruth McPherson
  8. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.

    • Paul L Auer
    • , Ulrike Peters
    •  & Charles Kooperberg
  9. School of Public Health, University of Wisconsin–Milwaukee, Milwaukee, Wisconsin, USA.

    • Paul L Auer
  10. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

    • Anuj Goel
    • , Martin Farrall
    •  & Hugh Watkins
  11. Department of Cardiovascular Medicine, University of Oxford, Oxford, UK.

    • Anuj Goel
    • , Martin Farrall
    • , Marju Orho-Melander
    • , Hugh Watkins
    •  & Olle Melander
  12. Division of Cardiology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA.

    • He Zhang
    •  & Cristen J Willer
  13. Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan, USA.

    • He Zhang
    •  & Cristen J Willer
  14. Department of Epidemiology, University of Washington School of Public Health, Seattle, Washington, USA.

    • Ulrike Peters
  15. Department of Clinical Sciences, Lund University, Malmö, Sweden.

    • Marju Orho-Melander
    •  & Olle Melander
  16. Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington, USA.

    • Charles Kooperberg
  17. Department of Medicine, Levanger Hospital, Nord-Trøndelag Health Trust, Levanger, Norway.

    • Kristian Hveem
  18. Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.

    • Sekar Kathiresan

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Contributions

D.J.L., S.K. and G.R.A. conceived and designed the study. D.J.L., G.M.P. and X.Z. carried out primary data analysis. D.J.L., X.Z. and S.F. wrote the software package implementing the proposed methodologies. O.L.H., M.N., P.L.A., A.G., H.Z., U.P., M.F., M.O.-M., C.K., R.M., H.W., C.J.W., K.H. and O.M. contributed phenotypes, exome array genotypes and analyses for the study. M.Z. conducted population genetics simulation analysis. D.J.L. and G.R.A. wrote the first version of the manuscript. All authors critically reviewed and approved the manuscript. S.K. and G.R.A. jointly supervised the study.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Dajiang J Liu or Gonçalo R Abecasis.

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DOI

https://doi.org/10.1038/ng.2852

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