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Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Nature Genetics volume 43, pages 801–805 (2011)Cite this article

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Abstract

Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes1,2,3,4, myocardial infarction5,6,7, aneurysm8, vertical cup disc ratio9 and at least five cancers10,11,12,13,14,15,16. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.

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Figure 1: Comparison of targeted sequencing to 1000 Genomes Pilot 1 data.
Figure 2: Percentage of variation at chromosome 9p21 captured in the type 2 diabetes disease cohort by different imputation scenarios.
Figure 3: Comparison of imputation from a genotyped (Geno) reference panel, directly from high-coverage resequencing data (Seq) and directly from 1000 Genomes Pilot 1 data.
Figure 4: Association results for type 2 diabetes and myocardial infarction at chromosome 9p21.

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Acknowledgements

Sample collections in the DGI study were funded by grants from the Sigrid Juselius and Folkhälsan foundations and from the Swedish Research Council (L.G.). The DGI GWAS study was supported by a grant from Novartis. The MIGen study was funded by the US National Institutes of Health (NIH) and the US National Heart, Lung, and Blood Institute's STAMPEED genomics research program through a grant to D.A. (R01 HL087676). S.K. is supported by a Doris Duke Charitable Foundation Clinical Scientist Development Award, a charitable gift from the Fannie E. Rippel Foundation, the Donovan Family Foundation, a career development award from the NIH and the Department of Medicine and Cardiovascular Research Center at Massachusetts General Hospital. D.A. and J.S. are supported in part by a Distinguished Clinical Scholar Award from the Doris Duke Charitable Foundation (to D.A.). Next-generation sequencing for this work was carried out by the Broad Institute Sequencing Platform, and genotyping was carried out by the Broad Institute Genetic Analysis Platform. We acknowledge their excellence and collaboration on this study. Sequencing was supported in part by a grant from the US National Human Genome Research Institute and by the Broad Institute. We thank M. Rivas, A. Sivachenco and K. Garimella for helpful discussions on sequencing, and B. Voight, S. Ripke and R. Do for helpful discussions on imputation.

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Authors and Affiliations

  1. Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Jessica Shea, Vineeta Agarwala, Anthony A Philippakis, Jared Maguire, Eric Banks, Mark DePristo, Brian Thomson, Candace Guiducci, Sekar Kathiresan, Stacey Gabriel, Noël P Burtt, Mark J Daly & David Altshuler

  2. Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts, USA

    Jessica Shea

  3. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA

    Jessica Shea, Vineeta Agarwala, Anthony A Philippakis & David Altshuler

  4. Program in Biophysics, Harvard University, Cambridge, Massachusetts, USA

    Vineeta Agarwala & Anthony A Philippakis

  5. Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Harvard Medical School, Boston, Massachusetts, USA

    Vineeta Agarwala & Anthony A Philippakis

  6. Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA

    Anthony A Philippakis, Sekar Kathiresan, Mark J Daly & David Altshuler

  7. Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA

    Anthony A Philippakis

  8. Genetic Analysis Platform, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Robert C Onofrio

  9. Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA

    Sekar Kathiresan, Mark J Daly & David Altshuler

  10. Cardiovascular Research Center, Massachusetts General Hospital, Boston, Massachusetts, USA

    Sekar Kathiresan

  11. Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA

    Sekar Kathiresan, Mark J Daly & David Altshuler

  12. Department of Clinical Sciences, Diabetes and Endocrinology Research Unit, University Hospital Malmö, Lund University, Malmö, Sweden

    Leif Groop

  13. Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, USA

    David Altshuler

Authors
  1. Jessica Shea
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The Myocardial Infarction Genetics Consortium

Contributions

J.S., V.A., A.A.P. and D.A. wrote the manuscript; L.G. and the Myocardial Infarction Genomics Consortium provided clinical samples; C.G., R.C.O., N.P.B. and S.G. contributed to next-generation sequencing data generation; A.A.P., J.M., E.B., M.D.P., S.G., M.J.D. and D.A. carried out sequencing analysis and variant calling; J.S., V.A., M.J.D. and D.A. carried out imputation and association analysis; J.S., V.A., B.T., C.G. and N.P.B. carried out genotyping and analysis.

Corresponding author

Correspondence to David Altshuler.

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The authors declare no competing financial interests.

Additional information

A list of members is provided in the Supplementary Note.

Supplementary information

Supplementary Text and Figures

Supplementary Table 1, Supplementary Figures 1–11 and Supplementary Note. (PDF 5012 kb)

Supplementary Table 2

List of PCR primers and hybrid selection baits used in sequencing (XLS 268 kb)

Supplementary Table 3

List of all variants identified in high coverage sequencing (XLS 340 kb)

Supplementary Table 4

Validation analysis for SNPs identified in sequencing on 9p21 (XLS 112 kb)

Supplementary Table 5

List of variants in the genotyped reference panel for 9p21 (XLS 140 kb)

Supplementary Table 6

Imputation and association results for T2D and MI on 9p21 (XLS 275 kb)

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Shea, J., Agarwala, V., Philippakis, A. et al. Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction. Nat Genet 43, 801–805 (2011). https://doi.org/10.1038/ng.871

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