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Bayesian refinement of association signals for 14 loci in 3 common diseases

Abstract

To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on posterior probability, to contain the causal disease-associated SNPs. In 3 of the 14 regions, TCF7L2 (T2D), CTLA4 (Graves' disease) and CDKN2A-CDKN2B (T2D), much of the posterior probability rested on a single SNP, and, in 4 other regions (CDKN2A-CDKN2B (CAD) and CDKAL1, FTO and HHEX (T2D)), the 95% sets were small, thereby excluding most SNPs as potentially causal. Very few SNPs in our credible sets had annotated functions, illustrating the limitations in understanding the mechanisms underlying susceptibility to common diseases. Our results also show the value of more detailed mapping to target sequences for functional studies.

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Figure 1: Association plots showing the signal strength in each region as the posterior probability of each SNP passing quality control.

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Acknowledgements

We are grateful to D. Altshuler and colleagues at the Broad Institute for provision of SNP discovery information in some of our fine-mapping regions. We acknowledge the many physicians, research fellows and research nurses who contributed to the various case collections and the collection teams and senior management of the UK Blood Services responsible for the UK Blood Services Collection. The principal funder of the project was the Wellcome Trust. For the 1958 Birth Cohort, venous blood collection was funded by the UK Medical Research Council, and cell line production and DNA extraction and processing were funded by the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory. Many of the authors of this paper received funding from the NIHR Biomedical Research Centers.

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The study was conceptually designed by M.A.B., P.R.B., M.J.C., A.C., M.F., A.S.H., A.T.H., A.V.S.H., C.G.M., M. Pembrey, J.S., M.R.S., J.W., N.C., M.H., W.O., M. Parkes, N.R., A.D., J.A.T., D.P.K., N.J.S., S.C.L.G., M.I.M., P. Deloukas and P. Donnelly. The study was implemented by P. Deloukas, J.B.M., S.M., A.M., G.M., D.P.K., M.I.M., M.A.B., N.R., J.A.T., N.J.S. and P. Donnelly. Statistical analyses were performed by J.B.M., J.B., D.V., Z.S., K.P., J.M.M.H., A.A., M. Pirinen, G.M. and P. Donnelly. The paper was written by P. Donnelly, G.M., M.I.M., N.J.S., S.C.L.G., J.A.T., J.M.M.H. and J.B.M.

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Correspondence to Peter Donnelly.

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Supplementary Figures 1–21, Supplementary Tables 1–13 and Supplementary Note (PDF 2664 kb)

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The Wellcome Trust Case Control Consortium., Maller, J., McVean, G. et al. Bayesian refinement of association signals for 14 loci in 3 common diseases. Nat Genet 44, 1294–1301 (2012). https://doi.org/10.1038/ng.2435

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