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

Julian B. Maller; Gilean McVean; Jake Byrnes; Damjan Vukcevic; Kimmo Palin; Zhan Su; Joanna M.M. Howson; Adam Auton; Simon Myers; Andrew Morris; Matti Pirinen; Matthew A. Brown; Paul R. Burton; Mark J. Caulfield; Alastair Compston; Martin Farrall; Alistair S. Hall; Andrew T. Hattersley; Adrian V.S. Hill; Christopher G. Mathew; Marcus Pembrey; Jack Satsangi; Michael R. Stratton; Jane Worthington; Nick Craddock; Matthew Hurles; Willem Ouwehand; Miles Parkes; Nazneen Rahman; Audrey Duncanson; John A. Todd; Dominic P. Kwiatkowski; Nilesh J. Samani; Stephen C.L. Gough; Mark I. McCarthy; Panagiotis Deloukas; Peter Donnelly

doi:10.1038/ng.2435

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

Julian B. Maller, Gilean McVean, Jake Byrnes, Damjan Vukcevic, Kimmo Palin, Zhan Su, Joanna M.M. Howson, Adam Auton, Simon Myers, Andrew Morris, Matti Pirinen, Matthew A. Brown, Paul R. Burton, Mark J. Caulfield, Alastair Compston, Martin Farrall, Alistair S. Hall, Andrew T. Hattersley, Adrian V.S. Hill, Christopher G. MathewMarcus Pembrey, Jack Satsangi, Michael R. Stratton, Jane Worthington, Nick Craddock, Matthew Hurles, Willem Ouwehand, Miles Parkes, Nazneen Rahman, Audrey Duncanson, John A. Todd, Dominic P. Kwiatkowski, Nilesh J. Samani, Stephen C.L. Gough, Mark I. McCarthy, Panagiotis Deloukas, Peter Donnelly

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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.

Original language	English (US)
Pages (from-to)	1294-1301
Number of pages	8
Journal	Nature Genetics
Volume	44
Issue number	12
DOIs	https://doi.org/10.1038/ng.2435
State	Published - Dec 2012
Externally published	Yes

ASJC Scopus subject areas

Genetics

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Maller, J. B., McVean, G., Byrnes, J., Vukcevic, D., Palin, K., Su, Z., Howson, J. M. M., Auton, A., Myers, S., Morris, A., Pirinen, M., Brown, M. A., Burton, P. R., Caulfield, M. J., Compston, A., Farrall, M., Hall, A. S., Hattersley, A. T., Hill, A. V. S., ... Donnelly, P. (2012). Bayesian refinement of association signals for 14 loci in 3 common diseases. Nature Genetics, 44(12), 1294-1301. https://doi.org/10.1038/ng.2435

Maller, JB, McVean, G, Byrnes, J, Vukcevic, D, Palin, K, Su, Z, Howson, JMM, Auton, A, Myers, S, Morris, A, Pirinen, M, Brown, MA, Burton, PR, Caulfield, MJ, Compston, A, Farrall, M, Hall, AS, Hattersley, AT, Hill, AVS, Mathew, CG, Pembrey, M, Satsangi, J, Stratton, MR, Worthington, J, Craddock, N, Hurles, M, Ouwehand, W, Parkes, M, Rahman, N, Duncanson, A, Todd, JA, Kwiatkowski, DP, Samani, NJ, Gough, SCL, McCarthy, MI, Deloukas, P & Donnelly, P 2012, 'Bayesian refinement of association signals for 14 loci in 3 common diseases', Nature Genetics, vol. 44, no. 12, pp. 1294-1301. https://doi.org/10.1038/ng.2435

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title = "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.",

author = "Maller, {Julian B.} and Gilean McVean and Jake Byrnes and Damjan Vukcevic and Kimmo Palin and Zhan Su and Howson, {Joanna M.M.} and Adam Auton and Simon Myers and Andrew Morris and Matti Pirinen and Brown, {Matthew A.} and Burton, {Paul R.} and Caulfield, {Mark J.} and Alastair Compston and Martin Farrall and Hall, {Alistair S.} and Hattersley, {Andrew T.} and Hill, {Adrian V.S.} and Mathew, {Christopher G.} and Marcus Pembrey and Jack Satsangi and Stratton, {Michael R.} and Jane Worthington and Nick Craddock and Matthew Hurles and Willem Ouwehand and Miles Parkes and Nazneen Rahman and Audrey Duncanson and Todd, {John A.} and Kwiatkowski, {Dominic P.} and Samani, {Nilesh J.} and Gough, {Stephen C.L.} and McCarthy, {Mark I.} and Panagiotis Deloukas and Peter Donnelly",

note = "Funding Information: 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.",

year = "2012",

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doi = "10.1038/ng.2435",

language = "English (US)",

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pages = "1294--1301",

journal = "Nature Genetics",

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T1 - Bayesian refinement of association signals for 14 loci in 3 common diseases

AU - Maller, Julian B.

AU - McVean, Gilean

AU - Byrnes, Jake

AU - Vukcevic, Damjan

AU - Palin, Kimmo

AU - Su, Zhan

AU - Howson, Joanna M.M.

AU - Auton, Adam

AU - Myers, Simon

AU - Morris, Andrew

AU - Pirinen, Matti

AU - Brown, Matthew A.

AU - Burton, Paul R.

AU - Caulfield, Mark J.

AU - Compston, Alastair

AU - Farrall, Martin

AU - Hall, Alistair S.

AU - Hattersley, Andrew T.

AU - Hill, Adrian V.S.

AU - Mathew, Christopher G.

AU - Pembrey, Marcus

AU - Satsangi, Jack

AU - Stratton, Michael R.

AU - Worthington, Jane

AU - Craddock, Nick

AU - Hurles, Matthew

AU - Ouwehand, Willem

AU - Parkes, Miles

AU - Rahman, Nazneen

AU - Duncanson, Audrey

AU - Todd, John A.

AU - Kwiatkowski, Dominic P.

AU - Samani, Nilesh J.

AU - Gough, Stephen C.L.

AU - McCarthy, Mark I.

AU - Deloukas, Panagiotis

AU - Donnelly, Peter

N1 - Funding Information: 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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N2 - 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.

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

Abstract

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