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

Maller, Julian B., McVean, Gilean, Byrnes, Jake, Vukcevic, Damjan, Palin, Kimmo, Su, Zhan, Howson, Joanna M. M., Auton, Adam, Myers, Simon, Morris, Andrew, Pirinen, Matti, Brown, Matthew A., Burton, Paul R., Caulfield, Mark J., Compston, Alastair, Farrall, Martin, Hall, Alistair S., Hattersley, Andrew T., Hill, Adrian V. S., Mathew, Christopher G., Pembrey, Marcus, Satsangi, Jack, Stratton, Michael R., Worthington, Jane, Craddock, Nick, Hurles, Matthew, Ouwehand, Willem, Parkes, Miles, Rahman, Nazneen, Duncanson, Audrey, Todd, John A., Kwiatkowski, Dominic P., Samani, Nilesh J., Gough, Stephen C. L., McCarthy, Mark I., Deloukas, Panagiotis and Donnelly, Peter (2012) Bayesian refinement of association signals for 14 loci in 3 common diseases. Nature Genetics, 44 12: 1294-1301. doi:10.1038/ng.2435

Author Maller, Julian B.
McVean, Gilean
Byrnes, Jake
Vukcevic, Damjan
Palin, Kimmo
Su, Zhan
Howson, Joanna M. M.
Auton, Adam
Myers, Simon
Morris, Andrew
Pirinen, Matti
Brown, Matthew A.
Burton, Paul R.
Caulfield, Mark J.
Compston, Alastair
Farrall, Martin
Hall, Alistair S.
Hattersley, Andrew T.
Hill, Adrian V. S.
Mathew, Christopher G.
Pembrey, Marcus
Satsangi, Jack
Stratton, Michael R.
Worthington, Jane
Craddock, Nick
Hurles, Matthew
Ouwehand, Willem
Parkes, Miles
Rahman, Nazneen
Duncanson, Audrey
Todd, John A.
Kwiatkowski, Dominic P.
Samani, Nilesh J.
Gough, Stephen C. L.
McCarthy, Mark I.
Deloukas, Panagiotis
Donnelly, Peter
Total Author Count Override 37
Title Bayesian refinement of association signals for 14 loci in 3 common diseases
Journal name Nature Genetics   Check publisher's open access policy
ISSN 1061-4036
Publication date 2012-12
Sub-type Article (original research)
DOI 10.1038/ng.2435
Volume 44
Issue 12
Start page 1294
End page 1301
Total pages 8
Place of publication New York, NY, United States
Publisher Nature Publishing Group
Collection year 2013
Language eng
Formatted 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.
Keyword Genome
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
UQ Diamantina Institute Publications
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Citation counts: TR Web of Science Citation Count  Cited 61 times in Thomson Reuters Web of Science Article | Citations
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