TY - JOUR
T1 - Bayesian meta-analysis of genetic association studies with different sets of markers
AU - Verzilli, Claudio
AU - Shah, Tina
AU - Casas, Juan P.
AU - Chapman, Juliet
AU - Sandhu, Manjinder
AU - Debenham, Sally L.
AU - Boekholdt, Matthijs S.
AU - Khaw, Kay Tee
AU - Wareham, Nicholas J.
AU - Judson, Richard
AU - Benjamin, Emelia J.
AU - Kathiresan, Sekar
AU - Larson, Martin G.
AU - Rong, Jian
AU - Sofat, Reecha
AU - Humphries, Steve E.
AU - Smeeth, Liam
AU - Cavalleri, Gianpiero
AU - Whittaker, John C.
AU - Hingorani, Aroon D.
PY - 2008
Y1 - 2008
N2 - Robust assessment of genetic effects on quantitative traits or complex-disease risk requires synthesis of evidence from multiple studies. Frequently, studies have genotyped partially overlapping sets of SNPs within a gene or region of interest, hampering attempts to combine all the available data. By using the example of C-reactive protein (CRP) as a quantitative trait, we show how linkage disequilibrium in and around its gene facilitates use of Bayesian hierarchical models to integrate informative data from all available genetic association studies of this trait, irrespective of the SNP typed. A variable selection scheme, followed by contextualization of SNPs exhibiting independent associations within the haplotype structure of the gene, enhanced our ability to infer likely causal variants in this region with population-scale data. This strategy, based on data from a literature based systematic review and substantial new genotyping, facilitated the most comprehensive evaluation to date of the role of variants governing CRP levels, providing important information on the minimal subset of SNPs necessary for comprehensive evaluation of the likely causal relevance of elevated CRP levels for coronary-heart-disease risk by Mendelian randomization. The same method could be applied to evidence synthesis of other quantitative traits, whenever the typed SNPs vary among studies, and to assist fine mapping of causal variants
AB - Robust assessment of genetic effects on quantitative traits or complex-disease risk requires synthesis of evidence from multiple studies. Frequently, studies have genotyped partially overlapping sets of SNPs within a gene or region of interest, hampering attempts to combine all the available data. By using the example of C-reactive protein (CRP) as a quantitative trait, we show how linkage disequilibrium in and around its gene facilitates use of Bayesian hierarchical models to integrate informative data from all available genetic association studies of this trait, irrespective of the SNP typed. A variable selection scheme, followed by contextualization of SNPs exhibiting independent associations within the haplotype structure of the gene, enhanced our ability to infer likely causal variants in this region with population-scale data. This strategy, based on data from a literature based systematic review and substantial new genotyping, facilitated the most comprehensive evaluation to date of the role of variants governing CRP levels, providing important information on the minimal subset of SNPs necessary for comprehensive evaluation of the likely causal relevance of elevated CRP levels for coronary-heart-disease risk by Mendelian randomization. The same method could be applied to evidence synthesis of other quantitative traits, whenever the typed SNPs vary among studies, and to assist fine mapping of causal variants
U2 - https://doi.org/10.1016/j.ajhg.2008.01.016
DO - https://doi.org/10.1016/j.ajhg.2008.01.016
M3 - Article
C2 - 18394581
SN - 0002-9297
VL - 82
SP - 859
EP - 872
JO - American journal of human genetics
JF - American journal of human genetics
IS - 4
ER -