Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
Todd, John Andrew
Human Molecular Genetics
Oxford University Press
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Guo, H., Fortune, M. D., Burren, O., Schofield, E., Todd, J. A., & Wallace, C. (2015). Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases. Human Molecular Genetics, 24 3305-3313. https://doi.org/10.1093/hmg/ddv077
The genes and cells that mediate genetic associations identified through genome-wide association studies (GWAS) are only partially understood. Several studies that have investigated the genetic regulation of gene expression have shown that disease-associated variants are over-represented amongst expression quantitative trait loci (eQTL) variants. Evidence for colocalisation of eQTL and disease causal variants can suggest causal genes and cells for these genetic associations. Here, we used colocalisation analysis to investigate whether 595 genetic associations to ten immune-mediated diseases are consistent with a causal variant that regulates, in cis, gene expression in resting B cells, and in resting and stimulated monocytes. Previously published candidate causal genes were over-represented amongst genes exhibiting colocalisation (odds ratio > 1.5), and we identified evidence for colocalisation (posterior odds > 5) between cis eQTLs in at least one cell type and at least one disease for six genes: ADAM15, RGS1, CARD9, LTBR, CTSH and SYNGR1. We identified cell-specific effects, such as for CTSH, the expression of which in monocytes, but not in B cells, may mediate type 1 diabetes and narcolepsy associations in the chromosome 15q25.1 region. Our results demonstrate the utility of integrating genetic studies of disease and gene expression for highlighting causal genes and cell types.
This work was supported by the JDRF [9-2011-253], the Wellcome Trust  and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre. The research leading to these results has received funding from the European Union′s 7th Framework Programme (FP7/2007-2013) under grant agreement no.241447 (NAIMIT). The Cambridge Institute for Medical Research (CIMR) is in receipt of a Wellcome Trust Strategic Award . The Wellcome Trust funded C.W. and H.G.  and M.D.F. . ImmunoBase.org is supported by Eli Lilly and Company. Funding to pay the Open Access publication charges for this article was provided by the Wellcome Trust.
External DOI: https://doi.org/10.1093/hmg/ddv077
This record's URL: https://www.repository.cam.ac.uk/handle/1810/247700
Attribution 2.0 UK: England & Wales
Licence URL: http://creativecommons.org/licenses/by/2.0/uk/
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