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A Systems Biology approach to determine cell-specific gene regulatory effects of genetic associations in multiple sclerosis

Accepted version
Peer-reviewed

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Article

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Abstract

Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. To overcome these barriers, we have conducted a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS); which analyzed a total of 47,351 cases and 68,284 controls and found more than 200 non-MHC genome-wide associations. Our approach makes extensive use of gene regulatory data generated by the ENCODE and REP projects to build data-driven models of the predicted regulatory effects (PRE) of each associated variant and their flanking correlated variation over a wide range of linkage disequilibrium thresholds. A human protein interactome is used to compute the likelihood that genes with high PRE in a given cell belong to the same pathway. This analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.

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Journal Title

Nature Communications

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Journal ISSN

2041-1723

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Publisher

Nature Publishing Group

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All rights reserved
Sponsorship
National Multiple Sclerosis Society (via Harvard University) (2834020103)
Medical Research Council (G1100125)
National Institutes of Health (NIH) (via University of California) (6399sc)
Cambridge NIHR Biomedical Research Centre,