Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/97956
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Type: Journal article
Title: Mining the human phenome using allelic scores that index biological intermediates
Author: Evans, D.
Brion, M.
Paternoster, L.
Kemp, J.
McMahon, G.
Munafo, M.
Whitfield, J.
Medland, S.
Montgomery, G.
GIANT consortium
CRP consortium
TAG Consortium
Timpson, N.
St Pourcain, B.
Lawlor, D.
Martin, N.
Dehghan, A.
Hirschhorn, J.
Smith, G.
Citation: PLoS Genetics, 2013; 9(10):e1003919-1-e1003919-15
Publisher: Public Library of Science
Issue Date: 2013
ISSN: 1553-7390
1553-7404
Statement of
Responsibility: 
David M. Evans, Marie Jo A. Brion, Lavinia Paternoster, John P. Kemp, George McMahon, Marcus Munafo, John B. Whitfield, Sarah E. Medland, Grant W. Montgomery, The GIANT consortium, The CRP consortium, The TAG Consortium, Nicholas J. Timpson, Beate St. Pourcain, Debbie A. Lawlor, Nicholas G. Martin, Abbas Dehghan, Joel Hirschhorn, George Davey Smith
Abstract: It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.
Keywords: Genome-Wide Association Study
Description: GIANT Consortium contributor; Lyle Palmer for the University of Adelaide
Rights: © 2013 Evans et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
RMID: 0030026910
DOI: 10.1371/journal.pgen.1003919
Grant ID: http://purl.org/au-research/grants/nhmrc/241944
http://purl.org/au-research/grants/nhmrc/339462
http://purl.org/au-research/grants/nhmrc/389927
http://purl.org/au-research/grants/nhmrc/389875
http://purl.org/au-research/grants/nhmrc/389891
http://purl.org/au-research/grants/nhmrc/389892
http://purl.org/au-research/grants/nhmrc/389938
http://purl.org/au-research/grants/nhmrc/442915
http://purl.org/au-research/grants/nhmrc/442981
http://purl.org/au-research/grants/nhmrc/496739
http://purl.org/au-research/grants/nhmrc/552485
http://purl.org/au-research/grants/nhmrc/552498
http://purl.org/au-research/grants/arc/A7960034
http://purl.org/au-research/grants/arc/A79906588
http://purl.org/au-research/grants/arc/A79801419
http://purl.org/au-research/grants/arc/DP0770096
http://purl.org/au-research/grants/arc/DP0212016
http://purl.org/au-research/grants/arc/DP0343921
Appears in Collections:Medicine publications

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