This article appears in the following Human Molecular Genetics issue: Association Studies [View the issue table of contents]
Genome-wide association studies: potential next steps on a genetic journey
1 Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK 2 Wellcome Trust Centre for Human Genetics, University of Oxford, Old Road, Headington, Oxford OX3 7BN, UK 3 Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LJ, UK 4 Program in Genomics and Divisions of Genetics and Endocrinology, Children's Hospital, Boston, MA 02115, USA 5 Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA 6 Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
* To whom correspondence should be addressed. Tel: +44 1865 857298; Fax: +44 1865 857299; Email: mark.mccarthy{at}drl.ox.ac.uk (M.I.M.); Children's Hospital, Enders 561, 300 Longwood Avenue, Boston, MA 02115, USA. Tel: +1 617 9192129; Fax: +1 617 7300253; Email: joelh{at}broad.mit.edu (J.N.H.)
Received September 2, 2008; Accepted September 5, 2008
Genome-wide association studies have successfully identified numerous loci at which common variants influence disease risk or quantitative traits. Despite these successes, the variants identified by these studies have generally explained only a small fraction of the heritable component of disease risk, and have not pinpointed with certainty the causal variant(s) at the associated loci. Furthermore, the mechanisms of action by which associated loci influence disease or quantitative phenotypes are often unclear, because we do not know through which gene(s) the associated variants exert their effects or because these gene(s) are of unknown function or have no clear connection to known disease biology. Thus, the initial set of genome-wide association studies serve as a starting point for future genetic and functional studies. We outline possible next steps that may help accelerate progress from genetic studies to the biological knowledge that can guide the development of predictive, preventive, or therapeutic measures.
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