This article appears in the following Human Molecular Genetics issue: Association Studies [View the issue table of contents]
Genome-wide association studies: implications for multiethnic samples
1 Department of Preventive Medicine and Epidemiology, Loyola University Chicago Stritch School of Medicine, 2160 S. First Ave., Maywood, IL 60153 USA 2 Department of Biostatistics and Epidemiology, Case Western Reserve University, Cleveland, OH USA
* To whom correspondence should be addressed at: Tel: +1 7083279010; Fax: +1 7083279009; Email: rcooper{at}lumc.edu
Received July 11, 2008; Accepted August 24, 2008
The current gene mapping for complex diseases is heavily weighted by studies of population samples from northern Europe. To capture the full range of genetic diversity and exploit the potential of genetic epidemiology to identify important variants, multiple additional populations will need to be examined. The conduct of genome-wide association studies will therefore confront many of the challenges identified in the first generation of candidate gene and linkage studies, with a substantial increase in complexity. Initial efforts to map causal effects will have to take account of varying patterns of linkage disequilibrium through careful attention to local haplotype structure. Refined statistical techniques that permit joint analyses of samples from multiple populations will also be required, as well as improved methods to account for on-going gene flow between populations with geographically distinct ancestral origins. This variation can either be an impediment, slowing the process of replication, or an opportunity, allowing finer dissection of the relevant variants. Clinical translation of these data will present major challenges. Large cosmopolitan populations, such as those found in large urban centers, are likely to exhibit both known and cryptic sub-structure across groups, as well as admixture within individuals. Great care will need to be devoted to generalizability of association findings to avoid their premature adoption as predictive tests in the face of this widespread heterogeneity.
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