Review
European Journal of Human Genetics (2008) 16, 554–564; doi:10.1038/ejhg.2008.12; published online 20 February 2008
The success of the genome-wide association approach: a brief story of a long struggle
Ku Chee Seng1 and Chia Kee Seng1
1Center for Molecular Epidemiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
Correspondence: CS Ku or Professor KS Chia, Center for Molecular Epidemiology, Yong Loo Lin School of Medicine, National University of Singapore, 16 Medical Drive, Singapore 117597, Singapore. Tel: +65 8138 8095; Fax: 6478 9913; E-mail: cmekcs@nus.edu.sg, cofcks@nus.edu.sg
Received 20 July 2007; Revised 19 December 2007; Accepted 11 January 2008; Published online 20 February 2008.
Abstract
The genome-wide association approach has been the most powerful and efficient study design thus far in identifying genetic variants that are associated with complex human diseases. This approach became feasible as the result of several key advancements in genetic knowledge, genotyping technologies, statistical analysis algorithms and the availability of large collections of cases and controls. With all these necessary tools in hand, many genome-wide association studies were recently completed, and many more studies which will explore the genetic basis of various complex diseases and quantitative traits are soon to come. This approach has started to reap the fruits of its labor over the past several months. Publications of genome-wide association studies in several complex diseases such as inflammatory bowel disease, type-2 diabetes, breast cancer and prostate cancer have been abundant in the first half of this year. The aims of this review are firstly, to provide a timely summary for most of the genome-wide association studies that have been published until June/July 2007 and secondly, to evaluate to what extent these results have been validated in subsequent replication studies.
Keywords:
genome-wide association, complex diseases, linkage disequilibrium, haplotype-tagging SNPs, copy number variations, International HapMap Project
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