Review
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World J Med Genet. Dec 27, 2011; 1(1): 23-35
Published online Dec 27, 2011. doi: 10.5496/wjmg.v1.i1.23
Genome-wide association studies: Where we are heading?
Xiaoyi Gao, Todd L Edwards
Xiaoyi Gao, Department of Ophthalmology and Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States
Todd L Edwards, Center for Human Genetics Research, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN 37203, United States
Author contributions: Gao X prepared the first draft of the manuscript, developed the themes and overall structure; Edwards TL edited, wrote some sections and advised on the content and references.
Supported by NIH grant 5U10EY011753-12 and the James H Zumberge Faculty Research and Innovation Fund at the University of Southern California (to Gao X) (in part); Vanderbilt Clinical and Translational Research Scholar award 5KL2RR024975 (to Edwards TL)
Correspondence to: Xiaoyi Gao, PhD, Department of Ophthalmology and Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States. ray.x.gao@gmail.com
Telephone: +1-323-4426509 Fax: +1-323-4426412
Received: July 12, 2011
Revised: October 20, 2011
Accepted: December 17, 2011
Published online: December 27, 2011
Abstract

We have witnessed tremendous success in genome-wide association studies (GWAS) in recent years. Since the identification of variants in the complement factor H gene on the risk of age-related macular degeneration, GWAS have become ubiquitous in genetic studies and have led to the identification of genetic variants that are associated with a variety of complex human diseases and traits. These discoveries have changed our understanding of the biological architecture of common, complex diseases and have also provided new hypotheses to test. New tools, such as next-generation sequencing, will be an important part of the future of genetics research; however, GWAS studies will continue to play an important role in disease gene discovery. Many traits have yet to be explored by GWAS, especially in minority populations, and large collaborative studies are currently being conducted to maximize the return from existing GWAS data. In addition, GWAS technology continues to improve, increasing genomic coverage for major global populations and decreasing the cost of experiments. Although much of the variance attributable to genetic factors for many important traits is still unexplained, GWAS technology has been instrumental in mapping over a thousand genes to hundreds of traits. More discoveries are made each month and the scale, quality and quantity of current work has a steady trend upward. We briefly review the current key trends in GWAS, which can be summarized with three goals: increase power, increase collaborations and increase populations.

Keywords: Genome-wide association studies; Single nucleotide polymorphisms; Sequencing; Genotype imputation; Meta-analysis; Genetic consortium