The Power of Meta-Analysis in Genome-Wide Association Studies

Author:

Panagiotou Orestis A.1,Willer Cristen J.2,Hirschhorn Joel N.3,Ioannidis John P.A.4

Affiliation:

1. Clinical and Molecular Epidemiology Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece;

2. Department of Internal Medicine, Department of Human Genetics, and Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan 48109;

3. Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital; Department of Genetics, Harvard Medical School; and Program in Medical and Population Genetics, Broad Institute, Boston, Massachusetts 02115;

4. Stanford Prevention Research Center, Department of Medicine, Department of Health Research and Policy, and Department of Statistics, Stanford University, Stanford, California 94305;

Abstract

Meta-analysis of multiple genome-wide association (GWA) studies has become common practice over the past few years. The main advantage of this technique is the maximization of power to detect subtle genetic effects for common traits. Moreover, one can use meta-analysis to probe and identify heterogeneity in the effect sizes across the combined studies. In this review, we systematically appraise and evaluate the characteristics of GWA meta-analyses with 10,000 or more subjects published up to June 2012. We provide an overview of the current landscape of variants discovered by GWA meta-analyses, and we discuss and assess with extrapolations from empirical data the value of larger meta-analyses for the discovery of additional genetic associations and new biology in the future. Finally, we discuss some emerging logistical and practical issues related to the conduct of meta-analysis of GWA studies.

Publisher

Annual Reviews

Subject

Genetics(clinical),Genetics,Molecular Biology

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