Article

Review Article

Ann Lab Med 2015; 35(3): 283-287

Published online May 1, 2015 https://doi.org/10.3343/alm.2015.35.3.283

Copyright © Korean Society for Laboratory Medicine.

Meta-Analysis of Genetic Association Studies

Young Ho Lee, M.D.

Division of Rheumatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea

Correspondence to: Young Ho Lee
Division of Rheumatology, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, 73 Inchon-ro, Seongbuk-gu, Seoul 136-705, Korea
Tel: +82-2-920-5645
Fax: +82-2-922-5974
E-mail: lyhcgh@korea.ac.kr

Received: July 15, 2014; Revised: November 2, 2014; Accepted: March 4, 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The object of this review is to help readers to understand meta-analysis of genetic association study. Genetic association studies are a powerful approach to identify susceptibility genes for common diseases. However, the results of these studies are not consistently reproducible. In order to overcome the limitations of individual studies, larger sample sizes or meta-analysis is required. Meta-analysis is a statistical tool for combining results of different studies on the same topic, thus increasing statistical strength and precision. Meta-analysis of genetic association studies combines the results from independent studies, explores the sources of heterogeneity, and identifies subgroups associated with the factor of interest. Meta-analysis of genetic association studies is an effective tool for garnering a greater understanding of complex diseases and potentially provides new insights into gene–disease associations.

Keywords: Gene, Polymorphism, Association study, Meta-analysis