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Table of Contents
Vol. 69, No. 2, 2010
Issue release date: January 2010
Section title: Original Paper
Hum Hered 2010;69:71–79

Allelic Heterogeneity in Genetic Association Meta-Analysis: An Application to DTNBP1 and Schizophrenia

Maher B.S.a · Reimers M.A.b · Riley B.P.a · Kendler K.S.a
aDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, and bDepartment of Biostatistics, Virginia Commonwealth University, Richmond, Va., USA
email Corresponding Author

Dr. Brion Maher

Department of Psychiatry

Virginia Commonwealth University

Richmond, VA 23298-0126 (USA)

Tel. +1 804 828 8928, Fax +1 804 828 1471, E-Mail bsmaher@vcu.edu

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Background/Aims: Meta-analysis of genetic association studies is a useful approach when individual investigations do not yield studywise significant results but the evidence across studies is modest and homogeneous. Current meta-analysis methods account for heterogeneity by down-weighting studies as a function of between-study variance. We contend that current approaches may obscure interesting phenomena in genetic association data. However, an appropriate approach to examining heterogeneity across studies is lacking. Methods: We develop a novel approach, based on the EM algorithm, to detect allelic heterogeneity, identify subpopulations and assign studies to those subpopulations. We then apply these methods to the association between DTNBP1 and schizophrenia (Scz), one of the most studied relationships in complex disease genetics. We examined 32 published and unpublished population and family-based association studies containing up to 14 SNPs spanning the DTNBP1 locus. Results: We explored heterogeneity in several ways including meta-regression and approaches aimed at exploring the mixture of heterogeneous studies at a particular SNP. We found significant evidence for a mixture of association distributions at multiple loci. Conclusion: We propose a novel approach that is broadly applicable and may be useful in large scale genetic association meta-analyses to detect significant allelic heterogeneity.

© 2009 S. Karger AG, Basel

Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: March 30, 2009
Accepted: June 24, 2009
Published online: December 04, 2009
Issue release date: January 2010

Number of Print Pages: 9
Number of Figures: 1
Number of Tables: 1

ISSN: 0001-5652 (Print)
eISSN: 1423-0062 (Online)

For additional information: http://www.karger.com/HHE

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