Login to MyKarger

New to MyKarger? Click here to sign up.

Login with Facebook

Forgot Password? Reset your password

Authors, Editors, Reviewers

For Manuscript Submission, Check or Review Login please go to Submission Websites List.

Submission Websites List

Institutional Login (Shibboleth)

For the academic login, please select your country in the dropdown list. You will be redirected to verify your credentials.

Table of Contents
Vol. 73, No. 1, 2012
Issue release date: March 2012
Section title: Original Paper
Free Access
Hum Hered 2012;73:35–46

On the Meta-Analysis of Genome-Wide Association Studies: A Robust and Efficient Approach to Combine Population and Family-Based Studies

Won S.a, b · Lu Q.c · Bertram L.d, e · Tanzi R.E.d · Lange C.f–j
aDepartment of Applied Statistics, and bThe Research Center for Data Science, Chung-Ang University, Seoul, Republic of Korea; cDepartment of Epidemiology, Michigan State University, East Lansing, Mich., dGenetics and Aging Research Unit, Department of Neurology, Massachusetts General Hospital, Charlestown, Mass., USA; eNeuropsychiatric Genetics Group, Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany; fDepartment of Biostatistics, Harvard School of Public Health, gHarvard Medical School, and hCenter for Genomic Medicine, Brigham and Women’s Hospital, Boston, Mass., USA; iInstitute for Genomic Mathematics, University of Bonn, and jGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
email Corresponding Author

Sungho Won

Department of Applied Statistics

Chung-Ang University

Seoul 156-756 (Republic of Korea)

Tel. +82 2 820 5217, E-Mail swon@cau.ac.kr

Do you have an account?

Login Information

Contact Information

I have read the Karger Terms and Conditions and agree.


For the meta-analysis of genome-wide association studies, we propose a new method to adjust for the population stratification and a linear mixed approach that combines family-based and unrelated samples. The proposed approach achieves similar power levels as a standard meta-analysis which combines the different test statistics or p values across studies. However, by virtue of its design, the proposed approach is robust against population admixture and stratification, and no adjustments for population admixture and stratification, even in unrelated samples, are required. Using simulation studies, we examine the power of the proposed method and compare it to standard approaches in the meta-analysis of genome-wide association studies. The practical features of the approach are illustrated with a meta-analysis of three genome-wide association studies for Alzheimer’s disease. We identify three single nucleotide polymorphisms showing significant genome-wide association with affection status. Two single nucleotide polymorphisms are novel and will be verified in other populations in our follow-up study.

© 2012 S. Karger AG, Basel

Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: March 13, 2011
Accepted: July 15, 2011
Published online: January 18, 2012
Issue release date: March 2012

Number of Print Pages: 12
Number of Figures: 2
Number of Tables: 5

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

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

Copyright / Drug Dosage / Disclaimer

Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher or, in the case of photocopying, direct payment of a specified fee to the Copyright Clearance Center.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.