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Table of Contents
Vol. 66, No. 1, 2008
Issue release date: March 2008
Section title: Original Paper
Free Access
Hum Hered 2008;66:35–49
(DOI:10.1159/000114164)

Meta-Analysis of 23 Type 2 Diabetes Linkage Studies from the International Type 2 Diabetes Linkage Analysis Consortium

Guan W.a · Pluzhnikov A.b · Cox N.J.b · Boehnke M.a
aDepartment of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, Mich., bSection of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, Ill., USA
email Corresponding Author

Abstract

Background: The International Type 2 Diabetes Linkage Analysis Consortium was formed to localize type 2 diabetes predisposing variants based on 23 autosomal linkage scans. Methods: We carried out meta-analysis using the genome scan meta-analysis (GSMA) method which divides the genome into bins of ∼30 cM, ranks the best linkage results in each bin for each sample, and then sums the ranks across samples. We repeated the meta-analysis using 2 cM bins, and/or replacing bin ranks with measures of linkage evidence: bin maximum LOD score or bin minimum p value for bins with p value <0.05 (truncated p value). We also carried out computer simulations to assess the empirical type I error rates of these meta-analysis methods. Results: Our analyses provided modest evidence for type 2 diabetes-predisposing variants on chromosomes 4, 10, and 14 (using LOD scores or truncated p values), or chromosome 10 and 16 (using ranks). Our simulation results suggested that uneven marker density across studies results in substantial variation in empirical type I error rates for all meta-analysis methods, but that 2 cM bins and scores that make more explicit use of linkage evidence, especially the truncated p values, reduce this problem. Conclusion: We identified regions modestly linked with type 2 diabetes by summarizing results from 23 autosomal genome scans.

© 2008 S. Karger AG, Basel


  

Key Words

  • Gene mapping
  • Genetics
  • GSMA
  • Linkage analysis
  • Meta-analysis
  • Type 2 diabetes

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Author Contacts

Michael Boehnke, PhD
Department of Biostatistics, School of Public Health
University of Michigan, 1420 Washington Heights
Ann Arbor, MI 48109-2029 (USA)
Tel. +1 734 936 1001, Fax +1 734 615 8322, E-Mail boehnke@umich.edu

  

Article Information

Received: June 4, 2007
Accepted after revision: September 5, 2007
Published online: January 28, 2007
Number of Print Pages : 15
Number of Figures : 2, Number of Tables : 7, Number of References : 56

  

Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 66, No. 1, Year 2008 (Cover Date: March 2008)

Journal Editor: Devoto, M. (Philadelphia, Pa.)
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 goverment 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.

Abstract

Background: The International Type 2 Diabetes Linkage Analysis Consortium was formed to localize type 2 diabetes predisposing variants based on 23 autosomal linkage scans. Methods: We carried out meta-analysis using the genome scan meta-analysis (GSMA) method which divides the genome into bins of ∼30 cM, ranks the best linkage results in each bin for each sample, and then sums the ranks across samples. We repeated the meta-analysis using 2 cM bins, and/or replacing bin ranks with measures of linkage evidence: bin maximum LOD score or bin minimum p value for bins with p value <0.05 (truncated p value). We also carried out computer simulations to assess the empirical type I error rates of these meta-analysis methods. Results: Our analyses provided modest evidence for type 2 diabetes-predisposing variants on chromosomes 4, 10, and 14 (using LOD scores or truncated p values), or chromosome 10 and 16 (using ranks). Our simulation results suggested that uneven marker density across studies results in substantial variation in empirical type I error rates for all meta-analysis methods, but that 2 cM bins and scores that make more explicit use of linkage evidence, especially the truncated p values, reduce this problem. Conclusion: We identified regions modestly linked with type 2 diabetes by summarizing results from 23 autosomal genome scans.

© 2008 S. Karger AG, Basel


  

Author Contacts

Michael Boehnke, PhD
Department of Biostatistics, School of Public Health
University of Michigan, 1420 Washington Heights
Ann Arbor, MI 48109-2029 (USA)
Tel. +1 734 936 1001, Fax +1 734 615 8322, E-Mail boehnke@umich.edu

  

Article Information

Received: June 4, 2007
Accepted after revision: September 5, 2007
Published online: January 28, 2007
Number of Print Pages : 15
Number of Figures : 2, Number of Tables : 7, Number of References : 56

  

Publication Details

Human Heredity (International Journal of Human and Medical Genetics)

Vol. 66, No. 1, Year 2008 (Cover Date: March 2008)

Journal Editor: Devoto, M. (Philadelphia, Pa.)
ISSN: 0001–5652 (Print), eISSN: 1423–0062 (Online)

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


Article / Publication Details

First-Page Preview
Abstract of Original Paper

Received: 6/4/2007
Accepted: 5/9/2007
Published online: 1/28/2007
Issue release date: March 2008

Number of Print Pages: 15
Number of Figures: 2
Number of Tables: 7

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

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


Copyright / Drug Dosage

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 goverment 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.

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