Meta-analysis of 23 type 2 diabetes linkage studies from the international type 2 diabetes linkage analysis consortium

Weihua Guan, Anna Pluzhnikov, Nancy J. Cox, Michael Boehnke

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)35-49
Number of pages15
JournalHuman heredity
Volume66
Issue number1
DOIs
StatePublished - Mar 2008

Keywords

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

Fingerprint

Dive into the research topics of 'Meta-analysis of 23 type 2 diabetes linkage studies from the international type 2 diabetes linkage analysis consortium'. Together they form a unique fingerprint.

Cite this