Identifying Plausible Genetic Models Based on Association and Linkage Results: Application to Type 2 Diabetes

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

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

When planning resequencing studies for complex diseases, previous association and linkage studies can constrain the range of plausible genetic models for a given locus. Here, we explore the combinations of causal risk allele frequency (RAFC) and genotype relative risk (GRRC) consistent with no or limited evidence for affected sibling pair (ASP) linkage and strong evidence for case-control association. We find that significant evidence for case-control association combined with no or moderate evidence for ASP linkage can define a lower bound for the plausible RAFC. Using data from large type 2 diabetes (T2D) linkage and genome-wide association study meta-analyses, we find that under reasonable model assumptions, 23 of 36 autosomal T2D risk loci are unlikely to be due to causal variants with combined RAFC < 0.005, and four of the 23 are unlikely to be due to causal variants with combined RAFC < 0.05.

Original languageEnglish (US)
Pages (from-to)820-828
Number of pages9
JournalGenetic epidemiology
Volume36
Issue number8
DOIs
StatePublished - Dec 2012

Keywords

  • Complex diseases
  • Gene mapping
  • Genetic structure
  • Genetics

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