Tests for the presence of two linked disease susceptibility genes

Joanna M. Biernacka, Lei Sun, Shelley B. Bull

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


For diseases with complex genetic etiology, more than one susceptibility gene may exist in a single chromosomal region. Under explicit assumptions about the number of disease genes in a region, generalized estimating equations (GEE) can be used to estimate the putative disease gene location(s) and expected identical-by-descent allele sharing in affected sib pairs at these gene(s). Extending the work of Liang et al. ([2001] Hum. Hered. 51:64-78), Biernacka et al. ([2005] Genet. Epidemiol. 28:33-47) developed a method for simultaneous localization of two susceptibility genes in one region using marker identical-by-descent (IBD) sharing in affected sib pairs. Here we propose methods to evaluate the evidence for two versus one disease loci in a region in a quasi-likelihood/GEE framework. We describe tests based on approximate quasi-likelihood ratio and generalized score test statistics. Because of difficulties in determining the asymptotic null distributions of these statistics and the small sample sizes that can be available in genetic studies, we recommend that significance be evaluated empirically. Application of the described methods to data from a genome scan for type 1 diabetes (Mein et al. [1998] Nat. Genet. 19:297-300) yielded some evidence for two linked disease genes on chromosome 6, approximately 20 cM apart (p value for an approximate quasi-likelihood ratio test=0.049). In simulation studies, we found that both tests performed quite well for a range of scenarios. Power to detect the presence of two linked disease genes increased with the number of affected sib pairs, greater IBD sharing at the two loci, and larger distance between the two loci.

Original languageEnglish (US)
Pages (from-to)389-401
Number of pages13
JournalGenetic epidemiology
Issue number4
StatePublished - Dec 1 2005


  • Affected sib pairs
  • Complex disease
  • Empirical p values
  • Generalized estimating equations
  • Hypothesis test
  • Identity by descent
  • Multi-locus linkage analysis

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)


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