The power of two-locus affected sib-pair linkage analysis to detect interacting disease loci

✍ Scribed by Ingileif B. Hallgrímsdóttir; Terence P. Speed

• Publisher: John Wiley and Sons
• Year: 2008
• Tongue: English
• Weight: 124 KB
• Volume: 32
• Category: Article
• ISSN: 0741-0395
• DOI: 10.1002/gepi.20254

✦ Synopsis

Abstract

It has been shown that two‐locus linkage analysis can, for some two‐locus disease models, be used to detect effects at disease loci that do not reach significance in a genome scan. However, few examples exist where two‐locus linkage has been successfully used to map genes. We study the possible gain in power of affected sib‐pair nonparametric two‐locus linkage analysis for two‐locus models which fulfil the two‐locus triangle constraints. Using a new parameterization of the two‐locus joint identity‐by‐descent sharing probabilities we can, for fixed marginal sharing at both of two unlinked disease loci, derive a two‐locus distribution such that the power of a two‐locus analysis is maximized. In a simulation study we look at two test statistics, the two‐locus maximum likelihood score and the correlation between nonparametric linkage scores, and study power as a function of marginal sharing. We show that in a best‐case scenario two‐locus linkage can have considerable power to detect pairs of interacting loci if there is a moderate increase in allele sharing at one of the two loci, even if there is a very small increase in allele sharing at the other locus. But we also show that the power to detect interacting loci in a two‐locus analysis decreases as the marginal sharing at the two loci decreases and for any distribution with a small increase in allele sharing at both loci the power of a two‐locus analysis is always low. Genet. Epidemiol. 2007. © 2007 Wiley‐Liss, Inc.