Modeling haplotype-haplotype interactions in case-control genetic association studies

Li Zhang, Ruitao Liu, Zhong Wang, Daniel A. Culver, Rongling Wu

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

Haplotype analysis has been increasingly used to study the genetic basis of human diseases, but models for characterizing genetic interactions between haplotypes from different chromosomal regions have not been well developed in the current literature. In this article, we describe a statistical model for testing haplotype-haplotype interactions for human diseases with a case-control genetic association design. The model is formulated on a contingency table in which cases and controls are typed for the same set of molecular markers. By integrating well-established quantitative genetic principles, the model is equipped with a capacity to characterize physiologically meaningful epistasis arising from interactions between haplotypes from different chromosomal regions. The model allows the partition of epistasis into different components due to additive × additive, additive × dominance, dominance × additive, and dominance × dominance interactions. We derive the EM algorithm to estimate and test the effects of each of these components on differences in the pattern of genetic variation between cases and controls and, therefore, examine their role in the pathogenesis of human diseases. The method was further extended to investigate gene-environment interactions expressed at the haplotype level. The statistical properties of the models were investigated through simulation studies and its usefulness and utilization validated by analyzing the genetic association of sarcoidosis from a human genetics project.

Original languageEnglish (US)
Article numberArticle 2
JournalFrontiers in Genetics
Volume3
Issue numberJAN
DOIs
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Genetics
  • Genetics(clinical)

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