The long term objective of this project is to develop powerful and computationally efficient statistical methods of identifying genes underlying complex genetic diseases in humans.
The specific aim of this project is to continue to develop survival models to incorporate age of onset data, environmental covariates information, gene-environment interactions, and multiple disease loci into family-based association analysis, joint linkage and linkage disequilibrium analyses, and multipoint multi-trait-locus linkage analysis of complex human diseases. The proposed methods build on our current methods and hinge on novel integration of methods in multivariate survival analysis and methods in modern human genetics. The focus will be on the development of survival models for: (1) incorporating age of onset and environmental risk factors into genetic association study using a linkage disequlibrium based Cox model for family data of any size; (2) joint analysis of linkage and linkage disequilibrium for age of onset data based on nuclear families; (3) for multipoint multi-trait-locus linkage tests that can incorporate age of onset and environmental covariates data using the additive genetic frailty model. The project will also investigate the power and efficiencies of these methods, and compare them with existing methods. In addition, this project will develop practical and feasible computer programs in order to implement the proposed methods, to evaluate the performance of these methods through extensive simulations and application to real data on HLA-associated diseases, including type 1 diabetes, rheumatoid arthritis, celiac disease, narcolepsy, and ankylosing spondylitis. The work proposed here will contribute both statistical methodology to mapping genes for complex diseases and multivariate survival analysis, offer insight into each of the clinical areas represented by the various data sets to evaluate these new methods, and facilitate final identification of genes involved in these complex diseases. All programs developed under this grant and detailed documentations will be made available free-of-charge to interested researchers via the World Wide Web.
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