The long-term objective of this proposal is to enable the discovery of genes underlying complex traits using family based association tests that detect linkage disequilibrium while protecting against spurious evidence of association due to population admixture. To achieve this, specific aims of this project are to: (i) develop computer program that implements family based association tests with arbitrary nuclear family structure including those with missing parental information; that can incorporate environmental covariates and multiple genes into the model; that can test for gene-gene and gene-environment interactions; and that may be applied to dichotomous, quantitative, and time-of-onset phenotypes; (ii) develop a simple and flexible use interface to the program and easy installation procedures, and make the program widely available via ftp; (iii) test the statistical properties of the methodology in simulations and in real data, and use the test results to develop guidelines for the use of the program; (iv) develop an online help system and well-indexed user's manual; provide user support for the program; and develop comprehensive documentation of the statistical procedures; and (v) to extend the methodology to handle pedigrees of arbitrary structure including families with missing founder information. The resulting methodology will be able to test candidate genes, to test for linkage in the presence of association, and to test for association in homogeneous populations where linkage has been established (fine mapping). The investigators also indicate that the new computer software will fill gaps in family based association tests, specifically in cases with arbitrary pedigrees missing parental information, multiple genes, covariates, gene-gene and gene-environment interactions, and survival end-points.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Study Section
Special Emphasis Panel (ZRG2-GNM (02))
Program Officer
Moldin, Steven Owen
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Harvard University
Biostatistics & Other Math Sci
Schools of Public Health
United States
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Hoffmann, Thomas J; Vansteelandt, Stijn; Lange, Christoph et al. (2011) Combining disease models to test for gene-environment interaction in nuclear families. Biometrics 67:1260-70
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