The long term objective of this research is to unravel the genetic mechanisms underlying human disease traits that have a multifactorial etiology. The project proposes to (1) extend the theoretical development of statistical methods for the genetic analysis of human pedigree data, with emphasis on linkage analysis, (2) develop standardized computer programs based on these theoretical methods (3) develop a more extensive map of the human genome, (4) analyze family and pedigree data, and (5) maintain a computer dedicated to genetic analysis. Both parametric and non-parametric methods of linkage analysis will be extended. Linkage parameters will be incorporated into regressive models for segregation analysis, with appropriate ascertainment corrections. The robust Haseman-Elston sibpair linkage test will be extended to other pairs of relatives, to multiple markers, and to multivariate traits. Modularized computer algorithms based on these new methods will be developed; all programs will be written in ANSI standard FORTRAN 77. To develop a more complete map of he human genome a polymorphism laboratory will be maintained and its capabilities extended to allow typing newer systems. In particular, an inexpensive method will be developed to determine DNA polymorphisms by using small oligonucleotide probes. Each such probe would detect 10-20 polymorphic fragments, making it possible to span the entire human genome with many fewer enzyme digestions that are currently necessary for determining restriction fragment length polymorphisms. Pedigrees that have previously been typed for 20-40 polymorphisms will be analyzed for linkage with the newer polymorphic markers (1) to obtain a virtually complete map of he human genome, and (2) to map specific genes involved in multifactorial diseases such as hypertension, hypertriglyceridemia and depression. Since it may confound linkage analysis, non-linkage allelic disequilibrium among the polymorphic markers will be investigated - as well as heterogeneity in the recombination fraction between linked genes due to parental age and sex. Finally, maintenance of a computer dedicated to genetic analysis will support not only the above aims, but also the analysis of family data collected by others over the next five years.
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