The traditional methods of linkage analysis, which test for cosegregation of disease and marker, were developed for Mendelian diseases. These methods may be misleading or inconclusive when applied to complex non- Mendelian diseases, because they require simplifying assumptions about the inheritance of the disease in order to infer disease gene location. In other words, an incorrect model of the disease may lead to incorrect conclusions. Model-free linkage analysis methods avoid this problem by directly testing for nonrandom segregation of markers to affected individuals. The model-free methods have a crucial and important role in the search for disease susceptibility loci involved in genetically complex diseases. One promising model-free method is the affected pedigree member (APM) method of linkage analysis. The APM method has the advantage of using marker information on all the affected relatives in each family, unlike the model-free sib-pair methods which only use information on the siblings and their parents. By the research proposed here, the APM method will be evaluated, improved, and extended, making it a more useful and efficient method for mapping genes involved in complex human diseases. Extensive computer simulations will be carried out to evaluate the number of families needed to detect linkage and the most efficient way to ascertain them. A model-free method to test for linkage heterogeneity will be developed and evaluated. These studies will provide a greater understanding of the potential and limitations of the APM method. An extension of the APM method that uses marker information from both unaffected and affected individuals will be developed and evaluated. Also, the APM statistic will be modified so that closely related pairs of affected relatives contribute more to the overall statistic than distantly related pairs of relatives, in effect, subcategorizing the disease into a more familial form. Our extended and modified methods will be evaluated by applying them to both simulated data and to a collection of pedigrees segregating for Alzheimer disease. In addition, an APM method for X-linked traits will be developed and evaluated. Ultimately, these studies will lead to better APM statistics with an improved ability to map a wide range of genetically complex diseases.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
First Independent Research Support & Transition (FIRST) Awards (R29)
Project #
1R29HG000719-01
Application #
3470838
Study Section
Genome Study Section (GNM)
Project Start
1992-07-01
Project End
1997-06-30
Budget Start
1992-07-01
Budget End
1993-06-30
Support Year
1
Fiscal Year
1992
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Type
Schools of Public Health
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
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