Chromosome imbalance is the leading known cause of mental retardation, spontaneous abortion, and congenital heart defects in human. Furthermore, over 50 percent of all human pregnancy loss is attributable to chromosome imbalance in the fetus, making chromosome abnormalities the leading cause of reproductive failure. Maternal age is well recognized as a major risk factor for chromosome abnormalities. Alterations of recombinations are also found to be strongly associated with human nondisjunctions. However, standard statistical methods used in human nondisjunction studies are biased. In addition, the standard methods are inefficient in extracting genetic information from nondisjunction data, which are characterized by a limited amount of available materials, unknown stage of origin of nondisjunction error, uninformative matings, and missing parents. Built on our previous studies on the crossover process, ordered tetrads, and half-tetrads, we will develop efficient multilocus statistical methods for human nondisjunction data to include: (1) joint marker information; (2) crossover interference; (3) the uncertainty in the stage of origin of nondisjunction error; (4) parental age effects; (5) untyped and uninformative markers; (6) families with only one available parent; and (7) genotyping errors. These statistical methods will maximally utilize the information in human nondisjunction data to identify basic mechanisms responsible for chromosome abnormalities. Using the statistical methods developed in this project, we will collaborate with leading researchers in human nondisjunction studies to analyze, interpret, and report scientific findings for chromosomes X, 13, 15, 16, 18, 21 and 22. To make our methods available to the scientific community, efficient and well-documented computer software will be developed, tested, and distributed on the World Wide Web. The ultimate goals are to understand recombination and its alterations during nondisjunction, and to provide the knowledge needed to monitor and prevent chromosome abnormalities.
