Advances in molecular and statistical methods have greatly facilitated the identification of susceptibility genes for diseases, such as Alzheimer disease, that are common in older adults. These same methods may be applied to the study of the natural aging process to identify genes that are associated with a long and healthy life. Identification of both disease-causing and health-promoting polymorphisms and their interactions with the environment has the potential to greatly improve the health of older adults, the most rapidly growing segment of the U.S. population. One method of identifying genes associated with a particular trait is to study relatively stable, isolated populations established by a few founding members, such as the Amish community in northern Indiana. This community has previously participated in a cross-sectional survey for cognitive impairment conducted from 1991-1993. Several families with multiple cognitively impaired individuals were identified and included in ongoing studies of the genetics of dementia at the DUMC Center for Human Genetics. We also observed in these families apparent clustering of """"""""successful aging"""""""", suggesting that this trait may be, in part, under genetic control. In light of these observations, we propose a second population survey to systematically evaluate Amish adults aged 80 and older for cognitive and functional impairment. We will determine the prevalence and degree of familial aggregation of successful aging in the Amish community and perform genetic studies to identify genes associated with successful aging. To accomplish these goals, we specifically propose to: (1) conduct a community survey of Amish residents aged 80 and older in Adams and surrounding counties in Indiana and Holmes and surrounding counties in Ohio; (2) examine the relationship between successful aging and genes implicated in longevity; (3) perform a complete genomic screen for successful aging loci, and (4) follow-up results of the genomic screen through positional cloning and candidate gene analysis approaches.
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