This study will build upon existing sib-pair methods for multipoint mapping of QTLs. It will greatly expand upon the statistical methodology to identify and localize QTLs for complex traits by merging sib-pair methods with a powerful twin design which uses phenotypic data on MZ and DZ twins to resolve phenotypic variability into genetic and non-genetic components, and partition human quantitative genetic variation into effects due to loci on specific chromosomal regions. This quantitative methodology will be applied to risk factors for cardiovascular disease -- one of the most pressing health problems in Western society. Population-based samples of Dutch, Swedish, and Australian twins have been identified in previous studies, phenotypic measures on lipids, lipoproteins, and other important cardiovascular risk factors have been obtained, and blood has been banked in a valuable resource which is available for use in this proposed project. In 500 DZ twin pairs, a series of 175 highly polymorphic microsatellite markers will be detected using an automated process for detecting fluorescent signals. These data will be analyzed using the new statistical methods both to confirm the effects of a series of candidate loci and to test for the effects of previously unknown QTLs.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
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Epidemiology and Disease Control Subcommittee 2 (EDC)
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Pennsylvania State University
Schools of Allied Health Profes
University Park
United States
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