Analysis of the Familial Component to Disease in a Biomedical Resource w/Link...
University Of Utah, Salt Lake City UT
Investigators
Linked publications & trials
Abstract
DESCRIPTION (provided by applicant): One of the many results of the mapping of the human genome will be a new, more detailed understanding of the genetic contribution to human disease and health. Such understanding will allow the further development of strategies to minimize or prevent disease, and to improve healing and health. A genetic basis might be suggested for many phenotypes, including disease predisposition, absence of disease, disease progression or prognosis, and response to environment and medications. A better understanding of the genetic contribution to these aspects of health and sickness will lead to improved health care. This project will begin data mining activities with a large, unique Utah resource by defining the heritable component to many disease- and health-related traits represented in the Utah biomedical resource. This biomedical/genetic resource consists of an existing University of Utah Health Sciences Center data warehouse with over 1.5 million patients and over 10 years of data, recently linked to an extensive computerized Utah genealogy representing 10 generations. Our population-based approach using these data, which considers evidence for a genetic contribution to disease using all genetic relationships represented, provides a more complete method than case-control studies to investigate common traits. The wide range of phenotypes available for this resource will make it unique and powerful in many ways. One of its greatest strengths is the high quality and quantity of the medical data available on a well-characterized and homogeneous population. We have three decades of experience with this genealogical resource, and with other linked disease data (cancer registry and death certificates). The newly linked medical data includes ICD 9 and CPT4 procedure coding data, as well as radiology, pharmacy, discharge summaries, and outpatient documentation. We have previously successfully defined the genetic component to cancer and other diseases, and have identified multiple disease predisposition genes, based on analysis of this resource. The analyses we perform will allow definition of the heritable component to many health and disease related traits not previously studied, and will eventually lead to the identification and understanding of disease predisposition, risk-modifying, and disease-associated and health-associated genes
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