Analysis of the Familial Component to Disease in a Biomedical Resource w/Link...

描述（由申请人提供）： 绘制人类基因组图谱的众多成果之一，将是对基因对人类疾病和健康的影响有一个新的、更详细的了解。这种理解将有助于进一步制定战略，以尽量减少或预防疾病，并改善愈合和健康。许多表型可能存在遗传基础，包括疾病易感性、无疾病、疾病进展或预后以及对环境和药物的反应。更好地了解基因对健康和疾病的这些方面的贡献将导致改善保健。该项目将通过定义犹他州生物医学资源中代表的许多疾病和健康相关性状的遗传成分，开始对犹他州大型独特资源的数据挖掘活动。这种生物医学/遗传资源包括现有的犹他州健康科学中心数据仓库，其中有150多万患者和10多年的数据，最近与代表10代人的广泛的计算机化犹他州家谱相关联。 我们的基于人群的方法使用这些数据，它考虑了遗传因素对疾病的贡献，使用所有的遗传关系表示的证据，提供了一个更完整的方法比病例对照研究，以调查共同的特征。广泛的表型可用于这一资源将使其独特和强大的许多方面。其最大的优势之一是在特征明确和同质的人口中提供高质量和数量的医疗数据。我们有三十年的经验与此家谱资源，并与其他相关的疾病数据（癌症登记和死亡证明）。新链接的医疗数据包括ICD 9和CPT 4程序编码数据，以及放射学、药房、出院总结和门诊记录。我们以前已经成功地确定了癌症和其他疾病的遗传成分，并根据对这一资源的分析确定了多种疾病易感基因。我们进行的分析将允许定义许多以前没有研究过的健康和疾病相关性状的遗传成分，并最终导致对疾病易感性，风险修饰以及疾病相关和健康相关基因的识别和理解

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