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

描述(由申请人提供)： 人类基因组图谱的众多结果之一将是对基因对人类疾病和健康的贡献有了新的、更详细的了解。这种了解将使我们能够进一步制定战略，最大限度地减少或预防疾病，并改善康复和健康。可能存在许多表型的遗传基础，包括疾病易感性、无病、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卫生保健。该项目将通过定义犹他州生物医学资源中代表的许多与疾病和健康相关的特征的可遗传成分，开始与犹他州大型、独特的资源的数据挖掘活动。这一生物医学/遗传资源包括一个现有的犹他大学健康科学中心数据仓库，其中有150多万名患者和10多年的数据，最近链接到代表10代人的广泛的计算机化犹他州家谱。 我们使用这些数据的基于人群的方法，使用所有代表的遗传关系来考虑遗传对疾病的贡献的证据，提供了比病例对照研究更完整的方法来调查共同的特征。这一资源的广泛表型将使其在许多方面具有独特性和强大功能。它最大的优势之一是高质量和高数量的医疗数据，这些数据针对具有良好特征和同质性的人群。我们在这一家谱资源以及其他相关疾病数据(癌症登记和死亡证明)方面有30年的经验。新链接的医疗数据包括ICD 9和CPT4程序编码数据，以及放射学、药房、出院摘要和门诊文件。我们之前已经成功地定义了癌症和其他疾病的遗传成分，并基于对该资源的分析确定了多个疾病易感基因。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特征的可遗传成分，最终将导致对疾病易感性、风险调整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