Bioinformatic Analysis of the Genetics of Common Complex Diseases

在发达国家，心血管疾病、自身免疫性疾病、神经疾病和代谢性疾病等复杂的多基因疾病占死亡和发病率的大部分。遗传关联数据库(GAD)(Becker等人(2004年)是遗传关联研究信息的公共储存库，这些研究将已发表的各种人类疾病关联研究存档，重点是非孟德尔常见疾病。它目前包含大约40,000个疾病和基因特定记录，包括关于3,300多个独特基因的信息，以及6,900多个独特疾病表型描述，包括阿尔茨海默病、自身免疫性疾病、感染、败血症、心血管疾病和中风等。目前，全球每天访问GAD网站的网页点击量在2,000到7,000之间。Http://geneticassociationdb.nih.gov/ 这项工作的目标是存档、组织和注释已发表的人类常见疾病遗传学信息，这些信息来自已发表的遗传关联研究，包括全基因组关联研究(GWAS)。我们收集的信息是已发布的摘要信息，不收集任何与个别患者或家庭成员有关的信息。这项工作是与CDC人类基因组流行病学网络和庞大的导航器数据库合作完成的。 我们目前正在对该数据库的内容进行系统的总结和分析。这涉及到在基于基因的复制方面总结常见疾病的遗传学，与相关和不同的疾病进行比较，以及与基础广泛的小鼠表型的遗传学进行直接比较。这个正在进行的项目的一部分涉及将人类和小鼠的遗传数据与基于人类和小鼠微阵列的基因表达数据相结合。与这一努力相关的是开发软件工具，以协调数据分析和整合。

Complex multi-genetic diseases such as cardiovascular disease, autoimmune disorders, neurological disorders and metabolic diseases make up a majority of mortality and morbidity in developed countries. The Genetic Association Database (GAD) (Becker et al. 2004) is a public repository of information from genetic association studies which archives published human disease association studies of all kinds with an emphasis on non-mendelian common disease. It currently contains approximately 40,000 disease and gene specific records, including information on over 3,300 unique genes, and over 6,900 unique disease phenotypic descriptions, including Alzheimers disease, autoimmune disease, infection, sepsis, cardiovascular disorders, and stroke; among many others. The GAD website is currently accessed worldwide by between 2,000 and 7,000 web hits per day. http://geneticassociationdb.nih.gov/ The goal of this effort is to archive, organize, and annotate published information on the genetics of common human diseases from published genetic association studies, including genome wide association studies (GWAS). The information we collect is published summary information and does not collect any information related to individual patients or family members. This is done in cooperation with CDC Human Genome Epidemiology Network and the HuGE Navigator database. We are currently involved in systematic summation and analysis of the contents of this database. This involves summarizing the genetics of common disease with regard to gene based replication, comparisons to related and disparate diseases, as well as direct comparisons to the genetics of broad based mouse phenotypes. A part of this ongoing project involved integration of human and mouse genetic data with human and mouse microarray based gene expression data. Associated with this effort is the development of software tools to mediate data analysis and integration.