Bioinformatic Analysis of the Genetics of Common Complex Diseases

心血管疾病、自身免疫性疾病、神经系统疾病和代谢性疾病等复杂的多遗传疾病构成了发达国家死亡率和发病率的大部分。遗传关联数据库 (GAD)（Becker 等人，2004）是遗传关联研究信息的公共存储库，其中存档已发表的各种人类疾病关联研究，重点是非孟德尔常见疾病。目前包含大约 40,000 条疾病和基因特定记录，包括 3,300 多个独特基因的信息，以及 6,900 多种独特疾病表型描述，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；等等。目前，全球 GAD 网站每天的访问量在 2,000 至 7,000 次之间。 http://genicassociationdb.nih.gov/ 这项工作的目标是从已发表的遗传关联研究（包括全基因组关联研究（GWAS））中归档、组织和注释有关常见人类疾病遗传学的已发表信息。我们收集的信息是已发布的摘要信息，不收集与个体患者或家庭成员相关的任何信息。这是与 CDC 人类基因组流行病学网络和 HuGE Navigator 数据库合作完成的。 目前我们正在对这个数据库的内容进行系统的总结和分析。这涉及总结关于基于基因的复制的常见疾病的遗传学、与相关和不同疾病的比较，以及与广泛的小鼠表型的遗传学的直接比较。这个正在进行的项目的一部分涉及将人类和小鼠遗传数据与基于人类和小鼠微阵列的基因表达数据整合。与此相关的工作是开发用于协调数据分析和集成的软件工具。

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.