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多くの病気は,遺伝的な背景と環境要因が複合的に作用して生じる。疾患の発症や経過を左右する原因遺伝子,または感受性遺伝子の発見は非常に重要となる。そのための遺伝子解析を行うには,個人情報保護の観点からセキュリティー対策はもとより,ハイスループット解析システムを確立する必要がある。具体的な課題として,多施設からの検体収集とその管理,多型マーカーの設定,微量化等反応系の確立,解析精度と速度,遺伝子型多型解析データベースの構築,診療情報データベースの構築,統計解析等がある。これらの全行程が効率よく回転することによって,候補遺伝子アプローチ,ゲノムワイドスキャン,家系を基にした連鎖解析,疾患群-対照群の相関解析等を大規模に行うことができる。
Complex diseases are caused by combination of multiple genetic and environmental factors. To understand the etiology of the disease, identification of these genetic factors is the most important way. We set up the high throughput genotyping system to discover genetic risk factors. We introduced 2D-code for anonymous numbering of samples from many institutes, and stored these 96 samples in one box as an analysis unit. A bar-cord label was pasted on the 96 well and 384 well type plates to trace the reactions, and to identify the sample in a well. Search of the genetic polymorphism marker was performed by data base-assisted bioinformatics analysis of the candidate locus. Genotyping of 8markers and 384 samples(=4 boxes)was carried out at once. The genome database is build from the individual genotyping data using microsatellite or SNP as markers and their allele frequency in Japanese population. The clinical database is construction of diagnosis and treatment of disease, gender, onset age, other clinical examination data and so on under the protection of privacy. The clinical database can be used to link to the genome database and marker database for statistic analysis. By using this system the genetic risk factor are able to identify through candidate gene based approach or genome wide scan. This system can be also used genetic linkage analysis for a family based disease and association study for common disease. Equipments composed the genotyping system are connected in the intra-network frame.
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