“大数据”预测分析与三丁基锡暴露有关疾病

通过毒理学“大数据”,挖掘三丁基锡（TBT）潜在的生物影响信息,预测分析TBT暴露与人类相关疾病的关系.通过比较毒理组学数据库（CTD）搜集到488个和TBT具有相互作用的基因.基因相互作用网络图显示TP53拥有相关联基因最多,处于中心地位;其次是ESR1和FN1.CTD分析与TBT相关的疾病,发现前10类疾病分别是癌症、神经系统疾病、心血管疾病、泌尿生殖系统疾病（女）、消化系统疾病、代谢疾病、泌尿生殖系统疾病（男）、内分泌系统疾病、免疫系统疾病、呼吸道疾病.KEGG通路和DAVID基因功能注释分析,发现TBT不仅和代谢性疾病有较高的关联性,其相互作用基因在糖代谢途径上亦有较密集的基因功能注释.PASS的活性预测也发现TBT可能影响多种与糖代谢相关的酶生物活性.这提示TBT对糖代谢相关疾病的影响应引起人们的注意.

Relationship analysis between tributyltin exposure and human diseases based on “big data”

The potential influence information of tributyltin (TBT) was excavated to predict the relationship between TBT exposure and human-related diseases by using the "big data" of toxicology database. In comparative toxicogenomics database (CTD), 488 genes interacting with TBT were collected. Among the 488 genes, TP53 was the most associated genes, followed by ESR1 and FN1. Using CTD analysis, it was also found that cancer, nervous system diseases, cardiovascular diseases, urogenital disease (female), digestive system diseases, metabolic disease, urogenital disease (male), endocrine system diseases, immune system diseases and respiratory tract disease were the top 10diseases related to TBT exposure. Based KEGG pathway and DAVID gene function annotation analysis, metabolic diseases were more susceptible to be induced by TBT exposure; moreover, intensive genes interacting with TBT were annotated in the pathways of glucose metabolism. PASS prediction found that biological activities of many sugar-related enzymes could be affected by TBT exposure, which suggested that the impact of TBT on glucose metabolism should be of concern.