Chemical-Induced Phenotypes at CTD Help Inform the Predisease State and Construct Adverse Outcome Pathways
Chemical-Induced Phenotypes at CTD Help Inform the Predisease State and Construct Adverse Outcome Pathways
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DOI：
10.1093/toxsci/kfy131
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发表时间：
2018-09-01
影响因子：
3.8
通讯作者：
Mattingly, Carolyn J.
中科院分区：
文献类型：
--
作者：
Davis, Allan Peter;Wiegers, Thomas C.;Mattingly, Carolyn J.
比较毒理基因组学数据库(CTD；http://ctdbase.org))是一个公共资源，它手动整理科学文献，提供阐明环境暴露影响人类健康的分子机制的内容。我们介绍了我们新的化学表型模块，该模块描述了化学物质如何影响分子、细胞和生理表型。在CTD，我们在操作上区分表型和疾病，其中表型是指非疾病的生物事件：例如，细胞周期停滞(表型)减少与肝癌(疾病)、脂肪细胞增殖增加(表型)与病态肥胖(疾病)等。化学-表型相互作用以正式的结构化符号表示，使用受控的化学物质、表型、分类单元和解剖描述符。将这些信息与CTD的化学疾病模块相结合，可以在表型和疾病之间做出推断，从而产生对疾病前状态的潜在洞察。所有4个CTD模块的集成为毒理学家提供了独特的机会来生成计算预测的不良结果路径，将化学基因分子启动事件与表型关键事件、不良疾病和人群水平的健康结果联系起来。作为例子，我们提供了三个不同的案例研究，以辨别车辆尾气对改变的白细胞迁移的影响，镉在阿尔茨海默病之前影响表型的作用，以及砷诱导的葡萄糖代谢表型与糖尿病的联系。到目前为止，CTD包含了超过165,000个相互作用，将超过6400种化学物质与来自215个物种的760个解剖学术语的3900个表型联系在一起，来自19,000多篇科学文章。据我们所知，这是向公众提供的第一套全面的人工管理的、基于文献的、上下文的、化学诱导的、非疾病的表型数据。
The Comparative Toxicogenomics Database (CTD; http://ctdbase.org) is a public resource that manually curates the scientific literature to provide content that illuminates the molecular mechanisms by which environmental exposures affect human health. We introduce our new chemical-phenotype module that describes how chemicals can affect molecular, cellular, and physiological phenotypes. At CTD, we operationally distinguish between phenotypes and diseases, wherein a phenotype refers to a nondisease biological event: eg, decreased cell cycle arrest (phenotype) versus liver cancer (disease), increased fat cell proliferation (phenotype) versus morbid obesity (disease), etc. Chemical-phenotype interactions are expressed in a formal structured notation using controlled terms for chemicals, phenotypes, taxon, and anatomical descriptors. Combining this information with CTD's chemical-disease module allows inferences to be made between phenotypes and diseases, yielding potential insight into the predisease state. Integration of all 4 CTD modules furnishes unique opportunities for toxicologists to generate computationally predictive adverse outcome pathways, linking chemicalgene molecular initiating events with phenotypic key events, adverse diseases, and population-level health outcomes. As examples, we present 3 diverse case studies discerning the effect of vehicle emissions on altered leukocyte migration, the role of cadmium in influencing phenotypes preceding Alzheimer disease, and the connection of arsenic-induced glucose metabolic phenotypes with diabetes. To date, CTD contains over 165 000 interactions that connect more than 6400 chemicals to 3900 phenotypes for 760 anatomical terms in 215 species, from over 19 000 scientific articles. To our knowledge, this is the first comprehensive set of manually curated, literature-based, contextualized, chemical-induced, nondisease phenotype data provided to the public.