title: Prediction of human genes and diseases targeted by xenobiotics using predictive toxicogenomic-derived models (PTDMs).
abstract: New technologies for systems-level determinants of human exposure to drugs, industrial chemicals, pesticides, and other environmental agents provide an invaluable opportunity to extend the understanding of human health and potential environmental hazards. We report here the development of a new computational-systems toxicology framework, called predictive toxicogenomics-derived models (PTDMs). PTDMs integrate three networks of chemical-gene interactions (CGIs), chemical-disease associations (CDAs) and gene-disease associations (GDAs) to infer chemical hazard profiles, identify exposure data gaps and to incorporate genes and disease networks into chemical safety evaluations. Three comprehensive networks addressing CGI, CDA and GDA extracted from the comparative toxicogenomics database (CTD) were constructed. The areas under the receiver operating characteristics curve ranged from 0.85 to 0.97 and were yielded using our methodology using a 10-fold cross validation by a simulation carried out 100 times. As the illustrated examples show, we predicted new potential target genes and diseases for bisphenol A and aspirin. The molecular hypothesis and experimental evidence from published literature for these predictions were provided. The results demonstrated that our method has potential applications for chemical profiling in human health exposure and environmental hazard assessment.
authors: Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China.
authors: Feixiong
authors: F
authors: Cheng
authors: Weihua
authors: W
authors: Li
authors: Yadi
authors: Y
authors: Zhou
authors: Jie
authors: J
authors: Li
authors: Jie
authors: J
authors: Shen
authors: Philip W
authors: PW
authors: Lee
authors: Yun
authors: Y
authors: Tang
mesh_terms: D001145:Arrhythmias, Cardiac / Q000188:drug therapy; D001241:Aspirin / Q000009:adverse effects / Q000378:metabolism / Q000627:therapeutic use; D001559:Benzhydryl Compounds / Q000378:metabolism / Q000633:toxicity; D001919:Bradycardia / Q000188:drug therapy; D003198:Computer Simulation; D062126:Databases, Chemical; D030541:Databases, Genetic; D003924:Diabetes Mellitus, Type 2 / Q000139:chemically induced; D050171:Dyslipidemias / Q000139:chemically induced; D004781:Environmental Exposure; D005796:Genes; D006212:Hallucinations / Q000139:chemically induced; D015386:Hazardous Substances / Q000633:toxicity; D006801:Humans; D006973:Hypertension / Q000139:chemically induced; D009393:Nephritis / Q000139:chemically induced; D009422:Nervous System Diseases / Q000139:chemically induced; D010636:Phenols / Q000378:metabolism / Q000633:toxicity; D021281:Quantitative Structure-Activity Relationship; D012372:ROC Curve; D043922:Toxicogenetics; D014202:Tremor / Q000139:chemically induced; D015262:Xenobiotics / Q000378:metabolism / Q000633:toxicity*; D000098826:Bisphenol A Compounds
chemical_list: D001241:Aspirin; D001559:Benzhydryl Compounds; D015386:Hazardous Substances; D010636:Phenols; D015262:Xenobiotics; C006780:bisphenol A; D000098826:Bisphenol A Compounds