title: Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: myocardial and infectious adverse reactions as application cases.
abstract: Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure-activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation.
authors.affiliation: Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China. Electronic address: kejian.wang.bio@gmail.com.
authors.forename: Kejian
authors.initials: K
authors.lastname: Wang
authors.affiliation: Japan National Institute of Occupational Safety and Health, Kawasaki, Japan.
authors.forename: Zuquan
authors.initials: Z
authors.lastname: Weng
authors.affiliation: Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China.
authors.forename: Liya
authors.initials: L
authors.lastname: Sun
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA.
authors.forename: Jiazhi
authors.initials: J
authors.lastname: Sun
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA.
authors.forename: Shu-Feng
authors.initials: SF
authors.lastname: Zhou
authors.affiliation: Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai, China. Electronic address: helin@Bio-X.com.
authors.forename: Lin
authors.initials: L
authors.lastname: He
mesh_terms: D000818:Animals; D030541:Databases, Genetic; D004341:Drug Evaluation; D004353:Drug Evaluation, Preclinical; D064420:Drug-Related Side Effects and Adverse Reactions / Q000235:genetics*; D020869:Gene Expression Profiling / Q000706:statistics & numerical data; D023281:Genomics; D006321:Heart / Q000187:drug effects; D006801:Humans; D007239:Infections / Q000209:etiology; D008957:Models, Genetic; D010597:Pharmacogenetics; D021281:Quantitative Structure-Activity Relationship; D012306:Risk
keywords: Adverse drug reaction; Black box warning; Connectivity Map; FDA boxed warning; Risk score model