title: Prediction of human population responses to toxic compounds by a collaborative competition.
abstract: The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: Federica
authors.identifier: http://orcid.org/0000-0002-7822-3867
authors.initials: F
authors.lastname: Eduati
authors.affiliation: Sage Bionetworks, Seattle, Washington, USA.
authors.forename: Lara M
authors.initials: LM
authors.lastname: Mangravite
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
authors.forename: Tao
authors.identifier: http://orcid.org/0000-0002-4355-149X
authors.initials: T
authors.lastname: Wang
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA.|The Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Tang
authors.affiliation: Sage Bionetworks, Seattle, Washington, USA.
authors.forename: J Christopher
authors.initials: JC
authors.lastname: Bare
authors.affiliation: Division of Preclinical Innovation, National Institutes of Health Chemical Genomics Center, National Center for Advancing Translational Sciences, Rockville, Maryland, USA.
authors.forename: Ruili
authors.initials: R
authors.lastname: Huang
authors.affiliation: Sage Bionetworks, Seattle, Washington, USA.
authors.forename: Thea
authors.initials: T
authors.lastname: Norman
authors.affiliation: Sage Bionetworks, Seattle, Washington, USA.
authors.forename: Mike
authors.initials: M
authors.lastname: Kellen
authors.affiliation: European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK.
authors.forename: Michael P
authors.initials: MP
authors.lastname: Menden
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
authors.forename: Jichen
authors.initials: J
authors.lastname: Yang
authors.affiliation: Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Xiaowei
authors.initials: X
authors.lastname: Zhan
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
authors.forename: Rui
authors.initials: R
authors.lastname: Zhong
authors.affiliation: Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
authors.forename: Guanghua
authors.initials: G
authors.lastname: Xiao
authors.affiliation: Division of Preclinical Innovation, National Institutes of Health Chemical Genomics Center, National Center for Advancing Translational Sciences, Rockville, Maryland, USA.
authors.forename: Menghang
authors.initials: M
authors.lastname: Xia
authors.affiliation: Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina, USA.|Department of Public Health, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan.
authors.forename: Nour
authors.initials: N
authors.lastname: Abdo
authors.affiliation: Department of Environmental Sciences and Engineering, University of North Carolina, Chapel Hill, North Carolina, USA.
authors.forename: Oksana
authors.initials: O
authors.lastname: Kosyk
authors.forename: Stephen
authors.initials: S
authors.lastname: Friend
authors.forename: Allen
authors.initials: A
authors.lastname: Dearry
authors.forename: Anton
authors.initials: A
authors.lastname: Simeonov
authors.forename: Raymond R
authors.initials: RR
authors.lastname: Tice
authors.forename: Ivan
authors.initials: I
authors.lastname: Rusyn
authors.forename: Fred A
authors.initials: FA
authors.lastname: Wright
authors.forename: Gustavo
authors.initials: G
authors.lastname: Stolovitzky
authors.forename: Yang
authors.initials: Y
authors.lastname: Xie
authors.forename: Julio
authors.initials: J
authors.lastname: Saez-Rodriguez
mesh_terms: D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005828:Genetics, Population; D015386:Hazardous Substances / Q000633:toxicity*; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D015994:Incidence; D008214:Lymphocytes / Q000166:cytology / Q000187:drug effects* / Q000502:physiology; D008957:Models, Genetic; D018570:Risk Assessment / Q000379:methods; D018675:Toxicity Tests / Q000379:methods
chemical_list: D015386:Hazardous Substances