Prediction of human population responses to toxic compounds by a collaborative 
competition

Eduati, F.; Mangravite, L. M.; Wang, T.; Tang, H.; Bare, J. C.; Huang, R.; Norman, T.; Kellen, M.; Menden, M. P.; Yang, J.; Zhan, X.; Zhong, R.; Xiao, G.; Xia, M.; Abdo, N.; Kosyk, O.; Collaboration, Niehs-Ncats-Unc Dream Toxicogenetics; van Bömmel, A.; Caffrey, B.; Heinig, M.; Huska, M.; Mammana, A.; Perner, J.; Vingron, M.; Friend, S.; Dearry, A.; Simeonov, A.; Tice, R. R.; Rusyn, I.; Wright, F. A.; Stolovitzky, G.; Xie, Y.; Saez-Rodriguez, J.

doi:10.1038/nbt.3299

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Prediction of human population responses to toxic compounds by a collaborative competition

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van Bömmel, A.
The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration;
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Caffrey, B.
The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration;
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50198

Heinig, M.
The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration;
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons73755

Huska, M.
The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration;
IMPRS for Computational Biology and Scientific Computing - IMPRS-CBSC (Kirsten Kelleher), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons73761

Mammana, A.
The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration;
Computational Epigenetics (Ho-Ryun Chung), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50467

Perner, J.
The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration;
IMPRS for Computational Biology and Scientific Computing - IMPRS-CBSC (Kirsten Kelleher), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50613

Vingron, M.
Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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http://www.ncbi.nlm.nih.gov/pubmed/26258538
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Zitation

Eduati, F., Mangravite, L. M., Wang, T., Tang, H., Bare, J. C., Huang, R., et al. (2015). Prediction of human population responses to toxic compounds by a collaborative competition. Nat Biotechnol, 33(9), 933-940. doi:10.1038/nbt.3299.

Zitierlink: https://hdl.handle.net/11858/00-001M-0000-002A-38D4-D

Zusammenfassung

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.