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

Federica Eduati , Lara M Mangravite , Tao Wang , Hao Tang , J Christopher Bare (1) , Rui Huang (2) , Thea Norman , Mike Kellen , Michael P Menden , Yang Yang (3) , Xiaowei Zhan , Rui Zhong (4) , Guanghua Xiao (5) , Menghang Xia (6) , Nour Abdo , Oksana Kosyk , Stephen Friend , Gustavo Stolovitzky , Allen Dearry , Raymond R Tice , Anton Simeonov , Ivan Rusyn , Fred A Wright , Yang Xie (7) , Salvatore Alaimo , Alicia Amadoz , Muhammad Ammad-Ud-Din , Chloé-Agathe Azencott (8, 9) , Jaume Bacardit , Pelham Barron , Elsa Bernard (10) , Andreas Beyer (11) , Shao Bin , Alena van Bömmel , Karsten Borgwardt , April M Brys , Brian Caffrey , Jeffrey Chang , Jungsoo Chang , Eleni G Christodoulou , Mathieu Clément-Ziza (12) , Trevor Cohen , Marianne Cowherd , Sofie Demeyer (13) , Joaquin Dopazo (14, 15, 16) , Joel D Elhard , Andre O Falcao (17) , Alfredo Ferro (18) , David A Friedenberg , Rosalba Giugno , Yunguo Gong (19, 20) , Jenni W Gorospe , Courtney A Granville , Dominik Grimm , Matthias Heinig (21) , Rosa D Hernansaiz , Sepp Hochreiter , Hua Huang (22) , Matthew Huska , Yunlong Jiao , Günter Klambauer , Michael Kuhn , Miron Bartosz Kursa , Rintu Kutum , Nicola Lazzarini , Inhan Lee (23) , Michael K K Leung , Weng Khong Lim (24) , Charlie Liu , Felipe Llinares López (25) , Alessandro Mammana , Andreas Mayr , Tom Michoel , Misael Mongiovì , Jonathan D Moore (26) , Ravi Narasimhan , Stephen Opiyo , Gaurav Pandey (27) , Andrea L Peabody , Juliane Perner , Alfredo Pulvirenti , Konrad Rawlik , Susanne Reinhardt (28) , Carol G Riffle , Douglas Ruderfer , Aaron J Sander (29) , Richard S Savage , Erwan Scornet (30) , Patricia Sebastian-Leon , Roded Sharan , Carl Johann Simon-Gabriel , Veronique Stoven (8, 9) , Jingchun Sun (31) , Ana L Teixeira , Albert Tenesa (32) , Jean-Philippe Vert (9, 8) , Martin Vingron , Thomas Walter (8, 9) , Sean Whalen , Zofia Wiśniewska , Yonghui Wu (33) , Hua Xu (34) , Shihua Zhang , Junfei Zhao (35) , W Jim Zheng (36) , Dai Ziwei , Julio Saez-Rodriguez (37, 38) , Xiaowei Xia (39) , Guanghua Xia (40)

1 IRD - Institut de Recherche pour le Développement
2 NCATS - National Center for Advancing Translational Sciences
3 Data Storage Institute - A*STAR
4 Capital Normal University [Beijing]
5 Southwest University of China
6 Sans affiliation
7 Shanghai Ocean University
8 CBIO - Centre de Bioinformatique
9 Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe
10 IGN - Institut National de l'Information Géographique et Forestière [IGN]
11 IFSTTAR/AME/SPLOTT - Systèmes Productifs, Logistique, Organisation des Transports et Travail
12 BIOTEC - Biotechnology Center [Dresden]
13 LNE - Laboratoire National de Métrologie et d'Essais [Trappes]
14 Centre for Biomedical Network Research on Rare Diseases (CIBERER)
15 Department of Computational Genomics
16 Functional Genomics Node (INB)
17 CA3 - Computational Intelligence Research Group
18 ACEEE
19 LTCI - Laboratoire Traitement et Communication de l'Information
20 LINCS - Laboratory of Information, Network and Communication Sciences
21 Institute of Computational Biology
22 SBU - Stony Brook University [SUNY]
23 University of Pensylvania
24 Institute for Infocomm Research - I²R [Singapore]
25 IRIT - Institut de recherche en informatique de Toulouse
26 MAE - UC Davis - Department of Mechanical and Aerospace Engineering [Univ California Davis]
27 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Canberra]
28 LMU - Ludwig Maximilian University [Munich] = Ludwig Maximilians Universität München
29 LAVUE - Laboratoire Architecture, Ville, Urbanisme, Environnement
30 LSTA - Laboratoire de Statistique Théorique et Appliquée
31 Agricultural Technological Extensive Station of Luntai County in Xinjiang
32 Medstar Research Institute
33 Huawei Technologies [Shanghaï]
34 School of Economics and Business Administration - School of Economics and Business Administration
35 NCMIS - National Center for Mathematics and Interdisciplinary Sciences [Beijing]
36 Division of Biostatistics
37 Helmholtz-Institute for Biomedical Engineering [RWTH Aachen University]
38 EMBL-EBI - European Bioinformatics Institute [Hinxton]
39 AII - Agricultural Information Institute
40 Department of Computer Science - Lafayette College

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.

Domaines: Bio-informatique [q-bio.QM]; Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement des images [eess.IV]; Bio-Informatique, Biologie Systémique [q-bio.QM]

Federica Eduati, Lara M Mangravite, Tao Wang, Hao Tang, J Christopher Bare, et al.. Prediction of human population responses to toxic compounds by a collaborative competition.. Nature Biotechnology, 2015, 33 (9), pp.933-40. ⟨10.1038/nbt.3299⟩. ⟨hal-01428019⟩