A data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades.

TitleA data-driven weighting scheme for multivariate phenotypic endpoints recapitulates zebrafish developmental cascades.
Publication TypeJournal Article
Year of Publication2017
AuthorsZhang, G, Roell, KR, Truong, L, Tanguay, RL, Reif, DM
JournalToxicol Appl Pharmacol
Volume314
Pagination109-117
Date Published2017 Jan 01
ISSN1096-0333
KeywordsAnimals, Models, Theoretical, Multivariate Analysis, Phenotype, Zebrafish
Abstract

Zebrafish have become a key alternative model for studying health effects of environmental stressors, partly due to their genetic similarity to humans, fast generation time, and the efficiency of generating high-dimensional systematic data. Studies aiming to characterize adverse health effects in zebrafish typically include several phenotypic measurements (endpoints). While there is a solid biomedical basis for capturing a comprehensive set of endpoints, making summary judgments regarding health effects requires thoughtful integration across endpoints. Here, we introduce a Bayesian method to quantify the informativeness of 17 distinct zebrafish endpoints as a data-driven weighting scheme for a multi-endpoint summary measure, called weighted Aggregate Entropy (wAggE). We implement wAggE using high-throughput screening (HTS) data from zebrafish exposed to five concentrations of all 1060 ToxCast chemicals. Our results show that our empirical weighting scheme provides better performance in terms of the Receiver Operating Characteristic (ROC) curve for identifying significant morphological effects and improves robustness over traditional curve-fitting approaches. From a biological perspective, our results suggest that developmental cascade effects triggered by chemical exposure can be recapitulated by analyzing the relationships among endpoints. Thus, wAggE offers a powerful approach for analysis of multivariate phenotypes that can reveal underlying etiological processes.

DOI10.1016/j.taap.2016.11.010
Alternate JournalToxicol. Appl. Pharmacol.
PubMed ID27884602
PubMed Central IDPMC5224523
Grant ListP30 ES025128 / ES / NIEHS NIH HHS / United States
U01 ES027294 / ES / NIEHS NIH HHS / United States
R01 ES023788 / ES / NIEHS NIH HHS / United States
T32 ES007329 / ES / NIEHS NIH HHS / United States
R01 ES019604 / ES / NIEHS NIH HHS / United States
RC4 ES019764 / ES / NIEHS NIH HHS / United States
P42 ES016465 / ES / NIEHS NIH HHS / United States
P30 ES000210 / ES / NIEHS NIH HHS / United States
P42 ES005948 / ES / NIEHS NIH HHS / United States