High Accuracy Classification of Developmental Toxicants by In Vitro Tests of Human Neuroepithelial and Cardiomyoblast Differentiation

Author:

Seidel FlorianORCID,Cherianidou Anna,Kappenberg FranziskaORCID,Marta Miriam,Dreser Nadine,Blum JonathanORCID,Waldmann Tanja,Blüthgen Nils,Meisig Johannes,Madjar Katrin,Henry Margit,Rotshteyn Tamara,Scholtz-Illigens Andreas,Marchan Rosemarie,Edlund KarolinaORCID,Leist MarcelORCID,Rahnenführer JörgORCID,Sachinidis AgapiosORCID,Hengstler Jan Georg

Abstract

Human-relevant tests to predict developmental toxicity are urgently needed. A currently intensively studied approach makes use of differentiating human stem cells to measure chemically-induced deviations of the normal developmental program, as in a recent study based on cardiac differentiation (UKK2). Here, we (i) tested the performance of an assay modeling neuroepithelial differentiation (UKN1), and (ii) explored the benefit of combining assays (UKN1 and UKK2) that model different germ layers. Substance-induced cytotoxicity and genome-wide expression profiles of 23 teratogens and 16 non-teratogens at human-relevant concentrations were generated and used for statistical classification, resulting in accuracies of the UKN1 assay of 87–90%. A comparison to the UKK2 assay (accuracies of 90–92%) showed, in general, a high congruence in compound classification that may be explained by the fact that there was a high overlap of signaling pathways. Finally, the combination of both assays improved the prediction compared to each test alone, and reached accuracies of 92–95%. Although some compounds were misclassified by the individual tests, we conclude that UKN1 and UKK2 can be used for a reliable detection of teratogens in vitro, and that a combined analysis of tests that differentiate hiPSCs into different germ layers and cell types can even further improve the prediction of developmental toxicants.

Funder

SysDT

Research Training Group “Biostatistical Methods for High-Dimensional Data in Toxicology”

BMBF (German Ministry of Education and Research) and the DFG (German Research Foundation

DK-EPA

Horizon 2020

Publisher

MDPI AG

Subject

General Medicine

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