A comparative transcriptomic dataset of hepatocytes derived from a panel of human induced pluripotent stem cells with different ethnicities as an in vitro population variability toxicity model.
- 1Division of Toxicology, Office of Chemistry and Toxicology, Office of Laboratory Operations and Applied Science, Human Foods Program, U.S. Food and Drug Administration, Laurel, MD, 20708, USA.
Abstract
Interindividual differences in response to chemicals have been typically addressed through the use of a 10-fold default "uncertainty" factor. It was only recently that in vitro models emerged to quantitatively assess interindividual variability in the human population for specific chemicals. We have attempted to establish an in vitro model for assessing population variability in hepatotoxicity testing using a panel of hepatocytes derived from nine human induced pluripotent stem cell (iPSC) lines belonging to three different ethnic groups, Black or African American (BAA), Latino or Hispanic (LOH), and Non-Hispanic White (NHW). The dataset described here was collected from the panel of iPSC-derived hepatocytes with or without exposure to two chemicals, diglycolic acid (DGA) and usnic acid (UA). Cells differentiated on day 23 were exposed to 3.0 mM DGA or 10.0 μM UA for 24 h and total RNA were isolated from the cells. Global gene expression was profiled by RNA sequencing (RNA-seq) on the Illumina NextSeq 2000 platform. Two replicates (n = 2) were included for each treatment group including untreated (control) cells. The RNA-seq dataset has been deposited in the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) repository of the National Center for Biotechnology Information with accession number GSE293032. The dataset provides a baseline for assessing interindividual variability in transcriptomic profile as well as in response to chemical exposure among the human population.
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BibTeX
@article{gao2026comparative,
title = {{A comparative transcriptomic dataset of hepatocytes derived from a panel of human induced pluripotent stem cells with different ethnicities as an in vitro population variability toxicity model.}},
author = {Xiugong Gao and Miranda R Yourick and Rong Li and Kayla Campasino and Robert L Sprando and Jeffrey J Yourick},
journal = {Data in brief},
year = {2026},
month = aug,
doi = {10.1016/j.dib.2026.113350},
url = {https://europepmc.org/article/MED/42927269},
note = {CC BY},
}
RIS
TY - JOUR
TI - A comparative transcriptomic dataset of hepatocytes derived from a panel of human induced pluripotent stem cells with different ethnicities as an in vitro population variability toxicity model.
AU - Xiugong Gao
AU - Miranda R Yourick
AU - Rong Li
AU - Kayla Campasino
AU - Robert L Sprando
AU - Jeffrey J Yourick
PY - 2026
DA - 2026/08/01
JO - Data in brief
DO - 10.1016/j.dib.2026.113350
UR - https://europepmc.org/article/MED/42927269
AB - Interindividual differences in response to chemicals have been typically addressed through the use of a 10-fold default "uncertainty" factor. It was only recently that in vitro models emerged to quantitatively assess interindividual variability in the human population for specific chemicals. We have attempted to establish an in vitro model for assessing population variability in hepatotoxicity testing using a panel of hepatocytes derived from nine human induced pluripotent stem cell (iPSC) lines belonging to three different ethnic groups, Black or African American (BAA), Latino or Hispanic (LOH), and Non-Hispanic White (NHW). The dataset described here was collected from the panel of iPSC-derived hepatocytes with or without exposure to two chemicals, diglycolic acid (DGA) and usnic acid (UA). Cells differentiated on day 23 were exposed to 3.0 mM DGA or 10.0 μM UA for 24 h and total RNA were isolated from the cells. Global gene expression was profiled by RNA sequencing (RNA-seq) on the Illumina NextSeq 2000 platform. Two replicates (n = 2) were included for each treatment group including untreated (control) cells. The RNA-seq dataset has been deposited in the Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) repository of the National Center for Biotechnology Information with accession number GSE293032. The dataset provides a baseline for assessing interindividual variability in transcriptomic profile as well as in response to chemical exposure among the human population.
SN - 2352-3409
ER -