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Rank-In Integrated Machine Learning and Bioinformatic Analysis Identified the Key Genes in HFPO-DA (GenX) Exposure to Human, Mouse, and Rat Organisms.

Authors :
Li, Xinyang
Xiao, Hua
Zhu, Liye
Liu, Qisijing
Zhang, Bowei
Wang, Jin
Wu, Jing
Song, Yaxiong
Wang, Shuo
Source :
Toxics; Jul2024, Vol. 12 Issue 7, p516, 15p
Publication Year :
2024

Abstract

Hexafluoropropylene Oxide Dimer Acid (HFPO-DA or GenX) is a pervasive perfluorinated compound with scant understood toxic effects. Toxicological studies on GenX have been conducted using animal models. To research deeper into the potential toxicity of GenX in humans and animals, we undertook a comprehensive analysis of transcriptome datasets across different species. A rank-in approach was utilized to merge different transcriptome datasets, and machine learning algorithms were employed to identify key genetic mechanisms common among various species and humans. We identified seven genes—TTR, ATP6V1B1, EPHX1, ITIH3, ATXN10, UBXN1, and HPX—as potential variables for classification of GenX-exposed samples, and the seven genes were verified in separate datasets of human, mouse, and rat samples. Bioinformatic analysis of the gene dataset further revealed that mitochondrial function and metabolic processes may be modulated by GenX through these key genes. Our findings provide insights into the underlying genetic mechanisms and toxicological impacts of GenX exposure across different species and offer valuable references for future studies using animal models to examine human exposure to GenX. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23056304
Volume :
12
Issue :
7
Database :
Complementary Index
Journal :
Toxics
Publication Type :
Academic Journal
Accession number :
178690711
Full Text :
https://doi.org/10.3390/toxics12070516