Metabolomics and Data-Driven Bioinformatics Revealed Key Maternal Metabolites Related to Fetal Lethality via Di(2-ethylhexyl)phthalate Exposure in Pregnant Mice

Abstract

We performed serum metabolome analysis of di(2-ethylhexyl)phthalate (DEHP)-exposed and control pregnant mice. Pregnant mice ( n = 5) were fed a DEHP-containing diet (0.1% or 0.2% DEHP) or a normal diet (control) from gestational days 0–18. After maternal exposure to 0.2% DEHP there were no surviving fetuses, indicating its strong fetal lethality. There were no significant differences in the numbers of fetuses and placentas between the 0.1% DEHP and control groups, although fetal viability differed significantly between them, suggesting that maternal exposure to 0.1% DEHP could inhibit fetal growth. Metabolomics successfully detected 169 metabolites in serum. Principal component analysis (PCA) demonstrated that the three groups were clearly separated on PCA score plots. The biological interpretation of PC1 was fetal lethality, whereas PC2 meant metabolic alteration of pregnant mice via DEHP exposure without fetal lethality. In particular, the first component was significantly correlated with fetal viability, demonstrating that maternal metabolome changes via DEHP exposure were strongly related to fetal lethality. Levels of some amino acids were significantly increased in the DEHP-exposed groups, whereas those of some fatty acids, nicotinic acid, and 1,5-anhydroglucitol were significantly decreased in the DEHP groups. DEHP-induced increases in glycine levels could cause fetal neurological disorders, and decreases in nicotinic acid could inhibit fetal growth. In addition, a machine-learning Random forest could determine 16 potential biomarkers of DEHP exposure, and data-driven network analysis revealed that nicotinic acid was the most influential hub metabolite in the metabolic network. These findings will be useful for understanding the effects of DEHP on the maternal metabolome in pregnancy and their relationship to fetal lethality.