LC/MS/MS-Based Liver Metabolomics to Identify Chronic Liver Injury Biomarkers Following Exposure to Arsenic in Rats

肝损伤 代谢组学 化学 药理学 医学 色谱法 有机化学
作者
Dingnian Bi,Mingyang Shi,Qian Hu,Hongling Wang,Didong Lou,Aihua Zhang,Yong Hu
出处
期刊:Biological Trace Element Research [Springer Science+Business Media]
卷期号:200 (10): 4355-4369 被引量:16
标识
DOI:10.1007/s12011-021-03026-0
摘要

Arsenic is a widespread natural metalloid element. Long-term chronic exposure to arsenic can lead to different degrees of liver injury. Although the etiology of this disease is well known, to date, the underlying mechanism of arsenic-induced liver injury remains unclear, and no specific treatment exists because of the complexity of arsenic. In the present study, potential biomarkers and metabolic pathways in the livers of Wistar rats treated with arsenic for 24 weeks were investigated using an integrated metabolic approach with an LC-Orbitrap Q Exactive™ HF-X mass spectrometer. Markedly increased liver levels of arsenic, alanine aminotransferase (ALT), alkaline phosphatase (ALP), and total bile acid (TBA) were detected in the arsenic treatment groups (P < 0.05). Furthermore, histopathological examination of liver tissues showed obviously swollen, loose cytoplasm and increased necrosis in the arsenic treatment groups compared with those in the control group (P < 0.05). Metabonomics results showed that 109 metabolites (variable importance in the projection (VIP) > 1; fold change > 2 or < 0.5; P adjusted < 0.05) changed significantly after exposure to arsenic and included 71 upregulated metabolites and 38 downregulated metabolites. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that 6 metabolic pathways with statistical significance-phenylalanine metabolism, pyruvate metabolism, glycolysis/gluconeogenesis, citrate cycle (TCA cycle), thiamine metabolism, and vitamin B6 metabolism-were selected, and 13 differential metabolites were detected to be involved in regulating these metabolic pathways. The present study could help identify potential biomarkers and their functions, as well as metabolic pathways, likely providing evidence for the early diagnosis, prevention, and mechanistic study of arsenism.
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