Related Experiment Video
Updated: Jan 11, 2026

An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
Identifying biomarkers for arsenic exposure-induced nonalcoholic fatty liver disease: An integrated proteomics,
Yiqiong Sun1, Fuping Li2, Weizhen Hua2
1State Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Regional and Urban Ecology, Ningbo Observation and Research Station, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Abstract:
Arsenic, a toxic metalloid prevalent in the environment, poses significant health risks to humans primarily via the contamination of water. Arsenic exposure has been demonstrated to cause nonalcoholic fatty liver disease (NAFLD); however, the biomarkers used for the identification of its NAFLD risk remain inadequately explored. Based on our previous finding that arsenic induces NAFLD (characterized by hepatic lipid accumulation) in rats, this study aimed to identify potential biomarkers for the risk assessment of environmentally relevant levels of arsenic-induced NAFLD using an integrated multi-omics and machine learning analysis. The results indicated that the alterations in the peroxisome proliferator-activated receptor (PPAR) signaling pathway and purine metabolism in rat liver are the primary contributors to arsenic-induced NAFLD. Notably, adenosine monophosphate (AMP) may play a key role in the interaction between these two pathways. Through a leave-one-out cross-validation, the model composed of AMP, 13-hydroxyoctadecadienoic acid (13-HODE), and hippuric acid demonstrated a robust capability to discriminate between NAFLD and controls in both rats (AUC = 0.94) and human populations (AUC = 0.86). This study provides novel insights for developing of effective metabolic biomarkers to identify NAFLD associated with environmental arsenic exposure, which could be used for early prediction and intervention.
More Related Videos
11:02Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
07:54Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy
Published on: December 15, 2011