The hidden effects of metabolism-disrupting agents on alcohol-related liver disease risk: an integrated epidemiological, machine learning, and network toxicology Analysis.
14 affiliations
- 1Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China.
- 2Shandong Clinical Research Center of Diabetes and Metabolic Diseases, Jinan, Shandong, 250021, China.
- 3Shandong Institute of Endocrine and Metabolic Diseases, Jinan, Shandong, 250021, China.
- 4"Chuangxin China" Innovation Base of stem cell and Gene Therapy for endocrine Metabolic diseases, Jinan, Shandong, 250021, China.
- 5Shandong Institute of Endocrine and Metabolic Diseases, Jinan, Shandong, 250021, China. [email protected].
- 6Endocrine and Metabolic Diseases Hospital of Shandong First Medical University, Jinan, Shandong, 250021, China. [email protected].
- 7Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China. [email protected].
- 8Shandong Clinical Research Center of Diabetes and Metabolic Diseases, Jinan, Shandong, 250021, China. [email protected].
- 9Shandong Institute of Endocrine and Metabolic Diseases, Jinan, Shandong, 250021, China. [email protected].
- 10"Chuangxin China" Innovation Base of stem cell and Gene Therapy for endocrine Metabolic diseases, Jinan, Shandong, 250021, China. [email protected].
- 11Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China. [email protected].
- 12Shandong Clinical Research Center of Diabetes and Metabolic Diseases, Jinan, Shandong, 250021, China. [email protected].
- 13Shandong Institute of Endocrine and Metabolic Diseases, Jinan, Shandong, 250021, China. [email protected].
- 14"Chuangxin China" Innovation Base of stem cell and Gene Therapy for endocrine Metabolic diseases, Jinan, Shandong, 250021, China. [email protected].
Abstract
Background
Individual susceptibility to alcohol-related liver disease (ALD) varies substantially despite similar alcohol consumption patterns. Emerging evidence suggests metabolism-disrupting agents (MDAs) may synergistically amplify alcohol-induced hepatotoxicity, yet population-level evidence remains limited. This study investigated associations between 40 MDAs and ALD risk using integrated analytical approaches.Methods
We analyzed 13,472 National Health and Nutrition Examination Survey participants (2005-2016). Forty MDAs spanning per- and polyfluoroalkyl substances, phenolic compounds, phthalate metabolites, polycyclic aromatic hydrocarbon metabolites, and volatile organic compound metabolites were measured using standardized protocols. Multivariable logistic regression assessed MDA-ALD associations. Restricted cubic splines characterized dose-response relationships. Subgroup analyses identified vulnerable populations by sex, age, race/ethnicity, body mass index, and hyperlipidemia status. Machine learning algorithms including LightGBM were developed with nested cross-validation (to prevent data leakage during feature selection) to identify predictive biomarkers. Network toxicology integrated computationally predicted MDA targets with ALD gene expression data (GEO GSE28619), followed by pathway enrichment analyses.Results
Three MDAs demonstrated robust positive associations: benzylmercapturic acid (BMA; OR: 1.56, 95% CI: 1.31-1.86), perfluorohexanesulfonic acid (PFHxS; OR: 1.56, 95% CI: 1.28-1.90), and benzophenone-3 (BP-3; OR: 1.40, 95% CI: 1.15-1.72). BMA and PFHxS exhibited linear dose-response relationships without thresholds, while ATCA showed an inverted U-shaped pattern and BP-3 displayed a plateau pattern. Phenolic compounds and phthalates demonstrated stronger associations in females. LightGBM achieved optimal performance (cross-validation AUC: 0.760, test AUC: 0.706), identifying N-acetyl-S-(3-hydroxypropyl)-L-cysteine, N-acetyl-S-(N-methylcarbamoyl)-L-cysteine, and mono-carboxyoctyl phthalate as key predictive biomarkers, including compounds not significant in regression. Network analysis identified 192 shared genes with enrichment in neuroactive ligand-receptor interactions and nuclear receptor pathways (PPARα/γ, PXR, FXR).Conclusions
Specific MDAs demonstrated significant ALD associations through complementary approaches. Evidence suggests MDAs may function as signal disruptors within neuro-endocrine-immune networks, with pathways paralleling alcohol-induced hepatotoxicity. Findings underscore incorporating environmental assessments into ALD risk stratification and highlight needs for prospective validation and mechanistic studies.
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BibTeX
@article{ma2026hidden,
title = {{The hidden effects of metabolism-disrupting agents on alcohol-related liver disease risk: an integrated epidemiological, machine learning, and network toxicology Analysis.}},
author = {Longpeng Ma and Jinning Zhang and Juntong Wei and Wenbo Bian and Tao Bo and Shanshan Shao and Xinhua Li and Jiajun Zhao and Zhenyu Yao},
journal = {Journal of translational medicine},
year = {2026},
month = jul,
doi = {10.1186/s12967-026-08673-2},
url = {https://europepmc.org/article/MED/42907914},
note = {CC BY},
}
RIS
TY - JOUR
TI - The hidden effects of metabolism-disrupting agents on alcohol-related liver disease risk: an integrated epidemiological, machine learning, and network toxicology Analysis.
AU - Longpeng Ma
AU - Jinning Zhang
AU - Juntong Wei
AU - Wenbo Bian
AU - Tao Bo
AU - Shanshan Shao
AU - Xinhua Li
AU - Jiajun Zhao
AU - Zhenyu Yao
PY - 2026
DA - 2026/07/01
JO - Journal of translational medicine
DO - 10.1186/s12967-026-08673-2
UR - https://europepmc.org/article/MED/42907914
AB - Background Individual susceptibility to alcohol-related liver disease (ALD) varies substantially despite similar alcohol consumption patterns. Emerging evidence suggests metabolism-disrupting agents (MDAs) may synergistically amplify alcohol-induced hepatotoxicity, yet population-level evidence remains limited. This study investigated associations between 40 MDAs and ALD risk using integrated analytical approaches.Methods We analyzed 13,472 National Health and Nutrition Examination Survey participants (2005-2016). Forty MDAs spanning per- and polyfluoroalkyl substances, phenolic compounds, phthalate metabolites, polycyclic aromatic hydrocarbon metabolites, and volatile organic compound metabolites were measured using standardized protocols. Multivariable logistic regression assessed MDA-ALD associations. Restricted cubic splines characterized dose-response relationships. Subgroup analyses identified vulnerable populations by sex, age, race/ethnicity, body mass index, and hyperlipidemia status. Machine learning algorithms including LightGBM were developed with nested cross-validation (to prevent data leakage during feature selection) to identify predictive biomarkers. Network toxicology integrated computationally predicted MDA targets with ALD gene expression data (GEO GSE28619), followed by pathway enrichment analyses.Results Three MDAs demonstrated robust positive associations: benzylmercapturic acid (BMA; OR: 1.56, 95% CI: 1.31-1.86), perfluorohexanesulfonic acid (PFHxS; OR: 1.56, 95% CI: 1.28-1.90), and benzophenone-3 (BP-3; OR: 1.40, 95% CI: 1.15-1.72). BMA and PFHxS exhibited linear dose-response relationships without thresholds, while ATCA showed an inverted U-shaped pattern and BP-3 displayed a plateau pattern. Phenolic compounds and phthalates demonstrated stronger associations in females. LightGBM achieved optimal performance (cross-validation AUC: 0.760, test AUC: 0.706), identifying N-acetyl-S-(3-hydroxypropyl)-L-cysteine, N-acetyl-S-(N-methylcarbamoyl)-L-cysteine, and mono-carboxyoctyl phthalate as key predictive biomarkers, including compounds not significant in regression. Network analysis identified 192 shared genes with enrichment in neuroactive ligand-receptor interactions and nuclear receptor pathways (PPARα/γ, PXR, FXR).Conclusions Specific MDAs demonstrated significant ALD associations through complementary approaches. Evidence suggests MDAs may function as signal disruptors within neuro-endocrine-immune networks, with pathways paralleling alcohol-induced hepatotoxicity. Findings underscore incorporating environmental assessments into ALD risk stratification and highlight needs for prospective validation and mechanistic studies.
SN - 1479-5876
ER -