Clin Mol Hepatol > Volume 31(3); 2025 > Article
Wang, Zhang, and Tang: Lipidomic analysis of alcohol use disorder patients revealed the biomarkers for alcohol-related liver disease susceptibility
Excess alcohol intake in alcohol use disorder patients triggers liver diseases including steatosis, fibrosis, cirrhosis, and even cancer, which are termed as alcohol-associated liver disease (ALD) [1,2]. However, the susceptibility to ALD differs in individuals due to genetic variants and metabolic phenotypes [3,4]. The findings and clinical merits of ALD biomarkers have been recently reported [5,6], but the lipidomic characteristics of patients with alcoholic intemperance and the biomarkers for ALD susceptibility are still unclear. Herein, we presented two serum lipid biomarkers NAPhe 22:4;O and LPC 16:0. Patients with elevations of these two biomarkers resisted ALD after long-term excess drinking, in contrast, lower levels indicated more susceptibility to ALD.
We recruited 83 alcohol use disorder (AUD) participants and 138 Non-AUD controls in the Brain Disease Hospital affiliated to Zhengzhou University. Informed consent was obtained from all participants. The study was approved by the ethics committees of the hospital (approval ID: KS2024-001-01). AUD was tested by the Alcohol Use Disorders Identification Test (AUDIT score ≥20, Supplementary Material). The fatty liver degree was identified by B-mode ultrasound. The criteria were: None: normal echotexture of the liver; Mild: a slight and diffuse increase of liver echogenicity but normal diaphragm and portal vein wall; Moderate: a moderate increase of liver echogenicity with slightly impaired appearance of diaphragm and portal vein wall; Severe: a marked increase of liver echogenicity with poor or no visualization of diaphragm and portal vein wall. The clinical characteristics were summarized in Supplementary Table 1. The ALD was diagnosed by AUDIT ≥20, moderate/severe fatty liver, and increases in serum lipid indicators, alanine aminotransferase or aspartate aminotransferase. The lipidomic investigation was used to identify differential-ly lipid molecules between Non-AUD controls and AUD patients (Methods, Supplementary Material). The potential biomarkers were further verified between the none/mild fatty liver subgroup and the moderated/severe fatty liver subgroup in the AUD group (Fig. 1A).
Long-term excess alcohol intake distinctly altered the lipidomic profile (Fig. 1B). The permutation plot indicated the model was appropriate (Fig. 1C). Based on the criteria of variables important to projection value >1, P<0.05, 95 lipid molecules were identified (Fig. 1D, Supplementary Table 2). To investigate the correlation of these molecules with ALD in AUD patients, only 3 lipids, NAPhe 22:4;O, LPC 16:0, and Cer 21:2;O2/38:6, showed statistical significance between none/mild fatty liver subgroup and moderate/severe subgroup of AUD patients (Fig. 1E). Furthermore, NAPhe 22:4;O and LPC 16:0 showed statistical significance of AUC (Fig. 1F). Interestingly, the levels of NAPhe 22:4;O and LPC 16:0 were elevated by alcohol intake in none/mild ALD patients but not in moderated/severe ALD patients, meaning that patients with elevations of these two biomarkers were resistant to ALD, while no change indicated the susceptibility to ALD. However, NAPhe 22:4;O and LPC 16:0 were not altered in the subgroups of Non-AUD, which strengthened their specificities for AUD (Supplementary Fig. 1). We then analyzed the joint AUC of NAPhe 22:4;O and LPC 16:0 to enhance the predicting efficacy of ALD susceptibility (Fig. 1G, Combination AUC=0.7282, P<0.01), which has the potential as a diagnostic tool for ALD susceptibility in alcohol intemperance patients.
Alcohol metabolism primarily occurs in the liver through the action of oxidoreductases, transferases, and hydrolases. These metabolic pathways generate acetaldehyde and NADH in the liver, disturb fatty acid metabolism, and ultimately lead to the accumulation of fat in the liver and liver lesions. However, different AUD patients responded differently to the alcohol intemperance, as some having none/mild fatty liver while others having moderate/severe fatty liver. Our findings revealed that the elevation of NAPhe 22:4;O and LPC 16:0 in AUD patients reflected a compensatory metabolic adaptation to long-time, excess alcohol intake. Importantly, these biomarkers remained unchanged in moderate/severe fatty liver subgroups and non-AUD controls, indicating that their upregulation was specific to individuals with preserved metabolic resistance to ALD. NAPhe affects ligases and hydrolases, playing a role in regulating intracellular lipid metabolism and inflammatory responses in the liver [7]. LPC (lysophosphatidylcholine) affects hydrolases and isomerases. Higher level of LPC is associated with the synthesis and secretion of lipoproteins, preventing fat accumulation and alleviating the severity of fatty liver disease [8]. Hence, the increases in NAPhe 22:4;O and LPC 16:0 might be the compensatory responses, which present the enhanced metabolic ability for alcohol and the resistance to ALD in patients with alcoholic intemperance (Fig. 1H). Further recruitment of more AUD patients and the experimental explorations were needed for elucidating the molecular mechanism of ALD susceptibility in AUD patients.

FOOTNOTES

Authors’ contributions
D.W: Methodology, Formal analysis, Investigation, Writing - Original Draft. H.Z: Investigation, Resources, Project administration, Funding acquisition. Y.T: Conceptualization, Supervision, Writing - Review & Editing, Funding acquisition.
Acknowledgements
This research was funded by the Henan Provincial Science and Technology Research Projects (Grant no. 24210231023). Y.T is supported by the Young Elite Scientists Sponsorship Program by CAST (2022QNRC001).
Conflicts of Interest
The authors have no conflicts to disclose.

SUPPLEMENTARY MATERIAL

Supplementary material is available at Clinical and Molecular Hepatology website (http://www.e-cmh.org).
SUPPLEMENTARY METHODS
Baseline patient demographics and characteristics post propensity score matching
cmh-2025-0227-Supplementary-Methods.pdf
Supplementary Table 1.
Characteristics of patients
cmh-2025-0227-Supplementary-Table-1.pdf
Supplementary Table 2.
Characteristics of serum lipids
cmh-2025-0227-Supplementary-Table-2.pdf
Supplementary Figure 1.
Column plots of NAPhe 22:4;O (A) and LPC 16:0 (B) in Non-AUD subgroups. AUD, alcohol use disorder.
cmh-2025-0227-Supplementary-Fig-1.pdf

Figure 1.
Susceptible biomarkers NAPhe 22:4;O and LPC 16:0 for alcohol-associated liver disease (ALD) in patients with alcohol use disorder (AUD). (A) Study scheme. (B) Score plot (R2X[cum]=0.786, R2Y[cum]=0.826, Q2[cum]=0.684), (C) permutation plot, and (D) heatmap visualization of the OPLS-DA model for the Non-AUD and AUD group. Light blue dots represent the Non-AUD group (n=138), and orange dots represent the AUD group (n=83). (E) Column plots and (F) ROC curves of the NAPhe 22:4;O, LPC 16:0 and Cer 21:2;O2/38:6. (G) The logistic regression model for the combination ROC curves of NAPhe 22:4;O and LPC 16:0. (H) The comparisons of metabolic enzymes among alcohol, NAPhe 22:4;O and LPC 16:0.

cmh-2025-0227f1.jpg

Abbreviations

ALD
alcohol-associated liver disease
AUD
alcohol use disorder
AUDIT
Alcohol Use Disorders Identification Test

REFERENCES

1. Arab JP, Addolorato G, Mathurin P, Thursz MR. Alcohol-associated liver disease: integrated management with alcohol use disorder. Clin Gastroenterol Hepatol 2023;21:2124-2134.
crossref pmid
2. Danpanichkul P, Díaz LA, Suparan K, Tothanarungroj P, Sirimangklanurak S, Auttapracha T, et al. Global epidemiology of alcohol-related liver disease, liver cancer, and alcohol use disorder, 2000-2021. Clin Mol Hepatol 2025;31:525-547.
pmid pmc
3. Mendoza YP, Tsouka S, Semmler G, Seubnooch P, Freiburghaus K, Mandorfer M, et al. Metabolic phenotyping of patients with advanced chronic liver disease for better characterization of cirrhosis regression. J Hepatol 2024;81:983-994.
crossref pmid
4. Norden-Krichmar TM, Rotroff D, Schwantes-An TH, Bataller R, Goldman D, Nagy LE, et al. Genomic approaches to explore susceptibility and pathogenesis of alcohol use disorder and alcohol-associated liver disease. Hepatology 2025;81:1595-1606.
crossref pmid
5. Papatheodoridi M, De Ledinghen V, Lupsor-Platon M, Bronte F, Boursier J, Elshaarawy O, et al. Agile scores in MASLD and ALD: external validation and their utility in clinical algorithms. J Hepatol 2024;81:590-599.
crossref pmid
6. Song DS, Kim HY, Jung YK, Kim TH, Yim HJ, Yoon EL, et al. Dynamic analysis of acute deterioration in chronic liver disease patients using modified quick sequential organ failure assessment. Clin Mol Hepatol 2024;30:388-405.
pmid pmc
7. Liao Y, Chen Q, Liu L, Huang H, Sun J, Bai X, et al. Amino acid is a major carbon source for hepatic lipogenesis. Cell Metab 2024;36:2437-2448.e8.
crossref pmid
8. Paul B, Lewinska M, Andersen JB. Lipid alterations in chronic liver disease and liver cancer. JHEP Rep 2022;4:100479.
crossref pmid pmc

Editorial Office
The Korean Association for the Study of the Liver
Room A1210, 53 Mapo-daero(MapoTrapalace, Dowha-dong), Mapo-gu, Seoul, 04158, Korea
TEL: +82-2-703-0051   FAX: +82-2-703-0071    E-mail: cmh_journal@ijpnc.com
Copyright © The Korean Association for the Study of the Liver.         
COUNTER
TODAY : 3022
TOTAL : 2897524
Close layer