Lipidomics for the Prediction of Progressive Liver Disease in Patients with Alcohol Use Disorder
Abstract
:1. Introduction
2. Results
2.1. Patient Cohort
2.2. Serum Lipidome
2.3. Fecal Lipidome
2.4. Lipid Biomarkers for Progressive Liver Disease
2.5. Association of Lipid Biomarkers with Clinical Parameters
2.6. Prediction of Progressive Liver Disease
2.7. Microbial Lipid Pathways
3. Discussion
4. Materials and Methods
4.1. Patients
4.2. Lipidomics Analysis
4.3. Shotgun Metagenomics Analysis
4.4. Statistical Analysis
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Non-Alcoholic Controls | Non-Progressive Liver Disease | Progressive Liver Disease | p-Value | |
---|---|---|---|---|
Clinical parameter | ||||
Total n | 17 | 16 | 16 | |
Age, years, n = 48 | 38 (27–71) | 37 (27–58) | 41 (28–59) | 0.470 |
Body Mass Index (BMI), kg/m², n = 48 | 22 (19–29) | 22 (19-31) | 24 (18–31) | 0.381 |
Gender (male), n (%), n = 48 | 14 (88) | 11 (69) | 14 (88) | 0.292 |
Laboratory parameter | ||||
Albumin (g/dL), n = 27 | 4.7 (4.2–5.2) | 4.7 (3.9–5.2) | 0.558 | |
Alkaline phosphatase (U/L), n = 28 | 65 (38–101) | 81 (47–113) | 0.072 | |
ALT (U/L), n = 32 | 19 (11–37) | 78 (37–184) | <0.001 | |
AST (U/L), n = 32 | 25 (15–36) | 81 (46–283) | <0.001 | |
Total bilirubin (mg/dL), n = 29 | 0.3 (0.2–1.1) | 0.5 (0.3–0.9) | 0.031 | |
GGT (U/L), n = 29 | 31 (4–213) | 139 (11–952) | 0.012 | |
Platelet counts (×109/L), n = 28 | 268 (165–339) | 220 (21–434) | 0.270 | |
Creatinine (mg/dL), n = 29 | 0.8 (0.5–1.0) | 0.8 (0.6–1.2) | 0.406 | |
International normalized ratio, n = 29 | 1.0 (0.9–1.2) | 0.9 (0.8–1.0) | 0.115 | |
Fibroscan (kpa), n = 32 | 4.8 (3.1–6.6) | 6.0 (3.2–7.0) | 0.122 | |
CAP, (dB/m), n = 32 CAP > 250 dB/m, n (%) | 254 (148–325) 9 (56) | 314 (222–381) 15 (94) | <0.001 | |
Fecal albumin (µg/L), n = 43 | 16.9 (4.7–66.6) | 56.8 (10.5–504.4) | 31.2 (2.2–98.1) | 0.002 |
CK18-M65 (U/L), n = 38 | 166 (104–282) | 332 (158–616) | 592 (316–1576) | <0.001 |
sCD14 (ng/mL), n = 38 | 1376 (1074–1810) | 1710 (1046–2570) | 1745 (1191–2266) | 0.033 |
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Gao, B.; Zeng, S.; Maccioni, L.; Shi, X.; Armando, A.; Quehenberger, O.; Zhang, X.; Stärkel, P.; Schnabl, B. Lipidomics for the Prediction of Progressive Liver Disease in Patients with Alcohol Use Disorder. Metabolites 2022, 12, 433. https://doi.org/10.3390/metabo12050433
Gao B, Zeng S, Maccioni L, Shi X, Armando A, Quehenberger O, Zhang X, Stärkel P, Schnabl B. Lipidomics for the Prediction of Progressive Liver Disease in Patients with Alcohol Use Disorder. Metabolites. 2022; 12(5):433. https://doi.org/10.3390/metabo12050433
Chicago/Turabian StyleGao, Bei, Suling Zeng, Luca Maccioni, Xiaochun Shi, Aaron Armando, Oswald Quehenberger, Xinlian Zhang, Peter Stärkel, and Bernd Schnabl. 2022. "Lipidomics for the Prediction of Progressive Liver Disease in Patients with Alcohol Use Disorder" Metabolites 12, no. 5: 433. https://doi.org/10.3390/metabo12050433
APA StyleGao, B., Zeng, S., Maccioni, L., Shi, X., Armando, A., Quehenberger, O., Zhang, X., Stärkel, P., & Schnabl, B. (2022). Lipidomics for the Prediction of Progressive Liver Disease in Patients with Alcohol Use Disorder. Metabolites, 12(5), 433. https://doi.org/10.3390/metabo12050433