| Autor: |
Daniels NJ; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA.; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44106, USA., Hershberger CE; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA.; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44106, USA., Kerosky M; Department of HPB Surgery and Liver Transplantation, Cleveland Clinic, Cleveland, OH 44106, USA., Wehrle CJ; Department of HPB Surgery and Liver Transplantation, Cleveland Clinic, Cleveland, OH 44106, USA., Raj R; Department of HPB Surgery and Liver Transplantation, Cleveland Clinic, Cleveland, OH 44106, USA., Aykun N; Department of HPB Surgery and Liver Transplantation, Cleveland Clinic, Cleveland, OH 44106, USA., Allende DS; Department of Pathology, Cleveland Clinic, Cleveland, OH 44106, USA., Aucejo FN; Department of HPB Surgery and Liver Transplantation, Cleveland Clinic, Cleveland, OH 44106, USA., Rotroff DM; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA.; Center for Quantitative Metabolic Research, Cleveland Clinic, Cleveland, OH 44106, USA.; Endocrinology and Metabolism Institute, Cleveland Clinic, Cleveland, OH 44106, USA. |
| Abstrakt: |
Chronic liver diseases, including non-alcoholic fatty liver disease (NAFLD), cirrhosis, and hepatocellular carcinoma (HCC), continue to be a global health burden with a rise in incidence and mortality, necessitating a need for the discovery of novel biomarkers for HCC detection. This study aimed to identify novel non-invasive biomarkers for these different liver disease states. We performed untargeted metabolomics in plasma (Healthy = 9, NAFLD = 14, Cirrhosis = 10, HCC = 34) and saliva samples (Healthy = 9, NAFLD = 14, Cirrhosis = 10, HCC = 22) to test for significant metabolite associations with each disease state. Additionally, we identified enriched biochemical pathways and analyzed correlations of metabolites between, and within, the two biofluids. We identified two salivary metabolites and 28 plasma metabolites significantly associated with at least one liver disease state. No metabolites were significantly correlated between biofluids, but we did identify numerous metabolites correlated within saliva and plasma, respectively. Pathway analysis revealed significant pathways enriched within plasma metabolites for several disease states. Our work provides a detailed analysis of the altered metabolome at various stages of liver disease while providing some context to altered pathways and relationships between metabolites. |
