Reliability\nof\nSerum-Derived Connectome Indicators\nin Identifying Cirrhosis

Patients\nwith cirrhosis face a heightened risk of complications,\nunderscoring the importance of identification. We have developed a\nConnectome strategy that combines metabolites with peptide spectral\nmatching (PSM) in proteomics to integrate metabolomics and proteomics,\nidentifying specific metabolites bound to blood proteins in cirrhosis\nusing open search proteomics methods. Analysis methods including Partial\nLeast Squares Discriminant Analysis (PLS-DA), Uniform Manifold Approximation\nand Projection (UMAP), and hierarchical clustering were used to distinguish\nsignificant differences among the Cirrhosis group, Chronic Hepatitis\nB (CHB) group, and Healthy group. In this study, we identified 81\ncirrhosis-associated connectomes and established an effective model\ndistinctly distinguishing cirrhosis from chronic hepatitis B and healthy\nsamples, confirmed by PLS-DA, hierarchical clustering analysis, and\nUMAP analysis, and further validated using six new cirrhosis samples.\nWe established a Unified Indicator for Identifying cirrhosis, including\ntyrosine, Unnamed_189.2, thiazolidine, etc., which not only enables\naccurate identification of cirrhosis groups but was also further validated\nusing six new cirrhosis samples and extensively supported by other\ncirrhosis research data (PXD035024). Our study reveals that characteristic\ncirrhosis connectomes can reliably distinguish cirrhosis from CHB\nand healthy groups. The established unified cirrhotic indicator facilitates\nthe identification of cirrhosis cases in both this study and additional\nresearch data.