Reliability of Serum-Derived Connectome Indicators in Identifying Cirrhosis

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