Identification of Molecular Subgroups in Liver Cirrhosis by Gene Expression Profiles

Background: Liver cirrhosis is characterized by high mortality, bringing a serious health and economic burden to the world. The clinical manifestations of liver are complex heterogeneous. According subgroup characteristics, identifying has become challenge. Objectives: purpose this study was evaluate difference between different subgroups cirrhosis. ultimate goal research on these phenotypes discover groups patients with unique treatment formulate targeted plans that improve prognosis disease patients’ quality life. Methods: We obtained relevant gene chip searching expression omnibus (GEO) database. profile, 79 were divided into four subgroups, which showed patterns. Therefore, we used weighted coexpression network analysis (WGCNA) find differences subgroups. Results: characteristics WGCNA module indicated subjects in I might exhibit inflammatory characteristics; II metabolically active arrhythmogenic right ventricular cardiomyopathy neuroactive ligand-receptive somatic interaction pathways significantly enriched IV. did not upregulated pathway third subgroup. Conclusions: In study, new type phenotype classification derived consensus clustering. This found may have method helps researchers explore strategies for based phenotypic characteristics.