Abstract
PURPOSE: Chronic liver disease (CLD) and complications of cirrhosis are responsible for the deaths of approximately two million people per year worldwide. Abnormal intestinal permeability in the intestinal-liver axis and development of intestinal dysbiosis increase disease progression contributing to chronic systemic inflammation in CLD patients. The intestinal microbiota acts as a bioreactor for autonomous metabolic and immunological functions in regulating the host's response to external stimuli in the intestinal microbiota. The study aimed to analyze the gut microbiota profile from colonic mucosal biopsy materials in CLD patients using a metagenomic application. MATERIALS AND METHODS: CLD and control groups were formed based on predefined inclusion and exclusion criteria from the study. In the metagenomic study, colonic mucosal biopsy material was studied from a total of 40 individuals, 20 with CLD and 20 healthy controls. We analyzed gut microbiota by 16 S rRNA metagenomic next-generation sequencing (NGS) method from colonic mucosal biopsy samples in CLD and healthy individuals. Metagenomic results were analyzed by Principal Component Analysis (PCA). RESULTS: Significant differences were observed between the CLD and control groups across multiple taxonomic levels. At the phylum level, Proteobacteria were significantly enriched in CLD patients, while Firmicutes predominated in controls. Class-level analysis showed increased Gammaproteobacteria in CLD, the former associated with inflammatory pathways. At the order level, Enterobacterales were significantly higher in CLD (OR: 1.89, p = 0.04), whereas Clostridiales were more abundant in controls. Family-level comparisons revealed elevated Enterobacteriaceae in CLD, while Ruminococcaceae and Veillonellaceae were relatively preserved in controls. At the genus level, Prevotella and Streptococcus were increased in controls. Alpha diversity indices (Shannon, Chao1) were significantly lower in the CLD group (p < 0.001), indicating reduced microbial richness. Beta diversity analysis (PCoA, Bray-Curtis) showed distinct clustering between groups, supporting compositional divergence. Integration of metagenomic findings with biochemical markers (e.g. , GGT: OR 0.79, p = 0.03) further underscored group-specific microbial signatures. CONCLUSION: We observed a significant compositional shift in the gut microbiota of patients with CLD. Notably, pro-inflammatory taxa were increased and a decrease in beneficial bacterial groups involved in maintaining microbial homeostasis. Diversity analyses indicated a reduction in microbial richness in the CLD group. These findings may aid in identifying CLD-specific microbial signatures. Furthermore, integrating metagenomic data with biochemical parameters may contribute to improved diagnostic strategies.