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<p>Metabolic dysfunction-associated steatotic liver disease (MASLD) has become one of the most prevalent chronic liver conditions worldwide, with its incidence steadily rising. However, the underlying mechanisms linking MASLD to colorectal adenoma remain unclear, and the role of gut microbiota and metabolites in this association requires further investigation. This study aims to characterise the gut microbiota and metabolites in patients with MASLD and colorectal adenoma. A cohort of 58 MASLD patients was enrolled and stratified into two groups based on colorectal adenoma status: the MASLD with colorectal adenoma group (M-CA group, <i>n</i> = 30) and the MASLD without colorectal adenoma group (M-NCA group, <i>n</i> = 28). The gut microbial ecosystem in the M-CA group showed significant dysregulation, evidenced by a decreased Gut Microbiome Health Index (GMHI) and significantly increased Microbiome Dysbiosis Index (MDI). Linear Discriminant Analysis Effect Size (LEfSe) identified 75 differentially abundant microbial taxa between groups, with <i>Bacteroides vulgatus</i>, <i>Bacteroides ovatus</i>, <i>uncultured bacterium of norank genus of Muribaculaceae family</i>,<i> Muribaculaceae</i>, and <i>norank of Muribaculaceae family</i> being significantly enriched in the M-CA group, representing potential microbial biomarkers for this cohort. Partial Least Squares Discriminant Analysis (PLS-DA) screened 116 differential metabolites. When combined with Random Forest (RF), Support Vector Machine (SVM) and Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithms, 16 significantly identified biomarkers were discovered. The joint analysis of both omics revealed that variations in differential metabolite levels were associated with changes in specific microbiota abundances. Kyoto encyclopedia of genes and genomes (KEGG) functional prediction analysis indicated that the coordinated alterations in metabolites and microbiota may collectively influence multiple metabolic pathways, including lipid metabolism, xenobiotics biodegradation and metabolism, amino acid metabolism, carbohydrate metabolism, biosynthesis of other secondary metabolites and nucleotide metabolism. This study revealed that patients with MASLD and colorectal adenoma exhibited significant alterations in the gut microbiota composition and metabolic profile, indicating potential impacts on associated metabolic pathways. These findings provided novel insights and a foundation for future research into potential intervention strategies for this clinical complication.</p>

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Characteristics of gut microbiota and metabolites in patients with metabolic dysfunction-associated steatotic liver disease and colorectal adenoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月27日

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  • Yuting Li,
  • Wen Fu,
  • Zhao Xiang,
  • Minzhu Zhao,
  • Xuancheng Xie,
  • Weibo Guo,
  • Ying Zhou,
  • Mengyao Zheng,
  • Jinhui Yang

摘要

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become one of the most prevalent chronic liver conditions worldwide, with its incidence steadily rising. However, the underlying mechanisms linking MASLD to colorectal adenoma remain unclear, and the role of gut microbiota and metabolites in this association requires further investigation. This study aims to characterise the gut microbiota and metabolites in patients with MASLD and colorectal adenoma. A cohort of 58 MASLD patients was enrolled and stratified into two groups based on colorectal adenoma status: the MASLD with colorectal adenoma group (M-CA group, n = 30) and the MASLD without colorectal adenoma group (M-NCA group, n = 28). The gut microbial ecosystem in the M-CA group showed significant dysregulation, evidenced by a decreased Gut Microbiome Health Index (GMHI) and significantly increased Microbiome Dysbiosis Index (MDI). Linear Discriminant Analysis Effect Size (LEfSe) identified 75 differentially abundant microbial taxa between groups, with Bacteroides vulgatus, Bacteroides ovatus, uncultured bacterium of norank genus of Muribaculaceae family, Muribaculaceae, and norank of Muribaculaceae family being significantly enriched in the M-CA group, representing potential microbial biomarkers for this cohort. Partial Least Squares Discriminant Analysis (PLS-DA) screened 116 differential metabolites. When combined with Random Forest (RF), Support Vector Machine (SVM) and Least Absolute Shrinkage and Selection Operator (LASSO) machine learning algorithms, 16 significantly identified biomarkers were discovered. The joint analysis of both omics revealed that variations in differential metabolite levels were associated with changes in specific microbiota abundances. Kyoto encyclopedia of genes and genomes (KEGG) functional prediction analysis indicated that the coordinated alterations in metabolites and microbiota may collectively influence multiple metabolic pathways, including lipid metabolism, xenobiotics biodegradation and metabolism, amino acid metabolism, carbohydrate metabolism, biosynthesis of other secondary metabolites and nucleotide metabolism. This study revealed that patients with MASLD and colorectal adenoma exhibited significant alterations in the gut microbiota composition and metabolic profile, indicating potential impacts on associated metabolic pathways. These findings provided novel insights and a foundation for future research into potential intervention strategies for this clinical complication.