Multi-Omics Approaches to Explore Vancomycin Treatment Mechanism in Patients with Primary Sclerosing Cholangitis (PSC) - Inflammatory Bowel Disease (IBD)

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2025

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Saudi Digital Library

Abstract

Introduction: Primary sclerosing cholangitis (PSC) is a comorbid condition associated with inflammatory bowel disease (PSC-IBD) that lacks effective treatments beyond liver transplantation. Although oral vancomycin (OV) has shown therapeutic promise, disease activity often returns after treatment withdrawal. This study aims to investigate the mechanisms of OV in PSC-IBD patients, supporting the development of more durable and targeted therapies. Method: Paired multi-omics data from 15 patients before and after OV treatment were analysed. The datasets included RNA-Seq, metatranscriptomics, bile acid metabolites, and 16S rRNA. After preprocessing, feature selection was performed using LASSO, ElasticNet, and Boruta-RF. Selected features were analysed in two complementary ways: first, intersected features that were identified by all models were assessed for their predictive robustness and integrated into correlation network graphs. Union features were subjected to pathway enrichment analysis to elucidate their biological significance. Results: The 3 models consistently selected a total of 13, 2, 4, and 3 intersected features simultaneously from RNA-Seq, metatranscriptomics, bile acid metabolites, and 16S rRNA, respectively. These features achieved predictive performance comparable to or superior to the full datasets. For example, intersected features outperformed the full dataset in metatranscriptomics, where Boruta-RF achieved a higher AUC (0.936 vs. 0.896), demonstrating the robustness and efficiency of selected features. Pathway enrichment analysis of union features in each omics revealed pathways related to mucosal healing, metabolism, and immune modulation. Correlation networks graphs demonstrated that OV-induced alterations in cross-omics before and after treatment. Conclusion: Based on paired data from only 15 patients, this study provided a comprehensive multi-omics perspective on OV’s impact in PSC-IBD patients and identified robust biomarkers. We also uncovered novel host–microbiome interactions not previously reported, highlighting potential targets for future therapies. While findings are promising, they require validation in larger, independent cohorts.

Description

Introduction: Primary sclerosing cholangitis (PSC) is a comorbid condition associated with inflammatory bowel disease (PSC-IBD) that lacks effective treatments beyond liver transplantation. Although oral vancomycin (OV) has shown therapeutic promise, disease activity often returns after treatment withdrawal. This study aims to investigate the mechanisms of OV in PSC-IBD patients, supporting the development of more durable and targeted therapies. Method: Paired multi-omics data from 15 patients before and after OV treatment were analysed. The datasets included RNA-Seq, metatranscriptomics, bile acid metabolites, and 16S rRNA. After preprocessing, feature selection was performed using LASSO, ElasticNet, and Boruta-RF. Selected features were analysed in two complementary ways: first, intersected features that were identified by all models were assessed for their predictive robustness and integrated into correlation network graphs. Union features were subjected to pathway enrichment analysis to elucidate their biological significance. Results: The 3 models consistently selected a total of 13, 2, 4, and 3 intersected features simultaneously from RNA-Seq, metatranscriptomics, bile acid metabolites, and 16S rRNA, respectively. These features achieved predictive performance comparable to or superior to the full datasets. For example, intersected features outperformed the full dataset in metatranscriptomics, where Boruta-RF achieved a higher AUC (0.936 vs. 0.896), demonstrating the robustness and efficiency of selected features. Pathway enrichment analysis of union features in each omics revealed pathways related to mucosal healing, metabolism, and immune modulation. Correlation networks graphs demonstrated that OV-induced alterations in cross-omics before and after treatment. Conclusion: Based on paired data from only 15 patients, this study provided a comprehensive multi-omics perspective on OV’s impact in PSC-IBD patients and identified robust biomarkers. We also uncovered novel host–microbiome interactions not previously reported, highlighting potential targets for future therapies. While findings are promising, they require validation in larger, independent cohorts.

Keywords

Inflammatory bowel disease, primary sclerosing cholangitis, host RNA, 16s rRNA, Metatranscriptomics, bile acid metabolites, machine learning, feature selection

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