What question did this study set out to answer?

This research aims to elucidate the relationship between mitochondrial metabolism and the immune microenvironment in inflammatory bowel disease (IBD).

June 17, 2026

Investigating Immune Microenvironment of Inflammatory Bowel Disease and the Mitochondrial Metabolism-Related Molecular Mechanisms: Combining a Multiomics Approach and Experimental Validation

Key Points

This research aims to elucidate the relationship between mitochondrial metabolism and the immune microenvironment in inflammatory bowel disease (IBD).
Utilized transcriptome datasets and single-cell sequencing from Gene Expression Omnibus.
Conducted differential expression analysis and weighted gene co-expression network analysis to identify key genes.
Applied machine learning for screening key genes and constructing risk prediction models.
Identified two downregulated key genes, MRPL35 and MRPL39, with strong diagnostic potential in IBD.
Revealed complex communication patterns between mononuclear phagocyte cells and other immune cells.
Constructed a ceRNA network highlighting interactions among XIST, hsa-miR-103a-3p, and MRPL35.

Abstract

Inflammatory bowel disease (IBD) is a chronic and recurrent gastrointestinal disease, the pathogenesis of which has not been fully elucidated. Increasing evidence suggests that the disorder of mitochondrial metabolism is closely related to the pathogenesis of IBD, but its specific regulatory network and key genes remain to be further investigated. IBD-related transcriptome datasets (GSE3365 and GSE75214) and single-cell sequencing dataset (GSE134809) were obtained from the Gene Expression Omnibus database. Differentially expressed genes and hub genes were identified through differential expression analysis and weighted gene co-expression network analysis, and candidate genes were obtained by intersecting these with mitochondrial metabolism-related genes, followed by functional enrichment analysis. Machine learning algorithms were used to screen key genes and construct risk prediction models. Additionally, analysis of GSE134809 single-cell data identified characteristic cell types and expression distribution of key genes in IBD and explored communication between different cell types. Furthermore, immune cell infiltration, competitive endogenous RNA (ceRNA) network, and transcription factor prediction were performed. Finally, the diagnostic performance of key genes was validated in GSE75214 and reverse transcription–quantitative polymerase chain reaction. Two key genes, mitochondrial ribosomal protein L35 ( MRPL35 ) and MRPL39 , were identified, which were downregulated in IBD, and had good diagnostic potential. Single-cell analysis revealed that key genes were predominantly highly expressed in mononuclear phagocyte (MNP) cells. MNP cells communicated with other cells through receptor ligands including MIF-(CD74 + CXCR4), MDK-SDC1, and ITGB2-ICAM2, which are complexly related to mitochondrial metabolism. With the progression of IBD, infiltration levels of resting natural killer cells, naive B cells, M2 macrophages, and naive CD4 T cells decreased, and correlations between different cells continuously changed. A ceRNA network centered on XIST, hsa-miR-103a-3p, and MRPL35 was constructed. Additionally, therapeutic drugs targeting key genes were predicted, including cimetidine, eugenol, chlortetracycline, vincristine, irinotecan, bisacodyl, and sulpiride, with molecular docking validating high affinity between these drugs and key targets. This study constructed a multiomics integrated analysis strategy and identified MRPL35 and MRPL39 as potential markers and therapeutic targets, providing new insights for the diagnosis and treatment of IBD.

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