Abstract Background Inflammatory bowel diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC), are complex conditions characterized by significant clinical, immunological, molecular, genetic, and microbiological heterogeneity. Current therapeutic strategies, particularly biologics and Janus kinase (JAK) inhibitors, are effective for inducing clinical remission and controlling inflammation. However, one-third of patients fail to respond to these treatments, highlighting the need for predictive biomarkers to better tailor therapy and improve outcomes. Methods In this study, we conducted a multi-omic approach, integrating transcriptomics, proteomics, metabolomics, and metagenomics to identify biomarkers of treatment response in IBD. A cohort of 57 active CD and 70 active UC patients was analyzed before and after 14 weeks of treatment with anti-TNF, ustekinumab, vedolizumab, or tofacitinib. Response was evaluated using endoscopic criteria, categorizing patients as responders or non-responders. Biological samples [serum, urine, serum extracellular vesicles (EVs), intestinal biopsies, and stool] were analysed using RNA sequencing, liquid chromatography-mass spectrometry, nuclear magnetic resonance, and 16S rRNA gene sequencing to assess molecular and microbial profiles. Results Our results identified multiple mRNAs, proteins and metabolites associated with treatment response (Table 1). Gene expression analysis in intestinal tissue showed significant differences between UC patients responders and non-responders to vedolizumab. Proteomic analysis of serum EVs and intestinal tissue samples revealed differentially expressed proteins between different study groups. Metabolomic analysis identified deregulation of 24 serum lipoproteins from CD responders to ustekinumab compared to non-responders. Pathway analysis highlighted significant enrichment in ketone and butyrate metabolism, mitochondrial electron transport chain activity, carnitine synthesis, and fatty acid oxidation pathways. Metagenomic analysis revealed microbial differences in UC patients responders to anti-TNF therapy compared to non-responders (Figure 1). Conclusion This multi-omics analysis uncovers promising biomarkers that could serve as predictive indicators of therapeutic response to biologics and JAK inhibitors. Nevertheless, further studies are crucial to confirm these findings and evaluate their clinical relevance in identifying patients most likely to respond to tailored therapeutic interventions. One of the challenges is integrating results from different omics approaches to create a more holistic understanding of the disease, potentially opening doors for more precise/early detection through multipanel biomarkers.
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