Multi-omics gut microbiome signatures for treat-to-target management in inflammatory bowel disease

Inflammatory bowel disease (IBD) care now relies on an expanding portfolio of biologics and small molecules, yet symptom-driven phenotyping often misses molecular endotypes, contributing to primary non-response and loss of response. This review examines how gut microbiota-centered multi-omics can be translated into decision support within treat-to-target (T2T) management and therapeutic drug monitoring (TDM). We synthesize evidence from stool and mucosal metagenomics/metatranscriptomics, virome and bacteriophage signals, metabolomics, blood proteomics, and host transcriptomic/epigenomic and genetic layers, emphasizing analytical validity, external validation, calibration, and action-linked thresholds. Longitudinal data indicate that IBD-associated dysbiosis is predominantly functional and time-varying, enabling applications in diagnosis, prognosis, therapy-response prediction, and monitoring of inflammatory burden and remission depth. However, many reported predictors show limited transportability due to pre-analytical variation, batch effects, endpoint heterogeneity, and confounding by diet, antibiotics, and prior therapies. We propose a pragmatic, tiered workflow: deploy minimal, interpretable signatures at baseline and early induction, and interpret outputs alongside fecal calprotectin/CRP, endoscopy or imaging when indicated, and drug exposure/anti-drug antibodies to distinguish underexposure and immunogenicity from true mechanistic non-response, guiding dose optimization versus mechanism switching. Digital/remote monitoring can operationalize iterative reassessment while reserving deeper omics for decision-critical checkpoints. Overall, the microbiome is best framed as an actionable layer within a multi-signal IBD management system rather than a standalone biomarker; translation will depend on standardization, workflow integration, prospective validation, and demonstrated clinical and economic value.