Abstract
OBJECTIVES: To overcome the limitations of invasive diagnostic approaches for ulcerative colitis (UC) diagnosis, this study integrates liquid chromatography-mass spectrometry (LC-MS)-based serum metabolomics with mucosal transcriptomics to elucidate the interplay between systemic metabolic perturbations and neuroendocrine signaling in UC pathogenesis. METHODS: Serum metabolites and mucosal differentially expressed genes (DEGs) were identified through multi-omics profiling. Key neurotransmitter receptor-related genes (NRRGs) were prioritized using three machine learning algorithms: LASSO, Random Forest, and SVM-RFE. A three-gene diagnostic nomogram was developed and rigorously validated across multiple independent cohorts (GSE48958, GSE73661) using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). RESULTS: The integrated analysis revealed 334 dysregulated metabolites and 3093 DEGs, both converging on the serotonergic synapse pathway. Specific molecular alterations were uncovered, including tryptophan depletion linked to the downregulation of SLC6A4, concomitant with abnormal serotonin accumulation and PTGS2-mediated inflammatory responses. The three-gene signature, HTR3C, RPS6KA6, and NETO2, formed a highly robust diagnostic model, achieving an area under the ROC curve (AUC) exceeding 0.96 in both the training cohort and external validation sets. CONCLUSIONS: This multi-omics study delineates a neuroimmune mechanism in UC centered on dysregulation of the serotonergic synapse. The resulting three-gene nomogram identifies a candidate biomarker signature that demonstrates strong discriminative potential; however, given the exceptionally high performance metrics, these findings should be interpreted as a preliminary diagnostic framework rather than a clinically validated tool, and its efficacy relative to standard markers like CRP or fecal calprotectin requires further investigation in prospective real-world cohorts. Nonetheless, this study provides critical mechanistic insights into gut-brain axis dysfunction in UC.