Abstract Introduction and aims Risk stratification of subjects with a history of inflammatory bowel disease (IBD) into those likely to relapse and those who will remain quiescent continues to be a significant challenge. The aim of this study was to investigate whether certain proteomic signature profiles or biomarkers during remission are associated with future disease relapse in patients with ulcerative colitis (UC). Methods Endoscopic rectal samples from patients with UC in clinical, endoscopic, and histological remission at index endoscopy were collected, as well as samplers from normal control individuals. The patients were stratified to early relapsers (ERs) if they developed clinical signs of UC flare within 6 months of index endoscopy or nonrelapsers (NRs) if there was no relapse after 36 months of follow-up. The pooled rectal samples from ERs, NRs, and control individuals were subjected to nano-liquid chromatography and tandem mass spectrometry as per standard iTRAQ (isobaric tags for relative and absolute quantitation) workflow methodology. Selected proteomics-yielded candidates were subjected to orthogonal validation via immunoblotting, in a biomarker discovery exercise. Results Sixty-one patients were included, of whom 8 had clinical relapse within 6 months from the index endoscopy, and 43 patients had no clinical symptoms of relapse within the 36-month follow-up period. Ten patients who had clinical signs of relapse between 6 and 36 months were excluded. Seventeen control individuals were also included. Soluble proteomics analyses between ERs, NRs, and control individuals revealed a series of upregulated and downregulated proteins. Following orthogonal validation, upregulated TRX (P = .001) and IGHA1 (P = .001) were observed in ERs relative to NRs. Conclusions Several novel candidate tissue biomarkers have been identified in this study, which could discriminate patients with UC at risk of early relapse from those in long-term sustained remission. Our findings may pave the way for pre-emptive UC disease monitoring and therapeutic decision making.