Objective We have previously described a prognostic transcriptional signature in CD8 T-cells that separates inflammatory bowel disease (IBD) patients into 2 phenotypically-distinct subgroups, termed IBD1 and IBD2. Here we sought to develop a blood-based test that could identify these subgroups without cell separation, and thus be suitable for clinical use in Crohn’s disease (CD) and ulcerative colitis (UC).

Design Patients with active IBD were recruited before treatment. Transcriptomic analyses were performed on purified CD8 T-cells and/or whole blood. Phenotype data was collected prospectively. IBD1/IBD2 patient subgroups were identified by consensus clustering of CD8 T-cell transcriptomes. In a training cohort, machine learning was used to identify groups of genes (“classifiers”) whose differential expression in whole blood re-created the IBD1/IBD2 subgroups. Genes from the best classifiers were qPCR-optimised, and further machine learning was used to identify the optimal qPCR classifier, which was locked-down for further testing. Independent validation was sought in separate cohorts of CD (n=66) and UC patients (n=57).

Results In both validation cohorts, a 17-gene qPCR-based classifier stratified patients into two distinct subgroups. Irrespective of the underlying diagnosis, IBDhi patients (analogous to the poor-prognosis IBD1 subgroup) experienced significantly more aggressive disease than IBDlo patients (analogous to IBD2), with earlier need for treatment escalation (hazard ratio=2.65 [CD], 3.12 [UC]) and more escalations over time (for multiple escalations within 18 months: sensitivity=72.7% [CD], 100% [UC]; NPV=90.9% [CD], 100% [UC]).

Conclusion This is the first validated prognostic biomarker that can predict prognosis in newly-diagnosed IBD patients, and represents a step towards personalised therapy.