Targeted Assessment of Mucosal Immune Gene Expression Predicts Clinical Outcomes in Children with Ulcerative Colitis

Abstract

Background and Aims

We aimed to determine whether a targeted gene expression panel could predict clinical outcomes in paediatric ulcerative colitis [UC] and investigated putative pathogenic roles of predictive genes.

Methods

In total, 313 rectal RNA samples from a cohort of newly diagnosed paediatric UC patients (PROTECT) were analysed by a real-time PCR microfluidic array for expression of type 1, 2 and 17 inflammation genes. Associations between expression and clinical outcomes were assessed by logistic regression. Identified prognostic markers were further analysed using existing RNA sequencing (RNA-seq) data sets and tissue immunostaining.

Results

IL13RA2 was associated with a lower likelihood of corticosteroid-free remission (CSFR) on mesalamine at week 52 (p = .002). A model including IL13RA2 and only baseline clinical parameters was as accurate as an established clinical model, which requires week 4 remission status. RORC was associated with a lower likelihood of colectomy by week 52. A model including RORC and PUCAI predicted colectomy by 52 weeks (area under the receiver operating characteristic curve 0.71). Bulk RNA-seq identified IL13RA2 and RORC as hub genes within UC outcome-associated expression networks related to extracellular matrix and innate immune response, and lipid metabolism and microvillus assembly, respectively. Adult UC single-cell RNA-seq data revealed IL13RA2 and RORC co-expressed genes were localized to inflammatory fibroblasts and undifferentiated epithelial cells, respectively, which was supported by protein immunostaining.

Conclusion

Targeted assessment of rectal mucosal immune gene expression predicts 52-week CSFR in treatment-naïve paediatric UC patients. Further exploration of IL-13Rɑ2 as a therapeutic target in UC and future studies of the epithelial-specific role of RORC in UC pathogenesis are warranted.

Lead Researchers

Link to Publication

Researchers

  1. David Mack

    Senior Scientist, CHEO Research Institute

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