Computational Learning of microRNA-Based Prediction of Pouchitis Outcome After Restorative Proctocolectomy in Patients With Ulcerative Colitis.
Inflamm Bowel Dis. 2021 Feb 20;:
Authors: Morilla I, Uzzan M, Cazals-Hatem D, Colnot N, Panis Y, Nancey S, Boschetti G, Amiot A, Tréton X, Ogier-Denis E, Daniel F
BACKGROUND: Ileal pouch-anal anastomosis (IPAA) is the standard of care after total proctocolectomy for ulcerative colitis (UC). However, inflammation often develops in the pouch, leading to acute or recurrent/chronic pouchitis (R/CP). MicroRNAs (miRNA) are used as accurate diagnostic and predictive biomarkers in many human diseases, including inflammatory bowel diseases. Therefore, we aimed to identify an miRNA-based biomarker to predict the occurrence of R/CP in patients with UC after colectomy and IPAA.
METHODS: We conducted a retrospective study in 3 tertiary centers in France. We included patients with UC who had undergone IPAA with or without subsequent R/CP. Paraffin-embedded biopsies collected from the terminal ileum during the proctocolectomy procedure were used for microarray analysis of miRNA expression profiles. Deep neural network-based classifiers were used to identify biomarkers predicting R/CP using miRNA expression and relevant biological and clinical factors in a discovery cohort of 29 patients. The classification algorithm was tested in an independent validation cohort of 28 patients.
RESULTS: A combination of 11 miRNA expression profiles and 3 biological/clinical factors predicted the outcome of R/CP with 88% accuracy (area under the curve = 0.94) in the discovery cohort. The performance of the classification algorithm was confirmed in the validation cohort with 88% accuracy (area under the curve = 0.90). Apoptosis, cytoskeletal regulation by Rho GTPase, and fibroblast growth factor signaling were the most dysregulated targets of the 11 selected miRNAs.
CONCLUSIONS: We developed and validated a computational miRNA-based algorithm for accurately predicting R/CP in patients with UC after IPAA.
PMID: 33609036 [PubMed – as supplied by publisher]
Full Text Link: https://libkey.io/33609036