Computational Learning of microRNA-Based Prediction of Pouchitis Outcome After Restorative Proctocolectomy in Patients With Ulcerative Colitis.

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...

Full description

Bibliographic Details
Published in:Inflammatory Bowel Diseases Vol. 27; no. 10; pp. 1653 - 1661
Main Authors: Morilla, Ian, Uzzan, Mathieu, Cazals-Hatem, Dominique, Colnot, Nathalie, Panis, Yves, Nancey, Stéphane, Boschetti, Gilles, Amiot, Aurélien, Tréton, Xavier, Ogier-Denis, Eric, Daniel, Fanny
Format: research tables/charts Journal Article
Published: Oxford University Press / USA Oct2021
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=153224088&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 153224088
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        10780998
        N0V
      jtl: Inflammatory Bowel Diseases
      issn: 10780998
      maglogo: N
    pubinfo:
      dt: Oct2021
      vid: 27
      iid: 10
      pid: 622
      pub: Oxford University Press / USA
    artinfo:
      ui:
        153224088
        153224088
        153224088
        10.1093/ibd/izab030
        153224088
      ppf: 1653
      ppct: 8
      formats:
      tig:
        atl: Computational Learning of microRNA-Based Prediction of Pouchitis Outcome After Restorative Proctocolectomy in Patients With Ulcerative Colitis.
      aug:
        au:
          Morilla, Ian
          Uzzan, Mathieu
          Cazals-Hatem, Dominique
          Colnot, Nathalie
          Panis, Yves
          Nancey, Stéphane
          Boschetti, Gilles
          Amiot, Aurélien
          Tréton, Xavier
          Ogier-Denis, Eric
          Daniel, Fanny
        affil: INSERM U1149, Université de Paris, Centre de Recherche sur l'inflammation, Team Gut Inflammation , Paris, France
      sug:
        subj:
          Colitis, Ulcerative Surgery
          Ileoanal Reservoir Adverse Effects
          Pouchitis Risk Factors
          Chronic Disease Risk Factors
          Recurrence Risk Factors
          Risk Assessment
          MicroRNA Analysis
          Biological Markers Blood
          Algorithms
          Human
          Retrospective Design
          Tertiary Health Care
          France
          Surgical Patients
          Neural Networks (Computer)
          Prospective Studies
          Prediction Models
          Descriptive Statistics
      ab: 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N