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Early Progression Prediction in Korean Crohn's Disease Using a Korean-Specific PrediXcan Model.

Tae-Woo Kim1, Soo Kyung Park1,2, Jaeyoung Chun3

  • 1Division of Gastroenterology, Department of Internal Medicine and Inflammatory Bowel Disease Center, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul 03181, Republic of Korea.

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Summary

This study developed a predictive model for Crohn's disease (CD) progression using clinical data and gene expression. The model accurately forecasts stricturing (B2) or penetrating (B3) phenotypes, enabling early intervention for high-risk patients.

Keywords:
Crohn’s diseaseearly progressionmachine learningpenetratingstructuring

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Area of Science:

  • Gastroenterology and Genetics
  • Inflammatory Bowel Disease Research
  • Personalized Medicine

Background:

  • Crohn's disease (CD) is a chronic inflammatory condition with potential for severe complications like stricturing (B2) and penetrating (B3) phenotypes.
  • Early identification of patients at risk for CD progression is crucial for effective, personalized treatment strategies.
  • Current methods lack robust predictive capabilities for identifying high-risk CD patients early.

Purpose of the Study:

  • To develop and validate a predictive model for early progression of Crohn's disease to B2 or B3 phenotypes.
  • To integrate clinical data with Korean-specific transcriptome-wide association study (TWAS) findings for enhanced predictive accuracy.
  • To identify key genes associated with CD progression to facilitate targeted therapeutic interventions.

Main Methods:

  • Retrospective analysis of 430 Korean CD patients from 15 centers, including genotyping and gene expression prediction via TWAS.
  • Development of logistic regression models combining clinical variables and TWAS-derived gene expression data.
  • Validation of the model's predictive performance for B2 and B3 progression within 24 months of diagnosis.

Main Results:

  • The integrated predictive model demonstrated strong performance with AUC values of 0.788 for B2 and 0.785 for B3 progression.
  • 13.9% of patients progressed to B2 and 16.9% to B3 within the study period.
  • Identified key predictive genes for B2 (e.g., CCDC154) and B3 (e.g., PUS7) progression.

Conclusions:

  • An integrative model combining clinical data and TWAS-based gene expression offers a robust approach for predicting CD progression.
  • This model can aid in the early identification of high-risk CD patients, enabling timely and personalized interventions.
  • Targeted interventions based on identified genetic markers may help mitigate disease progression and reduce complications in Crohn's disease.