Predicting Risk of Postoperative Disease Recurrence in Crohn's Disease: Patients With Indolent Crohn's Disease Have Distinct Whole Transcriptome Profiles at the Time of First Surgery.

BACKGROUND

Assessing risk of Crohn's disease (CD) recurrence following ileocolic resection (ICR) is necessary to optimize medical management and prevent long-term complications. This study aimed to identify noninvasive markers that could predict postoperative disease activity.

METHODS

Inclusion criteria were a diagnosis of CD, first ICR, interval colonoscopy, and whole transcriptome array meeting quality control standards. Demographic and clinical data were obtained from the electronic medical record. RNA extraction and human transcriptome microarray were performed on noninflamed ileal margins from operative specimens. Clinical data and random forest were analyzed in R. Principal components analysis, hierarchical clustering, and pathway enrichment were performed in Partek.

RESULTS

Sixty-five patients completed the study, and 5 were excluded from analysis due to extreme variability on whole transcriptome analysis. Unsupervised hierarchical clustering revealed that patients with an i0 Rutgeerts score generally segregated from all others. In anti-TNF-naïve patients, unsupervised hierarchical clustering revealed complete segregation of patients with an i0 score. Reduced escalation in therapy and continued mucosal remission, consistent with indolent disease, were seen in the 4 years following surgery. Random forest identified 30 transcripts differentiating i0 patients from the other groups. Pathway enrichment highlighted toll-like receptor, NOD-like receptor, and TNF signaling. This transcriptome signature did not identify i0 anti-TNF-exposed patients. However, anti-TNF-exposed patients with indolent postoperative courses were found to have a transcriptome signature distinct from those with aggressive disease.

CONCLUSIONS

Anti-TNF-naïve and -exposed patients have unique expression profiles at the time of surgery, which may offer predictive value in assessing the risk of nonrecurrence. 10.1093/ibd/izy228_video1izy228.video15804852517001.