Meta-Analysis of IBD Gut Samples Gene Expression Identifies Specific Markers of Ileal and Colonic Diseases

Abstract

Background Inflammatory bowel diseases (IBDs) are characterized by chronic inflammation and tissue damages in limited segments of the digestive tract. Pathogenesis in the tissue and mucosal inflammation probably differs according to disease location. Our aim was to further analyze transcriptomic profiles in different locations of IBD, differentiating ulcerative colitis (UC), colonic Crohn’s disease (CD), ileal CD, and pouchitis, with respect to normal colonic and ileal mucosa. We thus performed a meta-analysis focusing on specific transcriptomic signatures of ileal and colonic diseases. Methods We identified 5 cohorts with available transcriptomic data in ileal or colonic samples from active IBD and non-IBD control samples. The meta-analysis was performed on 1047 samples. In each cohort separately, we compared gene expression in CD ileitis and normal ileum; in CD colitis, UC, and normal colon; and finally in pouchitis and normal ileum. Results We identified specific markers of ileal (FOLH1, CA2) and colonic (REG3A) inflammation and showed that, with disease, some cells from the ileum start to express colonic markers. We confirmed by immunohistochemistry that these markers were specifically present in ileal or colonic diseases. We highlighted that, overall, colonic CD resembles UC and is distinct from ileal CD, which is in turn closer to pouchitis. Conclusions We demonstrated that ileal and colonic diseases exhibit specific signatures, independent of their initial clinical classification. This supports molecular, rather than clinical, disease stratification, and may be used to design drugs specifically targeting ileal or colonic diseases.

A gut-restricted glutamate carboxypeptidase II inhibitor reduces monocytic inflammation and improves preclinical colitis

“…GCPII is not normally expressed in the ileum or colon ( 9 – 11 ) but is markedly and specifically up-regulated in actively inflamed biopsies of patients with Crohn’s disease (CD) and ulcerative colitis (UC). This has been reported at the gene level, where up-regulation of GCPII’s encoding gene folate hydrolase 1 ( FOLH1 ) has been independently documented in six transcriptomic analyses of IBD biopsies from nonoverlapping patient cohorts ( 12 – 17 ), and confirmed by our laboratory, where GCPII enzymatic activity in CD and UC biopsies was found to be increased 2.8- to 41-fold in active inflamed CD and UC relative to nondiseased tissue ( 18 ).…”

Discordant effects ofex-vivoJAK inhibition on inflammatory responses in colonic compared to ileal mucosa

“…In contrast, lower response rates to enteral nutrition in colonic CD compared to ileal CD were reported 31,32 . While JAK1 inhibitors , including filgotinib and upadacitinib, have been shown to induce clinical remission in patients with CD 12,33 , a recent proof-of -concept study focusing on patient with small bowel Crohn's disease, filgotinib did not show statistically significant differences vs placebo in the proportion of patients who achieved clinical remission 34 .Moreover, in a meta-analysis examining the molecular differences between colonic and ileal IBD at the transcriptomic level, colonic samples of patients with CD resembled those of patients with UC and differed from ileal samples of patients with CD 35 . Overall, the molecular mechanisms underlying IBD in the colon may be different from those in the ileum, affecting response to therapy.…”

Drug Repositioning of Inflammatory Bowel Disease Based on Co-Target Gene Expression Signature of Glucocorticoid Receptor and TET2

“…To investigate the tissue transcriptome of IBD, we utilized NCBI's Gene Expression Omnibus (GEO) as our primary data source. Recognizing that sample location within IBD would have a large effect on the disease's expression patterns [18][19][20], we selectively analyzed colon samples from untreated patients with active disease and healthy controls from seven microarray experiments. The details of these datasets are shown in Table S1.…”

“…We meticulously collected 17 IBD biomarkers from recent literature, applying stringent criteria that necessitated their identification through both bioinformatics analysis and experimental validation [19,[24][25][26][27][28][29]]. Pearson's correlation analysis was conducted to explore the association between NR3C1 (which encodes GR) and TET2 expression with these biomarkers.…”