Introduction

Disorders of gut-brain interaction (DGBIs), such as functional dyspepsia and irritable bowel syndrome, are chronic gastrointestinal disorders with recurrent and bothersome abdominal symptoms. Although incompletely understood, immune activation, particularly involving eosinophils and mast cells, and visceral hypersensitivity have been implicated in their pathophysiology.

Aims & Methods

Using the normoglycemic Biobreeding diabetes-prone (BBDP-N) rat, we aim to 1) characterise the immune activation in jejunal and colonic mucosa and to 2) study the effect of budesonide, a local anti-inflammatory corticosteroid, on gut physiology and sensitivity.
90-day-old BBDP-N and Biobreeding diabetes-resistant (control) rats underwent a 28-day treatment with budesonide (0.5 mg/kg/day) or vehicle. Eosinophils and mast cells were identified by staining jejunal and colonic sections with Chromotrope 2R and anti-mast cell protease 2 antibody, respectively. To assess their activity, eosinophil peroxidase (EPO) and β-hexosaminidase levels were measured. Jejunal and colonic segments were mounted in modified Ussing chambers, and permeability was assessed by the transmucosal passage of a fluorescently labelled 20 and 4kDa dextran molecule (FITC-Dx4/20), and the transepithelial electrical resistance (TEER). Sensitivity to isobaric colorectal distension was assessed(1): the ∆ area under the curve (AUC) of the visceromotor response (VMR) to wall tension was calculated at baseline and after treatment. Depending on the normality of the data, an unpaired t-test or Mann-Whitney test was performed.

Results

Comparing vehicle-treated groups, the BBDP-N rats had higher numbers of jejunal eosinophils (1366.0±201.3 vs. 561.7±55.3 eosinophils/mm²; p<0.01) and mast cells (1151.0±136.7 vs. 549.1±44.8 mast cells/mm²; p<0.001), whereas only colonic eosinophil numbers were higher (222.7±40.4 vs. 128.9±14.5 eosinophils/mm²; p=0.03). Additionally, EPO levels were higher in the BBDP-N rats in both regions (jejunum: 59.4±9.8 vs. 4.4±3.0 µg/g tissue; p<0.01 & colon: 82.0±23.6 vs. 1.6±1.1 µg/g tissue; p<0.01), with no difference in mast cell activation. Following budesonide treatment, eosinophil (jejunum, BBDP-N: 167.3±53.6 vs. 1366.0±201.3 eosinophils/mm²; p<0.001 & control: 220.1±43.7 vs. 561.7±55.3 eosinophils/mm²; p<0.01, colon: BBDP-N: 58.2±11.9 vs. 222.7±40.4 eosinophils/mm²; p<0.01 & control: 78.1±14.4 vs. 128.9±14.5 eosinophils/mm²; p=0.01) and mast cell (jejunum: BBDP-N: 418.8±51.0 vs. 1151.0±136.7 mast cells/mm²; p<0.001 & control: 305.4±67.6 vs. 549.1±44.8 mast cells/mm²; p=0.01, colon: BBDP-N: 146.5±19.1 vs. 262.6±37.5 mast cells/mm²; p<0.01 & control: 137.4±17.8 vs. 244.9±29.4 mast cells/mm²; p<0.01) levels decreased in both groups in both regions. Colonic eosinophil activation was also reduced in BBDP-N rats (21.5±9.7 vs. 82.0±23.6 µg/g tissue; p=0.05), with no effect on mast cell activation. Jejunal permeability, assessed by 20kDa passage was increased in vehicle-treated BBDP-N rats (258.0±51.5 vs. 132.0±25.1 pmol/cm²; p=0.03). Budesonide treatment significantly increased colonic TEER in BBDP-N rats (73.2±4.3 vs. 38.3±4.1 Ω.cm²; p<0.001). Colonic sensitivity to distention was significantly reduced in BBDP-N following the treatment (-20.1±17.2 vs. 207.0±85.5 mV/s x mmHg.cm; p=0.02).

Conclusion

In conclusion, our work shows the importance of eosinophil and mast cell predominant immune activation in visceral hypersensitivity in a well-characterised preclinical model of DGBI. Anti-inflammatory treatments should be re-evaluated in DGBI with intestinal eosinophil and mast cell infiltration.

References

1: Meleine M et al. Neurogastroenterology and motility, 2019.

Introduction

The achievement of histological remission (HR) is a key treatment goal in ulcerative colitis (UC), as it is suggestive of better disease management and predicts response to therapy.
The absence of neutrophils in epithelium and lamina is crucial to define HR. However, the role of neutrophil number and localisation remains unclear. We aimed to develop a novel artificial intelligence (AI)-driven system to automate neutrophil detection, localisation, and quantification, supporting assessment of HR and enable the prediction of response to therapy.

Aims & Methods

We developed an AI-driven system by integrating two deep learning models to (1) segment whole slide images (WSIs) into epithelium, crypts and lamina propria and to (2) detect and quantify neutrophils. Outputs from these models were combined to compute neutrophil densities in the lamina propria, epithelium, and overall tissue. The optimal neutrophil density cut-offs to assess disease activity (Geboes score >2B.0) in UC patients were identified in the AMAC phase 2 Mirikizumab trial, and subsequently validated in the multicentre prospective PICaSSO cohort study. Cut-offs to determine treatment response at weeks 12 and 52 (histological improvement [HI; Geboes score ≤3.1] and histological remission [HR; Geboes score ≤2B.0]), were also evaluated.

Results

Table 1 shows the system diagnostic performance in assessing disease activity and predicting response to therapy at W12 and W52 in the Mirikizumab cohort.
303 WSIs from active UC patients from the multicentre, randomised, double-blind, parallel-arm, placebo-controlled phase 2 clinical trial of Mirikizumab were analysed. The model yielded a DICE SØrensen of 0.57 for segmentation, precision of 82.3% and recall of 77.0% for neutrophil detection. The system identified an overall optimal neutrophil density cut-off (cells/mm²) predictive of disease activity of >21.7.0 (>10.1 and >30.4 for epithelium and lamina propria, respectively), with an accuracy of 86% (85% and 85%, respectively). Further validation in the multicenter PICaSSO cohort yielded to similar results.
Moreover, the overall optimal cut-off to predict histological remission at W52 was <20.8 (<10.4 and <27.9 for epithelium and lamina propria, respectively), with an accuracy of 82.0% (81% and 80%, respectively).

Conclusion

Our novel AI-based system demonstrates strong potential as an automated tool to detect, localise, and quantify neutrophils to assess histological activity and predict response to therapy in a clinical trial UC cohort and real-world settings. This framework could be applied in clinical trials and routine clinical practice, offering objective guidance for personalised management in UC patients.

References

[1] Santacroce G, Meseguer P, Zammarchi I, et al. P406 A novel active learning-based digital pathology protocol annotation for histologic assessment in Ulcerative Colitis using PICaSSO Histologic Remission Index (PHRI). Journal of Crohn's and Colitis, Volume 18, Issue Supplement_1, January 2024, Pages i843–i844
[2] Graham S, Vu QD, Jahanifar M, et al. CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting. Med Image Anal. 2024;92:103047.

Disclosure

MI received research grants and consultant fees from Olympus, Pentax, Eli Lilly, and Janssen. All other authors declare no competing interests.