Local type 2 immunity in eosinophilic gastritis

TH2 cell compensatory effect following benralizumab treatment for eosinophilic gastritis

BACKGROUND

Eosinophil accumulation is a main feature of eosinophilic gastritis (EoG) and is associated with its histologic diagnosis and pathology. However, a recent clinical trial has demonstrated that EoG endoscopic, noneosinophil histologic, and clinical features remain persistent despite complete eosinophil depletion.

OBJECTIVE

Our aim was to examine gastric T-cell composition and associated cytokine levels of patients with EoG following benralizumab-induced eosinophil depletion versus following administration of placebo.

METHODS

A cohort of subjects with EoG from a subset of subjects who participated in a recent phase 2 benralizumab trial was treated for 12 weeks with administration of 3 doses of benralizumab (anti-IL-5 receptor α antibody [n = 5]) or placebo (n = 4). Single-cell suspensions obtained by gastric biopsy were stimulated with phorbol 12,13-dibutyrate and ionomycin in the presence of brefeldin A and monensin. Harvested cells were fixed, stained, and analyzed by flow cytometry to examine T-cell populations and associated cytokines.

RESULTS

Following benralizumab treatment but not placebo, blood and gastric eosinophil levels decreased 16-fold and 10-fold, respectively. Whereas histologic score and features were significantly decreased, no change was observed in endoscopic score and features. Following complete eosinophil depletion with benralizumab, gastric TH2 cell levels were 3-fold higher than the levels in the patients with EoG who were given placebo; and the levels of associated type 2 cytokine production of IL-4, IL-5, and IL-13 in the benralizumab-treated patients were, respectively, 4-, 5.5-, and 2.5-fold, higher than those in the placebo-treated patients.

CONCLUSION

We have identified a putative positive feedback loop whereby eosinophil depletion results in a paradoxic increase in levels of TH2 cells and derived cytokines; this finding suggests an explanation for the limited success of eosinophil depletion as monotherapy in eosinophil-associated gastrointestinal disorders.

Natural Histories and Disease Complications in a Cohort of 151 Children With Gastric or Duodenal Eosinophilia

INTRODUCTION

Eosinophilic gastritis (EoG) and duodenitis (EoD) are rare conditions that are poorly understood. Our aim was to describe the natural history of children with varying degrees of gastric or duodenal eosinophilia with respect to disease complications and histologic and endoscopic longitudinal trajectories.

METHODS

The electronic medical record at a tertiary children's hospital was queried to identify patients with EoG, EoD, or EoG + EoD who were cared for between January 2010 and 2022. Multiple logistic regression was performed to explore associations between baseline features and persistence/recurrence of eosinophilia or complications remote from diagnosis.

RESULTS

We identified 151 patients: 92 with EoG, 24 with EoD, 12 with EoG + EoD, and 23 with tissue eosinophilia but did not meet histologic criteria for EoG or EoD (low grade). The average age at diagnosis was 10.6 years, and average follow-up was 5.8 years. Twenty-five percent of patients with EoG or EoD had persistence/recurrence of eosinophilia; this was associated with increases in the EoG Endoscopic Reference Score (adjusted odds ratio [aOR] 1.34, confidence interval [CI] 1.03-1.74) on diagnostic endoscopy. Eighteen percent suffered from disease complications, and development of late complications was associated with presenting with a complication (aOR 9.63, CI 1.09-85.20), severity of duodenal endoscopic abnormalities (aOR 8.74, CI 1.67-45.60), and increases in the EoG Endoscopic Reference Score (aOR 1.70, CI 1.11-2.63).

DISCUSSION

Patients with gastric and duodenal eosinophilia should be followed closely to monitor for recurrence and complications, especially those presenting with endoscopic abnormalities or complications.

Histopathology of Eosinophilic Gastrointestinal Diseases Beyond Eosinophilic Esophagitis

Eosinophilic gastrointestinal diseases (EGID), such as eosinophilic gastritis (EoG), eosinophilic enteritis, and eosinophilic colitis (EoC), are chronic inflammatory conditions characterized by persistent gastrointestinal symptoms and elevated levels of activated eosinophils in the gastrointestinal tract. EoG and eosinophilic duodenitis (EoD) are strongly associated with food allergen triggers and TH2 inflammation, whereas EoC shows minimal transcriptomic overlap with other EGIDs. The level of expression of certain genes associated with TH2 immune response is associated with certain histopathologic findings of EoG, EoD, and EoC. Current immune therapy for EoG depletes tissue eosinophilia with persistence of other histopathologic features of disease.

Machine learning-based identification and characterization of mast cells in eosinophilic esophagitis

BACKGROUND

Eosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.

OBJECTIVES

Using machine learning, we localized and characterized esophageal mast cells (MCs) to decipher their potential role in disease pathology.

METHODS

Esophageal biopsy samples (EoE, control) were stained for MCs by anti-tryptase and imaged using immunofluorescence; high-resolution whole tissue images were digitally assembled. Machine learning software was trained to identify, enumerate, and characterize MCs, designated Mast Cell-Artificial Intelligence (MC-AI).

RESULTS

MC-AI enumerated cell counts with high accuracy. During active EoE, epithelial MCs increased and lamina propria (LP) MCs decreased. In controls and EoE remission patients, papillae had the highest MC density and negatively correlated with epithelial MC density. MC density in the epithelium and papillae correlated with the degree of epithelial eosinophilic inflammation, basal zone hyperplasia, and LP fibrosis. MC-AI detected greater MC degranulation in the epithelium, papillae, and LP in patients with EoE compared with control individuals. MCs were localized further from the basement membrane in active EoE than EoE remission and control individuals but were closer than eosinophils to the basement membrane in active EoE.

CONCLUSIONS

Using MC-AI, we identified a distinct population of homeostatic esophageal papillae MCs; during active EoE, this population decreases, undergoes degranulation, negatively correlates with epithelial MC levels, and significantly correlates with distinct histologic features. Overall, MC-AI provides a means to understand the potential involvement of MCs in EoE and other disorders.

Pathophysiology of Non-Esophageal Eosinophilic Gastrointestinal Disorders

Eosinophilic gastrointestinal disorder (EGID) is an umbrella term encompassing a group of chronic, immune-mediated disorders characterized by eosinophil-rich inflammation affecting one or more segments of the gastrointestinal tract. A recent consensus in nomenclature and emerging data made possible through multi-center consortia are beginning to unravel the molecular and cellular underpinnings of EGIDs below the esophagus. These emerging findings are revealing both overarching commonalities related to a food allergen-driven, chronic, Th2-mediated immune response as well as location-specific nuances in the pathophysiology of the collective EGIDs. Altogether, these advances offer promise for improved diagnoses and more efficacious interventional strategies.

Machine Learning Based Identification and Characterization of Mast cells in Eosinophilic Esophagitis

Background

Eosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.

Objective

Using machine learning, we localized and characterized esophageal mast cells to decipher their potential role in disease pathology.

Methods

Esophageal biopsy samples (EoE, control) were stained for mast cells by anti-tryptase and imaged using immunofluorescence; high-resolution whole tissue images were digitally assembled. Machine learning software was trained to identify, enumerate, and characterize mast cells, designated Mast Cell-Artificial Intelligence (MC-AI).

Results

MC-AI enumerated cell counts with high accuracy. During active EoE, epithelial mast cells increased and lamina propria (LP) mast cells decreased. In controls and EoE remission patients, papillae had the highest mast cell density and negatively correlated with epithelial mast cell density. Mast cell density in the epithelium and papillae correlated with the degree of epithelial eosinophilic inflammation, basal zone hyperplasia, and LP fibrosis. MC-AI detected greater mast cell degranulation in the epithelium, papillae, and LP in EoE patients compared with control individuals. Mast cells were localized further from the basement membrane in active EoE than EoE remission and controls individuals but were closer than eosinophils to the basement membrane in active EoE.

Conclusion

Using MC-AI, we identified a distinct population of homeostatic esophageal papillae mast cells; during active EoE, this population decreases, undergoes degranulation, negatively correlates with epithelial mast cell levels, and significantly correlates with distinct histologic features. Overall, MC-AI provides a means to understand the potential involvement of mast cells in EoE and other disorders.

Clinical Implication

We have developed a methodology for identifying, enumerating, and characterizing mast cells using artificial intelligence; this has been applied to decipher eosinophilic esophagitis and provides a platform approach for other diseases.

Capsule Summary

A machine learning protocol for identifying mast cells, designated Mast Cell-Artificial Intelligence, readily identified spatially distinct and dynamic populations of mast cells in EoE, providing a platform to better understand this cell type in EoE and other diseases.

Benralizumab for eosinophilic gastritis: a single-site, randomised, double-blind, placebo-controlled, phase 2 trial

BACKGROUND

In eosinophilic gastrointestinal diseases, the role of eosinophils in disease pathogenesis and the effect of eosinophil depletion on patient outcomes are unclear. Benralizumab, an eosinophil-depleting monoclonal antibody that targets the interleukin-5 receptor α, might eliminate gastric tissue eosinophils and improve outcomes in eosinophilic gastritis. We aimed to assess the efficacy and safety of benralizumab in patients with eosinophilic gastritis.

METHODS

We conducted a single-site, randomised, double-blind, placebo-controlled, phase 2 trial at Cincinnati Children's Hospital Medical Center (Cincinnati, OH, USA). Individuals aged 12-60 years with symptomatic, histologically active eosinophilic gastritis (peak gastric eosinophil count ≥30 eosinophils per high-power field [eos/hpf] in at least five hpfs) and blood eosinophilia (>500 eosinophils per μL [eos/μL]) were randomly assigned (1:1, block size of four) to benralizumab 30 mg or placebo, stratified by the use of glucocorticoids for gastric disease. Investigators, study staff, and study participants were masked to treatment assignment; statisticians were unmasked when analysing data. Treatments were administered subcutaneously once every 4 weeks for a 12-week double-blind period (three total injections). The primary endpoint was the proportion of patients who achieved histological remission (peak gastric eosinophil count <30 eos/hpf) at week 12. Key secondary endpoints were the changes from baseline to week 12 in peak gastric eosinophil count, blood eosinophil count, eosinophilic gastritis histology (total, inflammatory, and structural feature scores), Eosinophilic Gastritis Endoscopic Reference System (EG-REFS) score, and patient-reported outcome symptom measures (Severity of Dyspepsia Assessment [SODA] and Patient-Reported Outcome Measurement Information System [PROMIS] short-form questionnaire). After the 12-week double-blind period, patients were eligible for entry into two open-label extension (OLE) periods up to week 88, in which all patients received benralizumab. Efficacy was analysed in the intention-to-treat (ITT) population and safety was assessed in all patients who received at least one dose of study drug. The trial was registered on ClinicalTrials.gov, NCT03473977, and is completed.

FINDINGS

Between April 23, 2018, and Jan 13, 2020, 34 patients were screened, and 26 were subsequently randomly assigned to benralizumab (n=13) or placebo (n=13) and included in the ITT and safety populations (mean age 19·5 years [SD 7·3]; 19 [73%] male patients and seven [27%] female patients). At week 12, ten (77% [95% CI 50 to 92]) of 13 patients who received benralizumab and one (8% [1 to 33]) of 13 who received placebo achieved histological remission (difference 69 percentage points [95% CI 32 to 85]; p=0·0010). Changes from baseline to week 12 were significantly greater in the benralizumab group versus the placebo group for peak gastric eosinophil counts (mean -137 eos/hpf [95% CI -186 to -88] vs -38 eos/hpf [-94 to 18]; p=0·0080), eosinophilic gastritis histology total score (mean -0·31 [-0·42 to -0·20] vs -0·02 [-0·16 to 0·12]; p=0·0016), histology inflammatory score (mean -0·46 [-0·60 to -0·31] vs -0·04 [-0·22 to 0·13]; p=0·0006), and blood eosinophil counts (median -1060 eos/μL [IQR -1740 to -830] vs -160 eos/μL [-710 to 120]; p=0·0044). Changes were not significantly different between the groups for eosinophilic gastritis histology structural score (mean -0·07 [95% CI -0·19 to 0·05] vs 0·03 [-0·09 to 0·15]; p=0·23), EG-REFS score (mean -1·0 [-2·3 to 0·3] vs -0·5 [-2·0 to 1·0]; p=0·62), or in patient-reported outcomes (SODA and PROMIS). During the double-blind period, treatment-emergent adverse events occurred in 11 (85%) of 13 patients in the benralizumab group and six (46%) of 13 in the placebo group; the most common treatment-emergent adverse events were headache (six [46%] vs two [15%] patients), nausea (three [23%] vs two [15%]), and vomiting (two [15%] vs three [23%]). There were no treatment-related deaths. Two patients had serious adverse events (dizziness and rhabdomyolysis in one patient; aspiration in one patient) during the OLE periods, which were considered unrelated to study treatment.

INTERPRETATION

Benralizumab treatment induced histological remission, as defined by absence of tissue eosinophilia, in most patients with eosinophilic gastritis. However, the persistence of histological, endoscopic, and other features of the disease suggest a co-existing, eosinophil-independent pathogenic mechanism and the need for broader targeting of type 2 immunity.

FUNDING

AstraZeneca and the Division of Intramural Research (National Institute of Allergy and Infectious Diseases, US National Institutes of Health).