Single-cell RNA-sequencing of human eosinophils in allergic inflammation in the esophagus.

BACKGROUND: Eosinophils are elusive cells involved in allergic inflammation. Single-cell RNA-sequencing (scRNA-seq) is an emerging approach to deeply characterize cellular properties, heterogeneity, and functionality. OBJECTIVES: We sought to comprehensively characterize the transcriptome and biological functions of human eosinophils at a site of severe allergic inflammation in the esophagus (ie, eosinophilic esophagitis [EoE]). METHODS: We employed a gravity-based scRNA-seq methodology to sequence blood eosinophils from patients with EoE and control individuals compared to a reanalyzed public scRNA-seq dataset of human esophageal eosinophils of EoE patients. We used flow cytometry, immunostaining, and a stimulation assay to verify mRNA findings. RESULTS: In total, scRNA-seq was obtained from 586 eosinophils (188 from blood [n = 6 individuals] and 398 from esophagus [n = 6 individuals]). The esophageal eosinophils were composed of a population of activated eosinophils (enriched in 659 genes compared with peripheral blood-associated eosinophils) and a small population of eosinophils resembling peripheral blood eosinophils (enriched in 62 genes compared with esophageal eosinophils). Esophageal eosinophils expressed genes involved in sensing and responding to diverse stimuli, most notably IFN-γ, IL-10, histamine and leukotrienes, and succinate. Esophageal eosinophils were most distinguished from other esophageal populations by gene expression of the receptors CCR3, HRH4, SUCNR1, and VSTM1; transcription factors CEBPE, OLIG1, and OLIG2; protease PRSS33; and the hallmark eosinophil gene CLC. A web of bidirectional eosinophil interactions with other esophageal populations was derived. Comparing esophageal eosinophils and mast cells revealed that esophageal eosinophils expressed genes involved in DNAX-activation protein-12 (also known as TYROBP) interactions, IgG receptor-triggered events, immunoregulation, and IL-10 signaling. CONCLUSIONS: In EoE, esophageal eosinophils exist as 2 populations, a minority population resembling blood eosinophils and the other population characterized by high de novo transcription of diverse sensing receptors and inflammatory mediators readying them to potentially intersect with diverse cell types.

Eosinophil Depletion with Benralizumab for Eosinophilic Esophagitis.

BACKGROUND: Benralizumab is an eosinophil-depleting anti-interleukin-5 receptor α monoclonal antibody. The efficacy and safety of benralizumab in patients with eosinophilic esophagitis are unclear. METHODS: In a phase 3, multicenter, double-blind, randomized, placebo-controlled trial, we assigned patients 12 to 65 years of age with symptomatic and histologically active eosinophilic esophagitis in a 1:1 ratio to receive subcutaneous benralizumab (30 mg) or placebo every 4 weeks. The two primary efficacy end points were histologic response (≤6 eosinophils per high-power field) and the change from baseline in the score on the Dysphagia Symptom Questionnaire (DSQ; range, 0 to 84, with higher scores indicating more frequent or severe dysphagia) at week 24. RESULTS: A total of 211 patients underwent randomization: 104 were assigned to receive benralizumab, and 107 were assigned to receive placebo. At week 24, more patients had a histologic response with benralizumab than with placebo (87.4% vs. 6.5%; difference, 80.8 percentage points; 95% confidence interval [CI], 72.9 to 88.8; P<0.001). However, the change from baseline in the DSQ score did not differ significantly between the two groups (difference in least-squares means, 3.0 points; 95% CI, -1.4 to 7.4; P = 0.18). There was no substantial between-group difference in the change from baseline in the Eosinophilic Esophagitis Endoscopic Reference Score, which reflects endoscopic abnormalities. Adverse events were reported in 64.1% of the patients in the benralizumab group and in 61.7% of those in the placebo group. No patients discontinued the trial because of adverse events. CONCLUSIONS: In this trial involving patients 12 to 65 years of age with eosinophilic esophagitis, a histologic response (≤6 eosinophils per high-power field) occurred in significantly more patients in the benralizumab group than in the placebo group. However, treatment with benralizumab did not result in fewer or less severe dysphagia symptoms than placebo. (Funded by AstraZeneca; MESSINA ClinicalTrials.gov number, NCT04543409.).

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.

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.

The minichromosome maintenance complex drives esophageal basal zone hyperplasia.

Eosinophilic esophagitis (EoE) is a chronic gastrointestinal disorder characterized by food antigen-driven eosinophilic inflammation and hyperproliferation of esophageal mucosa. By utilizing a large-scale, proteomic screen of esophageal biopsies, we aimed to uncover molecular drivers of the disease. Proteomic analysis by liquid chromatography-tandem mass spectrometry identified 402 differentially expressed proteins (DEPs) that correlated with the EoE transcriptome. Immune cell-related proteins were among the most highly upregulated DEPs in EoE compared with controls, whereas proteins linked to epithelial differentiation were primarily downregulated. Notably, in the inflamed esophageal tissue, all 6 subunits of the minichromosome maintenance (MCM) complex, a DNA helicase essential for genomic DNA replication, were significantly upregulated at the gene and protein levels. Furthermore, treating esophageal epithelial cells with a known inhibitor of the MCM complex (ciprofloxacin) blocked esophageal epithelial proliferation. In a murine model of EoE driven by overexpression of IL-13, ciprofloxacin treatment decreased basal zone thickness and reduced dilated intercellular spaces by blocking the transition of epithelial cells through the S-phase of the cell cycle. Collectively, a broad-spectrum proteomic screen has identified the involvement of the MCM complex in EoE and has highlighted MCM inhibitors as potential therapeutic agents for the disease.

One-food versus six-food elimination diet therapy for the treatment of eosinophilic oesophagitis: a multicentre, randomised, open-label trial.

BACKGROUND: Empirical elimination diets are effective for achieving histological remission in eosinophilic oesophagitis, but randomised trials comparing diet therapies are lacking. We aimed to compare a six-food elimination diet (6FED) with a one-food elimination diet (1FED) for the treatment of adults with eosinophilic oesophagitis. METHODS: We conducted a multicentre, randomised, open-label trial across ten sites of the Consortium of Eosinophilic Gastrointestinal Disease Researchers in the USA. Adults aged 18-60 years with active, symptomatic eosinophilic oesophagitis were centrally randomly allocated (1:1; block size of four) to 1FED (animal milk) or 6FED (animal milk, wheat, egg, soy, fish and shellfish, and peanut and tree nuts) for 6 weeks. Randomisation was stratified by age, enrolling site, and gender. The primary endpoint was the proportion of patients with histological remission (peak oesophageal count <15 eosinophils per high-power field [eos/hpf]). Key secondary endpoints were the proportions with complete histological remission (peak count ≤1 eos/hpf) and partial remission (peak counts ≤10 and ≤6 eos/hpf) and changes from baseline in peak eosinophil count and scores on the Eosinophilic Esophagitis Histology Scoring System (EoEHSS), Eosinophilic Esophagitis Endoscopic Reference Score (EREFS), Eosinophilic Esophagitis Activity Index (EEsAI), and quality of life (Adult Eosinophilic Esophagitis Quality-of-Life and Patient Reported Outcome Measurement Information System Global Health questionnaires). Individuals without histological response to 1FED could proceed to 6FED, and those without histological response to 6FED could proceed to swallowed topical fluticasone propionate 880 µg twice per day (with unrestricted diet), for 6 weeks. Histological remission after switching therapy was assessed as a secondary endpoint. Efficacy and safety analyses were done in the intention-to-treat (ITT) population. This trial is registered on ClinicalTrials.gov, NCT02778867, and is completed. FINDINGS: Between May 23, 2016, and March 6, 2019, 129 patients (70 [54%] men and 59 [46%] women; mean age 37·0 years [SD 10·3]) were enrolled, randomly assigned to 1FED (n=67) or 6FED (n=62), and included in the ITT population. At 6 weeks, 25 (40%) of 62 patients in the 6FED group had histological remission compared with 23 (34%) of 67 in the 1FED group (difference 6% [95% CI -11 to 23]; p=0·58). We found no significant difference between the groups at stricter thresholds for partial remission (≤10 eos/hpf, difference 7% [-9 to 24], p=0·46; ≤6 eos/hpf, 14% [-0 to 29], p=0·069); the proportion with complete remission was significantly higher in the 6FED group than in the 1FED group (difference 13% [2 to 25]; p=0·031). Peak eosinophil counts decreased in both groups (geometric mean ratio 0·72 [0·43 to 1·20]; p=0·21). For 6FED versus 1FED, mean changes from baseline in EoEHSS (-0·23 vs -0·15; difference -0·08 [-0·21 to 0·05]; p=0·23), EREFS (-1·0 vs -0·6; difference -0·4 [-1·1 to 0·3]; p=0·28), and EEsAI (-8·2 vs -3·0; difference -5·2 [-11·2 to 0·8]; p=0·091) were not significantly different. Changes in quality-of-life scores were small and similar between the groups. No adverse event was observed in more than 5% of patients in either diet group. For patients without histological response to 1FED who proceeded to 6FED, nine (43%) of 21 reached histological remission; for patients without histological response to 6FED who proceeded to fluticasone propionate, nine (82%) of 11 reached histological remission. INTERPRETATION: Histological remission rates and improvements in histological and endoscopic features were similar after 1FED and 6FED in adults with eosinophilic oesophagitis. 6FED had efficacy in just less than half of 1FED non-responders and steroids had efficacy in most 6FED non-responders. Our findings indicate that eliminating animal milk alone is an acceptable initial dietary therapy for eosinophilic oesophagitis. FUNDING: US National Institutes of Health.

Local type 2 immunity in eosinophilic gastritis.

BACKGROUND: Eosinophilic gastritis (EoG) associates with type 2 immunity. However, the type 2 cytokine cellular source, gastric T-cell composition, and gastric T-cell relationship (or relationships) with disease pathology remain understudied. OBJECTIVE: We defined gastric T-cell populations and their association with histologic and endoscopic EoG pathology. METHODS: Gastric biopsy samples (n = 6 EoG, n = 7 control) were subjected to histologic, endoscopic, and flow cytometry analyses. In a complementary cohort (n = 83 EoG), IL4, IL5, and IL13 mRNA levels were correlated with EoG pathologic parameters. RESULTS: Gastric biopsy samples contained CD3+ T cells that were mainly CD8+; the CD8/CD4 ratio was comparable in EoG and control biopsy samples (5.7 ± 3.0 and 4.3 ± 0.6, respectively; P = .28). Gastric regulatory T (CD3+CD4+FOXP3+) and TH2 (CD3+CD4+GATA3+) cell levels were increased in EoG versus controls (2-fold, P < .05 and 10-fold, P < .001, respectively) and correlated with gastric eosinophil levels (r = 0.63, P < .05 and r = 0.85, P < .001, respectively), endoscopic pathology (r = 0.56, P < .01; r = 0.84, P < .001, respectively), and histopathology (r = 0.72, P < .01; r = 0.82, P < .01, respectively). Cytokine-positive, most notably IL-4+, TH2 cell levels strongly correlated with histologic and endoscopic scores (r = 0.82, P < .0001 and r = 0.78, P < .0001, respectively). In an independent EoG cohort (n = 83), bulk gastric IL4, IL5, and IL13 mRNA levels correlated with histologic score (r = 0.22, P < .005; r = 0.54, P < .0001; and r = 0.36, P < .0001, respectively) and endoscopic score (r = 0.27, P < .001; r = 0.40, P < .0001; and r = 0.35, P < .0001, respectively). CONCLUSIONS: EoG is a TH2 cell-associated disease featuring increased gastric type 2 cytokine-producing CD3+CD4+GATA3+TH2 cells that strongly correlate with disease pathologies.

Molecular analysis of duodenal eosinophilia.

BACKGROUND: Eosinophilic duodenitis (EoD), characterized by nonspecific gastrointestinal symptoms and increased numbers of duodenal eosinophils, may be in the eosinophilic gastrointestinal disease spectrum. However, diagnostic thresholds and pathogenic processes of duodenal tissue eosinophilia are inadequately characterized. OBJECTIVE: We aimed to define an EoD transcriptome and pathologic pathways. METHODS: RNA sequencing and histologic features of human duodenal biopsy samples were analyzed as a function of duodenal eosinophils levels. For analyses, we defined EoD as more than 52 peak eosinophils/hpf (n = 8), duodenal eosinophilia as 30 to 52 eosinophils/hpf (n = 11), and normal controls as fewer than 30 eosinophils/hpf (n = 8). Associations between gene expression and histologic features were analyzed with Spearman correlation. RESULTS: We identified 382 differentially expressed genes (EoD transcriptome) between EoD and normal controls (>2-fold change [adjusted P < .05]). The EoD transcriptome distinguished EoD from controls (duodenal eosinophilia and normal controls). The duodenal eosinophil count was correlated with a distinct EoD transcriptome when 50 to 60 peak eosinophils/hpf were present. The EoD transcriptome was enriched in genes involved in IL-4/IL-13 signaling, mast cells, and myeloid progenitor cells. Among duodenal histologic features, lamina propria eosinophil sheets was the most associated with transcriptomic changes (r = 0.66; P < .01). EoD gene signatures were shared with eosinophilic esophagitis and eosinophilic gastritis but not with eosinophilic colitis or celiac disease. CONCLUSION: We have identified an EoD transcriptomic signature that emerges at 50 to 60 peak eosinophils/hpf and established EoD as part of a spectrum of upper eosinophilic gastrointestinal disorder associated with type 2 immunity and distinct from eosinophilic colitis and celiac disease. These findings provide a basis for improving diagnosis and treatment.

Vitamin D receptor and STAT6 interactome governs oesophageal epithelial barrier responses to IL-13 signalling.

OBJECTIVE: The contribution of vitamin D (VD) deficiency to the pathogenesis of allergic diseases remains elusive. We aimed to define the impact of VD on oesophageal allergic inflammation. DESIGN: We assessed the genomic distribution and function of VD receptor (VDR) and STAT6 using histology, molecular imaging, motif discovery and metagenomic analysis. We examined the role of VD supplementation in oesophageal epithelial cells, in a preclinical model of IL-13-induced oesophageal allergic inflammation and in human subjects with eosinophilic oesophagitis (EoE). RESULTS: VDR response elements were enriched in oesophageal epithelium, suggesting enhanced VDR binding to functional gene enhancer and promoter regions. Metagenomic analysis showed that VD supplementation reversed dysregulation of up to 70% of the transcriptome and epigenetic modifications (H3K27Ac) induced by IL-13 in VD-deficient cells, including genes encoding the transcription factors HIF1A and SMAD3, endopeptidases (SERPINB3) and epithelial-mesenchymal transition mediators (TGFBR1, TIAM1, SRC, ROBO1, CDH1). Molecular imaging and chromatin immunoprecipitation showed VDR and STAT6 colocalisation within the regulatory regions of the affected genes, suggesting that VDR and STAT6 interactome governs epithelial tissue responses to IL-13 signalling. Indeed, VD supplementation reversed IL-13-induced epithelial hyperproliferation, reduced dilated intercellular spaces and barrier permeability, and improved differentiation marker expression (filaggrin, involucrin). In a preclinical model of IL-13-mediated oesophageal allergic inflammation and in human EoE, VD levels inversely associated with severity of oesophageal eosinophilia and epithelial histopathology. CONCLUSIONS: Collectively, these findings identify VD as a natural IL-13 antagonist with capacity to regulate the oesophageal epithelial barrier functions, providing a novel therapeutic entry point for type 2 immunity-related diseases.

Harnessing artificial intelligence to infer novel spatial biomarkers for the diagnosis of eosinophilic esophagitis.

Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory condition of the esophagus associated with elevated esophageal eosinophils. Second only to gastroesophageal reflux disease, EoE is one of the leading causes of chronic refractory dysphagia in adults and children. EoE is a clinicopathologic disorder and the histological portion of the diagnosis requires enumerating the density of esophageal eosinophils in esophageal biopsies, and evaluating additional features such as basal zone hyperplasia is helpful. However, this task requires time-consuming, somewhat subjective manual analysis, thus reducing the ability to process the complex tissue structure and infer its relationship with the patient's clinical status. Previous artificial intelligence (AI) approaches that aimed to improve histology-based diagnosis focused on recapitulating identification and quantification of the area of maximal eosinophil density, the gold standard manual metric for determining EoE disease activity. However, this metric does not account for the distribution of eosinophils or other histological features, over the whole slide image. Here, we developed an artificial intelligence platform that infers local and spatial biomarkers based on semantic segmentation of intact eosinophils and basal zone distributions. Besides the maximal density of eosinophils [referred to as Peak Eosinophil Count (PEC)] and a maximal basal zone fraction, we identify the value of two additional metrics that reflect the distribution of eosinophils and basal zone fractions. This approach enables a decision support system that predicts EoE activity and potentially classifies the histological severity of EoE patients. We utilized a cohort that includes 1,066 biopsy slides from 400 subjects to validate the system's performance and achieved a histological severity classification accuracy of 86.70%, sensitivity of 84.50%, and specificity of 90.09%. Our approach highlights the importance of systematically analyzing the distribution of biopsy features over the entire slide and paves the way toward a personalized decision support system that will assist not only in counting cells but can also potentially improve diagnosis and provide treatment prediction.

A Deep Multi-Label Segmentation Network For Eosinophilic Esophagitis Whole Slide Biopsy Diagnostics.

Eosinophilic esophagitis (EoE) is an allergic inflammatory condition of the esophagus associated with elevated numbers of eosinophils. Disease diagnosis and monitoring require determining the concentration of eosinophils in esophageal biopsies, a time-consuming, tedious and somewhat subjective task currently performed by pathologists. Here, we developed a machine learning pipeline to identify, quantitate and diagnose EoE patients' at the whole slide image level. We propose a platform that combines multi-label segmentation deep network decision support system with dynamics convolution that is able to process whole biopsy slide. Our network is able to segment both intact and not-intact eosinophils with a mean intersection over union (mIoU) of 0.93. This segmentation enables the local quantification of intact eosinophils with a mean absolute error of 0.611 eosinophils. We examined a cohort of 1066 whole slide images from 400 patients derived from multiple institutions. Using this set, our model achieved a global accuracy of 94.75%, sensitivity of 94.13%, and specificity of 95.25% in reporting EoE disease activity. Our work provides state-of-the-art performances on the largest EoE cohort to date, and successfully addresses two of the main challenges in EoE diagnostics and digital pathology, the need to detect several types of small features simultaneously, and the ability to analyze whole slides efficiently. Our results pave the way for an automated diagnosis of EoE and can be utilized for other conditions with similar challenges.

Laundry detergent promotes allergic skin inflammation and esophageal eosinophilia in mice.

The prevalence of allergic diseases is on the rise, yet the environmental factors that contribute to this increase are still being elucidated. Laundry detergent (LD) that contains cytotoxic ingredients including microbial enzymes continuously comes into contact with the skin starting in infancy. An impaired skin barrier has been suggested as a route of allergic sensitization. We hypothesized that exposure of skin to LD damages the skin barrier resulting in systemic sensitization to allergens that enter through the impaired skin barrier. Mouse skin samples exposed in vitro to microbial proteases or LD exhibited physical damage, which was more pronounced in neonatal skin as compared to adult skin. Exposure of the skin to microbial proteases in vitro resulted in an increase in the levels of interleukin (IL)-33 and thymic stromal lymphopoietin (TSLP). BALB/c wild type mice epicutaneously exposed to LD and ovalbumin (OVA) showed an increase in levels of transepidermal water loss, serum OVA-specific immunoglobulin (Ig) G1 and IgE antibodies, and a local increase of Il33, Tslp, Il4 and Il13 compared with LD or OVA alone. Following intranasal challenge with OVA, mice epicutaneously exposed to LD showed an increase in allergen-induced esophageal eosinophilia compared with LD or OVA alone. Collectively, these results suggest that LD may be an important factor that impairs the skin barrier and leads to allergen sensitization in early life, and therefore may have a role in the increase in allergic disease.

Single-cell RNA-Seq of human esophageal epithelium in homeostasis and allergic inflammation.

Inflammation of the esophageal epithelium is a hallmark of eosinophilic esophagitis (EoE), an emerging chronic allergic disease. Herein, we probed human esophageal epithelial cells at single-cell resolution during homeostasis and EoE. During allergic inflammation, the epithelial differentiation program was blocked, leading to loss of KRT6hi differentiated populations and expansion of TOP2hi proliferating, DSPhi transitioning, and SERPINB3hi transitioning populations; however, there was stability of the stem cell-enriched PDPNhi basal epithelial compartment. This differentiation program blockade was associated with dysregulation of transcription factors, including nuclear receptor signalers, in the most differentiated epithelial cells and altered NOTCH-related cell-to-cell communication. Each epithelial population expressed genes with allergic disease risk variants, supporting their functional interplay. The esophageal epithelium differed notably between EoE in histologic remission and controls, indicating that remission is a transitory state poised to relapse. Collectively, our data uncover the dynamic nature of the inflamed human esophageal epithelium and provide a framework to better understand esophageal health and disease.

Single-cell RNA sequencing of mast cells in eosinophilic esophagitis reveals heterogeneity, local proliferation, and activation that persists in remission.

BACKGROUND: Mast cells (MCs) are pleiotropic cells that accumulate in the esophagus of patients with eosinophilic esophagitis (EoE) and are thought to contribute to disease pathogenesis, yet their properties and functions in this organ are largely unknown. OBJECTIVES: This study aimed to perform a comprehensive molecular and spatial characterization of esophageal MCs in EoE. METHODS: Esophageal biopsies obtained from patients with active EoE, patients with EoE in histologic remission, and individuals with histologically normal esophageal biopsies and no history of esophageal disease (ie, control individuals) were subject to single-cell RNA sequencing, flow cytometry, and immunofluorescence analyses. RESULTS: This study probed 39,562 single esophageal cells by single-cell RNA sequencing; approximately 5% of these cells were MCs. Dynamic MC expansion was identified across disease states. During homeostasis, TPSAB1highAREGhigh resident MCs were mainly detected in the lamina propria and exhibited a quiescent phenotype. In patients with active EoE, resident MCs assumed an activated phenotype, and 2 additional proinflammatory MC populations emerged in the intraepithelial compartment, each linked to a proliferating MKI67high cluster. One proinflammatory activated MC population, marked as KIThighIL1RL1highFCER1Alow, was not detected in disease remission (termed "transient MC"), whereas the other population, marked as CMA1highCTSGhigh, was detected in disease remission where it maintained an activated state (termed "persistent MC"). MCs were prominent producers of esophageal IL-13 mRNA and protein, a key therapeutic target in EoE. CONCLUSIONS: Esophageal MCs comprise heterogeneous populations with transcriptional signatures associated with distinct spatial compartmentalization and EoE disease status. In active EoE, they assume a proinflammatory state and locally proliferate, and they remain activated and poised to reinitiate inflammation even during disease remission.

Evaluating Eosinophilic Colitis as a Unique Disease Using Colonic Molecular Profiles: A Multi-Site Study.

BACKGROUND & AIMS: Colonic eosinophilia, an enigmatic finding often referred to as eosinophilic colitis (EoC), is a poorly understood condition. Whether EoC is a distinct disease or a colonic manifestation of eosinophilic gastrointestinal diseases (EGIDs) or inflammatory bowel disease (IBD) is undetermined. METHODS: Subjects with EoC (n = 27) and controls (normal [NL, n = 20], Crohn's disease [CD, n = 14]) were enrolled across sites associated with the Consortium of Eosinophilic Gastrointestinal Disease Researchers. EoC was diagnosed as colonic eosinophilia (ascending ≥100, descending ≥85, sigmoid ≥65 eosinophils/high-power field) with related symptoms. Colon biopsies were subjected to RNA sequencing. Associations between gene expression and histologic features were analyzed with Spearman correlation; operational pathways and cellular constituents were computationally derived. RESULTS: We identified 987 differentially expressed genes (EoC transcriptome) between EoC and NL (>1.5-fold change, P < .05). Colonic eosinophil count correlated with 31% of EoC transcriptome, most notably with CCL11 and CLC (r = 0.78 and 0.77, P < .0001). Among EoC and other EGIDs, there was minimal transcriptomic overlap and minimal evidence of a strong allergic type 2 immune response in EoC compared with other EGIDs. Decreased cell cycle and increased apoptosis in EoC compared with NL were identified by functional enrichment analysis and immunostaining using Ki-67 and cleaved caspase-3. Pericryptal circumferential eosinophil collars were associated with the EoC transcriptome (P < .001). EoC transcriptome-based scores were reversible with disease remission and differentiated EoC from IBD, even after controlling for colonic eosinophil levels (P < .0001). CONCLUSIONS: We established EoC transcriptomic profiles, identified mechanistic pathways, and integrated findings with parallel IBD and EGID data. These findings establish EoC as a distinct disease compared with other EGIDs and IBD, thereby providing a basis for improving diagnosis and treatment.

Loss of Endothelial TSPAN12 Promotes Fibrostenotic Eosinophilic Esophagitis via Endothelial Cell-Fibroblast Crosstalk.

BACKGROUND & AIMS: Eosinophilic esophagitis (EoE) can progress to fibrostenosis by unclear mechanisms. Herein, we investigated gene dysregulation in fibrostenotic EoE, its association with clinical parameters and specific pathways, and the functional consequences. METHODS: Esophageal biopsies from subjects with EoE were collected across 11 Consortium of Eosinophilic Gastrointestinal Disease Researchers sites (n = 311) and 2 independent replication cohorts (n = 83). Inclusion criteria for fibrostenotic EoE were endoscopic rings, stricture, and/or a history of dilation. Endoscopic, histologic, and molecular features were assessed by the EoE Endoscopic Reference Score, EoE Histology Scoring System, EoE Diagnostic Panel, and RNA sequencing. Esophageal endothelial TSPAN12 expression and functional effects on barrier integrity and gene expression were analyzed in vitro. RESULTS: TSPAN12 was the gene most correlated with fibrostenosis (r = -0.40, P < .001). TSPAN12 was lower in fibrostenotic EoE and correlated with EoE Endoscopic Reference Score, EoE Diagnostic Panel, and EoE Histology Scoring System (r = 0.34-0.47, P < .001). Lower TSPAN12 associated with smaller esophageal diameter (r = 0.44, P = .03), increased lamina propria fibrosis (r = -0.41, P < .001), and genes enriched in cell cycle-related pathways. Interleukin (IL)-13 reduced TSPAN12 expression in endothelial cells. Conversely, anti-IL-13 therapy increased TSPAN12 expression. TSPAN12 gene silencing increased endothelial cell permeability and dysregulated genes associated with extracellular matrix pathways. Endothelial cell-fibroblast crosstalk induced extracellular matrix changes relevant to esophageal remodeling. CONCLUSIONS: Patients with fibrostenotic EoE express decreased levels of endothelial TSPAN12. We propose that IL-13 decreases TSPAN12, likely contributing to the chronicity of EoE by promoting tissue remodeling through fibroblast-endothelial cell crosstalk.

Remote immune processes revealed by immune-derived circulating cell-free DNA.

Blood cell counts often fail to report on immune processes occurring in remote tissues. Here, we use immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying human immune cell dynamics. We characterized cfDNA released from specific immune cell types in healthy individuals (N = 242), cross sectionally and longitudinally. Immune cfDNA levels had no individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza vaccination (N = 92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and predicted efficacy of antibody production. Patients with eosinophilic esophagitis (N = 21) and B-cell lymphoma (N = 27) showed selective elevation of eosinophil and B-cell cfDNA, respectively, which were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for monitoring immune responses to physiological and pathological processes that are not accessible using conventional methods.

Desmoplakin and periplakin genetically and functionally contribute to eosinophilic esophagitis.

Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory disease with a complex underlying genetic etiology. Herein, we conduct whole-exome sequencing of a multigeneration EoE pedigree (discovery set) and 61 additional multiplex families with EoE (replication set). A series of rare, heterozygous, missense variants are identified in the genes encoding the desmosome-associated proteins DSP and PPL in 21% of the multiplex families. Esophageal biopsies from patients with these variants retain dilated intercellular spaces and decrease DSP and PPL expression even during disease remission. These variants affect barrier integrity, cell motility and RhoGTPase activity in esophageal epithelial cells and have increased susceptibility to calpain-14-mediated degradation. An acquired loss of esophageal DSP and PPL is present in non-familial EoE. Taken together, herein, we uncover a pathogenic role for desmosomal dysfunction in EoE, providing a deeper mechanistic understanding of tissue-specific allergic responses.

Machine Learning Approach for Biopsy-Based Identification of Eosinophilic Esophagitis Reveals Importance of Global features.

GOAL: Eosinophilic esophagitis (EoE) is an allergic inflammatory condition characterized by eosinophil accumulation in the esophageal mucosa. EoE diagnosis includes a manual assessment of eosinophil levels in mucosal biopsies-a time-consuming, laborious task that is difficult to standardize. One of the main challenges in automating this process, like many other biopsy-based diagnostics, is detecting features that are small relative to the size of the biopsy. RESULTS: In this work, we utilized hematoxylin- and eosin-stained slides from esophageal biopsies from patients with active EoE and control subjects to develop a platform based on a deep convolutional neural network (DCNN) that can classify esophageal biopsies with an accuracy of 85%, sensitivity of 82.5%, and specificity of 87%. Moreover, by combining several downscaling and cropping strategies, we show that some of the features contributing to the correct classification are global rather than specific, local features. CONCLUSIONS: We report the ability of artificial intelligence to identify EoE using computer vision analysis of esophageal biopsy slides. Further, the DCNN features associated with EoE are based on not only local eosinophils but also global histologic changes. Our approach can be used for other conditions that rely on biopsy-based histologic diagnostics.