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.

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.

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.

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.

Environmental allergens trigger type 2 inflammation through ripoptosome activation.

Environmental allergens, including fungi, insects and mites, trigger type 2 immunity; however, the innate sensing mechanisms and initial signaling events remain unclear. Herein, we demonstrate that allergens trigger RIPK1-caspase 8 ripoptosome activation in epithelial cells. The active caspase 8 subsequently engages caspases 3 and 7, which directly mediate intracellular maturation and release of IL-33, a pro-atopy, innate immunity, alarmin cytokine. Mature IL-33 maintained functional interaction with the cognate ST2 receptor and elicited potent pro-atopy inflammatory activity in vitro and in vivo. Inhibiting caspase 8 pharmacologically and deleting murine Il33 and Casp8 each attenuated allergic inflammation in vivo. Clinical data substantiated ripoptosome activation and IL-33 maturation as likely contributors to human allergic inflammation. Our findings reveal an epithelial barrier, allergen-sensing mechanism that converges on the ripoptosome as an intracellular molecular signaling platform, triggering type 2 innate immune responses. These findings have significant implications for understanding and treating human allergic diseases.

Metastasis-Entrained Eosinophils Enhance Lymphocyte-Mediated Antitumor Immunity.

The recognition of the immune system as a key component of the tumor microenvironment (TME) led to promising therapeutics. Because such therapies benefit only subsets of patients, understanding the activities of immune cells in the TME is required. Eosinophils are an integral part of the TME especially in mucosal tumors. Nonetheless, their role in the TME and the environmental cues that direct their activities are largely unknown. We report that breast cancer lung metastases are characterized by resident and recruited eosinophils. Eosinophil recruitment to the metastatic sites in the lung was regulated by G protein-coupled receptor signaling but independent of CCR3. Functionally, eosinophils promoted lymphocyte-mediated antitumor immunity. Transcriptome and proteomic analyses identified the TME rather than intrinsic differences between eosinophil subsets as a key instructing factor directing antitumorigenic eosinophil activities. Specifically, TNFα/IFNγ-activated eosinophils facilitated CD4+ and CD8+ T-cell infiltration and promoted antitumor immunity. Collectively, we identify a mechanism by which the TME trains eosinophils to adopt antitumorigenic properties, which may lead to the development of eosinophil-targeted therapeutics. SIGNIFICANCE: These findings demonstrate antitumor activities of eosinophils in the metastatic tumor microenvironment, suggesting that harnessing eosinophil activity may be a viable clinical strategy in patients with cancer.

Bidirectional crosstalk between eosinophils and esophageal epithelial cells regulates inflammatory and remodeling processes.

Eosinophils accumulate adjacent to epithelial cells in the mucosa of patients with eosinophilic esophagitis (EoE), yet the bidirectional communication between these cells is not well understood. Herein, we investigated the crosstalk between human eosinophils and esophageal epithelial cells. We report that blood-derived eosinophils have prolonged survival when cocultured with epithelial cells; 96 ± 1% and 30 ± 6% viability was observed after 7 and 14 days of coculture, respectively, compared with 1 ± 0% and 0 ± 0% of monoculture. In the presence of IL-13 and epithelial cells, eosinophils had greater survival (68 ± 1%) at 14 days compared with cocultures lacking IL-13. Prolonged eosinophil viability did not require cellular contact and was observed when eosinophils were cultured in conditioned media from esophageal epithelial cells; neutralizing GM-CSF attenuated eosinophil survival. The majority of eosinophil transcripts (58%) were dysregulated in cocultured eosinophils compared with freshly isolated cells. Analysis of epithelial cell transcripts indicated that exposure to eosinophils induced differential expression of a subset of genes that were part of the EoE esophageal transcriptome. Collectively, these results uncover a network of crosstalk between eosinophils and esophageal epithelial cells involving epithelial mediated eosinophil survival and reciprocal changes in cellular transcripts, events likely to occur in EoE.

Broad transcriptional response of the human esophageal epithelium to proton pump inhibitors.

BACKGROUND: Proton pump inhibitors (PPIs) have been recognized as a primary treatment of eosinophilic esophagitis (EoE), an allergic inflammatory disease of the esophageal mucosa. The mechanisms underlying esophageal epithelial responses to PPIs remain poorly understood. OBJECTIVE: We hypothesized that PPIs can counteract IL-13-mediated esophageal epithelial responses that are germane for EoE pathogenesis. METHODS: Transcriptional responses of human esophageal cells to IL-13 and the PPIs omeprazole and esomeprazole were assessed by RT-PCR and RNA sequencing. Cytokine secretion was measured by multiplex analysis and ELISA. RESULTS: Human esophageal epithelial cells robustly responded to PPI stimulation by inducing a set of 479 core genes common between omeprazole and esomeprazole treatments. The transcriptional response to PPIs was partially mediated through the aryl hydrocarbon receptor signaling pathway, as the aryl hydrocarbon receptor antagonist GNF-351 modified approximately 200 genes, particularly those enriched in metabolic processes and regulation of cell death. PPI treatment reversed approximately 20% of the IL-13 transcriptome. Functional analysis of the PPI-responsive, upregulated genes revealed enrichment in metabolic and oxidation processes, and the unfolded protein response. In contrast, downregulated genes were overrepresented in functional terms related to cell division and cytoskeletal organization, which were also enriched for the genes in the EoE transcriptome reversed by PPIs. Furthermore, PPI treatment decreased the IL-13-induced proliferative response of esophageal epithelial cells. CONCLUSIONS: These results demonstrate broad effects of PPIs on esophageal epithelium, including their ability to curtail transcriptomic processes involved in cellular proliferation and IL-13-induced responses, and they highlight the importance of AHR signaling in mediating these responses.

Functional role of kallikrein 5 and proteinase-activated receptor 2 in eosinophilic esophagitis.

Eosinophilic esophagitis (EoE) is a chronic, food antigen-driven, inflammatory disease of the esophagus and is associated with impaired barrier function. Evidence is emerging that loss of esophageal expression of the serine peptidase inhibitor, kazal type 7 (SPINK7), is an upstream event in EoE pathogenesis. Here, we provide evidence that loss of SPINK7 mediates its pro-EoE effects via kallikrein 5 (KLK5) and its substrate, protease-activated receptor 2 (PAR2). Overexpression of KLK5 in differentiated esophageal epithelial cells recapitulated the effect of SPINK7 gene silencing, including barrier impairment and loss of desmoglein-1 expression. Conversely, KLK5 deficiency attenuated allergen-induced esophageal protease activity, modified commensal microbiome composition, and attenuated eosinophilia in a murine model of EoE. Inhibition of PAR2 blunted the cytokine production associated with loss of SPINK7 in epithelial cells and attenuated the allergen-induced esophageal eosinophilia in vivo. Clinical samples substantiated dysregulated PAR2 expression in the esophagus of patients with EoE, and delivery of the clinically approved drug α1 antitrypsin (A1AT, a protease inhibitor) inhibited experimental EoE. These findings demonstrate a role for the balance between KLK5 and protease inhibitors in the esophagus and highlight EoE as a protease-mediated disease. We suggest that antagonizing KLK5 and/or PAR2 has potential to be therapeutic for EoE.

Esophageal type 2 cytokine expression heterogeneity in eosinophilic esophagitis in a multisite cohort.

BACKGROUND: There is strong evidence for a role of type 2 cytokines in the pathogenesis of eosinophilic esophagitis (EoE); however, heterogeneity in type 2 gene expression has not been examined. OBJECTIVE: We examined type 2 immunity-associated gene expression in esophageal biopsy specimens, aiming to determine the degree of cytokine heterogeneity and its potential clinical significance. METHODS: Patients (n = 312) were recruited from 10 sites associated with the Consortium of Eosinophilic Gastrointestinal Disease Researchers. In addition to histologic and endoscopic assessment, esophageal biopsy specimens were examined for expression of 96 genes within the EoE diagnostic panel. RESULTS: Five subgroups of patients with active EoE were identified by unsupervised clustering based on expression of IL4, IL5, IL13, C-C motif chemokine ligand 26 (CCL26), thymic stromal lymphopoietin (TSLP), Charcot-Leyden crystal (CLC), C-C motif chemokine receptor 3 (CCR3), and CPA3. These groups differed in age (P < .02) and EoE diagnostic panel score (P < 1.08E-30) but not in eosinophil levels. The group V patients had the highest expression of IL5, TSLP, and CCL26 and genes associated with tissue remodeling, such as COL8A1, actin γ-2 (ACTG2), and tetraspanin 12 (TSPAN12). IL5 and IL13 were highly expressed in group IV; however, groups IV and V differed in age (34 vs 14 years [P < .05]). Groups II and III, which exhibited intermediate expression of IL5 and CPA3, were differentiated by high TSLP and IL13 in group III. CONCLUSION: We observed heterogeneous type 2 gene expression among patients with active EoE. Type 2 gene overexpression was not directly proportional to disease features; this was especially true for tissue remodeling events. These findings highlight a clinical opportunity for leveraging molecular endotypes to implement personalized medicine in EoE.

Molecular, endoscopic, histologic, and circulating biomarker-based diagnosis of eosinophilic gastritis: Multi-site study.

BACKGROUND: Eosinophilic gastritis (EG) is a clinicopathologic disorder with marked gastric eosinophilia and clinical symptoms. There is an unmet need among patients with EG for more precise diagnostic tools. OBJECTIVE: We aimed to develop tissue- and blood-based diagnostic platforms for EG. METHODS: Patients with EG and control subjects without EG were enrolled across 9 Consortium of Eosinophilic Gastrointestinal Disease Researchers-associated sites. An EG Diagnostic Panel (EGDP; gastric transcript subset) and EG blood biomarker panel (protein multiplex array) were analyzed. EGDP18 scores were derived from the expression of 18 highly dysregulated genes, and blood EG scores were derived from dysregulated cytokine/chemokine levels. RESULTS: Gastric biopsy specimens and blood samples from 185 subjects (patients with EG, n = 74; control subjects without EG, n = 111) were analyzed. The EGDP (1) identified patients with active EG (P < .0001, area under the curve ≥ 0.95), (2) effectively monitored disease activity in longitudinal samples (P = .0078), (3) highly correlated in same-patient samples (antrum vs body, r = 0.85, P < .0001), and (4) inversely correlated with gastric peak eosinophil levels (r = -0.83, P < .0001), periglandular circumferential collars (r = -0.73, P < .0001), and endoscopic nodularity (r = -0.45, P < .0001). For blood-based platforms, eotaxin-3, thymus and activation-regulated chemokine, IL-5, and thymic stromal lymphopoietin levels were significantly increased. Blood EG scores (1) distinguished patients with EG from control subjects without EG (P < .0001, area under the curve ≥ 0.91), (2) correlated with gastric eosinophil levels (plasma: r = 0.72, P = .0002; serum: r = 0.54, P = .0015), and (3) inversely correlated with EGDP18 scores (plasma: r = -0.64, P = .0015; serum: r = -0.46, P = .0084). Plasma eotaxin-3 levels strongly associated with gastric CCL26 expression (r = 0.81, P < .0001). CONCLUSION: We developed tissue- and blood-based platforms for assessment of EG and uncovered robust associations between specific gastric molecular profiles and histologic and endoscopic features, providing insight and clinical readiness tools for this emerging rare disease.

The antiprotease SPINK7 serves as an inhibitory checkpoint for esophageal epithelial inflammatory responses.

Loss of barrier integrity has an important role in eliciting type 2 immune responses, yet the molecular events that initiate and connect this with allergic inflammation remain unclear. We reveal an endogenous, homeostatic mechanism that controls barrier function and inflammatory responses in esophageal allergic inflammation. We show that a serine protease inhibitor, SPINK7 (serine peptidase inhibitor, kazal type 7), is part of the differentiation program of human esophageal epithelium and that SPINK7 depletion occurs in a human allergic, esophageal condition termed eosinophilic esophagitis. Experimental manipulation strategies reducing SPINK7 in an esophageal epithelial progenitor cell line and primary esophageal epithelial cells were sufficient to induce barrier dysfunction and transcriptional changes characterized by loss of cellular differentiation and altered gene expression known to stimulate allergic responses (for example, FLG and SPINK5). Epithelial silencing of SPINK7 promoted production of proinflammatory cytokines including thymic stromal lymphopoietin (TSLP). Loss of SPINK7 increased the activity of urokinase plasminogen-type activator (uPA), which in turn had the capacity to promote uPA receptor-dependent eosinophil activation. Treatment of epithelial cells with the broad-spectrum antiserine protease, α1 antitrypsin, reversed the pathologic features associated with SPINK7 silencing. The relevance of this pathway in vivo was supported by finding genetic epistasis between variants in TSLP and the uPA-encoding gene, PLAU We propose that the endogenous balance between SPINK7 and its target proteases is a key checkpoint in regulating mucosal differentiation, barrier function, and inflammatory responses and that protein replacement with antiproteases may be therapeutic for select allergic diseases.

Solute carrier family 9, subfamily A, member 3 (SLC9A3)/sodium-hydrogen exchanger member 3 (NHE3) dysregulation and dilated intercellular spaces in patients with eosinophilic esophagitis.

BACKGROUND: Eosinophilic esophagitis (EoE) is characterized by histopathologic modifications of esophageal tissue, including eosinophil-rich inflammation, basal zone hyperplasia, and dilated intercellular spaces (DIS). The underlying molecular processes that drive the histopathologic features of EoE remain largely unexplored. OBJECTIVE: We sought to investigate the involvement of solute carrier family 9, subfamily A, member 3 (SLC9A3) in esophageal epithelial intracellular pH (pHi) and DIS formation and the histopathologic features of EoE. METHODS: We examined expression of esophageal epithelial gene networks associated with regulation of pHi in the EoE transcriptome of primary esophageal epithelial cells and an in vitro esophageal epithelial 3-dimensional model system (EPC2-ALI). Molecular and cellular analyses and ion transport assays were used to evaluate the expression and function of SLC9A3. RESULTS: We identified altered expression of gene networks associated with regulation of pHi and acid-protective mechanisms in esophageal biopsy specimens from pediatric patients with EoE (healthy subjects, n = 6; patients with EoE, n = 10). The most dysregulated gene central to regulating pHi was SLC9A3. SLC9A3 expression was increased within the basal layer of esophageal biopsy specimens from patients with EoE, and expression positively correlated with disease severity (eosinophils/high-power field) and DIS (healthy subjects, n = 10; patients with EoE, n = 10). Analyses of esophageal epithelial cells revealed IL-13-induced, signal transducer and activator of transcription 6-dependent SLC9A3 expression and Na+-dependent proton secretion and that SLC9A3 activity correlated positively with DIS formation. Finally, we showed that IL-13-mediated, Na+-dependent proton secretion was the primary intracellular acid-protective mechanism within the esophageal epithelium and that blockade of SLC9A3 transport abrogated IL-13-induced DIS formation. CONCLUSIONS: SLC9A3 plays a functional role in DIS formation, and pharmacologic interventions targeting SLC9A3 function may suppress the histopathologic manifestations in patients with EoE.

Eosinophilic oesophagitis endotype classification by molecular, clinical, and histopathological analyses: a cross-sectional study.

BACKGROUND: Eosinophilic oesophagitis is understood in terms of quantifiable histological, endoscopic, and molecular features. Data are scant for inter-relations of these features and their potential to identify distinct disease endotypes. We aimed to identify clinical-pathological correlations between endoscopic and histological disease variables by transcription profiling of the oesophagus of patients with eosinophilic oesophagitis of varying severity and disease activity states. METHODS: We did a cross-sectional study across ten hospital sites in the USA associated with the Consortium of Eosinophilic Gastrointestinal Disease Researchers. We analysed oesophageal biopsy specimens taken from paediatric and adult patients with eosinophilic oesophagitis (discovery cohort), using the eosinophilic oesophagitis diagnostic panel (EDP), a set of 96 informative transcripts. Histological and endoscopic features were assessed by quantification of oesophageal eosinophils and use of the eosinophilic oesophagitis histology scoring system (HSS) and the eosinophilic oesophagitis endoscopic reference score (EREFS). Associations among the various histological, endoscopic, and molecular features were analysed by Spearman correlation. Results were replicated in a biologically independent, single-centre, validation cohort of patients with active eosinophilic oesophagitis. FINDINGS: The discovery cohort contained 185 samples and the validation cohort comprised 100 specimens. In the discovery cohort, EDP showed intersite consistency, significant correlation with oesophageal eosinophils (p<0·0001), and similar findings between paediatric and adult patients. Of eight HSS domains, basal zone hyperplasia correlated with the EDP (median Spearman ρ 0·47 [IQR 0·36-0·60]). Of five EREFS features, distal furrows correlated with the EDP (median Spearman ρ 0·42 [0·32-0·50]). By analysing active eosinophilic oesophagitis in the discovery cohort, the EDP identified three clusters associated with distinct endotypes (termed EoEe1-3) despite similar eosinophil levels. EoEe1 was associated with a normal-appearing oesophagus (risk ratio [RR] 3·27, 95% CI 1·04-10·27; p=0·0443), an inverse association with a history of oesophageal dilation (0·27, 0·09-0·82; p=0·0105) and showed relatively mild histological, endoscopic, and molecular changes. EoEe2 showed an inflammatory and steroid-refractory phenotype (RR 2·77, 95% CI 1·11-6·95; p=0·0376) and had the highest expression of inflammatory cytokines and steroid-responding genes. EoEe3 was associated with a narrow-calibre oesophagus (RR 7·98, 95% CI 1·84-34·64; p=0·0013) and adult onset (2·22, 1·19-4·12; p=0·0155), and showed the highest degree of endoscopic and histological severity and the lowest expression of epithelial differentiation genes. These endotypes were replicated in the validation cohort by clustering and with an eosinophilic oesophagitis endotype-prediction algorithm. INTERPRETATION: Our new disease classification stratifies patients with eosinophilic oesophagitis into subgroups with potential clinical and therapeutic significance and provides a framework for a precision medicine approach to eosinophilic oesophagitis. FUNDING: National Institutes of Health.