Eosinophilic esophagitis (EoE) is an allergic inflammatory disease of the esophagus that occurs in both children and adults. Previous studies of affected tissue from pediatric cohorts have identified prominent signatures of eosinophilia and type 2 inflammation. However, the details of the immune response in adults with EoE are still being elucidated. To determine whether EoE in adults shares inflammatory profiles with those observed in children, we performed RNA sequencing of paired human esophageal biopsies and blood samples from adults with EoE or gastroesophageal reflux disease. Unbiased analysis of differentially expressed genes in tissue revealed a strong IFN signature that was significantly enriched in EoE patients as compared with patients with gastroesophageal reflux disease. Both type I and type II IFN–responsive genes were upregulated in adult biopsies, but not in blood. A similar increase in expression of IFN gene sets was observed in pediatric EoE biopsies as compared with non-EoE samples, and in public pediatric and adult RNA-sequencing data. Finally, we found that human peripheral CD4+ T cells from children with EoE produce IFN-γ upon activation with EoE-causal allergens. Together, this work identifies a conserved IFN signature in pediatric and adult EoE, highlighting a role for non–type 2 inflammatory networks in the disease process in humans.

Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory disease that is triggered by specific foods, and characterized by Th2 cell–mediated inflammation and esophageal eosinophilia (1). Affecting ∼1 in 2500 (150,000) children and adults in the United States, EoE symptoms are debilitating and range from reflux, chest pain, and poor growth in children to esophageal stricture formation and food impaction in adolescents and adults (2). EoE is a chronic disease that affects both children and adults. However, the extent of pathophysiologic similarities and differences between pediatric and adult EoE are unknown.

EoE is an emerging disease, and our understanding of its pathophysiology is still evolving. The sine qua non of EoE is the presence of infiltrating eosinophils on esophageal biopsy and clinically, there are several features that link EoE to an allergic pathophysiology including increased prevalence in individuals with a history of atopy (3), being triggered by exposure to food and aeroallergens, and therapeutic efforts focused on allergen avoidance and/or use of corticosteroids. These initial observations have led to an early recognition of the critical role for type 2 inflammatory networks in EoE immunopathology (4). Indeed, experimental evidence supporting type 2 inflammation in EoE includes more than two decades of work profiling the transcriptional, cellular, and inflammatory features of inflamed esophagus (5), as well as more recent efforts that have focused on understanding the contribution of systemic and local T cell responses (3, 6).

Despite the strong link to type 2 inflammation within the esophageal mucosa, therapeutic attempts to block allergic pathways have had limited success in treating EoE (7, 8). Simultaneously, there has been a recent recognition of a role for non–type 2 inflammatory mediators in EoE pathophysiology. For example, TGF-β is now recognized as playing a critical role in EoE-related esophageal remodeling (911). Furthermore, there is evidence that cytokines and chemokines more often associated with type 1 inflammation (including IL-1 and IL-6) are elevated in the esophagus of individuals with EoE (12). Together, these observations suggest that although type 2 inflammatory networks represent an important subset of the relevant immune pathways activated during EoE, a deeper understanding of the mucosal inflammatory milieu is needed to advance diagnostic and therapeutic options for this disorder.

In this study, we use adult and pediatric patient cohorts to profile peripheral and esophageal EoE inflammatory networks in a minimally biased manner. We observe conserved IFN gene signatures in the esophagus of adult and pediatric EoE patients. We further identify circulating T cells from pediatric EoE patients that produce IFN-γ when stimulated with disease-causal allergens. Together, these results identify IFN-mediated inflammatory signaling as a feature of EoE immunopathology that is conserved between children and adults, and raise the possibility that circulating T cells are one source of IFN cytokines in EoE.

Nine adult patients receiving endoscopy for suspected EoE were enrolled at the Gastroenterology Department at the Virginia Mason Clinic. A diagnosis of EoE was confirmed in five patients by the presence of >15 eosinophils per high-power field (hpf) in biopsy sections. Four control patients underwent endoscopy for clinical indications but were found to have minimal or no eosinophil infiltrate in esophageal biopsies. None of the patients had received oral steroids before endoscopy, and all were on an open diet at the time of enrollment. Patient characteristics are summarized in Table I. Biopsies were collected in RNAlater (Thermo Fisher Scientific), and paired blood samples were collected in Tempus Blood RNA Tubes (Thermo Fisher Scientific) and stored at −80°C until use. The study was approved by the institutional review board (IRB) at Benaroya Research Institute, protocol 7109-477.03. All subjects provided informed consent.

A total of 17 pediatric subjects with symptoms consistent with EoE and undergoing endoscopy were enrolled at Children’s Hospital of Philadelphia (CHOP). Esophageal biopsy and/or peripheral blood samples were obtained under CHOP IRB-approved protocols 08-005998 or 18-015524 with subject consent. All pediatric patients in the biopsy cohort were on an open diet at the time of biopsy. The results shown in Tables I, II represent their initial biopsy findings prior to therapy. For peripheral blood T cell analyses, EoE subjects with confirmed, milk-triggered EoE, or non-EoE controls were recruited.

Total RNA was isolated from adult esophageal biopsies (one to two per subject) by homogenizing tissue in QIAzol lysis reagent (Qiagen) followed by column purification using the miRNeasy Kit with On-Column DNA Digestion (Qiagen). Whole-blood RNA was extracted using MagMax for Stabilized Blood Tubes RNA Isolation Kit, followed by globin reduction using GlobinClear Human (Thermo Fisher Scientific). Sequencing libraries were constructed from total RNA using the SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (Takara Bio) and NexteraXT DNA Sample Preparation Kit (Illumina) to generate Illumina-compatible barcoded libraries. Dual-index, single-read sequencing of pooled libraries was carried out on an HiSeq2500 sequencer (Illumina) with 58-base reads, using HiSeq v4 Cluster and SBS Kkits (Illumina) with a target depth of 5 million reads per sample. Base calls were processed to FASTQs on BaseSpace (Illumina). Reads were processed using workflows managed on the Galaxy platform; reads were trimmed by one base at the 3′ end, and then trimmed from both ends until base calls had a minimum quality score of at least 30 (Galaxy FASTQ Trimmer tool v1.0.0) (13). FastqMcf (v1.1.2, https://benthamopen.com/ABSTRACT/TOBIOIJ-7-1) was used to remove any remaining adapter sequence. Reads were aligned using the TopHat aligner (v1.4.1) (14) with the GRCh38 reference genome and gene annotations from ensembl release 77. Gene counts were generated using HTSeq-count (v0.4.1) (15). Quality metrics were compiled from PICARD (v1.134, http://broadinstitute.github.io/picard/), FASTQC (v0.11.3, http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), Samtools (v1.2) (16), and HTSeq-count (v0.4.1). RNA-sequencing data from the adult biopsies and whole-blood samples are deposited in the Gene Expression Omnibus (GEO) Repository (GSE156651, https://www.ncbi.nlm.nih.gov/gds/).

Total RNA was isolated from pediatric biopsies (Table I) and analyzed with a NanoString Human Immunology Panel (NanoString Technologies, Seattle, WA) consisting of 594 genes, including 15 internal reference genes. Immunology probe sets detect gene expression of a broad range of immune mediated molecules, including type I and type II IFNs and receptors. RNA was hybridized with unique barcoded probe sets overnight and digital images were processed with the nCounter digital analyzer to tabulate reporter probe counts. Gene expression was analyzed using the nSolver Analysis software (NanoString Technologies) by subtracting the geometric mean of the negative background probes, and normalization to the geometric mean of the housekeeping gene panel (ABCF1, EEF1G, G6PD, PPIA, RPL19, and TBP). Genes with expression below 13.19 reads across all subjects were excluded from analysis because of minimal expression.

Aligned gene counts from RNA sequencing were trimmed mean of M-values normalized with the package edgeR (17). Median coefficient of variation coverage (<0.5) and percent alignment (>85%) was used to eliminate libraries with poor quality (no libraries met this criteria). Patient sex check was used to exclude sample swaps. Differential gene expression was modeled separately for tissue and blood samples by the LIMMA R package (18). A two-group comparison between adult EoE and non-EoE samples was performed. Differentially expressed genes were used to query STRING-db for interactions and visualized by Cytoscape (19). Network visualizations used genes differentially expressed at ≤0.01 false discovery rate (FDR) and genes connected to those with a cutoff of ≤0.05 FDR. Gene ontology enrichment analysis was performed using the GOana function in the LIMMA R package (20). Hallmark gene sets (refined by algorithmic and expert curation) were downloaded from MSigDb (19), and gene set enrichment was computed by the ROAST package (21). Heatmaps displaying enriched genes were filtered at an FDR of 0.05 and were subjected to unsupervised hierarchical clustering. Gene expression data from the Sherrill et al. (22) study was downloaded from the National Center for Biotechnology Information GEO database with accession number GSE58640 and gene set enrichment performed as described. Gene set enrichment analysis (GSEA) for the Hallmark IFN-α and IFN-γ response gene sets was performed in the same manner on the normalized pediatric EoE and non-EoE biopsy gene counts generated with the NanoString Human Immunology Panel, without trimmed mean of M-values normalization.

Tissue and globin reduced whole-blood RNA (100 ng) from adult EoE and gastroesophageal reflux disease (GERD) patients was reverse transcribed into cDNA using SuperScriptIV reverse transcriptase (Life Technologies). Gene expression was detected using TaqMan gene expression assays specific for the STAT1, STAT2, ADAR, IFIT1, GBP2, and RPL36A genes (Applied Biosystems) on a 7500 Fast Real-Time PCR System (Applied Biosystems). Samples were run in triplicate in a single experiment. Mean Ct values were normalized to expression of the housekeeping gene (RPL36A) and then expressed relative to a technical positive control sample included on each plate.

The study protocol was approved by the IRB of CHOP, and informed consent was obtained from all participating donors (n = 18, nine per experimental arm). The donor characteristics are summarized in Table II. Five to fifteen milliliters of whole blood was obtained by venipuncture using sodium heparin collection tubes. To achieve processing within 5 h, tubes were transported at room temperature by foot to the Hill Laboratory at CHOP. PBMCs were isolated by Ficoll gradient using standard protocols and following the manufacturer’s instructions.

The median PBMC number obtained was 4.29 × 107 (range 1.16 × 107 to 9.42 × 107), and PBMCs were washed, counted, and cultured at 1 million cells per milliliter at 37°C and 5% CO2 in a 96-well round-bottom plate (Corning) in CTS OpTimizer T Cell Expansion Serum-Free Media (Life Technologies) in the presence or absence of 0.625 μg per well of tetanus toxoid or 6.25 μg per well of each of the five commonly allergenic milk proteins (α-lactalbumin, β-lactoglobulin, and α/β/κ-casein) cleaned of endotoxin. After 6 d, control and experimental T cells were treated with PMA/ionomycin/brefeldin A for a period of 4 h at 37°C and 5% CO2 to amplify the endogenous cytokine signal, washed, and surface stained with LiveDead Fixable Dye (1%; Invitrogen), CD8 (clone SK1, BV510, 1:100 dilution; BioLegend), CD19 (clone HIB19, CD19, 5:100 dilution; BioLegend), CD3 (clone SK7, allophycocyanin-780, 1:100 dilution; BioLegend), and CD4 (alone OKT4, BV605, 2.5:100 dilution; BioLegend). Cells were washed followed by fixation and permeabilization (Invitrogen), and intracellular staining for IFN-γ (Clone 4S.B3, PE/Cy7, 1:100 dilution; BioLegend) using standard protocols.

Samples were acquired using the BD FACSFortessa, using DIVA. Photo Multiplier Tube voltages were set using CS&T beads. Compensation was calculated using single-stained cells and/or compensation beads (eBioscience). A representative data set demonstrating the gating strategy is shown in Supplemental Fig. 3, and the results were audited. The median background reactivity for IFN-γ observed in this study was 0.75% of the parent gate (range 0.01–2.69) in CD4+ T cells. Culture supernatant IFN-γ levels were assayed by high-sensitivity Human T Cell Cytokine Luminex Assay (MilliporeSigma). Levels below the detectable limit were considered zero.

For transcript analysis, a two-group comparison was performed to identify differentially expressed genes between adult EoE and non-EoE samples, with p values computed by LIMMA via a modified t-statistic (two-sided). Gene ontology enrichment analysis was performed with the GOana function, which used a Wallenius noncentral hypergeometric test, based on an extension of the hypergeometric distribution. Gene set enrichment computed by the ROAST package used two-sided rotation tests, analogous to permutation tests, to test whether the genes within a gene set all change in the same direction. The p values resulting from all three analyses were adjusted for multiple comparisons using the Benjamini–Hochberg procedure. For quantitative PCR, a Mann–Whitney U test was performed to determine significant differences in gene expression between EoE and non-EoE samples. For flow cytometry and Luminex, significant outliers were identified and excluded by Grubbs test, and significant differences between the experimental groups were determined by one-sided Student t test.

Study approval.

All clinical investigation was conducted according to Declaration of Helsinki principles, following approval from the appropriate IRBs as detailed above. Written informed consent was obtained prior to patient participation in these studies.

Esophageal biopsies and paired blood samples were obtained from five adult patients with EoE and four control patients with normal endoscopies and histology who had symptoms consistent with GERD (Table I). Four of the EoE patients had a history of allergy and/or asthma, including one individual who developed EoE symptoms in response to peanut oral immunotherapy. No other EoE patients had a history of food-induced allergy. Non-EoE patients had no known history of allergy. None of the subjects had received oral glucocorticoids before endoscopy.

Table I.
Subject characteristics: RNA expression studies
Subject IDDiagnosisAgeSexEosinophils per hpf, Endoscopic AppearanceMedicationsBiopsy-Proven Eliciting Food Trigger, if KnownPeanut IgEMilk IgESoy IgEWheat IgEComments
Adult tissue, blood            
 1 EoE 75 >80 proximal, > 50 distal, edema and rings, EREFS=3 PPI  NA <0.01 <0.01 <0.01  
 2 EoE 34 40–50, proximal and distal, edema, rings, exudate, furrows, stricture, EREFS = 8 Histamine-2 blocker, antihistamine Peanut 37 0.39 0.84 0.16 History of IgE food allergy to peanut; allergic rhinitis 
 3 EoE 51 120 proximal, 42 distal, edema, rings, exudate, EREFS = 3 Histamine-2 blocker, antibiotic  0.17 0.16 0.21 0.27 Asthma, allergic rhinitis, eczema 
 4 EoE 32 25–50 proximal and distal, edema, rings, exudate, furrows, stricture, EREFS = 6   NA 0.31 <0.10 <0.10 Allergic rhinitis 
 5 EoE 25 85 proximal, 122 distal, edema, rings, EREFS = 3   4.84 0.14 1.12 4.04 Allergic rhinitis, possible pollen-related EoE (alder IgE 23.4) 
 7 Control 39 Negative   NA <0.10 <0.10 <0.10 Symptoms consistent with GERD 
 8 Control 60 Negative PPI  NA <0.10 <0.10 <0.10 Symptoms consistent with GERD 
 9 Control 65 Negative PPI, antihistamine  <0.01 <0.10 <0.10 <0.10 Symptoms consistent with GERD 
 10 Control 38 10–20, middle and distal   <0.01 <0.10 <0.10 0.24 Symptoms consistent with GERD 
Pediatric tissue            
 11 EoE 16 25, gross furrowing PPI  NA SPT6(−) SPT(−) SPT(−) History of food impaction 
 12 EoE 20 PPI  NA <0.01 <0.01 <0.01  
 13 EoE 12 50, reactive epithelial changes   NA NA NA NA  
 15 EoE 10 35, eosinophilic microabscesses and basal hyperplasia PPI Peanut, tree nut SPT(+) SPT(−) SPT(−) NA History of IgE food allergy to egg, had reincorporated into diet following food challenge 
 16 Control Negative   NA NA NA NA  
 17 Control Negative Polyethylene glycol 3350  NA NA NA NA  
 18 Control Negative   NA NA NA NA  
 19 Control 17 Negative   NA NA NA NA  
 20 Control 16 Negative   NA NA NA NA  
 21 Control 13 Negative PPI, dicyclomine  NA NA NA NA  
Subject IDDiagnosisAgeSexEosinophils per hpf, Endoscopic AppearanceMedicationsBiopsy-Proven Eliciting Food Trigger, if KnownPeanut IgEMilk IgESoy IgEWheat IgEComments
Adult tissue, blood            
 1 EoE 75 >80 proximal, > 50 distal, edema and rings, EREFS=3 PPI  NA <0.01 <0.01 <0.01  
 2 EoE 34 40–50, proximal and distal, edema, rings, exudate, furrows, stricture, EREFS = 8 Histamine-2 blocker, antihistamine Peanut 37 0.39 0.84 0.16 History of IgE food allergy to peanut; allergic rhinitis 
 3 EoE 51 120 proximal, 42 distal, edema, rings, exudate, EREFS = 3 Histamine-2 blocker, antibiotic  0.17 0.16 0.21 0.27 Asthma, allergic rhinitis, eczema 
 4 EoE 32 25–50 proximal and distal, edema, rings, exudate, furrows, stricture, EREFS = 6   NA 0.31 <0.10 <0.10 Allergic rhinitis 
 5 EoE 25 85 proximal, 122 distal, edema, rings, EREFS = 3   4.84 0.14 1.12 4.04 Allergic rhinitis, possible pollen-related EoE (alder IgE 23.4) 
 7 Control 39 Negative   NA <0.10 <0.10 <0.10 Symptoms consistent with GERD 
 8 Control 60 Negative PPI  NA <0.10 <0.10 <0.10 Symptoms consistent with GERD 
 9 Control 65 Negative PPI, antihistamine  <0.01 <0.10 <0.10 <0.10 Symptoms consistent with GERD 
 10 Control 38 10–20, middle and distal   <0.01 <0.10 <0.10 0.24 Symptoms consistent with GERD 
Pediatric tissue            
 11 EoE 16 25, gross furrowing PPI  NA SPT6(−) SPT(−) SPT(−) History of food impaction 
 12 EoE 20 PPI  NA <0.01 <0.01 <0.01  
 13 EoE 12 50, reactive epithelial changes   NA NA NA NA  
 15 EoE 10 35, eosinophilic microabscesses and basal hyperplasia PPI Peanut, tree nut SPT(+) SPT(−) SPT(−) NA History of IgE food allergy to egg, had reincorporated into diet following food challenge 
 16 Control Negative   NA NA NA NA  
 17 Control Negative Polyethylene glycol 3350  NA NA NA NA  
 18 Control Negative   NA NA NA NA  
 19 Control 17 Negative   NA NA NA NA  
 20 Control 16 Negative   NA NA NA NA  
 21 Control 13 Negative PPI, dicyclomine  NA NA NA NA  

EREFS score, edema, rings, exudate, furrows, and stricture, each scored on a scale of 0–2 and then summed across features; F, female; M, male; NA, not available; PPI, protein pump inhibitor; SPT, skin prick test.

Bulk RNA-sequencing data from esophageal biopsy and whole-blood RNA revealed a clear distinction in principal component (PC) 1 between the biopsy and blood transcript profiles and PC2, which distinguished profiles from EoE and non-EoE biopsies (Fig. 1A). In contrast, there was no distinction of transcript profiles from unstimulated whole-blood samples between EoE and non-EoE patients.

FIGURE 1.

Differential gene expression differentiates sample origin and disease type in adults. Bulk RNA sequencing was performed on whole-esophageal biopsies or paired whole blood from five adult EoE patients and four non-EoE control patients with symptoms consistent with GERD. (A) PC analysis distinguished tissue from blood samples (PC1), and EoE from non-EoE (PC2) in tissue samples but not blood. (B) Differential gene expression analysis. A two-group comparison was performed to identify differentially expressed genes between adult EoE versus non-EoE samples, with p values computed by LIMMA via a modified t-statistic and adjusted using the Benjamini–Hochberg procedure. Six hundred and seventy-seven genes were significantly differentially expressed in biopsies from adult EoE (n = 476, red symbols) or non-EoE subjects (n = 201, gold symbols) at FDR ≤ 0.05. (C) Heatmap of differentially expressed genes subjected to unsupervised hierarchical clustering. Differential gene expression distinguished EoE from non-EoE biopsy samples. Scaled gene expression is shown as blue (low) to red (high). (D) Enrichment of Gene Ontology (GO) gene sets in the differentially expressed genes in (B) was performed with the GOanna function in LIMMA using a Wallenius noncentral hypergeometric test. Gene sets were filtered at FDR ≤ 0.05 and plotted in a volcano plot as gene sets significantly enriched in EoE (red n = 200) versus gene sets significantly enriched in non-EoE (gold n = 19). The top 15 gene sets are annotated.

FIGURE 1.

Differential gene expression differentiates sample origin and disease type in adults. Bulk RNA sequencing was performed on whole-esophageal biopsies or paired whole blood from five adult EoE patients and four non-EoE control patients with symptoms consistent with GERD. (A) PC analysis distinguished tissue from blood samples (PC1), and EoE from non-EoE (PC2) in tissue samples but not blood. (B) Differential gene expression analysis. A two-group comparison was performed to identify differentially expressed genes between adult EoE versus non-EoE samples, with p values computed by LIMMA via a modified t-statistic and adjusted using the Benjamini–Hochberg procedure. Six hundred and seventy-seven genes were significantly differentially expressed in biopsies from adult EoE (n = 476, red symbols) or non-EoE subjects (n = 201, gold symbols) at FDR ≤ 0.05. (C) Heatmap of differentially expressed genes subjected to unsupervised hierarchical clustering. Differential gene expression distinguished EoE from non-EoE biopsy samples. Scaled gene expression is shown as blue (low) to red (high). (D) Enrichment of Gene Ontology (GO) gene sets in the differentially expressed genes in (B) was performed with the GOanna function in LIMMA using a Wallenius noncentral hypergeometric test. Gene sets were filtered at FDR ≤ 0.05 and plotted in a volcano plot as gene sets significantly enriched in EoE (red n = 200) versus gene sets significantly enriched in non-EoE (gold n = 19). The top 15 gene sets are annotated.

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Differential gene expression analysis was performed to identify transcript signatures differentiating adult EoE and GERD samples. We found a total of 677 differentially expressed genes between EoE and GERD biopsies (FDR ≤ 0.05), 476 of which were upregulated in EoE and 201 upregulated in GERD (Fig. 1B, 1C, Supplemental Table I). There were no significantly differentially expressed genes between EoE and GERD whole-blood samples (FDR ≥ 0.071, data not shown), consistent with no difference in PC2 in Fig. 1A. Thus, an EoE-specific transcript signature is not detectable in unfractionated unstimulated blood samples in adult patients.

Differentially expressed genes upregulated in EoE versus GERD biopsies were significantly enriched for gene sets [defined by the Gene Ontology consortium (20)] involving processes in the immune system, response to stress, defense response, response to stimulus, and innate immune response (FDR ≤ 6.19 × 10−8, Fig. 1D, Supplemental Table II). Likewise, GSEA identified genes involved in inflammation, signaling, and angiogenesis (FDR = 0.0125, Supplemental Table III). STRING-db network interactions showed several nodes of interacting genes (Fig. 2A). Two nodes included genes related to type 2 immune responses, including CCR3 (eotaxin receptor involved in eosinophil recruitment), PTGDR2 (PG D2 receptor 2, the canonical Th2 cell marker CRTH2), and ALOX15 [arachidonate 15-lipoxigenase, which is highly expressed in Th2A cells (23)]. As expected, there was expression of genes from a human eosinophil gene set (24) in adult EoE tissue, as well as genes from a previously identified EoE gene signature (Supplemental Fig. 1) (25). In contrast, genes enriched in non-EoE biopsies were enriched for gene sets related to keratinization, skin development, and epidermal cell differentiation (FDR ≤ 7.02 × 10−11, Fig. 1D, Supplemental Table II).

FIGURE 2.

An IFN response signature is enriched in adult EoE tissue. (A) Differentially expressed genes (n = 677) between five EoE and four non-EoE biopsy samples were analyzed for protein interactions using STRING-db. The network visualization shows genes at FDR ≤ 0.01 (bold borders) and connected genes at FDR ≤ 0.05 (no borders). The color of the rectangle indicates the log-fold change in gene expression in EoE versus non-EoE and ranges from blue (up in non-EoE) to red (up in EoE). A prominent node of IFN-related genes is indicated with the dotted circle. (B) GSEA of the Hallmark IFN-α and IFN-γ gene sets was computed on the biopsy RNA-sequencing data with the ROAST package, using two-sided rotation tests as described in the 2Materials and Methods section. The p values were adjusted using the Benjamini–Hochberg procedure. Heatmaps display enriched genes filtered at FDR ≤ 0.05 and were subjected to unsupervised hierarchical clustering. Scaled gene expression is shown as blue (low) to red (high). Shown are heatmaps for genes unique to each IFN gene set and a common set of IFN response genes. (C) Upregulation of select IFN response genes in EoE tissue compared with non-EoE biopsies was confirmed by quantitative PCR. Samples were run in triplicate in a single experiment. Group differences in gene expression were significant at *p < 0.05 using a Mann–Whitney U test.

FIGURE 2.

An IFN response signature is enriched in adult EoE tissue. (A) Differentially expressed genes (n = 677) between five EoE and four non-EoE biopsy samples were analyzed for protein interactions using STRING-db. The network visualization shows genes at FDR ≤ 0.01 (bold borders) and connected genes at FDR ≤ 0.05 (no borders). The color of the rectangle indicates the log-fold change in gene expression in EoE versus non-EoE and ranges from blue (up in non-EoE) to red (up in EoE). A prominent node of IFN-related genes is indicated with the dotted circle. (B) GSEA of the Hallmark IFN-α and IFN-γ gene sets was computed on the biopsy RNA-sequencing data with the ROAST package, using two-sided rotation tests as described in the 2Materials and Methods section. The p values were adjusted using the Benjamini–Hochberg procedure. Heatmaps display enriched genes filtered at FDR ≤ 0.05 and were subjected to unsupervised hierarchical clustering. Scaled gene expression is shown as blue (low) to red (high). Shown are heatmaps for genes unique to each IFN gene set and a common set of IFN response genes. (C) Upregulation of select IFN response genes in EoE tissue compared with non-EoE biopsies was confirmed by quantitative PCR. Samples were run in triplicate in a single experiment. Group differences in gene expression were significant at *p < 0.05 using a Mann–Whitney U test.

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Surprisingly, GSEA also revealed significant enrichment of IFN-α (FDR = 0.0125) and IFN-γ response genes (FDR = 0.0141) in the differentially expressed genes from the EoE and non-EoE biopsies (Supplemental Table III). Furthermore, there was a prominent node of upregulated IFN response genes related to TRIM22 in the STRING-db interaction network (Fig. 2A). To explore this further, we examined expression of genes in the Hallmark IFN-α (n = 97) and IFN-γ (n = 200) response gene sets in the biopsy RNA-sequencing data. Expression of 42 IFN response genes was enriched in the biopsies (FDR ≤ 0.05), including four genes unique to IFN-α, 22 genes unique to IFN-γ, and 16 genes shared between the IFN-α and -γ response. Unsupervised clustering of the enriched genes differentiated EoE from non-EoE biopsies with the exception of one non-EoE subject who had a partial IFN signature (Fig. 2B). Heatmaps of the expression of the full set of IFN-α and IFN-γ response genes are shown in Supplemental Fig. 2.

We confirmed increased expression of select IFN response genes in EoE versus non-EoE biopsies by quantitative PCR (Fig. 2C). Both STAT1 and STAT2 transcript levels were significantly higher in EoE biopsies consistent with IFN-mediated signaling; increased transcript levels were also detected for ADAR (induced by both IFN-α and IFN-γ), IFIT1 (IFN-γ-induced), and GBP2 (IFN-α–induced) in EoE versus non-EoE tissue. There was no significant difference in expression of these genes in whole-blood RNA from the same subjects (data not shown). These results highlight that IFN responses mediated by both IFN-α and IFN-γ are detected in EoE tissue. Likewise, there was no significant difference in gene enrichment between IFN-α– and IFN-γ–responsive genes in EoE biopsies relative to the total number of genes in the respective gene sets, indicating that both type I and type II IFNs are expressed in esophageal tissue from adult EoE patients.

To determine if upregulation of IFN response genes is a common finding in EoE, we validated our findings using a second publicly available tissue RNA-sequencing data set from a mixed-age cohort of 10 EoE and six non-EoE patients (GSE58640) (22). The demographics of this cohort are listed in Supplemental Table IV and included primarily pediatric patients in addition to three adults. Consistent with our data, GSEA demonstrated differential expression of IFN-α and IFN-γ response genes (FDR ≤ 0.05) in the EoE biopsies compared with non-EoE biopsies (Fig. 3). We also noted that a small set of IFN response genes unique to IFN-γ or shared between IFN-γ and IFN-α were enriched in the non-EoE biopsies in both the original and the validation dataset (Fig. 3, Supplemental Fig. 2), however the majority of IFN response genes were upregulated in the EoE tissue.

FIGURE 3.

Enrichment of IFN signatures in tissue from a validation set of mixed-age EoE patients. Publicly available RNA-sequencing data from pediatric (n = 7) and adult (n = 3) EoE biopsies and pediatric non-EoE (n = 6) biopsy samples was downloaded from National Center for Biotechnology Information GEO database (accession number GSE58640) (22). GSEA using the Hallmark IFN-α (n = 97) and IFN-γ (n = 200) gene sets was computed with the ROAST package, using two-sided rotation tests as described in the 2Materials and Methods section. The p values were adjusted using the Benjamini–Hochberg procedure. Heatmaps display enriched genes filtered at FDR ≤ 0.05 and were subjected to unsupervised hierarchical clustering. Scaled gene expression is shown as blue (low) to red (high). Shown are heatmaps for genes unique to each IFN gene set and a common set of IFN response genes.

FIGURE 3.

Enrichment of IFN signatures in tissue from a validation set of mixed-age EoE patients. Publicly available RNA-sequencing data from pediatric (n = 7) and adult (n = 3) EoE biopsies and pediatric non-EoE (n = 6) biopsy samples was downloaded from National Center for Biotechnology Information GEO database (accession number GSE58640) (22). GSEA using the Hallmark IFN-α (n = 97) and IFN-γ (n = 200) gene sets was computed with the ROAST package, using two-sided rotation tests as described in the 2Materials and Methods section. The p values were adjusted using the Benjamini–Hochberg procedure. Heatmaps display enriched genes filtered at FDR ≤ 0.05 and were subjected to unsupervised hierarchical clustering. Scaled gene expression is shown as blue (low) to red (high). Shown are heatmaps for genes unique to each IFN gene set and a common set of IFN response genes.

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An additional cohort of four pediatric EoE patients and six controls were studied using a more targeted approach (Table I). Non-EoE control pediatric patients were undergoing diagnostic evaluation for gastrointestinal symptoms and reported symptoms warranting esophagogastroduodenoscopy but had no prior diagnosis of EoE and had biopsies that excluded histopathologic abnormalities. Half of these control patients had a prior history of atopic dermatitis, IgE-mediated food allergy, allergic rhinitis, or asthma. In contrast, all of the EoE patients in this pediatric cohort had a prior personal history of atopy at the time of presentation with EoE. One of these individuals had a history of developing EoE subsequent to reintroduction of an IgE-mediated food allergen into the diet (egg). None of these patients had received oral or topical glucocorticoids before endoscopy (Table I). Total RNA from whole biopsies was analyzed using the NanoString Human Immunology Panel consisting of 579 immune related genes. GSEA showed upregulation of gene expression for IFN-γ response-specific genes, as well as shared IFN-α and IFN-γ response genes in the pediatric EoE tissue samples compared with the control samples (FDR < 0.1, Fig. 4). Two of the six non-EoE patients expressed higher levels of a small subset of the enriched IFN response genes. Together, this work indicates that an IFN response signature characterizes EoE tissue from patients over a range of ages.

FIGURE 4.

IFN gene expression is upregulated in pediatric EoE biopsies. Gene expression in esophageal biopsies from four pediatric EoE patients (active) and six non-EoE patients (control) was analyzed using the NanoString Human Immunology Panel. GSEA was performed on the normalized read counts using the Hallmark IFN-α (n = 97) and IFN-γ (n = 200) response gene sets, of which 63 genes were included on the NanoString panel. Gene set enrichment was computed with the ROAST package, using two-sided rotation tests as described in the 2Materials and Methods section. The p values were adjusted using the Benjamini–Hochberg procedure. Heatmaps display enriched genes filtered at an FDR < 0.1 and were subjected to unsupervised hierarchical clustering. Scaled log gene expression is shown as blue (low) to red (high). Genes unique to the IFN-γ response gene set are labeled light blue in the sidebar; genes in common between the IFN-α and IFN-γ gene sets are labeled pink. No genes unique to the IFN-α gene set were enriched at an FDR <0.1.

FIGURE 4.

IFN gene expression is upregulated in pediatric EoE biopsies. Gene expression in esophageal biopsies from four pediatric EoE patients (active) and six non-EoE patients (control) was analyzed using the NanoString Human Immunology Panel. GSEA was performed on the normalized read counts using the Hallmark IFN-α (n = 97) and IFN-γ (n = 200) response gene sets, of which 63 genes were included on the NanoString panel. Gene set enrichment was computed with the ROAST package, using two-sided rotation tests as described in the 2Materials and Methods section. The p values were adjusted using the Benjamini–Hochberg procedure. Heatmaps display enriched genes filtered at an FDR < 0.1 and were subjected to unsupervised hierarchical clustering. Scaled log gene expression is shown as blue (low) to red (high). Genes unique to the IFN-γ response gene set are labeled light blue in the sidebar; genes in common between the IFN-α and IFN-γ gene sets are labeled pink. No genes unique to the IFN-α gene set were enriched at an FDR <0.1.

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Previous studies have detected IFN-γ expression in CD8+ T cells in EoE biopsy tissues, suggesting circulating T cells may be one potential source of IFN in esophageal tissue (26). In this regard, it is notable that we did not detect an IFN signature in whole blood. However, we hypothesized that circulating T cells may not express IFN when not actively responding to food Ags. To test this, we isolated PBMCs from the blood of patients with milk-triggered EoE or non-EoE controls (Table II) and cultured them in vitro for 6 d in the presence or absence of five allergenic milk proteins (α-lactalbumin, β-lactoglobulin, and α/β/κ-casein). We then assayed CD4+ T cell IFN-γ production by intracellular flow cytometry (Supplemental Fig. 3). Compared with stimulated T cells isolated from controls, or unstimulated EoE T cells, EoE CD4+ T cells stimulated with purified milk proteins expressed significant amounts of IFN-γ by intracellular cytokine staining (Fig. 5A, 5B). As compared with control PBMCs, there was a trend toward increased IFN-γ levels in culture superannuates of milk-stimulated EoE PBMCs (Fig. 5C). We did not see a statistically significant increase in IFN-γ expression in CD8+ T cells from EoE patients stimulated with milk peptides (data not shown). Together, these results indicate that Ag-activated CD4 T cells may be a source of IFN-γ in EoE patients.

Table II.
Subject characteristics: T cell studies
Subject IDDiagnosisAgeSexEosinophils per hpf, Endoscopic AppearanceMedicationsBiopsy-Proven Eliciting Food Trigger, if KnownPeanut IgEMilk IgESoy IgEWheat IgEComments
Pediatric blood            
 22 EoE 11 18 PPI Milk SPT(−) SPT(−) SPT(−) SPT(−)  
 23 EoE up to 25 PPI Milk, egg, soy, wheat, beef NA NA NA NA Asthma, allergic rhinitis 
 24 EoE PPI Milk NA NA NA NA IgE food allergy, allergic rhinitis, eczema, adhesive allergy 
 25 EoE 55 PPI Milk NA NA NA NA  
 26 EoE 14 78 PPI Milk SPT(−) SPT(−) SPT(−) SPT(−)  
 27 EoE 20 PPI Milk, wheat, sesame, soy, tree nut, peanut NA NA NA NA Allergic rhinitis 
 28 EoE 0–8 PPI Milk, egg, tree nut NA NA NA NA Adhesive allergy 
 29 EoE 10 Remission PPI Milk SPT(−) SPT(+) SPT(−) SPT(−) Consumes baked milk 
 30 EoE Remission PPI, Dupixent Milk NA NA SPT(+) SPT(−) Receives Dupixent for eczema 
 31 Control 18 Negative   NA NA NA NA  
 32 Control 10 Negative   NA NA NA NA Drug allergy 
 33 Control 12 Negative PPI  NA NA NA NA  
 34 Control 27 NA   NA NA NA NA  
 35 Control 11 0–3 PPI  NA NA NA NA  
 36 Control 12 1–2 PPI  NA NA NA NA  
 37 Control 38 NA   NA NA NA NA  
 38 Control 17 Negative PPI  NA NA NA NA Drug allergy 
 39 Control 32 NA   NA NA NA NA  
Subject IDDiagnosisAgeSexEosinophils per hpf, Endoscopic AppearanceMedicationsBiopsy-Proven Eliciting Food Trigger, if KnownPeanut IgEMilk IgESoy IgEWheat IgEComments
Pediatric blood            
 22 EoE 11 18 PPI Milk SPT(−) SPT(−) SPT(−) SPT(−)  
 23 EoE up to 25 PPI Milk, egg, soy, wheat, beef NA NA NA NA Asthma, allergic rhinitis 
 24 EoE PPI Milk NA NA NA NA IgE food allergy, allergic rhinitis, eczema, adhesive allergy 
 25 EoE 55 PPI Milk NA NA NA NA  
 26 EoE 14 78 PPI Milk SPT(−) SPT(−) SPT(−) SPT(−)  
 27 EoE 20 PPI Milk, wheat, sesame, soy, tree nut, peanut NA NA NA NA Allergic rhinitis 
 28 EoE 0–8 PPI Milk, egg, tree nut NA NA NA NA Adhesive allergy 
 29 EoE 10 Remission PPI Milk SPT(−) SPT(+) SPT(−) SPT(−) Consumes baked milk 
 30 EoE Remission PPI, Dupixent Milk NA NA SPT(+) SPT(−) Receives Dupixent for eczema 
 31 Control 18 Negative   NA NA NA NA  
 32 Control 10 Negative   NA NA NA NA Drug allergy 
 33 Control 12 Negative PPI  NA NA NA NA  
 34 Control 27 NA   NA NA NA NA  
 35 Control 11 0–3 PPI  NA NA NA NA  
 36 Control 12 1–2 PPI  NA NA NA NA  
 37 Control 38 NA   NA NA NA NA  
 38 Control 17 Negative PPI  NA NA NA NA Drug allergy 
 39 Control 32 NA   NA NA NA NA  

F, female; M, male; NA, not available; PPI, protein pump inhibitor; SPT, skin prick test.

FIGURE 5.

IFN-γ is produced by circulating, milk-activated pediatric EoE T cells. (A) Flow-cytometric analysis of CD4+ T cells from peripheral blood of non-EoE (control) or milk-allergic EoE (EoE) pediatric subjects. PBMCs were cultured in vitro in the absence (unstimulated [Unstim.]) or presence of tetanus toxoid or milk proteins (α-lactalbumin, β-lactoglobulin, and α/β/κ-casein) for 6 d. Gated on Live, CD8, CD19, CD4+. Numbers indicate percentage of parent gate. (B) IFN-γ production by peripheral CD4+ T cells across multiple non-EoE or milk-allergic EoE subjects. (C) IFN-γ amounts in culture supernatants of peripheral CD4+ T cells from non-EoE or milk-allergic EoE subjects cultured in vitro in the presence of milk proteins (n = 8–9 subjects per experimental arm). *p ≤ 0.05.

FIGURE 5.

IFN-γ is produced by circulating, milk-activated pediatric EoE T cells. (A) Flow-cytometric analysis of CD4+ T cells from peripheral blood of non-EoE (control) or milk-allergic EoE (EoE) pediatric subjects. PBMCs were cultured in vitro in the absence (unstimulated [Unstim.]) or presence of tetanus toxoid or milk proteins (α-lactalbumin, β-lactoglobulin, and α/β/κ-casein) for 6 d. Gated on Live, CD8, CD19, CD4+. Numbers indicate percentage of parent gate. (B) IFN-γ production by peripheral CD4+ T cells across multiple non-EoE or milk-allergic EoE subjects. (C) IFN-γ amounts in culture supernatants of peripheral CD4+ T cells from non-EoE or milk-allergic EoE subjects cultured in vitro in the presence of milk proteins (n = 8–9 subjects per experimental arm). *p ≤ 0.05.

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Although it is known that the mucosal inflammation in EoE is heterogenous, study thus far has focused on the contribution of type 2 inflammation to the disease process. Furthermore, studies to date have predominantly been performed in children, leaving fundamental questions as to the extent to which adult EoE is a pathologic continuation of pediatric disease. In this study, we characterized the inflammatory response in pediatric and adult EoE using transcriptional profiling of esophageal biopsies in an effort to identify inflammatory characteristics that are conserved across age groups. Unbiased analysis of adult biopsies identified 677 differentially expressed genes compared with those from non-EoE patients. Although genes related to type 2 immunity were also upregulated in EoE tissue, we demonstrate there is a strong type I and type II IFN response gene expression signature that is conserved in both pediatric and adult populations. One strength of our analyses is that we replicate this finding in three cohorts: an adult biopsy tissue RNA-sequencing discovery cohort, a second mixed-age biopsy tissue RNA-sequencing EoE and control cohort, and using a digital multiplex gene analysis of biopsy tissue gene expression in a pediatric cohort. Notably, we did not observe significantly differentially expressed genes in unstimulated, unfractionated adult whole blood. This could be due to a technological limit of detection or the requirement for Ag activation of circulating food-specific T cells. Consistent with the latter hypothesis, we found that peripheral CD4+ T cells from children with EoE produce IFN-γ upon Ag activation. Together, these data reveal a conserved IFN signature in esophageal tissue of adults and children with EoE, which is also reflected in circulating Ag-activated T cells.

Previous profiling studies of effected tissue in EoE patients have identified signatures of eosinophilia, inflammation, and immune activation (22, 27). These studies led to the development of a molecular diagnostic gene expression panel that can distinguish EoE tissue from non-EoE biopsies in both pediatric and adult cohorts (25, 28). We found similar gene sets were enriched in adult EoE tissue, and observed several network clusters that included type 2 immune response genes. Accordingly, there was enrichment of eosinophil-related genes and differential expression of the above gene expression panel, consistent with type 2–mediated disease in our adult cohort.

Aspects of an IFN response have been previously detected in EoE, although not thoroughly studied. For example, prior studies have found upregulated IFN-γ expression in inflamed EoE biopsy tissue (29), and increased IFN-γ has been detected in the supernatant of cultured EoE biopsy tissue using ELISA (30). Our study adds to these observations by comprehensively describing differential expression of both IFN-α and IFN-γ response genes in esophageal tissue from both adult and pediatric EoE patients in a minimally biased effort across three independent patient cohorts and datasets. There was no preferential enrichment of IFN-α or IFN-γ response genes relative to the total numbers of genes in each Hallmark gene set and we confirmed increased expression of genes unique to the IFN-α or IFN-γ response by quantitative PCR, indicating that both type I and type II IFNs contribute to the IFN signature in EoE. The magnitude of the IFN signature differed among EoE patients, and a small number of IFN response genes were preferentially expressed in non-EoE patients, perhaps reflecting general effects of tissue damage. This finding may be related to the use of biopsies from patients with GERD as non-EoE controls for our adult cohort rather than biopsies from population-based controls with normal esophageal tissue. Notably, the EoE-associated gene C11orf30/EMSY is a repressor of IFN response gene expression, providing a plausible link to an increased IFN gene signature in EoE (31). One strength of our study is that our data derive from multiple medical centers and from patients across various age groups, yet seem to consistently point toward enrichment of type I and type II IFN response genes in EoE biopsy tissue.

Bulk RNA sequencing of esophageal biopsies does not allow us to distinguish the cells producing IFN and responding to IFN in our study. However, we demonstrate that peripheral blood CD4+ cells stimulated with milk Ags produce IFN-γ, raising the possibility that circulating T cells partly contribute to known IFN-γ–producing T cells in the inflamed EoE mucosa (25). Indeed, Wen and colleagues (26) have published single-cell RNA-sequencing data of tissue infiltrating T cells and detected IFN-γ RNA in over 84% of T cells in EoE biopsies, although there was no difference in the level of IFN-γ expression between cells from active EoE versus controls. Sayej and colleagues (32) examined lymphocytes from EoE biopsy tissue using flow cytometry and found significant elevation in TNF-α and IFN-γ production from the CD3+CD8+ T cell population but not from the CD3+CD4+ T cell population. We also detected enrichment of several genes unique to the IFN-α response in two of the datasets analyzed in our study, although data regarding the cellular source of IFN-α in EoE are lacking. A report that eosinophils in EoE tissue form extracellular traps that can elicit a type I IFN response from plasmacytoid dendritic cells suggests an additional plausible source of IFN (33). In support of this, we analyzed immune cell infiltrates in additional banked biopsies from a subset of the adult EoE and GERD patients in this study by flow cytometry and detected plasmacytoid dendritic cells in EoE tissue but not GERD biopsies (data not shown). Regardless, additional studies in mice and humans are needed to clarify the cellular participants in the IFN response in EoE.

Does IFN play a role in the pathology of EoE? This cross-sectional study does not allow us to definitively determine if the IFN response gene signature correlates with disease course. Our data correlate an IFN gene response signature with the presence of EoE mucosal disease. However, additional prospective studies of EoE patients before and after remission are required to establish a causal link between IFN and pathophysiologic features in EoE. From a mechanistic standpoint, IFN-γ has well known effects on HLA gene expression, which can enhance Ag presentation of allergens in esophageal tissue in EoE (34). IFN-γ also potentiates release of the IL-1 cytokine family member IL-33 from esophageal epithelial cells, which can then act as a ligand for ST2 on innate lymphoid cells type 2 cells, Th2 cells, mast cells, and basophils, thereby contributing to the type 2 immune response in the tissue (35). IFN-γ is known to enhance aspects of human eosinophil effector functions, including superoxide anion generation, degranulation, adhesion, and expression of multiple signaling and effector molecules (36), whereas both IFN-γ– and IFN-α–induced necrosis may contribute to tissue destruction in the esophagus (37). Finally, there is mounting interest in the role of IgG4 in EoE immunopathology (3840). This is of particular relevance, as IFN-α signaling has been shown to contribute to IgG4 production in other disease contexts (41). Future studies should focus on the mechanistic relationship between IFN and IgG4 in the context of EoE.

In summary, we show for the first time, to our knowledge, a conserved IFN gene expression signature in EoE biopsy tissue that is present in both pediatric and adult EoE patients. We conclude that IFN-responsive genes are an additional feature within the biopsy gene expression signature in EoE patients. This study extends the current knowledge of the mucosal inflammatory response in EoE, and specifically points to type I and type II IFN responses as a form of non-Th2–mediated inflammation that may be relevant to EoE immunopathology.

We acknowledge the Genomics Core laboratory at Benaroya Research Institute for the RNA sequencing of adult biopsies and blood samples, Dr. Mario Rosasco for transcript alignment and processing, as well as Drs. Amanda Muir and Alain Benitez from the CHOP Department of Gastroenterology for providing pediatric biopsy tissue for these studies. We also acknowledge Dr. Anne Hocking at Benaroya Research Institute for manuscript preparation.

This work was supported by a supplement to National Institute of Allergy and Infectious Diseases, National Institutes of Health Grants 1 R01 AI124220-01A (to S.F.Z.), K08AI148456 (to M.A.R.), and K08DK116668 (to D.A.H.), the Children’s Hospital of Philadelphia Food Allergy Frontier Grant (to J.M.S.), an American Partnership for Eosinophilic Disorders Hope Research Grant, and the American Academy of Allergy, Asthma, and Immunology (to D.A.H.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The sequences presented in this article have been submitted to the Gene Expression Omnibus Repository (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156651) under accession number GSE156651.

The online version of this article contains supplemental material.

Abbreviations used in this article:

CHOP

Children’s Hospital of Pennsylvania

EoE

eosinophilic esophagitis

FDR

false discovery rate

GERD

gastroesophageal reflux disease

GSEA

gene set enrichment analysis

hpf

high-power field

IRB

institutional review board

PC

principal component.

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The authors have no financial conflicts of interest.