Assessment of local and systemic signature of eosinophilic esophagitis (EoE) in children through multi-omics approaches

Abstract

BackgroundEosinophilic oesophagitis (EoE) is a chronic food allergic disorder limited to oesophageal mucosa whose pathogenesis is still only partially understood. Moreover, its diagnosis and follow-up need repeated endoscopies due to absence of non-invasive validated biomarkers. In the present study, we aimed to deeply describe local immunological and molecular components of EoE in well-phenotyped children, and to identify potential circulating EoE-biomarkers.MethodsBlood and oesophageal biopsies were collected simultaneously from French children with EoE (n=17) and from control subjects (n=15). Untargeted transcriptomics analysis was performed on mRNA extracted from biopsies using microarrays. In parallel, we performed a comprehensive analysis of immune components on both cellular and soluble extracts obtained from both biopsies and blood, using flow cytometry. Finally, we performed non-targeted plasma metabolomics using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Uni/multivariate supervised and non-supervised statistical analyses were then conducted to identify significant and discriminant components associated with EoE within local and/or systemic transcriptomics, immunologic and metabolomics datasets. As a proof of concept, we conducted multi-omics data integration to identify a plasmatic signature of EoE.ResultsFrench children with EoE shared the same transcriptomic signature as US patients. Network visualization of differentially expressed (DE) genes highlighted the major dysregulation of innate and adaptive immune processes, but also of pathways involved in epithelial cells and barrier functions, and in perception of chemical stimuli. Immune analysis of biopsies highlighted EoE is associated with dysregulation of both type (T) 1, T2 and T3 innate and adaptive immunity, in a highly inflammatory milieu. Although an immune signature of EoE was found in blood, untargeted metabolomics more efficiently discriminated children with EoE from control subjects, with dysregulation of vitamin B6 and various amino acids metabolisms. Multi-blocks integration suggested that an EoE plasma signature may be identified by combining metabolomics and cytokines datasets.ConclusionsOur study strengthens the evidence that EoE results from alterations of the oesophageal epithelium associated with altered immune responses far beyond a simplistic T2 dysregulation. As a proof of concept, combining metabolomics and cytokines data may provide a set of potential plasma biomarkers for EoE diagnosis, which needs to be confirmed on a larger and independent cohort.

Identification of CXC Chemokine Receptor 2 (CXCR2) as a Novel Eosinophils-Independent Diagnostic Biomarker of Pediatric Eosinophilic Esophagitis by Integrated Bioinformatic and Machine-Learning Analysis

“…In addition to the above-mentioned attempts, previous studies aiming at discovering common non-invasive indicators for EoE diagnosis, either failed in population testing, 9 , 63 scarcely tested in children, 64–66 or still staged in laboratory (ie, exosomes, esophageal microbiome, or non-targeted metabolomics). 67 For example, a panel of 8 cytokines (IL-4, IL-13, IL-5, IL-6, IL-12p70, CD40L, IL-1α, and IL-17) in plasma for identifying EoE has been tested but merely with a 61% sensitivity and 83% specificity.…”

“… 74 Moreover, the evidence demonstrating the highly conserved transcriptomic signature of EoE in children subjects across different countries, genders, age, allergic status, and triggers, to some extent, favored the credibility of our conclusion. 9 , 75 , 76 The fact that EoE and GERD patients shared some similar clinical manifestations (ie, dysphagia, epigastric pain, food impactions, or prominent esophageal eosinophilia infiltration) and diagnosing EoE by the presence of ≥ 15 eos/high power field (x400) in the esophageal tissue biopsy or other eosinophilic biomarkers are not that solid, 7 makes this biomarker more important. 77 Prior studies have confirmed that pediatric EoE patients showed higher levels of Tregs in their esophageal epithelium than GERD patients and healthy children, 78–80 which was in opposite to adult EoE patients that had impaired induction of Tregs.…”

“…To acquire EoE-correlated gene expression data, we searched the Gene Expression Omnibus (GEO) Database ( https://www.ncbi.nlm.nih.gov/geo/ ) 28 through the keyword: “Eosinophilic esophagitis” [MeSH Terms] AND “Homo sapiens” [porgn: txid9606]. The GSE184182 9 and GSE197702 29 datasets containing samples from the healthy or diseased children (without any other disease except for EoE) were obtained and we performed the principal component analysis of the GSE184182 dataset to demonstrate their distribution. Their expression matrix was processed following the criteria: [1] Removing empty probes that have no matched gene; [2] Deleting probes that match multiple genes; [3] Selecting the probe with the highest expression level if a gene corresponds to multiple probes; [4] Calculating the median values as the expression level if multiple probes identify the same gene.…”

“… 7 An inflammatory phenotype in childhood would progressively develop into a fibro-stenotic situation over time and an average delay of diagnosis of 3–5 years normally found in pediatric patients leads to elevated risk of esophageal stricture, 8 for they are neither unaware of the illness nor acceptant to repeated endoscopy inspection burden. 9 Moreover, eosinophilia in EoE is frequently patch, and at least four biopsies would be required. 7 Therefore, identifying sensitive and specific diagnostic biomarkers for early and accurate EoE diagnosis prior to reaching an irreversible fibrosis stage is important to improving outcomes in the long run.…”

“…To the best of our knowledge, available studies of pediatric EoE mainly concentrated on specific immunological or molecular mechanisms in the blood, and were mainly based on small-scale cohort analysis. 9 , 23 The definite cause of EoE still remains uncertain so far. Several genetic risk loci of EoE (ie, CAPN14, DEX1 and TSLP) have been determined by genome-wide association study (GWAS) or meta-analysis, 24–26 while their underlying associations remain an open issue.…”