Salivary microbiota composition may discriminate between patients with eosinophilic oesophagitis (EoE) and non‐EoE subjects. Issue 3 (17th June 2022)

• Record Type: Journal Article
• Authors: Facchin, Sonia; Calgaro, Matteo; Pandolfo, Mattia; Caldart, Federico; Ghisa, Matteo; Greco, Eliana; Sattin, Eleonora; Valle, Giorgio; Dellon, Evan S.; Vitulo, Nicola; Savarino, Edoardo Vincenzo
• Is Part Of: Alimentary pharmacology & therapeutics. Volume 56:Issue 3(2022)
• Page Start: 450
• Page End: 462
• Publication Date: 2022-06-17
• Subjects: Digestive organs -- Diseases -- Treatment -- Periodicals; Digestive organs -- Effect of drugs on -- Periodicals; Gastrointestinal system -- Diseases -- Treatment -- Periodicals; Gastrointestinal system -- Effect of drugs on -- Periodicals; 615.73
• DOI: 10.1111/apt.17091
• Languages: English
• ISSNs: 0269-2813

Abstract

Summary: Background: Data on the role of the microbiome in adult patients with eosinophilic oesophagitis (EoE) are limited. Aims: To prospectively collect and characterise the salivary, oesophageal and gastric microbiome in patients with EoE, further correlating the findings with disease activity. Methods: Adult patients with symptoms of oesophageal dysfunction undergoing upper endoscopy were consecutively enrolled. Patients were classified as EoE patients, in case of more than 15 eosinophils per high‐power field, or non‐EoE controls, in case of lack of eosinophilic infiltration. Before and during endoscopy, saliva, oesophageal and gastric fundus biopsies were collected. Microbiota assessment was performed by 16 s rRNA analysis. A Sparse Partial Least Squares Discriminant Analysis (sPLS‐DA) was implemented to identify biomarkers. Results: Saliva samples were collected from 29 EoE patients and 20 non‐EoE controls;, biopsies from 25 EoE and 5 non‐EoE controls. In saliva samples, 23 Amplicon Sequence Variants (ASVs) were positively associated with EoE and 27 ASVs with controls, making it possible to discriminate between EoE and non‐EoE patients with a classification error (CE) of 24%. In a validation cohort, the accuracy, sensitivity, specificity, positive predictive value and negative predictive value of this model were 78.6%, 80%, 75%, 80% and 60%, respectively. Moreover, the analysis of oesophageal microbiota samples observed a clear microbial pattern able to discriminate between active and inactive EoE (CE = 8%). Conclusion: Our preliminary data suggest that salivary metabarcoding analysis in combination with machine learning approaches could become a valid, cheap, non‐invasive test to segregate between EoE and non‐EoE patients. Abstract : Comparison between salivary, esophageal and gastric fundus microbioma in patients with eosinophilic esophagitis: the salivary microbioma is confirmed as the best test to segregate EoE patients from non‐EoE patients.