16S rRNA sequencing-based evaluation of the protective effects of key gut microbiota on inhaled allergen-induced allergic rhinitis.

INTRODUCTION

Allergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize the gut microbiota of patients with AR who are sensitized via inhalation, utilizing 16S rRNA sequencing to shed light on the pathogenesis of AR and identify potential therapeutic targets.

METHODS

To achieve the study's objectives, we compared the microbiota profiles between patients with AR and healthy controls. Microbial diversity was assessed using alpha and beta diversity indices, and differential microbiota populations were identified through Linear discriminant analysis Effect Size (LEfSe) analysis. A Least Absolute Shrinkage and Selection Operator (LASSO) regression model was employed to pinpoint key species. Additionally, PICRUSt2 was utilized to predict the functional pathways associated with these identified species.

RESULTS

The analysis identified a total of 1,122 common species, along with 1,803 species associated with AR and 1,739 species associated with healthy controls. LEfSe analysis revealed 20 significant discrepancies at the genus level. The LASSO regression model identified 8 key genera, including UCG-004 and , which exhibited AUC values exceeding 0.7, indicating strong diagnostic potential. Furthermore, functional pathway analysis suggested that these pivotal species are involved in pathways such as L-lysine biosynthesis and photorespiration, potentially contributing to the pathogenesis of AR.

DISCUSSION

This study identifies critical gut microbiota that could serve as potential biomarkers for allergic rhinitis, providing new insights into its pathogenesis and offering avenues for future therapeutic strategies. Further investigation into these microbiota may lead to enhanced understanding and management of AR.