Tang Yi, She Yongchuan, Chen Danping, Zhou Yibo, Xie Dan, Liu Zhai
Changsha Hospital of Traditional Chinese Medicine (Changsha Eighth Hospital), Changsha, China.
Front Microbiol. 2025 Jan 9;15:1497262. doi: 10.3389/fmicb.2024.1497262. eCollection 2024.
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.
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.
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.
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.
变应性鼻炎（AR）是一种常见的呼吸系统疾病，其发病机制受多种因素影响。最近的研究开始强调肠道微生物群在免疫调节中的重要作用及其与AR发生发展的潜在关联。本研究旨在通过16S rRNA测序对经吸入致敏的AR患者的肠道微生物群进行特征分析，以阐明AR的发病机制并确定潜在的治疗靶点。
为实现本研究目标，我们比较了AR患者和健康对照者的微生物群谱。使用α和β多样性指数评估微生物多样性，并通过线性判别分析效应大小（LEfSe）分析确定差异微生物种群。采用最小绝对收缩和选择算子（LASSO）回归模型来确定关键物种。此外，利用PICRUSt2预测与这些已鉴定物种相关的功能途径。
分析共鉴定出1122个常见物种，以及1803个与AR相关的物种和1739个与健康对照相关的物种。LEfSe分析揭示了属水平上的20个显著差异。LASSO回归模型确定了8个关键属，包括UCG-004等，其AUC值超过0.7，表明具有较强的诊断潜力。此外，功能途径分析表明，这些关键物种参与L-赖氨酸生物合成和光呼吸等途径，可能与AR的发病机制有关。
本研究确定了可作为变应性鼻炎潜在生物标志物的关键肠道微生物群，为其发病机制提供了新见解，并为未来的治疗策略提供了途径。对这些微生物群的进一步研究可能会增进对AR的理解和管理。
