Gut microbiota-based prediction of clinical response to sublingual immunotherapy in Artemisia pollen-induced allergic rhinitis: A prospective cohort study

Wang, Fei and Yang, Jinjin and Bao, Liming and Ya'nan, and Jin, Bat (2026) Gut microbiota-based prediction of clinical response to sublingual immunotherapy in Artemisia pollen-induced allergic rhinitis: A prospective cohort study. ACTA MICROBIOLOGICA ET IMMUNOLOGICA HUNGARICA, 73 (1). pp. 33-44. ISSN 1217-8950

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Abstract

The gut microbiota plays a crucial role in modulating mucosal immunity and allergic responses, yet its predictive value for sublingual immunotherapy (SLIT) outcomes remains underexplored in Artemisia pollen-induced allergic rhinitis (AR). In this single-center prospective cohort study, 204 adults with Artemisia pollen-induced AR underwent baseline stool collection before initiating standardized SLIT. Gut microbiota was analyzed using 16S rRNA sequencing of the V3–V4 region, with prespecified features including Shannon diversity index, composite abundance of butyrate-producing bacteria (Faecalibacterium, Roseburia, Eubacterium rectale group), and Prevotella-to-Bacteroides (P/B) ratio. Clinical response was defined as ≥30% reduction in combined symptom-medication score (CSMS) during the peak pollen season. We developed three prediction models: Model A (clinical variables only), Model B (clinical variables plus microbiota features), and Model C (parsimonious model via L1 regularization). The response rate was 54.41% (111/204). In multivariable analysis, all three microbiota features independently predicted treatment response: butyrate-producing bacteria (OR = 1.59, q = 0.006), P/B ratio (OR = 1.43, q = 0.020), and Shannon diversity (OR = 1.33, q = 0.046). Model B demonstrated superior discrimination compared to Model A (AUC 0.79 vs 0.71, ΔAUC = 0.08, P = 0.021), with improved calibration (intercept α = −0.03, slope β = 0.98) and significant net reclassification improvement (NRI = 0.36, P = 0.002). Decision curve analysis confirmed greater net benefit across clinically relevant threshold probabilities. The parsimonious Model C maintained good performance (optimism-corrected AUC = 0.78) with 77.48% sensitivity and 72.04% specificity. Baseline gut microbiota characteristics, particularly butyrate-producing bacterial abundance, microbial diversity, and Prevotella/Bacteroides community structure, significantly predict SLIT response in Artemisia pollen-induced AR and provide substantial incremental value over conventional clinical parameters. These findings support the integration of gut microbiota assessment into pretreatment stratification algorithms for allergen immunotherapy.

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