Multiple-Cytokine Profiling: A Novel Method for Early Prediction of the Efficacy of Sublingual Immunotherapy in Allergic Rhinitis Patients

多细胞因子谱分析:一种早期预测舌下免疫疗法治疗过敏性鼻炎患者疗效的新方法

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Abstract

BACKGROUND: Allergic rhinitis (AR) is a common inflammatory airway disease, and allergen-specific immunotherapy (AIT) is the only disease-modifying treatment for it. However, not all AR patients respond to AIT, and early prediction of patient response is extremely important. This study aimed to example serum levels of multiple cytokines in AR and explore their association with the efficacy of AIT. METHODS: A total of 74 AR patients treated with sublingual immunotherapy (SLIT) were prospectively recruited. Serum samples were obtained before the onset of SLIT and cytokine levels detected by multiplex analysis. All patients were followed for >1 year, and associations between cytokine levels and the early efficacy of SLIT were evaluated. Significantly distinctive cytokines were further verified in another independent cohort. RESULTS: Sixty patients completed the visit schedule set: 35 patients were put into a responder group and 25 a nonresponder group. Multiple-cytokine profiling showed that cytokine levels differed significantly between the two groups. The responder group had higher concentrations of BAFF and CCL11 and lower levels of CCL2, CCL7, IFNγ, IL8, IL10, IL16, and IL33 than the nonresponder group (P<0.05). Receiver-operating characteristic curves highlighted that serum BAFF, IFNγ, IL10, and IL33 levels were strongly predictive of the efficacy of SLIT (area under the curve <0.7, P<0.05). Serum IL10 and IL33 were overexpressed in nonresponders in the validation cohort. Patients in the responder group exhibited significantly higher IL10 levels and lower IL33 post-SLIT than pre-SLIT (P<0.05), but no statistical difference was found in nonresponders (P<0.05). CONCLUSION: Our data indicated that serum multiple-cytokine profiling was associated with response to SLIT and that IL10 and IL33 might serve as novel biomarkers for early prediction of efficacy and be involved in the therapeutic mechanisms of SLIT in AR patients.

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