Gotoh Minoru, Kaminuma Osamu, Nakaya Akihiro, Katayama Kazufumi, Motoi Yuji, Watanabe Nobumasa, Saeki Mayumi, Nishimura Tomoe, Kitamura Noriko, Yamaoka Kazuko, Okubo Kimihiro, Hiroi Takachika
Allergy and Immunology Project, Tokyo Metropolitan Institute of Medical Science, 2-1-6, Kamikitazawa, Setagaya-ku, Tokyo 156-8506, Japan.
Department of Otorhinolaryngology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, Tokyo 113-8603, Japan.
Int Immunol. 2017 Jun 1;29(6):291-300. doi: 10.1093/intimm/dxx034.
Sublingual immunotherapy (SLIT) is effective against allergic rhinitis, although a substantial proportion of individuals is refractory. Herein, we describe a predictive modality to reliably identify SLIT non-responders (NRs). We conducted a 2-year clinical study in 193 adult patients with Japanese cedar pollinosis, with biweekly administration of 2000 Japanese allergy units of cedar pollen extract as the maintenance dose. After identifying high-responder (HR) patients with improved severity scores and NR patients with unchanged or exacerbated symptoms, differences in 33 HR and 34 NR patients were evaluated in terms of peripheral blood cellular profiles by flow cytometry and serum factors by ELISA and cytokine bead array, both pre- and post-SLIT. Improved clinical responses were seen in 72% of the treated patients. Pre-therapy IL-12p70 and post-therapy IgG1 serum levels were significantly different between HR and NR patients, although these parameters alone failed to distinguish NR from HR patients. However, the analysis of serum parameters in the pre-therapy samples with the Adaptive Boosting (AdaBoost) algorithm distinguished NR patients with high probability within the training data set. Cluster analysis revealed a positive correlation between serum Th1/Th2 cytokines and other cytokines/chemokines in HR patients after SLIT. Thus, processing of pre-therapy serum parameters with AdaBoost and cluster analysis can be reliably used to develop a prediction method for HR/NR patients.
舌下免疫疗法（SLIT）对过敏性鼻炎有效，尽管有相当一部分个体对此疗法无效。在此，我们描述了一种预测方法，以可靠地识别SLIT无反应者（NRs）。我们对193名成年日本雪松花粉症患者进行了一项为期2年的临床研究，每两周给予2000日本过敏单位的雪松花粉提取物作为维持剂量。在确定症状严重程度评分改善的高反应者（HR）患者和症状未改变或加重的NR患者后，通过流式细胞术评估33名HR患者和34名NR患者外周血细胞谱的差异，并通过ELISA和细胞因子珠阵列评估SLIT前后血清因子的差异。72%的治疗患者出现了临床反应改善。HR患者和NR患者治疗前的IL-12p70和治疗后的IgG1血清水平存在显著差异，尽管仅这些参数无法区分NR患者和HR患者。然而，使用自适应增强（AdaBoost）算法对治疗前样本中的血清参数进行分析，在训练数据集中能够以较高概率区分出NR患者。聚类分析显示，SLIT后HR患者血清Th1/Th2细胞因子与其他细胞因子/趋化因子之间呈正相关。因此，使用AdaBoost处理治疗前血清参数并进行聚类分析，可可靠地用于开发HR/NR患者的预测方法。
