Department of Allergy, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Research Division of Clinical Pharmacology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Front Immunol. 2020 Nov 24;11:559746. doi: 10.3389/fimmu.2020.559746. eCollection 2020.
Allergic rhinitis is a common disorder that affects 10% to 40% of the population worldwide. Allergen immunotherapy (AIT) represents the only therapy that has the potential to resolve clinical symptoms of allergic rhinitis. However, up to 30% of patients do not respond to AIT. Biomarkers predicting the clinical efficacy of AIT as early as possible would significantly improve the patient selection and reduce unnecessary societal costs.
pollen allergic patients who received at least 1-year AIT were enrolled. Clinical responses before and after 1-year AIT were evaluated to determine AIT responders. specific IgE and IgG4 levels were measured by using ImmunoCAP and enzyme-linked immunosorbent assay (ELISA) separately. Stepwise regression analysis was performed to identify which rhinitis-relevant parameters explained the most variability in AIT results. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics was applied to identify the potential candidate biomarkers in the sera of responders and non-responders collected before and after 1-year therapy. The diagnostic performance of the potential biomarkers was then assessed using enzyme-linked immunosorbent assay (ELISA) in 30 responders and 15 non-responders.
specific IgE and IgG4 levels were elevated only in the responders. Regression analysis of allergic rhinitis-relevant parameters provided a robust model that included two most significant variables (sneeze and nasal congestion). Thirteen candidate biomarkers were identified for predicting AIT outcomes. Based on their association with allergy and protein fold change (more than 1.1 or less than 0.9), four proteins were identified to be potential biomarkers for predicting effective AIT. However, further ELISA revealed that only leukotriene A hydrolase (LTAH) was consistent with the proteomics data. The LTAH level in responders increased significantly (P < 0.001) after 1-year therapy, while that of non-responders remained unchanged. Assessment of LTAH generated area under curve (AUC) value of 0.844 (95% confidence interval: 0.727 to 0.962; P < 0.05) in distinguishing responders from the non-responders, suggesting that serum LTAH might be a potential biomarker for predicting the efficiency of AIT.
Serum LTAH may be a potential biomarker for early prediction of an effective AIT.
变应性鼻炎是一种常见疾病,影响全球 10%至 40%的人群。变应原免疫治疗(AIT)代表了唯一有可能解决变应性鼻炎临床症状的治疗方法。然而,多达 30%的患者对 AIT 无反应。预测 AIT 临床疗效的生物标志物可以尽早进行,这将显著改善患者选择,并降低不必要的社会成本。
入组至少接受 1 年 AIT 的花粉过敏患者。评估 1 年 AIT 前后的临床反应,以确定 AIT 应答者。分别使用 ImmunoCAP 和酶联免疫吸附试验(ELISA)测量特异性 IgE 和 IgG4 水平。进行逐步回归分析,以确定哪些鼻炎相关参数能最大程度地解释 AIT 结果的变异性。应用液相色谱-串联质谱(LC-MS/MS)-基于蛋白质组学的方法,在治疗前和治疗 1 年后收集的应答者和无应答者的血清中鉴定潜在的候选生物标志物。然后,在 30 名应答者和 15 名无应答者中使用酶联免疫吸附试验(ELISA)评估潜在生物标志物的诊断性能。
仅在应答者中升高特异性 IgE 和 IgG4 水平。对变应性鼻炎相关参数的回归分析提供了一个包含两个最重要变量(打喷嚏和鼻塞)的稳健模型。鉴定出 13 种候选生物标志物用于预测 AIT 结果。基于它们与过敏的相关性和蛋白折叠变化(大于 1.1 或小于 0.9),鉴定出 4 种蛋白作为预测有效 AIT 的潜在生物标志物。然而,进一步的 ELISA 显示,只有白三烯 A 水解酶(LTAH)与蛋白质组学数据一致。治疗 1 年后,应答者的 LTAH 水平显著升高(P < 0.001),而无应答者的 LTAH 水平保持不变。评估 LTAH 生成的曲线下面积(AUC)值为 0.844(95%置信区间:0.727 至 0.962;P < 0.05),可区分应答者和无应答者,提示血清 LTAH 可能是预测 AIT 疗效的潜在生物标志物。
血清 LTAH 可能是预测 AIT 有效早期的潜在生物标志物。