Zhang Xinwei, Liao Zhangdi, Chen Yangchun, Lu Huiqin, Wang Aodi, Shi Yingying, Zhang Qi, Wang Ying, Li Yan, Lan Jingying, Chen Chubing, Deng Chaoqiong, Zhuang Wuwei, Liu Lingyu, Qian Hongyan, Chen Shiju, Li Zhibin, Shi Guixiu, Liu Yuan
Department of Rheumatology and Clinical Immunology, School of Medicine, The First Affiliated Hospital of Xiamen University, Xiamen University, 55 Zhenhai Road, Xiamen, XM, 361000, China.
Xiamen Municipal Clinical Research Center for Immune Diseases, Xiamen, XM, 361000, China.
Arthritis Res Ther. 2024 Dec 19;26(1):217. doi: 10.1186/s13075-024-03459-7.
Minor salivary gland (MSG) biopsy is a critical but invasive method for the classification of primary Sjögren's disease (pSjD). Here we aimed to identify salivary proteins as potential biomarkers and to establish a non-invasive prediction model for pSjD.
Liquid chromatography-tandem mass spectrometry was conducted on whole saliva samples from patients with pSjD and non-Sjögren control subjects (non-pSjD). Proteins involved in immune processes were upregulated in the pSjD group, such as complement C3 (C3), complement factor B (CFB), clusterin (CLU), calreticulin (CALR), and neutrophil elastase (NE), which were further confirmed by ELISA. Multivariate logistic regression analyses were performed to identify markers that differentiated pSjD from non-pSjD; receiver operating characteristic (ROC) curves were constructed. A diagnostic model based on the combination of salivary biomarkers (CFB, CLU, and NE), serum autoantibodies (anti-SSA /Ro60 and anti-SSA/Ro52), and Schirmer's test was evaluated in 186 patients (derivation cohort) with replication in 72 patients (validation cohort).
In multivariate analyses, CFB, CLU, and NE were independent predictors of pSS. A model based on the combination of salivary biomarkers (CFB, CLU, and NE), serum autoantibodies (anti-SSA and anti-Ro52), and Schirmer's test achieved significant discrimination of pSS. In the derivation cohort, the area under curve (AUC) of the ROC was 0.930 (95% CI 0.877-0.965, P < 0.001), with a sensitivity and specificity of 84.85% and 92.45%, respectively. Notably, similar results were obtained in a validation cohort.
The 6-biomarker panel could provide a novel non-invasive tool for the classification of pSjD.
小唾液腺（MSG）活检是原发性干燥综合征（pSjD）分类的关键但具有侵入性的方法。在此，我们旨在鉴定唾液蛋白作为潜在生物标志物，并建立pSjD的非侵入性预测模型。
对pSjD患者和非干燥综合征对照受试者（非pSjD）的全唾液样本进行液相色谱 - 串联质谱分析。参与免疫过程的蛋白质在pSjD组中上调，如补体C3（C3）、补体因子B（CFB）、簇集素（CLU）、钙网蛋白（CALR）和中性粒细胞弹性蛋白酶（NE），这些通过酶联免疫吸附测定（ELISA）进一步证实。进行多变量逻辑回归分析以鉴定区分pSjD与非pSjD的标志物；构建受试者工作特征（ROC）曲线。在186例患者（推导队列）中评估了基于唾液生物标志物（CFB、CLU和NE）、血清自身抗体（抗SSA /Ro60和抗SSA/Ro52）和施默试验组合的诊断模型，并在72例患者（验证队列）中进行了重复验证。
在多变量分析中，CFB、CLU和NE是原发性干燥综合征（pSS）的独立预测因子。基于唾液生物标志物（CFB、CLU和NE）、血清自身抗体（抗SSA和抗Ro52）和施默试验组合的模型对pSS具有显著的鉴别能力。在推导队列中，ROC曲线下面积（AUC）为0.930（95%可信区间0.877 - 0.965，P < 0.001），敏感性和特异性分别为84.85%和92.45%。值得注意的是，在验证队列中获得了类似的结果。
6种生物标志物组合可为pSjD的分类提供一种新型非侵入性工具。
