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.

中文翻译：

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基于唾液生物标志物、血清自身抗体和 Schirmer 试验的原发性干燥病诊断的非侵入性模型


小唾液腺 （MSG） 活检是原发性干燥症 （pSjD） 分类的一种关键但有创的方法。在这里，我们旨在将唾液蛋白确定为潜在的生物标志物，并建立 pSjD 的非侵入性预测模型。对 pSjD 患者和非干燥对照受试者 （non-pSjD） 的全唾液样本进行液相色谱-串联质谱分析。pSjD 组参与免疫过程的蛋白质如补体 C3 （C3） 、补体因子 B （CFB） 、聚集蛋白 （CLU） 、钙网蛋白 （CALR） 和中性粒细胞弹性蛋白酶 （NE） 上调，ELISA 进一步证实。进行多因素 logistic 回归分析以确定区分 pSjD 和非 pSjD 的标志物;构建受试者工作特征 （ROC） 曲线。在 186 例患者（衍生队列）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 Schirmer 试验的组合的诊断模型，并在 72 例患者 （验证队列） 中进行了重复。在多变量分析中，CFB 、 CLU 和 NE 是 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 Schirmer 试验组合的模型实现了对 pSS 的显著区分。在衍生队列中，ROC 的曲线下面积 （AUC） 为 0.930 （95% CI 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 生物标志物面板可以为 pSjD 的分类提供一种新的非侵入性工具。