A non-invasive model for diagnosis of primary Sjogren’s disease based on salivary biomarkers, serum autoantibodies, and Schirmer’s test
Abstract Background 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. Methods Liquid chromatogr...
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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-12-01
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| Series: | Arthritis Research & Therapy |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13075-024-03459-7 |
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| Summary: | Abstract Background 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. Methods 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). Results 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. Conclusion The 6-biomarker panel could provide a novel non-invasive tool for the classification of pSjD. |
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| ISSN: | 1478-6362 |