Metabolomics analysis of saliva from patients with primary Sjögren's syndrome

Abstract

The recent development of salivary proteomics has led to the identification of potential biomarkers for diagnosing patients with primary Sjögren's syndrome (pSS). Here we sought to identify differentially produced salivary metabolites from pSS patients and healthy controls (HCs) that might be used to characterize this disease. We obtained salivary samples from 12 female pSS patients (mean age 44.2 ± 13.01) and 21 age-matched female HCs. The metabolite profiles of saliva were analysed by gas chromatography-mass spectrometry. The total metabolite levels in each of the samples were calculated and compared across the study participants. A total of 88 metabolites were detected across the study samples, 41 of which were observed at reduced levels in the samples from pSS patients. Principal component analysis (PCA) revealed a loss in salivary metabolite diversity in the pSS patient samples compared to the HC samples. The reduced presence of glycine, tyrosine, uric acid and fucose, which may reflect salivary gland destruction due to chronic sialoadenitis, contributed to the loss of diversity. Comparative PCA of the pSS patients revealed the presence of two subpopulations based on their metabolite profiles, and these two subpopulations showed a significant difference in the prevalence of major salivary glanditis (P = 0.014). In this study, we found that the salivary metabolite profile of pSS patients was less diverse than that of HCs and that the metabolite profiles in pSS patients were affected by the presence of major salivary glanditis.

Keywords: Sjögren's syndrome; major salivary glanditis; metabolomics; saliva.

Figure 1

Principal component analysis (PCA) analysis of salivary metabolites. (a) Plot analysis of healthy controls (HC) (◻) and primary Sjögren's syndrome (pSS) (●) PCA scores (PC1 = 0·431, PC2 = 0·192). (b) Loading plot from the PCA analysis comparing salivary metabolite production differences between pSS patients and HCs. (c) PCA analysis of pSS patient scores revealed the presence of two distinct pSS subgroups (PC1 = 0·333, PC2 = 0·297).