Non-invasive diagnosis of primary Sjögren's syndrome using ultrasonography and transcriptome biomarkers

Abstract

Diagnosing primary Sjögren's syndrome (pSS) is difficult due to clinical heterogeneity and the absence of non-invasive specific biomarkers. To develop non-invasive pSS diagnosis methods that integrate classic clinical indexes, major salivary gland ultrasonography (SGUS), and gene expression profiles shared by labial gland and peripheral blood, we conducted a study on a cohort of 358 subjects. We identified differentially expressed genes (DEGs) in glands and blood that were enriched in defense response to virus and type I interferon production pathways. Four upregulated DEGs common in glands and blood were identified as hub genes based on the protein-protein interaction networks. A random forest model was trained using features, including SGUS, anti-SSA/Ro60, keratoconjunctivitis sicca tests, and gene expression levels of MX1 and RSAD2. The model achieved comparable pSS diagnosis accuracy to the golden standard method based on labial gland biopsy. Our findings implicate this novel model as a promising diagnosis technique of pSS.