Sjögren's disease & overlap diseases
Discovery of biomarkers for primary Sj ögren’s syndrome based on multi-omics data, construction of diagnostic models, and clinical correlation analysis
Authors' conclusion
This study systematically defines specific metabolic features of pSS, establishes a validated diagnostic model for SNSS, and confirms the close association between metabolic disturbances and clinical heterogeneity.
Study context
- Population
- Patients with Primary Sjogren's syndrome (pSS), including seronegative patients (SNSS), and healthy controls (HC); plasma samples
- Comparison
- pSS vs healthy controls
- Outcome
- Metabolic alterations in pSS vs HC
Methodological detailsuntargeted metabolomic and lipidomic analyses, discovery cohort and independent validation cohort, machine learning-based metabolic model, ROC analysis
- Untargeted metabolomic and lipidomic analyses
- Discovery cohort and independent validation cohort
- Machine learning-based metabolic model
- ROC analysis
Performance
As reported in the abstract
Metabolites significantly altered in pSS (metabolomic analysis)
65
Lipids significantly altered in pSS (lipidomic analysis)
63
Further findings
Association with EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI)
- Biomarkers significantly correlated with ESSDAI
- Seven
Prediction of organ involvement
- AUC for pulmonary involvement
- 0.763
- AUC for hematological involvement
- 0.871
Redox-related metabolites
- Levels significantly associated with age, sex and anti-SSA antibody status
Original publication
Discovery of biomarkers for primary Sj ögren’s syndrome based on multi-omics data, construction of diagnostic models, and clinical correlation analysis. Arthritis Res Ther. Published 29 June 2026. doi:10.
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