Unique Sjögren's syndrome patient subsets defined by molecular features

Area of Science:

• Immunology and Rheumatology
• Genomics and Bioinformatics

Background:

• Primary Sjögren's syndrome (pSS) presents significant heterogeneity, complicating clinical trials and patient care.
• Understanding molecular phenotypes is crucial for stratifying pSS patients.
• Current classification criteria do not fully capture the molecular diversity within pSS.

Purpose of the Study:

• To characterize and cluster patients with primary Sjögren's syndrome (pSS) based on molecular phenotypes.
• To address the heterogeneity that complicates pSS clinical trials and research.
• To identify distinct molecular profiles for potential use in patient stratification.

Main Methods:

• Gene expression microarray data from 47 pSS patients were analyzed to derive correlated transcriptional modules.
• Unbiased random forest modeling was employed to cluster patients based on molecular data.
• Serum cytokines, chemokines, soluble receptors, and autoantibodies (anti-Ro/SSA, anti-La/SSB) were quantified.

Main Results:

• Three distinct molecular clusters of pSS patients were identified based on transcriptional modules.
• Cluster 2 exhibited strong interferon (IFN) and inflammation signatures with elevated IP-10/CXCL10, MIG/CXCL9, BAFF, and LIGHT.
• Cluster 3 showed moderate IFN signatures but suppressed inflammation, with increased IP-10/CXCL10, CXCL13, and trends for MIG/CXCL9, IL-1α, and IL-21.

Conclusions:

• Molecular profiles, including IFN, inflammation, and other signatures, can effectively differentiate pSS patient clusters.
• These distinct molecular signatures may facilitate more precise patient selection for clinical trials.
• Future application of these profiles could guide personalized treatment strategies for pSS.