Biomarker-based clustering identifies distinct pulmonary function trajectories in early systemic sclerosis

Area of Science:

• Immunology
• Pulmonology
• Biomarker Discovery

Background:

• Systemic sclerosis (SSc) is an autoimmune disease with interstitial lung disease (ILD) significantly impacting mortality.
• Chemokines and adhesion molecules are implicated in SSc's inflammatory, vascular, and fibrotic processes.
• Circulating levels of these molecules may reflect disease progression, but their role in predicting pulmonary outcomes is unclear.

Purpose of the Study:

• To investigate if serum chemokine and adhesion molecule profiles can stratify early severe SSc patients into subgroups with distinct pulmonary trajectories.
• To assess the potential utility of these biomarkers for early risk stratification in SSc-ILD.

Main Methods:

• Retrospective analysis of prospectively collected data from early severe SSc patients (n=92).
• Quantification of serum levels for five chemokines and four soluble adhesion molecules at baseline.
• K-means clustering to classify patients based on biomarker profiles.
• Comparison of pulmonary function changes (%VC) among identified clusters.

Main Results:

• Three patient clusters were identified based on biomarker profiles.
• Cluster 1 (elevated sICAM-1, sE-selectin) showed an early but attenuating decline in %VC.
• Cluster 2 (elevated CCL2, CXCL8, sP-selectin) exhibited a progressive decline in %VC.
• Cluster 3 (no distinct pattern) served as a stable reference group.

Conclusions:

• Serum chemokine and adhesion molecule profiles can stratify early severe SSc patients into biologically distinct subgroups.
• These subgroups demonstrate different pulmonary function trajectories, suggesting potential for early risk stratification in SSc-ILD.