Biomarkers in systemic sclerosis: Their potential to predict clinical courses

Area of Science:

• Biomarker discovery and validation in autoimmune diseases.
• Clinical applications of molecular diagnostics in rheumatology.
• Translational research in systemic sclerosis (SSc).

Background:

• Systemic sclerosis (SSc) exhibits significant heterogeneity in clinical features, disease progression, and treatment outcomes.
• The identification of reliable biomarkers is essential for personalized medicine and improved clinical management of SSc patients.
• Current diagnostic and prognostic tools for SSc have limitations, necessitating the search for novel predictive markers.

Purpose of the Study:

• To review current and potential biomarkers for systemic sclerosis (SSc).
• To highlight the utility of SSc-specific autoantibodies in diagnosis and clinical prediction.
• To explore novel serum biomarkers for interstitial lung disease, pulmonary arterial hypertension, fibrosis, and vascular involvement in SSc.

Main Methods:

• Review of existing literature on SSc biomarkers.
• Analysis of findings from multicenter prospective studies, particularly in Japanese early SSc cohorts.
• Evaluation of specific serum markers including glycoprotein, surfactant protein-D, CCL18, natriuretic peptides, and adhesion molecules.

Main Results:

• SSc-specific autoantibodies are valuable for diagnosis and predicting clinical phenotypes.
• Glycoprotein, surfactant protein-D, and CCL18 are promising for SSc-related interstitial lung disease.
• Serum ICAM-1, CXCL8, and P-selectin levels predict respiratory dysfunction and physical disability in early SSc.

Conclusions:

• Biomarkers are critical for managing SSc heterogeneity and guiding clinical practice.
• While SSc autoantibodies are established, further research is needed to identify and validate novel biomarkers.
• Prospective longitudinal studies are essential to confirm the predictive value of emerging biomarkers like ICAM-1, CXCL8, and P-selectin for SSc outcomes.