Cluster analysis reveals three clinical phenotypes of pulmonary artery hypertension associated with connective tissue diseases: insights into inflammation and immunity

Abstract

Inflammation and immune mechanisms play a crucial role in connective tissue disease-associated pulmonary arterial hypertension (CTD-PAH), though they remain inadequately understood. This study aimed to identify specific clinical phenotypes in CTD-PAH using inflammatory and immune markers through hierarchical cluster analysis. We conducted a single-center, retrospective cohort study of CTD-PAH patients from 2009 to 2024. Clinical variables, including neutrophil lymphocyte ratio (NLR), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and complement C3 and C4, were analyzed to form clusters based on baseline characteristics, clinical outcomes, and treatment goals. Among 184 patients (95.1% female; median age 40.42 years), three distinct clusters were identified: Cluster 1 (vasculopathic phenotype) exhibited lower inflammatory activity but worse hemodynamic outcomes; Cluster 2 (vasculitic phenotype) had higher inflammatory activity with favorable hemodynamics; Cluster 3 (mixed phenotype) showed active inflammation and poor hemodynamic status. Most vasculitic patients were classified as systemic lupus erythematosus-associated PAH (SLE-PAH), which had a shorter course and higher prevalence of autoantibodies. The vasculopathic and mixed phenotypes were common in scleroderma-related PAH (SSc-PAH), undifferentiated CTD- related PAH (UCTD-PAH), and mixed CTD- related PAH (MCTD-PAH), associated with poorer treatment outcomes and survival rate. Distinct clinical phenotypes in CTD-PAH correlate with inflammatory activity and hemodynamic status, influencing treatment responses and prognosis. Inflammation and immune mechanisms are essential for the development of CTD-PAH. Three distinct phenotypes in CTD-PAH were identified through cluster analysis. Distinct phenotypes correlate with inflammatory and hemodynamic status, influencing treatment responses and prognosis. Identifying disease phenotypes might improve the management algorithm for CTD-PAH.