Conclusion
Our study uncovers patient-specific transcriptomic patterns in PAH, providing a novel molecular sub-classification strategy. These findings represent a significant step toward personalized molecular diagnostics in PAH and eventual therapeutic interventions for clinically well-defined PAH patients, with potential applications in clinically accessible cell populations such as PBMCs.
Results
hPMECs from PAH patients and controls were exposed to static, low shear stress (LSS), and high shear stress (HSS) conditions, followed by bulk RNA-sequencing. While increasing shear stress resulted in a greater number of differentially expressed genes, traditional grouped analysis showed minimal overall transcriptional differences. Further, pathway enrichment analysis indicated common shear-induced responses in both groups, suggesting that standard analysis methods may mask meaningful disease-specific changes. Crucially, detailed dimensionality reduction analyses revealed pronounced inter-patient variability among PAH donors in response to increasing shear stress, facilitating the identification of 398 genes driving this transcriptional heterogeneity. Unsupervised clustering of these high-variability genes enabled the sub-classification of patients based on their unique transcriptomic profiles, each linked to specific combinations of PAH associated pathogenic pathways such as mesenchymal transition, inflammation, metabolism, extracellular matrix remodeling, and cell cycle/DNA damage signaling. Importantly, re-analysis of published peripheral blood mononuclear cell (PBMC) omics data from PAH patients confirmed the clinical feasibility to utilize these high-variability genes as a non-invasive, accessible approach for molecular patient stratification.