Rationale: Pulmonary hypertension (PH) poses a significant health threat. Current biomarkers for PH lack specificity and have poor prognostic capabilities. Objectives: To develop better biomarkers for PH that are useful for patient identification and management. Methods: An explorative analysis was conducted of a broad spectrum of metabolites in patients with PH, healthy control subjects, and diseased control subjects in training and validation cohorts, together with in vitro studies on human pulmonary arteries. Measurements and Main Results: High-resolution mass spectrometry was performed in 233 subjects coupled with machine learning analysis. Histologic and gene expression analysis was conducted, with a focus on lipid metabolism in human pulmonary arteries of idiopathic pulmonary arterial hypertension lungs and assessment of the acute effects of extrinsic fatty acids (FAs). We enrolled a training cohort of 74 patients with PH, 30 diseased control subjects without PH, and 65 healthy control subjects, as well as an independent validation cohort of 64 subjects. Among other metabolites, FAs were significantly increased. Machine learning showed a high diagnostic potential for PH. In addition, we developed fully explainable lipid ratios with exceptional diagnostic accuracy for PH (areas under the curve of 0.89 in the training cohort and 0.90 in the external validation cohort), outperforming machine learning results. These ratios were also prognostic and complemented established clinical markers and scores, significantly increasing their hazard ratios for mortality risk. Idiopathic pulmonary arterial hypertension lungs showed lipid accumulation and altered expression of lipid homeostasis-related genes. In human pulmonary artery smooth muscle and endothelial cells, FAs caused excessive proliferation and barrier dysfunction, respectively. Conclusions: Our metabolomics approach suggests that lipid alterations in PH provide diagnostic and prognostic information, complementing established markers. These alterations may reflect pathologic changes in the pulmonary arteries of patients with PH.
Keywords: biomarker; blood-based test; metabolomics; prognosis; pulmonary hypertension.