Pulmonary hypertension (PH) is associated with high morbidity and mortality with an urgent need for diagnostic and prognostic biomarkers. A training cohort of PH patients, disease controls without PH, and healthy controls was investigated using metabolomics and machine learning. Specific free fatty acid (FFA)/lipid-ratio biomarkers were diagnostic and predictive for PH survival with an area under the curve (AUC) of 0.89. FFA/lipid-ratio performance was independently validated in PH patients from other centers(AUC 0.90). Survival could be predicted in an age-independent manner and a combination with established clinical scores (FPHR4p, COMPERA 2.0) increased the scores hazard risk. Our mechanistic studies in healthy and diseased pulmonary artery endothelial and smooth muscle cells indicate a functional involvement of increased FFA levels in pathophysiology of PH. In conclusion, lipidomic changes in PH can be used as a novel diagnostic and prognostic approach and may help the discovery of new therapeutic targets.

NB, TP disclose that part of this work has been carried out with the K1 COMET Competence Center CBmed, which is funded by the Federal Ministry of Transport, Innovation and Technology; the Federal Ministry of Science, Research and Economy; Land Steiermark (Department 12, Business and Innovation); the Styrian Business Promotion Agency; and the Vienna Business Agency. The COMET program is executed by the Österreichische Forschungsförderungs GmbH FFG. VB is supported by the Austrian Science Foundation (FWF, T1032-B34).