Lipidomics for diagnosis and prognosis of pulmonary hypertension
- 1. Medical University of Graz, Department of Dermatology and Venereology, Graz, Austria
- 2. Ludwig Boltzmann Institute for Lung Vascular Research, Graz, Austria
- 3. Institute for Biomedical Research and Technologies (HEALTH), Joanneum Research Forschungsgesellschaft m.b.H, Graz, Austria
- 4. School of Informatics, Communications, and Media, University of Applied Sciences Upper Austria, Hagenberg, Austria
- 5. Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
- 6. Clinic of Pulmonology, University and University Hospital of Zurich, Switzerland
- 7. Department of Internal Medicine II, Pulmonology and Critical Care, Kreisklinik Bad Reichenhall, Bad Reichenhall, Germany
- 8. Department of Thoracic Surgery, Medical University of Vienna, Austria
- 9. Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz
Description
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.
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- Preprint: 10.1101/2023.05.17.23289772 (DOI)