Diagnosis of pulmonary arterial hypertension (PAH) is difficult due to the lack of specific clinical symptoms and biomarkers, especially at early stages. We compared plasma metabolic fingerprints of PAH patients (n = 20) with matched healthy volunteers (n = 20) using, for the first time, untargeted multiplatform metabolomics approach consisting of high-performance liquid and gas chromatography coupled with mass spectrometry. Multivariate statistical analyses were performed to select metabolites that contribute most to groups’ classification (21 from liquid in both ionization modes and 9 from gas chromatography-mass spectrometry). We found metabolites related to energy imbalance, such as glycolysis-derived metabolites, as well as metabolites involved in fatty acid, lipid and amino acid metabolism. We observed statistically significant changes in threitol and aminomalonic acid in PAH patients, which could provide new biochemical insights into the pathogenesis of the disease. The results were externally validated on independent case and control cohorts, confirming up to 16 metabolites as statistically significant in the validation study. Multiplatform metabolomics, followed by multivariate chemometric data analysis has a huge potential for explaining pathogenesis of PAH and for searching potential and new more specific and less invasive markers of the disease.