This study analyzed a lipidomic profile of platelets from blood stasis rats by liquid chromatography‐tandem mass spectrometry. The blood stasis rat was established by low‐dose continuous subcutaneous injection of adrenaline, and the evaluation indexes included hemorheology and platelet aggregation. Principal component analysis and partial least‐squares discriminant analysis were used to analyze platelet lipidomics, and p‐value < 0.05, fold change > 1.5, and variable importance plot > 2 were used to screen potential biomarkers. Then, the biomarkers were optimized by the receiver operating characteristic curve. Compared with the normal rat, the blood stasis model group's whole blood viscosity and platelet aggregation rate were also significantly increased at different shear rates (p < 0.05). Twenty‐four potential lipid biomarkers showed significant changes in platelets between the two groups. Among them, six long‐chain acylcarnitine components and three sphingosine components showed a consistent downward trend, suggesting that these two kinds of components may play an essential role in the process of platelet aggregation. Liquid chromatography‐tandem mass spectrometry‐based lipidomics studies provide much information to understand the pathology of platelets in blood stasis.

Polycythemia vera (PV) is a malignant clonal hematological disease of hematopoietic stem cells characterized by the proliferation of peripheral blood cells, and JAK2 mutation is one of the main causes of PV peripheral blood cell proliferation. Abnormal cell metabolism is a new feature of malignant proliferation of tumor cells, but the role of metabolism in the pathogenesis and prognosis of PV remains unclear. We analyzed metabolic differences of peripheral blood sera between 32 PV patients and 20 healthy controls (HCs) by liquid chromatography–mass spectrometry (LC–MS) to investigate their relationship with cell proliferation and to screen for prognosis-related metabolic biomarkers. Compared to HC, 33 endogenous metabolites were significantly changed in PV and were involved in fatty acid metabolism, glucose metabolism, sphingolipid metabolism, and amino acid metabolism pathways. Among them, seven metabolites were closely associated with JAK2 mutations, 2 of which may contribute to the proliferation of peripheral blood cells in PV patients. A set of potential prognostic metabolic biomarkers containing four metabolites was identified by a receiver operating characteristic (ROC) curve according to the risk stratification of the PV patients and their combined AUC value of 0.952, with a sensitivity of 90.905% and specificity of 90.909% at the optimal cutoff point. Metabonomics is an important tool for the study of the pathogenesis of PV and the relationship between JAK2 gene mutation. Furthermore, the potential biomarkers of this study may provide a reference for the prognosis of PV.