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DOI 10.1016/j.jpba.2020.113525

Медицинская библиотека · Journal of pharmaceutical and biomedical analysis · 2020

Application of untargeted lipidomics based on UHPLC-high resolution tandem MS analysis to profile the lipid metabolic disturbances in the heart of diabetic cardiomyopathy mice.

Xu Xuejun, Luo Zichen, He Yu, Shan Jinjun, Guo Jianming, Li Jianping

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Аннотация

Diabetic cardiomyopathy (DCM) is a distinct form of heart disease caused by diabetes. Lipid accumulation has been reported to present in the hearts of DCM animals, however characterization of disordered lipids, and their roles in the etiology and progress of DCM remain largely undefined. In present study, an untargeted lipidomics based on ultra-high performance liquid chromatography coupled with hybrid quadrupole-orbitrap mass spectrometers was established for global detection of lipids in the hearts of DCM mice. DCM mice showed significant cardiac dysfunction with decreased left ventricular fractional shortening (FS) and ratio of peak early filling velocity to atrial filling velocity (MV E/A). Histological lesion, fibrosis, hypertrophy, and lipid accumulation were also observed in the heart of DCM mice. By lipidomics analysis, a total of 244 lipids were identified, of which 89 lipids were significantly changed. The disordered metabolic profile of lipids in DCM mice heart were characterized by the accumulation of triacylglycerol, glycerophospholipid, cholesterol-sulfate, ceramide and sphingomyelin, as well as by the loss of glycerophospholipid. The lipid alterations in the heart were correlated with the development of cardiac dysfunction, lipotoxicity, inflammation and insulin resistance. Correlations between lipid metabolism disorders and DCM progress should be further explored.

Для цитирования: Xu Xuejun, Luo Zichen, He Yu, Shan Jinjun, Guo Jianming, Li Jianping. Application of untargeted lipidomics based on UHPLC-high resolution tandem MS analysis to profile the lipid metabolic disturbances in the heart of diabetic cardiomyopathy mice.. Journal of pharmaceutical and biomedical analysis. 2020. DOI: 10.1016/j.jpba.2020.113525.

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