A unique insight for energy metabolism disorders in depression based on chronic unpredictable mild stress rats using stable isotope-resolved metabolomics.
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2020
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Abstract
Depression is currently the main disease which endangers human health and emotion. However, the existing antidepressants have the disadvantages of slowly taking effect and high recurrence rate. Numerous studies have shown that depression causes disorders in energy metabolism, but the specific metabolic pathways remain unclear. The stable isotope-resolved metabolomics (SIRM) can clarify the specific metabolic pathways of energy metabolism disorders in depression and provide a strong basis for the pathogenesis of depression and new targets for the development of new antidepressants. We applied this method to the chronic unpredictable mild stress (CUMS) model, and the metabolites related to energy metabolism were comprehensively analyzed on HILIC and T3 columns through LC-MS. Conventional untargeted metabolomics found 50 differential metabolites, and most of them were focused on the energy metabolism pathway. SIRM exhibited that 78 metabolites related to energy metabolism were labeled, and 28 of them were observed significantly changed in the model group compared with control. Our results revealed depression inhibited TCA cycle and activated gluconeogenesis pathway, and abnormally increased pyruvic acid may participate in pyrimidine biosynthesis, phospholipid synthesis, and amino acid metabolism pathways. Pyruvate carboxylase (PC), pyruvate dehydrogenase (PDH), aspartate aminotransferase (AST) and phosphoenolpyruvate carboxykinase (PEPC) may be the new targets for depression. We established a SIRM method at animal level. To the best of our knowledge, it is the first time to apply the method for the study of depression. The method is of great significance and value for further explaining the pathogenesis of depression and the development of antidepressants.
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linghu2020ajournal
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| Authors | Linghu, Ting;Gao, Yao;Li, Aiping;Shi, Biyun;Tian, Junsheng;Qin, Xuemei; |
| Journal | Journal of pharmaceutical and biomedical analysis |
| Year | 2020 |
| DOI |
S0731-7085(20)31474-6
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