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Search for serum biomarkers in patients with bipolar disorder and major depressive disorder using metabolome analysis.
Sun, Xiao-Li; Ma, Li-Na; Chen, Zhen-Zhu; Xiong, Yan-Bing; Jia, Jiao; Wang, Yu; Ren, Yan.
Afiliação
  • Sun XL; Department of Psychiatry, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
  • Ma LN; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Chen ZZ; Department of Psychiatry, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
  • Xiong YB; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Jia J; Department of Psychiatry, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
  • Wang Y; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Ren Y; Department of Psychiatry, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, China.
Front Psychiatry ; 14: 1251955, 2023.
Article em En | MEDLINE | ID: mdl-37736060
ABSTRACT

Objective:

Bipolar disorder (BD) and major depressive disorder (MDD) are two common psychiatric disorders. Due to the overlapping clinical symptoms and the lack of objective diagnostic biomarkers, bipolar disorder (BD) is easily misdiagnosed as major depressive disorder (MDD), which in turn affects treatment decisions and prognosis. This study aimed to investigate biomarkers that could be used to differentiate BD from MDD.

Methods:

Nuclear magnetic resonance (NMR) spectroscopy was performed to assess serum metabolic profiles in depressed patients with BD (n = 59), patients with MDD (n = 14), and healthy controls (n = 10). Data was analyzed using partial least squares discriminant analysis, orthogonal partial least squares discriminant analysis and t-tests. Different metabolites (VIP > 1 and p < 0.05) were identified and further analyzed using Metabo Analyst 5.0 to identify relevant metabolic pathways.

Results:

The metabolic phenotypes of the BD and MDD groups were significantly different from those of the healthy controls, and there were different metabolite differences between them. In the BD group, the levels of 3-hydroxybutyric acid, n-acetyl glycoprotein, ß-glucose, pantothenic acid, mannose, glycerol, and lipids were significantly higher than those in the healthy control group, and the levels of lactate and acetoacetate were significantly lower than those in the healthy control group. In the MDD group, the levels of 3-hydroxybutyric acid, n-acetyl glycoprotein, pyruvate, choline, acetoacetic acid, and lipids were significantly higher than those of healthy controls, and the levels of acetic acid and glycerol were significantly lower than those of healthy controls.

Conclusion:

Glycerolipid metabolism is significantly involved in BD and MDD. Pyruvate metabolism is significantly involved in MDD. Pyruvate, choline, and acetate may be potential biomarkers for MDD to distinguish from BD, and pantothenic acid may be a potential biomarker for BD to distinguish from MDD.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article