Abstract

The aim of the study was to investigate differences in metabolic profiles between patients with major depressive disorder (MDD) with full remission (FR) and healthy controls (HCs). A total of 119 age-matched MDD patients with FR (n = 47) and HCs (n = 72) were enrolled and randomly split into training and testing sets. A 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomics approach was used to identify differences in expressions of plasma metabolite biomarkers. Eight metabolites, including histidine, succinic acid, proline, acetic acid, creatine, glutamine, glycine, and pyruvic acid, were significantly differentially-expressed in the MDD patients with FR in comparison with the HCs. Metabolic pathway analysis revealed that pyruvate metabolism via the tricarboxylic acid cycle linked to amino acid metabolism was significantly associated with the MDD patients with FR. An algorithm based on these metabolites employing a linear support vector machine differentiated the MDD patients with FR from the HCs with a predictive accuracy, sensitivity, and specificity of nearly 0.85. A metabolomics-based approach could effectively differentiate MDD patients with FR from HCs. Metabolomic signatures might exist long-term in MDD patients, with metabolic impacts on physical health even in patients with FR.

Highlights

  • The aim of the study was to investigate differences in metabolic profiles between patients with major depressive disorder (MDD) with full remission (FR) and healthy controls (HCs)

  • A significant difference was noted in the Hamilton Depression Rating Scale (HAMD) score between the MDD patients with FR and the HCs in the training group; both scores were within the range of FR (HAMD score ≤ 7)

  • Metabolites significantly differentially‐expressed between the MDD patients with FR and the HCs in the training group. 1H-nuclear magnetic resonance (NMR) spectra obtained from plasma corresponded to 27 known metabolites (Supplementary Table S1)

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Summary

Introduction

The aim of the study was to investigate differences in metabolic profiles between patients with major depressive disorder (MDD) with full remission (FR) and healthy controls (HCs). Cognitive dysfunction, which may hinder functional recovery, is one of the common residual symptoms of depression, and may persist during the remission p­ hase[25] This raises two interesting questions: (1) are there any differences in the metabolic profiles between MDD patients with FR and healthy controls (HCs), and (2) is it possible to establish an algorithm based on metabolites as biomarkers to differentiate MDD patients with FR from HCs?. Recurrence is common in MDD, and investigation of these issues may provide clues as to the recurrence of depression and subsequent prevention of depression

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