Abstract
BackgroundPost-stroke depression (PSD) is a mood disorder characterized by depression and anhedonia caused by stroke. Metabolomics identified metabolites associated with PSD, but previous studies are based on gas chromatography (GC)/mass spectrometry (MS). This study aimed to perform a liquid chromatography (LC)-MS-based metabolomics study of the plasma metabolite profiles between patients with PSD and controls.MethodsThis was a prospective study of patients with stroke enrolled between July and December 2017 at the Second Affiliated Hospital of Nanchang University. Patients were grouped as Hamilton Depression Rating Scale > 7 (PSD) or < 7 (controls). Metabonomics profiling of plasma sampled was conducted by LC-MS. By combining multivariable and univariable statistical analyses, significant differential metabolites between the two groups were screened. The threshold for significant differences was VIP ≥1 and P < 0.05. Log2FC is the logarithm of the mean ratio between the two groups.ResultsThere were no significant difference with respect to age, NIHSS score, and MMSE between the two groups (all P > 0.05). There were six differential metabolites between the PSD and stroke groups, of which three metabolites were increased and three were decreased. Compared with the control group, p-chlorophenylalanine (Log2FC = 1.37, P = 0.03), phenylacetyl glutamine (Log2FC = 0.21, P = 0.048), and DHA (Log2FC = 0.77, P = 0.01) levels were higher in the PSD group, while betaine (trimethylglycine) (Log2FC = − 0.79, P = 0.04), palmitic acid (Log2FC = − 0.51, P = 0.001), and MHPG-SO4 (Log2FC = − 2.37, P = 0.045) were decreased.ConclusionPlasma metabolomics showed that amino acid metabolism (phenylacetyl glutamine, p-chlorophenylalanine, trimethylglycine), lipid metabolism (DHA, palmitic acid, trimethylglycine), and oxidative stress (DHA, palmitic acid, trimethylglycine) were associated with PSD. These results could help to reveal the pathophysiological mechanism of PSD and eventually identify treatment targets.
Highlights
Post-stroke depression (PSD) is a mood disorder characterized by depression and anhedonia caused by stroke
Zhang et al found that azelaic acid, glyceric acid, pseudouridine, 5-hydroxycaproic acid, tyrosine, and phenylalanine can be used as biomarkers for the diagnosis of PSD [15]
The inclusion criteria for the PSD group were: 1) adult patients with confirmed acute stroke within 24 h after onset by computed tomography (CT) or magnetic resonance imaging (MRI); 2) patients meeting 2014 guidelines for the diagnosis of acute ischemic stroke in China; 3) patients meeting the diagnostic criteria of PSD [1]; 4) Hamilton Depression Rating Scale (HDRS; validated Chinese version [18]) > 7; 5) first-ever onset of stroke; 6) no history of antidepressant drugs; and 7) in the acute stage after stroke (< 1 month)
Summary
Post-stroke depression (PSD) is a mood disorder characterized by depression and anhedonia caused by stroke. Metabolomics identified metabolites associated with PSD, but previous studies are based on gas chromatography (GC)/mass spectrometry (MS). This study aimed to perform a liquid chromatography (LC)-MS-based metabolomics study of the plasma metabolite profiles between patients with PSD and controls. Post-stroke depression (PSD) is characterized by depression or severe depressive episode resulting from stroke, with mania or mixed characteristics [1]. The overall incidence of PSD is 31% at any time within 5 years after stroke. According to the monoamine neurotransmitter imbalance hypothesis, brain damage caused by stroke interferes with ascending projection from the brainstem to the frontal cortex through the thalamus and basal ganglia, which results in reduced bioavailability of serotonin, dopamine, and norepinephrine [3]. Some proinflammatory cytokines may affect the synthesis and metabolism of amine neurotransmitters: interferon (INF)-α can affect the synthesis and reuptake of serotonin [4], and interleukin (IL)-1β and tumor necrosis factor (TNF)-α can activate serotonin transporters to increase serotonin reuptake [5]
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