Zihong Liang

Metabolomic analysis reveals metabolic disturbances in the prefrontal cortex of the lipopolysaccharide-induced mouse model of depression.

Major depressive disorder (MDD) is a debilitating illness. However, the underlying molecular mechanisms of depression remain largely unknown. Increasing evidence supports that inflammatory cytokine disturbances may be associated with the pathophysiology of depression in humans. Systemic administration of lipopolysaccharide (LPS) has been used to study inflammation-associated neurobehavioral changes in rodents, but no metabonomic study has been conducted to assess differential metabolites in the prefrontal cortex (PFC) of a LPS-induced mouse model of depression. Here, we employed a gas chromatography-mass spectrometry-based metabonomic approach in the LPS-induced mouse model of depression to investigate any significant metabolic changes in the PFC. Multivariate statistical analysis, including principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and pair-wise orthogonal projections to latent structures discriminant analysis (OPLS-DA), was implemented to identify differential PFC metabolites between LPS-induced depressed mice and healthy controls. A total of 20 differential metabolites were identified. Compared with control mice, LPS-treated mice were characterized by six lower level metabolites and 14 higher level metabolites. These molecular changes were closely related to perturbations in neurotransmitter metabolism, energy metabolism, oxidative stress, and lipid metabolism, which might be evolved in the pathogenesis of MDD. These findings provide insight into the pathophysiological mechanisms underlying MDD and could be of valuable assistance in the clinical diagnosis of MDD.

Recombinant Tissue Plasminogen Activator Induces Neurological Side Effects Independent on Thrombolysis in Mechanical Animal Models of Focal Cerebral Infarction: A Systematic Review and Meta-Analysis

Background and Purpose Recombinant tissue plasminogen activator (rtPA) is the only effective drug approved by US FDA to treat ischemic stroke, and it contains pleiotropic effects besides thrombolysis. We performed a meta-analysis to clarify effect of tissue plasminogen activator (tPA) on cerebral infarction besides its thrombolysis property in mechanical animal stroke. Methods Relevant studies were identified by two reviewers after searching online databases, including Pubmed, Embase, and ScienceDirect, from 1979 to 2016. We identified 6, 65, 17, 12, 16, 12 and 13 comparisons reporting effect of endogenous tPA on infarction volume and effects of rtPA on infarction volume, blood-brain barrier, brain edema, intracerebral hemorrhage, neurological function and mortality rate in all 47 included studies. Standardized mean differences for continuous measures and risk ratio for dichotomous measures were calculated to assess the effects of endogenous tPA and rtPA on cerebral infarction in animals. The quality of included studies was assessed using the Stroke Therapy Academic Industry Roundtable score. Subgroup analysis, meta-regression and sensitivity analysis were performed to explore sources of heterogeneity. Funnel plot, Trim and Fill method and Egger’s test were obtained to detect publication bias. Results We found that both endogenous tPA and rtPA had not enlarged infarction volume, or deteriorated neurological function. However, rtPA would disrupt blood-brain barrier, aggravate brain edema, induce intracerebral hemorrhage and increase mortality rate. Conclusions This meta-analysis reveals rtPA can lead to neurological side effects besides thrombolysis in mechanical animal stroke, which may account for clinical exacerbation for stroke patients that do not achieve vascular recanalization with rtPA.

Behavioral characterization of CD36 knockout mice with SHIRPA primary screen.

CD36 is a member of the class B scavenger receptor family of cell surface proteins, which plays a major role in fatty acid, glucose and lipid metabolism. Besides, CD36 functions as a microglial surface receptor for amyloid beta peptide. Regarding this, we suggest CD36 might also contribute to neuropsychiatric disease. The aim of this study was to achieve a behavioral phenotype of CD36 knockout (CD36(-/-)) mice. We characterized the behavior of CD36(-/-) mice and C57BL/6J mice by subjecting them to a series of tests, which include SHIRPA primary behavioral screen test, 1% sucrose preference test, elevated plus-maze test, open-field test and forced swimming test. The results showed that CD36(-/-) mice traversed more squares, emitted more defecation, exhibited higher tail elevation and had more aggressive behaviors than C57BL/6J mice. The CD36(-/-) mice spent more time and traveled longer distance in periphery zone in the open-field test. Meanwhile, the numbers that CD36(-/-) mice entered in the open arms of elevated plus-maze were reduced. These findings suggest that CD36(-/-) mice present an anxious phenotype and might be involved in neuropsychiatric disorders.

Quantitative proteomics analysis of the liver reveals immune regulation and lipid metabolism dysregulation in a mouse model of depression.

Major depressive disorder (MDD) is a highly prevalent and debilitating mental illness with substantial impairments in quality of life and functioning. However, the pathophysiology of major depression remains poorly understood. Combining the brain and body should provide a comprehensive understanding of the etiology of MDD. As the largest internal organ of the human body, the liver has an important function, yet no proteomic study has assessed liver protein expression in a preclinical model of depression. Using the chronic unpredictable mild stress (CUMS) mouse model of depression, differential protein expression between CUMS and control (CON) mice was examined in the liver proteome using isobaric tag for relative and absolute quantitation (iTRAQ) coupled with tandem mass spectrometry. More than 4000 proteins were identified and 66 most significantly differentiated proteins were used for further bioinformatic analysis. According to the ingenuity pathway analysis (IPA), we found that proteins related to the inflammation response, immune regulation, lipid metabolism and NFκB signaling network were altered by CUMS. Moreover, four proteins closely associated with these processes, hemopexin, haptoglobin, cytochrome P450 2A4 (CYP2A4) and bile salt sulfotransferase 1 (SULT2A1), were validated by western blotting. In conclusion, we report, for the first time, the liver protein expression profile in the CUMS mouse model of depression. Our findings provide novel insight (liver-brain axis) into the multifaceted mechanisms of major depressive disorder.

GC–MS-based metabolomic study on the antidepressant-like effects of diterpene ginkgolides in mouse hippocampus

Ginkgo biloba extract (GBE), including EGb-761, have been suggested to have antidepressant activity based on previous behavioral and biochemical analyses. However, because GBE contain many constituents, the mechanisms underlying this suggested antidepressant activity are unclear. Here, we investigated the antidepressant-like effects of diterpene ginkgolides (DG), an important class of constituents in GBE, and studied their effects in the mouse hippocampus using a GC-MS-based metabolomics approach. Mice were randomly divided into five groups and injected daily until testing with 0.9% NaCl solution, one of three doses of DG (4.06, 12.18, and 36.54mg/kg), or venlafaxine. Sucrose preference (SPT) and tail suspension (TST) tests were then performed to evaluate depressive-like behaviors in mice. DG (12.18 and 36.54mg/kg) and venlafaxine (VLX) administration significantly increased hedonic behavior in mice in the SPT. DG (12.18mg/kg) treatment also shortened immobility time in the TST, suggestive of antidepressant-like effects. Significant differences in the metabolic profile in the DG (12.18mg/kg) compared with the control or VLX group indicative of an antidepressant-like effect were observed using multivariate analysis. Eighteen differential hippocampal metabolites were identified that discriminated the DG (12.18mg/kg) and control groups. These biochemical changes involved neurotransmitter metabolism, oxidative stress, glutathione metabolism, lipid metabolism, energy metabolism, and kynurenic acid, providing clues to the therapeutic mechanisms of DG. Thus, this study showed that DG has antidepressant-like activities in mice and shed light on the biological mechanisms underlying the effects of diterpene ginkgolides on behavior, providing an important drug candidate for the treatment of depression.

Venlafaxine exerts antidepressant effects possibly by activating MAPK-ERK1/2 and P13K-AKT pathways in the hippocampus.

Serotonin noradrenaline reuptake inhibitors are effective antidepressant drugs, which include venlafaxine and duloxetine. Venlafaxine is commonly used in a clinical context, but the molecular biological mechanisms behind its effects have not been fully determined. Here, we explored the potential biological effects of venlafaxine on mouse hippocampus. Mice were randomly divided into two groups and injected daily with 0.9% NaCl solution or venlafaxine. A GC-MS-based metabolomic approach was used to identify possible metabolic differences between these groups, and the key proteins involved in the relevant pathways were validated by western blotting. In our experiments, 27 hippocampal metabolites that distinguished the venlafaxine group from the control group were identified. These differential metabolites were subjected to Ingenuity Pathway Analysis, which revealed that they were strongly related to two metabolic pathways (MAPK-ERK1/2 and P13K-AKT signaling pathways). Six key proteins, BDNF, p-c-Raf, p-MAPK, p-MEK, p-AKT, and CREB, were verified by western blotting and the results were consistent with the differential metabolites identified by GC-MS. This study sheds light on the biological mechanisms underlying the effects of venlafaxine.

Identification and validation of argininosuccinate synthase as a candidate urinary biomarker for major depressive disorder

BACKGROUND Major depressive disorder (MDD) is a debilitating psychiatric mood disorder. However, no objective laboratory-based test is yet available to aid in the diagnosis of this disorder. METHODS In order to identify urinary protein biomarker candidates for MDD, the differential proteomic analysis of urine samples from first-episode drug-naïve MDD subjects and healthy controls (HC) was carried out by using two-dimensional gel electrophoresis separation followed by MALDI-TOF/TOF-MS/MS identification. Then, the differential expression levels of some candidate proteins were further validated by immunoblot analysis. RESULTS Through mass spectrometry and database searching, a total of 27 differential proteins were identified, primarily including enzymes, plasma proteins, serpins, and adhesion molecules. Five proteins were selected for subsequent validation by Western blotting. One arginine recycling enzyme - argininosuccinate synthase (ASS1) - was further confirmed to be significantly downregulated in the urine of 30 depressed subjects while remaining unchanged in the plasma. Importantly, receiver-operator curve analyses revealed that ASS1 displayed strong efficacy in distinguishing MDD subjects from HC. CONCLUSION The present study provides a range of urinary protein biomarker candidates for MDD, and further demonstrates that ASS1 has a potential for clinical diagnosis of this disorder.

Insight into the metabolic mechanism of Diterpene Ginkgolides on antidepressant effects for attenuating behavioural deficits compared with venlafaxine

Depression is a severe and chronic mental disorder, affecting about 322 million individuals worldwide. A recent study showed that diterpene ginkgolides (DG) have antidepressant-like effects on baseline behaviours in mice. Here, we examined the effects of DG and venlafaxine (VLX) in a chronic social defeat stress model of depression. Both DG and VLX attenuated stress-induced social deficits, despair behaviour and exploratory behaviour. To elucidate the metabolic changes underlying the antidepressive effects of DG and VLX, we investigated candidate functional pathways in the prefrontal cortex using a GC-MS-based metabolomics approach. Metabolic functions and pathways analysis revealed that DG and VLX affect protein biosynthesis and nucleotide metabolism to enhance cell proliferation, with DG having a weaker impact than VLX. Glutamate and aspartate metabolism played important roles in the antidepressant effects of DG and VLX. Tyrosine degradation and cell-to-cell signaling and interaction helped discriminate the two antidepressants. L-glutamic acid was negatively correlated, while hypoxanthine was positively correlated, with the social interaction ratio. Understanding the metabolic changes produced by DG and VLX should provide insight into the mechanisms of action of these drugs and aid in the development of novel therapies for depression.

Brain region-specific metabolite networks regulate antidepressant effects of venlafaxine

Venlafaxine (VLX) is one of the most commonly prescribed clinical antidepressants. Although the initial targets of venlafaxine are known to be neurotransmitter systems, the mechanisms underlying chronic therapeutic effects in different key brain regions have not been fully clarified. In this study, we used depression-related behavior to evaluate the effects of chronic VLX therapy in rats. Gas chromatography-mass spectrometry-based metabolomics was used to characterize metabolomic responses to VLX in the hippocampus and prefrontal cortex. The results demonstrated significant differences in despair behaviors between VLX-treated and control groups of rats, and the metabolic profiles of both the hippocampus and prefrontal cortex were significantly altered after VLX treatment. Furthermore, the altered metabolites had significant brain region specificities, and the altered metabolites in the hippocampus had significant correlations with the despair behaviors. The results obtained from such a metabolic profiling strategy potentially provide a unique perspective on the molecular mechanisms of VLX, and these findings could have important implications for antidepressant drug discovery efforts.

Metabolite-related antidepressant action of diterpene ginkgolides in the prefrontal cortex

Purpose Ginkgo biloba extract (GBE) contains diterpene ginkgolides (DGs), which have been shown to have neuroprotective effects by a number of previous studies. We previously demonstrated part of the action of DG. However, the impact of DG on the prefrontal cortex (PFC) remains unclear. Here, we evaluated the effects of DG and venlafaxine (for comparison) on behavioral and metabolite changes in the PFC using mice models and gas chromatography–mass spectrometry-based metabolomics. Materials and methods Mice were randomly divided into control (saline), DG (12.18 mg/kg) and venlafaxine (16 mg/kg) groups. After 2 weeks of treatment, depression and anxiety-related behavioral tests were performed. Metabolic profiles of the PFC were detected by gas chromatography–mass spectrometry. Results The DG group exhibited positive effects in the sucrose preference test. The differential metabolites were mainly related to amino acid metabolism, energy metabolism and lipid metabolism. The results indicated that the DG group exhibited perturbed lipid metabolism, molecular transport and small-molecule biochemistry in the PFC. Compared with the control group, pathway analysis indicated that venlafaxine and DG had similar effects on alanine, aspartate and glutamate metabolism. Conclusion These findings demonstrate that DG has antidepressant-like, but not anxiolytic-like, effects in mice, suggesting that it might have therapeutic potential for the treatment of major depressive disorder.