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Background: Major depressive disorder (MDD) is a psychiatric disorder caused by various etiologies. Chronic stress models are used to simulate the heterogeneous pathogenic processes of depression. However, few studies have compared transcriptional features between stress models and MDD patients.Methods: We generated hippocampal transcriptional profiles of the chronic social defeat model by RNA sequencing and downloaded raw data of the same brain region from public databases of the chronic unpredictable mild stress model, the learned helplessness model, and MDD patients. Differential expression and gene co-expression analyses were integrated to compare transcriptional features between stress models and MDD patients.Results: Each stress model shared 11.4% to 16.3% of differentially expressed genes with MDD patients. Functional analysis at the gene expression level identified altered ensheathment of neurons in both stress models and MDD patients. At the gene network level, each stress model shared 20.9% to 41.6% of co-expressed genes with MDD patients. Functional analysis based on these genes found that axon guidance signaling is the most significantly enriched pathway that was shared by all stress models and MDD patients.Limitations: This study was limited by considering only a single brain region and a single sex of stress model animals.Conclusions: Our results show that hippocampal transcriptional features of stress models partially overlap with those of MDD patients. The canonical pathways of MDD patients, including ensheathment of neurons, PTEN signaling, and axonal guidance signaling, were shared with all stress models. Our findings provide further clues to understand the molecular mechanisms of depression. [ABSTRACT FROM AUTHOR]

• The transcriptome characteristics of CSDS were more focused on neuronal and synapse. • The transcriptome characteristics of FMT were more focused on inflammation. • The common transcriptome characteristics of two models was energy metabolism. • The CSDS had large more alternative splicing events than FMT. Depression is a complex disorder with multiple contributing factors, and chronic stress has previously been recognized as a major causative factor, while gut microbes have also been found to be involved in depression recently. However, gene expression in depression models with different etiologies is unclear. Here, we compared the transcriptomes of the striatum in chronic social defeat stress (CSDS) model of C57BL/6J male mice and fecal microbiota transplant (FMT) model of Kumming male mice. We found that the proportion of shared differentially expressed genes (DEGs) between the two models was only 24 %. The specific DEGs of FMT model were enriched in immune and inflammatory, and are associated with changes in vascular and ciliated ependymal cells. The specific DEGs of CSDS model were enriched in neuron and synapse. The results of network analysis suggested the expression patterns and biological function of depressive-like behaviors-related modules in the two models are different. Further, the alternative splicing events of CSDS are more than FMT. Our results suggested models of depression induced by different etiologies differ significantly in gene expression and biological function. Our study also suggested us to pay attention to the characteristics of models of depression of different etiologies and provided a more comprehensive understanding of the heterogeneity of depression. [ABSTRACT FROM AUTHOR]

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16 S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response. [ABSTRACT FROM AUTHOR]

Depression is a serious mental illness, but the molecular mechanisms of depression remain unclear. Previous research has reported metabolomic changes in the blood of patients with depression, while integrated analysis based on these altered metabolites was still lacking. The objective of this study was to integrate metabolomic changes to reveal the underlying molecular alternations of depression. We retrieved altered metabolites in the blood of patients with depression from the MENDA database. Pathway analysis was conducted to explore enriched pathways based on candidate metabolites. Pathway crosstalk analysis was performed to explore potential correlations of these enriched pathways, based on their shared candidate metabolites. Moreover, potential interactions of candidate metabolites with other biomolecules such as proteins were assessed by network analysis. A total of 854 differential metabolite entries were retrieved in peripheral blood of patients with depression, including 555 unique candidate metabolites. Pathway analysis identified 215 significantly enriched pathways, then pathway crosstalk analysis revealed that these pathways were clustered into four modules, including amino acid metabolism, nucleotide metabolism, energy metabolism and others. Additionally, eight molecular networks were identified in the molecular network analysis. The main functions of these networks involved amino acid metabolism, molecular transport, inflammatory responses and others. Based on integrated analysis, our study revealed pathway-based modules and molecular networks associated with depression. These results will contribute to the underlying knowledge of the molecular mechanisms in depression. [ABSTRACT FROM AUTHOR]

The gut-brain axis has been shown to play an important role in depression. However, few studies have examined proteomic changes in the intestine of the nonhuman primate model of depression. We investigated the intestinal proteome of macaques (Macaca fascicularis) with depression-like (DL) behaviors by data-independent acquisition techniques. We also performed integration analyses of proteomic changes, previous metabolomic and microbiotic data. Moreover, we confirmed the gene expressions of key proteins. Sixty-five differentially expressed proteins (DEPs) were identified, of which fifty-four DEPs were down-regulated and the others were altered conversely in DL macaques compared with the control group. Pathway analysis indicated that mitochondrial function and energy metabolism were representative functions of DEPs. The key DEPs were significantly associated with glycerophospholipid metabolism and imbalances of gut microbe. We confirmed that key molecules (NDUFB4, UQCR10, PISD) were significantly inhibited, which may disturb the energy transformation of the electron respiratory chain and the homeostasis of the mitochondrial membrane. Further research is warranted to determine the effects of depression on other peripheral organs. These findings suggest the functional disorder of intestinal mitochondria in DL macaques. The disturbances of glycerophospholipid metabolism and gut microbiota may exacerbate disruptions of energy metabolism. Taking together, our study provides new clues to the relationship between depression and intestinal proteome. • This is the first study to identify intestinal proteomics in a non-human primate model of depression. • Depressive states significantly affect intestinal homeostasis, with mitochondrial dysfunction being the most prominent alteration. • In depressed states, alterations in intestinal mitochondrial function are focused on the electron respiratory chain and the synthesis of phosphatidylethanolamine. • Disturbances in glycerophospholipid metabolism and changes in the microbiota synergistically affect energy metabolism in the intestine under depressed states. [ABSTRACT FROM AUTHOR]

Background: Schizophrenia (SCZ) is a serious psychiatric disorder. Metabolite disturbance is an important pathogenic factor in schizophrenic patients. In this study, we aim to identify plasma lipid and amino acid biomarkers for SCZ using targeted metabolomics. Methods: Plasma from 76 SCZ patients and 50 matched controls were analyzed using the LC/MS‐based multiple reaction monitoring (MRM) metabolomics approach. A total of 182 targeted metabolites, including 22 amino acids and 160 lipids or lipid‐related metabolites were observed. We used binary logistic regression analysis to determine whether the lipid and amino acid biomarkers could discriminate SCZ patients from controls. The area under the curve (AUC) from receiver operation characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the biomarkers panel. Results: We identified 19 significantly differentially expressed metabolites between the SCZ patients and the controls (false discovery rate < 0.05), including one amino acid and 18 lipids or lipid‐related metabolites. The binary logistic regression‐selected panel showed good diagnostic performance in the drug‐naïve group (AUC = 0.936) and all SCZ patients (AUC = 0.948), especially in the drug‐treated group (AUC = 0.963). Conclusions: Plasma lipids and amino acids showed significant dysregulation in SCZ, which could effectively discriminate SCZ patients from controls. The LC/MS/MS‐based approach provides reliable data for the objective diagnosis of SCZ. [ABSTRACT FROM AUTHOR]

• Comparison of blood VEGF levels in MDD, SCZ, and BD based on data from 44 studies. • No significant differences were found between MDD, SCZ, BDd, BDe, BDm, and HC. • VEGF levels detected by ELISA may be used to distinguish MDD and SCZ. • VEGF levels may be increased in medication-treated MDD compared with controls. The peripheral levels of vascular endothelial growth factor (VEGF) have been studied in major psychiatric diseases compared with healthy controls (HCs), but the results were inconsistent. Moreover, few studies have compared VEGF levels between these psychiatric diseases. The aim of the present study was to compare blood VEGF levels in major depressive disorder (MDD), schizophrenia (SCZ), bipolar disorder either in a manic episode, a depressive episode, or a euthymic state, and HC. We supposed that VEGF levels may be elevated in some of these diseases as a potential biomarker. In this study, forty-four studies with 6343 participants were included, and network meta-analysis was used to synthesize evidence from both direct and indirect comparisons. The main analysis showed that no significant differences were found between these groups. Subgroup analysis found that patients with MDD may have higher blood VEGF levels than patients with SCZ when the levels were measured through ELISA, and VEGF levels were increased in medication-treated MDD patients compared with HCs. Taken together, blood VEGF levels may be unaltered in these psychiatric disorders, while detection of VEGF in blood by ELISA may a feasible way to distinguish MDD and SCZ. Further replicated studies with larger samples are needed. [ABSTRACT FROM AUTHOR]

Background: Our understanding of the molecular mechanisms of depression remains largely unclear. Previous studies have shown that the prefrontal cortex (PFC) is among most important brain regions that exhibits metabolic changes in depression. A comprehensive analysis based on candidate metabolites in the PFC of animal models of depression will provide valuable information for understanding the pathogenic mechanism underlying depression. Methods: Candidate metabolites that are potentially involved in the metabolic changes of the PFC in animal models of depression were retrieved from the Metabolite Network of Depression Database. The significantly altered metabolic pathways were revealed by canonical pathway analysis, and the relationships among altered pathways were explored by pathway crosstalk analysis. Additionally, drug-associated pathways were investigated using drug-associated metabolite set enrichment analysis. The interrelationships among metabolites, proteins, and other molecules were analyzed by molecular network analysis. Results: Among 88 candidate metabolites, 87 altered canonical pathways were identified, and the top five ranked pathways were tRNA charging, the endocannabinoid neuronal synapse pathway, (S)-reticuline biosynthesis II, catecholamine biosynthesis, and GABA receptor signaling. Pathway crosstalk analysis revealed that these altered pathways were grouped into three interlinked modules involved in amino acid metabolism, nervous system signaling/neurotransmitters, and nucleotide metabolism. In the drug-associated metabolite set enrichment analysis, the main enriched drug pathways were opioid-related and antibiotic-related action pathways. Furthermore, the most significantly altered molecular network was involved in amino acid metabolism, molecular transport, and small molecule biochemistry. Conclusions: This study provides important clues for the metabolic characteristics of the PFC in depression. [ABSTRACT FROM AUTHOR]

Depression is a seriously disabling psychiatric disorder with a significant burden of disease. Metabolic abnormalities have been widely reported in depressed patients and animal models. However, there are few systematic efforts that integrate meaningful biological insights from these studies. Herein, available metabolic knowledge in the context of depression was integrated to provide a systematic and panoramic view of metabolic characterization. After screening more than 10 000 citations from five electronic literature databases and five metabolomics databases, we manually curated 5675 metabolite entries from 464 studies, including human, rat, mouse and non-human primate, to develop a new metabolite-disease association database, called MENDA (http://menda.cqmu.edu.cn:8080/index.php). The standardized data extraction process was used for data collection, a multi-faceted annotation scheme was developed, and a user-friendly search engine and web interface were integrated for database access. To facilitate data analysis and interpretation based on MENDA, we also proposed a systematic analytical framework, including data integration and biological function analysis. Case studies were provided that identified the consistently altered metabolites using the vote-counting method, and that captured the underlying molecular mechanism using pathway and network analyses. Collectively, we provided a comprehensive curation of metabolic characterization in depression. Our model of a specific psychiatry disorder may be replicated to study other complex diseases. [ABSTRACT FROM AUTHOR]

Background: Major depressive disorder (MDD) is a complex psychiatric illness involving multiple brain regions. Increasing evidence indicates that the striatum is involved in depression, but the molecular mechanisms remain unclear. Methods: In this study, we performed a gas chromatography–mass spectrometer (GC/MS)-based metabolomic analysis in the striatum of depressed rats induced by chronic unpredictable mild stress (CUMS). We then compared striatal data with our previous data from the hippocampus and cerebellum to systematically investigate the potential pathogenesis of depression. Results: We identified 22 differential metabolites in the striatum between the CUMS and control groups; these altered metabolites were mainly involved in amino acid, carbohydrate, and nucleotide metabolism. Pathway analysis revealed that the shared metabolic pathways of the striatum, hippocampus, and cerebellum were mainly involved in the glutamine–glutamate metabolic system. Four genes in the striatum (GS, GLS2, GLT1, and SSADH), six genes in the hippocampus (GS, SNAT1, GAD1, SSADH, VGAT, and ABAT), and five genes in the cerebellum (GS, ABAT, SNAT1, VGAT, and GDH) were found to be significantly altered using RT-qPCR. Correlation analysis indicated that these differential genes were strongly correlated. Conclusion: These results suggest that chronic stress might induce depressive behaviors by disturbing the glutamine–glutamate–GABA cycle in the striatum, hippocampus, and cerebellum, and that the glutamine–glutamate–GABA cycle among these three brain regions might generate cooperative action in response to chronic stress. [ABSTRACT FROM AUTHOR]

High workloads and heavy academic pressure can have significant implications for the risk for depression and poor quality of life (QoL). This study aimed to investigate QoL and depressive symptoms in medical students undergoing postgraduate neurology specialty training in China. The survey covered demographic characteristics, the 8-itemMedical Outcomes Study Short-Formquestionnaire (SF-8), and the 2-itemPrimary Care Evaluation of Mental Disorders depression screening tool. Logistic regression analysis was used to investigate the determinants of QoL and depressive symptoms. Participants were 1,814 postgraduates from 249 hospitals in 27 Chinese provinces. The mean SF-8 physical and mental component summary scores were 78.17 (standard deviation [SD] 15.20) and 68.33 (SD 17.15), respectively. One-third of respondents had depressive symptoms, and those without depressive symptoms had significantly higher QoL scores. The multivariate regression analysis showed that factors independently associated with depressive symptoms were being in the second year of study, a lower household income, and less sleep time. Although QoL among our sample of Chinese medical students undergoing postgraduate neurology specialty training was favorable relative to other comparable populations, one-third of respondents had depressive symptoms. Accurate measures should be taken to change this situation. [ABSTRACT FROM AUTHOR]

Background: Neuropsychiatric disorders are devastating illnesses worldwide; however, the potential involvement of viruses in the pathophysiological mechanisms of psychiatric diseases have not been clearly elucidated. Borna disease virus (BDV) is a neurotropic, noncytopathic RNA virus. Materials and methods: In this study, we infected neonatal rats intracranially with BDV Hu-H1 and Strain V within 24 hours of birth. Psychological phenotypes were assessed using sucrose preference test, open field test, elevated plus maze test, and forced swim test. The protein expression of ERK/CREB/BDNF pathway was assessed by Western blotting of in vitro and in vivo samples. Results: Hu-H1-infected rats showed anxiety-like behavior 8 weeks postinfection while Strain V-infected rats demonstrated a certain abnormal behavior. Phosphorylated ERK1/2 was significantly upregulated in the hippocampi of Strain V- and Hu-H1-infected rats compared with control rats, indicating that Raf/MEK/ERK signaling was activated. Conclusion: The data suggested that infection of neonatal rats with BDV Hu-H1 and Strain V caused behavioral abnormalities that shared common molecular pathways, providing preliminary evidences to investigate the underlying mechanisms of psychiatric disorders caused by BDV. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a highly prevalent mental disorder with obvious sex differences.[1] Numerous metabolomics studies have investigated the differential expressed metabolic signatures in MDD; however, few studies have investigated the sex differences at the large-scale molecular level other than transcriptome.[[2]] Here, we investigated the sex differences of plasma metabolome signatures in antidepressant-naive patients with MDD. GLO:82I/01nov19:pcn12925-sup-0001-FigureS1.jpg PHOTO (COLOR): Figure S1 Metabolomic analysis of plasma samples from male and female major depressive disorder (MDD) patients versus healthy controls (HC). GLO:82I/01nov19:pcn12925-sup-0004-FigureS4.jpg PHOTO (COLOR): Figure S4 Weighted gene correlation network analysis of metabolic profiles of patients with major depressive disorder (MDD). For the rank-rank hypergeometric overlap test plot, a hot spot in the bottom left corner indicates overlap in metabolites upregulated in male and female patients. gl. [Extracted from the article]

• A meta-analysis of evaluating differences of CRP concentrations in suicidal PDDs. • Peripheral CRP levels were significantly increased in patients with suicidal PDDs. • The results support that inflammatory processes may be involved in suicidal behavior. Suicide is devastating with a high incidence in patients with depressive disorder (PDDs). Although some studies have explored underlying associations between C-reactive protein (CRP) levels and suicidal behavior in PDDs, consistent results have not been reached. Therefore, the aim of this meta-analysis was to explore the differences of peripheral blood CRP concentrations between suicidal and non-suicidal PDDs, and between suicidal PDDs and healthy controls (HCs). To this end, PubMed, Embase, and Web of science were searched for eligible studies, and pooled effect sizes from eligible studies were calculated by random-effect models. Furthermore, sensitivity and meta-regression analyses were performed to explain the causes of heterogeneity. Eventually, 7 studies with 2,108 participants were included. Our statistical results suggested that the concentrations of peripheral CRP may be significantly increased for suicidal PDDs, both compared with non-suicidal PDDs and HCs, respectively. The differences of detection methods may be linked with the sources of heterogeneity. In short, our findings showed both compared with non-suicidal PDDs and HCs, peripheral blood CRP levels may be significantly increased in suicidal PDDs, while more studies with large sample sizes are needed to validate our findings. [ABSTRACT FROM AUTHOR]