Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex

Background

Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation.

Methods

We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls.

Results

Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power.

Conclusions

The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Alterations of the gut microbiota in patients with schizophrenia

Introduction

Schizophrenia is a complex psychiatric disorder, of which molecular pathogenesis remains largely unknown. Accumulating evidence suggest that gut microbiota may affect brain function via the complex gut-brain axis, which may be a potential contributor to schizophrenia. However, the alteration of gut microbiota showed high heterogeneity across different studies. Therefore, this study aims to identify the consistently altered gut microbial taxa associated with schizophrenia.

Methods

We conducted a systematic search and synthesis of the up-to-date human gut microbiome studies on schizophrenia, and performed vote counting analyses to identify consistently changed microbiota. Further, we investigated the effects of potential confounders on the alteration of gut microbiota.

Results

We obtained 30 available clinical studies, and found that there was no strong evidence to support significant differences in α-diversity and β-diversity between schizophrenic patients and healthy controls. Among 428 differential gut microbial taxa collected from original studies, we found that 8 gut microbial taxa were consistently up-regulated in schizophrenic patients, including Proteobacteria, Gammaproteobacteria, Lactobacillaceae, Enterobacteriaceae, Lactobacillus, Succinivibrio, Prevotella and Acidaminococcus. While 5 taxa were consistently down-regulated in schizophrenia, including Fusicatenibacter, Faecalibacterium, Roseburia, Coprococcus and Anaerostipes.

Discussion

These findings suggested that gut microbial changes in patients with schizophrenia were characterized by the depletion of anti-inflammatory butyrate-producing genera, and the enrichment of certain opportunistic bacteria genera and probiotics. This study contributes to further understanding the role of gut microbiota in schizophrenia, and developing microbiota-based diagnosis and therapy for schizophrenia.

Age-related changes after intracerebral hemorrhage: a comparative proteomics analysis of perihematomal tissue

The risk factors and causes of intracerebral hemorrhage (ICH) and the degree of functional recovery after ICH are distinct between young and elderly patients. The increasing incidence of ICH in young adults has become a concern; however, research on the molecules and pathways involved ICH in subjects of different ages is lacking. In this study, tandem mass tag (TMT)-based proteomics was utilized to examine the protein expression profiles of perihematomal tissue from young and aged mice 24 h after collagenase-induced ICH. Among the 5,129 quantified proteins, ICH induced 108 and 143 differentially expressed proteins (DEPs) in young and aged mice, respectively; specifically, there were 54 common DEPs, 54 unique DEPs in young mice and 89 unique DEPs in aged mice. In contrast, aging altered the expression of 58 proteins in the brain, resulting in 39 upregulated DEPs and 19 downregulated DEPs. Bioinformatics analysis indicated that ICH activated different proteins in complement pathways, coagulation cascades, the acute phase response, and the iron homeostasis signaling pathway in mice of both age groups. Protein-protein interaction (PPI) analysis and ingenuity pathway analysis (IPA) demonstrated that the unique DEPs in the young and aged mice were related to lipid metabolism and carbohydrate metabolism, respectively. Deeper paired-comparison analysis demonstrated that apolipoprotein M exhibited the most significant change in expression as a result of both aging and ICH. These results help illustrate age-related protein expression changes in the acute phase of ICH.

Integrated pathway and network analyses of metabolomic alterations in peripheral blood of patients with depression

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.

Multi-Omics Analysis Reveals Age-Related Microbial and Metabolite Alterations in Non-Human Primates

Aging is a systemic physiological degenerative process, with alterations in gut microbiota and host metabolism. However, due to the interference of multiple confounding factors, aging-associated molecular characteristics have not been elucidated completely. Therefore, based on 16S ribosomal RNA (rRNA) gene sequencing and non-targeted metabolomic detection, our study systematically analyzed the composition and function of the gut microbiome, serum, and fecal metabolome of 36 male rhesus monkeys spanning from 3 to 26 years old, which completely covers juvenile, adult, and old stages. We observed significant correlations between 41 gut genera and age. Moreover, 86 fecal and 49 serum metabolites exhibited significant age-related correlations, primarily categorized into lipids and lipid-like molecules, organic oxygen compounds, organic acids and derivatives, and organoheterocyclic compounds. Further results suggested that aging is associated with significant downregulation of various amino acids constituting proteins, elevation of lipids, particularly saturated fatty acids, and steroids. Additionally, age-dependent changes were observed in multiple immune-regulatory molecules, antioxidant stress metabolites, and neurotransmitters. Notably, multiple age-dependent genera showed strong correlations in these changes. Together, our results provided new evidence for changing characteristics of gut microbes and host metabolism during aging. However, more research is needed in the future to verify our findings.

Proteomics reveals mitochondrial dysfunction and energy metabolism disturbance of intestine in a nonhuman primate model of depression

BACKGROUND

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.

METHODS

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.

RESULTS

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.

LIMITATIONS

Further research is warranted to determine the effects of depression on other peripheral organs.

CONCLUSIONS

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.

Integrative Analysis of Long Non-coding RNAs, Messenger RNAs, and MicroRNAs Indicates the Neurodevelopmental Dysfunction in the Hippocampus of Gut Microbiota-Dysbiosis Mice

Major depressive disorder is caused by gene–environment interactions and the gut microbiota plays a pivotal role in the development of depression. However, the underlying mechanisms remain elusive. Herein, the differentially expressed hippocampal long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), and microRNAs (miRNAs) between mice inoculated with gut microbiota from major depressive disorder patients or healthy controls were detected, to identify the effects of gut microbiota-dysbiosis on gene regulation patterns at the transcriptome level, and in further to explore the microbial-regulated pathological mechanisms of depression. As a result, 200 mRNAs, 358 lncRNAs, and 4 miRNAs were differentially expressed between the two groups. Functional analysis of these differential mRNAs indicated dysregulated inflammatory response to be the primary pathological change. Intersecting these differential mRNAs with targets of differentially expressed miRNAs identified 47 intersected mRNAs, which were mainly related to neurodevelopment. Additionally, a microbial-regulated lncRNA–miRNA–mRNA network based on RNA–RNA interactions was constructed. Subsequently, according to the competitive endogenous RNAs (ceRNA) hypothesis and the biological functions of these intersected genes, two neurodevelopmental ceRNA sub-networks implicating in depression were identified, one including two lncRNAs (4930417H01Rik and AI480526), one miRNA (mmu-miR-883b-3p) and two mRNAs (Adcy1 and Nr4a2), and the other including six lncRNAs (5930412G12Rik, 6430628N08Rik, A530013C23Rik, A930007I19Rik, Gm15489, and Gm16251), one miRNA (mmu-miR-377-3p) and three mRNAs (Six4, Stx16, and Ube3a), and these molecules could be recognized as potential genetic and epigenetic biomarkers in microbial-associated depression. This study provides new understanding of the pathogenesis of depression induced by gut microbiota-dysbiosis and may act as a theoretical basis for the development of gut microbiota-based antidepressants.

Proteomics analysis of the gut-brain axis in a gut microbiota-dysbiosis model of depression

Major depressive disorder (MDD) is a serious mental illness. Increasing evidence from both animal and human studies suggested that the gut microbiota might be involved in the onset of depression via the gut-brain axis. However, the mechanism in depression remains unclear. To explore the protein changes of the gut-brain axis modulated by gut microbiota, germ-free mice were transplanted with gut microbiota from MDD patients to induce depression-like behaviors. Behavioral tests were performed following fecal microbiota transplantation. A quantitative proteomics approach was used to examine changes in protein expression in the prefrontal cortex (PFC), liver, cecum, and serum. Then differential protein analysis and weighted gene coexpression network analysis were used to identify microbiota-related protein modules. Our results suggested that gut microbiota induced the alteration of protein expression levels in multiple tissues of the gut-brain axis in mice with depression-like phenotype, and these changes of the PFC and liver were model specific compared to chronic stress models. Gene ontology enrichment analysis revealed that the protein changes of the gut-brain axis were involved in a variety of biological functions, including metabolic process and inflammatory response, in which energy metabolism is the core change of the protein network. Our data provide clues for future studies in the gut-brain axis on protein level and deepen the understanding of how gut microbiota cause depression-like behaviors.

Comparative analysis of hippocampal transcriptional features between major depressive disorder patients and animal models

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.

Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: A targeted metabolomics study

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.

Transcriptomics Analysis Reveals Shared Pathways in Peripheral Blood Mononuclear Cells and Brain Tissues of Patients With Schizophrenia

Background: Schizophrenia is a serious mental disorder with complicated biological mechanisms. Few studies explore the transcriptional features that are shared in brain tissue and peripheral blood. In the present study, we aimed to explore the biological pathways with similar expression patterns in both peripheral blood mononuclear cells (PBMCs) and brain tissues. Methods: The present study used transcriptomics technology to detect mRNA expression of PBMCs of 10 drug-naïve patients with schizophrenia and 20 healthy controls. Transcriptome data sets of brain tissue of patients with schizophrenia downloaded from public databases were also analyzed in our study. The biological pathways with similar expression patterns in the PBMCs and brain tissues were uncovered by differential expression analysis, weighted gene co-expression network analysis (WGCNA), and pathway analysis. Finally, the expression levels of differential expressed genes (DEGs) were validated by real-time fluorescence quantitative polymerase chain reaction (qPCR) in another 12 drug-naïve patients with schizophrenia and 12 healthy controls. Results: We identified 542 DEGs, 51 DEGs, 732 DEGs, and 104 DEGs in PBMCs, dorsolateral prefrontal cortex, anterior cingulate gyrus, and nucleus accumbent, respectively. Five DEG clusters were recognized as having similar gene expression patterns in PBMCs and brain tissues by WGCNA. The pathway analysis illustrates that these DEG clusters are mainly enriched in several biological pathways that are related to phospholipid metabolism, ribosome signal transduction, and mitochondrial oxidative phosphorylation. The differential significance of PLAAT3, PLAAT4, PLD2, RPS29, RPL30, COX7C, COX7A2, NDUFAF2, and ATP5ME were confirmed by qPCR. Conclusions: This study finds that the pathways associated with phospholipid metabolism, ribosome signal transduction, and energy metabolism have similar expression patterns in PBMCs and brain tissues of patients with schizophrenia. Our results supply a novel insight for revealing the pathogenesis of schizophrenia and might offer a new approach to explore potential biological markers of peripheral blood in schizophrenia.

An integrated meta-analysis of peripheral blood metabolites and biological functions in major depressive disorder

Major depressive disorder (MDD) is a serious mental illness, characterized by high morbidity, which has increased in recent decades. However, the molecular mechanisms underlying MDD remain unclear. Previous studies have identified altered metabolic profiles in peripheral tissues associated with MDD. Using curated metabolic characterization data from a large sample of MDD patients, we meta-analyzed the results of metabolites in peripheral blood. Pathway and network analyses were then performed to elucidate the biological themes within these altered metabolites. We identified 23 differentially expressed metabolites between MDD patients and controls from 46 studies. MDD patients were characterized by higher levels of asymmetric dimethylarginine, tyramine, 2-hydroxybutyric acid, phosphatidylcholine (32:1), and taurochenodesoxycholic acid and lower levels of L-acetylcarnitine, creatinine, L-asparagine, L-glutamine, linoleic acid, pyruvic acid, palmitoleic acid, L-serine, oleic acid, myo-inositol, dodecanoic acid, L-methionine, hypoxanthine, palmitic acid, L-tryptophan, kynurenic acid, taurine, and 25-hydroxyvitamin D compared with controls. L-tryptophan and kynurenic acid were consistently downregulated in MDD patients, regardless of antidepressant exposure. Depression rating scores were negatively associated with decreased levels of L-tryptophan. Pathway and network analyses revealed altered amino acid metabolism and lipid metabolism, especially for the tryptophan-kynurenine pathway and fatty acid metabolism, in the peripheral system of MDD patients. Taken together, our integrated results revealed that metabolic changes in the peripheral blood were associated with MDD, particularly decreased L-tryptophan and kynurenic acid levels, and alterations in the tryptophan-kynurenine and fatty acid metabolism pathways. Our findings may facilitate biomarker development and the elucidation of the molecular mechanisms that underly MDD.

Increased C-reactive protein concentrations were associated with suicidal behavior in patients with depressive disorders: a meta-analysis

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.

Vascular endothelial growth factor in major depressive disorder, schizophrenia, and bipolar disorder: A network meta-analysis

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.

Metabolomic analysis of animal models of depression

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.

MRI Signal Intensity and Electron Ultrastructure Classification Predict the Long-Term Outcome of Skull Base Chordomas

BACKGROUND AND PURPOSE

MR imaging is a useful and widely used evaluation for chordomas. Prior studies have classified chordomas into cell-dense type and matrix-rich type according to the ultrastructural features. However, the relationship between the MR imaging signal intensity and ultrastructural classification is unknown. We hypothesized that MR imaging signal intensity may predict both tumor ultrastructural classification and prognosis.

MATERIALS AND METHODS

Seventy-nine patients with skull base chordomas who underwent 95 operations were included in this retrospective single-center series. Preoperative tumor-to-pons MR imaging signal intensity ratios were calculated and designated as ratio on T1 FLAIR sequence (R_T1), ratio on T2 sequence (R_T2), and ratio on enhanced T1 FLAIR sequence (R_EN), respectively. We assessed the relationships among signal intensity ratios, ultrastructural classification, and survival.

RESULTS

Compared with the matrix-rich type group, the cell-dense type chordomas showed lower R_T2 (cell-dense type: 1.90 ± 0.38; matrix-rich type: 2.61 ± 0.60 P < .001). The model of predicting cell-dense type based on R_T2 had an area under the curve of 0.83 (95% CI, 0.75-0.92). In patients without radiation therapy, both progression-free survival (P = .003) and overall survival (P = .002) were longer in the matrix-rich type group than in the cell-dense type group. R_EN was a risk factor for progression-free survival (hazard ratio = 10.24; 95% CI, 1.73-60.79); R_T2 was a protective factor for overall survival (hazard ratio  = 0.33; 95% CI, 0.12-0.87); and R_EN was a risk factor for overall survival (hazard ratio = 4.76; 95% CI, 1.51-15.01).

CONCLUSIONS

The difference in MR imaging signal intensity in chordomas can be explained by electron microscopic features. Both signal intensity ratios and electron microscopic features may be prognostic factors.

Pro-inflammatory cytokines are associated with the development of post-stroke depression in the acute stage of stroke: A meta-analysis

Background: Pro-inflammatory cytokines may be associated with post-stroke depression (PSD); however, results from different studies are inconsistent.Objectives: To investigate whether pro-inflammatory cytokines are associated with the development of PSD in acute stroke.Methods: PubMed, Embase, and Web of science were searched for relevant literature. Meta-analyzes were performed to determine whether the baseline blood concentrations of pro-inflammatory cytokines differed between acute stroke patients with and without depression. Sensitivity analyzes and regression analyzes were conducted to explore sources of heterogeneity.Results: We included 889 acute stroke patients from eight original studies, 312 of whom developed PSD and 577 did not. The serum concentrations of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) were higher in the PSD group, compared with the non-PSD group (IL-6: SMD = 1.26, 95% CI = [0.55, 1.97], P < 0.001; TNF-α: SMD = 0.61, 95% CI = [0.13, 1.10], P = 0.010).Conclusions: This study indicates IL-6 and TNF-α as potential biomarkers of PSD in the acute stage of stroke and provides theoretical support for the early prevention and treatment of PSD.

[Texture analysis of diffusion-weighted magnetic resonance imaging to identify atypically enhanced small hepatocellular carcinoma and dysplastic nodules under the background of cirrhosis]

Objective: To investigate the value of texture analysis based on diffusion-weighted magnetic resonance imaging (DWI) in the differential diagnosis of atypically enhanced small hepatocellular carcinoma (sHCC) and dysplastic nodules (DNs) in liver cirrhosis. Methods: Data of 59 cases with atypical enhancement and solitary cirrhotic nodule (≤2 cm) confirmed by dynamic contrast enhanced MRI and surgical pathology specimen were analyzed retrospectively. Among them, 37 cases were of atypically enhanced sHCC and 22 cases of DNS. The DWI signal characteristics of the lesions were analyzed to measure the average apparent diffusion coefficient (ADC) value of the lesions, and the ADC ratio of the lesion to the liver parenchyma. MaZda software was used to manually draw the region of interest to extract the texture parameters of DWI lesions. The three sets (combination of Fisher coefficient, classification of error probability combined with average correlation coefficient and interactive information) were used to select the thirty optimal texture parameters. Raw data analysis (RDA), principal component analysis (PCA), linear discriminant analysis (LDA) and non-linear discriminant analysis (NDA) were performed for texture classification. The difference of ADC value and ADC ratio between sHCC and DNS group was compared by independent sample t-test, and χ2 test was used to compare the count data (or rate). ROC curve analysis was used to evaluate the diagnostic efficiency. Results: The sensitivity, specificity and accuracy of DWI high-signal in the identification of atypically enhanced sHCC and DNs were 94.6% (35/37), 68.2% (15/22), and 84.7% (50/59), respectively. The ADC ratio of atypically enhanced sHCC was significantly lower than DNs, and the difference was statistically significant (t = 2.99, P = 0.002). The sensitivity, specificity, and accuracy for the diagnosis of atypically enhanced sHCC were 73.0% (27/37), 72.7% (16/22) and 72.9% (43/59), respectively. The sensitivity, specificity and accuracy of DWI texture analysis in diagnosing atypically enhanced sHCC were 94.6% (35/37), 95.5% (21/22) and 94.9% (56/59).The diagnostic efficiency of DWI texture analysis (AUC = 0.94) was significantly higher than DWI high-signal (AUC = 0.81) and ADC ratio (AUC = 0.72). Conclusion: The texture analysis based on DWI can identify atypically enhanced sHCC and dysplastic nodules under the background of cirrhosis, and its efficacy is better than qualitative and quantitative DWI.

Chronic Stress in a Rat Model of Depression Disturbs the Glutamine-Glutamate-GABA Cycle in the Striatum, Hippocampus, and Cerebellum

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.

Depressive symptoms and quality of life among Chinese medical postgraduates: a national cross-sectional study

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.

MENDA: a comprehensive curated resource of metabolic characterization in depression

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.

Relationship between burnout and career choice regret among Chinese neurology postgraduates

BACKGROUND

In China, the shortage of doctors leads to stressful clinical work and increasing turnover. Medical students undergoing postgraduate specialty training will be the country's medical workforce in the coming decades, but are also subject to high workloads and academic pressure. This may have significant implications for burnout and career choice regret. Despite the importance of burnout and career choice regret, the status and relationship of these aspects in Chinese neurology postgraduates are largely unexplored, and associated factors remain unknown.

METHODS

This study investigated the prevalence of and factors influencing burnout and career choice regret among neurology postgraduates in China. We conducted a national cross-sectional study of Chinese neurology postgraduates. Data were collected using a self-administered questionnaire that covered demographic information, the Maslach Burnout Inventory, and additional item to assess career choice regret.

RESULTS

Of 4902 neurology postgraduates, 2008 returned completed questionnaires (response rate 41%). After excluding incomplete questionnaires, data for 1814 participants were analyzed. In total, 83.6% of participants had experienced symptoms of burnout, and 46.6% reported career choice regret. Binary logistic regression analysis showed postgraduate entrance examination scores, marital status, and having children were associated with burnout (all P <  0.05). Career choice regret was the strongest risk factor for burnout (odds ratio [OR] = 3.17, 95% confidence interval [CI] 2.33-4.32). Multiple logistic regression showed postgraduates with shorter work or study hours per week (OR = 0.64, 95% CI 0.47-0.88) had a low risk for career choice regret, whereas married participants (OR = 1.54, 95% CI 1.07-2.20) had a high risk for career choice regret. No symptoms of burnout (OR = 0.33, 95% CI 0.24-0.45) was also associated with a low risk for career choice regret.

CONCLUSIONS

Burnout symptoms and career choice regret are prevalent among neurology postgraduates in China. Career choice regret is an important predictor of burnout. Further research on reducing burnout and career choice regret among neurology postgraduates is needed.

The gut microbiome from patients with schizophrenia modulates the glutamate-glutamine-GABA cycle and schizophrenia-relevant behaviors in mice

Schizophrenia (SCZ) is a devastating mental disorder with poorly defined underlying molecular mechanisms. The gut microbiome can modulate brain function and behaviors through the microbiota-gut-brain axis. Here, we found that unmedicated and medicated patients with SCZ had a decreased microbiome α-diversity index and marked disturbances of gut microbial composition versus healthy controls (HCs). Several unique bacterial taxa (e.g., Veillonellaceae and Lachnospiraceae) were associated with SCZ severity. A specific microbial panel (Aerococcaceae, Bifidobacteriaceae, Brucellaceae, Pasteurellaceae, and Rikenellaceae) enabled discriminating patients with SCZ from HCs with 0.769 area under the curve. Compared to HCs, germ-free mice receiving SCZ microbiome fecal transplants had lower glutamate and higher glutamine and GABA in the hippocampus and displayed SCZ-relevant behaviors similar to other mouse models of SCZ involving glutamatergic hypofunction. Together, our findings suggest that the SCZ microbiome itself can alter neurochemistry and neurologic function in ways that may be relevant to SCZ pathology.

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.

Activation of ERK/CREB/BDNF pathway involved in abnormal behavior of neonatally Borna virus-infected rats

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.

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.

Melatonin inhibits cell growth and migration, but promotes apoptosis in gastric cancer cell line, SGC7901

The pineal hormone, melatonin (MLT), has been shown to have therapeutic effects in patients with gastric cancer; however, the mechanisms for the anti-cancer effects are unknown. We investigated the effects of melatonin on cell proliferation, apoptosis, colony formation and cell migration in the gastric adenocarcinoma cell line, SGC7901, using MTT assay, Hoechst 33258 staining, flow cytometry, western blot, caspase-3 activity assay, soft agar colony formation assay, and scratch-wound assay. Our results showed that melatonin could inhibit cell proliferation, colony formation and migration efficiency, and it promoted apoptosis of SGC7901 cells. Our findings suggest that the anti-cancer effects of melatonin may be due to both inhibition of tumor cell proliferation and reduction of the metastatic potential of tumor cells.

Expression of estrogen receptor α and growth factors in human prolactinoma and its correlation with clinical features and gender

BACKGROUND

Many studies demonstrate that growth factors play an important role in the pathogenesis of prolactinoma induced by estrogen. The effects of estrogen are mainly mediated through its nuclear receptor (ERα); however, expression of ERα and growth factors in prolactinoma and healthy pituitary and their relationship remain obscure.

AIM

To obtain new insights regarding the expression differences of these factors and their relationship and to investigate the correlation between gender and clinical features in patients with prolactinoma.

SUBJECTS AND METHODS

A total of 21 human prolactinomas and 6 healthy human pituitaries were examined for mRNA expression of ERα, basic fibroblast growth factor (bFGF), transforming growth factor α (TGFα), TGFβ1, TGFβ3, and TGFβ receptor type II (TGFβRII) by means of real-time PCR. Patient clinical data was also analyzed.

RESULTS

Both PRL level and tumor volume of the male patient group were higher than that of the female patient group. There was a significant correlation between PRL level and tumor volume in the total patient group. Expression of ERα, bFGF, TGFα, and TGFβ3 mRNA levels of the patient group were significantly different from that of the control group. A significant correlation between ERα mRNA levels and PRL levels, tumor volume, TGFβ1 mRNA levels in the total patient group were found.

CONCLUSIONS

PRL level and tumor volume have a significant difference between genders in prolactinoma patients. ERα and some growth factors may be involved in the tumorigenesis of prolactinoma. ERα could potentially be an effective therapy target for treating prolactinoma.

Analysis of differential gene expression by bead-based fiber-optic array in nonfunctioning pituitary adenomas

Nonfunctioning pituitary adenomas (NFPAs) are relatively common, accounting for 30% of all pituitary adenomas; however, their pathogenesis remains enigmatic. To explore the possible pathogenesis of NFPAs, we used fiber-optic BeadArray to examine gene expression in 5 NFPAs compared with 3 normal pituitaries. 4 differentially expressed genes were chosen randomly for validation by reverse transcriptase-real time quantitative polymerase chain reaction (RT-qPCR). We then analyzed the differentially expressed gene profile with Kyoto Encyclopedia of Genes and Genomes (KEGG). The array analysis indentified significant increases in the expression of 1,402 genes and 383 expressed sequence tags (ESTs), and decreases in 1,697 genes and 113 ESTs in the NFPAs. Bioinformatic and pathway analysis showed that the genes HIGD1B, FAM5C, PMAIP1 and the pathway cell-cycle regulation may play an important role in tumorigenesis and progression of NFPAs. Our data suggest fiber-optic BeadArray combined with pathway analysis of differential gene expression profile appears to be a valid approach for investigating the pathogenesis of tumors.

Population aging and the need for long term care: a comparison of the United States and the People's Republic of China

Both developing and major developed countries of the world are facing the global aging of their citizenry. The United States and the People's Republic of China each share in this phenomenon. The rapid growth of their aging populations comes as both countries are experiencing a sustained period of economic stability with an accompanying drop in fertility rates (Coale & Watkins 1986; Dyson & Murphy 1985). Together with longer expected life spans in both countries, these factors have caused a shift in the population structure which will result in increasingly large portions of the population who will potentially require assistance with ADL's and/or long term care (Olson 1990; Kennedy, LaPlante & Kaye 1997). The careful assessment and interpretation of available data to define the actual extent of need should be part of a process to help guide each country as they prepare for the future.

A new elderly support system in rural areas in Shanghai

"In early 1987, we started an experiment in the rural areas in Shanghai suburbs on how to replace the elderly support system then in effect, which was funded by the community, with one that was to be jointly supported by the State, the community and private individuals. The two-year experiment has yielded a new elderly support system applicable to China's rural areas that have a more developed economy and a fairly large number of collectively owned township enterprises.... This article gives a brief introduction to the economic and social background and characteristics of the system."

[Effect of kidney replenishing Chinese herbs on insulin-like growth factor-1 and its receptor in androgen induced sterile rats]

OBJECTIVE

To observe the effect of Kidney replenishing Chinese herbs (KRCH) on insulin-like growth factor-1 and its receptor (IGF-1/IGF-1R) in androgen induced sterile rats (ASR).

METHODS

ASR model was set up and screened by vaginal smear. The level of serum IGF-1 was detected by radioimmunoassay, and IGF-1R by immunohistochemical method.

RESULTS

(1) Serum IGF-1 level in model rats group > model rats treated with KRCH group > normal control group, but no statistical difference was found among them. KRCH could lower the level of serum IGF-1. (2) Level of IGF-1R in pancreas, liver, ovary and adrenal gland showed an opposite sequence to that of serum IGF-1.

CONCLUSION

ASR shows a high IGF-1 level in serum and low IGF-1R level in main target organs, and KRCH could adjust the levels in certain degree. From this, it is inferred that the ovulation effect of KRCH on ASR may come true partly by adjusting the level of IGF-1/IGF-1R.

[Effect of kidney yin-yang replenishing Chinese herbs on the binding character of insulin receptor on hepatocyte membrane in androgen-induced sterility rats]

OBJECTIVE

To observe the effect of Kidney Yin-Yang replenishing Chinese herbs on the binding character of insulin receptor (IR) on hepatocyte membrane from androgen-induced sterility rats (ASR).

METHODS

The number and affinity of IR on hepatocyte membrane of ASR were determined with radioligand binding assay.

RESULTS

There was no significant difference of the number or affinity for both high and low affinity sites of IR between normal and ASR.

CONCLUSION

The treatment with Kidney Yin-Yang replenishing Chinese herbs had no effect on insulin binding although a relatively high rate of ovulation induction on ASR was observed.

A survey report on the life cycle of the Chinese elderly

"In August 1992...the Chinese-Japanese Survey Group on the Life Cycle of the Elderly conducted a sample survey on the life experience and status quo of the elderly in Zhejiang Province and the City of Shanghai, which covered 1,583 urban and rural elderly at or above the age of 60....[The aim was to] not only help change the attitudes towards reproduction among women at child-bearing age, but also contribute to a well-drafted development program for the elderly care system in China so as to prepare the country for the situation after the 2020s when the parents of only children become senior citizens."

A survey analysis of the status of influent reproductive age women in Shanghai--a survey report

Characteristics of the female transient population of reproductive age in Shanghai, China, are assessed using data from an October 1988 survey. "Not only did this survey supply large quantities of basic data on the floating population for the Shanghai government and related departments, but [it] was also very enlightening for our research into how to make a good job of family planning administration for China's urban-rural floating population."

Elderly populations in the Jingan district of Shanghai and the special districts of Tokyo: a comparative analysis

"The present paper is a comparative analysis of part of the survey of the elderly population conducted in the Jingan District of Shanghai in October 1987, and part of the survey on the social welfare (the actual living conditions) of the elderly in the special districts of Tokyo, with a view to finding the similarities and differences between the two localities.... The purpose...[is] to pinpoint certain measures adopted by Japan with respect to the aging issue that might be of interest to China." Consideration is given to marital status, family structure, number of children, health status, education, and employment. The role of family support of the elderly receives particular attention.