Search

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [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]

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. [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]

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Tao, Wang, Pu, Liu, Gui, Zhong, Yang, Zhou, Tao, Chen, Chen, Chen, Chen and Xie.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Xiao, Li, Yang, Shen, Liu, Xiong, Wu, Wang, Dang, Gui, Deng, Manaenko, Xie and Li.)

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.

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.