Identification and validation of urinary metabolite biomarkers for major depressive disorder

Systematical Comparison Reveals Distinct Brain Transcriptomic Characteristics in Depression Models Induced by Gut Microbiota Dysbiosis and Chronic Stress

Major depressive disorder (MDD) is a devastating psychiatric illness with various etiologies. Both chronic stress and gut microbiome dysbiosis are implicated in the pathogenesis of MDD. However, limited research has been conducted to delineate the distinct effects of these two pathogenic factors on the brain transcriptome. We generated and compared transcriptomic features of the anterior cingulate cortex (ACC) from depressive-like mice induced by gut microbiome dysbiosis and canonical chronic stress paradigms, focusing on gene expression patterns and network characteristics. Data derived from MDD patients served as a reference standard to filter the molecular alterations associated with the disorder. Chronic stress induced a plethora of altered genes and biological functions associated with depression, prominently involving mitochondrial dysfunction. However, gut microbiota dysbiosis specifically regulated narrower range of genes and biological mechanisms, targeting aberrations in vesicular transport systems and perturbations of autophagy pathways. Network analysis revealed that hierarchical gene co-expression was specifically affected by gut microbiota dysbiosis rather than chronic stress. Further functional clustering analysis, along with the central distribution of inflammation-related differentially expressed genes, suggested an intricate interplay between disrupted autophagy processes, microglia-mediated inflammation, and synaptic dysfunctions in the network influenced by gut microbiota dysbiosis. Our findings reveal the distinctive transcriptomic alterations of brain shaped by gut microbiota and chronic stress in the development of MDD, contributing to a deeper understanding the heterogeneity of depression. Additionally, we provide a valuable data resource and bioinformatic analysis template for future studies.

Alterations of serum metabolic profile in major depressive disorder: A case-control study in the Chinese population

BACKGROUND

Major depressive disorder (MDD) is characterized by persistent depressed mood and cognitive symptoms. This study aimed to discover biomarkers for MDD, explore its pathological mechanisms, and examine the associations of the identified biomarkers with clinical and psychological variables.

AIM

To discover candidate biomarkers for MDD identification and provide insight into the pathological mechanism of MDD.

METHODS

The current study adopted a single-center cross-sectional case-control design. Serum samples were obtained from 100 individuals diagnosed with MDD and 97 healthy controls (HCs) aged between 18 to 60 years. Metabolomics was performed on an Ultimate 3000 UHPLC system coupled with Q-Exactive MS (Thermo Scientific). The online software Metaboanalyst 6.0 was used to process and analyze the acquired raw data of peak intensities from the instrument.

RESULTS

The study included 100 MDD patients and 97 HCs. Metabolomic profiling identified 35 significantly different metabolites (e.g., cortisol, sebacic acid, and L-glutamic acid). Receiver operating characteristic curve analysis highlighted 8-HETE, 10-HDoHE, cortisol, 12-HHTrE, and 10-hydroxydecanoic acid as top diagnostic biomarkers for MDD. Significant correlations were found between metabolites (e.g., some lipids, steroids, and amino acids) and clinical and psychological variables.

CONCLUSION

Our study reported metabolites (some lipids, steroids, amino acids, carnitines, and alkaloids) responsible for discriminating MDD patients and HCs. This metabolite profile may enable the development of a laboratory-based diagnostic test for MDD. The mechanisms underlying the association between psychological or clinical variables and differential metabolites deserve further exploration.

Decreased gut microbiome-derived indole-3-propionic acid mediates the exacerbation of myocardial ischemia/reperfusion injury following depression via the brain-gut-heart axis

Despite the increasing recognition of the interplay between depression and cardiovascular disease (CVD), the precise mechanisms by which depression contributes to the pathogenesis of cardiovascular disease remain inadequately understood. The involvement of gut microbiota and their metabolites to health and disease susceptibility has been gaining increasing attention. In this study, it was found that depression exacerbated cardiac injury, impaired cardiac function (EF%: P < 0.01; FS%: P < 0.05), hindered long-term survival (P < 0.01), and intensified adverse cardiac remodeling (WGA: P < 0.01; MASSON: P < 0.0001) after myocardial ischemia/reperfusion (MI/R) in mice. Then we found that mice receiving microbiota transplants from chronic social defeat stress (CSDS) mice exhibited worse cardiac function (EF%: P < 0.01; FS%: P < 0.01) than those receiving microbiota transplants from non-CSDS mice after MI/R injury. Moreover, impaired tryptophan metabolism due to alterations in gut microbiota composition and structure was observed in the CSDS mice. Mechanistically, we analyzed the metabolomics of fecal and serum samples from CSDS mice and identified indole-3-propionic acid (IPA) as a protective agent for cardiomyocytes against ferroptosis after MI/R via NRF2/System xc-/GPX4 axis, played a role in mediating the detrimental influence of depression on MI/R. Our findings provide new insights into the role of the gut microbiota and IPA in depression and CVD, forming the basis of intervention strategies aimed at mitigating the deterioration of cardiac function following MI/R in patients experiencing depression.

The Clinical Utility of Biomarkers in Diagnosing Major Depressive Disorder in Adults: A Systematic Review of Literature From 2013 to 2023

OBJECTIVE

The variety and efficacy of biomarkers available that may be used objectively to diagnose major depressive disorder (MDD) in adults are unclear. This systematic review aims to identify and evaluate the variety of objective markers used to diagnose MDD in adults.

METHODS

The search strategy was applied via PubMed and PsycINFO over the past 10 years (2013-2023) to capture the latest available evidence supporting the use of biomarkers to diagnose MDD. Data was reported through narrative synthesis.

RESULTS

Forty-two studies were included in the review. Findings were synthesised based on the following measures: blood, neuroimaging/neurophysiology, urine, dermatological, auditory, vocal, cerebrospinal fluid and combinatory-and evaluated based on its sensitivity/specificity and area under the curve values. The best predictors of blood (MYT1 gene), neuroimaging/neurophysiological (5-HT1A auto-receptor binding in the dorsal and median raphe), urinary (combined albumin, AMBP, HSPB, APOA1), cerebrospinal fluid-based (neuron specific enolase, microRNA) biomarkers were found to be closely linked to the pathophysiology of MDD.

CONCLUSION

A large variety of biomarkers were available to diagnose MDD, with the best performing biomarkers intrinsically related to the pathophysiology of MDD. Potential for future research lies in investigating the joint sensitivity of the best performing biomarkers identified via machine learning methods and establishing the causal effect between these biomarkers and MDD.

Non-pharmacological therapeutic paradigms in stress-induced depression: from novel therapeutic perspective with focus on cell-based strategies

Major depressive disorder (MDD) is considered a psychiatric disorder and have a relationship with stressful events. Although the common therapeutic approaches against MDD are diverse, a large number of patients do not present an adequate response to antidepressant treatments. On the other hand, effective non-pharmacological treatments for MDD and their tolerability are addressed. Several affective treatments for MDD are used but non-pharmacological strategies for decreasing the common depression-related drugs side effects have been focused recently. However, the potential of extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs), microRNAs (miRNAs) as cell-based therapeutic paradigms, besides other non-pharmacological strategies including mitochondrial transfer, plasma, transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS), and exercise therapy needs to further study. This review explores the therapeutic potential of cell-based therapeutic non-pharmacological paradigms for MDD treatment. In addition, plasma therapy, mitotherapy, and exercise therapy in several in vitro and in vivo conditions in experimental disease models along with tDCS and TMS will be discussed as novel non-pharmacological promising therapeutic approaches.

The effect of exercise on depression and gut microbiota: Possible mechanisms

Exercise can effectively prevent and treat depression and anxiety, with gut microbiota playing a crucial role in this process. Studies have shown that exercise can influence the diversity and composition of gut microbiota, which in turn affects depression through immune, endocrine, and neural pathways in the gut-brain axis. The effectiveness of exercise varies based on its type, intensity, and duration, largely due to the different changes in gut microbiota. This article summarizes the possible mechanisms by which exercise affects gut microbiota and how gut microbiota influences depression. Additionally, we reviewed literature on the effects of exercise on depression at different intensities, types, and durations to provide a reference for future exercise-based therapies for depression.

Microbiota Alters and Its Correlation with Molecular Regulation Underlying Depression in PCOS Patients

Depression is one of the complications in patients with polycystic ovary syndrome (PCOS) that leads to considerable mental health. Accumulating evidence suggests that human gut microbiomes are associated with the progression of PCOS and depression. However, whether microbiota influences depression development in PCOS patients is still uncharacterized. In this study, we employed metagenomic sequencing and transcriptome sequencing (RNA-seq) to profile the composition of the fecal microbiota and gene expression of peripheral blood mononuclear cells in depressed women with PCOS (PCOS-DP, n = 27) in comparison to mentally healthy women with PCOS (PCOS, n = 18) and compared with healthy control (HC, n = 27) and patients with major depressive disorder (MDD, n = 29). Gut microbiota assessment revealed distinct patterns in the relative abundance in the PCOS-DP compared to HC, MDD, and PCOS groups. Several gut microbes exhibited uniquely and significantly higher abundance in the PCOS-DP compared to PCOS patients, inducing EC Ruminococcus torques, Coprococcus comes, Megasphaera elsdenii, Acidaminococcus intestini, and Barnesiella viscericola. Bacteroides eggerthii was a potential gut microbial biomarker for the PCOS-DP. RNA-seq profiling identified that 35 and 37 genes were significantly elevated and downregulated in the PCOS-DP, respectively. The enhanced differential expressed genes (DEGs) in the PCOS-DP were enriched in pathways involved in signal transduction and endocrine and metabolic diseases, whereas several lipid metabolism pathways were downregulated. Intriguingly, genes correlated with the gut microbiota were found to be significantly enriched in pathways of neurodegenerative diseases and the immune system, suggesting that changes in the microbiota may have a systemic impact on the expression of neurodegenerative diseases and immune genes. Gut microbe-related DEGs of CREB3L3 and CCDC173 were possible molecular biomarkers and therapeutic targets of women with PCOS-DP. Our multi-omics data indicate shifts in the gut microbiome and host gene regulation in PCOS patients with depression, which is of possible etiological and diagnostic importance.

Alcohol use-associated alterations in the circulating metabolite profile in the general population and in individuals with major depressive disorder

Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in persons with depression. If so, these findings could partially explain the link between alcohol use and depression. We applied a targeted liquid chromatography mass spectrometry method to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the non-depressed general population (GP) (n = 247) and a cohort of individuals with major depressive disorder (MDD) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of hippuric acid in the GP cohort. In the GP cohort, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the MDD cohort, but in these individuals it was regardless of their level of alcohol use. Reduced serum concentrations of hippuric acid suggest that already-moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and depression.

Evaluation of metabolomics-based urinary biomarker models for recognizing major depression disorder and bipolar disorder

BACKGROUND

Major depressive disorder (MDD) and bipolar disorder (BD) are psychiatric disorders with overlapping symptoms, leading to high rates of misdiagnosis due to the lack of biomarkers for differentiation. This study aimed to identify metabolic biomarkers in urine samples for diagnosing MDD and BD, as well as to establish unbiased differential diagnostic models.

METHODS

We utilized a metabolomics approach employing ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) to analyze the metabolic profiles of urine samples from individuals with MDD (n = 50), BD (n = 12), and healthy controls (n = 50). The identification of urine metabolites was verified using MS data analysis tools and online metabolite databases.

RESULTS

Two diagnostic panels consisting of a combination of metabolites and clinical indicators were identified-one for MDD and another for BD. The discriminative capacity of these panels was assessed using the area under the receiver operating characteristic (ROC) curve, yielding an area under the curve (AUC) of 0.9084 for MDD and an AUC value of 0.9017 for BD.

CONCLUSIONS

High-resolution mass spectrometry-based assays show promise in identifying urinary biomarkers for depressive disorders. The combination of urine metabolites and clinical indicators is effective in differentiating healthy controls from individuals with MDD and BD. The metabolic pathway indicating oxidative stress is seen to significantly contribute to depressive disorders.

Association between cheese and fish consumption and the occurrence of depression based on European population: mediating role of metabolites

Background

The consumption of cheese and fish has been linked to the onset of depression. However, the connection between consuming cheese, consuming fish, experiencing depression, and the pathways that mediate this relationship remains unclear. The purpose of this research was to investigate the potential association between the consumption of cheese and fish and the occurrence of depression. Moreover, it is important to identify any metabolites that might be involved and understand their respective roles and functions.

Methods

A two-step, two-sample Mendelian randomization (MR) study was conducted using genome-wide association study (GWAS) data on cheese, non-oily fish, and oily fish consumption and depression, along with 12 alternate mediators. The study included a total of 451,486 participants in the cheese consumption group, 460,880 in the non-oily fish consumption group, 460,443 in the oily fish consumption group, and 322,580 with a diagnosis of depression. The single nucleotide polymorphism (SNP) estimates were pooled using inverse-variance weighted, weighted median, MR-Egger, simple mode, and weighted mode.

Results

The data we collected suggested that consuming more cheese correlated with a lower likelihood of experiencing depression (OR: 0.95; 95% CI: 0.92 to 0.98). Neither non-oily fish nor oily fish consumption was directly linked to depression onset (p = 0.08, p = 0.78, respectively). Although there was a direct causal relationship with depression, the mediating relationship of triglycerides (TG), total cholesterol in large HDL, cholesterol to total lipids ratio in large HDL, free cholesterol to total lipids ratio in large HDL, glycine, and phospholipids to total lipids ratio in very large HDL of cheese intake on depression risk were - 0.002 (95% CI: -0.023 - 0.020), -0.002 (95% CI: -0.049 - 0.045), -0.001 (95% CI: -0.033 - 0.031), -0.001 (95% CI: -0.018 - 0.015), 0.001 (95% CI: -0.035 - 0.037), and - 0.001 (95% CI: -0.024 - 0.021), respectively. The mediating relationship of uridine, free cholesterol to total lipids ratio in large HDL, total cholesterol in large HDL, acetoacetate, and 3-hydroxybutyrate (3-HB) between non-oily fish consumption and depression risk were 0.016 (95% CI: -0.008 - 0.040), 0.011 (95% CI: -1.269 - 1.290), 0.010 (95% CI: -1.316 - 1.335), 0.011 (95% CI: -0.089 - 0.110), and 0.008 (95% CI: -0.051 - 0.068), respectively. The mediation effect of uridine and free cholesterol to total lipids ratio in large HDL between intake of oily fish and the risk of depression was found to be 0.006 (95% CI: -0.015 - 0.028) and - 0.002 (95% CI: -0.020 - 0.017), respectively. The correlation between eating cheese and experiencing depression persisted even when adjusting for other variables like Indian snacks, mango consumption, sushi consumption, and unsalted peanuts using multivariable MR.

Conclusion

The consumption of cheese and fish influenced the likelihood of experiencing depression, and this may be mediated by certain metabolites in the body. Our study provided a new perspective on the clinical treatment of depression.

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12 years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

Mood and microbes: a comprehensive review of intestinal microbiota's impact on depression

Depression is considered a multifaceted and intricate mental disorder of growing concern due to its significant impact on global health issues. The human gut microbiota, also known as the "second brain," has an important role in the CNS by regulating it through chemical, immunological, hormonal, and neurological processes. Various studies have found a significant bidirectional link between the brain and the gut, emphasizing the onset of depression therapies. The biological and molecular processes underlying depression and microbiota are required, as the bidirectional association may represent a novel study. However, profound insights into the stratification and diversity of the gut microbiota are still uncommon. This article investigates the emerging evidence of a bacterial relationship between the gut and the brain's neurological system and its potential pathogenicity and relevance. The interplay of microbiota, immune system, nervous system neurotransmitter synthesis, and neuroplasticity transitions is also widely studied. The consequences of stress, dietary fibers, probiotics, prebiotics, and antibiotics on the GB axis are being studied. Multiple studies revealed the processes underlying this axis and led to the development of effective microbiota-based drugs for both prevention and treatment. Therefore, the results support the hypothesis that gut microbiota influences depression and provide a promising area of research for an improved knowledge of the etiology of the disease and future therapies.

Precision Medicine in Depression: The Role of Proteomics and Metabolomics in Personalized Treatment Approaches

Depression, or major depressive disorder (MDD), is a widespread mental health condition marked by enduring feelings of sorrow and loss of interest. Treatment of depression frequently combines psychotherapy, medication, and lifestyle modifications. However, the occurrence of treatment resistance in certain individuals makes it difficult for physicians to effectively manage this disorder, calling for the implementation of alternative therapeutic strategies. Recently, precision medicine has gained increased attention in the field of mental health, paving the way for more personalized and effective therapeutic interventions in depression. Also known as personalized medicine, this approach relies on genetic composition, molecular profiles, and environmental variables to customize therapies to individual patients. In particular, precision medicine has offered novel viewpoints on depression through two specific domains: proteomics and metabolomics. On one hand, proteomics is the thorough study of proteins in a biological system, while metabolomics focuses on analyzing the complete set of metabolites in a living being. In the past few years, progress in research has led to the identification of numerous depression-related biomarkers using proteomics and metabolomics techniques, allowing for early identification, precise diagnosis, and improved clinical outcome. However, despite significant progress in these techniques, further efforts are required for advancing precision medicine in the diagnosis and treatment of depression. The overarching goal of this chapter is to provide the current state of knowledge regarding the use of proteomics and metabolomics in identifying biomarkers related to depression. It also highlights the potential of proteomics and metabolomics in elucidating the intricate processes underlying depression, opening the door for tailored therapies that could eventually enhance clinical outcome in depressed patients. This chapter finally discusses the main challenges in the use of proteomics and metabolomics and discusses potential future research directions.

The effect of prenatal stress on offspring depression susceptibility in relation to the gut microbiome and metabolome

Prenatal stress (PS) increases offspring susceptibility to depression, but the underlying mechanism remains unclear. Our previous results showed that PS can affect depression-like behavior in offspring through neurotransmitters and neuroinflammatory substances in the hippocampus and frontal cortex. In recent years there has been increasing evidence for a role of the gut microbiome in depression. The brain-gut axis theory suggests there is a need to further explore the mechanism involving the gut microbiome in the susceptibility of offspring to depression caused by PS. In the present study we used a stress model relevant to depression in which pregnant female rats undergo prenatal restraint stress and the offspring show susceptibility to depression. High-resolution gene sequencing for 16S ribosomal RNA markers and non-targeted metabolomic analysis were used to evaluate the fecal microbiome and the availability of metabolites, respectively. PS was found to induce depressive-like behavior in susceptible offspring (PS-S), as detected by the sucrose preference and forced swimming tests, as well as altering Alpha and Beta diversity. The different microbiota between the PS-S and control groups were mainly involved in membrane transport, carbohydrate metabolism, amino acid metabolism, and replication and repair pathways. In total, 237 and 136 important differential metabolites with significant influence on modeling analysis were obtained under positive and negative modes, respectively. The main canonical pathways found to be altered were glycerophospholipid metabolism and glycerolipid metabolism. These results suggest that gut microbiota might contribute to the onset of PS-induced depression-like behavior by affecting the glycerophospholipid and glycerolipid metabolic pathways.

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.

Mental stress objective screening for workers using urinary neurotransmitters

BACKGROUND

Almost 10% of the population develop depression or anxiety disorder during their lifetime. Considering that people who are exposed to high stress are more likely to develop mental disorders, it is important to detect and remove mental stress before depression or anxiety disorder develops. We aimed to develop an objective screening test that quantifies mental stress in workers so that they can recognize and remove it before the disorder develops.

METHODS

We obtained urine specimens from 100 healthy volunteers (49 men and 51 women; age = 48.2 ± 10.8 years) after they received medical checks and answered the Brief Job Stress Questionnaire (BJSQ). Participants were divided into high- and low- stress groups according to their total BJSQ scores. We further analyzed six urinary neurotransmitters (dopamine, serotonin, 5-hydoroxyindoleacetic acid, gamma-aminobutyric acid, homovanillic acid, and vanillylmandelic acid) using liquid chromatography-mass spectrometry to compare their levels between the two groups.

RESULTS

We obtained the concentrations of the six analytes from 100 examinees and revealed that the levels of urinary dopamine (p = 0.0042) and homovanillic acid (p = 0.020) were significantly lower in the high-stress group than those in the low-stress group. No biases were observed between the two groups in 36 laboratory items. The stress index generated from the six neurotransmitter concentrations recognized high-stress group significantly. Moreover, we discovered that the level of each urinary neurotransmitter changed depending on various stress factors, such as dissatisfaction, physical fatigue, stomach and intestine problems, poor appetite, poor working environments, sleep disturbance, isolation, worry, or insecurity.

CONCLUSION

We revealed that urinary neurotransmitters could be a promising indicator to determine underlying mental stress. This study provides clues for scientists to develop a screening test not only for workers but also for patients with depression.

Altered MANF and RYR2 concentrations associated with hypolipidemia in the serum of patients with schizophrenia

Schizophrenia (SCZ) is associated with abnormal serum lipid profiles, but their relationship is poorly understood. Mesencephalic astrocyte-derived neurotrophic factor (MANF) is an important regulator of lipid metabolism. Previous studies have shown its involvement in the pathogenesis of numerous neuropsychiatric disorders, while its role in SCZ is still unknown. Therefore, this study was conducted to examine serum MANF levels in patients with SCZ, and to investigate the potential relationship between MANF, serum lipid levels and SCZ. The results showed that total cholesterol (TC) levels were significantly lower in 225 patients with SCZ than in 233 healthy controls (HCs). According to Ingenuity Pathway Analysis, hypolipidemia is associated with SCZ via MANF/ryanodine receptor 2 (RYR2) pathway. This theory was supported by another sample set, which showed significantly lower MANF levels and higher RYR2 levels in the serum of 170 SCZ patients compared to 80 HCs. Moreover, MANF and RYR2 levels both were significantly correlated with the severity of psychotic symptoms and TC levels. In addition, a model consisting of MANF and RYR2 was found to be effective in distinguishing SCZ patients from HCs. These findings suggested that the MANF/RYR2 pathway might serve as a bridge between hypolipidemia and SCZ, and MANF and RYR2 held promise as biomarkers for SCZ.

Plasma metabolomics and network pharmacology identified glutamate, glutamine, and arginine as biomarkers of depression under Shuganjieyu capsule treatment

Depression is a psychiatric disorder and confers an enormous burden on society. Mild to moderate forms of depression (MMD) are particularly common. Our previous studies showed that the Shuganjieyu (SGJY) capsule might improve depressive and cognitive symptoms in patients with MMD. However, biomarkers evaluating the efficacy of SGJY and the underlying mechanism remains unclear. The aim of the present study was to discover efficacy biomarkers and explore the underlying mechanisms of SGJY as antidepression treatment. Twenty-three patients with MMD were recruited and administered with SGJY for 8 weeks. Results showed that the content of 19 metabolites changed significantly in the plasma of patients with MMD, among which 8 metabolites improved significantly after SGJY treatment. Network pharmacology analysis showed that 19 active compounds, 102 potential targets, and 73 enzymes were related to the mechanistic action of SGJY. Through a comprehensive analysis, we identified four hub enzymes (GLS2, GLS, GLUL, and ADC), three key differential metabolites (glutamine, glutamate, and arginine), and two shared pathways (alanine, aspartate, and glutamate metabolism; and arginine biosynthesis). Receiver operating characteristic curve (ROC) analysis showed that the three metabolites had a high diagnostic ability. The expression of hub enzymes was validated using RT-qPCR in animal models. Overall, glutamate, glutamine, and arginine may be potential biomarkers for evaluating the efficacy of SGJY. The present study provides a new strategy for pharmacodynamic evaluation and mechanistic study of SGJY, and offers new information for clinical practice and treatment research.

Untargeted metabolomic analysis of metabolites related to body dysmorphic disorder (BDD)

Body dysmorphic disorder (BDD) is a disorder associated with depression and eating disorders. It often arises from minor defects in appearance or an individual imagining that he or she is defective. However, the mechanisms causing BDD remain unclear, and its pathogenesis and adjuvant treatment methods still need to be explored. Here, we employed a liquid chromatography-mass spectrometry (LC-MS)-based metabolomics approach to identify key metabolic differences in BDD versus healthy patients. We obtained plasma samples from two independent cohorts (including eight BDD patients and eight healthy control patients). Raw data were analyzed using Compound Discoverer to determine peak alignment, retention time correction, and extraction of peak areas. Metabolite structure identification was also obtained using Compound Discoverer by of accurate mass matching (< 10 ppm) and secondary spectral matching queries of compound databases. Next, multidimensional statistical analyses were performed using the ropls R package. These analyses included: unsupervised principal component analysis, supervised partial Least-Squares Discriminant Analysis, and orthogonal partial Least-Squares Discriminant Analysis. We then identified the most promising metabolic signatures associated with BDD across all metabolomic datasets. Principal component analysis showed changes in small-molecule metabolites in patients, and we also found significant differences in metabolite abundance between the BDD and normal groups. Our findings suggest that the occurrence of BDD may be related to metabolites participating in the following KEGG pathways: ABC transporters, purine metabolism, glycine, serine and threonine metabolism, pyrimidine, pyrimidine metabolism, biosynthesis of 12-, 14-, and 16-membered macrolides, microbial metabolism in diverse environments, biosynthesis of secondary metabolites, and caffeine and insect hormone biosynthesis.

Perinatal mood and anxiety disorders: biomarker discovery using plasma proteomics

BACKGROUND

Perinatal mood and anxiety disorders encompass a range of mental health disorders that occur during pregnancy and up to 1 year postpartum, affecting approximately 20% of women. Traditional risk factors, such as a history of depression and pregnancy complications including preeclampsia, are known. Their predictive utility, however, is not specific or sensitive enough to inform clinical decision-making or prevention strategies for perinatal mood and anxiety disorders. Better diagnostic and prognostic models are needed for early identification and referral to treatment.

OBJECTIVE

This study aimed to determine if a panel of novel third-trimester plasma protein biomarkers in pregnant women can be used to identify those who have a high predisposed risk for perinatal mood and anxiety disorders within 3 months postpartum.

STUDY DESIGN

We studied 52 women (n=34 with a risk for perinatal mood and anxiety disorders and n=18 controls) among whom mental health screening was conducted at 2 time points, namely in the third trimester and again at 3 months postdelivery. An elevated perinatal mood and anxiety disorder risk was identified by screening individuals with above-validated cutoffs for depression (Edinburgh Postnatal Depression Scale ≥12), anxiety (Overall Anxiety Severity and Impairment Scale ≥7), and/or posttraumatic stress disorder (Impact of Events Scale >26) at both time points. Plasma samples collected in the third trimester were screened using the aptamer-based SomaLogic SomaScan proteomic assay technology to evaluate perinatal mood and anxiety disorder-associated changes in the expression of 1305 protein analytes. Ingenuity Pathway Analysis was conducted to highlight pathophysiological relationships between perinatal mood and anxiety disorder-specific proteins found to be significantly up- or down-regulated in all subjects with perinatal mood and anxiety disorder and in those with perinatal mood and anxiety disorders and no preeclampsia.

RESULTS

From a panel of 53 significant perinatal mood and anxiety disorder-associated proteins, a unique 20-protein signature differentiated perinatal mood and anxiety disorder cases from controls in a principal component analysis (P<.05). This protein signature included NCAM1, NRCAM, and NTRK3 that converge around neuronal signaling pathways regulating axonal guidance, astrocyte differentiation, and maintenance of GABAergic neurons. Interestingly, when we restricted the analysis to subjects without preeclampsia, a 30-protein signature differentiated perinatal mood and anxiety disorder cases from all controls without overlap on the principal component analysis (P<.001). In the nonpreeclamptic perinatal mood and anxiety disorder group, we observed increased expression of proteins, such as CXCL11, CXCL6, MIC-B, and B2MG, which regulate leucocyte migration, inflammation, and immune function.

CONCLUSION

Participants with perinatal mood and anxiety disorders had a unique and distinct plasma protein signature that regulated a variety of neuronal signaling and proinflammatory pathways. Additional validation studies with larger sample sizes are needed to determine whether some of these molecules can be used in conjunction with traditional risk factors for the early detection of perinatal mood and anxiety disorders.

MANF/EWSR1/ANXA6 pathway might as the bridge between hypolipidemia and major depressive disorder

Major depressive disorder (MDD) involves changes in lipid metabolism, but previous findings are contradictory. Mesencephalic astrocyte-derived neurotrophic factor (MANF) is considered to be a regulator of lipid metabolism. To date, the function of MANF has been studied in many brain disorders, but not in MDD. Therefore, to better understand the role of lipids in MDD, this study was conducted to examine lipid levels in the serum of MDD patients and to investigate the potential function of MANF in MDD. First, the data on total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) in serum from 354 MDD patients and 360 healthy controls (HCs) were collected and analyzed. The results showed that there were significantly lower concentrations of TC and LDL-C in MDD patients compared with HCs, and TC levels were positively correlated with LDL-C levels. Bioinformatics analysis indicated that MANF/EWSR1/ANXA6 pathway might serve as the connecting bridge through which hypolipidemia played a functional role in MDD. Second, to verify this hypothesis, serum samples were collected from 143 MDD patients, and 67 HCs to measure the levels of MANF, EWSR1, and ANXA6 using ELISA kits. The results showed that compared to HCs, MDD patients had a significantly lower level of MANF and higher levels of ANXA6 and EWSR1, and these molecules were significantly correlated with both TC level and Hamilton Depression Rating Scales (HDRS) score. In addition, a discriminative model consisting of MANF, EWSR1, and ANXA6 was identified. This model was capable of distinguishing MDD subjects from HCs, yielded an area under curve of 0.9994 in the training set and 0.9569 in the testing set. Taken together, our results suggested that MANF/EWSR1/ANXA6 pathway might act as the bridge between hypolipidemia and MDD, and these molecules held promise as potential biomarkers for MDD.

Gut microbiome metabolites as key actors in atherosclerosis co-depression disease

Cardiovascular diseases, mainly characterized by atherosclerosis (AS), and depression have a high comorbidity rate. However, previous studies have been conducted under a single disease, and there is a lack of studies in comorbid states to explore the commonalities in the pathogenesis of both diseases. Modern high-throughput technologies have made it clear that the gut microbiome can affect the development of the host's own disorders and have shown that their metabolites are crucial to the pathophysiology of AS and depression. The aim of this review is to summarize the current important findings on the role of gut microbiome metabolites such as pathogen-associated molecular patterns, bile acids, tryptophan metabolites, short-chain fatty acids, and trimethylamine N -oxide in depression and AS disease, with the aim of identifying potential biological targets for the early diagnosis and treatment of AS co-depression disorders.

Tryptophan-5-HT pathway disorder was uncovered in the olfactory bulb of a depression mice model by metabolomic analysis

Major depression (MD) is a severe mental illness that creates a heavy social burden, and the potential molecular mechanisms remain largely unknown. Lots of research demonstrate that the olfactory bulb is associated with MD. Recently, gas chromatography-mass spectrometry-based metabolomic studies on depressive rats indicated that metabolisms of purine and lipids were disordered in the olfactory bulb. With various physicochemical properties and extensive concentration ranges, a single analytical technique could not completely cover all metabolites, hence it is necessary to adopt another metabolomic technique to seek new biomarkers or molecular mechanisms for depression. Therefore, we adopted a liquid chromatography-mass spectrometry metabonomic technique in the chronic mild stress (CMS) model to investigate significant metabolic changes in the olfactory bulb of the mice. We discovered and identified 16 differential metabolites in the olfactory bulb of the CMS treatments. Metabolic pathway analysis by MetaboAnalyst 5.0 was generated according to the differential metabolites, which indicated that the tryptophan metabolism pathway was the core pathogenesis in the olfactory bulb of the CMS depression model. Further, the expressions of tryptophan hydroxylase (TpH) and aromatic amino acid decarboxylase (AAAD) were detected by western blotting and immunofluorescence staining. The expression of TpH was increased after CMS treatment, and the level of AAAD was unaltered. These results revealed that abnormal metabolism of the tryptophan pathway in the olfactory bulb mediated the occurrence of MD.

The molecular pathophysiology of depression and the new therapeutics

Major depressive disorder (MDD) is a highly prevalent and disabling disorder. Despite the many hypotheses proposed to understand the molecular pathophysiology of depression, it is still unclear. Current treatments for depression are inadequate for many individuals, because of limited effectiveness, delayed efficacy (usually two weeks), and side effects. Consequently, novel drugs with increased speed of action and effectiveness are required. Ketamine has shown to have rapid, reliable, and long-lasting antidepressant effects in treatment-resistant MDD patients and represent a breakthrough therapy for patients with MDD; however, concerns regarding its efficacy, potential misuse, and side effects remain. In this review, we aimed to summarize molecular mechanisms and pharmacological treatments for depression. We focused on the fast antidepressant treatment and clarified the safety, tolerability, and efficacy of ketamine and its metabolites for the MDD treatment, along with a review of the potential pharmacological mechanisms, research challenges, and future clinical prospects.

Differential Gut Microbiota Compositions Related With the Severity of Major Depressive Disorder

Objective

Increasing evidence shows a close relationship between gut microbiota and major depressive disorder (MDD), but the specific mechanisms remain unknown. This study was conducted to explore differential gut microbiota compositions related to the severity of MDD.

Methods

Healthy controls (HC) (n = 131) and MDD patients (n = 130) were included. MDD patients with Hamilton Depression Rating Scale (HDRS) score <25 and ≥25 were assigned into moderate (n = 72) and severe (n = 58) MDD groups, respectively. Univariate and multivariate analyses were used to analyze the gut microbiota compositions at the genus level.

Results

Thirty-six and 27 differential genera were identified in moderate and severe MDD patients, respectively. The differential genera in moderate and severe MDD patients mainly belonged to three (Firmicutes, Actinobacteriota, and Bacteroidota) and two phyla (Firmicutes and Bacteroidota), respectively. One specific covarying network from phylum Actinobacteriota was identified in moderate MDD patients. In addition, five genera (Collinsella, Eggerthella, Alistipes, Faecalibacterium, and Flavonifractor) from the shared differential genera by two MDD groups had a fair efficacy in diagnosing MDD from HC (AUC = 0.786).

Conclusions

Our results were helpful for further exploring the role of gut microbiota in the pathogenesis of depression and developing objective diagnostic methods for MDD.

Urinary metabolites as a predictive marker for perinatal depression: A secondary analysis of the mothers, Omega-3 & Mental Health Study

Background:

Perinatal depression has been associated with unfavorable pregnancy and childhood development outcomes; however, no objective markers exist to identify perinatal mood disorders. We investigated whether metabolites in maternal urine during pregnancy can predict increased depressive symptoms in late pregnancy and postpartum among pregnant women at risk for perinatal depression.

Methods:

We evaluated metabolomic markers in urine collected at 12–20 and 34–36 weeks’ gestation. We analyzed 49 urinary metabolites using ion pairing reversed-phase liquid chromatography-mass spectrometry. Depressive symptom severity was identified using Beck Depression Inventory (BDI) scores from 105 participants at 12–20 and 34–36 weeks’ gestation, and 6–8 weeks’ postpartum. Mixed model repeated measures analysis evaluated associations between changes in maternal urinary metabolites and BDI scores across pregnancy.

Results:

Increases in urinary xanthine and hypoxanthine were positively associated with increases in maternal depressive symptoms throughout pregnancy (p = 0.03 and 0.02, respectively). This finding did not persist after false discovery rate correction. None of the urinary metabolites examined were significantly associated with development of postpartum depressive symptoms.

Limitations:

This study is an exploratory secondary biologic sample analysis from a trial whose sample size was determined by a different primary outcome and expected effect size, which may have limited statistical power to detect associations between urinary metabolites, depressive symptoms, and mood trajectory over time.

Conclusions:

Increasing concentrations of xanthine and hypoxanthine were associated with increasing depressive symptoms throughout pregnancy. Further research is needed to evaluate the utility of these metabolic markers in identifying women at risk for perinatal depressive symptoms.

Metabolomics of Major Depressive Disorder: A Systematic Review of Clinical Studies

Although the understanding of the pathophysiology of major depressive disorder (MDD) has advanced greatly, this has not been translated into improved outcomes. To date, no biomarkers have been identified for the diagnosis, prognosis, and therapeutic management of MDD. Thus, we aim to review the biomarkers that are differentially expressed in MDD. A systematic review was conducted in January 2022 in the PubMed/MEDLINE, Scopus, Embase, PsycINFO, and Gale Academic OneFile databases for clinical studies published from January 2001 onward using the following terms: "Depression" OR "Depressive disorder" AND "Metabolomic." Multiple metabolites were found at altered levels in MDD, demonstrating the involvement of cellular signaling metabolites, components of the cell membrane, neurotransmitters, inflammatory and immunological mediators, hormone activators and precursors, and sleep controllers. Kynurenine and acylcarnitine were identified as consistent with depression and response to treatment. The most consistent evidence found was regarding kynurenine and acylcarnitine. Although the data obtained allow us to identify how metabolic pathways are affected in MDD, there is still not enough evidence to propose changes to current diagnostic and therapeutic actions. Some limitations are the heterogeneity of studies on metabolites, methods for detection, analyzed body fluids, and treatments used. The experiments contemplated in the review identified increased or reduced levels of metabolites, but not necessarily increased or reduced the activity of the associated pathways. The information acquired through metabolomic analyses does not specify whether the changes identified in the metabolites are a cause or a consequence of the pathology.

Sodium hydrosulfide reverses β2-microglobulin-induced depressive-like behaviors of male Sprague-Dawley rats: Involving improvement of synaptic plasticity and enhancement of Warburg effect in hippocampus

BACKGROUND

Our previous works demonstrated that β2-microglobulin (β2m), a systemic pro-aging factor, induce depressive-like behaviors. Hydrogen sulfide (H₂S) is identified as a potential target for treatment of depression. The aim of the present work is to explore whether H₂S antagonizes β2m-induced depressive-like behaviors and the underlying mechanisms.

METHODS

The depressive-like behaviors were detected using the novelty suppressed feeding test (NSFT), tail suspension test (TST), forced swimming test (FST) and open field test (OFT). The expressions of Warburg-related proteins, including hexokinase II (HK II), pyruvate kinase M2 (PKM2), Lactate dehydrogenase A (LDHA), pyruvate dehydrogenase (PDH) and pyruvate dehydrogenase kinase 1(PDK1), and synaptic plasticity-related proteins, including postsynaptic density protein 95 (PSD95) and synaptophysin1 (SYN1), were determined by western blotting.

RESULT

we found that NaHS (the donor of H₂S) attenuated the depressive-like behaviors in the β2m-exposed rats, as judged by NSFT, TST, FST, and OFT. We also demonstrated that NaHS enhanced the synaptic plasticity, as evidenced by the upregulations of PSD95 and SYN1 expressions in the hippocampus of β2m-exposed rats. Furthermore, NaHS improved the Warburg effect in the hippocampus of β2m-exposed rats, as evidenced by the upregulations of HK II, PKM2, LDHA and PDK1 expressions, and the downregulation of PDH expression.

CONCLUSION

H₂S prevents β2m-induced depressive-like behaviors, which is involved in improvement of hippocampal synaptic plasticity as a result of enhancement of hippocampal Warburg effect.

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.

Circulating choline pathway nutrients and depression after ischemic stroke

BACKGROUND AND PURPOSE

Choline pathway nutrients, including choline and betaine, are reported to exert antidepressant effects. However, there is little population-based evidence on the relationships between circulating choline and betaine and poststroke depression (PSD). We aimed to prospectively explore the associations between plasma choline and betaine and depression after ischemic stroke.

METHODS

This study was based on the China Antihypertensive Trial in Acute Ischemic Stroke. A total of 612 participants with plasma choline and betaine concentrations were included in the analysis. The study outcome was depression 3 months after ischemic stroke. Logistic regression models were performed to estimate the relationships between plasma choline and betaine and the risk of PSD. Risk reclassification and calibration of models with choline or betaine were analyzed.

RESULTS

Patients with PSD had lower choline and betaine levels than those without PSD (p < 0.05). Compared with tertile 1, the multivariable-adjusted odds ratios (95% CIs) for tertile 3 of choline and betaine were 0.54 (0.35-0.83) and 0.59 (0.38-0.92), respectively. Per 1 SD increase in choline or betaine was associated with a 25% (95% CI 9%-37%) or an 19% (95% CI 3%-32%) decreased risk of PSD, respectively. Furthermore, the addition of choline or betaine to the established risk factors model improved the risk reclassification for PSD, as shown by an increase in the net reclassification index and integrated discrimination improvement (all p < 0.05).

CONCLUSIONS

Patients with elevated levels of choline and betaine had a lower risk of depression after acute ischemic stroke, suggesting the protective significance of choline pathway nutrients for PSD.

Post-weaning A1/A2 β-casein milk intake modulates depressive-like behavior, brain μ-opioid receptors, and the metabolome of rats

The postnatal period is critical for brain and behavioral development and is sensitive to environmental stimuli, such as nutrition. Prevention of weaning from maternal milk was previously shown to cause depressive-like behavior in rats. Additionally, loss of dietary casein was found to act as a developmental trigger for a population of brain opioid receptors. Here, we explore the effect of exposure to milk containing A1 and A2 β-casein beyond weaning. A1 but not A2 β-casein milk significantly increased stress-induced immobility in rats, concomitant with an increased abundance of Clostridium histolyticum bacterial group in the caecum and colon of A1 β-casein fed animals, brain region-specific alterations of μ-opioid and oxytocin receptors, and modifications in urinary biochemical profiles. Moreover, urinary gut microbial metabolites strongly correlated with altered brain metabolites. These findings suggest that consumption of milk containing A1 β-casein beyond weaning age may affect mood via a possible gut-brain axis mechanism.

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Postnatal brain development is sensitive to nutritional exposures

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Consumption of A1 but not A2 β-casein milk post-weaning affects mood in rats

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Gut microbial, biochemical, and neurochemical changes accompany mood alterations

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Urinary gut microbial metabolites correlate with brain metabolites

Involvement of Tricarboxylic Acid Cycle Metabolites in Kidney Diseases

Mitochondria are complex organelles that orchestrate several functions in the cell. The primary function recognized is energy production; however, other functions involve the communication with the rest of the cell through reactive oxygen species (ROS), calcium influx, mitochondrial DNA (mtDNA), adenosine triphosphate (ATP) levels, cytochrome c release, and also through tricarboxylic acid (TCA) metabolites. Kidney function highly depends on mitochondria; hence mitochondrial dysfunction is associated with kidney diseases. In addition to oxidative phosphorylation impairment, other mitochondrial abnormalities have been described in kidney diseases, such as induction of mitophagy, intrinsic pathway of apoptosis, and releasing molecules to communicate to the rest of the cell. The TCA cycle is a metabolic pathway whose primary function is to generate electrons to feed the electron transport system (ETS) to drives energy production. However, TCA cycle metabolites can also release from mitochondria or produced in the cytosol to exert different functions and modify cell behavior. Here we review the involvement of some of the functions of TCA metabolites in kidney diseases.

Gut Microbiota-Derived Inflammation-Related Serum Metabolites as Potential Biomarkers for Major Depressive Disorder

Background

Although many works have been conducted to explore the biomarkers for diagnosing major depressive disorder (MDD), the widely accepted biomarkers are still not identified. Thus, the combined application of serum metabolomics and fecal microbial communities was used to identify gut microbiota-derived inflammation-related serum metabolites as potential biomarkers for MDD.

Methods

MDD patients and healthy controls (HCs) were included in this study. Both serum samples and fecal samples were collected. The liquid chromatography mass spectrometry (LC-MS) was used to detect the metabolites in serum samples, and the 16S rRNA gene sequencing was used to analyze the gut microbiota compositions in fecal samples.

Results

Totally, 60 MDD patients and 60 HCs were recruited. The 24 differential serum metabolites were identified, and 10 of these were inflammation-related metabolites. Three significantly affected inflammation-related pathways were identified using differential metabolites. The 17 differential genera were identified, and 14 of these genera belonged to phyla Firmicutes. Four significantly affected inflammation-related pathways were identified using differential genera. Five inflammation-related metabolites (LysoPC(16:0), deoxycholic acid, docosahexaenoic acid, taurocholic acid and LysoPC(20:0)) were identified as potential biomarkers. These potential biomarkers had significant correlations with genera belonged to phyla Firmicutes. The panel consisting of these biomarkers could effectively distinguish MDD patients from HCs with an area under the curve (AUC) of 0.95 in training set and 0.92 in testing set.

Conclusion

These findings suggested that the disturbance of phyla Firmicutes might be involved in the onset of depression by regulating host’s inflammatory response, and these potential biomarkers could be useful for future investigating the objective methods for diagnosing MDD.

Metabolomics-based discrimination of patients with remitted depression from healthy controls using 1H-NMR spectroscopy

The aim of the study was to investigate differences in metabolic profiles between patients with major depressive disorder (MDD) with full remission (FR) and healthy controls (HCs). A total of 119 age-matched MDD patients with FR (n = 47) and HCs (n = 72) were enrolled and randomly split into training and testing sets. A 1H-nuclear magnetic resonance (NMR) spectroscopy-based metabolomics approach was used to identify differences in expressions of plasma metabolite biomarkers. Eight metabolites, including histidine, succinic acid, proline, acetic acid, creatine, glutamine, glycine, and pyruvic acid, were significantly differentially-expressed in the MDD patients with FR in comparison with the HCs. Metabolic pathway analysis revealed that pyruvate metabolism via the tricarboxylic acid cycle linked to amino acid metabolism was significantly associated with the MDD patients with FR. An algorithm based on these metabolites employing a linear support vector machine differentiated the MDD patients with FR from the HCs with a predictive accuracy, sensitivity, and specificity of nearly 0.85. A metabolomics-based approach could effectively differentiate MDD patients with FR from HCs. Metabolomic signatures might exist long-term in MDD patients, with metabolic impacts on physical health even in patients with FR.

Emerging application of metabolomics on Chinese herbal medicine for depressive disorder

Depressive disorder is a kind of emotional disorder that is mainly manifested with spontaneous and persistent low mood. Its etiology is complex and still not fully understood. Metabolomics, an important part of system biology characterized by its integrity and systematicness, analyzes endogenous metabolites of small molecules in vivo and examines the metabolic status of the organism. It is widely used in the field of disease research for its unique advantage in the disease molecular marker discovering Due to fewer adverse reactions and high safety, Chinese herbal medicine (CHM) has great advantages in the treatment of chronic diseases including depression. Metabolomics has been gradually applied to the efficacy evaluation of CHM in treatment of depression and the metabolomics analysis exhibits a systemic metabolic shift in amino acids (such as alanine, glutamic acid, valine, etc.), organic acids (lactic acid, citric acid, stearic acid, palmitic acid, etc.), and sugars, amines, etc. These differential metabolites are mainly involved in energy metabolism, amino acid metabolism, lipid metabolism, etc. In this review, we have exemplified the study of CHM in animals or clinics on the depression, and revealed that CHM treatment has significantly changed the metabolic disorders associated with depression, promoting metabolic network reorganization through restoring of key metabolites, and metabolic pathways, which may be the main mechanism basis of CHM's treatment on depression. Besides, we further envisioned the future application of metabolomics in the study of CHM treatment of depression.

Assessment of trimethylamine N-oxide (TMAO) as a potential biomarker of severe stress in patients vulnerable to posttraumatic stress disorder (PTSD) after acute myocardial infarction

Background: Posttraumatic stress disorder (PTSD) is a frequently observed stress-related disorder after acute myocardial infarction (AMI) and it is characterized by numerous symptoms, such as flashbacks, intrusions and anxiety, as well as uncontrollable thoughts and feelings related to the trauma. Biological correlates of severe stress might contribute to identifying PTSD-vulnerable patients at an early stage. Objective: Aims of the study were (1) to determine whether blood levels of trimethylamine N-oxide (TMAO) vary immediately after AMI in patients with/without AMI-induced PTSD symptomatology, (2) to investigate whether TMAO is a potential biomarker that might be useful in the prediction of PTSD and the PTSD symptom subclusters re-experiencing, avoidance and hyperarousal, and (3) to investigate whether TMAO varies immediately after AMI in patients with/without depression 6 months after AMI. Method: A total of 114 AMI patients were assessed with the Hamilton-Depression Scale after admission to the hospital and 6 months later. The Clinician Administered PTSD Scale for DSM-5 was used to explore PTSD-symptoms at the time of AMI and 6 months after AMI. To assess patients' TMAO status, serum samples were collected at hospitalization and 6 months after AMI. Results: Participants with PTSD-symptomatology had significantly higher TMAO levels immediately after AMI than patients without PTSD-symptoms (ANCOVA: TMAO(PTSD x time), F = 4.544, df = 1, p = 0.035). With the inclusion of additional clinical predictors in a hierarchical logistic regression model, TMAO became a significant predictor of PTSD-symptomatology. No significant differences in TMAO levels immediately after AMI were detected between individuals with/without depression 6 months after AMI. Conclusions: An elevated TMAO level immediately after AMI might reflect severe stress in PTSD-vulnerable patients, which might also lead to a short-term increase in gut permeability to trimethylamine, the precursor of TMAO. Thus, an elevated TMAO level might be a biological correlate for severe stress that is associated with vulnerability to PTSD.

Assessment of Phytochemicals and Herbal Formula for the Treatment of Depression through Metabolomics

Depression is a widespread and persistent psychiatric disease. Due to various side effects and no curative treatments of conventional antidepressant drugs, botanical medicines have attracted considerable attention as a complementary and alternative approach. The pathogenesis of depression is quite complicated and unclear. Metabolomics is a promising new technique for the discovery of novel biomarkers for exploring the potential mechanisms of diverse diseases and assessing the therapeutic effects of drugs. In this article, we systematically reviewed the study of botanical medicine for the treatment of depression using metabolomics over a period from 2010 to 2019. Additionally, we summarized the potential biomarkers and metabolic pathways associated with herbal medicine treatment for depression. Through a comprehensive evaluation of herbal medicine as novel antidepressants and understanding of their pharmacomechanisms, a new perspective on expanding the application of botanical medicines for the treatment of depression is provided.

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.

Ferritin disorder in the plasma and hippocampus associated with major depressive disorder

Major depressive disorder (MDD) is a debilitating mental illness that can cause significant emotional disturbances and severe socioeconomic burdens. Rodent and nonhuman primate-based depression models have been studied, such as brain-derived neurotrophic factor (BDNF) and monoamine acid disorder hypotheses, as well as peripheral microbiota disturbances causing MDD; however, the pathogenesis is still largely unknown. This study aims to explore the relationship between ferritin and MDD. First, alterations in ferritin, including ferritin light chain (FTL) and ferritin heavy chain (FTH), in MDD patient plasma compared with healthy control (HC) plasma were detected using ELISA. Then, serum ferritin expression in cLPS-depressed mice was measured by ELISA. The existence of FTH in the hippocampus was validated by immunofluorescence, and the change in FTH levels in the hippocampus of mice injected with cLPS was detected by western blotting. FTL levels in MDD patients were decreased compared with those in HCs. In cLPS-depressed mice, serum ferritin was not different from that in the control group, while the expression of FTH in the hippocampus was significantly reduced in depressed mice. Our findings demonstrate the alteration of ferritin expression in MDD and provide new insight into the pathogenesis of MDD.

Perturbations in Amino Acid Metabolism in Reserpine-Treated Zebrafish Brain Detected by 1H Nuclear Magnetic Resonance-Based Metabolomics

Depression is a complex and disabling psychiatric disorder, which is expected to be a leading cause for disability by 2030. According to World Health Organization, about 350 million people are suffering with mental health disorders around the globe, especially depression. However, the mechanisms involved in stress-induced depression have not been fully elucidated. In this study, a stress-like state was pharmacologically induced in zebrafish using reserpine, a drug widely used to mediate depression in experimental animal models. Zebrafish received single intraperitoneal (i.p.) injections of 20, 40, and 80 mg/kg body weight reserpine doses and were subjected to open-field test at 2, 24, 48, 72, and 96 h after the treatment. Along with observed changes in behavior and measurement of cortisol levels, the fish were further examined for perturbations in their brain metabolites by ¹H nuclear magnetic resonance (NMR)-based metabolomics. We found a significant increase in freezing duration, whereas total distance travelled was decreased 24 h after single intraperitoneal injection of reserpine. Cortisol level was also found to be higher after 48 h of reserpine treatment. The ¹H NMR data showed that the levels of metabolites such as glutamate, glutamine, histamine, valine, leucine and histidine, lactate, l-fucose, betaine and γ-amino butyric acid (GABA), β-hydroxyisovalerate, and glutathione were significantly decreased in the reserpine-treated group. This study provided some insights into the molecular nature of stress that could contribute toward a better understanding of depression disorder.

Metabolic Profiling Indicates Diversity in the Metabolic Physiologies Associated With Maternal Postpartum Depressive Symptoms

Background: Postpartum depression (PPD) is a devastating disease requiring improvements in diagnosis and prevention. Blood metabolomics identifies biological markers discriminatory between women with and those without antenatal depressive symptoms. Whether this cutting-edge method can be applied to postpartum depressive symptoms merits further investigation. Methods: As a substudy within the Biology, Affect, Stress, Imagine and Cognition Study, 24 women with PPD symptom (PPDS) assessment at 6 weeks postpartum were included. Controls were selected as having a score of ≤ 6 and PPDS cases as ≥12 on the Edinburgh Postnatal Depression Scale. Blood plasma was collected at 10 weeks postpartum and analyzed with gas chromatography-mass spectrometry metabolomics. Results: Variations of metabolomic profiles within the PPDS samples were identified. One cluster showed altered kidney function, whereas the other, a metabolic syndrome profile, both previously associated with depression. Five metabolites (glycerol, threonine, 2-hydroxybutanoic acid, erythritol, and phenylalanine) showed higher abundance among women with PPDSs, indicating perturbations in the serine/threonine and glycerol lipid metabolism, suggesting oxidative stress conditions. Conclusions: Alterations in certain metabolites were associated with depressive pathophysiology postpartum, whereas diversity in PPDS physiologies was revealed. Hence, plasma metabolic profiling could be considered in diagnosis and pathophysiological investigation of PPD toward providing clues for treatment. Future studies require standardization of various subgroups with respect to symptom onset, lifestyle, and comorbidities.

Urinary Metabolite Signatures for Predicting Elderly Stroke Survivors with Depression

BACKGROUND

Post-stroke depression (PSD) is a major complication in stroke survivors, especially in elderly stroke survivors. But there are still no objective methods to diagnose depression in elderly stroke survivors. Thus, this study was conducted to identify potential biomarkers for diagnosing elderly PSD subjects.

METHODS

Elderly (60 years or older) stroke survivors with depression were assigned into the PSD group, and elderly stroke survivors without depression and elderly healthy controls (HCs) were assigned into the non-depressed group. Urinary metabolite signatures obtained from gas chromatography-mass spectrometry (GC-MS)-based metabolomic platform were collected. Both univariate and multivariate statistical analysis were used to find the differential urinary metabolites between the two groups.

RESULTS

The 78 elderly HCs, 122 elderly stroke survivors without depression and 124 elderly PSD subjects were included. A set of 13 differential urinary metabolites responsible for distinguishing PSD subjects from non-depressed subjects were found. The Phenylalanine, tyrosine and tryptophan biosynthesis, Phenylalanine metabolism and Galactose metabolism were found to be significantly changed in elderly PSD subjects. The phenylalanine was significantly negatively correlated with age and depressive symptoms. Meanwhile, a biomarker panel consisting of 3-hydroxyphenylacetic acid, tyrosine, phenylalanine, sucrose, palmitic acid, glyceric acid, azelaic acid and α-aminobutyric acid was identified.

CONCLUSION

These results provided candidate molecules for developing objective methods to diagnose depression in elderly stroke survivors, suggested that taking supplements of phenylalanine might be an effective method to prevent depression in elderly stroke survivors, and would be helpful for future revealing the pathophysiological mechanism of PSD.

A Load to Find Clinically Useful Biomarkers for Depression

Depression is heterogeneous and complex disease with diverse symptoms. Its neurobiological underpinning is still not completely understood. For now, there are still no validated, easy obtainable, clinically useful noninvasive biomarker(s) or biomarker panel that will be able to confirm a diagnosis of depression, its subtypes and improve diagnostic procedures. Future multimodal preclinical and clinical research that involves (epi)genetic, molecular, cellular, imaging, and other studies is necessary to advance our understanding of the role of monoamines, GABA, HPA axis, neurotrophins, metabolome, and glycome in the pathogenesis of depression and their potential as diagnostic, prognostic, and treatment response biomarkers. These studies should be focused to include the first-episode depression and antidepressant drug-naïve patients with large sample sizes to reduce variability in different biological and clinical parameters. At present, metabolomics study revealed with high precision that a neurometabolite panel consisting of plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) might represent clinically useful biomarkers of MDD.

Bacterial Metabolites of Human Gut Microbiota Correlating with Depression

Depression is a global threat to mental health that affects around 264 million people worldwide. Despite the considerable evolution in our understanding of the pathophysiology of depression, no reliable biomarkers that have contributed to objective diagnoses and clinical therapy currently exist. The discovery of the microbiota-gut-brain axis induced scientists to study the role of gut microbiota (GM) in the pathogenesis of depression. Over the last decade, many of studies were conducted in this field. The productions of metabolites and compounds with neuroactive and immunomodulatory properties among mechanisms such as the mediating effects of the GM on the brain, have been identified. This comprehensive review was focused on low molecular weight compounds implicated in depression as potential products of the GM. The other possible mechanisms of GM involvement in depression were presented, as well as changes in the composition of the microbiota of patients with depression. In conclusion, the therapeutic potential of functional foods and psychobiotics in relieving depression were considered. The described biomarkers associated with GM could potentially enhance the diagnostic criteria for depressive disorders in clinical practice and represent a potential future diagnostic tool based on metagenomic technologies for assessing the development of depressive disorders.

Peripheral Markers of Depression

Major Depressive Disorder (MDD) is a leading cause of disability worldwide, creating a high medical and socioeconomic burden. There is a growing interest in the biological underpinnings of depression, which are reflected by altered levels of biological markers. Among others, enhanced inflammation has been reported in MDD, as reflected by increased concentrations of inflammatory markers-C-reactive protein, interleukin-6, tumor necrosis factor-α and soluble interleukin-2 receptor. Oxidative and nitrosative stress also plays a role in the pathophysiology of MDD. Notably, increased levels of lipid peroxidation markers are characteristic of MDD. Dysregulation of the stress axis, along with increased cortisol levels, have also been reported in MDD. Alterations in growth factors, with a significant decrease in brain-derived neurotrophic factor and an increase in fibroblast growth factor-2 and insulin-like growth factor-1 concentrations have also been found in MDD. Finally, kynurenine metabolites, increased glutamate and decreased total cholesterol also hold promise as reliable biomarkers for MDD. Research in the field of MDD biomarkers is hindered by insufficient understanding of MDD etiopathogenesis, substantial heterogeneity of the disorder, common co-morbidities and low specificity of biomarkers. The construction of biomarker panels and their evaluation with use of new technologies may have the potential to overcome the above mentioned obstacles.

Acyl-Carnitine plasma levels and their association with metabolic syndrome in individuals with schizophrenia

The metabolic syndrome (MetS) affects individuals with schizophrenia at a higher rate when compared to individuals in the general population. Accumulating evidence indicated that subjects with MetS generally manifest elevated levels of acyl-carnitines, which are important carriers for transporting fatty acyl group. Abnormalities of acyl-carnitines in individuals with schizophrenia with or without MetS had not been sufficiently characterized. We conducted this post-hoc analysis with our published data to further evaluate the differences of 29 acyl-carnitines in 46 individuals with schizophrenia with MetS and 123 without MetS. The rate of MetS was 27.2% (46/169) in the individuals with schizophrenia. After FDR correction, the individuals with schizophrenia and MetS showed significantly higher levels of 17 plasma acyl-carnitines, compared to individuals without MetS. Eight acyl-carnitines (i.e., C3, C4, C5, C6: 1, C10: 1, C10: 2, C14: 2-OH, C16: 2-OH) were significantly different between two groups after adjusting for age and sex. The correlation analysis reported that acyl-carnitine concentrations have potential correlations with certain metabolic parameters. Our findings provide valuable new clues for exploring the roles of acyl-carnitines in the diagnosis and treatment of schizophrenia. More data and molecular biology evidences are needed to replicate our findings and elucidate relevant mechanisms.

Urine metabolomic responses to aerobic and resistance training in rats under chronic unpredictable mild stress

Background

It is known that bioenergetics of aerobic and resistance exercise are not the same but both can effectively improve depression. However, it is not clear whether and how different types of exercise can influence depression through the same metabolic regulatory system. Metabolomics provides a way to study the correlation between metabolites and changes in exercise and/or diseases through the quantitative analysis of all metabolites in the organism. The objective of this study was to investigate the effects of aerobic and resistance training on urinary metabolites by metabolomics analysis in a rodent model of depression.

Methods

Male Sprague-Dawley rats were given chronic unpredictable mild stress (CUMS) for eight weeks. The validity of the modeling was assessed by behavioral indices. After four weeks of CUMS, the rats that developed depression were randomly divided into a depression control group, an aerobic training group and a resistance training group. There was also a normal control group. From week 5, the rats in the exercise groups were trained for 30 min per day, five days per week, for four weeks. The urine samples were collected pre and post the training program, and analyzed by proton nuclear magnetic resonance (¹H-NMR) spectroscopy.

Results

Both types of training improved depression-like behavior in CUMS rats. Compared with normal control, 21 potential biomarkers were identified in the urine of CUMS rats, mainly involved in energy, amino acids and intestinal microbial metabolic pathways. Common responses to the training were found in the two exercise groups that the levels of glutamine, acetone and creatine were significantly recalled (all P<0.05) Aerobic training also resulted in changes in pyruvate and trigonelline, while resistance training modified α-Oxoglutarate, citric acid, and trimethylamine oxide (all P<0.05).

Conclusions

Aerobic and resistance training resulted in common effects on the metabolic pathways of alanine-aspartate-glutamate, TCA cycle, and butyric acid. Aerobic training also had effects on glycolysis or gluconeogenesis and pyruvate metabolism, while resistance training had additional effect on intestinal microbial metabolism.

NMR-Based Metabonomic Study Reveals Intervention Effects of Polydatin on Potassium Oxonate-Induced Hyperuricemia in Rats

Previous studies have disclosed the antihyperuricemic effect of polydatin, a natural precursor of resveratrol; however, the mechanisms of action still remain elusive. The present study was undertaken to evaluate the therapeutic effects and the underlying mechanisms of polydatin on potassium oxonate-induced hyperuricemia in rats through metabonomic technology from a holistic view. Nuclear magnetic resonance (NMR) spectroscopy was applied to capture the metabolic changes in sera and urine collected from rats induced by hyperuricemia and polydatin treatment. With multivariate data analysis, significant metabolic perturbations were observed in hyperuricemic rats compared with the healthy controls. A total of eleven and six metabolites were identified as differential metabolites related to hyperuricemia in serum and urine of rats, respectively. The proposed pathways primarily included branched-chain amino acid (BCAA) metabolism, glycolysis, the tricarboxylic acid cycle, synthesis and degradation of ketone bodies, purine metabolism, and intestinal microflora metabolism. Additionally, some metabolites indicated the risk of renal injury induced by hyperuricemia. Polydatin significantly lowered the levels of serum uric acid, creatinine, and blood urea nitrogen and alleviated the abnormal metabolic status in hyperuricemic rats by partially restoring the balance of the perturbed metabolic pathways. Our findings shed light on the understanding of the pathophysiological process of hyperuricemia and provided a reference for revealing the metabolic mechanism produced by polydatin in the treatment of hyperuricemia.