Energy metabolism in major depressive disorder: Recent advances from omics technologies and imaging

Exploring the shared genetic basis of major depressive disorder and frailty

BACKGROUND

Major depressive disorder (MDD) and frailty impose substantial health and economic burdens. MDD is recognized as a significant risk factor for frailty, but the genetic associations between these conditions remain unclear. This study investigates the genetic correlation, shared pleiotropic loci, causal relationships, and comorbid genes between MDD and frailty.

METHODS

The genetic correlation between MDD and frailty was assessed using linkage disequilibrium score regression (LDSC) based on data from genome-wide association studies (GWAS). A detailed analysis was performed to identify shared pleiotropic loci and causal relationships through cross-phenotype association tests and Mendelian randomization. Additionally, tissue enrichment analysis was conducted using stratified LDSC, gene-based associations with both conditions were assessed using Multimarker Analysis of Genomic Annotation (MAGMA), and pathway analysis of comorbid genes was performed using the g: GOSt tool.

RESULTS

Our findings revealed a significant positive genetic correlation between MDD and frailty (rg = 0.65, P = 1.49E-219). We identified 57 shared risk SNPs between the two conditions, including 6 novel SNPs. Mendelian randomization analyses indicated robust causal effects of MDD on frailty and vice versa. Furthermore, we observed tissue-specific heritability enrichment in 9 brain tissues. By combining MAGMA and CPASSOC analyses, we identified 10 comorbid genes associated with both MDD and frailty, primarily involved in synapse formation, modulation, plasticity, and desaturase activity.

CONCLUSION

This study provides strong evidence for a shared genetic basis between MDD and frailty. The identification of comorbid genes offers new insights into the mechanisms underlying the relationship between these conditions.

Bioenergetic mapping of 'healthy microbiomes' via compound processing potential imprinted in gut and soil metagenomes

Despite mounting evidence of their importance in human health and ecosystem functioning, the definition and measurement of 'healthy microbiomes' remain unclear. More advanced knowledge exists on health associations for compounds used or produced by microbes. Environmental microbiome exposures (especially via soils) also help shape, and may supplement, the functional capacity of human microbiomes. Given the synchronous interaction between microbes, their feedstocks, and micro-environments, with functional genes facilitating chemical transformations, our objective was to examine microbiomes in terms of their capacity to process compounds relevant to human health. Here we integrate functional genomics and biochemistry frameworks to derive new quantitative measures of in silico potential for human gut and environmental soil metagenomes to process a panel of major compound classes (e.g., lipids, carbohydrates) and selected biomolecules (e.g., vitamins, short-chain fatty acids) linked to human health. Metagenome functional potential profile data were translated into a universal compound mapping 'landscape' based on bioenergetic van Krevelen mapping of function-level meta-compounds and corresponding functional relative abundances, reflecting imprinted genetic capacity of microbiomes to metabolize an array of different compounds. We show that measures of 'compound processing potential' associated with human health and disease (examining atherosclerotic cardiovascular disease, colorectal cancer, type 2 diabetes and anxious-depressive behavior case studies), and displayed seemingly predictable shifts along gradients of ecological disturbance in plant-soil ecosystems (three case studies). Ecosystem quality explained 60-92 % of variation in soil metagenome compound processing potential measures in a post-mining restoration case study dataset. With growing knowledge of the varying proficiency of environmental microbiota to process human health associated compounds, we might design environmental interventions or nature prescriptions to modulate our exposures, thereby advancing microbiota-oriented approaches to human health. Compound processing potential offers a simplified, integrative approach for applying metagenomics in ongoing efforts to understand and quantify the role of microbiota in environmental- and human-health.

Ganoderic acid A ameliorates depressive-like behaviors in CSDS mice: Insights from proteomic profiling and molecular mechanisms

OBJECTIVE

Ganoderic Acid A (GAA), a primary bioactive component in Ganoderma, has demonstrated ameliorative effects on depressive-like behaviors in a Chronic Social Defeat Stress (CSDS) mouse model. This study aims to elucidate the underlying molecular mechanisms through proteomic analysis.

METHODS

C57BL/6 J mice were allocated into control (CON), chronic social defeat stress (CSDS), GAA, and imipramine (IMI) groups. Post-depression induction via CSDS, the GAA and IMI groups received respective treatments of GAA (2.5 mg/kg) and imipramine (10 mg/kg) for five days. Behavioral assessments utilized standardized tests. Proteins from the prefrontal cortex were analyzed using LC-MS, with further examination via bioinformatics and PRM for differential expression. Western blot analysis confirmed protein expression levels.

RESULTS

Chronic social defeat stress (CSDS) induced depressive-like behaviors in mice, which were significantly alleviated by GAA treatment, comparably to imipramine (IMI). Proteomic analysis identified distinct proteins in control (305), GAA-treated (949), and IMI-treated (289) groups. Enrichment in mitochondrial and synaptic proteins was evident from GO and PPI analyses. PRM analysis revealed significant expression changes in proteins crucial for mitochondrial and synaptic functions (namely, Naa30, Bnip1, Tubgcp4, Atxn3, Carmil1, Nup37, Apoh, Mrpl42, Tprkb, Acbd5, Dcx, Erbb4, Ppp1r2, Fam3c, Rnf112, and Cep41). Western blot validation in the prefrontal cortex showed increased levels of Mrpl42, Dcx, Fam3c, Ppp1r2, Rnf112, and Naa30 following GAA treatment.

CONCLUSION

GAA exhibits potential antidepressant properties, with its action potentially tied to the modulation of synaptic functions and mitochondrial activities.

Metabolic Insights into Neuropsychiatric Illnesses and Ketogenic Therapies: A Transcriptomic View

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances, and the therapeutic effects of metabolic ketogenic therapy, remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

Novel Insights into Changes in Gene Expression within the Hypothalamus in Two Asthma Mouse Models: A Transcriptomic Lung-Brain Axis Study

Patients with asthma experience elevated rates of mental illness. However, the molecular links underlying such lung-brain crosstalk remain ambiguous. Hypothalamic dysfunction is observed in many psychiatric disorders, particularly those with an inflammatory component due to many hypothalamic regions being unprotected by the blood-brain barrier. To gain a better insight into such neuropsychiatric sequelae, this study investigated gene expression differences in the hypothalamus following lung inflammation (asthma) induction in mice, using RNA transcriptome profiling. BALB/c mice were challenged with either bacterial lipopolysaccharide (LPS, E. coli) or ovalbumin (OVA) allergens or saline control (n = 7 per group), and lung inflammation was confirmed via histological examination of postmortem lung tissue. The majority of the hypothalamus was micro-dissected, and total RNA was extracted for sequencing. Differential expression analysis identified 31 statistically significant single genes (false discovery rate FDR5%) altered in expression following LPS exposure compared to controls; however, none were significantly changed following OVA treatment, suggesting a milder hypothalamic response. When gene sets were examined, 48 were upregulated and 8 were downregulated in both asthma groups relative to controls. REACTOME enrichment analysis suggests these gene sets are involved in signal transduction metabolism, immune response and neuroplasticity. Interestingly, we identified five altered gene sets directly associated with neurotransmitter signaling. Intriguingly, many of these altered gene sets can influence mental health and or/neuroinflammation in humans. These findings help characterize the links between asthma-induced lung inflammation and the brain and may assist in identifying relevant pathways and therapeutic targets for future intervention.

Repurposing Ketamine in the Therapy of Depression and Depression-Related Disorders: Recent Advances and Future Potential

Depression represents a prevalent and enduring mental disorder of significant concern within the clinical domain. Extensive research indicates that depression is very complex, with many interconnected pathways involved. Most research related to depression focuses on monoamines, neurotrophic factors, the hypothalamic-pituitary-adrenal axis, tryptophan metabolism, energy metabolism, mitochondrial function, the gut-brain axis, glial cell-mediated inflammation, myelination, homeostasis, and brain neural networks. However, recently, Ketamine, an ionotropic N-methyl-D-aspartate (NMDA) receptor antagonist, has been discovered to have rapid antidepressant effects in patients, leading to novel and successful treatment approaches for mood disorders. This review aims to summarize the latest findings and insights into various signaling pathways and systems observed in depression patients and animal models, providing a more comprehensive view of the neurobiology of anxious-depressive-like behavior. Specifically, it highlights the key mechanisms of ketamine as a rapid-acting antidepressant, aiming to enhance the treatment of neuropsychiatric disorders. Moreover, we discuss the potential of ketamine as a prophylactic or therapeutic intervention for stress-related psychiatric disorders.

Abnormal energy metabolism, oxidative stress, and polyunsaturated fatty acid metabolism in depressed adolescents associated with childhood maltreatment: A targeted metabolite analysis

The purpose of this study was to explore the metabolomic differences between Major depressive disorder (MDD) and healthy individuals among adolescents and the association between childhood maltreatment (CM) and differentially abundant metabolites. The exploratory study included 40 first-episode drug-naïve adolescents with MDD and 20 healthy volunteers. We used the Beck Depression Inventory (BDI-13) to assess the severity of depression and the Childhood Trauma Questionnaire (CTQ) to assess the presence of childhood maltreatment. The plasma samples from all participants were collected for targeted metabolomics analysis using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC‒MS/MS) methods. Spearman correlation was applied to analyse the correlations between clinical variables and metabolites. We found 11 increased metabolites and 37 decreased metabolites that differed between adolescents with MDD and healthy individuals. Pathway enrichment analysis of differentially abundant metabolites showed abnormalities in energy metabolism and oxidative stress in MDD. Importantly, we found that creatine, valine, isoleucine, glutamic acid and pyroglutamic acid were negatively correlated with the BDI-13, while isocitric acid, fatty acid and acylcarnitine were negatively associated with CTQ, and 4-hydroxyproline was positively related to CTQ in adolescents with MDD. These studies provide new ideas for the pathogenesis and potential treatment of adolescents with MDD.

Differentially Altered Metabolic Pathways in the Amygdala of Subjects with Schizophrenia, Bipolar Disorder and Major Depressive Disorder

Background and hypothesis

A growing number of studies implicate a key role for metabolic processes in psychiatric disorders. Recent studies suggest that ketogenic diet may be therapeutically effective for subgroups of people with schizophrenia (SCZ), bipolar disorder (BPD) and possibly major depressive disorder (MDD). Despite this promise, there is currently limited information regarding brain energy metabolism pathways across these disorders, limiting our understanding of how brain metabolic pathways are altered and who may benefit from ketogenic diets. We conducted gene expression profiling on the amygdala, a key region involved in in the regulation of mood and appetitive behaviors, to test the hypothesis that amygdala metabolic pathways are differentially altered between these disorders.

Study Design

We used a cohort of subjects diagnosed with SCZ, BPD or MDD, and non-psychiatrically ill control subjects (n=15/group), together with our bioinformatic 3-pod analysis consisting of full transcriptome pathway analysis, targeted pathway analysis, leading-edge gene analysis and iLINCS perturbagen analysis.

Study Results

We identified differential expression of metabolic pathways in each disorder. Subjects with SCZ displayed downregulation of mitochondrial respiration and nucleotide metabolism pathways. In comparison, we observed upregulation of mitochondrial respiration pathways in subjects with MDD, while subjects with BPD displayed enrichment of pathways involved in carbohydrate metabolism. Several pathways associated with brain metabolism including immune system processes and calcium ion transport were also differentially altered between diagnosis groups.

Conclusion

Our findings suggest metabolic pathways are differentially altered in the amygdala in these disorders, which may impact approaches for therapeutic strategies.

Behavioral as well as hippocampal transcriptomic and microglial responses differ across sexes in adult mouse offspring exposed to a dual genetic and environmental challenge

INTRODUCTION

A wide range of positive, negative, and cognitive symptoms compose the clinical presentation of schizophrenia. Schizophrenia is a multifactorial disorder in which genetic and environmental risk factors interact for a full emergence of the disorder. Infectious challenges during pregnancy are a well-known environmental risk factor for schizophrenia. Also, genetic variants affecting the function of fractalkine signaling between neurons and microglia were linked to schizophrenia. Translational animal models recapitulating these complex gene-environment associations have a great potential to untangle schizophrenia neurobiology and propose new therapeutic strategies.

METHODS

Given that genetic variants affecting the function of fractalkine signaling between neurons and microglia were linked to schizophrenia, we compared the outcomes of a well-characterized model of maternal immune activation induced using the viral mimetic polyinosinic:polycytidylic acid (Poly I:C) in wild-type versus fractalkine receptor knockout mice. Possible behavioral and immune alterations were assessed in male and female offspring during adulthood. Considering the role of the hippocampus in schizophrenia, microglial analyses and bulk RNA sequencing were performed within this region to assess the neuroimmune dynamics at play. Males and females were examined separately.

RESULTS

Offspring exposed to the dual challenge paradigm exhibited symptoms relevant to schizophrenia and unpredictably to mood disorders. Males displayed social and cognitive deficits related to schizophrenia, while females mainly presented anxiety-like behaviors related to mood disorders. Hippocampal microglia in females exposed to the dual challenge were hypertrophic, indicative of an increased surveillance, whereas those in males showed on the other end of the spectrum blunted morphologies with a reduced phagocytosis. Hippocampal bulk-RNA sequencing further revealed a downregulation in females of genes related to GABAergic transmission, which represents one of the main proposed causes of mood disorders.

CONCLUSIONS

Building on previous results, we identified in the current study distinctive behavioral phenotypes in female mice exposed to a dual genetic and environmental challenge, thus proposing a new model of neurodevelopmentally-associated mood and affective symptoms. This paves the way to future sex-specific investigations into the susceptibility to developmental challenges using animal models based on genetic and immune vulnerability as presented here.

Characteristics of gut microbiota and metabolic phenotype in patients with major depressive disorder based on multi-omics analysis

Depression is a chronic, relapsing mental illness, often accompanied by loss of appetite, increased fatigue, insomnia and poor concentration. Here, we performed serum and urine metabolomics and fecal 16S rDNA sequencing studies on 57 unmedicated patients with major depressive disorder (MDD) and 57 healthy controls to characterize the metabolic and flora profile of MDD patients. We observed significant differences in serum and urinary metabolome between MDD patients and healthy individuals. Specifically, glycerophospholipid metabolism, primary bile acid biosynthesis and linoleic acid metabolism were significantly disordered in serum, and aminoacyl-tRNA biosynthesis, arginine biosynthesis, purine metabolism, phenylalanine metabolism, alanine, aspartate and glutamate metabolism, and pyrimidine metabolism were significantly impaired in urine. On this basis, we identified four potential diagnostic biomarkers for carnitine and four fatty acid classes in serum and urine, respectively. In addition, we observed significant disturbances of the gut microbiota in MDD patients. Spearman correlation analysis showed that imbalances in the gut microbiota were associated with metabolic disturbances, suggesting an important role of the gut microbiota in the pathogenesis of MDD. Our study provides a theoretical basis for further understanding of the pathogenesis of depression and for future clinical diagnosis and screening, as well as a basis for targeting the gut flora to optimize its structure for the prevention and treatment of depression.

Overview of metabolomic aspects in postpartum depression

Along with the typical biochemical alterations that occur during pregnancy, certain metabolic changes might be associated with the development of several psychiatric disorders, including postpartum depression (PPD), which is the most common type of psychiatric disorder during pregnancy or first postpartum year, and it develops in about 15% of women. Metabolomics is a rapidly developing discipline that deals with the metabolites as the final products of all genetically controlled biochemical pathways, highly influenced by external and internal changes. The aim of this paper was to review the published studies whose results suggest or deny a possible association between the fine regulation of the metabolome and PPD, enabling conclusions about whether metabolomics could be a useful tool in defining the biochemical pathways directly involved in the etiology, diagnosis and course of PPD. Beside numerous hormonal changes, a lot of different metabolic pathways have been discovered to be affected in women with PPD or associated with its development, including alterations in the energy metabolism, tryptophan and amino acid metabolism, steroid metabolism, purine cycle, as well as neurotransmitter metabolism. Additionally, metabolomics helped in defining the association between PPD and the exposure to various endocrine disrupting metabolites during pregnancy. Finally, metabolome reflects different PPD therapies and exposure of fetus or breastfed infants to pharmacotherapy prescribed to a mother suffering from PPD. This review can help in creating the picture about metabolomics' broad application in PPD studies, but it also implies that its potential is still not completely used.

Downregulated NPAS4 in multiple brain regions is associated with major depressive disorder

Major Depressive Disorder (MDD) is a commonly observed psychiatric disorder that affects more than 2% of the world population with a rising trend. However, disease-associated pathways and biomarkers are yet to be fully comprehended. In this study, we analyzed previously generated RNA-seq data across seven different brain regions from three distinct studies to identify differentially and co-expressed genes for patients with MDD. Differential gene expression (DGE) analysis revealed that NPAS4 is the only gene downregulated in three different brain regions. Furthermore, co-expressing gene modules responsible for glutamatergic signaling are negatively enriched in these regions. We used the results of both DGE and co-expression analyses to construct a novel MDD-associated pathway. In our model, we propose that disruption in glutamatergic signaling-related pathways might be associated with the downregulation of NPAS4 and many other immediate-early genes (IEGs) that control synaptic plasticity. In addition to DGE analysis, we identified the relative importance of KEGG pathways in discriminating MDD phenotype using a machine learning-based approach. We anticipate that our study will open doors to developing better therapeutic approaches targeting glutamatergic receptors in the treatment of MDD.

Impaired eating behaviors but intact metabolic hormone levels in individuals with major depressive disorder and generalized anxiety disorder

BACKGROUND

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) contribute significantly to global health burdens. Identifying disease markers for these comorbid disorders can increase understanding of pathogenesis and improve screening and intervention strategies. This study examined the association of physical health factors with MDD and MDD + GAD, across sexes.

METHODS

Two samples of participants from the Tulsa-1000 study (exploratory cohort: N = 136; confirmatory cohort: N = 185) completed body composition measurements, eating behavior (Three Factor Eating Questionnaire [TFEQ], Eating Disorder Diagnostic Scale [EDDS]), exercise questionnaires, and a blood draw. Metabolic hormone concentrations (leptin, insulin, and adiponectin) were analyzed from blood samples. Within each cohort, a two-way analysis of variance compared three groups (MDD, MDD + GAD, and healthy controls [HC]), sex, and their interaction on dependent variables. Hedges g was calculated to reflect effect size magnitude.

RESULTS

Medium-to-large group main effects across cohorts indicated that compared to HC: (1) MDD (g = 1.71/0.57) and MDD + GAD (g = 0.93/0.69) reported higher TFEQ Disinhibition scores; (2) MDD endorsed higher TFEQ Hunger scores (g = 0.66/0.48); and (3) MDD (g = 1.60/1.30) and MDD + GAD (g = 0.92/1.72) reported greater EDDS scores. Large sex main effects across cohorts indicated that females exhibited higher levels than males for percent body fat (g = 1.07/1.17), leptin (g = 1.27/1.12), and adiponectin (g=0.82/0.88).

LIMITATIONS

The power to detect group*sex interactions was limited due to a greater number of females (than males) in the study, and over half of clinical participants were taking medications.

CONCLUSIONS

Individuals with MDD and MDD + GAD demonstrate difficulties in regulating eating behaviors, potentially contributing to functional impairment and increased disease burden.

A review on linking stress, depression, and insulin resistance via low-grade chronic inflammation

Stress is a disturbance in homeostasis caused by psychological, physiological, or environmental factors. Prolonged reactions to chronic stress can be detrimental, resulting in various metabolic abnormalities, referred to as metabolic syndrome (MS). There is a reciprocal increased risk between MS and major depressive disorder. Recent studies established an association between inflammation and insulin signaling in type 2 diabetes mellitus with depression. In the present review, we discuss chronic low-grade inflammation, pathways of insulin resistance, and brain glucose metabolism in the context of neuroinflammation and depression. Specific attention is given to psychotropic drugs such as bupropion, mirtazapine, and nefazodone, anti-inflammatory drugs like Celecoxib (COX-2 inhibitor), Etanercept, adalimumab, IL-4Ra antagonist, Anti-IL- 17A antibody (Ixekizumab) and lifestyle modifications including exercise, dietary changes, and sleep hygiene. These therapeutic solutions offer potential in treating depression by targeting metabolic conditions like insulin resistance and inflammatory pathways. The article further explains the significance of a nutrition and antioxidants-rich diet, emphasizing the role of omega-3 fatty acids, vitamin D, zinc, and polyphenols, to improve immunity and activate anti-inflammatory signaling pathways.

Si-Ni-San reverses dietary fat absorption defects in a murine model of depression

Depression is often associated with fatigue/energy loss. However, we lack a detailed understanding of the factors explaining this association. In this study, we uncovered that depressed mice have a defect in fat absorption, resulting in weight loss and reduced circulating lipid levels. Si-Ni-San (SNS), a basic formula of traditional Chinese medicine (TCM) for the treatment of depression, was found to not only alleviate depression-like behaviors, but also reverse the weight loss and dietary fat absorption of depressed mice. We found that SNS improved body weight and circulating lipid levels of depressed mice by up-regulating proteins [such as FFA uptake protein (CD36), TAG synthesis proteins (GPAT3, MOGAT2, DGAT1 and DGAT2) and chylomicron packaging proteins (MTP and APOB)] in the fat absorption pathway. Furthermore, cell-based results conducted with LPS-stimulated mouse MODE-K and human Caco-2 cells support that SNS, as well as Sinensetin (SIN) and Nobiletin (NOB), the two active components of the formula, have a role in regulating lipid absorption. Mechanistic studies revealed that SNS reverses body weight and fat absorption defects of depressed mice in part through the NR1D1/BMAL1/DGAT2 axis. These findings advance our understanding of the crosstalk between depression and energy loss, highlight the importance of gut function in disease management, and provide a basis for the application of SNS in the clinical treatment of depression and related disorders.

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Neural energy computations based on Hodgkin-Huxley models bridge abnormal neuronal activities and energy consumption patterns of major depressive disorder

Limited by the current experimental techniques and neurodynamical models, the dysregulation mechanisms of decision-making related neural circuits in major depressive disorder (MDD) are still not clear. In this paper, we proposed a neural coding methodology using energy to further investigate it, which has been proven to strongly complement the neurodynamical methodology. We augmented the previous neural energy calculation method, and applied it to our VTA-NAc-mPFC neurodynamical H-H models. We particularly focused on the peak power and energy consumption of abnormal ion channel (ionic) currents under different concentrations of dopamine input, and investigated the abnormal energy consumption patterns for the MDD group. The results revealed that the energy consumption of medium spiny neurons (MSNs) in the NAc region were lower in the MDD group than that of the normal control group despite having the same firing frequencies, peak action potentials, and average membrane potentials in both groups. Dopamine concentration was also positively correlated with the energy consumption of the pyramidal neurons, but the patterns of different interneuron types were distinct. Additionally, the ratio of mPFC's energy consumption to total energy consumption of the whole network in MDD group was lower than that in normal control group, revealing that the mPFC region in MDD group encoded less neural information, which matched the energy consumption patterns of BOLD-fMRI results. It was also in line with the behavioral characteristics that MDD patients demonstrated in the form of reward insensitivity during decision-making tasks. In conclusion, the model in this paper was the first neural network energy computational model for MDD, which showed success in explaining its dynamical mechanisms with an energy consumption perspective. To build on this, we demonstrated that energy consumption levels can be used as a potential indicator for MDD, which also showed a promising pipeline to use an energy methodology for studying other neuropsychiatric disorders.

Downregulation of mGluR1-mediated signaling underlying autistic-like core symptoms in Shank1 P1812L-knock-in mice

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms that consist of social deficits and repetitive behaviors. Unfortunately, no effective medication is available thus far to target the core symptoms of ASD, since the pathogenesis remains largely unknown. To investigate the pathogenesis of the core symptoms in ASD, we constructed Shank1 P1812L-knock-in (KI) mice corresponding to a recurrent ASD-related mutation, SHANK1 P1806L, to achieve construct validity and face validity. Shank1 P1812L-KI heterozygous (HET) mice presented with social deficits and repetitive behaviors without the presence of confounding comorbidities. HET mice also exhibited downregulation of metabotropic glutamate receptor (mGluR1) and associated signals, along with structural abnormalities in the dendritic spines and postsynaptic densities. Combined with findings from Shank1 R882H-KI mice, our study confirms that mGluR1-mediated signaling dysfunction is a pivotal mechanism underlying the core symptoms of ASD. Interestingly, Shank1 P1812L-KI homozygous (HOM) mice manifested behavioral signs of impaired long-term memory rather than autistic-like core traits; thus, their phenotype was markedly different from that of Shank1 P1812L-KI HET mice. Correspondingly, at the molecular level, Shank1 P1812L-KI HOM displayed upregulation of AMPA receptor (GluA2)-related signals. The different patterns of protein changes in HOM and HET mice may explain the differences in behaviors. Our study emphasizes the universality of mGluR1-signaling hypofunction in the pathogenesis of the core symptoms in ASD, providing a potential target for therapeutic drugs. The precise correspondence between genotype and phenotype, as shown in HOM and HET mice, indicates the importance of reproducing disease-related genotypes in mouse models.

Chronic jet lag reduces motivation and affects other mood-related behaviors in male mice

Introduction: The circadian system regulates various physiological processes such as sleep-wake cycles, hormone secretion, metabolism, and the reaction to both natural and drug-based rewards. Chronic disruption of the circadian system caused by unsteady synchronization with light-dark (LD) schedules, such as advancing chronic jet lag (CJL), leads to adverse physiological effects and pathologies, and is linked with changes in mood and depressive behaviors in humans and rodent models. Methods: C57BL/6J male mice were subjected to circadian disruption through phase advances of 6 h every 2 days (CJL +6/2). Mice under 12:12-h LD cycle were used as controls. After 8 weeks under these conditions, a battery of behavioral tests was performed to assess if mood-related behaviors were affected. Results: Compared to controls under 24 h LD cycles, mice under CJL presented desynchronization of activity-rest rhythms that led to several behavioral impairments, including a decrease in motivation for food reward, and an increase in anxiety, anhedonia, and depressive-like behavior. Conclusion: Chronic circadian disruption, caused by an experimental CJL protocol, affects mood-related and reward-related behaviors in mice. Understanding the importance of the circadian system and its potential role for disruption due to CJL is important for maintaining good health and well-being.

Astrocyte metabolism and signaling pathways in the CNS

Astrocytes comprise half of the cells in the central nervous system and play a critical role in maintaining metabolic homeostasis. Metabolic dysfunction in astrocytes has been indicated as the primary cause of neurological diseases, such as depression, Alzheimer's disease, and epilepsy. Although the metabolic functionalities of astrocytes are well known, their relationship to neurological disorders is poorly understood. The ways in which astrocytes regulate the metabolism of glucose, amino acids, and lipids have all been implicated in neurological diseases. Metabolism in astrocytes has also exhibited a significant influence on neuron functionality and the brain's neuro-network. In this review, we focused on metabolic processes present in astrocytes, most notably the glucose metabolic pathway, the fatty acid metabolic pathway, and the amino-acid metabolic pathway. For glucose metabolism, we focused on the glycolysis pathway, pentose-phosphate pathway, and oxidative phosphorylation pathway. In fatty acid metabolism, we followed fatty acid oxidation, ketone body metabolism, and sphingolipid metabolism. For amino acid metabolism, we summarized neurotransmitter metabolism and the serine and kynurenine metabolic pathways. This review will provide an overview of functional changes in astrocyte metabolism and provide an overall perspective of current treatment and therapy for neurological disorders.

Venlafaxine's effect on resilience to stress is associated with a shift in the balance between glucose and fatty acid utilization

Brain metabolism is a fundamental process involved in the proper development of the central nervous system and in the maintenance of the main higher functions in humans. As consequence, energy metabolism imbalance has been commonly associated to several mental disorders, including depression. Here, by employing a metabolomic approach, we aimed to establish if differences in energy metabolite concentration may underlie the vulnerability and resilience in an animal model of mood disorder named chronic mild stress (CMS) paradigm. In addition, we have investigated the possibility that modulation of metabolite concentration may represent a pharmacological target for depression by testing whether repeated treatment with the antidepressant venlafaxine may normalize the pathological phenotype by acting at metabolic level. The analyses were conducted in the ventral hippocampus (vHip) for its key role in the modulation of anhedonia, a core symptom of patients affected by depression. Interestingly, we showed that a shift from glycolysis to beta oxidation seems to be responsible for the vulnerability to chronic stress and that vHip metabolism contributes to the ability of the antidepressant venlafaxine to normalize the pathological phenotype, as shown by the reversal of the changes observed in specific metabolites. These findings may provide novel perspectives on metabolic changes that could serve as diagnostic markers and preventive strategies for the early detection and treatment of depression as well as for the identification of potential drug targets.

Effects of Escitalopram on the Functional Neural Circuits in an Animal Model of Adolescent Depression

PURPOSE

Although escitalopram is known to be an effective drug for adult depression, its disease-modifying efficacy on adolescents remains controversial. The present study aimed to evaluate the therapeutic effect of escitalopram on behavioral aspects as well as functional neural circuits by means of positron emission tomography.

PROCEDURES

To generate the animal models of depression, restraint stress was used during the peri-adolescent period (RS group). Thereafter, escitalopram was administered after the end of stress exposure (Tx group). We performed NeuroPET studies of glutamate, glutamate, GABA, and serotonin systems.

RESULTS

The Tx group showed no body weight change compared to the RS group. In the behavioral tests, the Tx group also displayed the similar time spent in open arms and immobility time to those for RS. In the PET studies, brain uptake values for the Tx group revealed no significant differences in terms of glucose, GABA_A, and 5-HT_1A receptor densities, but lower mGluR5 PET uptake compared to the RS group. In the immunohistochemistry, the Tx group showed the significant loss of neuronal cells in the hippocampus compared to the RS group.

CONCLUSION

The administration of escitalopram had no therapeutic effect on the adolescent depression.

Microfluidic/HPLC combination to study carnosine protective activity on challenged human microglia: Focus on oxidative stress and energy metabolism

Carnosine (β-alanyl-L-histidine) is a naturally occurring endogenous peptide widely distributed in excitable tissues such as the brain. This dipeptide possesses well-demonstrated antioxidant, anti-inflammatory, and anti-aggregation properties, and it may be useful for treatment of pathologies characterized by oxidative stress and energy unbalance such as depression and Alzheimer's disease (AD). Microglia, the brain-resident macrophages, are involved in different physiological brain activities such synaptic plasticity and neurogenesis, but their dysregulation has been linked to the pathogenesis of numerous diseases. In AD brain, the activation of microglia towards a pro-oxidant and pro-inflammatory phenotype has found in an early phase of cognitive decline, reason why new pharmacological targets related to microglia activation are of great importance to develop innovative therapeutic strategies. In particular, microglia represent a common model of lipopolysaccharides (LPS)-induced activation to identify novel pharmacological targets for depression and AD and numerous studies have linked the impairment of energy metabolism, including ATP dyshomeostasis, to the onset of depressive episodes. In the present study, we first investigated the toxic potential of LPS + ATP in the absence or presence of carnosine. Our studies were carried out on human microglia (HMC3 cell line) in which LPS + ATP combination has shown the ability to promote cell death, oxidative stress, and inflammation. Additionally, to shed more light on the molecular mechanisms underlying the protective effect of carnosine, its ability to modulate reactive oxygen species production and the variation of parameters representative of cellular energy metabolism was evaluated by microchip electrophoresis coupled to laser-induced fluorescence and high performance liquid chromatography, respectively. In our experimental conditions, carnosine prevented LPS + ATP-induced cell death and oxidative stress, also completely restoring basal energy metabolism in human HMC3 microglia. Our results suggest a therapeutic potential of carnosine as a new pharmacological tool in the context of multifactorial disorders characterize by neuroinflammatory phenomena including depression and AD.

Astrocytic lactate dehydrogenase A regulates neuronal excitability and depressive-like behaviors through lactate homeostasis in mice

Alterations in energy metabolism are associated with depression. However, the role of glycolysis in the pathogenesis of depression and the underlying molecular mechanisms remain unexplored. Through an unbiased proteomic screen coupled with biochemical verifications, we show that the levels of glycolysis and lactate dehydrogenase A (LDHA), a glycolytic enzyme that catalyzes L-lactate production, are reduced in the dorsomedial prefrontal cortex (dmPFC) of stress-susceptible mice in chronic social defeat stress (CSDS) model. Conditional knockout of LDHA from the brain promotes depressive-like behaviors in both male and female mice, accompanied with reduced L-lactate levels and decreased neuronal excitability in the dmPFC. Moreover, these phenotypes could be duplicated by knockdown of LDHA in the dmPFC or specifically in astrocytes. In contrast, overexpression of LDHA reverses these phenotypic changes in CSDS-susceptible mice. Mechanistic studies demonstrate that L-lactate promotes neuronal excitability through monocarboxylic acid transporter 2 (MCT2) and by inhibiting large-conductance Ca²⁺-activated potassium (BK) channel. Together, these results reveal a role of LDHA in maintaining neuronal excitability to prevent depressive-like behaviors.

Skin Cancer Metabolic Profile Assessed by Different Analytical Platforms

Skin cancer, including malignant melanoma (MM) and keratinocyte carcinoma (KC), historically named non-melanoma skin cancers (NMSC), represents the most common type of cancer among the white skin population. Despite decades of clinical research, the incidence rate of melanoma is increasing globally. Therefore, a better understanding of disease pathogenesis and resistance mechanisms is considered vital to accomplish early diagnosis and satisfactory control. The "Omics" field has recently gained attention, as it can help in identifying and exploring metabolites and metabolic pathways that assist cancer cells in proliferation, which can be further utilized to improve the diagnosis and treatment of skin cancer. Although skin tissues contain diverse metabolic enzymes, it remains challenging to fully characterize these metabolites. Metabolomics is a powerful omics technique that allows us to measure and compare a vast array of metabolites in a biological sample. This technology enables us to study the dermal metabolic effects and get a clear explanation of the pathogenesis of skin diseases. The purpose of this literature review is to illustrate how metabolomics technology can be used to evaluate the metabolic profile of human skin cancer, using a variety of analytical platforms including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Data collection has not been based on any analytical method.

The Effects of Prenatal Dexamethasone Exposure on Brain Metabolic Homeostasis in Adulthood: Implications for Depression

Since depression produces a long-term negative impact on quality of life, understanding the pathophysiological changes implicated in this disorder is urgent. There is growing evidence that demonstrates a key role for dysfunctional energy metabolism in driving the onset of depression; thus, bioenergetic alterations should be extensively studied. Brain metabolism is known to be a glucocorticoid-sensitive process, but the long-lasting consequences in adulthood following high levels of glucocorticoids at the early stages of life are unclear. We examined a possible association between brain energetic changes induced by synthetic glucocorticoid-dexamethasone treatment in the prenatal period and depressive-like behavior. The results show a reduction in the oxidative phosphorylation process, Krebs cycle impairment, and a weakening of the connection between the Krebs cycle and glycolysis in the frontal cortex of animals receiving dexamethasone, which leads to ATP reduction. These changes appear to be mainly due to decreased expression of pyruvate dehydrogenase, impairment of lactate transport to neurons, and pyruvate to the mitochondria. Acute stress in adulthood only slightly modified the observed alterations in the frontal cortex, while in the case of the hippocampus, prenatal exposure to dexamethasone made this structure more sensitive to future adverse factors.

Maternal Metabolites Indicative of Mental Health Status during Pregnancy

Approximately 25% of individuals report poor mental health during their pregnancy or postpartum period, which may impact fetal neurodevelopment, birth outcomes, and maternal behaviors. In the present study, maternal serum samples were collected from pregnancies at 28-32 weeks gestation from the All Our Families (Alberta, Canada) cohort and assessed using nuclear magnetic resonance spectroscopy (¹H-NMR) and inductively coupled plasma-mass spectrometry (ICP-MS). Individuals with poor mental health at 34-36 weeks gestation were age-matched with mentally healthy pregnant controls. Metabolites were examined against validated self-reported mental health questionnaires for associations with depressive symptoms (Edinburgh Perinatal Depression Scale) and anxiety symptoms (Spielberger State-Trait Anxiety Inventory). ¹H-NMR metabolites were identified for depression (alanine, leucine, valine, methionine, phenylalanine, glucose, lactate, 3-hydroxybutyrate, and pyruvate) and anxiety (3-hydroxybutyrate). For ICP-MS, antimony and zinc were significant for depression and anxiety, respectively. Upon false discovery rate (FDR) correction at 10%, five ¹H-NMR metabolites (alanine, leucine, lactate, glucose, and phenylalanine) for depression remained significantly increased. Although results warrant further validation, the identified metabolites may serve as a predictive tool for assessing mental health during pregnancy as earlier identification has the potential to aid intervention and management of poor mental health symptomology, thus avoiding harmful consequences to both mother and offspring.

Diagnosis of Neural Activity among Abnormal Brain Regions in Patients with Major Depressive Disorder by Magnetic Resonance Imaging Features

In order to explore the diagnostic value of magnetic resonance imaging (MRI) for neural activity among abnormal brain regions in patients with major depressive disorder (MDD), thirty patients with MDD (observation group) were selected for comparison with 30 healthy people without MDD (control group). The included subjects were examined by MRI to compare the MRI features and were analyzed for regional homogeneity (ReHo) and amplitude low-frequency fluctuations (ALFF). The results showed that compared with the control group, the brain regions with increased ReHo and ALFF in the observation group were medial frontal gyrus (right), middle temporal lobe (left), inferior parietal lobe (left), and posterior cerebellar lobe (right); the brain region with increased ReHo and ALFF in the observation group was the middle temporal gyrus (right). Compared with the control group, there were significant differences in ReHo and ALFF in the observation group. It was found that the brain function of patients with MDD was abnormal compared with that of the normal subjects, and the brain network activity was also abnormal. MRI features can be used to explore abnormal brain regions in patients with MDD and have positive guiding value.

Adaptation of Lipid Profiling in Depression Disease and Treatment: A Critical Review

Major depressive disorder (MDD), also called depression, is a serious disease that impairs the quality of life of patients and has a high incidence, affecting approximately 3.8% of the world population. Its diagnosis is very subjective and is not supported by measurable biomarkers mainly due to the lack of biochemical markers. Recently, disturbance of lipid profiling has been recognized in MDD, in animal models of MDD or in depressed patients, which may contribute to unravel the etiology of the disease and find putative new biomarkers, for a diagnosis or for monitoring the disease and therapeutics outcomes. In this review, we provide an overview of current knowledge of lipidomics analysis, both in animal models of MDD (at the brain and plasma level) and in humans (in plasma and serum). Furthermore, studies of lipidomics analyses after antidepressant treatment in rodents (in brain, plasma, and serum), in primates (in the brain) and in humans (in plasma) were reviewed and give evidence that antidepressants seem to counteract the modification seen in lipids in MDD, giving some evidence that certain altered lipid profiles could be useful MDD biomarkers for future precision medicine.

A Whole Transcriptome Analysis in Peripheral Blood Suggests That Energy Metabolism and Inflammation Are Involved in Major Depressive Disorder

INTRODUCTION

Previous studies on transcriptional profiles suggested dysregulation of multiple RNA species in major depressive disorder (MDD). However, the interaction between different types of RNA was neglected. Therefore, integration of different RNA species in transcriptome analysis would be helpful for interpreting the functional readout of the transcriptome in MDD.

METHODS

A whole transcriptome sequencing were performed on the peripheral blood of 15 patients with MDD and 15 matched healthy controls (HCs). The differential expression of miRNAs, lncRNAs, circRNAs, and mRNAs was examined between MDD and HCs using empirical analysis of digital gene expression data in R (edgeR). Weighted correlation network analysis (WGCNA) was used to identify RNA co-expression modules associated with MDD. A ceRNA network was constructed for interpretation of interactions between different RNA species. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore potential biological mechanisms associated with MDD.

RESULTS

Multiple RNAs and co-expression modules were identified to be significantly dysregulated in MDD compared to HCs. Based on the differential RNAs, a ceRNA network that were dysregulated in MDD were constructed. The pathway networks that related to oxidative phosphorylation and the chemokine signaling were found to be associated with MDD.

CONCLUSION

Our results suggested that the processes of energy metabolism and inflammation may be involved in the pathophysiology of MDD.

Breathomics profiling of metabolic pathways affected by major depression: Possibilities and limitations

BACKGROUND

Major depressive disorder (MDD) is one of the most common psychiatric disorders with multifactorial etiologies. Metabolomics has recently emerged as a particularly potential quantitative tool that provides a multi-parametric signature specific to several mechanisms underlying the heterogeneous pathophysiology of MDD. The main purpose of the present study was to investigate possibilities and limitations of breath-based metabolomics, breathomics patterns to discriminate MDD patients from healthy controls (HCs) and identify the altered metabolic pathways in MDD.

METHODS

Breath samples were collected in Tedlar bags at awakening, 30 and 60 min after awakening from 26 patients with MDD and 25 HCs. The non-targeted breathomics analysis was carried out by proton transfer reaction mass spectrometry. The univariate analysis was first performed by T-test to rank potential biomarkers. The metabolomic pathway analysis and hierarchical clustering analysis (HCA) were performed to group the significant metabolites involved in the same metabolic pathways or networks. Moreover, a support vector machine (SVM) predictive model was built to identify the potential metabolites in the altered pathways and clusters. The accuracy of the SVM model was evaluated by receiver operating characteristics (ROC) analysis.

RESULTS

A total of 23 differential exhaled breath metabolites were significantly altered in patients with MDD compared with HCs and mapped in five significant metabolic pathways including aminoacyl-tRNA biosynthesis (p = 0.0055), branched chain amino acids valine, leucine and isoleucine biosynthesis (p = 0.0060), glycolysis and gluconeogenesis (p = 0.0067), nicotinate and nicotinamide metabolism (p = 0.0213) and pyruvate metabolism (p = 0.0440). Moreover, the SVM predictive model showed that butylamine (p = 0.0005, p_FDR=0.0006), 3-methylpyridine (p = 0.0002, p_FDR = 0.0012), endogenous aliphatic ethanol isotope (p = 0.0073, p_FDR = 0.0174), valeric acid (p = 0.005, p_FDR = 0.0162) and isoprene (p = 0.038, p_FDR = 0.045) were potential metabolites within identified clusters with HCA and altered pathways, and discriminated between patients with MDD and non-depressed ones with high sensitivity (0.88), specificity (0.96) and area under curve of ROC (0.96).

CONCLUSION

According to the results of this study, the non-targeted breathomics analysis with high-throughput sensitive analytical technologies coupled to advanced computational tools approaches offer completely new insights into peripheral biochemical changes in MDD.

In vivo magnetic resonance spectrometry imaging demonstrates comparable adaptation of brain energy metabolism to metabolic stress induced by 72 h of fasting in depressed patients and healthy volunteers

Major depressive disorder (MDD) is characterized by dysregulation of stress systems and by abnormalities in cerebral energy metabolism. Stress induction has been shown to impact neurometabolism in healthy individuals. Contrarily, neurometabolic changes in response to stress are insufficiently investigated in MDD patients. Metabolic stress was induced in MDD patients (MDD, N = 24) and in healthy individuals (CTRL, N = 22) by application of an established fasting protocol in which calorie intake was omitted for 72 h. Both study groups were comparable regarding age, gender distribution, and body mass index (BMI). Fasting-induced effects on brain high-energy phosphate levels and membrane phospholipid metabolism were assessed using phosphorus-31 magnetic resonance spectroscopy (³¹P-MRS). Two-way repeated measures ANOVAs did not reveal significant interaction effects (group x fasting) or group differences in adenosine triphosphate (ATP), phosphocreatine (PCr), inorganic phosphate (Pi), phosphomonoesters (PME), phosphodiesters (PDE), or pH levels between MDD and CTRL. Fasting, independent of group, significantly increased ATP and decreased Pi levels and an overall increase in PME/PDE ratio as marker for membrane turnover was observed. Overall these results indicate reactive changes in cerebral energetics and in membrane phospholipid metabolism in response to fasting. The observed effects did not significantly differ between CTRL and MDD, indicating that neurometabolic adaptation to metabolic stress is preserved in MDD patients.