Delineation of molecular pathway activities of the chronic antidepressant treatment response suggests important roles for glutamatergic and ubiquitin-proteasome systems

Early Handling Exerts Anxiolytic Effects and Alters Brain Mitochondrial Dynamics in Adult High Anxiety Mice

Early handling (EH), the brief separation of pups from their mother during early life, has been shown to exert beneficial effects. However, the impact of EH in a high anxiety background as well as the role of brain mitochondria in shaping EH-driven responses remain elusive.Here, we used a high (HAB) vs. normal (NAB) anxiety-related behavior mouse model to study how EH affects pup and dam behavior in divergent anxiety backgrounds. We also investigated EH-induced effects at the protein and mRNA levels in adult male HAB mice in the hypothalamus, the prefrontal cortex, and the hippocampus by examining the same mitochondrial/energy pathways and mitochondrial dynamics mechanisms (fission, fusion, biogenesis, and mitophagy) in all three brain regions.EH exerts anxiolytic effects in adult HAB but not NAB male mice and does not affect HAB or NAB maternal behavior, although basal HAB vs. NAB maternal behaviors differ. In adult HAB male mice, EH does not impact oxidative phosphorylation (OXPHOS) and oxidative stress in any of the brain regions studied but leads to increased protein expression of glycolysis enzymes and a correlation of anxiety-related behavior with Krebs cycle enzymes in HAB mice in the hypothalamus. Intriguingly, EH alters mitochondrial dynamics by increasing hypothalamic DRP1, OPA1, and PGC1a protein levels. At the mRNA level, we observe altered, EH-driven mitochondrial dynamics mRNA signatures which predominantly affect the prefrontal cortex.Taken together, our results show that EH exerts anxiolytic effects in adulthood in high anxiety and modulates mitochondrial dynamics pathways in a brain region-specific manner.

Deciphering the Metabolome under Stress: Insights from Rodent Models

Despite intensive research efforts to understand the molecular underpinnings of psychological stress and stress responses, the underlying molecular mechanisms remain largely elusive. Towards this direction, a plethora of stress rodent models have been established to investigate the effects of exposure to different stressors. To decipher affected molecular pathways in a holistic manner in these models, metabolomics approaches addressing altered, small molecule signatures upon stress exposure in a high-throughput, quantitative manner provide insightful information on stress-induced systemic changes in the brain. In this review, we discuss stress models in mice and rats, followed by mass spectrometry (MS) and nuclear magnetic resonance (NMR) metabolomics studies. We particularly focus on acute, chronic and early life stress paradigms, highlight how stress is assessed at the behavioral and molecular levels and focus on metabolomic outcomes in the brain and peripheral material such as plasma and serum. We then comment on common metabolomics patterns across different stress models and underline the need for unbiased -omics methodologies and follow-up studies of metabolomics outcomes to disentangle the complex pathobiology of stress and pertinent psychopathologies.

Antidepressant treatment effects on hippocampal protein turnover: Molecular and spatial insights from mass spectrometry

A major challenge in managing depression is that antidepressant drugs take a long time to exert their therapeutic effects. For the development of faster acting therapies, it is crucial to get an improved understanding of the molecular mechanisms underlying antidepressant mode of action. Here, we used a novel mass spectrometry-based workflow to investigate how antidepressant treatment affects brain protein turnover at single cell and subcellular resolution. We combined stable isotope metabolic labeling, quantitative Tandem Mass Spectrometry (qTMS) and Multi-isotope Imaging Mass Spectrometry (MIMS) to simultaneously quantify and image protein synthesis and turnover in hippocampi of mice treated with the antidepressant paroxetine. We identified changes in turnover of individual hippocampal proteins that reveal altered metabolism-mitochondrial processes and report on subregion-specific turnover patterns upon paroxetine treatment. This workflow can be used to investigate brain protein turnover changes upon pharmacological interventions at a resolution and precision that has not been possible with other methods to date. Our results reveal acute paroxetine effects on brain protein turnover and shed light on antidepressant mode of action. This article is protected by copyright. All rights reserved.

Duloxetine attenuates pain in association with downregulation of platelet serotonin transporter in patients with burning mouth syndrome and atypical odontalgia

OBJECTIVE

The aim of this study was evaluation of the association between severity of pain and expression of total or ubiquitinated serotonin transporter (SERT) protein in patients with burning mouth syndrome and atypical odontalgia (BMS/AO), who were treated by duloxetine.

METHODS

Patients with BMS/AO were assessed for severity of pain using the visual analog scale (VAS), and expression of total and ubiquitinated SERT protein in platelets before (baseline) and 12 weeks after duloxetine-treatment.

RESULTS

The expression of total and ubiquitinated SERT protein at baseline in all patients (n = 33) were higher and lower, respectively, compared to those in healthy controls. 12 weeks after duloxetine-treatment, there was no difference in the total SERT protein levels between patients (n = 21) and healthy controls. In the 16 patients who could be measured, mean VAS scores and total SERT protein levels were significantly decreased after the treatment, compared to those at baseline. There was tendency for a positive correlation between total SERT protein levels and VAS scores in these patients.

CONCLUSIONS

Our findings indicate that duloxetine relieves pain in association with downregulation of platelet SERT expression in patients with BMS/AO.

Multi-Omics Analysis Reveals Myelin, Presynaptic and Nicotinate Alterations in the Hippocampus of G72/G30 Transgenic Mice

The primate-specific G72/G30 gene locus has been associated with major psychiatric disorders, such as schizophrenia and bipolar disorder. We have previously generated transgenic mice which carry the G72/G30 locus and express the longest G72 splice variant (LG72) protein encoded by this locus with schizophrenia-related symptoms. Here, we used a multi-omics approach, including quantitative proteomics and metabolomics to investigate molecular alterations in the hippocampus of G72/G30 transgenic (G72Tg) mice. Our proteomics analysis revealed decreased expression of myelin-related proteins and NAD-dependent protein deacetylase sirtuin-2 (Sirt2) as well as increased expression of the scaffolding presynaptic proteins bassoon (Bsn) and piccolo (Pclo) and the cytoskeletal protein plectin (Plec1) in G72Tg compared to wild-type (WT) mice. Metabolomics analysis indicated decreased levels of nicotinate in G72Tg compared to WT hippocampi. Decreased hippocampal protein expression for selected proteins, namely myelin oligodentrocyte glycoprotein (Mog), Cldn11 and myelin proteolipid protein (Plp), was confirmed with Western blot in a larger population of G72Tg and WT mice. The identified molecular pathway alterations shed light on the hippocampal function of LG72 protein in the context of neuropsychiatric phenotypes.

Molecular Mechanisms Associated with Antidepressant Treatment on Major Depression

Major depressive disorder (MDD) is a complex and multifactorial psychiatric disorder that causes serious health, social, and economic concerns worldwide. The main treatment of the symptoms is through antidepressant (AD) drugs. However, not all patients respond properly to these drugs. Omic sciences are widely used to analyze not only biomarkers for the AD response but also their molecular mechanism. In this review, we aimed to focus on omics data to better understand the molecular mechanisms involving AD effects on MDD. We consistently found, from preclinical to clinical data, that glutamatergic transmission, immune/inflammatory processes, energy metabolism, oxidative stress, and lipid metabolism were associated with traditional and potential new ADs. Despite efforts of studies investigating biomarkers of response to ADs, which could contribute to personalized treatment, there is no biomarker panel available for clinical application. From clinical genomic studies, we found that the main findings contribute to the development of pharmacogenomic tests for AD efficacy for each patient. Several studies pointed at DRD2, PXDNL, CACNA1E, and CACNA2D1 genes as potential targets for MDD treatment and the efficacy and rapid-antidepressant effect of ketamine. Finally, more in-depth studies of the molecular targets pointed here are needed to determine the clinical relevance and provide further evidence for precision MDD treatment.

Exploring the metabolomic profile of cerebellum after exposure to acute stress

Psychological stress and stress-related disorders constitute a major health problem in modern societies. Although the brain circuits involved in emotional processing are intensively studied, little is known about the implication of cerebellum in stress responses whereas the molecular changes induced by stress exposure in cerebellum remain largely unexplored. Here, we investigated the effects of acute stress exposure on mouse cerebellum. We used a forced swim test (FST) paradigm as an acute stressor. We then analyzed the cerebellar metabolomic profiles of stressed (n = 11) versus control (n = 11) male CD1 mice by a Nuclear Magnetic Resonance (NMR)-based, untargeted metabolomics approach. Our results showed altered levels of 19 out of the 47 annotated metabolites, which are implicated in neurotransmission and N-acetylaspartic acid (NAA) turnover, as well as in energy and purine/pyrimidine metabolism. We also correlated individual metabolite levels with FST behavioral parameters, and reported associations between FST readouts and levels of 4 metabolites. This work indicates an altered metabolomic signature after acute stress in the cerebellum and highlights a previously unexplored involvement of cerebellum in stress responses.

Autophagy Induction and Accumulation of Phosphorylated Tau in the Hippocampus and Prefrontal Cortex of Adult C57BL/6 Mice Subjected to Adolescent Fluoxetine Treatment

BACKGROUND

Fluoxetine (FLX) represents the antidepressant of choice for the management of pediatric mood-related illnesses. Accumulating preclinical evidence suggests that ontogenic FLX exposure leads to deregulated affect-related phenotypes in adulthood. Mood-related symptomatology constitutes a risk-factor for various neurological disorders, including Alzheimer's disease (AD), making it possible for juvenile FLX history to exacerbate the development of neurodegenerative diseases.

OBJECTIVE

Because AD is characterized by the pathological accumulation of hyperphosphorylated tau, which can result from impaired function of protein degradation pathways, such as autophagy and the ubiquitin-proteasome system (UPS), we evaluated the long-term effects of adolescent FLX exposure on these pathways, using mice as a model system.

METHODS

We subjected C57BL/6 adolescent male mice to FLX (20 mg/kg/day) from postnatal day (PD) 35 to PD49. Twenty-one days after the last FLX injection (i.e., adulthood; PD70), mice were euthanized and, using immunoblotting analysis, we evaluated protein markers of autophagy (Beclin-1, LC3-II, p62) and the UPS (K48-pUb), as well as AD-associated forms of phosphorylated tau, within the hippocampus and prefrontal cortex.

RESULTS

Juvenile FLX pre-exposure mediated long-term changes in the expression of protein markers (increased LC3-II and decreased p62) that is consistent with autophagy activation, particularly in the prefrontal cortex. Furthermore, FLX history induced persistent accumulation of AD-associated variants of tau in both the hippocampus and prefrontal cortexConclusion: Adolescent FLX treatment may have enduring effects in the neuronal protein degradation machinery, which could adversely influence clearance of abnormal proteins, potentially predisposing individuals to developing AD in later life.

Exploring the metabolic characteristics and pharmacokinetic variation of paroxetine in healthy volunteers using a pharmacometabonomic approach

The pharmacokinetic parameters of paroxetine vary between individuals, leading to differences in efficacy. The focus of our research was to predict responses to paroxetine using a pharmacometabonomic approach combining metabolic phenotypes and pharmacokinetic parameters. The pharmacokinetics of 12 healthy volunteers treated with paroxetine over two cycles was determined using high-performance liquid chromatography tandem mass spectrometry. Metabolic profiling and phenotyping were performed on the blood samples that remained after pharmacokinetic studies, using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry. Thirty-nine metabolites (p < 0.05) increased or decreased after treatment with paroxetine. Vitamin B6 metabolism; valine, leucine, and isoleucine biosynthesis; phenylalanine metabolism; pantothenate and coenzyme A biosynthesis; tyrosine metabolism; and glyoxylate and dicarboxylate metabolism were likely to be relevant for the effects of paroxetine. The two-stage partial least squares (PLS) strategy was used to screen potential biomarkers and predict the pharmacokinetic parameters of paroxetine. An orthogonal PLS discriminant analysis strategy was then applied to separate the high- and low-value groups based on the screened biomarkers. Pearson correlation test and receiver operating characteristic curve analysis confirmed the key prediction biomarkers. Seven common biomarkers were able to predict both the area under the curve (AUC) and the maximum concentration (C_max): cortisone, l-tyrosine, phenylpyruvate, l-valine, 2-oxoglutarate, l-lactate, and glycerate. Furthermore, homoprotocatechuate and l-glutamate were unique biomarkers for AUC, and citicoline and fumarate were unique biomarkers for C_max. The selected biomarkers were able to predict the AUC and C_max and discriminate good responders from poor responders to paroxetine treatment. This trial was registered with http://www.chinadrugtrials.org.cn/ (no. CTR20171590).

Alteration of transthyretin and thyroxine-binding globulin in major depressive disorder: multiple reaction monitoring-based proteomic analysis

Background

Major depressive disorder (MDD), common mental disorder, lacks objective diagnostic and prognosis biomarkers. The objective of this study was to perform proteomic analysis to identify proteins with changed expression levels after antidepressant treatment and investigate differences in protein expression between MDD patients and healthy individuals.

Methods

A total of 111 proteins obtained from literature review were subjected to multiple reaction monitoring (MRM)-based protein quantitation. Finally, seven proteins were quantified for plasma specimens of 10 healthy controls and 78 MDD patients (those at baseline and at 6 weeks after antidepressant treatment of either selective serotonin reuptake inhibitors (SSRIs) or mirtazapine).

Results

Among 78 MDD patients, 35 patients were treated with SSRIs and 43 patients were treated with mirtazapine. Nineteen (54.3%) and 16 (37.2%) patients responded to SSRIs and mirtazapine, respectively. Comparing MDD patients with healthy individuals, alteration of transthyretin was observed in MDD (P = 0.026). A few differences were observed in protein levels related to SSRIs treatment, although they were not statistically significant. Plasma thyroxine-binding globulin (TBG) was different between before and after mirtazapine treatment only in responders (P = 0.007).

Conclusions

In proteomic analysis of plasma specimens from MDD patients, transthyretin and TBG levels were altered in MDD and changed after antidepressant treatment.

Construction and Analysis of a Diagnostic Model Based on Differential Expression Genes in Patients With Major Depressive Disorder

Background: Major depressive disorder (MDD) is a common and severe psychiatric disorder with a heavy burden on the individual and society. However, the prevalence varies significantly owing to the lack of auxiliary diagnostic biomarkers. To identify the shared differential expression genes (DEGs) with potential diagnostic value in both the hippocampus and whole blood, a systematic and integrated bioinformatics analysis was carried out. Methods: Two datasets from the Gene Expression Omnibus database (GSE53987 and GSE98793) were downloaded and analyzed separately. A weighted gene co-expression network analysis was performed to construct the co-expression gene network of DEGs from GSE53987, and the most disease-related module was extracted. The shared DEGs from the module and GSE98793 were identified using a Venn diagram. Functional pathway prediction was used to identify the most disease-related DEGs. Finally, several DEGs were chosen, and their potential diagnostic value was determined by receiver operating characteristic curve analysis. Results: After weighted gene co-expression network analysis, the most MDD-related module (MEgrey) was identified, and 623 DEGs were extracted from this module. The intersection between MEgrey and GSE98793 was calculated, and 163 common DEGs were identified. The co-expression network of 163 DEGs from these was then reconstructed. All hub genes were identified based on the connective degree of the reconstructed co-expression network. Based on the results of functional pathway enrichment, 17 candidate hub genes were identified. Finally, logistic regression and receiver operating characteristic curves showed that three candidate hub genes (CEP350, SMAD5, and HSPG2) had relatively high auxiliary value in the diagnosis of MDD. Conclusion: Our results showed that the combination of CEP350, SMAD5, and HSPG2 has a relatively high diagnostic value for MDD. Pathway enrichment analysis also showed that these genes may play an important role in the pathogenesis of MDD. These results suggest a potentially important role for this gene combination in clinical practice.

Paroxetine binding and activation of phosphofructokinase implicates energy metabolism in antidepressant mode of action

Selective serotonin reuptake inhibitors (SSRIs) are the predominant drugs prescribed for Major Depressive Disorder. The immediate pharmacological target of SSRIs is the serotonin transporter. However, the delayed therapeutic effect and high rate of patient non-response make it highly likely that SSRIs also have other molecular targets that are yet to be identified. Cellular thermal shift assay (CETSA) is a method based on thermal stabilization of target proteins upon drug binding. In the present study, we show that the SSRI paroxetine binds to phosphofructokinase (PFK) protein using CETSA. We found that mouse brain PFK and recombinant human PFK proteins are stabilized by paroxetine incubation. Chronic paroxetine treatment also significantly increased mouse brain PFK thermal stability. Paroxetine significantly elevated in vitro and in vivo PFK activity. Levels of several metabolites in glutamate- and energy metabolism-related pathways are significantly correlated with PFK activity in mouse hippocampus. Our data show that paroxetine can bind to PFK and affect its activity. Implications of these results for the antidepressant mode of action of paroxetine are discussed.

Paroxetine Administration Affects Microbiota and Bile Acid Levels in Mice

Recent interest in the role of microbiota in health and disease has implicated gut microbiota dysbiosis in psychiatric disorders including major depressive disorder. Several antidepressant drugs that belong to the class of selective serotonin reuptake inhibitors have been found to display antimicrobial activities. In fact, one of the first antidepressants discovered serendipitously in the 1950s, the monoamine-oxidase inhibitor Iproniazid, was a drug used for the treatment of tuberculosis. In the current study we chronically treated DBA/2J mice for 2 weeks with paroxetine, a selective serotonin reuptake inhibitor, and collected fecal pellets as a proxy for the gut microbiota from the animals after 7 and 14 days. Behavioral testing with the forced swim test revealed significant differences between paroxetine- and vehicle-treated mice. Untargeted mass spectrometry and 16S rRNA profiling of fecal pellet extracts showed several primary and secondary bile acid level, and microbiota alpha diversity differences, respectively between paroxetine- and vehicle-treated mice, suggesting that microbiota functions are altered by the drug. In addition to their lipid absorbing activities bile acids have important signaling activities and have been associated with gastrointestinal diseases and colorectal cancer. Antidepressant drugs like paroxetine should therefore be used with caution to prevent undesirable side effects.

Glucocorticoids negatively regulates chaperone mediated autophagy and microautophagy

Glucocorticoids are released from the adrenal cortex and are important for regulating various physiological functions. However, a persistent increase in glucocorticoids due to chronic stress causes various dysfunctions in the central nervous system which can lead to mental disorders such as depression. Macroautophagy, one of the pathways of the autophagy-lysosome protein degradation system, is dysregulated in psychiatric disorders, implicating a disturbance of protein degradation in the pathogenesis of psychiatric disorders. In the present study, we investigated whether glucocorticoids affect the activity of chaperone-mediated autophagy (CMA) and microautophagy (mA), the other two pathways of the autophagy-lysosome system. Treatment of human-derived AD293 cells and primary cultured rat cortical neurons with dexamethasone, a potent glucocorticoid receptor agonist, and endogenous glucocorticoids decreased both CMA and mA activities. However, this decrease was significantly suppressed by treatment with RU-486, a glucocorticoid receptor antagonist. In addition, dexamethasone significantly decreased lysosomal Hsc70. These findings suggest that glucocorticoids negatively regulate CMA and mA in a glucocorticoid receptor-dependent manner, and provide evidence for CMA and mA as novel therapeutic targets for depression.

A metabolomic study on the gender-dependent effects of maternal exposure to fenvalerate on neurodevelopment in offspring mice

BACKGROUND

The general population is widely exposed to fenvalerate. However, the effects of maternal exposure to fenvalerate on neurodevelopment in offspring and the underlying metabolic mechanism are largely unknown.

METHODS

Pregnant mice were exposed to fenvalerate for 11 consecutive days. The forced swimming test (FST) was performed in 35 day-old offspring to investigate the effects of fenvalerate on neurobehavioral responses. Blood serum free T4 and free T3 concentrations were measured using commercial ELISA. Blood and thyroid samples were used for metabolomic analyses with UPLC Q-Exactive. The expression levels of neurotransmitter metaolite receptors were determined in the frontal cortex of offspring using real-time PCR.

RESULTS

The immobility time, free T4 and free T3, and expression levels of Htr1a and Htr2a were statistically changed in offspring male mice. Metabolomic analysis revealed that the pentose phosphate pathway, starch and sucrose metabolism, glutamic acid metabolism were the key changed pathways in the blood, and thiamine metabolism was the key changed pathway in the thyroid.

CONCLUSION

Prenatal exposure to fenvalerate affected neurodevelopment in male offspring mice both via the changed abundances of metabolites involved in glycolysis related metabolism and medium-chain fatty acid metabolism, and the changes in 5-HT receptor expression.

Sialylated N-glycan profile during acute and chronic infections with Toxoplasma gondii in mice

Toxoplasma gondii is associated with physiological and psychiatric perturbations. The immune response is interrelated to the progress of anhedonia and despair symptoms of T. gondii-infected subjects. We recently reported that serum N-glycans were altered in mice displayed depressive-like behaviors. However, a novel biomarker that correlated to T. gondii infection and associated behaviors is demanded. Glycomics has been used to find affected glycoproteins during depression. The objective of this study is to investigate serum N-glycomics changes during infection with T. gondii in BALB/c mice, immunocompetent, or in severe combined immunodeficient mice, and after treatment with an immunostimulant; 1-methyl tryptophan. Glycans were examined through glycoblotting-protocol then investigated by MALDI-TOF/MS. Both depressive and sickness-related behaviors were significantly abundant (P ≤ 0.001 each), during acute T. gondii in immunocompetent mice, compared to controls. Only sickness symptoms were evident in immunodeficient mice infected with T. gondii, as associated with high expression level (P ≤ 0.001) of Peak # 15 (2 × Neu5Gc) compared to controls. The alteration of sialylated N-glycan expressions is important to detect the immune status of animals/humans against T. gondii. Moreover, 1-methyl tryptophan reduced depressive-like behavior (P ≤ 0.001) compared to controls. Therefore, sialylated N-glycan (Neu5Ac/Neu5Gc-terminal) is targeted to be used as a novel biomarker of sickness/depressive-like behaviors.

Gene expression signature of antidepressant treatment response/non-response in Flinders Sensitive Line rats subjected to maternal separation

Neurobiological underpinnings of treatment-resistant depression, a debilitating condition associated with significant functional impairment, have not been elucidated. Consequently, the aim of this study was to use animal models of response and resistance to antidepressant treatment, in an attempt to identify differences in associated transcriptional responses. Flinders Sensitive Line rats were subjected to maternal separation (MS) and chronically treated with Escitalopram or Nortriptyline. Antidepressants reduced immobility time in the forced swim test in non-MS rats, while lack of antidepressant behavioural response was observed in MS animals. We developed a novel bioinformatic algorithm that enabled identification of transcriptional signatures in hippocampus and pre-frontal cortex that discriminate vehicle- and antidepressant-treated subjects in both MS and non-MS rats. Functional annotation analysis showed that in antidepressant-responder rats the most enriched pathways included IQGAPs activation, toll-like receptor trafficking, energy metabolism, and regulation of endopeptidase activity. The analysis of interacting proteins implicated synaptic vesicles and neurotransmitter release, ubiquitin regulation, cytoskeleton organisation and carbohydrate metabolism. In contrast, in treatment-resistant MS rats, main expression changes were revealed in ribosomal proteins, inflammatory responses, transcriptional/epigenetic regulation, and small GTPases. Susceptibility signature shared Rtn1, Zdhhc5, Igsf6, and Sim1 genes with the latest depression GWAS meta-analysis, while antidepressant resistance signature shared Ctnnd1, Rbms3, Atp1a3, and Pla2r1 genes. In conclusion, this study demonstrated that distinct transcriptional signatures are associated with behavioural response or non-response to antidepressant treatment. The identification of genes involved in antidepressant response will increase the comprehension of the neurobiological underpinnings of treatment-resistant depression, thus contributing to identification of novel therapeutic targets.

Co-Expression Network Analysis Revealed That the ATP5G1 Gene Is Associated With Major Depressive Disorder

Major depressive disorder (MDD) is a leading cause of disability worldwide, although its etiology and mechanism remain unknown. The aim of our study was to identify hub genes associated with MDD and to illustrate the underlying mechanisms. A weighted gene co-expression network analysis (WGCNA) was performed to identify significant gene modules and hub genes associated with MDD in peripheral blood mononuclear cells (PBMCs) (n = 45). In the blue module (R ² = 0.95), five common hub genes in both co-expression network and protein-protein interaction (PPI) network were regarded as "real" hub genes. In another independent dataset, GSE52790, four genes were still significantly down-regulated in PBMCs from MDD patients compared with the controls. Furthermore, these four genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in PBMCs from 33 MDD patients and 41 healthy controls. The qRT-PCR analysis showed that ATP synthase membrane subunit c locus 1 (ATP5G1) was significantly down-regulated in samples from MDD patients than in control samples (t = -2.89, p-value = 0.005). Moreover, this gene was significantly differentially expressed between patients and controls in the prefrontal cortex (z = -2.83, p-value = 0.005). Highly significant differentially methylated positions were identified in the Brodmann area 25 (BA25), with probes in the ATP5G1 gene being significantly associated with MDD: cg25495775 (t = 2.82, p-value = 0.008), cg25856120 (t = -2.23, p-value = 0.033), and cg23708347 (t = -2.24, p-value = 0.032). These findings indicate that the ATP5G1 gene is associated with the pathogenesis of MDD and that it could serve as a peripheral biomarker for MDD.

Amitriptyline at an Environmentally Relevant Concentration Alters the Profile of Metabolites Beyond Monoamines in Gilt-Head Bream

The antidepressant amitriptyline is a widely used selective serotonin reuptake inhibitor that is found in the aquatic environment. The present study investigates alterations in the brain and the liver metabolome of gilt-head bream (Sparus aurata) after exposure at an environmentally relevant concentration (0.2 µg/L) of amitriptyline for 7 d. Analysis of variance-simultaneous component analysis is used to identify metabolites that distinguish exposed from control animals. Overall, alterations in lipid metabolism suggest the occurrence of oxidative stress in both the brain and the liver-a common adverse effect of xenobiotics. However, alterations in the amino acid arginine are also observed. These are likely related to the nitric oxide system that is known to be associated with the mechanism of action of antidepressants. In addition, changes in asparagine and methionine levels in the brain and pantothenate, uric acid, and formylisoglutamine/N-formimino-L-glutamate levels in the liver could indicate variation of amino acid metabolism in both tissues; and the perturbation of glutamate in the liver implies that the energy metabolism is also affected. These results reveal that environmentally relevant concentrations of amitriptyline perturb a fraction of the metabolome that is not typically associated with antidepressant exposure in fish. Environ Toxicol Chem 2019;00:1-13. © 2019 SETAC.

Interactome Studies of Psychiatric Disorders

High comorbidity and complexity have precluded reliable diagnostic assessment and treatment of psychiatric disorders. Impaired molecular interactions may be relevant for underlying mechanisms of psychiatric disorders but by and large remain unknown. With the help of a number of publicly available databases and various technological tools, recent research has filled the paucity of information by generating a novel dataset of psychiatric interactomes. Different technological platforms including yeast two-hybrid screen, co-immunoprecipitation-coupled with mass spectrometry-based proteomics, and transcriptomics have been widely used in combination with cellular and molecular techniques to interrogate the psychiatric interactome. Novel molecular interactions have been identified in association with different psychiatric disorders including autism spectrum disorders, schizophrenia, bipolar disorder, and major depressive disorder. However, more extensive and sophisticated interactome research needs to be conducted to overcome the current limitations such as incomplete interactome databases and a lack of functional information among components. Ultimately, integrated psychiatric interactome databases will contribute to the implementation of biomarkers and therapeutic intervention.

Blood plasma/IgG N-glycome biosignatures associated with major depressive disorder symptom severity and the antidepressant response

While N-linked glycosylation has been extensively studied in the context of inflammatory and metabolic disorders, its relationship with major depressive disorder (MDD) and antidepressant treatment response has not been investigated. In our exploratory study, we analysed N-glycan profiles in blood plasma samples collected from MDD patients (n = 18) and found gender-dependent correlations with severity of depressive symptoms prior to initiating antidepressant treatment. In addition, several N-glycosylation traits showed gender-dependent associations with clinical antidepressant response. Follow up proteomics analysis in peripheral blood mononuclear cells (PBMCs) collected from MDD patients (n = 20) identified baseline and post-antidepressant treatment pathway differences between responder and non-responder patients. Reactome data analysis further delineated potential biological reaction differences between responder and non-responder patients. Our preliminary results suggest that specific glycosylation traits are associated with depressive symptom severity and antidepressant response and may be of use as biomarkers.

Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response

Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.