Purine and pyrimidine metabolism: Convergent evidence on chronic antidepressant treatment response in mice and humans

Treatment response of venlafaxine induced alterations of gut microbiota and metabolites in a mouse model of depression

Antidepressants remain the first-line treatment for depression. However, the factors influencing medication response are still unclear. Accumulating evidence implicates an association between alterations in gut microbiota and antidepressant response. Therefore, the aim of this study is to investigate the role of the gut microbiota-brain axis in the treatment response of venlafaxine. After chronic social defeat stress and venlafaxine treatment, mice were divided into responders and non-responders groups. We compared the composition of gut microbiota using 16 S ribosomal RNA sequencing. Meanwhile, we quantified metabolomic alterations in serum and hippocampus, as well as hippocampal neurotransmitter levels using liquid chromatography-mass spectrometry. We found that the abundances of 29 amplicon sequence variants (ASVs) were significantly altered between the responders and non-responders groups. These ASVs belonged to 8 different families, particularly Muribaculaceae. Additionally, we identified 38 and 39 differential metabolites in serum and hippocampus between the responders and non-responders groups, respectively. Lipid, amino acid, and purine metabolisms were enriched in both serum and hippocampus. In hippocampus, the concentrations of tryptophan, phenylalanine, gamma-aminobutyric acid, glutamic acid, and glutamine were increased, while the level of succinic acid was decreased in the responders group, compared with the non-responders group. Our findings suggest that the gut microbiota may play a role in the antidepressant effect of venlafaxine by modulating metabolic processes in the central and peripheral tissues. This provides a novel microbial and metabolic framework for understanding the impact of the gut microbiota-brain axis on antidepressant response.

Modulation of anxiety-like behavior in galactooligosaccharide-fed mice: A potential role for bacterial tryptophan metabolites and reduced microglial reactivity

Prebiotic galactooligosaccharides (GOS) reduce anxiety-like behaviors in mice and humans. However, the biological pathways behind these behavioral changes are not well understood. To begin to study these pathways, we utilized C57BL/6 mice that were fed a standard diet with or without GOS supplementation for 3 weeks prior to testing on the open field. After behavioral testing, colonic contents and serum were collected for bacteriome (16S rRNA gene sequencing, colonic contents only) and metabolome (UPLC-MS, colonic contents and serum data) analyses. As expected, GOS significantly reduced anxiety-like behavior (i.e., increased time in the center) and decreased cytokine gene expression (Tnfa and Ccl2) in the prefrontal cortex. Notably, time in the center of the open field was significantly correlated with serum methyl-indole-3-acetic acid (methyl-IAA). This metabolite is a methylated form of indole-3-acetic acid (IAA) that is derived from bacterial metabolism of tryptophan. Sequencing analyses showed that GOS significantly increased Lachnospiraceae UCG006 and Akkermansia; these taxa are known to metabolize both GOS and tryptophan. To determine the extent to which methyl-IAA can affect anxiety-like behavior, mice were intraperitoneally injected with methyl-IAA. Mice given methyl-IAA had a reduction in anxiety-like behavior in the open field, along with lower Tnfa in the prefrontal cortex. Methyl-IAA was also found to reduce TNF-α (as well as CCL2) production by LPS-stimulated BV2 microglia. Together, these data support a novel pathway through which GOS reduces anxiety-like behaviors in mice and suggests that the bacterial metabolite methyl-IAA reduces microglial cytokine and chemokine production, which in turn reduces anxiety-like behavior.

Serum Metabolites as Potential Markers and Predictors of Depression-like Behavior and Effective Fluoxetine Treatment in Chronically Socially Isolated Rats

Metabolic perturbation has been associated with depression. An untargeted metabolomics approach using liquid chromatography-high resolution mass spectrometry was employed to detect and measure the rat serum metabolic changes following chronic social isolation (CSIS), an animal model of depression, and effective antidepressant fluoxetine (Flx) treatment. Univariate and multivariate statistics were used for metabolic data analysis and differentially expressed metabolites (DEMs) determination. Potential markers and predictive metabolites of CSIS-induced depressive-like behavior and Flx efficacy in CSIS were evaluated by the receiver operating characteristic (ROC) curve, and machine learning (ML) algorithms, such as support vector machine with linear kernel (SVM-LK) and random forest (RF). Upregulated choline following CSIS may represent a potential marker of depressive-like behavior. Succinate, stachydrine, guanidinoacetate, kynurenic acid, and 7-methylguanine were revealed as potential markers of effective Flx treatment in CSIS rats. RF yielded better accuracy than SVM-LK (98.50% vs. 85.70%, respectively) in predicting Flx efficacy in CSIS vs. CSIS, however, it performed almost identically in classifying CSIS vs. control (75.83% and 75%, respectively). Obtained DEMs combined with ROC curve and ML algorithms provide a research strategy for assessing potential markers or predictive metabolites for the designation or classification of stress-induced depressive phenotype and mode of drug action.

Exploring the human gut microbiota targets in relation to the use of contemporary antidepressants

BACKGROUND

Antidepressants, specifically selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs), are commonly prescribed for depression treatment. Animal studies have shown that antidepressants can influence gut microbiota composition and specific bacterial taxa. We aimed to investigate the association between antidepressant use and human gut microbiota composition and functional pathway.

METHODS

We collected information on antidepressant use, demographic, food patterns, and clinical characteristics through questionnaires and medical records. The gut microbiota profiles of 271 depressive patients were carried out through 16S rRNA gene sequencing. Patients were categorized based on different types of antidepressant use groups for gut microbiota comparisons. MaAsLin2 was performed to evaluate microbiota composition across groups. PICRUSt2 was used to predict microbiota functional pathways.

RESULTS

Patients taking SSRIs or SNRIs had a lower microbiota diversity. We found seven taxa abundances (Turicibacter, Barnesiella, Lachnospiraceae_ND3007_group, Romboutia, Akkermansia, Dialister, Romboutia and Fusicatenibacter) differed in patients with various types of antidepressants compared with those without antidepressant treatments (p < 0.05). Turicibacter inversely correlated with depression severity in SSRIs or SNRI users (r = -0.43, p < 0.05). Top identified pathways were related to compound fermentation and biosynthesis in microbiota function.

CONCLUSION

Antidepressant usage, especially SSRIs and SNRIs, associates with changes in gut microbiota composition and specific taxa. Given our study's preliminary cross-sectional nature, further research is warranted to comprehend the relationship between antidepressant use, treatment response, and gut microbiota, aiming to enhance therapeutic interventions in the future.

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.

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.

Novel Multi-Strain E3 Probiotic Formulation Improved Mental Health Symptoms and Sleep Quality in Hong Kong Chinese

Mental health issues have emerged as a significant concern in public health, given their association with physical and psychological comorbidities and the resultant socioeconomic burdens. Recent studies have highlighted the interplay between gut microbes and brain functions through the gut-brain axis. To investigate this further, we conducted a targeted 16S rRNA sequencing and comprehensive bioinformatic analysis among Southern Chinese individuals to explore the role of the gut microbiome in depression, anxiety, and sleep disturbance. We analyzed the differences in the gut microbiome profile of 68 participants with sleep disturbance and mood symptoms before and after an 8-week course of a novel oral E3 multi-strain probiotics formula. The results revealed a significant improvement in subjective sleep quality (PSQI: mean 8.79 at baseline vs. 7.10 at week 8, p < 0.001), depressive symptoms (PHQ9: mean 6.17 at baseline vs. 4.76 at week 8, p < 0.001), and anxious symptoms (GAD7: mean 4.90 at baseline vs. 3.76 at week 8, p < 0.001). Additionally, there were notable differences in beta diversity (weighted UniFrac; p = 0.045) and increased Firmicutes/Bacteroidetes (F/B) ratio (p = 4 × 10-4) were observed in the gut microbiome analysis. Furthermore, the relative abundance of Bifidobacterium bifidum (p < 0.001), Lactobacillus acidophilus (p < 0.001), Lactobacillus helveticus (p < 0.001) and Lactobacillus plantarum (p < 0.001) were significantly increased after the 8-week probiotic supplementation. Our study suggests that the gut microbial landscape varies between responders and non-responders at multiple levels, including genera, species, functional, and network interaction. Notably, the use of probiotics in populations with depressive or anxious symptoms and poor sleeping quality remodeled the gut microbiome and demonstrated improved mood and sleep quality.

Understanding ayahuasca effects in major depressive disorder treatment through in vitro metabolomics and bioinformatics

Emerging insights from metabolomic-based studies of major depression disorder (MDD) are mainly related to biochemical processes such as energy or oxidative stress, in addition to neurotransmission linked to specific metabolite intermediates. Hub metabolites represent nodes in the biochemical network playing a critical role in integrating the information flow in cells between metabolism and signaling pathways. Limited technical-scientific studies have been conducted to understand the effects of ayahuasca (Aya) administration in the metabolism considering MDD molecular context. Therefore, this work aims to investigate an in vitro primary astrocyte model by untargeted metabolomics of two cellular subfractions: secretome and intracellular content after pre-defined Aya treatments, based on DMT concentration. Mass spectrometry (MS)-based metabolomics data revealed significant hub metabolites, which were used to predict biochemical pathway alterations. Branched-chain amino acid (BCAA) metabolism, and vitamin B6 and B3 metabolism were associated to Aya treatment, as "housekeeping" pathways. Dopamine synthesis was overrepresented in the network results when considering the lowest tested DMT concentration (1 µmol L^-1). Building reaction networks containing significant and differential metabolites, such as nicotinamide, L-DOPA, and L-leucine, is a useful approach to guide on dose decision and pathway selection in further analytical and molecular studies.

Circuit-wide proteomics profiling reveals brain region-specific protein signatures in the male WKY rats with endogenous depression

BACKGROUND

Although the Wistar Kyoto (WKY) rat has been consistently recognized as an animal model with endogenous depression, the exact molecular mechanisms underlying its genetic susceptibility to depression remain undetermined.

METHODS

Compared with the Wistar rats, the depression-like behaviors of the male WKY ones were evaluated by both the sucrose preference test and forced swimming test. Golgi staining analysis was conducted to access the dendritic morphology. TMT-labelled quantitative proteomics analyses were respectively performed in the medial prefrontal cortex (mPFC), nucleus accumbens (NAc), and hippocampus (Hip), followed by KEGG enrichment-based clustering analysis, Venn diagram analysis, and Pearson correlation analysis.

RESULTS

The WKY strain showed significant differences in both the depression-like behaviors and synaptic plasticity. Moreover, the WKY model displayed markedly distinct differentially-expressed protein (DEP) profiles, with minor differences between the WKY subgroups. A cerebral regional commonality and specificity were evident in the signaling pathways enriched in the WKY model, and a total of 15 brain region-specific DEPs were identified to closely correlate with the depression-like phenotypes (in the mPFC: Lrrc8d, Dcun1d2, and Mtnd5; in the NAc: Ccdc154, Sec14l2, Kif2a, LOC680322, Me1, Mknk1, and Ret7; in the Hip: Sec14l2, Serpinf2, LOC103694855, Fam13c, and Loxl1). Data were available via ProteomeXchange with identifier PXD029079.

LIMITATIONS

Female WKY rats are not included, and the roles of these candidate DEPs in depression remain further elucidation.

CONCLUSION

The present study further evidences the brain region-specific protein signatures in the male WKY model with endogenous depression, providing novel insights into the pathogenesis of depression in males.

Plasma metabolic disturbances during pregnancy and postpartum in women with depression

Examining plasma metabolic profiling during pregnancy and postpartum could help clinicians understand the risk factors for postpartum depression (PPD) development. This analysis targeted paired plasma metabolites in mid-late gestational and 1 month postpartum periods in women with (n = 209) or without (n = 222) PPD. Gas chromatogram-mass spectrometry was used to analyze plasma metabolites at these two time points. Among the 170 objected plasma metabolites, principal component analysis distinguished pregnancy and postpartum metabolites but failed to discriminate women with and without PPD. Compared to women without PPD, those with PPD exhibited 37 metabolites with disparate changes during pregnancy and the 1-month postpartum period and an enriched citrate cycle. Machine learning and multivariate statistical analysis identified two or three compounds that could be potential biomarkers for PPD prediction during pregnancy. Our findings suggest metabolic disturbances in women with depression and may help to elucidate metabolic processes associated with PPD development.

Synergistic neuroprotective effect of saikosaponin A and albiflorin on corticosterone-induced apoptosis in PC12 cells via regulation of metabolic disorders and neuroinflammation

BACKGROUND

Saikosaponin A (SSA) and albiflorin (AF) are major bioactive compounds of Radix Bupleuri and Radix Paeoniae alba respectively, which possess antidepressant effects in pharmacological experiments. However, whether SSA and AF have synergistic neuroprotective effects and the synergistic mechanisms are still unknown.

METHODS AND RESULTS

The corticosterone-induced PC12 cells apoptosis model was employed to assess the neuroprotective effects of SSA and AF, and the synergistic effect was analyzed using three mathematical models. Meanwhile, cell metabolomics was used to detect the effects on metabolite regulation of SSA and AF. Furthermore, the key metabolites, metabolic enzymes, and cellular markers were verified by ELISA and Western blotting. The results showed that the combination of SSA and AF has a synergistic neuroprotective effect. Besides, the combination could regulate more metabolites than a single agent and possessed a stronger adjustment effect on metabolites. The TCA cycle was regulated by SSA and AF via improving mitochondrial function. The purine metabolism was regulated by SSA via inhibition xanthine oxidase activity and the glutamate metabolism was regulated by AF via inhibition glutaminase activity. Moreover, the oxidative stress induced by the purine metabolism was attenuated by SSA via a reduction in the ROS level. Additionally, the inflammation induced by the oxidative stress was attenuated by the SSA and AF via inhibition of the NLRP3 protein expression.

CONCLUSIONS

This study for the first time demonstrated the synergistic neuroprotective effects of SSA and AF, and the synergistic mechanisms were involved in metabolic disorders regulation and neuroinflammation inhibition.

Impact of CYP2C19 metaboliser status on SSRI response: a retrospective study of 9500 participants of the Australian Genetics of Depression Study

BACKGROUND

Variation within the CYP2C19 gene has been linked to differential metabolism of selective serotonin reuptake inhibitors (SSRIs). Pharmacogenetic recommendations based on the effect of CYP2C19 variants have been made available and are used increasingly by clinical practitioners. Nonetheless, the underlying assumption linking differential metabolism to efficacy or adverse side effects remains understudied. Here, we aim to fill this gap by studying CYP2C19 polymorphisms and inferred metabolism and patient-reported antidepressant response in a sample of 9531 Australian adults who have taken SSRIs.

METHODS

Metaboliser status was inferred for participants based on CYP2C19 alleles. Primary analysis consisted of assessing differences in treatment efficacy and tolerability between normal (reference) and: ultrarapid, rapid, intermediate and poor metabolisers.

RESULTS

Across medications, poor metabolisers reported a higher efficacy, whereas rapid metabolisers reported higher tolerability. When stratified by drug, associations between metaboliser status and efficacy did not survive multiple testing correction. Intermediate metabolisers were at greater odds of reporting any side effect for sertraline and higher number of side effects across medications and for sertraline.

CONCLUSIONS

The effects between metaboliser status and treatment efficacy, tolerability and side effects were in the expected direction. Our power analysis suggests we would detect moderate to large effects, at least nominally. Reduced power may also be explained by heterogeneity in antidepressant dosages or concomitant medications, which we did not measure. The fact that we identify slower metabolisers to be at higher risk of side effects even without adjusting for clinical titration, and the nominally significant associations consistent with the expected metabolic effects provide new evidence for the link between CYP2C19 metabolism and SSRI response. Nonetheless, longitudinal and interventional designs such as randomized clinical trials that stratify by metaboliser status are necessary to establish the effects of CYP2C19 metabolism on SSRI treatment efficacy or adverse effects.

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.

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).

Design, Synthesis, Molecular Modeling and Antitumor Evaluation of Novel Indolyl-Pyrimidine Derivatives with EGFR Inhibitory Activity

Scaffolds hybridization is a well-known drug design strategy for antitumor agents. Herein, series of novel indolyl-pyrimidine hybrids were synthesized and evaluated in vitro and in vivo for their antitumor activity. The in vitro antiproliferative activity of all compounds was obtained against MCF-7, HepG2, and HCT-116 cancer cell lines, as well as against WI38 normal cells using the resazurin assay. Compounds 1-4 showed broad spectrum cytotoxic activity against all these cancer cell lines compared to normal cells. Compound 4g showed potent antiproliferative activity against these cell lines (IC₅₀ = 5.1, 5.02, and 6.6 μM, respectively) comparable to the standard treatment (5-FU and erlotinib). In addition, the most promising group of compounds was further evaluated for their in vivo antitumor efficacy against EAC tumor bearing mice. Notably, compound 4g showed the most potent in vivo antitumor activity. The most active compounds were evaluated for their EGFR inhibitory (range 53-79%) activity. Compound 4g was found to be the most active compound against EGFR (IC₅₀ = 0.25 µM) showing equipotency as the reference treatment (erlotinib). Molecular modeling study was performed on compound 4g revealed a proper binding of this compound inside the EGFR active site comparable to erlotinib. The data suggest that compound 4g could be used as a potential anticancer agent.

Behavioral and Metabolome Differences between C57BL/6 and DBA/2 Mouse Strains: Implications for Their Use as Models for Depression- and Anxiety-Like Phenotypes

Mouse models are widely used to study behavioral phenotypes related to neuropsychiatric disorders. However, different mouse strains vary in their inherent behavioral and molecular characteristics, which needs to be taken into account depending on the nature of the study. Here, we performed a detailed behavioral and molecular comparison of C57BL/6 (B6) and DBA/2 (DBA) mice, two inbred strains commonly used in neuropsychiatric research. We analyzed anxiety-related and depression-like traits, quantified hippocampal and plasma metabolite profiles, and assessed total antioxidant capacity (ΤAC). B6 mice exhibit increased depression-like and decreased anxiety-related behavior compared to DBA mice. Metabolite level differences indicate alterations in amino acid, nucleotide and mitochondrial metabolism that are accompanied by a decreased TAC in B6 compared to DBA mice. Our data reveal multiple behavioral and molecular differences between B6 and DBA mouse strains, which should be considered in the experimental design for phenotype, pharmacological and mechanistic studies relevant for neuropsychiatric disorders.

Metabolomic analysis of animal models of depression

BACKGROUND

Our understanding of the molecular mechanisms of depression remains largely unclear. Previous studies have shown that the prefrontal cortex (PFC) is among most important brain regions that exhibits metabolic changes in depression. A comprehensive analysis based on candidate metabolites in the PFC of animal models of depression will provide valuable information for understanding the pathogenic mechanism underlying depression.

METHODS

Candidate metabolites that are potentially involved in the metabolic changes of the PFC in animal models of depression were retrieved from the Metabolite Network of Depression Database. The significantly altered metabolic pathways were revealed by canonical pathway analysis, and the relationships among altered pathways were explored by pathway crosstalk analysis. Additionally, drug-associated pathways were investigated using drug-associated metabolite set enrichment analysis. The interrelationships among metabolites, proteins, and other molecules were analyzed by molecular network analysis.

RESULTS

Among 88 candidate metabolites, 87 altered canonical pathways were identified, and the top five ranked pathways were tRNA charging, the endocannabinoid neuronal synapse pathway, (S)-reticuline biosynthesis II, catecholamine biosynthesis, and GABA receptor signaling. Pathway crosstalk analysis revealed that these altered pathways were grouped into three interlinked modules involved in amino acid metabolism, nervous system signaling/neurotransmitters, and nucleotide metabolism. In the drug-associated metabolite set enrichment analysis, the main enriched drug pathways were opioid-related and antibiotic-related action pathways. Furthermore, the most significantly altered molecular network was involved in amino acid metabolism, molecular transport, and small molecule biochemistry.

CONCLUSIONS

This study provides important clues for the metabolic characteristics of the PFC in depression.

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.

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.

Systematic impacts of chronic unpredictable mild stress on metabolomics in rats

Depression is the most common disabling psychiatric disease, with a high prevalence and mortality. Chronic unpredictable mild stress (CUMS) is a well-accepted method used to mimic clinical depression. Recent evidence has consistently suggested that the cumulative effects of CUMS could lead to allostatic overload in the body, thereby inducing systemic disorders; however, there are no previous systematic metabonomics studies on the main stress-targeted tissues associated with depression. A non-targeted gas chromatography–mass spectrometry (GC–MS) approach was used to identify metabolic biomarkers in the main stress-targeted tissues (serum, heart, liver, brain, and kidney) in a CUMS model of depression. Male Sprague–Dawley rats were randomly allocated to the CUMS group (n = 8) or a control group (n = 8). Multivariate analysis was performed to identify the metabolites that were differentially expressed between the two groups. There were 10, 10, 9, 4, and 7 differentially expressed metabolites in the serum, heart, liver, brain and kidney tissues, respectively, between the control and CUMS groups. These were linked to nine different pathways related to the metabolism of amino acids, lipids, and energy. In summary, we provided a comprehensive understanding of metabolic alterations in the main stress-targeted tissues, helping to understand the potential mechanisms underlying depression.

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

BACKGROUND

Major depressive disorder (MDD) is a complex psychiatric illness involving multiple brain regions. Increasing evidence indicates that the striatum is involved in depression, but the molecular mechanisms remain unclear.

METHODS

In this study, we performed a gas chromatography-mass spectrometer (GC/MS)-based metabolomic analysis in the striatum of depressed rats induced by chronic unpredictable mild stress (CUMS). We then compared striatal data with our previous data from the hippocampus and cerebellum to systematically investigate the potential pathogenesis of depression.

RESULTS

We identified 22 differential metabolites in the striatum between the CUMS and control groups; these altered metabolites were mainly involved in amino acid, carbohydrate, and nucleotide metabolism. Pathway analysis revealed that the shared metabolic pathways of the striatum, hippocampus, and cerebellum were mainly involved in the glutamine-glutamate metabolic system. Four genes in the striatum (GS, GLS2, GLT1, and SSADH), six genes in the hippocampus (GS, SNAT1, GAD1, SSADH, VGAT, and ABAT), and five genes in the cerebellum (GS, ABAT, SNAT1, VGAT, and GDH) were found to be significantly altered using RT-qPCR. Correlation analysis indicated that these differential genes were strongly correlated.

CONCLUSION

These results suggest that chronic stress might induce depressive behaviors by disturbing the glutamine-glutamate-GABA cycle in the striatum, hippocampus, and cerebellum, and that the glutamine-glutamate-GABA cycle among these three brain regions might generate cooperative action in response to chronic stress.

Exposure-induced changes of plasma metabolome and gene expression in patients with panic disorder

BACKGROUND

Anxiety disorders including panic disorder (PD) are the most prevalent psychiatric diseases leading to high disability and burden in the general population. Acute panic attacks are distinctive for PD but also frequent in other anxiety disorders. The neurobiology or specific molecular changes leading to and present during panic attacks are insufficiently known so far.

METHODS

In the present pilot study, we investigated dynamic metabolomic and gene expression changes in peripheral blood of patients with PD (n = 25) during two exposure-induced acute panic attacks.

RESULTS

The results show that the metabolite glyoxylate was dynamically regulated in peripheral blood. Additionally, glyoxylate levels were associated with basal anxiety levels and showed gender-related differences at baseline. As glyoxylate is part of the degradation circuit of cholecystokinin, this suggests that this neuropeptide might be directly involved in exposure-induced panic attacks. Only gene expression changes of very small magnitude were observed in this experimental setting.

CONCLUSIONS

From this first metabolome and gene expression study in exposure-induced acute panic attacks in PD we conclude that metabolites can potentially serve as dynamic markers for different anxiety states. However, these findings have to be replicated in cohorts with greater sample sizes.

Metabolomic signature of exposure and response to citalopram/escitalopram in depressed outpatients

Metabolomics provides valuable tools for the study of drug effects, unraveling the mechanism of action and variation in response due to treatment. In this study we used electrochemistry-based targeted metabolomics to gain insights into the mechanisms of action of escitalopram/citalopram focusing on a set of 31 metabolites from neurotransmitter-related pathways. Overall, 290 unipolar patients with major depressive disorder were profiled at baseline, after 4 and 8 weeks of drug treatment. The 17-item Hamilton Depression Rating Scale (HRSD17) scores gauged depressive symptom severity. More significant metabolic changes were found after 8 weeks than 4 weeks post baseline. Within the tryptophan pathway, we noted significant reductions in serotonin (5HT) and increases in indoles that are known to be influenced by human gut microbial cometabolism. 5HT, 5-hydroxyindoleacetate (5HIAA), and the ratio of 5HIAA/5HT showed significant correlations to temporal changes in HRSD17 scores. In the tyrosine pathway, changes were observed in the end products of the catecholamines, 3-methoxy-4-hydroxyphenylethyleneglycol and vinylmandelic acid. Furthermore, two phenolic acids, 4-hydroxyphenylacetic acid and 4-hydroxybenzoic acid, produced through noncanconical pathways, were increased with drug exposure. In the purine pathway, significant reductions in hypoxanthine and xanthine levels were observed. Examination of metabolite interactions through differential partial correlation networks revealed changes in guanosine-homogentisic acid and methionine-tyrosine interactions associated with HRSD17. Genetic association studies using the ratios of these interacting pairs of metabolites highlighted two genetic loci harboring genes previously linked to depression, neurotransmission, or neurodegeneration. Overall, exposure to escitalopram/citalopram results in shifts in metabolism through noncanonical pathways, which suggest possible roles for the gut microbiome, oxidative stress, and inflammation-related mechanisms.

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.

Pyrrolopyrazoles: Synthesis, Evaluation and Pharmacological Screening as Antidepressant Agents

BACKGROUND

Pyrroles and fused pyrroles are of great interest as biologically active compounds, among these activities; antidepressant activity is of special concern.

OBJECTIVE

Synthesis of a series of pyrrolopyrazoles and their pyrimidine derivatives and their characterization using spectral data to be monitored for antidepressant activity using behavioral techniques.

METHODS

A control group was administered the vehicle i.p., positive control group received fluoxetine as standard and all other groups were administered the tested compounds. The groups were subjected to tail suspension test (TST) to determine the antidepressant activity compared with fluoxetine as a standard drug. The compounds exhibiting antidepressant activity were then used to analyze changes in serotonin (5HT) level in the brain of albino mice.

RESULTS

TST results showed that both pyrazoles and pyrazolopyrimidines derivatives exhibit promising anti-depressant activity.

CONCLUSION

Compounds [pyrazoles & pyrazlopyrimidines] showed promising antidepressant activity possibly mediated by the increased levels of 5HT.

Prophylactic ketamine alters nucleotide and neurotransmitter metabolism in brain and plasma following stress

Recently, we have shown that ketamine given prior to stress exposure protects against the development of depressive-like behavior in mice. These data suggest that it may be possible to prevent the induction of affective disorders before they develop by administering prophylactic pharmaceuticals, a relatively nascent and unexplored strategy for psychiatry. Here, we performed metabolomics analysis of brain and plasma following prophylactic ketamine treatment in order to identify markers of stress resilience enhancement. We administered prophylactic ketamine in mice to buffer against fear expression. Following behavioral analyses, untargeted metabolomic profiling was performed on both hemispheres of the prefrontal cortex (PFC) and the hippocampus (HPC), and plasma. We found that prophylactic ketamine attenuated learned fear. Eight metabolites were changed in the PFC and HPC upon ketamine treatment. Purine and pyrimidine metabolism were most significantly changed in the HPC, PFC, and, interestingly, plasma of mice two weeks after prophylactic administration. Moreover, most precursors to inhibitory neurotransmitters were increased whereas precursors to excitatory neurotransmitters were decreased. Strikingly, these long-term metabolomic changes were not observed when no stressor was administered. Our results suggest that prophylactic treatment differentially affects purine and pyrimidine metabolism and neurotransmission in brain and plasma following stress, which may underlie the long-lasting resilience to stress induced by a single injection of ketamine. These data may provide novel targets for prophylactic development, and indicate an interaction effect of prophylactic ketamine and stress. To our knowledge, this is the first study that identifies metabolomic alterations and biomarker candidates for prophylactic ketamine efficacy in mice.

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.

Fluoxetine Administration in Juvenile Monkeys: Implications for Pharmacotherapy in Children

Fluoxetine therapy has been approved for children with major depressive disorder and obsessive compulsive disorder for over 14 years and has expanded to other childhood behavior disorders. As use increases, more detail on fluoxetine effects during juvenile brain development can help maintain safe and effective use of this therapy. Here, a narrative review is provided of previously published findings from a large nonhuman primate project. Fluoxetine was administered to juvenile male rhesus monkeys for an extended period (2 years) prior to puberty. Compared to controls, treated monkeys showed sleep disruption, facilitated social interaction, greater impulsivity, and impaired sustained attention during treatment. No effects on growth were seen. Metabolomics assays characterized a distinctive response to fluoxetine and demonstrated individual differences that were related to the impulsivity measure. Fluoxetine interactions with monoamine oxidase A polymorphisms that influenced behavior and metabolomics markers were an important, previously unrecognized finding of our studies. After treatment was discontinued, some behavioral effects persisted, but short-term memory and cognitive flexibility testing did not show drug effects. This detailed experimental work can contribute to clinical research and continued safe and effective fluoxetine pharmacotherapy in children.

Differential Peripheral Proteomic Biosignature of Fluoxetine Response in a Mouse Model of Anxiety/Depression

The incorporation of peripheral biomarkers in the treatment of major depressive disorders (MDD) could improve the efficiency of treatments and increase remission rate. Peripheral blood mononuclear cells (PBMCs) represent an attractive biological substrate allowing the identification of a drug response signature. Using a proteomic approach with high-resolution mass spectrometry, the present study aimed to identify a biosignature of antidepressant response (fluoxetine, a Selective Serotonin Reuptake Inhibitor) in PBMCs in a mouse model of anxiety/depression. Following determination of an emotionality score, using complementary behavioral analysis of anxiety/depression across three different tests (Elevated Plus Maze, Novelty Suppressed Feeding, Splash Test), we showed that a 4-week corticosterone treatment (35 μg/ml, CORT model) in C57BL/6NTac male mice induced an anxiety/depressive-like behavior. Then, chronic fluoxetine treatment (18 mg/kg/day for 28 days in the drinking water) reduced corticosterone-induced increase in emotional behavior. However, among 46 fluoxetine-treated mice, only 30 of them presented a 50% decrease in emotionality score, defining fluoxetine responders (CORT/Flx-R). To determine a peripheral biological signature of fluoxetine response, proteomic analysis was performed from PBMCs isolated from the “most” affected corticosterone/vehicle (CORT/V), corticosterone/fluoxetine responders and non-responders (CORT/Flx-NR) animals. In comparison to CORT/V, a total of 263 proteins were differently expressed after fluoxetine exposure. Expression profile of these proteins showed a strong similarity between CORT/Flx-R and CORT/Flx-NR (R = 0.827, p < 1e^-7). Direct comparison of CORT/Flx-R and CORT/Flx-NR groups revealed 100 differently expressed proteins, representing a combination of markers associated either with the maintenance of animals in a refractory state, or associated with behavioral improvement. Finally, 19 proteins showed a differential direction of expression between CORT/Flx-R and CORT/Flx-NR that drove them away from the CORT-treated profile. Among them, eight upregulated proteins (RPN2, HSPA9, NPTN, AP2B1, UQCRC2, RACK-1, TOLLIP) and one downregulated protein, TLN2, were previously associated with MDD or antidepressant drug response in the literature. Future preclinical studies will be required to validate whether proteomic changes observed in PBMCs from CORT/Flx-R mice mirror biological changes in brain tissues.