Elevated striatal γ-aminobutyric acid in youth with major depressive disorder

Examining the Role of GLU/GABA to GLN Metabolic Cycle in the Pathogenesis of Post-Stroke Depressive Disorder and Insomnia

Objective

This study aims to elucidate the potential links between the GLU/GABA to GLN metabolic cycle disruptions and the onset of depressive and insomnia disorders following a stroke. We particularly focus on understanding if these disorders share a common underlying pathogenic mechanism.

Methods

We examined 63 patients with post-stroke insomnia, 62 patients with post-stroke depression, and 18 healthy individuals. The study involved assessing insomnia using the Acute Insomnia Scale (AIS) and depression using the Hamilton Depression Rating Scale. We measured serum concentrations of GLN, GLU, and GABA and analyzed their correlations with AIS and HAMD scores.

Results

Our results indicate no significant difference in the serum levels of GLN, GLU, and GABA between the post-stroke insomnia and depression groups. However, these levels were notably lower in both patient groups compared to the healthy control group. A negative correlation between AIS scores and GABA levels was observed in the post-stroke insomnia group, suggesting a potential link between GABAergic disturbances and insomnia. Conversely, no significant correlation was found between Hamilton Depression Rating Scale scores and the levels of GABA, GLU, or GLN in the post-stroke depression group.

Conclusion

The study highlights that abnormalities in the GLU/GABA to GLN metabolic cycle, particularly the levels of GLN, GABA, and GAD, might be intricately linked to the pathogenesis of post-stroke insomnia and depression. Our findings suggest that GABAergic imbalances could be indicative of post-stroke insomnia, serving as potential biological markers for differential diagnosis in clinical settings. Further research is warranted to explore these relationships in greater depth, potentially leading to new diagnostic and therapeutic approaches for post-stroke neuropsychiatric disorders.

Meta-analysis and open-source database for in vivo brain Magnetic Resonance spectroscopy in health and disease

Proton (1H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo. Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Meta-analysis and Open-source Database for In Vivo Brain Magnetic Resonance Spectroscopy in Health and Disease

Proton ( 1 H) Magnetic Resonance Spectroscopy (MRS) is a non-invasive tool capable of quantifying brain metabolite concentrations in vivo . Prioritization of standardization and accessibility in the field has led to the development of universal pulse sequences, methodological consensus recommendations, and the development of open-source analysis software packages. One on-going challenge is methodological validation with ground-truth data. As ground-truths are rarely available for in vivo measurements, data simulations have become an important tool. The diverse literature of metabolite measurements has made it challenging to define ranges to be used within simulations. Especially for the development of deep learning and machine learning algorithms, simulations must be able to produce accurate spectra capturing all the nuances of in vivo data. Therefore, we sought to determine the physiological ranges and relaxation rates of brain metabolites which can be used both in data simulations and as reference estimates. Using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we've identified relevant MRS research articles and created an open-source database containing methods, results, and other article information as a resource. Using this database, expectation values and ranges for metabolite concentrations and T 2 relaxation times are established based upon a meta-analyses of healthy and diseased brains.

Carnitine and Depression

Depression has become one of the most common mental diseases in the world, but the understanding of its pathogenesis, diagnosis and treatments remains insufficient. Carnitine is a natural substance that exists in organisms, which can be synthesized in vivo or supplemented by intake. Relationships of carnitine with depression, bipolar disorder and other mental diseases have been reported in different studies. Several studies show that the level of acylcarnitines (ACs) changes significantly in patients with depression compared with healthy controls while the supplementation of acetyl-L-carnitine is beneficial to the treatment of depression. In this review, we aimed to clarify the effects of ACs in depressive patients and to explore whether ACs might be the biomarkers for the diagnosis of depression and provide new ideas to treat depression.

GABA System in Depression: Impact on Pathophysiology and Psychopharmacology

BACKGROUND

The pathophysiology of major depressive disorder (MDD), one of the major causes of worldwide disability, is still largely unclear, despite the increasing data reporting evidence of multiple alterations of different systems. Recently, there was a renewed interest in the signalling of gamma aminobutyric acid (GABA) - the main inhibitory neurotransmitter.

OBJECTIVE

The aim of this study was to review and comment on the available literature about the involvement of GABA in MDD, as well as on novel GABAergic compounds possibly useful as antidepressants.

METHODS

We carried out a narrative review through Pubmed, Google Scholar and Scopus, by using specific keywords.

RESULTS

The results, derived from various research tools, strongly support the presence of a deficiency of the GABA system in MDD, which appears to be restored by common antidepressant treatments. More recent publications would indicate the complex interactions between GABA and all the other processes involved in MDD, such as monoamine neurotransmission, hypothalamus-pituitary adrenal axis functioning, neurotrophism, and immune response. Taken together, all these findings seem to further support the complexity of the pathophysiology of MDD, possibly reflecting the heterogeneity of the clinical pictures.

CONCLUSION

Although further data are necessary to support the specificity of GABA deficiency in MDD, the available findings would suggest that novel GABAergic compounds might constitute innovative therapeutic strategies in MDD.

Multimodal Investigations of Reward Circuitry and Anhedonia in Adolescent Depression

Depression is a highly prevalent condition with devastating personal and public health consequences that often first manifests during adolescence. Though extensively studied, the pathogenesis of depression remains poorly understood, and efforts to stratify risks and identify optimal interventions have proceeded slowly. A major impediment has been the reliance on an all-or-nothing categorical diagnostic scheme based solely on whether a patient endorses an arbitrary number of common symptoms for a sufficiently long period. This approach masks the well-documented heterogeneity of depression, a disorder that is highly variable in presentation, severity, and course between individuals and is frequently comorbid with other psychiatric conditions. In this targeted review, we outline the limitations of traditional diagnosis-based research and instead advocate an alternative approach centered around symptoms as unique dimensions of clinical dysfunction that span across disorders and more closely reflect underlying neurobiological abnormalities. In particular, we highlight anhedonia-the reduced ability to anticipate and experience pleasure-as a specific, quantifiable index of reward dysfunction and an ideal candidate for dimensional investigation. Anhedonia is a core symptom of depression but also a salient feature of numerous other conditions, and its severity varies widely within clinical and even healthy populations. Similarly, reward dysfunction is a hallmark of depression but is evident across many psychiatric conditions. Reward function is especially relevant in adolescence, a period characterized by exaggerated reward-seeking behaviors and rapid maturation of neural reward circuitry. We detail extensive work by our research group and others to investigate the neural and systemic factors contributing to reward dysfunction in youth, including our cumulative findings using multiple neuroimaging and immunological measures to study depressed adolescents but also trans-diagnostic cohorts with diverse psychiatric symptoms. We describe convergent evidence that reward dysfunction: (a) predicts worse clinical outcomes, (b) is associated with functional and chemical abnormalities within and beyond the neural reward circuitry, (c) is linked to elevated peripheral levels of inflammatory biomarkers, and (d) manifests early in the course of illness. Emphasis is placed on high-resolution neuroimaging techniques, comprehensive immunological assays, and data-driven analyses to fully capture and characterize the complex, interconnected nature of these systems and their contributions to adolescent reward dysfunction.

Macro- and Microscale Stress-Associated Alterations in Brain Structure: Translational Link With Depression

Major depressive disorder (MDD) is a stress-related disorder associated with many cytoarchitectural and neurochemical changes. However, the majority of these changes cannot be reliably detected in the living brain. The examination of animal stress models and postmortem human brain tissue has significantly contributed to our understanding of the pathophysiology of MDD. Ronald Duman's work in humans and in rodent models was critical to the investigation of the contribution of synaptic deficits to MDD and chronic stress pathology, their role in the development and expression of depressive-like behavior, and reversal by novel drugs. Here, we review evidence from magnetic resonance imaging in humans and animals that suggests that corticolimbic alterations are associated with depression symptomatology. We also discuss evidence of cytoarchitectural alterations affecting neurons, astroglia, and synapses in MDD and highlight how similar changes are described in rodent chronic stress models and are linked to the emotion-related behavioral deficits. Finally, we report on the latest approaches developed to measure the synaptic and astroglial alterations in vivo, using positron emission tomography, and how it can inform on the contribution of MDD-associated cytoarchitectural alterations to the symptomatology and the treatment of stress-related disorders.

Diminished reward responsiveness is associated with lower reward network GluCEST: an ultra-high field glutamate imaging study

Low reward responsiveness (RR) is associated with poor psychological well-being, psychiatric disorder risk, and psychotropic treatment resistance. Functional MRI studies have reported decreased activity within the brain's reward network in individuals with RR deficits, however the neurochemistry underlying network hypofunction in those with low RR remains unclear. This study employed ultra-high field glutamate chemical exchange saturation transfer (GluCEST) imaging to investigate the hypothesis that glutamatergic deficits within the reward network contribute to low RR. GluCEST images were acquired at 7.0 T from 45 participants (ages 15-29, 30 females) including 15 healthy individuals, 11 with depression, and 19 with psychosis spectrum symptoms. The GluCEST contrast, a measure sensitive to local glutamate concentration, was quantified in a meta-analytically defined reward network comprised of cortical, subcortical, and brainstem regions. Associations between brain GluCEST contrast and Behavioral Activation System Scale RR scores were assessed using multiple linear regressions. Analyses revealed that reward network GluCEST contrast was positively and selectively associated with RR, but not other clinical features. Follow-up investigations identified that this association was driven by the subcortical reward network and network areas that encode the salience of valenced stimuli. We observed no association between RR and the GluCEST contrast within non-reward cortex. This study thus provides new evidence that reward network glutamate levels contribute to individual differences in RR. Decreased reward network excitatory neurotransmission or metabolism may be mechanisms driving reward network hypofunction and RR deficits. These findings provide a framework for understanding the efficacy of glutamate-modulating psychotropics such as ketamine for treating anhedonia.

The mRNA expression levels of GABAA receptor α1 and α2 subunits in patients with major depressive disorder during onset and remission

OBJECTIVE

We aimed to investigate the expression levels of GABA and GABA_A receptor α1 and α2 subunits in patients with major depressive disorder (MDD) during onset and remission.

MATERIALS AND METHODS

48 patients with MDD during onset and 45 patients with MDD during remission who were treated in our university were selected. Moreover, the control group included 46 healthy volunteers recruited in the community. The depression and anxiety symptoms were assessed by Hamilton Depression (HAMD) Scale and Hamilton Anxiety (HAMA) Scale. ELISA was used to determine the serum GABA levels. The mRNA expression of GABA_A receptor α1 and α2 subunits in peripheral blood were detected by RT-PCR.

RESULTS

The expression levels of serum GABA and of GABA_A receptor α1 and α2 subunits in MDD depression attack group were notably decreased in comparison with those in MDD remission group and control group ((4.10 ± 0.73) v.s. (5.91 ± 1.25) and (5.83 ± 1.17) umol/L, F = 5.61, p < 0.001; (0.53 ± 0.32) v.s. (0.91 ± 0.18) and (0.93 ± 0.21), F = 8.37, p < 0.001; (1.45 ± 0.86) v.s. (2.33 ± 1.49) and (2.28 ± 1.50), F = 8.23, p < 0.001). However, there were no marked difference in the levels of these three indices between the MDD remission group and the control group (p > 0.05). Serum GABA levels were negatively correlated with HAMA total score (r = -0.34, p = 0.02), HAMD total score (r = -0.46, p = 0.01) and depression core symptom score (r = -0.32, p = 0.03).

CONCLUSIONS

During the onset of MDD, there may be GABA neuronal dysfunction and abnormal expression of GABA_A receptor subunits, and those changes showed a state change, which gradually returned to normal during remission.

Glutamate and GABA Homeostasis and Neurometabolism in Major Depressive Disorder

Major depressive disorder (MDD) is a leading cause of distress, disability, and suicides. As per the latest WHO report, MDD affects more than 260 million people worldwide. Despite decades of research, the underlying etiology of depression is not fully understood. Glutamate and γ-aminobutyric acid (GABA) are the major excitatory and inhibitory neurotransmitters, respectively, in the matured central nervous system. Imbalance in the levels of these neurotransmitters has been implicated in different neurological and psychiatric disorders including MDD. ¹H nuclear magnetic resonance (NMR) spectroscopy is a powerful non-invasive method to study neurometabolites homeostasis in vivo. Additionally, ¹³C-NMR spectroscopy together with an intravenous administration of non-radioactive ¹³C-labeled glucose or acetate provides a measure of neural functions. In this review, we provide an overview of NMR-based measurements of glutamate and GABA homeostasis, neurometabolic activity, and neurotransmitter cycling in MDD. Finally, we highlight the impact of recent advancements in treatment strategies against a depressive disorder that target glutamate and GABA pathways in the brain.

GABAB receptor intracellular signaling: novel pathways for depressive disorder treatment?

Affecting over 320 million people around the world, depression has become a formidable challenge for modern medicine. In addition, an increasing number of studies cast doubt on the monoamine theory of depressive disorder and, worryingly, antidepressant medications only significantly benefit patients with severe depression. Thus, it is not surprising that researchers have shown an increased interest in new theories attempting to explain the pathogenesis of this disease. One example is the excitatory/inhibitory transmission imbalance theory. These abnormalities involve glutamate and γ-aminobutyric acid (GABA) signaling. Studies on GABA_B receptors and their antagonists are particularly promising for the treatment of depressive disorders. In this paper, intracellular pathways controlled by GABA_B receptors and their links to depression are described, including the impact of ketamine on GABAergic synaptic transmission.

Accelerated J-resolved 1 H-MRSI with limited and sparse sampling of ( k , t 1 , t 2 -space

PURPOSE

To accelerate the acquisition of J-resolved proton magnetic resonance spectroscopic imaging (¹ H-MRSI) data for high-resolution mapping of brain metabolites and neurotransmitters.

METHODS

The proposed method used a subspace model to represent multidimensional spatiospectral functions, which significantly reduced the number of parameters to be determined from J-resolved ¹ H-MRSI data. A semi-LASER-based (Localization by Adiabatic SElective Refocusing) echo-planar spectroscopic imaging (EPSI) sequence was used for data acquisition. The proposed data acquisition scheme sampled k , t 1 , t 2 -space in variable density, where t₁ and t₂ specify the J-coupling and chemical-shift encoding times, respectively. Selection of the J-coupling encoding times (or, echo time values) was based on a Cramer-Rao lower bound analysis, which were optimized for gamma-aminobutyric acid (GABA) detection. In image reconstruction, parameters of the subspace-based spatiospectral model were determined by solving a constrained optimization problem.

RESULTS

Feasibility of the proposed method was evaluated using both simulated and experimental data from a spectroscopic phantom. The phantom experimental results showed that the proposed method, with a factor of 12 acceleration in data acquisition, could determine the distribution of J-coupled molecules with expected accuracy. In vivo study with healthy human subjects also showed that 3D maps of brain metabolites and neurotransmitters can be obtained with a nominal spatial resolution of 3.0 × 3.0 × 4.8 mm³ from J-resolved ¹ H-MRSI data acquired in 19.4 min.

CONCLUSIONS

This work demonstrated the feasibility of highly accelerated J-resolved ¹ H-MRSI using limited and sparse sampling of k , t 1 , t 2 -space and subspace modeling. With further development, the proposed method may enable high-resolution mapping of brain metabolites and neurotransmitters in clinical applications.

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.

Chronic unpredictable mild stress induced depression-like behaviours and glutamate-glutamine cycling dysfunctions in both blood and brain of mice

CONTEXT

Currently, there is no cure or early preclinical diagnostic assay available for depression. Recently, depression has been observed in association with metabolic abnormalities of the glutamate (Glu)-glutamine (Gln) cycling, which is regulated by Glu, Gln and γ-aminobutyric acid (GABA) amino acids.

OBJECTIVE

The purpose of this study is to determine the changes of Glu, Gln and GABA in blood and brain of chronic unpredictable mild stress (CUMS) induced mice and to clarify the depression biomarkers in the Glu-Gln cycling.

MATERIALS AND METHODS

Male Kunming mice were divided into model group and control group randomly (n = 12). The depression model of mice was established by CUMS stimulation for 56 days. The liquid chromatography-fluorescence method was used for simultaneous determination of Glu, Gln and GABA in the plasma and brain of mice. o-Phthalaldehyde and β-mercaptoethanol were used as pre-column derivatization reagents. Neurotransmitters were analysed on high performance liquid chromatography (HPLC) on an HPH C18 column in combination with a fluorescence detector.

RESULTS

The method was simple, highly sensitive and showed excellent linearity with regression coefficients higher than 0.999, good accuracy (95-108%) and good inter-day precision (RSD <15%) for all analytes. Limit of quantification (LOQ) values were established as 0.01, 0.01 and 0.005 μg/mL for Glu, Gln and GABA. The GABA in the CUMS mouse brain (p < 0.01) was significantly increased and Gln in plasma (p < 0.01) and brain (p < 0.01) were both decreased.

CONCLUSIONS

Our study demonstrates that the Gln in plasma can be used as a biological marker of depression.