Mechanisms of ketamine on mice hippocampi shown by gas chromatography-mass spectrometry-based metabolomic analysis

Evidence from preclinical and clinical metabolomics studies on the antidepressant effects of ketamine and esketamine

The antidepressant effects of ketamine and esketamine are well-documented. Nonetheless, most of the underlying molecular mechanisms have to be uncovered yet. In the last decade, metabolomics has emerged as a useful means to investigate the metabolic phenotype associated with depression as well as changes induced by antidepressant treatments. This mini-review aims at summarizing the main findings from preclinical and clinical studies that used metabolomics to investigate the metabolic effects of subanesthetic, antidepressant doses of ketamine and esketamine and their relationship with clinical response. Both animal and human studies report alterations in several metabolic pathways - including the tricarboxylic acid cycle, glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, the kynurenine pathway, and the urea cycle - following the administration of ketamine or its enantiomers. Although more research is needed to clarify commonalities and differences in molecular mechanisms of action between the racemic compound and its enantiomers, these findings comprehensively support an influence of ketamine and esketamine on mitochondrial and cellular energy production, membrane homeostasis, neurotransmission, and signaling. Metabolomics may thus represent a promising strategy to clarify molecular mechanisms underlying treatment-resistant depression and related markers of clinical response to ketamine and esketamine. This body of preclinical and clinical evidence, if further substantiated, has the potential to guide clinicians towards personalized approaches, contributing to new paradigms in the clinical management of depression.

Mapping metabolite change in the mouse brain after esketamine injection by ambient mass spectrometry imaging and metabolomics

Ketamine is a new, fast, and effective antidepression treatment method; however, the possible dissociation effects, sensory changes, abuse risk, and the inability to accurately identify whether patients have a significant response to ketamine limit its clinical use. Further exploration of the antidepressant mechanisms of ketamine will contribute to its safe and practical application. Metabolites, the products of upstream gene expression and protein regulatory networks, play an essential role in various physiological and pathophysiological processes. In traditional metabonomics it is difficult to achieve the spatial localization of metabolites, which limits the further analysis of brain metabonomics by researchers. Here, we used a metabolic network mapping method called ambient air flow-assisted desorption electrospray ionization (AFADESI)-mass spectrometry imaging (MSI). We found the main changes in glycerophospholipid metabolism around the brain and sphingolipid metabolism changed mainly in the globus pallidus, which showed the most significant metabolite change after esketamine injection. The spatial distribution of metabolic changes was evaluated in the whole brain, and the potential mechanism of esketamine's antidepressant effect was explored in this research.

Non-targeted Metabolomics Profiling of Plasma Samples From Patients With Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is a neuropsychiatric disorder caused by multiple factors. Although there are clear guidelines for the diagnosis of MDD, the direct and objective diagnostic methods remain inadequate thus far.

METHODS

This study aims to discover peripheral biomarkers in patients with MDD and promote the diagnosis of MDD. Plasma samples of healthy controls (HCs, n = 52) and patients with MDD (n = 38) were collected, and then, metabolism analysis was performed using ultrahigh-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Heatmap analysis was performed to identify the different metabolites. Meanwhile, receiver operating characteristic (ROC) curves of these differential metabolites were generated.

RESULTS

Six differential metabolites were found by LC-MS/MS analysis. Three of these were increased, including L-aspartic acid (Asp), diethanolamine, and alanine. Three were decreased, including O-acetyl-L-carnitine (LAC), cystine, and fumarate. In addition, LAC, Asp, fumarate, and alanine showed large areas under the curve (AUCs) by ROC analysis.

CONCLUSION

The study explored differences in peripheral blood between depressed patients and HCs. These results indicated that differential metabolites with large AUCs may have the potential to be promising biomarkers for the diagnosis of MDD.

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.

Metabolomics in Psychiatric Disorders: What We Learn from Animal Models

Biomarkers are a recent research target within biological factors of psychiatric disorders. There is growing evidence for deriving biomarkers within psychiatric disorders in serum or urine samples in humans, however, few studies have investigated this differentiation in brain or cerebral fluid samples in psychiatric disorders. As brain samples from humans are only available at autopsy, animal models are commonly applied to determine the pathogenesis of psychiatric diseases and to test treatment strategies. The aim of this review is to summarize studies on biomarkers in animal models for psychiatric disorders. For depression, anxiety and addiction disorders studies, biomarkers in animal brains are available. Furthermore, several studies have investigated psychiatric medication, e.g., antipsychotics, antidepressants, or mood stabilizers, in animals. The most notable changes in biomarkers in depressed animal models were related to the glutamate-γ-aminobutyric acid-glutamine-cycle. In anxiety models, alterations in amino acid and energy metabolism (i.e., mitochondrial regulation) were observed. Addicted animals showed several biomarkers according to the induced drugs. In summary, animal models provide some direct insights into the cellular metabolites that are produced during psychiatric processes. In addition, the influence on biomarkers due to short- or long-term medication is a noticeable finding. Further studies should combine representative animal models and human studies on cerebral fluid to improve insight into mental disorders and advance the development of novel treatment strategies.

Absence of gut microbiota during early life affects anxiolytic Behaviors and monoamine neurotransmitters system in the hippocampal of mice

The gut microbiome is composed of an enormous number of microorganisms, generally regarded as commensal bacteria. Resident gut bacteria are an important contributor to health and significant evidence suggests that the presence of healthy and diverse gut microbiota is important for normal cognitive and emotional processing. Here we measured the expression of monoamine neurotransmitter-related genes in the hippocampus of germ-free (GF) mice and specific-pathogen-free (SPF) mice to explore the effect of gut microbiota on hippocampal monoamine functioning. In total, 19 differential expressed genes (Htr7, Htr1f, Htr3b, Drd3, Ddc, Maob, Tdo2, Fos, Creb1, Akt1, Gsk3a, Pik3ca, Pla2g5, Cyp2d22, Grk6, Ephb1, Slc18a1, Nr4a1, Gdnf) that could discriminate between the two groups were identified. Interestingly, GF mice displayed anxiolytic-like behavior compared to SPF mice, which were not reversed by colonization with gut microbiota from SPF mice. Besides, colonization of adolescent GF mice by gut microbiota was not sufficient to reverse the altered gene expression associated with their GF status. Taking these findings together, the absence of commensal microbiota during early life markedly affects hippocampal monoamine gene-regulation, which was associated with anxiolytic behaviors and monoamine neurological signs.