Acute effects of ketamine on the pregenual anterior cingulate: linking spontaneous activation, functional connectivity, and glutamate metabolism

Ketamine exerts its rapid antidepressant effects via modulation of the glutamatergic system. While numerous imaging studies have investigated the effects of ketamine on a functional macroscopic brain level, it remains unclear how altered glutamate metabolism and changes in brain function are linked. To shed light on this topic we here conducted a multimodal imaging study in healthy volunteers (N = 23) using resting state fMRI and proton (1H) magnetic resonance spectroscopy (MRS) to investigate linkage between metabolic and functional brain changes induced by ketamine. Subjects were investigated before and during an intravenous ketamine infusion. The MRS voxel was placed in the pregenual anterior cingulate cortex (pgACC), as this region has been repeatedly shown to be involved in ketamine’s effects. Our results showed functional connectivity changes from the pgACC to the right frontal pole and anterior mid cingulate cortex (aMCC). Absolute glutamate and glutamine concentrations in the pgACC did not differ significantly from baseline. However, we found that stronger pgACC activation during ketamine was linked to lower glutamine concentration in this region. Furthermore, reduced functional connectivity between pgACC and aMCC was related to increased pgACC activation and reduced glutamine. Our results thereby demonstrate how multimodal investigations in a single brain region could help to advance our understanding of the association between metabolic and functional changes.

The Interplay between Pathophysiological Pathways in Early-Onset Severe Preeclampsia Unveiled by Metabolomics

Introduction: Preeclampsia is a multi-system disorder unique to pregnancy responsible for a great part of maternal and perinatal morbidity and mortality. The precise pathogenesis of this complex disorder is still unrevealed. Methods: We examined the pathophysiological pathways involved in early-onset preeclampsia, a specific subgroup representing its most severe presentation, using LC-MS/MS metabolomic analysis based on multi-level extraction of lipids and small metabolites from maternal blood samples, collected at the time of diagnosis from 14 preeclamptic and six matched healthy pregnancies. Statistical analysis comprised multivariate and univariate approaches with the application of over representation analysis to identify differential pathways. Results: A clear difference between preeclamptic and control pregnancies was observed in principal component analysis. Supervised multivariate analysis using orthogonal partial least square discriminant analysis provided a robust model with goodness of fit (R2X = 0.91, p = 0.002) and predictive ability (Q2Y = 0.72, p < 0.001). Finally, univariate analysis followed by 5% false discovery rate correction indicated 82 metabolites significantly altered, corresponding to six overrepresented pathways: (1) aminoacyl-tRNA biosynthesis; (2) arginine biosynthesis; (3) alanine, aspartate and glutamate metabolism; (4) D-glutamine and D-glutamate metabolism; (5) arginine and proline metabolism; and (6) histidine metabolism. Conclusion: Metabolomic analysis focusing specifically on the early-onset severe form of preeclampsia reveals the interplay between pathophysiological pathways involved in this form. Future studies are required to explore new therapeutic approaches targeting these altered metabolic pathways in early-onset preeclampsia.

San-Huang-Yi-Shen Capsule Ameliorates Diabetic Nephropathy in Rats Through Modulating the Gut Microbiota and Overall Metabolism

San-Huang-Yi-Shen capsule (SHYS) has been used in the treatment of diabetic nephropathy (DN) in clinic. However, the mechanisms of SHYS on DN remain unknown. In this study, we used a high-fat diet (HFD) combined with streptozotocin (STZ) injection to establish a DN rat model. Next, we used 16S rRNA sequencing and untargeted metabolomics to study the potential mechanisms of SHYS on DN. Our results showed that SHYS treatment alleviated the body weight loss, hyperglycemia, proteinuria, pathological changes in kidney in DN rats. SHYS could also inhibite the oxidative stress and inflammatory response in kidney. 16S rRNA sequencing analysis showed that SHYS affected the beta diversity of gut microbiota community in DN model rats. SHYX could also decrease the Firmicutes to Bacteroidetes (F to B) ratio in phylum level. In genus level, SHYX treatment affected the relative abundances of Lactobacillus, Ruminococcaceae UCG-005, Allobaculum, Anaerovibrio, Bacteroides and Candidatus_Saccharimonas. Untargeted metabolomics analysis showed that SHYX treatment altered the serum metabolic profile in DN model rats through affecting the levels of guanidineacetic acid, L-kynurenine, prostaglandin F1α, threonine, creatine, acetylcholine and other 21 kind of metabolites. These metabolites are mainly involved in glycerophospholipid metabolism, tryptophan metabolism, alanine, aspartate and glutamate metabolism, arginine biosynthesis, tricarboxylic acid (TCA) cycle, tyrosine metabolism, arginine and proline metabolism, arginine and proline metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, and D-glutamine and D-glutamate metabolism pathways. Spearman correlation analysis showed that Lactobacillus, Candidatus_Saccharimonas, Ruminococcaceae UCG-005, Anaerovibrio, Bacteroides, and Christensenellaceae_R-7_group were closely correlated with most of physiological data and the differential metabolites following SHYS treatment. In conclusion, our study revealed multiple ameliorative effects of SHYS on DN including the alleviation of hyperglycemia and the improvement of renal function, pathological changes in kidney, oxidative stress, and the inflammatory response. The mechanism of SHYS on DN may be related to the improvement of gut microbiota which regulates arginine biosynthesis, TCA cycle, tyrosine metabolism, and arginine and proline metabolism.

Metabolomic Signatures for the Effects of Weight Loss Interventions on Severe Obesity in Children and Adolescents

Childhood obesity has increased worldwide, and many clinical and public interventions have attempted to reduce morbidity. We aimed to determine the metabolomic signatures associated with weight control interventions in children with obesity. Forty children from the “Intervention for Children and Adolescent Obesity via Activity and Nutrition (ICAAN)” cohort were selected according to intervention responses. Based on changes in body mass index z-scores, 20 were responders and the remaining non-responders. Their serum metabolites were quantitatively analyzed using capillary electrophoresis time-of-flight mass spectrometry at baseline and after 6 and 18 months of intervention. After 18 months of intervention, the metabolite cluster changes in the responders and non-responders showed a difference on the heatmap, but significant metabolites were not clear. However, regardless of the responses, 13 and 49 metabolites were significant in the group of children with obesity intervention at 6 months and 18 months post-intervention compared to baseline. In addition, the top five metabolic pathways (D-glutamine and D-glutamate metabolism; arginine biosynthesis; alanine, aspartate, and glutamate metabolism; TCA cycle; valine, leucine, and isoleucine biosynthesis) including several amino acids in the metabolites of obese children after 18 months were significantly changed. Our study showed significantly different metabolomic profiles based on time post obesity-related intervention. Through this study, we can better understand and predict childhood obesity through metabolite analysis and monitoring.

Metabolomic Biomarkers Related to Non-suicidal Self-injury in Patients with Bipolar Disorder

Background: Non-suicidal self-injury (NSSI) is an important symptom of bipolar disorder (BD) and other mental disorders and has attracted the attention of researchers lately. Metabolomics is a relatively new field that can provide complementary insights into data obtained from genomic, transcriptomic, and proteomic analyses of psychiatric disorders. The aim of this study was to identify the metabolic pathways associated with BD with NSSI and assess important diagnostic and predictive indices of NSSI in BD.Method: Nuclear magnetic resonance spectrometry was performed to evaluate the serum metabolic profiles of patients with BD with NSSI (n = 31), patients with BD without NSSI (n = 46), and healthy controls (n = 10). Data were analyzed using an Orthogonal Partial Least Square Discriminant Analysis and a t-test. Differential metabolites were identified (VIP > 1 and p < 0.05), and further analyzed using Metabo Analyst 3.0 to identify associated metabolic pathways.Results: Eight metabolites in the serum and two important metabolic pathways, the urea and glutamate metabolism cycles, were found to distinguish patients with BD with NSSI from healthy controls. Eight metabolites in the serum, glycine and serine metabolism pathway, and the glucose-alanine cycle were found to distinguish patients with BD without NSSI from healthy controls. Five metabolites in the serum and the purine metabolism pathway were found to distinguish patients with BD with NSSI from those with BD without NSSI.Conclusions: Abnormalities in the urea cycle, glutamate metabolism, and purine metabolism played important roles in the pathogenesis of BD with NSSI.

A Metabolomics Study of Serum in Hospitalized Patients With Chronic Schizophrenia

Purpose: Metabolomics has attracted attention as a new method for understanding the molecular mechanisms of psychiatric disorders. Current metabolomics technology allows us to measure over hundreds of metabolites at a time and is a useful indicator of the consequences of complex and continuous changes in metabolic profiles due to the execution of genomic information and external factors of biological activity. Therefore, metabolomics is imperative to the discovery of biomarkers and mechanisms associated with pathophysiological processes. In this study, we investigated metabolites changes in hospitalized patients with chronic schizophrenia compared to that in healthy controls, and examined the correlations between the metabolites and psychiatric symptoms.Patients and Methods: Thirty patients with schizophrenia and ten healthy controls participated in this study between September 2019 and June 2020. The mean duration of disease in patients with schizophrenia was 26 years. Clinical and neuropsychiatric symptoms of patients with schizophrenia were assessed using the Positive and Negative Syndrome Scale (PANSS). Metabolomics was conducted using Capillary Electrophoresis Fourier Transform Mass Spectrometry (CE-FTMS), using serum samples from patients with schizophrenia and healthy controls. Metabolomics assigned a candidate compound to the 446 (cation 279, anion 167) peaks. Hierarchical cluster analysis (HCA), principal component analysis (PCA), logistic regression analysis, receiver operating characteristic (ROC) analysis, and linear regression analysis were used to analyze the metabolites changes, identifying the disease and the relationship between metabolites and psychiatric symptoms.Results: HCA showed that approximately 60% of metabolites had lower peak values in patients with schizophrenia than in healthy controls. Glutamate metabolism and the urea cycle had the highest proportions in the metabolic pathway, which decreased in patients with schizophrenia. PCA showed a clear separation between patients with schizophrenia and healthy controls in the first principal component (the contribution ratio of the first principal component was 15.9%). Logistic regression analysis suggested that the first principal component was a predictor of disease (odds = 1.36, 95%CI = 1.11–1.67, p = 0.0032). ROC analysis showed a sensitivity of 93% and a specificity of 100% for the diagnosis of schizophrenia with a cut-off value of the first principal component; −3.33 (AUC = 0.95). We extracted the high factor loading for the first principal component. Gamma-glutamyl-valine (γ-Glu-Val) was significantly negatively correlated with PANSS total scores (r = −0.45, p = 0.012) and PANSS general scores (r = −0.49, p = 0.0055). Gamma-glutamyl-phenylalanine (γ-Glu-Phe) was significantly negatively correlated with PANSS total score (r = −0.40, p = 0.031) and PANSS general score (r = −0.41, p = 0.025). Tetrahydrouridine was significantly positively correlated with PANSS negative scores (r = 0.53, p = 0.0061).Conclusion: Metabolites changes in hospitalized patients with chronic schizophrenia showed extensive and generalized declines. Glutamate metabolism and the urea cycle had the highest proportions in the metabolic pathway, which decreased in the schizophrenia group. Metabolomic analysis was useful to identify chronic schizophrenia. Some glutamate compound metabolites had a relationship with psychiatric symptoms.

Integrated Metabolomics and Network Pharmacology to Establish the Action Mechanism of Qingrekasen Granule for Treating Nephrotic Syndrome

Nephrotic syndrome (NS) is a clinical syndrome resulting from abnormal glomerular permeability, mainly manifesting as edema and proteinuria. Qingrekasen granule (QRKSG), a Chinese Uyghur folk medicine, is a single-flavor preparation made from chicory (Cichorium intybus L.), widely used in treating dysuria and edema. Chicory, the main component in QRKSG, effectively treats edema and protects kidneys. However, the active components in QRKSG and its underlying mechanism for treating NS remain unclear. This study explored the specific mechanism and composition of QRKSG on an NS rat model using integrated metabolomics and network pharmacology. First, metabolomics explored the relevant metabolic pathways impacted by QRKSG in the treatment of NS. Secondly, network pharmacology further explored the possible metabolite targets. Afterward, a comprehensive network was constructed using the results from the network pharmacology and metabolomics analysis. Finally, the interactions between the active components and targets were predicted by molecular docking, and the differential expression levels of the target protein were verified by Western blotting. The metabolomics results showed “D-Glutamine and D-glutamate metabolism” and “Alanine, aspartate, and glutamate metabolism” as the main targeted metabolic pathways for treating NS in rats. AKT1, BCL2L1, CASP3, and MTOR were the core QRKSG targets in the treatment of NS. Molecular docking revealed that these core targets have a strong affinity for flavonoids, terpenoids, and phenolic acids. Moreover, the expression levels of p-PI3K, p-AKT1, p-mTOR, and CASP3 in the QRKSG group significantly decreased, while BCL2L1 increased compared to the model group. These findings established the underlying mechanism of QRKSG, such as promoting autophagy and anti-apoptosis through the expression of AKT1, CASP3, BCL2L1, and mTOR to protect podocytes and maintain renal tubular function.

Bacterial challenge-associated metabolic phenotypes in Hermetia illucens defining nutritional and functional benefits

Black soldier fly (BSF, Hermetia illucens) is popular for its applications in animal feed, waste management and antimicrobial peptide source. The major advantages of BSF larva include their robust immune system and high nutritional content that can be further developed into more potential agricultural and medical applications. Several strategies are now being developed to exploit their fullest capabilities and one of these is the immunity modulation using bacterial challenges. The mechanism underlying metabolic responses of BSF to different bacteria has, however, remained unclear. In the current study, entometabolomics was employed to investigate the metabolic phenoconversion in response to either Escherichia coli, Staphylococcus aureus, or combined challenges in BSF larva. We have, thus far, characterised 37 metabolites in BSF larva challenged with different bacteria with the major biochemical groups consisting of amino acids, organic acids, and sugars. The distinct defense mechanism-specific metabolic phenotypes were clearly observed. The combined challenge contributed to the most significant metabolic phenoconversion in BSF larva with the dominant metabolic phenotypes induced by S. aureus. Our study suggested that the accumulation of energy-related metabolites provided by amino acid catabolism is the principal metabolic pathway regulating the defense mechanism. Therefore, combined challenge is strongly recommended for raising BSF immunity as it remarkably triggered amino acid metabolisms including arginine and proline metabolism and alanine, aspartate and glutamate metabolism along with purine metabolism and pyruvate metabolism that potentially result in the production of various nutritional and functional metabolites.