Serum glutamate and glutamine-to-glutamate ratio are associated with coronary angiography defined coronary artery disease

Circulating glutamine/glutamate ratio is closely associated with type 2 diabetes and its associated complications

Objective

This study aims to conduct a comprehensive investigation of the serum amino acid profiles of individuals with type 2 diabetes (T2D) and its related complications.

Methods

Patients with T2D were enrolled in this study. Sixteen kinds of common amino acids in the fasting circulating were assessed through liquid chromatography-mass spectrometry (LC-MS). Subsequently, correlation, regression analyses, and receiver operating characteristic (ROC) curves were conducted to assess the associations between amino acids and clinical indicators.

Results

Thirteen different kinds of amino acids were identified in diabetic patients, as compared with normal controls. The Glutamine/Glutamate (Gln/Glu) ratio was negatively correlated with BMI, HbA1c, serum uric acid, and the triglyceride-glucose (TyG) index, while it was positively correlated with HDL-C. Logistic regression analyses indicated that Gln/Glu was a consistent protective factor for both T2D (OR = 0.65, 95% CI 0.50-0.86) and obesity (OR = 0.79, 95% CI 0.66-0.96). The ROC curves demonstrated that Gln/Glu, proline, valine, and leucine provided effective predictions for diabetes risk, with Gln/Glu exhibiting the highest AUC [0.767 (0.678-0.856)]. In patients with T2D, Gln was the only amino acid that displayed a negative correlation with HbA1c (r = -0.228, p = 0.017). Furthermore, HOMA-β exhibited a negative correlation with Glu (r = -0.301, p = 0.003) but a positive correlation with Gln/Glu (r = 0.245, p = 0.017). Notably, logistic regression analyses revealed an inverse correlation of Gln/Glu with the risk of diabetic kidney disease (OR = 0.74, 95% CI 0.55-0.98) and a positive association with the risk of diabetic retinopathy (OR = 1.53, 95% CI 1.08-2.15).

Conclusion

The Gln/Glu ratio exhibited a significant association with diabetes, common metabolic parameters, and diabetic complications. These findings shed light on the pivotal role of Gln metabolism in T2D and its associated complications.

Plasma Metabolic Profiling and Multiclass Diagnostic Model Development for Stable Angina Pectoris and Acute Myocardial Infarction

Coronary heart disease remains a major global health challenge, with a clear need for enhanced early risk assessment. This study aimed to elucidate metabolic signatures across various stages of coronary heart disease and develop an effective multiclass diagnostic model. Using metabolomic approaches, gas chromatography-mass and liquid chromatography-tandem mass spectrometry were used to analyze plasma samples from healthy controls, patients with stable angina pectoris, and those with acute myocardial infarction. Pathway enrichment analysis was conducted on metabolites exhibiting significant differences. The key metabolites were identified using Random Forest and Recursive Feature Elimination strategies to construct a multiclass diagnostic model. The performance of the model was validated through 10-fold cross-validation and evaluated using confusion matrices, receiver operating characteristic curves, and calibration curves. Metabolomics was used to identify 1491 metabolites, with 216, 567, and 295 distinctly present among the healthy controls, patients with stable angina pectoris, and those with acute myocardial infarction, respectively. This implicated pathways such as the glucagon signaling pathway, d-amino acid metabolism, pyruvate metabolism, and amoebiasis across various stages of coronary heart disease. After selection, testosterone isobutyrate, N-acetyl-tryptophan, d-fructose, l-glutamic acid, erythritol, and gluconic acid were identified as core metabolites in the multiclass diagnostic model. Evaluating the diagnostic model demonstrated its high discriminative ability and accuracy. This study revealed metabolic pathway perturbations at different stages of coronary heart disease, and a precise multiclass diagnostic model was established based on these findings. This study provides new insights and tools for the early diagnosis and treatment of coronary heart disease.

Gut microbiota in combination with blood metabolites reveals characteristics of the disease cluster of coronary artery disease and cognitive impairment: a Mendelian randomization study

Background

The coexistence of coronary artery disease (CAD) and cognitive impairment has become a common clinical phenomenon. However, there is currently limited research on the etiology of this disease cluster, discovery of biomarkers, and identification of precise intervention targets.

Methods

We explored the causal connections between gut microbiota, blood metabolites, and the disease cluster of CAD combined with cognitive impairment through two-sample Mendelian randomization (TSMR). Additionally, we determine the gut microbiota and blood metabolites with the strongest causal associations using Bayesian model averaging multivariate Mendelian randomization (MR-BMA) analysis. Furthermore, we will investigate the mediating role of blood metabolites through a two-step Mendelian randomization design.

Results

We identified gut microbiota that had significant causal associations with cognitive impairment. Additionally, we also discovered blood metabolites that exhibited significant causal associations with both CAD and cognitive impairment. According to the MR-BMA results, the free cholesterol to total lipids ratio in large very low density lipoprotein (VLDL) was identified as the key blood metabolite significantly associated with CAD. Similarly, the cholesteryl esters to total lipids ratio in small VLDL emerged as the primary blood metabolite with a significant causal association with dementia with lewy bodies (DLB). For the two-step Mendelian randomization analysis, we identified blood metabolites that could potentially mediate the association between genus Butyricicoccus and CAD in the potential causal links.

Conclusion

Our study utilized Mendelian randomization (MR) to identify the gut microbiota features and blood metabolites characteristics associated with the disease cluster of CAD combined with cognitive impairment. These findings will provide a meaningful reference for the identification of biomarkers for the disease cluster of CAD combined with cognitive impairment as well as the discovery of targets for intervention to address the problems in the clinic.

Glutamate and obesity - what is the link?

PURPOSE OF REVIEW

Many studies using metabolomics have tried to unravel the metabolic signature of obesity and understand the pathophysiology of this complex and heterogeneous disease. Circulating levels of the amino acid glutamate have been consistently associated with obesity and more specifically with measurements of abdominal fat accumulation. The purpose of this narrative review is to highlight recent studies documenting this association.

RECENT FINDINGS

Circulating glutamate concentrations have been positively correlated with measurements of central fat accumulation such as waist circumference and visceral adipose tissue area. Moreover, elevated glutamate levels have been linked to a higher prevalence of type 2 diabetes, cardiovascular diseases and nonalcoholic fatty liver disease. The association with adiposity is detected in early life, and genetic predisposition does not appear as a major driver. Glutamate levels reflect in vivo synthesis rather than dietary intake. However, interventions generating metabolic improvements such as incretin receptor agonist treatment or dietary improvements may reduce plasma levels of this amino acid.

SUMMARY

Recent findings confirm the consistent association between circulating glutamate and abdominal obesity and its cardiometabolic complications. The pathophysiological pathways underlying this phenomenon are still unclear. Furthermore, studies are needed to establish the usefulness of this analyte as a biomarker of abdominal obesity.

Bone marrow plasma metabonomics of idiopathic acquired aplastic anemia patients using 1H nuclear magnetic resonance spectroscopy

INTRODUCTION

Idiopathic acquired aplastic anemia (AA) is a bone marrow failure disorder where aberrant T-cell functions lead to depletion of hematopoietic stem and progenitor cells in the bone marrow (BM) microenvironment. T-cells undergo metabolic rewiring, which regulates their proliferation and differentiation. Therefore, studying metabolic variation in AA patients may aid us with a better understanding of the T-cell regulatory pathways governed by metabolites and their pathological engagement in the disease.

OBJECTIVE

To identify the differential metabolites in BM plasma of AA patients, AA follow-up (AAF) in comparison to normal controls (NC) and to identify potential disease biomarker(s).

METHODS

The study used 1D 1H NMR Carr-Purcell-Meiboom-Gill (CPMG) spectra to identify the metabolites present in the BM plasma samples of AA (n = 40), AAF (n = 16), and NC (n = 20). Metabolic differences between the groups and predictive biomarkers were identified by using multivariate analysis and receiver operating characteristic (ROC) module of Metaboanalyst V5.0 tool, respectively.

RESULTS

The AA and AAF samples were well discriminated from NC group as per Principal Component analysis (PCA). Further, we found significant alteration in the levels of 17 metabolites in AA involved in amino-acid (Leucine, serine, threonine, phenylalanine, lysine, histidine, valine, tyrosine, and proline), carbohydrate (Glucose, lactate and mannose), fatty acid (Acetate, glycerol myo-inositol and citrate), and purine metabolism (hypoxanthine) in comparison to NC. Additionally, biomarker analysis predicted Hypoxanthine and Acetate can be used as a potential biomarker.

CONCLUSION

The study highlights the significant metabolic alterations in the BM plasma of AA patients which may have implication in the disease pathobiology.

A consortium of three-bacteria isolated from human feces inhibits formation of atherosclerotic deposits and lowers lipid levels in a mouse model

By a survey of metagenome-wide association studies (MWAS), we found a robust depletion of Bacteroides cellulosilyticus, Faecalibacterium prausnitzii, and Roseburia intestinalis in individuals with atherosclerotic cardiovascular disease (ACVD). From an established collection of bacteria isolated from healthy Chinese individuals, we selected B. cellulosilyticus, R. intestinalis, and Faecalibacterium longum, a bacterium related to F. prausnitzii, and tested the effects of these bacteria in an Apoe^/- atherosclerosis mouse model. We show that administration of these three bacterial species to Apoe^-/- mice robustly improves cardiac function, reduces plasma lipid levels, and attenuates the formation of atherosclerotic plaques. Comprehensive analysis of gut microbiota, plasma metabolome, and liver transcriptome revealed that the beneficial effects are associated with a modulation of the gut microbiota linked to a 7α-dehydroxylation-lithocholic acid (LCA)-farnesoid X receptor (FXR) pathway. Our study provides insights into transcriptional and metabolic impact whereby specific bacteria may hold promises for prevention/treatment of ACVD.

Serum nuclear magnetic resonance metabolomics analysis of human metastatic colorectal cancer: Biomarkers and pathway analysis

We describe the use of nuclear magnetic resonance metabolomics to analyze blood serum samples from healthy individuals (n = 26) and those with metastatic colorectal cancer (CRC; n = 57). The assessment, employing both linear and nonlinear multivariate data analysis techniques, revealed specific metabolite changes associated with metastatic CRC, including increased levels of lactate, glutamate, and pyruvate, and decreased levels of certain amino acids and total fatty acids. Biomarker ratios such as glutamate-to-glutamine and pyruvate-to-alanine were also found to be related to CRC. The study also found that glutamate was linked to progression-free survival and that both glutamate and 3-hydroxybutyrate were risk factors for metastatic CRC. Additionally, gas chromatography coupled to flame-ionization detection was utilized to analyze the fatty acid profile and pathway analysis was performed on the profiled metabolites to understand the metabolic processes involved in CRC. A correlation was also found between the presence of certain metabolites in the blood of CRC patients and certain clinical features.

Circulating Amino Acids and Risk of Peripheral Artery Disease in the PREDIMED Trial

Effective prevention and risk prediction are important for peripheral artery disease (PAD) due to its poor prognosis and the huge disease burden it produces. Circulating amino acids (AA) and their metabolites may serve as biomarkers of PAD risk, but they have been scarcely investigated. The objective was to prospectively analyze the associations of baseline levels of plasma AA (and their pathways) with subsequent risk of PAD and the potential effect modification by a nutritional intervention with the Mediterranean diet (MedDiet). A matched case-control study was nested in the PREDIMED trial, in which participants were randomized to three arms: MedDiet with tree nut supplementation group, MedDiet with extra-virgin olive oil (EVOO) supplementation group or control group (low-fat diet). One hundred and sixty-seven PAD cases were matched with 250 controls. Plasma AA was measured with liquid chromatography/mass spectrometry at the Broad Institute. Baseline tryptophan, serine and threonine were inversely associated with PAD (OR_{for 1 SD increase} = 0.78 (0.61-0.99); 0.67 (0.51-0.86) and 0.75 (0.59-0.95), respectively) in a multivariable-adjusted conditional logistic regression model. The kynurenine/tryptophan ratio was directly associated with PAD (OR_{for 1 SD increase} = 1.50 (1.14-1.98)). The nutritional intervention with the MedDiet+nuts modified the association between threonine and PAD (p-value interaction = 0.018) compared with the control group. However, subjects allocated to the MedDiet+EVOO group were protected against PAD independently of baseline threonine. Plasma tryptophan, kynurenine/tryptophan ratio, serine and threonine might serve as early biomarkers of future PAD in subjects at a high risk of cardiovascular disease. The MedDiet supplemented with EVOO exerted a protective effect, regardless of baseline levels of threonine.

Comprehensive Metabolic Profiling of Inflammation Indicated Key Roles of Glycerophospholipid and Arginine Metabolism in Coronary Artery Disease

Background

Systemic immune inflammation is a key mediator in the progression of coronary artery disease (CAD), concerning various metabolic and lipid changes. In this study, the relationship between the inflammatory index and metabolic profile in patients with CAD was investigated to provide deep insights into metabolic disturbances related to inflammation.

Methods

Widely targeted plasma metabolomic and lipidomic profiling was performed in 1,234 patients with CAD. Laboratory circulating inflammatory markers were mainly used to define general systemic immune and low-grade inflammatory states. Multivariable-adjusted linear regression was adopted to assess the associations between 860 metabolites and 7 inflammatory markers. Least absolute shrinkage and selection operator (LASSO) logistic-based classifiers and multivariable logistic regression were applied to identify biomarkers of inflammatory states and develop models for discriminating an advanced inflammatory state.

Results

Multiple metabolites and lipid species were linearly associated with the seven inflammatory markers [false discovery rate (FDR) <0.05]. LASSO and multivariable-adjusted logistic regression analysis identified significant associations between 45 metabolites and systemic immune-inflammation index, 46 metabolites and neutrophil-lymphocyte ratio states, 32 metabolites and low-grade inflammation score, and 26 metabolites and high-sensitivity C-reactive protein states (P < 0.05). Glycerophospholipid metabolism and arginine and proline metabolism were determined as key altered metabolic pathways for systemic immune and low-grade inflammatory states. Predictive models based solely on metabolite combinations showed feasibility (area under the curve: 0.81 to 0.88) for discriminating the four parameters that represent inflammatory states and were successfully validated using a validation cohort. The inflammation-associated metabolite, namely, β-pseudouridine, was related to carotid and coronary arteriosclerosis indicators (P < 0.05).

Conclusions

This study provides further information on the relationship between plasma metabolite profiles and inflammatory states represented by various inflammatory markers in CAD. These metabolic markers provide potential insights into pathological changes during CAD progression and may aid in the development of therapeutic targets.