Circulating glutamate level as a potential biomarker for abdominal obesity and metabolic risk

Multiomics Picture of Obesity in Young Adults

Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC-MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC-MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m2, incorporating an average of 24 proteins per model. Metabolomics showed slightly lower performance (MAE = 6.06 ± 0.33 kg/m2), followed by genomics (MAE = 6.20 ± 0.34 kg/m2). As expected, multiomic models demonstrated better accuracy, particularly the combination of proteomics and metabolomics (MAE = 4.77 ± 0.33 kg/m2), while including genomics data did not enhance the results. This manuscript is the first multiomics study of obesity in a gender-balanced cohort of young adults profiled by genomic, proteomic, and metabolomic methods. The comprehensive approach provides novel insights into the molecular mechanisms of obesity, opening avenues for more targeted interventions.

Multi-omic integration of microbiome data for identifying disease-associated modules

Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and analyzing such complex datasets poses significant challenges. Most notably, current analysis methods often yield extensive lists of disease-associated features (e.g., species, pathways, or metabolites), without capturing the multi-layered structure of the data. Here, we address this challenge by introducing "MintTea", an intermediate integration-based approach combining canonical correlation analysis extensions, consensus analysis, and an evaluation protocol. MintTea identifies "disease-associated multi-omic modules", comprising features from multiple omics that shift in concord and that collectively associate with the disease. Applied to diverse cohorts, MintTea captures modules with high predictive power, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome study, MintTea identifies a module with serum glutamate- and TCA cycle-related metabolites, along with bacterial species linked to insulin resistance. In another dataset, MintTea identifies a module associated with late-stage colorectal cancer, including Peptostreptococcus and Gemella species and fecal amino acids, in line with these species' metabolic activity and their coordinated gradual increase with cancer development. This work demonstrates the potential of advanced integration methods in generating systems-level, multifaceted hypotheses underlying microbiome-disease interactions.

Impacts of glutamate, an exercise-responsive metabolite on insulin signaling

AIMS

Disruption of the insulin signaling pathway leads to insulin resistance (IR). IR is characterized by impaired glucose and lipid metabolism. Elevated levels of circulating glutamate are correlated with metabolic indicators and may potentially predict the onset of metabolic diseases. Glutamate receptor antagonists have significantly enhanced insulin sensitivity, and improved glucose and lipid metabolism. Exercise is a well-known strategy to combat IR. The aims of our narrative review are to summarize preclinical and clinical findings to show the correlations between circulating glutamate levels, IR and metabolic diseases, discuss the causal role of excessive glutamate in IR and metabolic disturbance, and present an overview of the exercise-induced alteration in circulating glutamate levels.

MATERIALS AND METHODS

A literature search was conducted to identify studies on glutamate, insulin signaling, and exercise in the PubMed database. The search covered articles published from December 1955 to January 2024, using the search terms of "glutamate", "glutamic acid", "insulin signaling", "insulin resistance", "insulin sensitivity", "exercise", and "physical activity".

KEY FINDINGS

Elevated levels of circulating glutamate are correlated with IR. Excessive glutamate can potentially hinder the insulin signaling pathway through various mechanisms, including the activation of ectopic lipid accumulation, inflammation, and endoplasmic reticulum stress. Glutamate can also modify mitochondrial function through Ca2+ and induce purine degradation mediated by AMP deaminase 2. Exercise has the potential to decrease circulating levels of glutamate, which can be attributed to accelerated glutamate catabolism and enhanced glutamate uptake.

SIGNIFICANCE

Glutamate may act as a mediator in the exercise-induced improvement of insulin sensitivity.

Explainable Machine Learning-Based Prediction Model for Diabetic Nephropathy

The aim of this study is to analyze the effect of serum metabolites on diabetic nephropathy (DN) and predict the prevalence of DN through a machine learning approach. The dataset consists of 548 patients from April 2018 to April 2019 in the Second Affiliated Hospital of Dalian Medical University (SAHDMU). We select the optimal 38 features through a least absolute shrinkage and selection operator (LASSO) regression model and a 10-fold cross-validation. We compare four machine learning algorithms, including extreme gradient boosting (XGB), random forest, decision tree, and logistic regression, by AUC-ROC curves, decision curves, and calibration curves. We quantify feature importance and interaction effects in the optimal predictive model by Shapley additive explanation (SHAP) method. The XGB model has the best performance to screen for DN with the highest AUC value of 0.966. The XGB model also gains more clinical net benefits than others, and the fitting degree is better. In addition, there are significant interactions between serum metabolites and duration of diabetes. We develop a predictive model by XGB algorithm to screen for DN. C2, C5DC, Tyr, Ser, Met, C24, C4DC, and Cys have great contribution in the model and can possibly be biomarkers for DN.

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.

Serum metabolomics profiling of improved metabolic syndrome is characterized by decreased pro-inflammatory biomarkers: A longitudinal study in Chinese male adults

Metabolic syndrome (MetS) is a serious global health concern. The objective of this study is to dynamically investigate the changes of metabolic profiles and metabolites in Chinese male MetS subjects after an 18 months diet and exercise intervention. Fifty male MetS patients defined according to International Diabetes Federation 2005 guidelines were subjected to diet and exercise counseling for 18 months. Serum samples were taken at baseline, 12 months, and 18 months, respectively, for clinical evaluation and metabolomics analyses. Diet and exercise intervention for 18 months achieved significant improvements in the metabolic profiles of all participants. Nineteen subjects (38.0%) exhibited MetS remission at the end of the study. A total of 812 relative features were characterized and 61 were successfully identified. Furthermore, 17 differential metabolites were of significance at both time points (baseline-12 months, baseline-18 months) and presented nonlinear trends through time. Eight metabolites (47.1%) were predominantly converged to inflammation and oxidative stress. Pro-inflammatory biomarkers were remarkably decreased after 18 months of intervention, and prostaglandin E2, neuroprotectin D1, and taxiphyllin in combination were firstly found to demonstrate a fair discriminative power (area under curve = 0.911) to predict the improvement of MetS undergone diet and exercise intervention. The significant shift of metabolomic profiling after 18 months of lifestyle counseling provide a novel insight and reveal that earlier inflammation control may be of potential benefit in MetS management.

A novel approach to repositioning memantine for metabolic syndrome-induced steatohepatitis: Modulation of hepatic autophagy, inflammation, and fibrosis

AIMS

This study investigated the possible hepatoprotective effects of memantine, compared to pioglitazone, in rat steatohepatitis, emphasizing its role in modulating hepatic autophagy.

MAIN METHODS

Metabolic syndrome (MetS) was provoked in adult male Wistar rats by a high fructose/fat/salt regimen for eight weeks. Then, rats were administered either memantine or pioglitazone daily for 10 weeks (both at 20 mg/kg, orally). An oral glucose tolerance test (OGTT) was done at the end of the study, and serum liver enzymes, lipids, and fasting blood glucose were measured. Also, hepatic contents of inflammatory, oxidative, and autophagy markers were quantified. Additionally, histopathological examinations of general hepatic structure and glycogen content were performed.

KEY FINDINGS

Compared to the MetS rats, memantine normalized fasting serum insulin, Homeostatic Model Assessment (HOMA-IR), serum lipids, and liver enzymes (ALT and AST). Memantine also markedly reduced hepatic inflammatory markers; NF-κB and TNF-α. In addition, hepatic NRF2 and GSH were augmented, while hepatic MDA was reduced by memantine. Interestingly, livers of the memantine group showed elevated Beclin1 and LC3 and reduced p62 contents compared to the MetS group indicating that memantine preserved hepatic autophagy. Histopathological examination revealed that memantine ameliorated hepatic steatosis and inflammation. Pioglitazone also mitigated most of the steatohepatitis-related changes, however, memantine was more effective in most of the studied parameters.

SIGNIFICANCE

The hepatoprotective effect of memantine against steatohepatitis is mediated, at least partly, through conserving hepatic autophagy along with anti-inflammatory, antioxidant, and anti-fibrotic effects.

Metabolomic biomarkers of the mediterranean diet in pregnant individuals: A prospective study

BACKGROUND AND AIMS

Metabolomic profiling is a systematic approach to identifying biomarkers for dietary patterns. Yet, metabolomic markers for dietary patterns in pregnant individuals have not been investigated. The aim of this study was to identify plasma metabolomic markers and metabolite panels that are associated with the Mediterranean diet in pregnant individuals.

METHODS

This is a prospective study of 186 pregnant individuals who had both dietary intake and metabolomic profiles measured from the Fetal Growth Studies-Singletons cohort. Dietary intakes during the peri-conception/1st trimester and the second trimester were accessed at 8-13 and 16-22 weeks of gestation, respectively. Adherence to the Mediterranean diet was measured by the alternate Mediterranean Diet (aMED) score. Fasting plasma samples were collected at 16-22 weeks and untargeted metabolomics profiling was performed using the mass spectrometry-based platforms. Metabolites individually or jointly associated with aMED scores were identified using linear regression and least absolute shrinkage and selection operator (LASSO) regression models with adjustment for potential confounders, respectively.

RESULTS

Among 459 annotated metabolites, 64 and 41 were individually associated with the aMED scores of the diet during the peri-conception/1st trimester and during the second trimester, respectively. Fourteen metabolites were associated with the Mediterranean diet in both time windows. Most Mediterranean diet-related metabolites were lipids (e.g., acylcarnitine, cholesteryl esters (CEs), linoleic acid, long-chain triglycerides (TGs), and phosphatidylcholines (PCs), amino acids, and sugar alcohols. LASSO regressions also identified a 10 metabolite-panel that were jointly associated with aMED score of the diet during the peri-conception/1st trimester (AUC: 0.74; 95% CI: 0.57, 0.91) and a 3 metabolites-panel in the 2nd trimester (AUC: 0.68; 95% CI: 0.50, 0.86).

CONCLUSION

We identified plasma metabolomic markers for the Mediterranean diet among pregnant individuals. Some of them have also been reported in previous studies among non-pregnant populations, whereas others are novel. The results from our study warrant replication in pregnant individuals by future studies.

CLINICAL TRIAL REGISTRATION NUMBER

This study was registered at ClinicalTrials.gov.

Association between Circulating Amino Acids and COVID-19 Severity

The severity of the symptoms associated with COVID-19 is highly variable, and has been associated with circulating amino acids as a group of analytes in metabolomic studies. However, for each individual amino acid, there are discordant results among studies. The aims of the present study were: (i) to investigate the association between COVID-19-symptom severity and circulating amino-acid concentrations; and (ii) to assess the ability of circulating amino-acid levels to predict adverse outcomes (intensive-care-unit admission or hospital death). We studied a sample of 736 participants from the Biobanque Québécoise COVID-19. All participants tested positive for COVID-19, and the severity of symptoms was determined using the World-Health-Organization criteria. Circulating amino acids were measured by HPLC-MS/MS. We used logistic models to assess the association between circulating amino acids concentrations and the odds of presenting mild vs. severe or mild vs. moderate symptoms, as well as their accuracy in predicting adverse outcomes. Patients with severe COVID-19 symptoms were older on average, and they had a higher prevalence of obesity and type 2 diabetes. Out of 20 amino acids tested, 16 were significantly associated with disease severity, with phenylalanine (positively) and cysteine (inversely) showing the strongest associations. These associations remained significant after adjustment for age, sex and body mass index. Phenylalanine had a fair ability to predict the occurrence of adverse outcomes, similar to traditionally measured laboratory variables. A multivariate model including both circulating amino acids and clinical variables had a 90% accuracy at predicting adverse outcomes in this sample. In conclusion, patients presenting severe COVID-19 symptoms have an altered amino-acid profile, compared to those with mild or moderate symptoms.

Adipose tissue macrophages: implications for obesity-associated cancer

Obesity is one of the most serious global health problems, with an incidence that increases yearly and coincides with the development of cancer. Adipose tissue macrophages (ATMs) are particularly important in this context and contribute to linking obesity-related inflammation and tumor progression. However, the functions of ATMs on the progression of obesity-associated cancer remain unclear. In this review, we describe the origins, phenotypes, and functions of ATMs. Subsequently, we summarize the potential mechanisms on the reprogramming of ATMs in the obesity-associated microenvironment, including the direct exchange of dysfunctional metabolites, inordinate cytokines and other signaling mediators, transfer of extracellular vesicle cargo, and variations in the gut microbiota and its metabolites. A better understanding of the properties and functions of ATMs under conditions of obesity will lead to the development of new therapeutic interventions for obesity-related cancer.

Novel weight loss diet attenuates dietary-induced obesity in mice and might correlate with altered gut microbiota and metabolite profiles

Although many dietary patterns have been studied for weight loss, various limitations still exist. Therefore, we designed a novel weight loss diet (NWLD) with carbohydrate, protein, and fat (energy) contents of 45%, 20%, and 35%, respectively. The saturated fatty acids: monounsaturated fatty acids:polyunsaturated fatty acids ratio was 1:2:1, and the insoluble: soluble dietary fiber ratio was 2:1. We aimed to observe the effect of NWLD on weight loss and understand the underlying metabolic mechanisms. Twenty-nine male C57BL/6J mice were selected. Nine mice were fed ordinary feed in a blank control group, and the rest were fed a high-fat diet (HFD) to establish obese mouse models. Twelve weeks later, obesity models were established, and 10 obese mice were switched to NWLD feeding. Six weeks after switching the diet, the serum, intestinal feces, and kidneys of mice were collected. Obesity-related indicators, gut microbial composition, and fecal metabolite profiles of all the mice were determined, and the correlations among these indicators were analyzed. Kidney function indicators were also assessed. The results showed that the NWLD attenuated HFD-induced weight gain, serum triglycerides (TG), and inflammatory factors, optimized the body composition without kidney function impairment. Amino acid metabolism pathways and metabolites might play key roles in this process. The findings of this research imply that NWLD could be an effective nutritional remedy for managing dietary-induced obesity.

Large-scale analysis of circulating glutamate and adipose gene expression in relation to abdominal obesity

Circulating levels of the amino acid glutamate are associated with central fat accumulation, yet the pathophysiology of this relationship remains unknown. We aimed to (i) refine and validate the association between circulating glutamate and abdominal obesity in a large twin cohort, and (ii) investigate whether transcriptomic profiles in adipose tissue could provide insight into the biological mechanisms underlying the association. First, in a cohort of 4665 individuals from the TwinsUK resource, we identified individuals with abdominal obesity and compared prevalence of the latter across circulating glutamate quintiles. Second, we used transcriptomic signatures generated from adipose tissue, both subcutaneous and visceral, to investigate associations with circulating glutamate levels. Individuals in the top circulating glutamate quintile had a sevenfold higher prevalence of abdominal obesity compared to those in the bottom quintile. The adipose tissue transcriptomic analyses identified GLUL, encoding Glutamate-Ammonia Ligase, as being associated with circulating glutamate and abdominal obesity, with pronounced signatures in the visceral depot. In conclusion, circulating glutamate is positively associated with the prevalence of abdominal obesity which relates to dysregulated GLUL expression specifically in visceral adipose tissue.

Serum metabolites associated with increased insulin resistance and low cardiorespiratory fitness in overweight adolescents

BACKGROUND AND AIMS

Obesity affects metabolism, increasing the risk of developing non-communicable diseases in adolescence, due to excess adipose tissue and low cardiorespiratory fitness (CRF). The metabolomics approach allows the elucidation of metabolites, which may have the concentrations altered by several factors, such as body composition (BC). We aimed to analyze the metabolomic profile of normal-weight and overweight adolescents and associate the metabolites with clinical markers related to BC, insulin resistance (IR), and CRF.

METHODS AND RESULTS

The sample was composed of 57 adolescents and divided into two groups: the normal-weight group (NWG, n = 24) and the overweight group (OWG, n = 33). They underwent blood collection and anthropometric, BC, and CRF assessment. Blood serum samples were analyzed by ¹H-NMR spectroscopy (600 MHz). The OWG presented higher values of body weight (BW), body mass index (BMI), waist circumference (WC), fasting glucose, insulin, IR, cholesterol, and percentage of fat mass (%FM) and lower levels of peak oxygen consumption (VO₂ peak) compared with the NWG. The OWG presented lower concentrations of 3-hydroxyisovalerate, glutamate, and methionine as well as higher concentrations of aspartate, asparagine, creatine, glycerol, myo-inositol, proline, pyruvate, tyrosine, and valerate compared with the NWG. The concentrations of glutamate, myo-inositol, creatine, methionine, and valerate correlated with %FM; pyruvate and valerate positively correlated with IR; and glutamate, tyrosine, and valerate negatively correlated with CRF.

CONCLUSION

Changes in the BC lead to changes in the metabolomic profile of adolescents, and the altered metabolites are associated with increased IR and low CRF. These results indicate new targets for health monitoring and prevention of cardiovascular and metabolic diseases in adolescents.

Plasma amino acid profile, a biomarker for visceral adipose tissue that can substitute for waist circumference in Japanese Americans

BACKGROUND

Greater visceral fat area (VFA) is associated with cardiometabolic outcomes. We sought to identify cross-sectional and longitudinal associations between amino acid (AA) levels and VFA in Japanese-Americans.

METHODS

From the cohort of 342 Japanese-American participants (51% men) in a study of diabetes risk factors who were free from diabetes, we measured levels of 20 AA by mass spectrometry, height, weight, waist circumference (WC), VFA, subcutaneous fat area by single-slice CT at the umbilicus. Using AA significantly associated with VFA in univariate analyses, we created a VFA prediction index, termed the 4A index. We compared area under receiver-operating characteristic curve (AUROC) of the 4A index to WC and an existing AA index (Yamakado et al. Clin Obes 2012) in classifying VFA at different cutoff values. We fit age-adjusted linear regression models to evaluate associations between AA levels and change in VFA over 5 years.

RESULTS

All 20 AA levels significantly detected VFA excess, but WC was better. The 4A index performed better than Yamakado index at classifying VFA ≥ 100 cm² (0.798, 0.807 vs. 0.677, 0.671 for men and women, p < 0.0033) and VFA ≥ sex-specific median values (0.797, 0.786 vs. 0.676, 0.629 for men and women, p < 0.0017). AA significantly associated with change in VFA over 5 years were asparagine, glutamate, glutamine, glycine, methionine, proline, threonine in men; and histidine, isoleucine, tyrosine in women (p < 0.05).

CONCLUSIONS

The 4A index can serve as a biomarker for VFA in Japanese-Americans and be considered for this purpose when WC is not available.

Processed Foods - Getting Back to The Basics

PURPOSE OF REVIEW

Real-world data suggested that more than half of daily energy intake is coming from processed and ultra-processed foods in most western countries. This high consumption of processed foods is of concern, given laboratory and epidemiological studies' findings that prove overwhelming harms of processed foods on human health.

RECENT FINDINGS

Data demonstrate that consumption of processed foods is increasing with more reports linking ultra-processed foods to various medical conditions; namely, obesity, metabolic syndrome, atherosclerotic cardiovascular diseases, and certain types of cancer. Scientific community's understanding of the mechanisms and substances by which processed foods are affecting human health is expanding. Holistic approach to the current critical situation is advisable and requires collaborative public health strategies. The current review describes recent classification of processed foods and highlights the pertinent findings in the relationship between processed foods and health. It also outlines key clinical data relevant to the topic.

The central role of the glutamate metabolism in long-term antiretroviral treated HIV-infected individuals with metabolic syndrome

Metabolic syndrome (MetS) is a significant factor for cardiometabolic comorbidities in people living with HIV (PLWH) and a barrier to healthy aging. The long-term consequences of HIV-infection and combination antiretroviral therapy (cART) in metabolic reprogramming are unknown. In this study, we investigated metabolic alterations in well-treated PLWH with MetS to identify potential mechanisms behind the MetS phenotype using advanced statistical and machine learning algorithms. We included 200 PLWH from the Copenhagen Comorbidity in HIV-infection (COCOMO) study. PLWH were grouped into PLWH with MetS (n = 100) defined according to the International Diabetes Federation (IDF) consensus worldwide definition of the MetS or without MetS (n = 100). The untargeted plasma metabolomics was performed using ultra-high-performance liquid chromatography/mass spectrometry (UHPLC/MS/MS) and immune-phenotyping of Glut1 (glucose transporter), xCT (glutamate/cysteine transporter) and MCT1 (pyruvate/lactate transporter) by flow cytometry. We applied several conventional approaches, machine learning algorithms, and linear classification models to identify the biologically relevant metabolites associated with MetS in PLWH. Of the 877 identified biochemicals, 9% (76/877) differed significantly between PLWH with and without MetS (false discovery rate < 0.05). The majority belonged to amino acid metabolism (43%). A consensus identification by combining supervised and unsupervised methods indicated 11 biomarkers of MetS phenotype in PLWH. A weighted co-expression network identified seven communities of positively intercorrelated metabolites. A single community contained six of the potential biomarkers mainly related to glutamate metabolism. Transporter expression identified altered xCT and MCT in both lymphocytic and monocytic cells. Combining metabolomics and immune-phenotyping indicated altered glutamate metabolism associated with MetS in PLWH, which has clinical significance.

Early identification of metabolic syndrome risk: A review of reviews and proposal for defining pre-metabolic syndrome status

AIMS

a) To analyze the relationship of known and emerging biomarkers/indicators for early risk identification of cardiometabolic health risk; b) to identify early risk markers to be used in both clinical and nonclinical settings; and c) to propose a definition of early risk identification in terms of pre-metabolic syndrome (PreMetSyn).

DATA SYNTHESIS

Pubmed/Medline, Web of Science, Embase, and Cochrane were searched for Systematic Reviews and Meta-analysis. Selected studies were evaluated, and relevant data were extracted and synthesized.

CONCLUSIONS

Serum uric acid is a good predictive biomarker of metabolic syndrome (MetSyn) and has been associated with non-alcoholic liver fat disease (NAFLD) and type 2 diabetes. NAFLD emerges as an early risk indicator of PreMetSyn by itself. Muscle strength should also be included as an early risk marker of cardiometabolic health. High serum triglycerides and waist circumference confirm their predictive value regarding MetSyn. Indicators related to an inflammatory/pro-inflammatory status usually linked to MetSyn showed limited evidence as robust biomarkers for PreMetSyn. Authors suggest defining PreMetSyn related to cardiometabolic risk. It is also necessary to determine how close people are to the cut-off point of MetSyn components, including emerging indicators proposed by our review. Some biomarkers could be used as indicators of PreMetSyn, before any of the MetSyn components appear, allowing early health interventions to prevent its development. Defining a PreMetSyn status might consider both emerging indicators and those variables already included in the definition of MetSyn. New indicators should be considered to create a new risk score specifically meant for PreMetSyn.

Plasma Amino Acids and Residual Hypertriglyceridemia in Diabetic Patients Under Statins: Two Independent Cross-Sectional Hospital-Based Cohorts

Objective: The objective of the study was to investigate the relationship of amino acid metabolism with hypertriglyceridemia in diabetic patients under statins free of prior cardiovascular diseases.

Methods: Two independent cross-sectional hospital based cohorts, i.e., Liaoning Medical University First Affiliated Hospital (LMUFAH, n = 146) and the Second Affiliated Hospital of Dalian Medical University (SAHDMU, n = 294) were included in the current analysis. Hypertriglyceridemia was defined as triglyceride ≥1.7 mmol/L, and well-controlled LDL-C was defined as <2.6 mmol/L. The adjusted ORs (95% CI) of circulating metabolic measures for hypertriglyceridemia were assessed using logistic regression. Pooled results of metabolites with the same direction of association in both cohorts were combined using inverse variance-weighted fixed-effect meta-analysis. Difference of identified metabolites in patients with and without hypertriglyceridemia were also obtained in the context of LDL-C.

Results: Patients, 86 and 106, were with hypertriglyceridemia in LMUFAH and SAHDMU, respectively. We observed that elevated alanine, asparagine, leucine, and valine were consistently associated with increased hypertriglyceridemia in both cohorts. In fixed-effect pooled analysis, the OR (95% CI) per SD increase was 1.71 (1.32–2.20) for alanine, 1.62 (1.20–2.19) for asparagine, 1.64 (1.22–2.20) for leucine, and 1.62 (1.22–2.13) for valine (all P values ranged from 0.0018 to <0.0001); adjusting for C-peptide attenuated effect sizes of Ala, Leu, and Val for hypertriglyceridemia. The difference were robust in groups with well- or bad-controlled LDL-C.

Conclusion: Among 23 amino acids, alanine, asparagine, leucine, and valine were positively associated with increased residual risk of hypertriglyceridemia in diabetic patients with statin treatment.

Quercetin Ameliorates Gut Microbiota Dysbiosis That Drives Hypothalamic Damage and Hepatic Lipogenesis in Monosodium Glutamate-Induced Abdominal Obesity

Monosodium glutamate (MSG)-induced abdominal obesity, conventionally caused by hypothalamic damage, is a critical risk factor for health problem. Microbiota-gut-brain axis plays important roles in a variety of metabolic diseases. However, whether gut microbiota is involved in the pathogenesis for MSG-induced abdominal obesity and the effect of quercetin on it remains unclear. Herein, we find that MSG-induced gut microbiota dysbiosis contributes to neuronal damage in the hypothalamus, as indicated by antibiotics-induced microbiota depletion and co-house treatment. Inspired by this finding, we investigate the mechanism in-depth for MSG-induced abdominal obesity. Liver transcriptome profiling shows retinol metabolism disorder in MSG-induced abdominal obese mice. In which, retinol saturase (RetSat) in the liver is notably up-regulated, and the downstream lipogenesis is correspondingly elevated. Importantly, microbiota depletion or co-house treatment eliminates the difference of RetSat expression in the liver, indicating gut microbiota changes are responsible for liver retinol metabolism disorder. Moreover, this study finds dietary quercetin could modulate MSG-induced gut microbiota dysbiosis, alleviate hypothalamic damage and down-regulate liver RetSat expression, thus ameliorating abdominal obesity. Our study enriches the pathogenesis of MSG-induced abdominal obesity and provides a prebiotic agent to ameliorate abdominal obesity.

Dietary glutamic acid and aspartic acid as biomarkers for predicting diabetic retinopathy

The screening rate of diabetic retinopathy (DR) is low despite the importance of early diagnosis. We investigated the predictive value of dietary glutamic acid and aspartic acid for diagnosis of DR using the Korea National Diabetes Program cohort study. The 2067 patients with type 2 diabetes without DR were included. The baseline intakes of energy, glutamic acid and aspartic acid were assessed using a 3-day food records. The risk of DR incidence based on intake of glutamic acid and aspartic acid was analyzed. The DR group was older, and had higher HbA1c, longer DM duration, lower education level and income than non-DR group (all p < 0.05). The intake of total energy, glutamic acid and aspartic acid were lower in DR group than non-DR group (p = 0.010, p = 0.025 and p = 0.042, respectively). There was no difference in the risk of developing DR according to the intake of glutamic acid and ascorbic acid. But, aspartic acid intake had a negative correlation with PDR. Hence, the intake of glutamic acid and aspartic acid did not affect in DR incidence. However, lower aspartic acid intake affected the PDR incidence.

Activation of N-methyl-D-aspartate receptor regulates insulin sensitivity and lipid metabolism

RATIONALE

Although significant progress has been made in understanding the mechanisms of steatosis and insulin resistance, the physiological functions of regulators in these processes remain largely elusive. Evidence has suggested that the glutamate/N-methyl-D-aspartic acid receptor (NMDAR) axis contributes to acute lung injury, pulmonary arterial hypertension, and diabetes, but the specific metabolic contribution of the glutamate/NMDAR axis is not clear. Here we provide data at the animal, cellular, and molecular levels to support the role of the glutamate/NMDAR axis as a therapeutic target for metabolic syndrome in obesity. Methods: We examined the glutamate level in the obese mouse induced by a high-fat diet (HFD) for 12 weeks. To assess the role of NMDAR in insulin sensitivity and lipid metabolism, we tested the effects of Memantine (an NMDAR antagonist) and NMDA (an NMDAR agonist) on mice fed with HFD or standard chow diet. The in vitros NMDAR roles were analyzed in hepatocytes and potential mechanisms involved in regulating lipid metabolism were investigated. Results: Glutamate was increased in the serum of HFD-treated mice. The NMDAR blockade by Memantine decreased the susceptibility to insulin resistance and hepatic steatosis in obese mice. NMDA treatment for 6 months induced obesity in mice, characterized by hyperglycemia, hyperlipidemia, insulin resistance, and pathological changes in the liver. We provided in vitro evidence demonstrating that NMDAR activation facilitated metabolic syndrome in obesity through promoting lipid accumulation. NMDAR inhibition attenuated lipid accumulation induced by palmitic acid. Mechanistically, NMDAR activation impaired fatty acid oxidation by reducing PPARα phosphorylation and activity. The PPARα activity reduction induced by NMDAR activation was reversibly mediated by ERK1/2 signaling. Conclusion: These findings revealed that targeting NMDAR might be a promising therapeutic strategy for metabolic syndrome in obesity.

High Prevalence of Metabolic Syndrome and Its Related Demographic Factors in North of Iran: Results from the PERSIAN Guilan Cohort Study

INTRODUCTION

The prevalence of metabolic syndrome has increased in recent decades around the world and is currently reaching epidemic levels as it is a major public health and clinical concern. The aim of this study was to evaluate the prevalence of metabolic syndrome and its related demographic factors in a population-based study.

METHODS

In this cross-sectional study, the target population consisted of 10520 individuals aged 35-70 years in Phase 1 of the Persian Guilan cohort study (Guilan site/Some'e Sara) that was conducted in 2014-2017. Demographic, anthropometric, blood pressure, and biochemical data were used in this study. The IDF definitions were used to diagnose the metabolic syndrome.

RESULTS

The prevalence of the syndrome according to IDF and ATP definition was 42.87% (95% CI: 41.92-41.81) and 40.68% (95% CI: 39.74-41.62), respectively. The prevalence of components for central obesity, high triglyceride, HDL cholesterol, blood glucose, and hypertension components was 75.8%, 43.1%, 40.6%, 39.2% and 37.9%, respectively. All demographic variables were related to the syndrome, and among them age, gender, and residence were identified as independent and strong predictive variables in the regression model. More than 92% of the population had at least one component of the syndrome.

CONCLUSION

The results of the study show a high prevalence of metabolic syndrome risk factors. It is essential to educate healthy lifestyle behaviors and further health education in the high-risk groups identified in this study, especially the elderly, women, and rural residents.

A chemical-specific adjustment factor for human interindividual differences in kinetics for glutamates (E620-625)

Use of a default methodology for establishment of a health-based guidance value (HBGV) resulted in a group acceptable daily intake (ADI) for glutamates (E620-625) below the normal dietary glutamate intake, and also lower than the intake of free glutamate by breast fed babies. Use of a chemical-specific adjustment factor (CSAF) may overcome this problem. The present study investigates the interindividual human variability in glutamate plasma and brain levels in order to define a CSAF for the interindividual variation in kinetics, a HK_AF, for glutamates. Human clinical data on plasma glutamate levels available from different groups of subjects at Mitsui Memorial Hospital as well as literature data on plasma and brain-related glutamate levels were collected and analysed. The median HK_AF value obtained amounted to 2.62-2.74 to 2.33-2.52 for plasma derived values and to 1.68-1.81 for brain derived values. Combining these values with the CSAF for the interspecies differences in kinetics of 1 and the default factors for interspecies and interindividual differences in dynamics of 2.5 and 3.16 results in an overall CSAF of 16-20. Using this CSAF will result in a HBGV for glutamate that is no longer below the acceptable range of oral intake (AROI).

A metagenome-wide association study of gut microbiome and visceral fat accumulation

Purpose

Visceral fat is an independent risk factor for metabolic and cardiovascular disease. The study aimed to investigate the associations between gut microbiome and visceral fat.

Methods

We recruited 32 obese adults and 30 healthy controls at baseline. Among the obese subjects, 14 subjects underwent laparoscopic sleeve gastrectomy (LSG) and were followed 6 months after surgery. Abdominal visceral fat area (VFA) and subcutaneous fat area (SFA) were measured by magnetic resonance imaging. Waist, hipline, waist-to-hip ratio (WHR) and body mass index (BMI) were included as simple obese parameters. Gut microbiome was analyzed by metagenomic sequencing.

Results

Among the obese parameters, VFA had the largest number of correlations with the species that were differentially enriched between obese and healthy subjects, following by waist, WHR, BMI, hipline, and SFA. Within the species negatively correlated with VFA, Eubacterium eligens had the strongest correlation, following by Clostridium citroniae, C. symbiosum, Bacteroides uniformis, E. ventriosum, Ruminococcaceae bacterium D16, C. hathewayi, etc. C. hathewayi and C. citroniae were increased after LSG. Functional analyses showed that among all the obese parameters, VFA had strongest correlation coefficients with the obesity-related microbial pathways. Microbial pathways involved in carbohydrate fermentation and biosynthesis of L-glutamate and L-glutamine might contribute to visceral fat accumulation.

Conclusions

Visceral fat was more closely correlated with gut microbiome compared with subcutaneous fat, suggesting an intrinsic connection between gut microbiome and metabolic cardiovascular diseases. Specific microbial species and pathways which were closely associated with visceral fat accumulation might contribute to new targeted therapies for metabolic disorders.

Protein, amino acids and obesity treatment

Dietary proteins have been used for years to treat obesity. Body weight loss is beneficial when it concerns fat mass, but loss of fat free mass - especially muscle might be detrimental. This occurs because protein breakdown predominates over synthesis, thus administering anabolic dietary compounds like proteins might counter fat free mass loss while allowing for fat mass loss.Indeed, varying the quantity of proteins will decrease muscle anabolic response and increase hyperphagia in rodents fed a low protein diet; but it will favor lean mass maintenance and promote satiety, in certain age groups of humans fed a high protein diet. Beyond protein quantity, protein source is an important metabolic regulator: whey protein and plant based diets exercize favorable effects on the risk of developing obesity, body composition, metabolic parameters or fat free mass preservation of obese patients. Specific amino-acids like branched chain amino acids (BCAA), methionine, tryptophan and its metabolites, and glutamate can also positively influence parameters and complications of obesity especially in rodent models, with less studies translating this in humans.Tuning the quality and quantity of proteins or even specific amino-acids can thus be seen as a potential therapeutic intervention on the body composition, metabolic syndrome parameters and appetite regulation of obese patients. Since these effects vary across age groups and much of the data comes from murine models, long-term prospective studies modulating proteins and amino acids in the human diet are needed.

Exercise training modulates the gut microbiota profile and impairs inflammatory signaling pathways in obese children

Childhood obesity has reached epidemic levels and is a serious health concern associated with metabolic syndrome, nonalcoholic fatty liver disease, and gut microbiota alterations. Physical exercise is known to counteract obesity progression and modulate the gut microbiota composition. This study aims to determine the effect of a 12-week strength and endurance combined training program on gut microbiota and inflammation in obese pediatric patients. Thirty-nine obese children were assigned randomly to the control or training group. Anthropometric and biochemical parameters, muscular strength, and inflammatory signaling pathways in mononuclear cells were evaluated. Bacterial composition and functionality were determined by massive sequencing and metabolomic analysis. Exercise reduced plasma glucose levels and increased dynamic strength in the upper and lower extremities compared with the obese control group. Metagenomic analysis revealed a bacterial composition associated with obesity, showing changes at the phylum, class, and genus levels. Exercise counteracted this profile, significantly reducing the Proteobacteria phylum and Gammaproteobacteria class. Moreover, physical activity tended to increase some genera, such as Blautia, Dialister, and Roseburia, leading to a microbiota profile similar to that of healthy children. Metabolomic analysis revealed changes in short-chain fatty acids, branched-chain amino acids, and several sugars in response to exercise, in correlation with a specific microbiota profile. Finally, the training protocol significantly inhibited the activation of the obesity-associated NLRP3 signaling pathway. Our data suggest the existence of an obesity-related deleterious microbiota profile that is positively modified by physical activity intervention. Exercise training could be considered an efficient nonpharmacological therapy, reducing inflammatory signaling pathways induced by obesity in children via microbiota modulation.

Physical fitness regimens could stimulate shifts in gut microbiome composition and metabolism that counteract health risks associated with childhood obesity. This condition can increase the risk of metabolic and cardiovascular disease later in life. Several studies have indicated that disturbances in the microbial populations in the digestive tract may contribute to these diseases. Researchers led by Sonia Sánchez-Campos of the Institute of Biomedicine, León,Spain, recently assessed the impact of exercise and endurance training on microbiome composition in obese children. They determined that these regimens can produce measurable shifts in the gut microbe population, yielding bacterial communities that are more similar to those seen in non-obese children. These shifts were accompanied by alterations in metabolic activity that may help mitigate inflammatory signaling and other processes that fuel obesity-related disease.