The potential role of glutamate in the current diabetes epidemic

Hyperglycemia impairs EAAT2 glutamate transporter trafficking and glutamate clearance in islets of Langerhans: implications for type 2 diabetes pathogenesis and treatment

Pancreatic endocrine cells employ a sophisticated system of paracrine and autocrine signals to synchronize their activities, including glutamate, which controls hormone release and β-cell viability by acting on glutamate receptors expressed by endocrine cells. We here investigate whether alteration of the excitatory amino acid transporter 2 (EAAT2), the major glutamate clearance system in the islet, may occur in type 2 diabetes mellitus and contribute to β-cell dysfunction. Increased EAAT2 intracellular localization was evident in islets of Langerhans from T2DM subjects as compared with healthy control subjects, despite similar expression levels. Chronic treatment of islets from healthy donors with high-glucose concentrations led to the transporter internalization in vesicular compartments and reduced [H3]-d-glutamate uptake (65 ± 5% inhibition), phenocopying the findings in T2DM pancreatic sections. The transporter relocalization was associated with decreased Akt phosphorylation protein levels, suggesting an involvement of the phosphoinositide 3-kinase (PI3K)/Akt pathway in the process. In line with this, PI3K inhibition by a 100-µM LY294002 treatment in human and clonal β-cells caused the transporter relocalization in intracellular compartments and significantly reduced the glutamate uptake compared to control conditions, suggesting that hyperglycemia changes the trafficking of the transporter to the plasma membrane. Upregulation of the glutamate transporter upon treatment with the antibiotic ceftriaxone rescued hyperglycemia-induced β-cells dysfunction and death. Our data underscore the significance of EAAT2 in regulating islet physiology and provide a rationale for potential therapeutic targeting of this transporter to preserve β-cell survival and function in diabetes.NEW & NOTEWORTHY The glutamate transporter SLC1A2/excitatory amino acid transporter 2 (EAAT2) is expressed on the plasma membrane of pancreatic β-cells and controls islet glutamate clearance and β-cells survival. We found that the EAAT2 membrane expression is lost in the islets of Langerhans from type 2 diabetes mellitus (T2DM) patients due to hyperglycemia-induced downregulation of the phosphoinositide 3-kinase/Akt pathway and modification of its intracellular trafficking. Pharmacological rescue of EAAT2 expression prevents β-cell dysfunction and death, suggesting EAAT2 as a new potential target of intervention in T2DM.

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.

Alterations of the glutamatergic system in diabetes mellitus

Diabetes mellitus (DM) is a chronic disease characterized by elevated blood glucose levels caused by a lack of insulin production (type 1 diabetes) or insulin resistance (type 2 diabetes). It is well known that DM is associated with cognitive deficits and metabolic and neurophysiological changes in the brain. Glutamate is the main excitatory neurotransmitter in the central nervous system that plays a key role in synaptic plasticity, learning, and memory processes. An increasing number of studies have suggested that abnormal activity of the glutamatergic system is implicated in the pathophysiology of DM. Dysfunction of glutamatergic neurotransmission in the central nervous system can provide an important neurobiological substrate for many disorders. Magnetic resonance spectroscopy (MRS) is a non-invasive technique that allows a better understanding of the central nervous system factors by measuring in vivo the concentrations of brain metabolites within the area of interest. Here, we briefly review the MRS studies that have examined glutamate levels in the brain of patients with DM. The present article also summarizes the available data on abnormalities in glutamatergic neurotransmission observed in different animal models of DM. In addition, the role of gut microbiota in the development of glutamatergic alterations in DM is addressed. We speculate that therapeutic strategies targeting the glutamatergic system may be beneficial in the treatment of central nervous system-related changes in diabetic patients.

Machine learning for predicting diabetic metabolism in the Indian population using polar metabolomic and lipidomic features

AIMS

To identify metabolite and lipid biomarkers of diabetes in the Indian subpopulation in newly diagnosed diabetic and long-term diabetic individuals. To utilize the global polar metabolomic and lipidomic profiles to predict the susceptibility of an individual to diabetes using machine learning algorithms.

MATERIALS AND METHODS

87 individuals, including healthy, newly diabetic, and long-term diabetics on medication, were included in the study. Post consent, their serum was used to isolate polar metabolome and lipidome. NMR and LCMS were used to identify the polar metabolites and lipids, respectively. Statistical analysis was done to determine significantly altered molecules. NMR and LCMS comprehensive data were utilized to generate diabetic models using machine learning algorithms. 10 more individuals (pre-diabetic) were recruited, and their polar metabolomic and lipidomic profiles were generated. Pre-diabetic metabolic profiles were then utilized to predict the diabetic status of the metabolome and lipidome beyond glucose levels.

RESULTS

Mannose, Betaine, Xanthine, Triglyceride (38:1), Sphingomyelin (d63:7), and Phosphatidic acid (37:2) are some of the top key biomarkers of diabetes. The predictive model generated showed the receiver operating characteristic area under the curve (ROC-AUC) as 1 on both test and validation data indicating excellent accuracy. This model then predicted the diabetic closeness of the metabolism of pre-diabetic individuals based on probability scores.

CONCLUSION

Polar metabolic and lipid profile of diabetic individuals is very different from that of healthy individuals. Lipid profile alters before the polar metabolic profile in diabetes-susceptible individuals. Without regard to glucose, the diabetic closeness of the metabolism of any individual can be determined.

Metabolomics analysis delineates the therapeutic effects of Yinlan Tiaozhi capsule on triton WR-1339 -induced hyperlipidemia in mice

Hyperlipidemia is a disorder of lipid metabolism resulting from abnormal blood lipid metabolism and is one of the most frequent metabolic diseases that endanger people's health. Yinlan Tiaozhi capsule (YL) is a formulated TCM widely used to treat hyperlipidemia. The purpose of this study was to discover biomarkers utilizing untargeted metabolomics techniques, as well as to analyze the mechanisms underlying the changes in metabolic pathways linked to lipid-lowering, anti-inflammation, and regulation of angiogenesis in hyperlipidemia mice. To assess the efficacy of YL, serum total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), and high-density lipoprotein cholesterol (HDL-c) levels were measured. Biochemical examinations showed that YL significantly reduced the levels of TC, TG, LDL-c, Il6, Tnf-α, and Vegfa in hyperlipidemia mice (p < 0.01). YL also significantly increased the levels of HDL-c and Alb (p < 0.01). Twenty-seven potential serum biomarkers associated with hyperlipidemia were determined. These differential metabolites were related to the reduction of serum lipid levels in hyperlipidemia mice, probably through metabolic pathways such as linoleic acid metabolism, glycerophospholipid metabolism, phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and D-glutamine and D-glutamate metabolism. Further correlation analysis showed that the serum lipid reduction through YL was related to the metabolites (amino acid metabolites, phospholipids metabolites, and fatty acids metabolites). The present study reveals that YL has a profound effect on alleviating triton WR-1339-induced hyperlipidemia, inflammation, and angiogenesis and that the positive effects of YL were primarily associated with the correction of metabolic abnormalities and the maintenance of metabolite dynamic balance.

Multi-omics approach to socioeconomic disparity in metabolic syndrome reveals roles of diet and microbiome

The epidemy of metabolic syndrome (MetS) is typically preceded by adoption of a "risky" lifestyle (e.g., dietary habit) among populations. Evidence shows that those with low socioeconomic status (SES) are at an increased risk for MetS. To investigate this, we recruited 123 obese subjects (body mass index [BMI] ≥ 30) from Chicago. Multi-omic data were collected to interrogate fecal microbiota, systemic markers of inflammation and immune activation, plasma metabolites, and plasma glycans. Intestinal permeability was measured using the sugar permeability testing. Our results suggest a heterogenous metabolic dysregulation among obese populations who are at risk of MetS. Systemic inflammation, linked to poor diet, intestinal microbiome dysbiosis, and gut barrier dysfunction may explain the development of MetS in these individuals. Our analysis revealed 37 key features associated with increased numbers of MetS features. These features were used to construct a composite metabolic-inflammatory (MI) score that was able to predict progression of MetS among at-risk individuals. The MI score was correlated with several markers of poor diet quality as well as lower levels of gut microbial diversity and abnormalities in several species of bacteria. This study reveals novel targets to reduce the burden of MetS and suggests access to healthy food options as a practical intervention.

Increased glutamate in type 2 diabetes in the Korean population is associated with increased plasminogen levels

BACKGROUND

Glutamate is a major neurotransmitter, although it causes cytotoxicity and inflammation in nonneuronal organs. This study aimed to investigate the metabolic disorders in which glutamate, associated with type 2 diabetes onset, is induced in the liver.

METHODS

An analysis of Korean community-based Ansan-Ansung cohort study data as well as functional research using in vitro and mouse models were performed.

RESULTS

Groups with high plasma glutamate levels (T2, T3) had a significantly increased risk of diabetes incidence after 8 years, compared to the group with relatively low glutamate levels (T1). Analysis of the effect of glutamate on diabetes onset in vitro showed that glutamate induces insulin resistance by increasing glucose-related protein 78 (GRP78) and phosphoenolpyruvate carboxykinase (PEPCK) expression in SK-Hep-1 human liver cells. In addition, three different genes, FRMB4B, PLG, and PARD3, were significantly associated with glutamate and were identified via genome-wide association studies. Among glutamate-related genes, plasminogen (PLG) levels were most significantly increased in several environments in which insulin resistance was induced, and was also upregulated by glutamate. Glutamate-induced increase in PLG in liver cells was caused by metabotropic glutamate receptor 5 activation, and PLG levels were also upregulated after extracellular secretion. Moreover, glutamate increased the expression of plasminogen activator inhibitor-1 (PAI-1). Thus, extracellular secreted PLG cannot be converted to plasmin (fibrinolytic enzyme) by increased PAI-1.

CONCLUSIONS

Increased glutamate is closely associated with the development of diabetes, and it may cause metabolic disorders by inhibiting the fibrinolytic system, which plays an important role in determining blood clots, a hallmark of diabetes.

Association of Long-term Antiseizure Medication Use and Incident Type 2 Diabetes Mellitus

BACKGROUND AND OBJECTIVES

Diabetes mellitus (DM) contributes significantly to metabolic syndrome and cardiovascular events, and it may be a comorbidity of epilepsy. The objective of this study was to investigate whether long-term antiseizure medication (ASM) use is associated with the risk of developing type 2 diabetes.

METHODS

We analyzed data from the Chang Gung Research Database. Patients aged ≥45 years who received ASM treatment from January 2001 to May 2019 were identified. Patients with DM-associated diseases and short-term ASM use were excluded. The patients were classified into nonenzyme interaction, enzyme-inducing, enzyme-inhibiting, and mixed ASM groups. The rate of incident diabetes associated with individual ASM was further analyzed. Propensity score weighting was performed to balance between-group differences. Analyses were conducted with Cox proportional regression models and stabilized inverse probability of treatment weighting (IPTW). Hazard ratios (HRs) were calculated at 3, 4, 6, and 9 years after the index date and the end of follow-up.

RESULTS

A total of 5,103 patients were analyzed, of whom 474 took nonenzyme interaction ASMs, 1,156 took enzyme-inducing ASMs, 336 took enzyme-inhibiting ASMs, and 3,137 took mixed ASMs. During follow-up (39,248 person-years), 663 patients developed new-onset DM, and the prevalence was 13.0%. The incidence of DM plateaued at 6-9 years after ASM initiation. Enzyme-inhibiting ASMs were significantly associated with a higher HR starting at the third year and then throughout the study period. The HRs were 1.93 (95% CI 1.33-2.80), 1.85 (95% CI 1.24-2.75), and 2.08 (95% CI 1.43-3.03) in unadjusted, adjusted, and stabilized IPTW models, respectively, at the end of follow-up. The dosing of ASM did not increase the risk of DM, and none of the individual ASM analyses reached statistical significance.

DISCUSSION

The long-term use of enzyme-inhibiting ASMs was associated with an increased risk of incident DM, and the risk increased with the duration of treatment. These findings may guide the choice of drugs in those requiring long-term ASM therapy, particularly in high-risk individuals.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that enzyme-inhibiting ASMs were associated with an increased risk of developing DM compared with nonenzyme interaction ASMs.

Metabolomic profiling of glucose homeostasis in African Americans: the Insulin Resistance Atherosclerosis Family Study (IRAS-FS)

INTRODUCTION

African Americans are at increased risk for type 2 diabetes.

OBJECTIVES

This work aimed to examine metabolomic signature of glucose homeostasis in African Americans.

METHODS

We used an untargeted liquid chromatography-mass spectrometry metabolomic approach to comprehensively profile 727 plasma metabolites among 571 African Americans from the Insulin Resistance Atherosclerosis Family Study (IRAS-FS) and investigate the associations between these metabolites and both the dynamic (S_I, insulin sensitivity; AIR, acute insulin response; DI, disposition index; and S_G, glucose effectiveness) and basal (HOMA-IR and HOMA-B) measures of glucose homeostasis using univariate and regularized regression models. We also compared the results with our previous findings in the IRAS-FS Mexican Americans.

RESULTS

We confirmed increased plasma metabolite levels of branched-chain amino acids and their metabolic derivatives, 2-aminoadipate, 2-hydroxybutyrate, glutamate, arginine and its metabolic derivatives, carbohydrate metabolites, and medium- and long-chain fatty acids were associated with insulin resistance, while increased plasma metabolite levels in the glycine, serine and threonine metabolic pathway were associated with insulin sensitivity. We also observed a differential ancestral effect of glutamate on glucose homeostasis with significantly stronger effects observed in African Americans than those previously observed in Mexican Americans.

CONCLUSION

We extended the observations that metabolites are useful biomarkers in the identification of prediabetes in individuals at risk of type 2 diabetes in African Americans. We revealed, for the first time, differential ancestral effect of certain metabolites (i.e., glutamate) on glucose homeostasis traits. Our study highlights the need for additional comprehensive metabolomic studies in well-characterized multiethnic cohorts.

Metabolic perspective of astrocyte dysfunction in Alzheimer's disease and type 2 diabetes brains

The term type III diabetes (T3DM) has been proposed for Alzheimer's disease (AD) due to the shared molecular and cellular features between type 2 diabetes (T2DM) and insulin resistance-associated memory deficits and cognitive decline in elderly individuals. Astrocytes elicit neuroprotective or deleterious effects in AD progression and severity. Patients with T2DM are at a high risk of cognitive impairment, and targeting astrocytes might be promising in alleviating neurodegeneration in the diabetic brain. Recent studies focusing on cell-specific activities in the brain have revealed the important role of astrocytes in brain metabolism (e.g., glucose metabolism, lipid metabolism), neurovascular coupling, synapses, and synaptic plasticity. In this review, we discuss how astrocytes and their dysfunction result in multiple pathological and clinical features of AD and T2DM from a metabolic perspective and the potential comorbid mechanism in these two diseases from the perspective of astrocytes.

Metabolic Changes and Their Associations with Selected Nutrients Intake in the Group of Workers Exposed to Arsenic

Arsenic (As) exposure causes numerous adverse health effects, which can be reduced by the nutrients involved in the metabolism of iAs (inorganic As). This study was carried out on two groups of copper-smelting workers: WN, workers with a urinary total arsenic (tAs) concentration within the norm (n = 75), and WH, workers with a urinary tAs concentration above the norm (n = 41). This study aimed to analyze the association between the intake level of the nutrients involved in iAs metabolism and the signal intensity of the metabolites that were affected by iAs exposure. An untargeted metabolomics analysis was carried out on urine samples using liquid chromatography-mass spectrometry, and the intake of the nutrients was analyzed based on 3-day dietary records. Compared with the WN group, five pathways (the metabolism of amino acids, carbohydrates, glycans, vitamins, and nucleotides) with twenty-five putatively annotated metabolites were found to be increased in the WH group. In the WN group, the intake of nutrients (methionine; vitamins B2, B6, and B12; folate; and zinc) was negatively associated with six metabolites (cytosine, D-glucuronic acid, N-acetyl-D-glucosamine, pyroglutamic acid, uridine, and urocanic acid), whereas in the WH group, it was associated with five metabolites (D-glucuronic acid, L-glutamic acid, N-acetyl-D-glucosamine, N-acetylneuraminic acid, and uridine). Furthermore, in the WH group, positive associations between methionine, folate, and zinc intake and the signal intensity of succinic acid and 3-mercaptolactic acid were observed. These results highlight the need to educate the participants about the intake level of the nutrients involved in iAs metabolism and may contribute to further considerations with respect to the formulation of dietary recommendations for people exposed to iAs.

Monosodium glutamate in a type 2 diabetes context: A large scoping review

This scoping review aimed to map and elaborate the heterogenous and inconclusive body of evidence relating monosodium glutamate (MSG) and type 2 diabetes (T2DM). For this reason, multiple health outcomes related to T2DM were included and a systematic search was conducted. Experimental and observational trials between 1995 and January 2021 were collected. The tests were highly heterogenous in their samples, doses, route of exposures, durations, diets and conclusions. There was a pattern of negative effects of MSG at oral doses ≥2,000 mg/kg of body weight, and by gavage or injection at any given dose. Evidence was lacking in many areas and most of the evidence relied on short term tests. Further research should focus on standardizing and justifying methodologies, conducting long term studies and toxicokinetic tests, and avoiding bias. Focusing on the gaps highlighted and investigating mechanisms of action of MSG is crucial. Evidence-based toxicology is encouraged.

Ethnic disparities attributed to the manifestation in and response to type 2 diabetes: insights from metabolomics

Type 2 diabetes (T2D) associated health disparities among different ethnicities have long been known. Ethnic variations also exist in T2D related comorbidities including insulin resistance, vascular complications and drug response. Genetic heterogeneity, dietary patterns, nutrient metabolism and gut microbiome composition attribute to ethnic disparities in both manifestation and progression of T2D. These factors differentially regulate the rate of metabolism and metabolic health. Metabolomics studies have indicated significant differences in carbohydrate, lipid and amino acid metabolism among ethnicities. Interestingly, genetic variations regulating lipid and amino acid metabolism might also contribute to inter-ethnic differences in T2D. Comprehensive and comparative metabolomics analysis between ethnicities might help to design personalized dietary regimen and newer therapeutic strategies. In the present review, we explore population based metabolomics data to identify inter-ethnic differences in metabolites and discuss how (a) genetic variations, (b) dietary patterns and (c) microbiome composition may attribute for such differences in T2D.

Fermented Rosa Roxburghii Tratt Juice Alleviates High-Fat Diet-Induced Hyperlipidemia in Rats by Modulating Gut Microbiota and Metabolites

Hyperlipidemia endangers human health and has become a significant public health problem. This study aimed to investigate the mechanism of the hypolipidemic effects of Fermented Rosa roxburghii Tratt juice (FRRT) on hyperlipidemic rats and a new hypolipidemic intervention strategy was disclosed. The study revealed 12 weeks FRRT treatment significantly decreased the body weight, total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-c), while high-density lipoprotein cholesterol (HDL-c) increased. We integrated the 16S rDNA sequencing and metabolomic profiling to evaluate the changes in the gut microbiota and metabolites. Significant changes in microbial composition accompanied marked changes in 56 feces metabolites. The results showed that FRRT could decrease the ratio of Firmicutes to Bacteroidetes, while increase the abundance of some bacterial genera (Prevotella, Paraprevotellaceae_Prevotella, Ruminococcus, Oscillospira). Metabolomics analysis displayed that the metabolisms of bile acid, amino acid and lipid were significantly affected by FRRT. Correlation analysis suggest that the reductions in serum lipids by FRRT are associated with the gut microbial community and their associated metabolites (amino acid metabolites, bile acid metabolites, and lipid metabolites). This study confirmed FRRT could be used as a new dietary and therapeutic strategy to dyslipidemia by improving the gut microbiota dysbiosis, metabolomic disorders and regulating the dyslipidemia. Our study also extended the understanding of the relationship between gut microbiota, metabolites, and lipid-lowering functions.

Metabolomic Analysis of Serum and Tear Samples from Patients with Obesity and Type 2 Diabetes Mellitus

Metabolomics strategies are widely used to examine obesity and type 2 diabetes (T2D). Patients with obesity (n = 31) or T2D (n = 26) and sex- and age-matched controls (n = 28) were recruited, and serum and tear samples were collected. The concentration of 23 amino acids and 10 biogenic amines in serum and tear samples was analyzed. Statistical analysis and Pearson correlation analysis along with network analysis were carried out. Compared to controls, changes in the level of 6 analytes in the obese group and of 10 analytes in the T2D group were statistically significant. For obesity, the energy generation, while for T2D, the involvement of NO synthesis and its relation to insulin signaling and inflammation, were characteristic. We found that BCAA and glutamine metabolism, urea cycle, and beta-oxidation make up crucial parts of the metabolic changes in T2D. According to our data, the retromer-mediated retrograde transport, the ethanolamine metabolism, and, consequently, the endocannabinoid signaling and phospholipid metabolism were characteristic of both conditions and can be relevant pathways to understanding and treating insulin resistance. By providing potential therapeutic targets and new starting points for mechanistic studies, our results emphasize the importance of complex data analysis procedures to better understand the pathomechanism of obesity and diabetes.

Statistical mediation of the relationships between chronological age and lipoproteins by nonessential amino acids in healthy men

Aging is a major risk factor for metabolic impairment that may lead to age-related diseases such as cardiovascular disease. Different mechanisms that may explain the interplay between aging and lipoproteins, and between aging and low-molecular-weight metabolites (LMWMs), in the metabolic dysregulation associated with age-related diseases have been described separately. Here, we statistically evaluated the possible mediation effects of LMWMs on the relationships between chronological age and lipoprotein concentrations in healthy men ranging from 19 to 75 years of age. Relative and absolute concentrations of LMWMs and lipoproteins, respectively, were assessed by nuclear magnetic resonance (NMR) spectroscopy. Multivariate linear regression and mediation analysis were conducted to explore the associations between age, lipoproteins and LMWMs. The statistical significance of the identified mediation effects was evaluated using the bootstrapping technique, and the identified mediation effects were validated on a publicly available dataset. Chronological age was statistically associated with five lipoprotein classes and subclasses. The mediation analysis showed that serine mediated 24.1% (95% CI: 22.9 – 24.7) of the effect of age on LDL-P, and glutamate mediated 17.9% (95% CI: 17.6 – 18.5) of the effect of age on large LDL-P. In the publicly available data, glutamate mediated the relationship between age and an NMR-derived surrogate of cholesterol. Our results suggest that the age-related increase in LDL particles may be mediated by a decrease in the nonessential amino acid glutamate. Future studies may contribute to a better understanding of the potential biological role of glutamate and LDL particles in aging mechanisms and age-related diseases.

Combinatorial, additive and dose-dependent drug-microbiome associations

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery^1-5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.

Effects of Polygonatum sibiricum saponin on hyperglycemia, gut microbiota composition and metabolic profiles in type 2 diabetes mice

Diabetes is a global disease that endangers human health. As reported, saponins are effective bioactive compounds for treating type 2 diabetes mellitus (T2DM) and have nontoxic side effects. This study aimed to examine the hypoglycemic effects of Polygonatum sibiricum saponin (PSS) on T2DM mice. We found that PSS could significantly decrease the levels of insulin secretion and fasting blood glucose (FBG) in T2DM mice. And the level of triacylglycerol (TG), total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in the blood was decreased. In contrast, the content of high-density lipoprotein cholesterol (HDL-C) was increased. 16S rDNA sequencing was used to evaluate the changes in the gut microbiota of T2DM mice, and metabolites were analyzed by metabolomic profiling. The results showed that PSS could decrease the abundance of Firmicutes in T2DM mice, increase the abundance of Bacteroidetes. It also increased the abundance of some bacterial genera (Lactobacillus, Lachnospiraceae_NK4A136_group and Intestinimonas). The phenotypes of the gut microbiome also changed accordingly. Metabolomics analysis showed that carbohydrate metabolism and amino acid metabolisms, such as L-alanine and L-glutamic acid, were greatly affected by PSS. In addition, the levels of inositol and chlorogenic acid in metabolites also increased significantly under PSS intervention. In general, PSS could exert its hypoglycemic effect, regulate the gut microbiota and affect the metabolism of T2DM mice.

Iron Metabolism in Pancreatic Beta-Cell Function and Dysfunction

Iron is an essential element involved in a variety of physiological functions. In the pancreatic beta-cells, being part of Fe-S cluster proteins, it is necessary for the correct insulin synthesis and processing. In the mitochondria, as a component of the respiratory chain, it allows the production of ATP and reactive oxygen species (ROS) that trigger beta-cell depolarization and potentiate the calcium-dependent insulin release. Iron cellular content must be finely tuned to ensure the normal supply but also to prevent overloading. Indeed, due to the high reactivity with oxygen and the formation of free radicals, iron excess may cause oxidative damage of cells that are extremely vulnerable to this condition because the normal elevated ROS production and the paucity in antioxidant enzyme activities. The aim of the present review is to provide insights into the mechanisms responsible for iron homeostasis in beta-cells, describing how alteration of these processes has been related to beta-cell damage and failure. Defects in iron-storing or -chaperoning proteins have been detected in diabetic conditions; therefore, the control of iron metabolism in these cells deserves further investigation as a promising target for the development of new disease treatments.

Perturbation of serum metabolome in relation to type 2 diabetes mellitus and urinary levels of phthalate metabolites and bisphenols

BACKGROUND

Emerging evidence has proved the associations between exposure to phthalates (PAEs) and bisphenols and type 2 diabetes mellitus (T2DM), but the underlying mechanisms for these associations are poorly understood. Metabolomics is a powerful tool to identify differential metabolites and metabolic pathways related to diseases and chemical exposure, which may reveal underlying mechanisms. However, little is known about the roles of metabolism in the associations for PAE and bisphenol exposure with T2DM.

OBJECTIVES

The purpose of the study was to investigate the roles of metabolism in the associations for exposure to PAEs and bisphenols with T2DM.

METHODS

In this study, 60 T2DM cases and 60 controls, who were matched in age, sex, and body mass index (BMI), were selected from the total study population in our previous studies. Fasting blood and spot urine samples of the volunteers were used for non-targeted metabolomics analysis and determination of phthalate metabolites (mPAEs) and bisphenols, respectively. The associations of urinary mPAEs and bisphenols with screened metabolic biomarkers in metabolomics analysis were analyzed using multiple linear regression models.

RESULTS

Based on non-targeted metabolomics, 19 serum metabolic biomarkers were screened between T2DM cases and controls, mostly related to galactose metabolism, amino acid metabolism, and pyrimidine metabolism. More than half of mPAEs were mostly positively associated with up-regulated metabolic biomarkers and negatively associated with down-regulated biomarkers. Different from PAEs, no evident results suggested the roles of metabolism in the associations between bisphenol exposure and T2DM.

CONCLUSIONS

Combined with the positive associations between most urinary mPAEs and T2DM in our previous study, our findings indicated that PAE exposure may contribute to T2DM risk through disturbing galactose metabolism, amino acid metabolism (especially arginine biosynthesis and alanine, aspartate and glutamate metabolism), and pyrimidine metabolism.

Integrated Metabolomics and Proteomics Analyses in the Local Milieu of Islet Allografts in Rejection versus Tolerance

An understanding of the immune mechanisms that lead to rejection versus tolerance of allogeneic pancreatic islet grafts is of paramount importance, as it facilitates the development of innovative methods to improve the transplant outcome. Here, we used our established intraocular islet transplant model to gain novel insight into changes in the local metabolome and proteome within the islet allograft’s immediate microenvironment in association with immune-mediated rejection or tolerance. We performed integrated metabolomics and proteomics analyses in aqueous humor samples representative of the graft’s microenvironment under each transplant outcome. The results showed that several free amino acids, small primary amines, and soluble proteins related to the Warburg effect were upregulated or downregulated in association with either outcome. In general, the observed shifts in the local metabolite and protein profiles in association with rejection were consistent with established pro-inflammatory metabolic pathways and those observed in association with tolerance were immune regulatory. Taken together, the current findings further support the potential of metabolic reprogramming of immune cells towards immune regulation through targeted pharmacological and dietary interventions against specific metabolic pathways that promote the Warburg effect to prevent the rejection of transplanted islets and promote their immune tolerance.

A Scoping Review: Metabolomics Signatures Associated with Animal and Plant Protein Intake and Their Potential Relation with Cardiometabolic Risk

The dietary shift from animal protein (AP) to plant protein (PP) sources is encouraged for both environmental and health reasons. For instance, PPs are associated with lower cardiovascular and diabetes risks compared with APs, although the underlying mechanisms mostly remain unknown. Metabolomics is a valuable tool for globally and mechanistically characterizing the impact of AP and PP intake, given its unique ability to provide integrated signatures and specific biomarkers of metabolic effects through a comprehensive snapshot of metabolic status. This scoping review is aimed at gathering and analyzing the available metabolomics data associated with PP- and AP-rich diets, and discusses the metabolic effects underlying these metabolomics signatures and their potential implication for cardiometabolic health. We selected 24 human studies comparing the urine, plasma, or serum metabolomes associated with diets with contrasted AP and PP intakes. Among the 439 metabolites reported in those studies as able to discriminate AP- and PP-rich diets, 46 were considered to provide a robust level of evidence, according to a scoring system, especially amino acids (AAs) and AA-related products. Branched-chain amino acids, aromatic amino acids (AAAs), glutamate, short-chain acylcarnitines, and trimethylamine-N-oxide, which are known to be related to an increased cardiometabolic risk, were associated with AP-rich diets, whereas glycine (rather related to a reduced risk) was associated with PP-rich diets. Tricarboxylic acid (TCA) cycle intermediates and products from gut microbiota AAA degradation were also often reported, but the direction of their associations differed across studies. Overall, AP- and PP-rich diets result in different metabolomics signatures, with several metabolites being plausible candidates to explain some of their differential associations with cardiometabolic risk. Additional studies specifically focusing on protein type, with rigorous intake control, are needed to better characterize the associated metabolic phenotypes and understand how they could mediate differential AP and PP effects on cardiometabolic risk.

Assessment of the amino acid profile in Thai patients with type 2 diabetes mellitus using liquid chromatography-mass spectrometry

Background

Type 2 diabetes mellitus (T2DM) is a global health problem. Early identification of those at risk is necessary to prevent its onset through lifestyle and pharmacologic interventions. T2DM is characterized by metabolic abnormalities, including protein metabolism. Evaluation of the amino acid profile might be beneficial for early assessment.

Methods

Liquid chromatography-mass spectrometry was performed to separate and quantify plasma amino acids from two groups of Thai individuals, patients with T2DM (n=103) and healthy individuals (n=104). Multivariate analysis was applied to compare free amino acid levels between groups. Subgroup analyses of patients with T2DM were performed to assess the association between amino acid profiles and important T2DM clinical characteristics.

Results

The multivariate analysis showed that glutamic acid was significantly associated with T2DM (OR 1.113, 95% CI 1.006 to 1.231) and results from the subgroup analyses showed that this correlation was significant in all subgroups of patients (p<0.05).

Conclusions

This finding needs to be confirmed in larger groups of patients with T2DM to explore glutamic acid as a biomarker for early prevention in particular at-risk groups. An in-depth understanding of the involvement of glutamic acid in T2DM could enhance our understanding of the disease and potentially provide novel interventions.

Library-assisted nonlinear blind separation and annotation of pure components from a single 1H nuclear magnetic resonance mixture spectra

Due to its capability for high-throughput screening ¹H nuclear magnetic resonance (NMR) spectroscopy is commonly used for metabolite research. The key problem in ¹H NMR spectroscopy of multicomponent mixtures is overlapping of component signals and that is increasing with the number of components, their complexity and structural similarity. It makes metabolic profiling, that is carried out through matching acquired spectra with metabolites from the library, a hard problem. Here, we propose a method for nonlinear blind separation of highly correlated components spectra from a single ¹H NMR mixture spectra. The method transforms a single nonlinear mixture into multiple high-dimensional reproducible kernel Hilbert Spaces (mRKHSs). Therein, highly correlated components are separated by sparseness constrained nonnegative matrix factorization in each induced RKHS. Afterwards, metabolites are identified through comparison of separated components with the library comprised of 160 pure components. Thereby, a significant number of them are expected to be related with diabetes type 2. Conceptually similar methodology for nonlinear blind separation of correlated components from two or more mixtures is presented in the Supplementary material. Single-mixture blind source separation is exemplified on: (i) annotation of five components spectra separated from one ¹H NMR model mixture spectra; (ii) annotation of fifty five metabolites separated from one ¹H NMR mixture spectra of urine of subjects with and without diabetes type 2. Arguably, it is for the first time a method for blind separation of a large number of components from a single nonlinear mixture has been proposed. Moreover, the proposed method pinpoints urinary creatine, glutamic acid and 5-hydroxyindoleacetic acid as the most prominent metabolites in samples from subjects with diabetes type 2, when compared to healthy controls.

High plasma glutamate and low glutamine-to-glutamate ratio are associated with type 2 diabetes: Case-cohort study within the PREDIMED trial

BACKGROUND AND AIMS

Glutamate, glutamine are involved in energy metabolism, and have been related to cardiometabolic disorders. However, their roles in the development of type-2 diabetes (T2D) remain unclear. The aim of this study was to examine the effects of Mediterranean diet on associations between glutamine, glutamate, glutamine-to-glutamate ratio, and risk of new-onset T2D in a Spanish population at high risk for cardiovascular disease (CVD).

METHODS AND RESULTS

The present study was built within the PREDIMED trial using a case-cohort design including 892 participants with 251 incident T2D cases and 641 non-cases. Participants (mean age 66.3 years; female 62.8%) were non diabetic and at high risk for CVD at baseline. Plasma levels of glutamine and glutamate were measured at baseline and after 1-year of intervention. Higher glutamate levels at baseline were associated with increased risk of T2D with a hazard ratio (HR) of 2.78 (95% CI, 1.43-5.41, P for trend = 0.0002). In contrast, baseline levels of glutamine (HR: 0.64, 95% CI, 0.36-1.12; P for trend = 0.04) and glutamine-to-glutamate ratio (HR: 0.31, 95% CI, 0.16-0.57; P for trend = 0.0001) were inversely associated with T2D risk when comparing extreme quartiles. The two Mediterranean diets (MedDiet + EVOO and MedDiet + mixed nuts) did not alter levels of glutamine and glutamate after intervention for 1 year. However, MedDiet mitigated the positive association between higher baseline plasma glutamate and T2D risk (P for interaction = 0.01).

CONCLUSION

Higher levels of glutamate and lower levels of glutamine were associated with increased risk of T2D in a Spanish population at high risk for CVD. Mediterranean diet might mitigate the association between the imbalance of glutamine and glutamate and T2D risk. This trial is registered at http://www.controlled-trials.com, ISRCTN35739639.

Nine Amino Acids Are Associated With Decreased Insulin Secretion and Elevated Glucose Levels in a 7.4-Year Follow-up Study of 5,181 Finnish Men

Several amino acids (AAs) have been shown to be associated with insulin resistance and increased risk of type 2 diabetes, but no previous studies have investigated the association of AAs with insulin secretion in a longitudinal setting. Our study included 5,181 participants of the cross-sectional METabolic Syndrome In Men (METSIM) study having metabolomics data on 20 AAs. A total of 4,851 had a 7.4-year follow-up visit. Nine AAs (phenylalanine, tryptophan, tyrosine, alanine, isoleucine, leucine, valine, aspartate, and glutamate) were significantly (P < 5.8 × 10^-5) associated with decreases in insulin secretion (disposition index) and the elevation of fasting or 2-h glucose levels. Five of these AAs (tyrosine, alanine, isoleucine, aspartate, and glutamate) were also found to be significantly associated with an increased risk of incident type 2 diabetes after adjustment for confounding factors. Our study is the first population-based large cohort to report that AAs are associated not only with insulin resistance but also with decreased insulin secretion.

The association of sleep with metabolic pathways and metabolites: evidence from the Dietary Approaches to Stop Hypertension (DASH)-sodium feeding study

INTRODUCTION

Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile.

OBJECTIVES

To assess the association between sleep and blood metabolites.

METHODS

We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)-Sodium feeding trial (1997-1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher's method to calculate associations between sleep and 38 metabolic pathways.

RESULTS

Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association).

CONCLUSION

Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep.

Targeted metabolomics to understand the association between arsenic metabolism and diabetes-related outcomes: Preliminary evidence from the Strong Heart Family Study

BACKGROUND

Inorganic arsenic exposure is ubiquitous and both exposure and inter-individual differences in its metabolism have been associated with cardiometabolic risk. A more efficient arsenic metabolism profile (lower MMA%, higher DMA%) has been associated with reduced risk for arsenic-related health outcomes. This profile, however, has also been associated with increased risk for diabetes-related outcomes.

OBJECTIVES

The mechanism behind these conflicting associations is unclear; we hypothesized the one-carbon metabolism (OCM) pathway may play a role.

METHODS

We evaluated the influence of OCM on the relationship between arsenic metabolism and diabetes-related outcomes (HOMA2-IR, waist circumference, fasting plasma glucose) using metabolomic data from an OCM-specific and P180 metabolite panel measured in plasma, arsenic metabolism measured in urine, and HOMA2-IR and FPG measured in fasting plasma. Samples were drawn from baseline visits (2001-2003) in 59 participants from the Strong Heart Family Study, a family-based cohort study of American Indians aged ≥14 years from Arizona, Oklahoma, and North/South Dakota.

RESULTS

In unadjusted analyses, a 5% increase in DMA% was associated with higher HOMA2-IR (geometric mean ratio (GMR)= 1.13 (95% CI: 1.03, 1.25)) and waist circumference (mean difference=3.66 (0.95, 6.38). MMA% was significantly associated with lower HOMA2-IR and waist circumference. After adjustment for OCM-related metabolites (SAM, SAH, cysteine, glutamate, lysophosphatidylcholine 18.2, and three phosphatidlycholines), associations were attenuated and no longer significant.

CONCLUSIONS

These preliminary results indicate that the association of lower MMA% and higher DMA% with diabetes-related outcomes may be influenced by OCM status, either through confounding, reverse causality, or mediation.

Altered Asparagine and Glutamate Homeostasis Precede Coronary Artery Disease and Type 2 Diabetes

CONTEXT

Type 2 diabetes mellitus (T2DM) is accompanied by an increased risk for coronary artery disease (CAD), but the overlapping metabolic disturbances preceding both diseases are insufficiently described.

OBJECTIVE

We hypothesized that alterations in metabolism occur years before clinical manifestation of T2DM and CAD and that these alterations are reflected in the plasma metabolome. We thus aimed to identify plasma metabolites that predict future T2DM and CAD.

DESIGN

Through use of targeted liquid chromatography-mass spectrometry, 35 plasma metabolites (amino acid metabolites and acylcarnitines) were quantified in 1049 individuals without CAD and diabetes, drawn from a population sample of 5386 in the Malmö Preventive Project (mean age, 69.5 years; 31% women). The sample included 204 individuals who developed T2DM, 384 who developed CAD, and 496 who remained T2DM and CAD free during a mean follow-up of 6.1 years.

RESULTS

In total, 16 metabolites were significantly associated with risk for developing T2DM according to logistic regression models. Glutamate (OR, 1.96; P = 5.4e-12) was the most strongly associated metabolite, followed by increased levels of branched-chain amino acids. Incident CAD was predicted by three metabolites: glutamate (OR, 1.28; P = 6.6e-4), histidine (OR, 0.76; P = 5.1e-4), and asparagine (OR, 0.80; P = 2.2e-3). Glutamate (OR, 1.48; P = 1.6e-8) and asparagine (OR, 0.75; P = 1.8e-5) were both associated with a composite endpoint of developing T2DM or CAD.

CONCLUSION

Several plasma metabolites were associated with incidence of T2DM and CAD; elevated glutamate and reduced asparagine levels were associated with both diseases. We thus discovered associations that might help shed additional light on why T2DM and CAD commonly co-occur.

Early metabolic markers identify potential targets for the prevention of type 2 diabetes

AIMS/HYPOTHESIS

The aims of this study were to evaluate systematically the predictive power of comprehensive metabolomics profiles in predicting the future risk of type 2 diabetes, and to identify a panel of the most predictive metabolic markers.

METHODS

We applied an unbiased systems medicine approach to mine metabolite combinations that provide added value in predicting the future incidence of type 2 diabetes beyond known risk factors. We performed mass spectrometry-based targeted, as well as global untargeted, metabolomics, measuring a total of 568 metabolites, in a Finnish cohort of 543 non-diabetic individuals from the Botnia Prospective Study, which included 146 individuals who progressed to type 2 diabetes by the end of a 10 year follow-up period. Multivariate logistic regression was used to assess statistical associations, and regularised least-squares modelling was used to perform machine learning-based risk classification and marker selection. The predictive performance of the machine learning models and marker panels was evaluated using repeated nested cross-validation, and replicated in an independent French cohort of 1044 individuals including 231 participants who progressed to type 2 diabetes during a 9 year follow-up period in the DESIR (Data from an Epidemiological Study on the Insulin Resistance Syndrome) study.

RESULTS

Nine metabolites were negatively associated (potentially protective) and 25 were positively associated with progression to type 2 diabetes. Machine learning models based on the entire metabolome predicted progression to type 2 diabetes (area under the receiver operating characteristic curve, AUC = 0.77) significantly better than the reference model based on clinical risk factors alone (AUC = 0.68; DeLong's p = 0.0009). The panel of metabolic markers selected by the machine learning-based feature selection also significantly improved the predictive performance over the reference model (AUC = 0.78; p = 0.00019; integrated discrimination improvement, IDI = 66.7%). This approach identified novel predictive biomarkers, such as α-tocopherol, bradykinin hydroxyproline, X-12063 and X-13435, which showed added value in predicting progression to type 2 diabetes when combined with known biomarkers such as glucose, mannose and α-hydroxybutyrate and routinely used clinical risk factors.

CONCLUSIONS/INTERPRETATION

This study provides a panel of novel metabolic markers for future efforts aimed at the prevention of type 2 diabetes.

Signals in the pancreatic islet microenvironment influence β-cell proliferation

The progressive loss of pancreatic β-cell mass that occurs in both type 1 and type 2 diabetes is a primary factor driving efforts to identify strategies for effectively increasing, enhancing or restoring β-cell mass. While factors that seem to influence β-cell proliferation in specific contexts have been described, reliable stimulation of human β-cell proliferation has remained a challenge. Importantly, β-cells exist in the context of a complex, integrated pancreatic islet microenvironment where they interact with other endocrine cells, vascular endothelial cells, extracellular matrix, neuronal projections and islet macrophages. This review highlights different components of the pancreatic microenvironment, and reviews what is known about how signaling that occurs between β-cells and these other components influences β-cell proliferation. Future efforts to further define the role of the pancreatic islet microenvironment on β-cell proliferation may lead to the development of successful approaches to increase or restore β-cell mass in diabetes.

An excessive increase in glutamate contributes to glucose-toxicity in β-cells via activation of pancreatic NMDA receptors in rodent diabetes

In the nervous system, excessive activation of NMDA receptors causes neuronal injury. Although activation of NMDARs has been proposed to contribute to the progress of diabetes, little is known about the effect of excessive long-term activation of NMDARs on β-cells, especially under the challenge of hyperglycemia. Here we thoroughly investigated whether endogenous glutamate aggravated β-cell dysfunction under chronic exposure to high-glucose via activation of NMDARs. The glutamate level was increased in plasma of diabetic mice or patients and in the supernatant of β-cell lines after treatment with high-glucose for 72 h. Decomposing the released glutamate improved GSIS of β-cells under chronic high-glucose exposure. Long-term treatment of β-cells with NMDA inhibited cell viability and decreased GSIS. These effects were eliminated by GluN1 knockout. The NMDAR antagonist MK-801 or GluN1 knockout prevented high-glucose-induced dysfunction in β-cells. MK-801 also decreased the expression of pro-inflammatory cytokines, and inhibited I-κB degradation, ROS generation and NLRP3 inflammasome expression in β-cells exposed to high-glucose. Furthermore, another NMDAR antagonist, Memantine, improved β-cells function in diabetic mice. Taken together, these findings indicate that an increase of glutamate may contribute to the development of diabetes through excessive activation of NMDARs in β-cells, accelerating β-cells dysfunction and apoptosis induced by hyperglycemia.

SVMRFE based approach for prediction of most discriminatory gene target for type II diabetes

Type II diabetes is a chronic condition that affects the way our body metabolizes sugar. The body's important source of fuel is now becoming a chronic disease all over the world. It is now very necessary to identify the new potential targets for the drugs which not only control the disease but also can treat it. Support vector machines are the classifier which has a potential to make a classification of the discriminatory genes and non-discriminatory genes. SVMRFE a modification of SVM ranks the genes based on their discriminatory power and eliminate the genes which are not involved in causing the disease. A gene regulatory network has been formed with the top ranked coding genes to identify their role in causing diabetes. To further validate the results pathway study was performed to identify the involvement of the coding genes in type II diabetes. The genes obtained from this study showed a significant involvement in causing the disease, which may be used as a potential drug target.

Objectively measured physical activity and plasma metabolomics in the Shanghai Physical Activity Study

BACKGROUND

Physical activity is associated with a variety of health benefits, but the biological mechanisms that explain these associations remain unclear. Metabolomics is a powerful tool to comprehensively evaluate global metabolic signature associated with physical activity and helps to pinpoint the pathways that mediate the health effects of physical activity. There has been limited research on metabolomics and habitual physical activity, and no metabolomics study has examined sedentary behaviour and physical activity of different intensities.

METHODS

In a group of Chinese adults (N = 277), we used an untargeted approach to examine 328 plasma metabolites in relation to accelerometer-measured physical activity, including overall volume of physical activity (physical activity energy expenditure (PAEE) and duration of physically active time) and sedentary time, and measures related to different intensities of physical activity (moderate-to-vigorous activity (MVPA), light activity, average physical activity intensity).

RESULTS

We identified 11 metabolites that were associated with total activity, with a false discovery rate of 0.2 or lower. Notably, we observed generally lower levels of amino acids in the valine, leucine and isoleucine metabolism pathway and of carbohydrates in sugar metabolism among participants with higher activity levels. Moreover, we found that PAEE, time spent in light activity and duration of physically active time were associated with a similar metabolic pattern, whereas the metabolic signature associated with sedentary time mirrored this pattern. In contrast, average activity intensity and time spent in MVPA appeared to be associated with somewhat different metabolic patterns.

CONCLUSIONS

Overall, the metabolomics patterns support a beneficial role of higher volume of physical activity in cardiometabolic health. Our findings identified candidate pathways and provide insight into the mechanisms underlying the health effects of physical activity.

Metabolomic biomarkers for personalised glucose lowering drugs treatment in type 2 diabetes

We aimed to identify metabolites to predict patients' response to glucose lowering treatment during the first 5 years after detection of type 2 diabetes. Metabolites were measured by GC-MS in baseline samples from 346 screen-detected type 2 diabetes patients in the ADDITION-NL study. The response to treatment with metformin and/or sulphonylurea (SU) was analysed to identify metabolites predictive of 5 year HbA1c change by multiple regression analysis. Baseline glucose and 1,5 anhydro-glucitol were associated with HbA_1c decrease in all medication groups. In patients on SU no other metabolite was associated with HbA1c decrease. A larger set of metabolites was associated with HbA1c change in the metformin and the combination therapy (metformin + SU) groups. These metabolites included metabolites related to liver metabolism, such as 2-hydroxybutanoic acid, 3-hydroxybutanoic acid, 2-hydroxypiperidine and 4-oxoproline). Metabolites involved in oxidative stress and insulin resistance were higher when the HbA1c decrease was larger in the metformin/sulphonylurea group. The associations between baseline metabolites and responsiveness to medication are in line with its mode of action. If these results could be replicated in other populations, the most promising predictive candidates might be tested to assess whether they could enhance personalised treatment.

Neurotransmitters and Neuropeptides: New Players in the Control of Islet of Langerhans' Cell Mass and Function

Islets of Langerhans control whole body glucose homeostasis, as they respond, releasing hormones, to changes in nutrient concentrations in the blood stream. The regulation of hormone secretion has been the focus of attention for a long time because it is related to many metabolic disorders, including diabetes mellitus. Endocrine cells of the islet use a sophisticate system of endocrine, paracrine and autocrine signals to synchronize their activities. These signals provide a fast and accurate control not only for hormone release but also for cell differentiation and survival, key aspects in islet physiology and pathology. Among the different categories of paracrine/autocrine signals, this review highlights the role of neurotransmitters and neuropeptides. In a manner similar to neurons, endocrine cells synthesize, accumulate, release neurotransmitters in the islet milieu, and possess receptors able to decode these signals. In this review, we provide a comprehensive description of neurotransmitter/neuropetide signaling pathways present within the islet. Then, we focus on evidence supporting the concept that neurotransmitters/neuropeptides and their receptors are interesting new targets to preserve β-cell function and mass. A greater understanding of how this network of signals works in physiological and pathological conditions would advance our knowledge of islet biology and physiology and uncover potentially new areas of pharmacological intervention. J. Cell. Physiol. 231: 756-767, 2016. © 2015 Wiley Periodicals, Inc.

Diabetes and retinal vascular dysfunction

Diabetes predominantly affects the microvascular circulation of the retina resulting in a range of structural changes unique to this tissue. These changes ultimately lead to altered permeability, hyperproliferation of endothelial cells and edema, and abnormal vascularization of the retina with resulting loss of vision. Enhanced production of inflammatory mediators and oxidative stress are primary insults with significant contribution to the pathogenesis of diabetic retinopathy (DR). We have determined the identity of the retinal vascular cells affected by hyperglycemia, and have delineated the cell autonomous impact of high glucose on function of these cells. We discuss some of the high glucose specific changes in retinal vascular cells and their contribution to retinal vascular dysfunction. This knowledge provides novel insight into the molecular and cellular defects contributing to the development and progression of diabetic retinopathy, and will aid in the development of innovative, as well as target specific therapeutic approaches for prevention and treatment of DR.

Finding needles in a haystack: application of network analysis and target enrichment studies for the identification of potential anti-diabetic phytochemicals

Diabetes mellitus is a debilitating metabolic disorder and remains a significant threat to public health. Herbal medicines have been proven to be effective anti-diabetic agents compared to synthetic drugs in terms of side effects. However, the complexity in their chemical constituents and mechanism of action, hinder the effort to discover novel anti-diabetic drugs. Hence, understanding the biological and chemical basis of pharmacological action of phytochemicals is essential for the discovery of potential anti-diabetic drugs. Identifying important active compounds, their protein targets and the pathways involved in diabetes would serve this purpose. In this context, the present study was aimed at exploring the mechanism of action of anti-diabetic plants phytochemicals through network and chemical-based approaches. This study also involves a focused and constructive strategy for preparing new effective anti-diabetic formulations. Further, a protocol for target enrichment was proposed, to identify novel protein targets for important active compounds. Therefore, the successive use of network analysis combined with target enrichment studies would accelerate the discovery of potential anti-diabetic phytochemicals.

Monosodium glutamate intake is inversely related to the risk of hyperglycemia

BACKGROUND & AIMS

In animal studies, monosodium glutamate (MSG) intake at a particular age has been found to increase the risk of insulin resistance and obesity. Inconsistent associations between MSG intake and overweight have been reported in humans. No population study has assessed the association between MSG intake and diabetes risk. This study aims to prospectively examine the association between MSG intake and hyperglycemia in a Chinese population.

METHODS

We followed 1056 healthy adults aged 20 years and older from 2002 to 2007. Dietary data were collected during home visits using a 3-day food record and a food frequency questionnaire. Fasting blood samples were collected at baseline and follow up. Hyperglycemia was defined as fasting plasma glucose >5.6 mmol/l.

RESULTS

During the follow-up we identified 125 cases of hyperglycemia. The highest quartile of MSG intake was associated with a lower risk of incident hyperglycemia, even after adjustment for a number of covariates, including dietary patterns. Comparing the highest with the lowest quartiles of MSG intake, the odds ratio (OR) for hyperglycemia was 0.30 (95% CI 0.13-0.66). There was a linear inverse association between MSG intake and change in blood glucose.

CONCLUSION

This cohort study suggests that high MSG intake is associated with a decreased risk of hyperglycemia in Chinese adults.

Effects of taurine supplementation on hepatic markers of inflammation and lipid metabolism in mothers and offspring in the setting of maternal obesity

Maternal obesity is associated with obesity and metabolic disorders in offspring. However, intervention strategies to reverse or ameliorate the effects of maternal obesity on offspring health are limited. Following maternal undernutrition, taurine supplementation can improve outcomes in offspring, possibly via effects on glucose homeostasis and insulin secretion. The effects of taurine in mediating inflammatory processes as a protective mechanism has not been investigated. Further, the efficacy of taurine supplementation in the setting of maternal obesity is not known. Using a model of maternal obesity, we examined the effects of maternal taurine supplementation on outcomes related to inflammation and lipid metabolism in mothers and neonates. Time-mated Wistar rats were randomised to either: 1) control : control diet during pregnancy and lactation (CON); 2) CON supplemented with 1.5% taurine in drinking water (CT); 3) maternal obesogenic diet (high fat, high fructose) during pregnancy and lactation (MO); or 4) MO supplemented with taurine (MOT). Maternal and neonatal weights, plasma cytokines and hepatic gene expression were analysed. A MO diet resulted in maternal hyperinsulinemia and hyperleptinemia and increased plasma glucose, glutamate and TNF-α concentrations. Taurine normalised maternal plasma TNF-α and glutamate concentrations in MOT animals. Both MO and MOT mothers displayed evidence of fatty liver accompanied by alterations in key markers of hepatic lipid metabolism. MO neonates displayed a pro-inflammatory hepatic profile which was partially rescued in MOT offspring. Conversely, a pro-inflammatory phenotype was observed in MOT mothers suggesting a possible maternal trade-off to protect the neonate. Despite protective effects of taurine in MOT offspring, neonatal mortality was increased in CT neonates, indicating possible adverse effects of taurine in the setting of normal pregnancy. These data suggest that maternal taurine supplementation may ameliorate the adverse effects observed in offspring following a maternal obesogenic diet but these effects are dependent upon prior maternal nutritional background.

Pathophysiology and treatment of diabetic retinopathy

In the past years, the management of diabetic retinopathy (DR) relied primarily on a good systemic control of diabetes mellitus, and as soon as the severity of the vascular lesions required further treatment, laser photocoagulation or vitreoretinal surgery was done to the patient. Currently, even if the intensive metabolic control is still mandatory, a variety of different clinical strategies could be offered to the patient. The recent advances in understanding the complex pathophysiology of DR allowed the physician to identify many cell types involved in the pathogenesis of DR and thus to develop new treatment approaches. Vasoactive and proinflammatory molecules, such as vascular endothelial growth factor (VEGF), play a key role in this multifactorial disease. Current properly designed trials, evaluating agents targeting VEGF or other mediators, showed benefits in the management of DR, especially when metabolic control is lacking. Other agents, directing to the processes of vasopermeability and angiogenesis, are under investigations, giving more hope in the future management of this still sight-threatening disease.