Search

Brown adipose tissue (BAT) is best known for thermogenesis. Rodent studies demonstrated that enhanced BAT thermogenesis is tightly associated with increased energy expenditure, reduced body weight, and improved glucose homeostasis. However, human BAT is protective against type 2 diabetes, independent of body weight. The mechanism underlying this dissociation remains unclear. Here, we report that impaired mitochondrial catabolism of branched-chain amino acids (BCAAs) in BAT, by deleting mitochondrial BCAA carriers (MBCs), caused systemic insulin resistance without affecting energy expenditure and body weight. Brown adipocytes catabolized BCAA in the mitochondria as nitrogen donors for the biosynthesis of non-essential amino acids and glutathione. Impaired mitochondrial BCAA-nitrogen flux in BAT resulted in increased oxidative stress, decreased hepatic insulin signaling, and decreased circulating BCAA-derived metabolites. A high-fat diet attenuated BCAA-nitrogen flux and metabolite synthesis in BAT, whereas cold-activated BAT enhanced the synthesis. This work uncovers a metabolite-mediated pathway through which BAT controls metabolic health beyond thermogenesis., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

High-throughput proteomics allows researchers to simultaneously explore the roles of thousands of biomarkers in the pathophysiology of diabetes. We conducted proteomic association studies of incident type 2 diabetes and physiologic responses to an intravenous glucose tolerance test (IVGTT) to identify novel protein contributors to glucose homeostasis and diabetes risk. We tested 4,776 SomaScan proteins measured in relation to 18-year incident diabetes risk in participants from the Cardiovascular Health Study (N = 2,631) and IVGTT-derived measures in participants from the HERITAGE Family Study (N = 752). We characterize 51 proteins that were associated with longitudinal diabetes risk, using their respective 39, 9, and 8 concurrent associations with insulin sensitivity index (SI), acute insulin response to glucose (AIRG), and glucose effectiveness (SG). Twelve of the 51 diabetes associations appear to be novel, including β-glucuronidase, which was associated with increased diabetes risk and lower SG, suggesting an alternative pathway to insulin for glucose disposal; and plexin-B2, which also was associated with increased diabetes risk, but with lower AIRG, and not with SI, indicating a mechanism related instead to pancreatic dysfunction. Other novel protein associations included alcohol dehydrogenase-1C, fructose-bisphosphate aldolase-B, sorbitol dehydrogenase with elevated type 2 diabetes risk, and a leucine-rich repeat containing protein-15 and myocilin with decreased risk., Article Highlights: Plasma proteins are associated with the risk of incident diabetes in older adults independent of various demographic, lifestyle, and biochemical risk factors. These same proteins are associated with subtle differences in measures of glucose homeostasis earlier in life. Proteins that are associated with lower insulin sensitivity in individuals without diabetes tend to be associated with appropriate compensatory mechanisms, such as a stronger acute insulin response or higher glucose effectiveness. Proteins that are associated with future diabetes risk, but not with insulin insensitivity, tend to be associated with lower glucose effectiveness and/or impaired acute insulin response., (© 2023 by the American Diabetes Association.)

Adipose tissue secretions are depot-specific and vary based on anatomical location. Considerable attention has been focused on visceral (VAT) and subcutaneous (SAT) adipose tissue with regard to metabolic disease, yet our knowledge of the secretome from these depots is incomplete. We conducted a comprehensive analysis of VAT and SAT secretomes in the context of metabolic function. Conditioned media generated using SAT and VAT explants from individuals with obesity were analyzed using proteomics, mass spectrometry, and multiplex assays. Conditioned media were administered in vitro to rat hepatocytes and myotubes to assess the functional impact of adipose tissue signaling on insulin responsiveness. VAT secreted more cytokines (IL-12p70, IL-13, TNF-α, IL-6, and IL-8), adipokines (matrix metalloproteinase-1, PAI-1), and prostanoids (TBX2, PGE2) compared with SAT. Secretome proteomics revealed differences in immune/inflammatory response and extracellular matrix components. In vitro, VAT-conditioned media decreased hepatocyte and myotube insulin sensitivity, hepatocyte glucose handling, and increased basal activation of inflammatory signaling in myotubes compared with SAT. Depot-specific differences in adipose tissue secretome composition alter paracrine and endocrine signaling. The unique secretome of VAT has distinct and negative impact on hepatocyte and muscle insulin action., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Despite good adherence to supervised endurance exercise training (EET), some individuals experience no or little improvement in peripheral insulin sensitivity. The genetic and molecular mechanisms underlying this phenomenon are currently not understood. By investigating genome-wide variants associated with baseline and exercise-induced changes (∆) in insulin sensitivity index (S i ) in healthy volunteers, we have identified novel candidate genes whose mouse knockouts phenotypes were consistent with a causative effect on S i . An integrative analysis of functional genomic and transcriptomic profiles suggests genetic variants have an aggregate effect on baseline S i and ∆S i , focused around cholinergic signalling, including downstream calcium and chemokine signalling. The identification of calcium regulated MEF2A transcription factor as the most statistically significant candidate driving the transcriptional signature associated to ∆S i further strengthens the relevance of calcium signalling in EET mediated S i response., (© 2021. The Author(s).)

Context: There is little information about fatty liver in prediabetes as it transitions to early diabetes., Objective: This study is aimed at evaluating the prevalence and determinants of fatty liver in the Diabetes Prevention Program (DPP)., Methods: We measured liver fat as liver attenuation (LA) in Hounsfield units (HU) in 1876 participants at ~14 years following randomization into the DPP, which tested the effects of lifestyle or metformin interventions versus standard care to prevent diabetes. LA was compared among intervention groups and in those with versus without diabetes, and associations with baseline and follow-up measurements of anthropometric and metabolic covariates were assessed., Results: There were no differences in liver fat between treatment groups at 14 years of follow-up. Participants with diabetes had lower LA (mean ± SD: 46 ± 16 vs 51 ± 14 HU; P < 0.001) and a greater prevalence of fatty liver (LA < 40 HU) (34% vs 17%; P < 0.001). Severity of metabolic abnormalities at the time of LA evaluation was associated with lower LA categories in a graded manner and more strongly in those with diabetes. Averaged annual fasting insulin (an index of insulin resistance [OR, 95% CI 1.76, 1.41-2.20]) waist circumference (1.63, 1.17-2.26), and triglyceride (1.42, 1.13-1.78), but not glucose, were independently associated with LA < 40 HU prevalence., Conclusion: Fatty liver is common in the early phases of diabetes development. The association of LA with insulin resistance, waist circumference, and triglyceride levels emphasizes the importance of these markers for hepatic steatosis in this population and that assessment of hepatic fat in early diabetes development is warranted., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Endocrine Society.)

G protein-coupled receptors (GPCRs) comprise the largest group of membrane receptors in eukaryotic genomes and collectively they regulate nearly all cellular processes. Despite the widely recognized importance of this class of proteins, many GPCRs remain understudied. G protein-coupled receptor 27 (Gpr27) is an orphan GPCR that displays high conservation during vertebrate evolution. Although, GPR27 is known to be expressed in tissues that regulate metabolism including the pancreas, skeletal muscle, and adipose tissue, its functions are poorly characterized. Therefore, to investigate the potential roles of Gpr27 in energy metabolism, we generated a whole body gpr27 knockout zebrafish line. Loss of gpr27 potentiated the elevation in glucose levels induced by pharmacological or nutritional perturbations. We next leveraged a mass spectrometry metabolite profiling platform to identify other potential metabolic functions of Gpr27. Notably, genetic deletion of gpr27 elevated medium-chain acylcarnitines, in particular C6-hexanoylcarnitine, C8-octanoylcarnitine, C9-nonanoylcarnitine, and C10-decanoylcarnitine, lipid species known to be associated with insulin resistance in humans. Concordantly, gpr27 deletion in zebrafish abrogated insulin-dependent Akt phosphorylation and glucose utilization. Finally, loss of gpr27 increased the expression of key enzymes in carnitine shuttle complex, in particular the homolog to the brain-specific isoform of CPT1C which functions as a hypothalamic energy senor. In summary, our findings shed light on the biochemical functions of Gpr27 by illuminating its role in lipid metabolism, insulin signaling, and glucose homeostasis., (© 2019 The Authors. The FASEB Journal published by Wiley Periodicals, Inc. on behalf of Federation of American Societies for Experimental Biology.)

Experimental studies have suggested possible protective effects of dimethylglycine (DMG) on glucose metabolism. DMG is degraded to glycine through a DMG-dehydrogenase (DMGDH)-catalyzed reaction, and this is the only known pathway for the breakdown of DMG in mammals. In this study, we aimed to identify the strongest genetic determinant of circulating DMG concentration and to investigate its associations with metabolic traits and incident diabetes. In the cohort with full metabolomics data (n = 709), low plasma levels of DMG were significantly associated with higher blood glucose levels (P = 3.9E(-4)). In the genome-wide association study (GWAS) of the discovery cohort (n = 5,205), the strongest genetic signal of plasma DMG was conferred by rs2431332 at the DMGDH locus, where the major allele was associated with lower DMG levels (P = 2.5E(-15)). The same genetic variant (major allele of rs2431332) was also significantly associated with higher plasma insulin (P = 0.019), increased HOMA insulin resistance (P = 0.019), and an increased risk of incident diabetes (P = 0.001) in the pooled analysis of the discovery cohort together with the two replication cohorts (n = 20,698 and n = 7,995). These data are consistent with a possible causal role of DMG deficiency in diabetes development and encourage future studies examining if inhibition of DMGDH, or alternatively, supplementation of DMG, might prove useful for the treatment/prevention of diabetes., (© 2015 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Insulin resistance (IR) is a complex trait with multiple genetic and environmental components. Confounded by large differences between the sexes, environment, and disease pathology, the genetic basis of IR has been difficult to dissect. Here we examine IR and related traits in a diverse population of more than 100 unique male and female inbred mouse strains after feeding a diet rich in fat and refined carbohydrates. Our results show dramatic variation in IR among strains of mice and widespread differences between sexes that are dependent on genotype. We uncover more than 15 genome-wide significant loci and validate a gene, Agpat5, associated with IR. We also integrate plasma metabolite levels and global gene expression from liver and adipose tissue to identify metabolite quantitative trait loci (mQTL) and expression QTL (eQTL), respectively. Our results provide a resource for analysis of interactions between diet, sex, and genetic background in IR., (Copyright © 2015 Elsevier Inc. All rights reserved.)

To identify distinct biological pathways of glucose metabolism, we conducted a systematic evaluation of biochemical changes after an oral glucose tolerance test (OGTT) in a community-based population. Metabolic profiling was performed on 377 nondiabetic Framingham Offspring cohort participants (mean age 57 years, 42% women, BMI 30 kg/m(2)) before and after OGTT. Changes in metabolite levels were evaluated with paired Student t tests, cluster-based analyses, and multivariable linear regression to examine differences associated with insulin resistance. Of 110 metabolites tested, 91 significantly changed with OGTT (P ≤ 0.0005 for all). Amino acids, β-hydroxybutyrate, and tricarboxylic acid cycle intermediates decreased after OGTT, and glycolysis products increased, consistent with physiological insulin actions. Other pathways affected by OGTT included decreases in serotonin derivatives, urea cycle metabolites, and B vitamins. We also observed an increase in conjugated, and a decrease in unconjugated, bile acids. Changes in β-hydroxybutyrate, isoleucine, lactate, and pyridoxate were blunted in those with insulin resistance. Our findings demonstrate changes in 91 metabolites representing distinct biological pathways that are perturbed in response to an OGTT. We also identify metabolite responses that distinguish individuals with and without insulin resistance. These findings suggest that unique metabolic phenotypes can be unmasked by OGTT in the prediabetic state.

Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.

Glucose ingestion after an overnight fast triggers an insulin-dependent, homeostatic program that is altered in diabetes. The full spectrum of biochemical changes associated with this transition is currently unknown. We have developed a mass spectrometry-based strategy to simultaneously measure 191 metabolites following glucose ingestion. In two groups of healthy individuals (n=22 and 25), 18 plasma metabolites changed reproducibly, including bile acids, urea cycle intermediates, and purine degradation products, none of which were previously linked to glucose homeostasis. The metabolite dynamics also revealed insulin's known actions along four key axes--proteolysis, lipolysis, ketogenesis, and glycolysis--reflecting a switch from catabolism to anabolism. In pre-diabetics (n=25), we observed a blunted response in all four axes that correlated with insulin resistance. Multivariate analysis revealed that declines in glycerol and leucine/isoleucine (markers of lipolysis and proteolysis, respectively) jointly provide the strongest predictor of insulin sensitivity. This observation indicates that some humans are selectively resistant to insulin's suppression of proteolysis, whereas others, to insulin's suppression of lipolysis. Our findings lay the groundwork for using metabolic profiling to define an individual's 'insulin response profile', which could have value in predicting diabetes, its complications, and in guiding therapy.

Objective: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi‐omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns. Methods: We performed machine learning‐based, integrative unsupervised clustering to identify proteomics‐ and metabolomics‐defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m2), leveraging data from 243 individuals in the Multi‐Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits. Results: We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high‐density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2. Conclusions: Although the two identified clusters may represent progressive obesity‐related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage. [ABSTRACT FROM AUTHOR]

Context: There is little information about fatty liver in prediabetes as it transitions to early diabetes.Objective: This study is aimed at evaluating the prevalence and determinants of fatty liver in the Diabetes Prevention Program (DPP).Methods: We measured liver fat as liver attenuation (LA) in Hounsfield units (HU) in 1876 participants at ~14 years following randomization into the DPP, which tested the effects of lifestyle or metformin interventions versus standard care to prevent diabetes. LA was compared among intervention groups and in those with versus without diabetes, and associations with baseline and follow-up measurements of anthropometric and metabolic covariates were assessed.Results: There were no differences in liver fat between treatment groups at 14 years of follow-up. Participants with diabetes had lower LA (mean ± SD: 46 ± 16 vs 51 ± 14 HU; P < 0.001) and a greater prevalence of fatty liver (LA < 40 HU) (34% vs 17%; P < 0.001). Severity of metabolic abnormalities at the time of LA evaluation was associated with lower LA categories in a graded manner and more strongly in those with diabetes. Averaged annual fasting insulin (an index of insulin resistance [OR, 95% CI 1.76, 1.41-2.20]) waist circumference (1.63, 1.17-2.26), and triglyceride (1.42, 1.13-1.78), but not glucose, were independently associated with LA < 40 HU prevalence.Conclusion: Fatty liver is common in the early phases of diabetes development. The association of LA with insulin resistance, waist circumference, and triglyceride levels emphasizes the importance of these markers for hepatic steatosis in this population and that assessment of hepatic fat in early diabetes development is warranted. [ABSTRACT FROM AUTHOR]

Obesity is an epidemic internationally. While weight loss interventions are efficacious, they are compounded by heterogeneity with regards to clinically relevant metabolic responses. Thus, we sought to identify metabolic biomarkers that are associated with beneficial metabolic changes to weight loss and which distinguish individuals with obesity who would most benefit from a given type of intervention. Liquid chromatography mass spectrometry-based profiling was used to measure 765 metabolites in baseline plasma from three different weight loss studies: WLM (behavioral intervention, N = 443), STRRIDE-PD (exercise intervention, N = 163), and CBD (surgical cohort, N = 125). The primary outcome was percent change in insulin resistance (as measured by the Homeostatic Model Assessment of Insulin Resistance [%ΔHOMA-IR]) over the intervention. Overall, 92 individual metabolites were associated with %ΔHOMA-IR after adjustment for multiple comparisons. Concordantly, the most significant metabolites were triacylglycerols (TAGs; p = 2.3e-5) and diacylglycerols (DAGs; p = 1.6e-4), with higher baseline TAG and DAG levels associated with a greater improvement in insulin resistance with weight loss. In tests of heterogeneity, 50 metabolites changed differently between weight loss interventions; we found amino acids, peptides, and their analogues to be most significant (4.7e-3) in this category. Our results highlight novel metabolic pathways associated with heterogeneity in response to weight loss interventions, and related biomarkers which could be used in future studies of personalized approaches to weight loss interventions. [ABSTRACT FROM AUTHOR]

Identifying markers of human insulin resistance may permit development of new approaches for treatment and prevention of type 2 diabetes. To this end, we analyzed the fasting plasma metabolome in metabolically characterized human volunteers across a spectrum of insulin resistance. We demonstrate that plasma betaine levels are reduced in insulin-resistant humans and correlate closely with insulin sensitivity. Moreover, betaine administration to mice with diet-induced obesity prevents the development of impaired glucose homeostasis, reduces hepatic lipid accumulation, increases white adipose oxidative capacity, and enhances whole-body energy expenditure. In parallel with these beneficial metabolic effects, betaine supplementation robustly increased hepatic and circulating fibroblast growth factor (Fgf)21 levels. Betaine administration failed to improve glucose homeostasis and liver fat content in Fgf21(-/-) mice, demonstrating that Fgf21 is necessary for betaine's beneficial effects. Together, these data indicate that dietary betaine increases Fgf21 levels to improve metabolic health in mice and suggest that betaine supplementation merits further investigation as a supplement for treatment or prevention of type 2 diabetes in humans. [ABSTRACT FROM AUTHOR]

Background: Although obesity and cardiometabolic traits commonly overlap, underlying pathways remain incompletely defined. The association of metabolite profiles across multiple cardiometabolic traits may lend insights into the interaction of obesity and metabolic health. We sought to investigate metabolic signatures of obesity and related cardiometabolic traits in the community using broad-based metabolomic profiling. Methods and Results: We evaluated the association of 217 assayed metabolites and cross-sectional as well as longitudinal changes in cardiometabolic traits among 2,383 Framingham Offspring cohort participants. Body mass index (BMI) was associated with 69 of 217 metabolites (P<0.00023 for all), including aromatic (tyrosine, phenylalanine) and branched chain amino acids (valine, isoleucine, leucine). Additional metabolic pathways associated with BMI included the citric acid cycle (isocitrate, alpha-ketoglutarate, aconitate), the tryptophan pathway (kynurenine, kynurenic acid), and the urea cycle. There was considerable overlap in metabolite profiles between BMI, abdominal adiposity, insulin resistance [IR] and dyslipidemia, modest overlap of metabolite profiles between BMI and hyperglycemia, and little overlap with fasting glucose or elevated blood pressure. Metabolite profiles were associated with longitudinal changes in fasting glucose, but the involved metabolites (ornithine, 5-HIAA, aminoadipic acid, isoleucine, cotinine) were distinct from those associated with baseline glucose or other traits. Obesity status appeared to “modify” the association of 9 metabolites with IR. For example, bile acid metabolites were strongly associated with IR among obese but not lean individuals, whereas isoleucine had a stronger association with IR in lean individuals. Conclusions: In this large-scale metabolite profiling study, body mass index was associated with a broad range of metabolic alterations. Metabolite profiling highlighted considerable overlap with abdominal adiposity, insulin resistance, and dyslipidemia, but not with fasting glucose or blood pressure traits. [ABSTRACT FROM AUTHOR]

To identify distinct biological pathways of glucose metabolism, we conducted a systematic evaluation of biochemical changes after an oral glucose tolerance test (OGTT in a community-based population. Metabolic profiling was performed on 377 nondiabetic Framingham Offspring cohort participants (mean age 57 years, 42%5 women BMI 30 kg/m² before and after OGTT. Changes in metabolite levels were evaluated with paired Student t tests, cluster-based analyses, and multivariable linear regression to examine differences associated with insulin resistance. Of 110 metabolites tested, 91 significantly changed with OGTT (P ≤ 0.0005 for all). Amino acid β-bydroxybutyrate, and tricarboxylic acid cycle intermediates de creased after OGTT, and glycolysis products increased, consistent with physiological insulin actions. Other pathways affected by OGTT included decreases in serotonin derivatives, urea cycle metabolites, and B vitamins. We also observed an increase in conjugated, and a decrease in unconjugated, bile acids. Changes in β-hydroxybutyrate, isoleucine, lactate, and pyridoxate were blunted in those with insulin resistance. Our findings demonstrate changes in 91 metabolites representing distinct biological pathways that are perturbed in response to an OGTT. We also identify metabolite responses that distinguish individuals with and without insulin resistance. These findings suggest that unique metabolic phenotypes can be unmasked by OGTT in the prediabetic state. [ABSTRACT FROM AUTHOR]

The authors discuss a study by S. H. Shah and colleagues on the metabolomic signatures of cardiovascular diseases. Metabolic changes are cited as the most proximal reporters of the body's response to a disease process or drug therapy. Nuclear magnetic resonance and tandem mass spectrometry (MS/MS) are two core technologies used to perform metabolic profiling. The study by Shah and colleagues suggest that certain amino acids may be markers of insulin resistance. The study also highlights a metabolic signature that predicts future cardiovascular events.

The article presents a study that examines whether mild renal dysfunction is associated with an increase in a leukocyte subpopulation rich in monocytes. It shows that cystatin C levels were positively and plasma high-density lipoprotein cholesterol levels negatively associated with monocyte count at baseline. It indicates that a low high-density lipoprotein cholesterol, insulin resistane phenotype occurs in subjects with mild renal dysfunction.

Background--Although metabolic risk factors are known to cluster in individuals who are prone to developing diabetes mellitus and cardiovascular disease, the underlying biological mechanisms remain poorly understood. Methods and Results--To identify pathways associated with cardiometabolic risk, we used liquid chromatography/mass spectrometry to determine the plasma concentrations of 45 distinct metabolites and to examine their relation to cardiometabolic risk in the Framingham Heart Study (FHS; n=1015) and the Malmö Diet and Cancer Study (MDC; n=746). We then interrogated significant findings in experimental models of cardiovascular and metabolic disease. We observed that metabolic risk factors (obesity, insulin resistance, high blood pressure, and dyslipidemia) were associated with multiple metabolites, including branched-chain amino acids, other hydrophobic amino acids, tryptophan breakdown products, and nucleotide metabolites. We observed strong associations of insulin resistance traits with glutamine (standardized regression coefficients, -0.04 to -0.22 per 1-SD change in log-glutamine; PcO.OOl), glutamate (0.05 to 0.14; PcO.OOl), and the glutamine-toglutamate ratio (--0.05 to --0.20; P<0.001 ) in the discovery sample (FHS); similar associations were observed in the replication sample (MDC). High glutamine-to-glutamate ratio was associated with lower risk of incident diabetes mellitus in FHS (odds ratio, 0.79; adjusted P=0.03) but not in MDC. In experimental models, administration of glutamine in mice led to both increased glucose tolerance (,P=0.01) and decreased blood pressure (P<0.05). Conclusions--Biochemical profiling identified circulating metabolites not previously associated with metabolic traits. Experimentally interrogating one of these pathways demonstrated that excess glutamine relative to glutamate, resulting from exogenous administration, is associated with reduced metabolic risk in mice. [ABSTRACT FROM AUTHOR]

Background: Substantial heterogeneity exists in the individual response to physical activity, and identifying biomarkers that predict clinical responsiveness to exercise remains an unmet clinical need. We recently identified dimethylguanidino valeric acid (DMGV) as a novel circulating marker of hepatic fat and predictor of incident diabetes in healthy subjects in the community. Here we examined the relationship between DMGV and metabolic health changes after endurance exercise training (ET). Methods: We used targeted mass spectrometry to measure DMGV before and after ET in 441 Caucasian individuals (mean age = 36) free of cardiometabolic disease from the HERITAGE Family Study. Subjects performed supervised cycle ergometry sessions of increasing amount and intensity, such that they exercised at 75% VO2max, 50 min/session, 3x/week over the final 6 weeks of a 20-week program. Multivariate linear regression was performed to assess the relationship between DMGV and measures of body composition, insulin and glucose homeostasis, and lipids. Changes in plasma DMGV levels in response to ET were determined using paired t tests. Statistical significance was set at P < 0.05. Results: Baseline DMGV levels were positively associated with visceral fat, body fat percentage, VLDL-C and triglycerides, and inversely related to VO2max, insulin sensitivity, LDL and HDL size, and HDL-C (all P < 0.001, adjusting for age and sex). Median DMGV levels decreased after exercise training (-9.4%, P = 0.00018). Baseline DMGV levels were positively associated with changes in small HDL-particles and inversely associated with changes in medium and total HDL-particles, apolipoprotein A1 (Model 3, Figure 1), and insulin sensitivity (P < 0.05 adjusting for age, sex, and baseline trait, results not shown) after ET. Conclusions: DMGV is an early marker of cardiometabolic dysfunction that is associated with diminished responses in HDL traits and insulin sensitivity with regular exercise. [ABSTRACT FROM AUTHOR]