Relationships between circulating metabolic intermediates and insulin action in overweight to obese, inactive men and women

Association between protein signals and type 2 diabetes incidence

Understanding early determinants of type 2 diabetes is essential for refining disease prevention strategies. Proteomic technology may provide a useful approach to identify novel protein patterns potentially related to pathophysiological changes that lead up to diabetes. In this study, we sought to identify protein signals that are associated with diabetes incidence in a middle-aged population. Serum samples from 519 participants in a nested case-control selection (167 cases and 352 age-, sex- and BMI-matched normoglycemic control subjects, median follow-up 14.0 years) within the Whitehall-II cohort were analyzed by linear matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). Nine protein peaks were found to be associated with incident diabetes. Rate ratios for high peak intensity ranged between 0.4 (95% CI, 0.2-0.8) and 4.0 (95% CI, 1.7-9.2) and were robust to adjustment for main potential confounders, including obesity, lipids and C-reactive protein. The proteins associated with these peaks may reflect diabetes pathogenesis. Our study exemplifies the utility of an approach that combines proteomic and epidemiological data.

Topographical body fat distribution links to amino acid and lipid metabolism in healthy obese women [corrected]

Visceral adiposity is increasingly recognized as a key condition for the development of obesity related disorders, with the ratio between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) reported as the best correlate of cardiometabolic risk. In this study, using a cohort of 40 obese females (age: 25–45 y, BMI: 28–40 kg/m²) under healthy clinical conditions and monitored over a 2 weeks period we examined the relationships between different body composition parameters, estimates of visceral adiposity and blood/urine metabolic profiles. Metabonomics and lipidomics analysis of blood plasma and urine were employed in combination with in vivo quantitation of body composition and abdominal fat distribution using iDXA and computerized tomography. Of the various visceral fat estimates, VAT/SAT and VAT/total abdominal fat ratios exhibited significant associations with regio-specific body lean and fat composition. The integration of these visceral fat estimates with metabolic profiles of blood and urine described a distinct amino acid, diacyl and ether phospholipid phenotype in women with higher visceral fat. Metabolites important in predicting visceral fat adiposity as assessed by Random forest analysis highlighted 7 most robust markers, including tyrosine, glutamine, PC-O 44∶6, PC-O 44∶4, PC-O 42∶4, PC-O 40∶4, and PC-O 40∶3 lipid species. Unexpectedly, the visceral fat associated inflammatory profiles were shown to be highly influenced by inter-days and between-subject variations. Nevertheless, the visceral fat associated amino acid and lipid signature is proposed to be further validated for future patient stratification and cardiometabolic health diagnostics.

Bioengineering silicon quantum dot theranostics using a network analysis of metabolomic and proteomic data in cardiac ischemia

Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment.

Systems Epidemiology: A New Direction in Nutrition and Metabolic Disease Research

Systems epidemiology applied to the field of nutrition has potential to provide new insight into underlying mechanisms and ways to study the health effects of specific foods more comprehensively. Human intervention and population-based studies have identified i) common genetic factors associated with several nutrition-related traits and ii) dietary factors altering the expression of genes and levels of proteins and metabolites related to inflammation, lipid metabolism and/or gut microbial metabolism, results of high relevance to metabolic disease. System-level tools applied type 2 diabetes and related conditions have revealed new pathways that are potentially modified by diet and thus offer additional opportunities for nutritional investigations. Moving forward, harnessing the resources of existing large prospective studies within which biological samples have been archived and diet and lifestyle have been measured repeatedly within individual will enable systems-level data to be integrated, the outcome of which will be improved personalized optimal nutrition for prevention and treatment of disease.

Associations between metabolomic compounds and incident heart failure among African Americans: the ARIC Study

Heart failure is more prevalent among African Americans than in the general population. Metabolomic studies among African Americans may efficiently identify novel biomarkers of heart failure. We used untargeted methods to measure 204 stable serum metabolites and evaluated their associations with incident heart failure hospitalization (n = 276) after a median follow-up of 20 years (1987-2008) by using Cox regression in data from 1,744 African Americans aged 45-64 years without heart failure at baseline from the Jackson, Mississippi, field center of the Atherosclerosis Risk in Communities (ARIC) Study. After adjustment for established risk factors, we found that 16 metabolites (6 named with known structural identities and 10 unnamed with unknown structural identities, the latter denoted by using the format X-12345) were associated with incident heart failure (P < 0.0004 based on a modified Bonferroni procedure). Of the 6 named metabolites, 4 are involved in amino acid metabolism, 1 (prolylhydroxyproline) is a dipeptide, and 1 (erythritol) is a sugar alcohol. After additional adjustment for kidney function, 2 metabolites remained associated with incident heart failure (for metabolite X-11308, hazard ratio = 0.75, 95% confidence interval: 0.65, 0.86; for metabolite X-11787, hazard ratio = 1.23, 95% confidence interval: 1.10, 1.37). Further structural analysis revealed X-11308 to be a dihydroxy docosatrienoic acid and X-11787 to be an isoform of either hydroxyleucine or hydroxyisoleucine. Our metabolomic analysis revealed novel biomarkers associated with incident heart failure independent of traditional risk factors.

Clinical metabolomics paves the way towards future healthcare strategies

Metabolomics is recognized as a powerful top-down system biological approach to understand genetic-environment-health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation.

Metabolite profiles during oral glucose challenge

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.

Measuring the exposome: a powerful basis for evaluating environmental exposures and cancer risk

Advances in laboratory sciences offer much in the challenge to unravel the complex etiology of cancer and to therefore provide an evidence-base for prevention. One area where improved measurements are particularly important to epidemiology is exposure assessment; this requirement has been highlighted through the concept of the exposome. In addition, the ability to observe genetic and epigenetic alterations in individuals exposed to putative risk factors also affords an opportunity to elucidate underlying mechanisms of carcinogenesis, which in turn may allow earlier detection and more refined molecular classification of disease. In this context the application of omics technologies to large population-based studies and their associated biobanks raise exciting new avenues of research. This review considers the areas of genomics, transcriptomics, epigenomics and metabolomics and the evidence to date that people exposed to well-defined factors (for example, tobacco, diet, occupational exposures, environmental pollutants) have specific omics profiles. Although in their early stages of development these approaches show promising evidence of distinct exposure-derived biological effects and indicate molecular pathways that may be particularly relevant to the carcinogenic process subsequent to environmental and lifestyle exposures. Such an interdisciplinary approach is vital if the full benefits of advances in laboratory sciences and investments in large-scale prospective cohort studies are to be realized in relation to cancer prevention.

Circulating lysophosphatidylcholines are markers of a metabolically benign nonalcoholic fatty liver

OBJECTIVE

Nonalcoholic fatty liver (NAFL) is thought to contribute to insulin resistance and its metabolic complications. However, some individuals with NAFL remain insulin sensitive. Mechanisms involved in the susceptibility to develop insulin resistance in humans with NAFL are largely unknown. We investigated circulating markers and mechanisms of a metabolically benign and malignant NAFL by applying a metabolomic approach.

RESEARCH DESIGN AND METHODS

A total of 265 metabolites were analyzed before and after a 9-month lifestyle intervention in plasma from 20 insulin-sensitive and 20 insulin-resistant subjects with NAFL. The relevant plasma metabolites were then tested for relationships with insulin sensitivity in 17 subjects without NAFL and in plasma from 29 subjects with liver tissue samples.

RESULTS

The best separation of the insulin-sensitive from the insulin-resistant NAFL group was achieved by a metabolite pattern including the branched-chain amino acids leucine and isoleucine, ornithine, the acylcarnitines C3:0-, C16:0-, and C18:0-carnitine, and lysophosphatidylcholine (lyso-PC) C16:0 (area under the ROC curve, 0.77 [P = 0.00023] at baseline and 0.80 [P = 0.000019] at follow-up). Among the individual metabolites, predominantly higher levels of lyso-PC C16:0, both at baseline (P = 0.0039) and at follow-up (P = 0.001), were found in the insulin-sensitive compared with the insulin-resistant subjects. In the non-NAFL groups, no differences in lyso-PC C16:0 levels were found between the insulin-sensitive and insulin-resistant subjects, and these relationships were replicated in plasma from subjects with liver tissue samples.

CONCLUSIONS

From a plasma metabolomic pattern, particularly lyso-PCs are able to separate metabolically benign from malignant NAFL in humans and may highlight important pathways in the pathogenesis of fatty liver-induced insulin resistance.

Branched chain amino acids are novel biomarkers for discrimination of metabolic wellness

OBJECTIVE

To identify novel biomarkers through metabolomic profiles that distinguish metabolically well (MW) from metabolically unwell (MUW) individuals, independent of body mass index (BMI).

MATERIALS/METHODS

This study was conducted as part of the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) project. Individuals from 3 cohorts were classified as lean (BMI<25kg/m²), overweight (BMI≥25kg/m², BMI<30kg/m²) or obese (BMI≥30kg/m²). Cardiometabolic abnormalities were defined as: (1) impaired fasting glucose (≥100mg/dL and ≤126mg/dL); (2) hypertension; (3) triglycerides ≥150mg/dL; (4) HDL-C <40mg/dL in men, <50mg/dL in women; and (5) insulin resistance (calculated Homeostatic Model Assessment (HOMA-IR) index of >5.13). MW individuals were defined as having <2 cardiometabolic abnormalities and MUW individuals had≥two cardiometabolic abnormalities. Targeted profiling of 55 metabolites used mass-spectroscopy-based methods. Principal components analysis (PCA) was used to reduce the large number of correlated metabolites into clusters of fewer uncorrelated factors.

RESULTS

Of 1872 individuals, 410 were lean, 610 were overweight, and 852 were obese. Of lean individuals, 67% were categorized as MUW, whereas 80% of overweight and 87% of obese individuals were MUW. PCA-derived factors with levels that differed the most between MW and MUW groups were factors 4 (branched chain amino acids [BCAA]) [p<.0001], 8 (various metabolites) [p<.0001], 9 (C4/Ci4, C3, C5 acylcarnitines) [p<.0001] and 10 (amino acids) [p<.0002]. Further, Factor 4, distinguishes MW from MUW individuals independent of BMI.

CONCLUSION

BCAA and related metabolites are promising biomarkers that may aid in understanding cardiometabolic health independent of BMI category.

Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.

Regulation of adipose branched-chain amino acid catabolism enzyme expression and cross-adipose amino acid flux in human obesity

Elevated blood branched-chain amino acids (BCAA) are often associated with insulin resistance and type 2 diabetes, which might result from a reduced cellular utilization and/or incomplete BCAA oxidation. White adipose tissue (WAT) has become appreciated as a potential player in whole body BCAA metabolism. We tested if expression of the mitochondrial BCAA oxidation checkpoint, branched-chain α-ketoacid dehydrogenase (BCKD) complex, is reduced in obese WAT and regulated by metabolic signals. WAT BCKD protein (E1α subunit) was significantly reduced by 35-50% in various obesity models (fa/fa rats, db/db mice, diet-induced obese mice), and BCKD component transcripts significantly lower in subcutaneous (SC) adipocytes from obese vs. lean Pima Indians. Treatment of 3T3-L1 adipocytes or mice with peroxisome proliferator-activated receptor-γ agonists increased WAT BCAA catabolism enzyme mRNAs, whereas the nonmetabolizable glucose analog 2-deoxy-d-glucose had the opposite effect. The results support the hypothesis that suboptimal insulin action and/or perturbed metabolic signals in WAT, as would be seen with insulin resistance/type 2 diabetes, could impair WAT BCAA utilization. However, cross-tissue flux studies comparing lean vs. insulin-sensitive or insulin-resistant obese subjects revealed an unexpected negligible uptake of BCAA from human abdominal SC WAT. This suggests that SC WAT may not be an important contributor to blood BCAA phenotypes associated with insulin resistance in the overnight-fasted state. mRNA abundances for BCAA catabolic enzymes were markedly reduced in omental (but not SC) WAT of obese persons with metabolic syndrome compared with weight-matched healthy obese subjects, raising the possibility that visceral WAT contributes to the BCAA metabolic phenotype of metabolically compromised individuals.

Application of combined omics platforms to accelerate biomedical discovery in diabesity

Diabesity has become a popular term to describe the specific form of diabetes that develops late in life and is associated with obesity. While there is a correlation between diabetes and obesity, the association is not universally predictive. Defining the metabolic characteristics of obesity that lead to diabetes, and how obese individuals who develop diabetes different from those who do not, are important goals. The use of large-scale omics analyses (e.g., metabolomic, proteomic, transcriptomic, and lipidomic) of diabetes and obesity may help to identify new targets to treat these conditions. This report discusses how various types of omics data can be integrated to shed light on the changes in metabolism that occur in obesity and diabetes.

Early metabolic markers of the development of dysglycemia and type 2 diabetes and their physiological significance

Metabolomic screening of fasting plasma from nondiabetic subjects identified α-hydroxybutyrate (α-HB) and linoleoyl-glycerophosphocholine (L-GPC) as joint markers of insulin resistance (IR) and glucose intolerance. To test the predictivity of α-HB and L-GPC for incident dysglycemia, α-HB and L-GPC measurements were obtained in two observational cohorts, comprising 1,261 nondiabetic participants from the Relationship between Insulin Sensitivity and Cardiovascular Disease (RISC) study and 2,580 from the Botnia Prospective Study, with 3-year and 9.5-year follow-up data, respectively. In both cohorts, α-HB was a positive correlate and L-GPC a negative correlate of insulin sensitivity, with α-HB reciprocally related to indices of β-cell function derived from the oral glucose tolerance test (OGTT). In follow-up, α-HB was a positive predictor (adjusted odds ratios 1.25 [95% CI 1.00-1.60] and 1.26 [1.07-1.48], respectively, for each standard deviation of predictor), and L-GPC was a negative predictor (0.64 [0.48-0.85] and 0.67 [0.54-0.84]) of dysglycemia (RISC) or type 2 diabetes (Botnia), independent of familial diabetes, sex, age, BMI, and fasting glucose. Corresponding areas under the receiver operating characteristic curve were 0.791 (RISC) and 0.783 (Botnia), similar in accuracy when substituting α-HB and L-GPC with 2-h OGTT glucose concentrations. When their activity was examined, α-HB inhibited and L-GPC stimulated glucose-induced insulin release in INS-1e cells. α-HB and L-GPC are independent predictors of worsening glucose tolerance, physiologically consistent with a joint signature of IR and β-cell dysfunction.

Leucine and protein metabolism in obese Zucker rats

Branched-chain amino acids (BCAAs) are circulating nutrient signals for protein accretion, however, they increase in obesity and elevations appear to be prognostic of diabetes. To understand the mechanisms whereby obesity affects BCAAs and protein metabolism, we employed metabolomics and measured rates of [1-¹⁴C]-leucine metabolism, tissue-specific protein synthesis and branched-chain keto-acid (BCKA) dehydrogenase complex (BCKDC) activities. Male obese Zucker rats (11-weeks old) had increased body weight (BW, 53%), liver (107%) and fat (∼300%), but lower plantaris and gastrocnemius masses (−21–24%). Plasma BCAAs and BCKAs were elevated 45–69% and ∼100%, respectively, in obese rats. Processes facilitating these rises appeared to include increased dietary intake (23%), leucine (Leu) turnover and proteolysis [35% per g fat free mass (FFM), urinary markers of proteolysis: 3-methylhistidine (183%) and 4-hydroxyproline (766%)] and decreased BCKDC per g kidney, heart, gastrocnemius and liver (−47–66%). A process disposing of circulating BCAAs, protein synthesis, was increased 23–29% by obesity in whole-body (FFM corrected), gastrocnemius and liver. Despite the observed decreases in BCKDC activities per gm tissue, rates of whole-body Leu oxidation in obese rats were 22% and 59% higher normalized to BW and FFM, respectively. Consistently, urinary concentrations of eight BCAA catabolism-derived acylcarnitines were also elevated. The unexpected increase in BCAA oxidation may be due to a substrate effect in liver. Supporting this idea, BCKAs were elevated more in liver (193–418%) than plasma or muscle, and per g losses of hepatic BCKDC activities were completely offset by increased liver mass, in contrast to other tissues. In summary, our results indicate that plasma BCKAs may represent a more sensitive metabolic signature for obesity than BCAAs. Processes supporting elevated BCAA]BCKAs in the obese Zucker rat include increased dietary intake, Leu and protein turnover along with impaired BCKDC activity. Elevated BCAAs/BCKAs may contribute to observed elevations in protein synthesis and BCAA oxidation.

The relationship between aerobic fitness level and metabolic profiles in healthy adults

SCOPE

Application of metabolomics to nutrition and health research is increasing and while much effort has been invested in understanding factors that influence the metabolomic profile there is relatively little known about the impact of fitness level. This study aimed to examine the relationship between fitness level, substrate oxidation rates, and the metabolic profile.

METHODS AND RESULTS

Two hundred and fourteen healthy adults (18-60 years) were recruited and 65 subjects were selected based on their estimated maximal oxygen consumption levels. Metabolomic analysis was performed. The subjects were split into fitness groups according to their maximal oxygen consumption levels (mL/kg/min) and analysis revealed significant differences in normalized fat and carbohydrate oxidation levels between the groups. Urinary metabolomic analysis revealed significantly different profiles in the groups with 15 amino acids significantly higher in the low fitness groups. Effects of fitness level in the plasma metabolic profiles were also demonstrated.

CONCLUSION

This study demonstrates a relationship between fitness level and the amino acid profile. Moreover, the metabolite changes show that a reduced excretion of amino acids in adults is associated with increased fitness levels and an increased fat oxidation rate during exercise. Interestingly, higher levels of branched chain amino acids were associated with lower fitness levels and higher insulin resistance.

Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults

OBJECTIVE

Branched-chain and aromatic amino acids are associated with the risk for future type 2 diabetes; however, the underlying mechanisms remain elusive. We tested whether amino acids predict insulin resistance index in healthy young adults.

RESEARCH DESIGN AND METHODS

Circulating isoleucine, leucine, valine, phenylalanine, tyrosine, and six additional amino acids were quantified in 1,680 individuals from the population-based Cardiovascular Risk in Young Finns Study (baseline age 32 ± 5 years; 54% women). Insulin resistance was estimated by homeostasis model assessment (HOMA) at baseline and 6-year follow-up. Amino acid associations with HOMA of insulin resistance (HOMA-IR) and glucose were assessed using regression models adjusted for established risk factors. We further examined whether amino acid profiling could augment risk assessment of insulin resistance (defined as 6-year HOMA-IR >90th percentile) in early adulthood.

RESULTS

Isoleucine, leucine, valine, phenylalanine, and tyrosine were associated with HOMA-IR at baseline and for men at 6-year follow-up, while for women only leucine, valine, and phenylalanine predicted 6-year HOMA-IR (P < 0.05). None of the other amino acids were prospectively associated with HOMA-IR. The sum of branched-chain and aromatic amino acid concentrations was associated with 6-year insulin resistance for men (odds ratio 2.09 [95% CI 1.38-3.17]; P = 0.0005); however, including the amino acid score in prediction models did not improve risk discrimination.

CONCLUSIONS

Branched-chain and aromatic amino acids are markers of the development of insulin resistance in young, normoglycemic adults, with most pronounced associations for men. These findings suggest that the association of branched-chain and aromatic amino acids with the risk for future diabetes is at least partly mediated through insulin resistance.

Genetic determinant for amino acid metabolites and changes in body weight and insulin resistance in response to weight-loss diets: the Preventing Overweight Using Novel Dietary Strategies (POUNDS LOST) trial

BACKGROUND

Circulating branched-chain amino acids and aromatic amino acids were recently related to insulin resistance and diabetes mellitus in prospective cohorts. We tested the effects of a genetic determinant of branched-chain amino acid/aromatic amino acid ratio on changes in body weight and insulin resistance in a 2-year diet intervention trial.

METHODS AND RESULTS

We genotyped the branched-chain amino acid/aromatic amino acid ratio-associated variant rs1440581 near the PPM1K gene in 734 overweight or obese adults who were assigned to 1 of 4 diets varying in macronutrient content. At 6 months, dietary fat significantly modified genetic effects on changes in weight, fasting insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) after adjustment for the confounders (all P for interaction ≤0.006). Further adjustment for weight change did not appreciably change the interactions for fasting insulin and HOMA-IR. In the high-fat diet group, the C allele was related to less weight loss and smaller decreases in serum insulin and HOMA-IR (all P ≤ 0.02 in an additive pattern), whereas an opposite genotype effect on changes in insulin and HOMA-IR was observed in the low-fat diet group (P=0.02 and P=0.04, respectively). At 2 years, the gene-diet interactions remained significant for weight loss (P=0.008) but became null for changes in serum insulin and HOMA-IR resulting from weight regain.

CONCLUSIONS

Individuals carrying the C allele of the branched-chain amino acid/aromatic amino acid ratio-associated variant rs1440581 may benefit less in weight loss and improvement of insulin sensitivity than those without this allele when undertaking an energy-restricted high-fat diet.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT00072995.

Branched-chain amino acids alter neurobehavioral function in rats

Recently, we have described a strong association of branched-chain amino acids (BCAA) and aromatic amino acids (AAA) with obesity and insulin resistance. In the current study, we have investigated the potential impact of BCAA on behavioral functions. We demonstrate that supplementation of either a high-sucrose or a high-fat diet with BCAA induces anxiety-like behavior in rats compared with control groups fed on unsupplemented diets. These behavioral changes are associated with a significant decrease in the concentration of tryptophan (Trp) in brain tissues and a consequent decrease in serotonin but no difference in indices of serotonin synaptic function. The anxiety-like behaviors and decreased levels of Trp in the brain of BCAA-fed rats were reversed by supplementation of Trp in the drinking water but not by administration of fluoxetine, a selective serotonin reuptake inhibitor, suggesting that the behavioral changes are independent of the serotonergic pathway of Trp metabolism. Instead, BCAA supplementation lowers the brain levels of another Trp-derived metabolite, kynurenic acid, and these levels are normalized by Trp supplementation. We conclude that supplementation of high-energy diets with BCAA causes neurobehavioral impairment. Since BCAA are elevated spontaneously in human obesity, our studies suggest a potential mechanism for explaining the strong association of obesity and mood disorders.

Insulin resistance and the metabolism of branched-chain amino acids

Insulin resistance (IR) is a key pathological feature of metabolic syndrome and subsequently causes serious health problems with an increased risk of several common metabolic disorders. IR related metabolic disturbance is not restricted to carbohydrates but impacts global metabolic network. Branched-chain amino acids (BCAAs), namely valine, leucine and isoleucine, are among the nine essential amino acids, accounting for 35% of the essential amino acids in muscle proteins and 40% of the preformed amino acids required by mammals. The BCAAs are particularly responsive to the inhibitory insulin action on amino acid release by skeletal muscle and their metabolism is profoundly altered in insulin resistant conditions and/or insulin deficiency. Although increased circulating BCAA concentration in insulin resistant conditions has been noted for many years and BCAAs have been reported to be involved in the regulation of glucose homeostasis and body weight, it is only recently that BCAAs are found to be closely associated with IR. This review will focus on the recent findings on BCAAs from both epidemic and mechanistic studies.

Metabolomics in human type 2 diabetes research

The high prevalence of diabetes and diabetic complications has caused a huge burden on the modern society. Although scientific advances have led to effective strategies for preventing and treating diabetes over the past several decades, little progress has been made toward curing the disease or even getting it under control, from a public health and overall societal standpoint. There is still a lack of reliable biomarkers indicative of metabolic alterations associated with diabetes and different drug responses, highlighting the need for the development of early diagnostic and prognostic markers for diabetes and diabetic complications. The emergence of metabolomics has allowed researchers to systemically measure the small molecule metabolites, which are sensitive to the changes of both environmental and genetic factors and therefore, could be regarded as the link between genotypes and phenotypes. During the last decade, the progression made in metabolomics has provided insightful information on disease development and disease onset prediction. Recent studies using metabolomics approach coupled with statistical tools to predict incident diabetes revealed a number of metabolites that are significantly altered, including branched-chain and aromatic amino acids, such as isoleucine, leucine, valine, tyrosine and phenylalanine, as diagnostic or highly-significant predictors of future diabetes. This review summarizes the current findings of metabolomic studies in human investigations with the most common form of diabetes, type 2 diabetes.

Personalized medicine in women's obesity prevention and treatment: implications for research, policy and practice

The prevalence of obesity in America has reached epidemic proportions, and obesity among women is particularly concerning. Severe obesity (body mass index ≥35 kg m(-2) ) is more prevalent in women than men. Further, women have sex-specific risk factors that must be considered when developing preventive and therapeutic interventions. This review presents personalized medicine as a dynamic approach to obesity prevention, management and treatment for women. First, we review obesity as a complex health issue, with contributing sex-specific, demographic, psychosocial, behavioural, environmental, epigenetic and genetic/genomic risk factors. Second, we present personalized medicine as a rapidly advancing field of health care that seeks to quantify these complex risk factors to develop more targeted and effective strategies that can improve disease management and/or better minimize an individual's likelihood of developing obesity. Third, we discuss how personalized medicine can be applied in a clinical setting with current and emerging tools, including health risk assessments, personalized health plans, and strategies for increasing patient engagement. Finally, we discuss the need for additional research, training and policy that can enhance the practice of personalized medicine in women's obesity, including further advancements in the '-omics' sciences, physician training in personalized medicine, and additional development and standardization of innovative targeted therapies and clinical tools.

Comparative analysis of sample preparation methods to handle the complexity of the blood fluid metabolome: when less is more

Blood sample preparation before LC-MS metabolomic fingerprinting is one of the most challenging and error-prone parts of the analytical procedure. Besides proteins, phospholipids contained in blood fluids are known to cause matrix effects and ion suppression phenomena, thus masking biological variation. Nevertheless, the commonly used sample preparation techniques do not consider their removal prior to analysis. Pooled plasma and serum samples were used as biological material, partly as raw samples and partly spiked with distinct concentrations of a metabolite mix (1-5 μg/mL). Prior to LC-ESI-qToF-MS-driven metabolomic analysis, samples were subjected to different preparation methods consisting of three extractions with organic solvents (acetonitrile, methanol, and methanol/ethanol), a membrane-based solvent-free technique, and a hybrid method combining solvent extraction and SPE-mediated removal of phospholipids. The comparative analysis among sample preparation procedures was based on the capacity to detect endogenous compounds in raw samples, differentiate raw versus spiked samples, and reveal real-life metabolomic changes, following a dietary intervention. Method speed, minimum sample handling, compatibility to automation, and applicability to large-scale metabolomic studies were also considered. The combination of solvent deproteinization and the selective removal of phospholipids was revealed to be the most suitable method, in terms of improvement of nonlipid metabolite coverage, extraction reproducibility, quickness, and compatibility with automation, the minimization of matrix effects being among the most probable causes for the good extraction performance associated with the removal of phospholipid species. The main advantage of conventional solvent extraction procedures was the metabolite information coverage for lipid low-molecular-weight species, and extraction with acetonitrile was generally the second choice for sample preparation. Ultrafiltration was the least effective method for plasma and serum preparation; thus, its use without a previous solvent extraction step of the samples should be discarded. According to the presented data, there is no apparent reason to believe that sacrificing information on lipid compounds is too high of a price to pay in order to gain more information on nonlipid LMW metabolites.

Carnitine and acylcarnitines: pharmacokinetic, pharmacological and clinical aspects

L-Carnitine (levocarnitine) is a naturally occurring compound found in all mammalian species. The most important biological function of L-carnitine is in the transport of fatty acids into the mitochondria for subsequent β-oxidation, a process which results in the esterification of L-carnitine to form acylcarnitine derivatives. As such, the endogenous carnitine pool is comprised of L-carnitine and various short-, medium- and long-chain acylcarnitines. The physiological importance of L-carnitine and its obligatory role in the mitochondrial metabolism of fatty acids has been clearly established; however, more recently, additional functions of the carnitine system have been described, including the removal of excess acyl groups from the body and the modulation of intracellular coenzyme A (CoA) homeostasis. In light of this, acylcarnitines cannot simply be considered by-products of the enzymatic carnitine transfer system, but provide indirect evidence of altered mitochondrial metabolism. Consequently, examination of the contribution of L-carnitine and acylcarnitines to the endogenous carnitine pool (i.e. carnitine pool composition) is critical in order to adequately characterize metabolic status. The concentrations of L-carnitine and its esters are maintained within relatively narrow limits for normal biological functioning in their pivotal roles in fatty acid oxidation and maintenance of free CoA availability. The homeostasis of carnitine is multifaceted with concentrations achieved and maintained by a combination of oral absorption, de novo biosynthesis, carrier-mediated distribution into tissues and extensive, but saturable, renal tubular reabsorption. Various disorders of carnitine insufficiency have been described but ultimately all result in impaired entry of fatty acids into the mitochondria and consequently disturbed lipid oxidation. Given the sensitivity of acylcarnitine concentrations and the relative carnitine pool composition in reflecting the intramitochondrial acyl-CoA to free CoA ratio (and, hence, any disturbances in mitochondrial metabolism), the relative contribution of L-carnitine and acylcarnitines within the total carnitine pool is therefore considered critical in the identification of mitochondria dysfunction. Although there is considerable research in the literature focused on disorders of carnitine insufficiency, relatively few have examined relative carnitine pool composition in these conditions; consequently, the complexity of these disorders may not be fully understood. Similarly, although important studies have been conducted establishing the pharmacokinetics of exogenous carnitine and short-chain carnitine esters in healthy volunteers, few studies have examined carnitine pharmacokinetics in patient groups. Furthermore, the impact of L-carnitine administration on the kinetics of acylcarnitines has not been established. Given the importance of L-carnitine as well as acylcarnitines in maintaining normal mitochondrial function, this review seeks to examine previous research associated with the homeostasis and pharmacokinetics of L-carnitine and its esters, and highlight potential areas of future research.

Metabolomics in diabetes research

Diabetes represents one of the most important global health problems because it is associated with a large economic burden on the health systems of many countries. Whereas the diagnosis and treatment of manifest diabetes have been well investigated, the identification of novel pathways or early biomarkers indicative of metabolic alterations or insulin resistance related to the development of diabetes is still in progress. Over half of the type 2 diabetes patients show manifestations of diabetes-related diseases, which highlight the need for early screening markers of diabetes. During the last decade, the rapidly growing research field of metabolomics has introduced new insights into the pathology of diabetes as well as methods to predict disease onset and has revealed new biomarkers. Recent epidemiological studies first used metabolism to predict incident diabetes and revealed branched-chain and aromatic amino acids including isoleucine, leucine, valine, tyrosine and phenylalanine as highly significant predictors of future diabetes. This review summarises the current findings of metabolic research regarding diabetes in animal models and human investigations.

Analysis of serum metabolic profiles in women with endometrial cancer and controls in a population-based case-control study

CONTEXT

Endometrial cancer is associated with metabolic disturbances related to its underlying risk factors, including obesity and diabetes. Identifying metabolite biomarkers associated with endometrial cancer may have value for early detection, risk assessment, and understanding etiology.

OBJECTIVE

The objective of the study was to evaluate the reliable measurement of metabolites in epidemiological studies with nonstandardized blood collection; confirm previously reported correlations of metabolites with body size; and assess differences in metabolite levels between cases and controls.

DESIGN

This was the Polish Endometrial Cancer Study (2001-2003).

SETTING

This study was a population-based case-control study.

PATIENTS

Patients included 250 cases and 250 controls.

INTERVENTION

The intervention included the measurement of serum metabolite levels of 15 amino acids, 45 acylcarnitines, and nine fatty acids.

MAIN OUTCOME MEASURE

The main outcome measure was endometrial cancer.

RESULTS

Body mass index was correlated with levels of valine (r = 0.26, P = 3.4 × 10(-5)), octenoylcarnitine (r = 0.24, P = 1.5 × 10(-4)), palmitic acid (r = 0.26, P = 4.4 × 10(-5)), oleic acid (r = 0.28, P = 9.9 × 10(-6)), and stearic acid (r = 0.26, P = 2.9 × 10(-5)) among controls. Only stearic acid was inversely associated with endometrial cancer case status (quartile 4 vs. quartile 1: odds ratio 0.37, 95% confidence interval 0.20-0.69, P for trend = 1.2 × 10(-4)). Levels of the C5-acylcarnitines, octenoylcarnitine, decatrienoylcarnitine, and linoleic acid were significantly lower in cases than controls (odds ratios ranged from 0.21 to 0.38).

CONCLUSIONS

These data demonstrate that previously reported variations in metabolomic profiles with body mass index can be replicated in population-based studies with nonfasting blood collection protocols. We also provide preliminary evidence that large differences in metabolite levels exist between cases and controls, independent of body habitus. Our findings warrant assessment of metabolic profiles, including the candidate markers identified herein, in prospectively collected blood samples to define biomarkers and etiological factors related to endometrial cancer.

The relationship between BMI and metabolomic profiles: a focus on amino acids

The role of metabolomics in the field of nutrition is continuing to grow and it has the potential to assist in the understanding of metabolic regulation and explain how minor perturbations can have a multitude of biochemical endpoints. It is this development, which creates the potential to provide the knowledge necessary to facilitate a more targeted approach to nutrition. In recent years, there has been interest in applying metabolomics to examine alterations in the metabolic profile according to weight gain/obesity. Emerging from these studies is the strong evidence that alterations in the amino acid (AA) profiles are associated with obesity. Several other studies have also shown a relationship between branched-chain amino acids (BCAA), obesity and insulin resistance. The present review focuses on the proposed link between AA and in particular BCAA, obesity and insulin resistance. In conclusion, a wealth of information is accumulating to support the role of AA, and in particular of the BCAA, in obesity.

Daily Variation of Serum Acylcarnitines and Amino Acids

To characterize daily variation of amino acids (AAs) and acylcarnitines (ACs) in response to feeding and activity, we measured serum metabolites at various times and after various activities during the day. Subjects were admitted overnight for serial serum sampling, collected in the evening (6-8pm, n=40), before rising from bed or eating (8AM, n=40), 1 hour after rising but before eating (9 AM, n=20), 1-2 hours after rising and breakfast (9-10 AM, n=40), and at noon (12 PM, n=20). Measurements of 15 AAs and 45 ACs were performed by quantitative tandem mass spectrometry using stable-isotope dilution. Coefficients of variation within and between patients were calculated for individual metabolite values and factors derived from principal components analysis. The change of state between timepoints was evaluated by nearest neighbor non-parametric analysis of values at one timepoint compared to the next subsequent value. Relative to baseline AM recumbent concentrations, AA concentrations rose after activity and feeding while AC concentrations rose after activity and decreased with feeding. Furthermore, for all AAs, ACs, and their factors, biological variation was quantifiably evident and distinct from daily variation. This study confirms the daily variation of AAs and provides the first report of daily variation for a large panel of ACs. Although standardization of sample collection is highly desirable to control for daily variation (within a subject due to activity or feeding), this study demonstrated measurable biological variability (across subjects) suggesting that non-standardized sample collections could potentially provide insights into specific AA and AC metabolic pathways and disease mechanisms.

Circulating metabolite predictors of glycemia in middle-aged men and women

OBJECTIVE

Metabolite predictors of deteriorating glucose tolerance may elucidate the pathogenesis of type 2 diabetes. We investigated associations of circulating metabolites from high-throughput profiling with fasting and postload glycemia cross-sectionally and prospectively on the population level.

RESEARCH DESIGN AND METHODS

Oral glucose tolerance was assessed in two Finnish, population-based studies consisting of 1,873 individuals (mean age 52 years, 58% women) and reexamined after 6.5 years for 618 individuals in one of the cohorts. Metabolites were quantified by nuclear magnetic resonance spectroscopy from fasting serum samples. Associations were studied by linear regression models adjusted for established risk factors.

RESULTS

Nineteen circulating metabolites, including amino acids, gluconeogenic substrates, and fatty acid measures, were cross-sectionally associated with fasting and/or postload glucose (P < 0.001). Among these metabolic intermediates, branched-chain amino acids, phenylalanine, and α1-acid glycoprotein were predictors of both fasting and 2-h glucose at 6.5-year follow-up (P < 0.05), whereas alanine, lactate, pyruvate, and tyrosine were uniquely associated with 6.5-year postload glucose (P = 0.003-0.04). None of the fatty acid measures were prospectively associated with glycemia. Changes in fatty acid concentrations were associated with changes in fasting and postload glycemia during follow-up; however, changes in branched-chain amino acids did not follow glucose dynamics, and gluconeogenic substrates only paralleled changes in fasting glucose.

CONCLUSIONS

Alterations in branched-chain and aromatic amino acid metabolism precede hyperglycemia in the general population. Further, alanine, lactate, and pyruvate were predictive of postchallenge glucose exclusively. These gluconeogenic precursors are potential markers of long-term impaired insulin sensitivity that may relate to attenuated glucose tolerance later in life.

Bayesian independent component analysis recovers pathway signatures from blood metabolomics data

Interpreting the complex interplay of metabolites in heterogeneous biosamples still poses a challenging task. In this study, we propose independent component analysis (ICA) as a multivariate analysis tool for the interpretation of large-scale metabolomics data. In particular, we employ a Bayesian ICA method based on a mean-field approach, which allows us to statistically infer the number of independent components to be reconstructed. The advantage of ICA over correlation-based methods like principal component analysis (PCA) is the utilization of higher order statistical dependencies, which not only yield additional information but also allow a more meaningful representation of the data with fewer components. We performed the described ICA approach on a large-scale metabolomics data set of human serum samples, comprising a total of 1764 study probands with 218 measured metabolites. Inspecting the source matrix of statistically independent metabolite profiles using a weighted enrichment algorithm, we observe strong enrichment of specific metabolic pathways in all components. This includes signatures from amino acid metabolism, energy-related processes, carbohydrate metabolism, and lipid metabolism. Our results imply that the human blood metabolome is composed of a distinct set of overlaying, statistically independent signals. ICA furthermore produces a mixing matrix, describing the strength of each independent component for each of the study probands. Correlating these values with plasma high-density lipoprotein (HDL) levels, we establish a novel association between HDL plasma levels and the branched-chain amino acid pathway. We conclude that the Bayesian ICA methodology has the power and flexibility to replace many of the nowadays common PCA and clustering-based analyses common in the research field.

Metabolomic profiling in blood from umbilical cords of low birth weight newborns

BACKGROUND

Low birth weight has been linked to an increased risk to develop obesity, type 2 diabetes, and hypertension in adult life, although the mechanisms underlying the association are not well understood. The objective was to determine whether the metabolomic profile of plasma from umbilical cord differs between low and normal birth weight newborns.

METHODS

Fifty healthy pregnant women and their infants were selected. The eligibility criteria were being born at term and having a normal pregnancy. Pairs were grouped according to their birth weight: low birth weight (LBW, birth weight < 10th percentile, n = 20) and control (control, birth weight between the 75th-90th percentiles, n = 30). Nuclear Magnetic Resonance (NMR) was used to generate metabolic fingerprints of umbilical cord plasma samples. Simultaneously, the metabolomic profiles of the mothers were analysed. The resulting data were subjected to chemometric, principal component and partial least squares discriminant analyses.

RESULTS

Umbilical cord plasma from LBW and control newborns displayed a clearly differentiated metabolic profile. Seven metabolites were identified that discriminate the LBW from the control group. LBW newborns had lower levels of choline, proline, glutamine, alanine and glucose than did the control newborns, while plasma levels of phenylalanine and citrulline were higher in LBW newborns (p < 0.05). No significant differences were found between the two groups of mothers.

CONCLUSIONS

Low birth weight newborns display a differential metabolomic profile than those of normal birth weight, a finding not present in the mothers. The meaning and the potential utility of the findings as biomarkers of risk need to be addressed in future studies.

Hyperglycemia and a common variant of GCKR are associated with the levels of eight amino acids in 9,369 Finnish men

We investigated the association of glycemia and 43 genetic risk variants for hyperglycemia/type 2 diabetes with amino acid levels in the population-based Metabolic Syndrome in Men (METSIM) Study, including 9,369 nondiabetic or newly diagnosed type 2 diabetic Finnish men. Plasma levels of eight amino acids were measured with proton nuclear magnetic resonance spectroscopy. Increasing fasting and 2-h plasma glucose levels were associated with increasing levels of several amino acids and decreasing levels of histidine and glutamine. Alanine, leucine, isoleucine, tyrosine, and glutamine predicted incident type 2 diabetes in a 4.7-year follow-up of the METSIM Study, and their effects were largely mediated by insulin resistance (except for glutamine). We also found significant correlations between insulin sensitivity (Matsuda insulin sensitivity index) and mRNA expression of genes regulating amino acid degradation in 200 subcutaneous adipose tissue samples. Only 1 of 43 risk single nucleotide polymorphisms for type 2 diabetes or hyperglycemia, the glucose-increasing major C allele of rs780094 of GCKR, was significantly associated with decreased levels of alanine and isoleucine and elevated levels of glutamine. In conclusion, the levels of branched-chain, aromatic amino acids and alanine increased and the levels of glutamine and histidine decreased with increasing glycemia, reflecting, at least in part, insulin resistance. Only one single nucleotide polymorphism regulating hyperglycemia was significantly associated with amino acid levels.

Adipokines promote lipotoxicity in human skeletal muscle cells

Studies have shown the implication of specific adipokines or fatty acids (FA) in the pathogenesis of insulin resistance. However, the interplay of adipokines with FA remains poorly understood. This study aimed to investigate the combined effects of adipokines and low concentrations of palmitic acid (PA, 100 µmol/l) on skeletal muscle metabolism. Human skeletal muscle cells were incubated with adipocyte-conditioned medium (CM), PA or PA+CM, and FA transporter and FA metabolism were analysed. CM-incubation increased CD36 level (1.8 fold) and PA-uptake (1.4 fold). However, only co-application of PA+CM resulted in profound lipid accumulation (5.3 fold), 60% reduction of PA-oxidation and 3.5 fold increased diacylglycerol content. Our results support a novel role for adipokines in the pathogenesis of T2D by increasing the lipotoxic potential of PA, notably of low concentrations. This implies an increased lipotoxic risk already at an early stage of weight gain, when lipolysis has not yet contributed to increased plasma free FA levels.

Metabolomic profiling reveals mitochondrial-derived lipid biomarkers that drive obesity-associated inflammation

Obesity has reached epidemic proportions worldwide. Several animal models of obesity exist, but studies are lacking that compare traditional lard-based high fat diets (HFD) to “Cafeteria diets" (CAF) consisting of nutrient poor human junk food. Our previous work demonstrated the rapid and severe obesogenic and inflammatory consequences of CAF compared to HFD including rapid weight gain, markers of Metabolic Syndrome, multi-tissue lipid accumulation, and dramatic inflammation. To identify potential mediators of CAF-induced obesity and Metabolic Syndrome, we used metabolomic analysis to profile serum, muscle, and white adipose from rats fed CAF, HFD, or standard control diets. Principle component analysis identified elevations in clusters of fatty acids and acylcarnitines. These increases in metabolites were associated with systemic mitochondrial dysfunction that paralleled weight gain, physiologic measures of Metabolic Syndrome, and tissue inflammation in CAF-fed rats. Spearman pairwise correlations between metabolites, physiologic, and histologic findings revealed strong correlations between elevated markers of inflammation in CAF-fed animals, measured as crown like structures in adipose, and specifically the pro-inflammatory saturated fatty acids and oxidation intermediates laurate and lauroyl carnitine. Treatment of bone marrow-derived macrophages with lauroyl carnitine polarized macrophages towards the M1 pro-inflammatory phenotype through downregulation of AMPK and secretion of pro-inflammatory cytokines. Results presented herein demonstrate that compared to a traditional HFD model, the CAF diet provides a robust model for diet-induced human obesity, which models Metabolic Syndrome-related mitochondrial dysfunction in serum, muscle, and adipose, along with pro-inflammatory metabolite alterations. These data also suggest that modifying the availability or metabolism of saturated fatty acids may limit the inflammation associated with obesity leading to Metabolic Syndrome.

Metabolic signatures of insulin resistance in 7,098 young adults

Metabolite associations with insulin resistance were studied in 7,098 young Finns (age 31 ± 3 years; 52% women) to elucidate underlying metabolic pathways. Insulin resistance was assessed by the homeostasis model (HOMA-IR) and circulating metabolites quantified by high-throughput nuclear magnetic resonance spectroscopy in two population-based cohorts. Associations were analyzed using regression models adjusted for age, waist, and standard lipids. Branched-chain and aromatic amino acids, gluconeogenesis intermediates, ketone bodies, and fatty acid composition and saturation were associated with HOMA-IR (P < 0.0005 for 20 metabolite measures). Leu, Ile, Val, and Tyr displayed sex- and obesity-dependent interactions, with associations being significant for women only if they were abdominally obese. Origins of fasting metabolite levels were studied with dietary and physical activity data. Here, protein energy intake was associated with Val, Phe, Tyr, and Gln but not insulin resistance index. We further tested if 12 genetic variants regulating the metabolites also contributed to insulin resistance. The genetic determinants of metabolite levels were not associated with HOMA-IR, with the exception of a variant in GCKR associated with 12 metabolites, including amino acids (P < 0.0005). Nonetheless, metabolic signatures extending beyond obesity and lipid abnormalities reflected the degree of insulin resistance evidenced in young, normoglycemic adults with sex-specific fingerprints.

Interplay between lipids and branched-chain amino acids in development of insulin resistance

Fatty acids (FA) and FA-derived metabolites have long been implicated in the development of insulin resistance and type 2 diabetes. Surprisingly, application of metabolomics technologies has revealed that branched-chain amino acids (BCAA) and related metabolites are more strongly associated with insulin resistance than many common lipid species. Moreover, the BCAA-related signature is predictive of incident diabetes and intervention outcomes and uniquely responsive to therapeutic interventions. Nevertheless, in animal feeding studies, BCAA supplementation requires the background of a high-fat diet to promote insulin resistance. This Perspective develops a model to explain how lipids and BCAA may synergize to promote metabolic diseases.

Lipid-induced mitochondrial stress and insulin action in muscle

The interplay between mitochondrial energetics, lipid balance, and muscle insulin sensitivity has remained a topic of intense interest and debate for decades. One popular view suggests that increased oxidative capacity benefits metabolic wellness, based on the premise that it is healthier to burn fat than glucose. Attempts to test this hypothesis using genetically modified mouse models have produced contradictory results and instead link muscle insulin resistance to excessive fat oxidation, acylcarnitine production, and increased mitochondrial H(2)O(2)-emitting potential. Here, we consider emerging evidence that insulin action in muscle is driven principally by mitochondrial load and redox signaling rather than oxidative capacity.

The association of specific metabolites of lipid metabolism with markers of oxidative stress, inflammation and arterial stiffness in men with newly diagnosed type 2 diabetes

OBJECTIVE

To determine whether circulating metabolic intermediates are associated with inflammation, oxidative stress and arterial stiffness in men with newly diagnosed type 2 diabetes and investigate the circulating metabolic intermediates that may predict the risk of developing diabetes.

RESEARCH DESIGN AND METHODS

Men with newly diagnosed type 2 diabetes (n = 26) and age- and body mass index-matched nondiabetic men (n = 27) were included. We measured inflammatory and oxidative markers and arterial stiffness by brachial-ankle pulse wave velocity (ba-PWV). Metabolomic profiling was analysed with ultra performance liquid chromatography and quadrupole time-of-flight mass spectrometry.

RESULTS

Diabetic men showed higher circulating levels of glucose, triglyceride, oxidized low-density lipoprotein (LDL), high-sensitivity C-reactive protein, interleukin (IL)-6, tumour necrosis factor-alpha (TNF-α), homeostasis model assessment-insulin resistance, urinary 8-epi-prostaglandin F(2α) (8-epi-PGF(2α)) and ba-PWV than nondiabetic men. In plasma, 19 metabolites including three amino acids, eight acylcarnitines, six lysophosphatidylcholines (lysoPCs), and two lysophosphatidylethanolamines (lysoPEs; C18:2 and C22:6) significantly increased in diabetes men, whereas serine and lysoPE (C18:1) decreased. Decanoyl carnitine, lysoPCs (C14:0, C16:1, C18:1 and C22:6) and lysoPE (C18:1) with variable importance in the projection values >1·0 were major plasma metabolites that distinguished nondiabetic and diabetic men. Decanoyl carnitine positively correlated with oxidized LDL, 8-epi-PGF(2α), IL-6, TNF-α and ba-PWV. ba-PWV correlated positively with lysoPCs C14:0 and C16:1, and negatively with lysoPE C18:1. 8-epi-PGF(2α) correlated positively with lipoprotein-associated phospholipase A(2), ba-PWV and lysoPCs (C14:0 and C16:1). The receiver operating characteristic curve estimation suggested that decanoyl carnitine and lysoPC (C14:0) are the best metabolites for predicting the risk of developing diabetes.

CONCLUSIONS

Circulating lipid-related intermediate metabolites can be closely associated with inflammation, oxidative stress and arterial stiffness in early diabetes.

Caloric restriction alters the metabolic response to a mixed-meal: results from a randomized, controlled trial

Objectives

To determine if caloric restriction (CR) would cause changes in plasma metabolic intermediates in response to a mixed meal, suggestive of changes in the capacity to adapt fuel oxidation to fuel availability or metabolic flexibility, and to determine how any such changes relate to insulin sensitivity (S_I).

Methods

Forty-six volunteers were randomized to a weight maintenance diet (Control), 25% CR, or 12.5% CR plus 12.5% energy deficit from structured aerobic exercise (CR+EX), or a liquid calorie diet (890 kcal/d until 15% reduction in body weight)for six months. Fasting and postprandial plasma samples were obtained at baseline, three, and six months. A targeted mass spectrometry-based platform was used to measure concentrations of individual free fatty acids (FFA), amino acids (AA), and acylcarnitines (AC). S_I was measured with an intravenous glucose tolerance test.

Results

Over three and six months, there were significantly larger differences in fasting-to-postprandial (FPP) concentrations of medium and long chain AC (byproducts of FA oxidation) in the CR relative to Control and a tendency for the same in CR+EX (CR-3 month P = 0.02; CR-6 month P = 0.002; CR+EX-3 month P = 0.09; CR+EX-6 month P = 0.08). After three months of CR, there was a trend towards a larger difference in FPP FFA concentrations (P = 0.07; CR-3 month P = 0.08). Time-varying differences in FPP concentrations of AC and AA were independently related to time-varying S_I (P<0.05 for both).

Conclusions

Based on changes in intermediates of FA oxidation following a food challenge, CR imparted improvements in metabolic flexibility that correlated with improvements in S_I.

Trial Registration

ClinicalTrials.gov NCT00099151

Metabolomic profiling of fatty acid and amino acid metabolism in youth with obesity and type 2 diabetes: evidence for enhanced mitochondrial oxidation

OBJECTIVE

We compared acylcarnitine (AcylCN) species, common amino acid and fat oxidation (FOX) byproducts, and plasma amino acids in normal weight (NW; n = 39), obese (OB; n = 64), and type 2 diabetic (n = 17) adolescents.

RESEARCH DESIGN AND METHODS

Fasting plasma was analyzed by tandem mass spectrometry, body composition by dual energy X-ray absorptiometry and computed tomography, and total-body lipolysis and substrate oxidation by [(2)H(5)]glycerol and indirect calorimetry, respectively. In vivo insulin sensitivity (IS) was assessed with a 3-h hyperinsulinemic-euglycemic clamp.

RESULTS

Long-chain AcylCNs (C18:2-CN to C14:0-CN) were similar among the three groups. Medium- to short-chain AcylCNs (except C8 and C10) were significantly lower in type 2 diabetes compared with NW, and when compared with OB, C2-, C6-, and C10-CN were lower. Amino acid concentrations were lower in type 2 diabetes compared with NW. Fasting lipolysis and FOX were higher in OB and type 2 diabetes compared with NW, and the negative association of FOX to C10:1 disappeared after controlling for adiposity, Tanner stage, and sex. IS was lower in OB and type 2 diabetes with positive associations between IS and arginine, histidine, and serine after adjusting for adiposity, Tanner stage, and sex.

CONCLUSIONS

These metabolomics results, together with the increased rates of in vivo FOX, are not supportive of defective fatty acid or amino acid metabolism in obesity and type 2 diabetes in youth. Such observations are consistent with early adaptive metabolic plasticity in youth, which over time-with continued obesity and aging-may become dysfunctional, as observed in adults.

Critical appraisal of four IL-6 immunoassays

BACKGROUND

Interleukin-6 (IL-6) contributes to numerous inflammatory, metabolic, and physiologic pathways of disease. We evaluated four IL-6 immunoassays in order to identify a reliable assay for studies of metabolic and physical function. Serial plasma samples from intravenous glucose tolerance tests (IVGTTs), with expected rises in IL-6 concentrations, were used to test the face validity of the various assays.

METHODS AND FINDINGS

IVGTTs, administered to 14 subjects, were performed with a single infusion of glucose (0.3 g/kg body mass) at time zero, a single infusion of insulin (0.025 U/kg body mass) at 20 minutes, and frequent blood collection from time zero to 180 minutes for subsequent Il-6 measurement. The performance metrics of four IL-6 detection methods were compared: Meso Scale Discovery immunoassay (MSD), an Invitrogen Luminex bead-based multiplex panel (LX), an Invitrogen Ultrasensitive Luminex bead-based singleplex assay (ULX), and R&D High Sensitivity ELISA (R&D). IL-6 concentrations measured with MSD, R&D and ULX correlated with each other (Pearson Correlation Coefficients r = 0.47-0.94, p<0.0001) but only ULX correlated (r = 0.31, p = 0.0027) with Invitrogen Luminex. MSD, R&D, and ULX, but not LX, detected increases in IL-6 in response to glucose. All plasma samples were measurable by MSD, while 35%, 1%, and 4.3% of samples were out of range when measured by LX, ULX, and R&D, respectively. Based on representative data from the MSD assay, baseline plasma IL-6 (0.90 ± 0.48 pg/mL) increased significantly as expected by 90 minutes (1.29 ± 0.59 pg/mL, p = 0.049), and continued rising through 3 hours (4.25 ± 3.67 pg/mL, p = 0.0048).

CONCLUSION

This study established the face validity of IL-6 measurement by MSD, R&D, and ULX but not LX, and the superiority of MSD with respect to dynamic range. Plasma IL-6 concentrations increase in response to glucose and insulin, consistent with both an early glucose-dependent response (detectable at 1-2 hours) and a late insulin-dependent response (detectable after 2 hours).

Branched-chain amino acid levels are associated with improvement in insulin resistance with weight loss

AIMS/HYPOTHESIS

Insulin resistance (IR) improves with weight loss, but this response is heterogeneous. We hypothesised that metabolomic profiling would identify biomarkers predicting changes in IR with weight loss.

METHODS

Targeted mass spectrometry-based profiling of 60 metabolites, plus biochemical assays of NEFA, β-hydroxybutyrate, ketones, insulin and glucose were performed in baseline and 6 month plasma samples from 500 participants who had lost ≥4 kg during Phase I of the Weight Loss Maintenance (WLM) trial. Homeostatic model assessment of insulin resistance (HOMA-IR) and change in HOMA-IR with weight loss (∆HOMA-IR) were calculated. Principal components analysis (PCA) and mixed models adjusted for race, sex, baseline weight, and amount of weight loss were used; findings were validated in an independent cohort of patients (n = 22).

RESULTS

Mean weight loss was 8.67 ± 4.28 kg; mean ∆HOMA-IR was -0.80 ± 1.73, range -28.9 to 4.82). Baseline PCA-derived factor 3 (branched chain amino acids [BCAAs] and associated catabolites) correlated with baseline HOMA-IR (r = 0.50, p < 0.0001) and independently associated with ∆HOMA-IR (p < 0.0001). ∆HOMA-IR increased in a linear fashion with increasing baseline factor 3 quartiles. Amount of weight loss was only modestly correlated with ∆HOMA-IR (r = 0.24). These findings were validated in the independent cohort, with a factor composed of BCAAs and related metabolites predicting ∆HOMA-IR (p = 0.007).

CONCLUSIONS/INTERPRETATION

A cluster of metabolites comprising BCAAs and related analytes predicts improvement in HOMA-IR independent of the amount of weight lost. These results may help identify individuals most likely to benefit from moderate weight loss and elucidate novel mechanisms of IR in obesity.

Serum glycerophosphate levels are increased in Japanese men with type 2 diabetes

OBJECTIVE

To identify metabolites showing changes in serum levels among Japanese male with diabetes.

METHODS

We performed metabolite profiling by coupling capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry using fasting serum samples from Japanese male subjects with diabetes (n=17), impaired glucose tolerance (IGT; n=5) and normal glucose tolerance (NGT; n=14).

RESULTS

Other than the expected differences in characteristics related to abnormal glucose metabolism, the percent body fat was significantly different among subjects with diabetes, IGT and NGT (27.3±6.2, 22.2±4.5 and 19.2±6.0%, respectively, p=0.0022). Therefore, percent body fat was considered as a possible confounding factor in subsequent analyses. Of 560 metabolites detected using our platform, the levels of 74 metabolites were quantified in all of the serum samples. Significant differences between diabetes and NGT were observed for 24 metabolites. The top-ranked metabolite was glycerol-3-phophate (glycerophosphate), which was significantly higher in subjects with diabetes than in those with NGT, even after Bonferroni correction for multiple testing (11.7±3.6 vs. 6.4±1.9 µM, respectively; corrected p=0.0222). Stepwise multiple regression analyses revealed that serum glycerophosphate levels were significantly correlated with 2-h plasma glucose after a 75-g oral glucose tolerance test (r=0.553, p=0.0005), independently of other characteristics, including FPG and HbA1c.

CONCLUSION

Serum glycerophosphate levels were found to be elevated in Japanese men with diabetes, and correlated with 2-h PG, independent of FPG and HbA1c. Namely, serum glycerophosphate level at fasting condition can be a marker for predicting glucose intolerance. These results warrant further studies to evaluate the relevance of glycerophosphate in the pathophysiology of diabetes.