827 resultados para metabolic coding


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Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

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AIMS: We examined, in a country of the African region, i) the prevalence of the metabolic syndrome (MetS) according to three definitions (ATP, WHO and IDF); ii) the distribution of the MetS criteria; iii) the level of agreement between these three definitions and iv) we also examined these issues upon exclusion of people with diabetes. METHODS: We conducted an examination survey on a sample representative of the general population aged 25-64 years in the Seychelles (Indian Ocean, African region), attended by 1255 participants (participation rate of 80.3%). RESULTS: The prevalence of MetS increased markedly with age. According to the ATP, WHO and IDF definitions, the prevalence of MetS was, respectively, 24.0%, 25.0%, 25.1% in men and 32.2%, 24.6%, 35.4% in women. Approximately 80% of participants with diabetes also had MetS and the prevalence of MetS was approximately 7% lower upon exclusion of diabetic individuals. High blood pressure and adiposity were the criteria found most frequently among MetS holders irrespective of the MetS definitions. Among people with MetS based on any of the three definitions, 78% met both ATP and IDF criteria, 67% both WHO and IDF criteria, 54% both WHO and ATP criteria and only 37% met all three definitions. CONCLUSION: We identified a high prevalence of MetS in this population in epidemiological transition. The prevalence of MetS decreased by approximately 32% upon exclusion of persons with diabetes. Because of limited agreement between the MetS definitions, the fairly similar proportions of MetS based on any of the three MetS definitions classified, to a substantial extent, different subjects as having MetS.

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This study investigates the effects of digoxin, an inhibitor of the Na+ pump (Na(+)-K(+)-ATPase), on resting metabolic rate (RMR), respiratory quotient (RQ), and nutrient oxidation rate. Twelve healthy male subjects followed a double-blind protocol design and received either 1 mg/day digoxin or a placebo 2 days before indirect calorimetry measurements. Digoxin induced a 0.22 +/- 0.07 kJ/min or 3.8 +/- 1.5% (mean +/- SE, P = 0.01) decrease in RMR and a 0.40 +/- 0.13 kJ/min (P = 0.01) decrease in fat oxidation rate, whereas carbohydrate and protein oxidation rates did not change significantly. A dose-response relationship between serum digoxin and RQ was observed. These results suggest that digoxin reduces not only RMR but also fat oxidation rate by mechanisms that remain to be elucidated. Because a linkage and an association between genes coding the Na(+)-K(+)-ATPase and the RQ have been previously observed, the present demonstration of an effect of Na(+)-K(+)-ATPase inhibition on fat oxidation rate strengthens the concept that the activity of this enzyme may play a role in body weight regulation.

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AIMS: To investigate the relationships between gestational diabetes mellitus (GDM) and the metabolic syndrome (MS), as it was suggested that insulin resistance was the hallmark of both conditions. To analyse post-partum screening in order to identify risk factors for the subsequent development of type 2 diabetes mellitus (DM). METHODS: A retrospective analysis of all singleton pregnancies diagnosed with GDM at the Lausanne University Hospital for 3 consecutive years. Pre-pregnancy obesity, hypertension and dyslipidaemia were recorded as constituents of the MS. RESULTS: For 5788 deliveries, 159 women (2.7%) with GDM were identified. Constituents of the MS were present before GDM pregnancy in 26% (n = 37/144): 84% (n = 31/37) were obese, 38% (n = 14/37) had hypertension and 22% (n = 8/37) had dyslipidaemia. Gestational hypertension was associated with obesity (OR = 3.2, P = 0.02) and dyslipidaemia (OR = 5.4, P=0.002). Seventy-four women (47%) returned for post-partum OGTT, which was abnormal in 20 women (27%): 11% (n = 8) had type 2 diabetes and 16% (n = 12) had impaired glucose tolerance. Independent predictors of abnormal glucose tolerance in the post-partum were: having > 2 abnormal values on the diagnostic OGTT during pregnancy and presenting MS constituents (OR = 5.2, CI 1.8-23.2 and OR = 5.3, CI 1.3-22.2). CONCLUSIONS: In one fourth of GDM pregnancies, metabolic abnormalities precede the appearance of glucose intolerance. These women have a high risk of developing the MS and type 2 diabetes in later years. Where GDM screening is not universal, practitioners should be aware of those metabolic risks in every pregnant woman presenting with obesity, hypertension or dyslipidaemia, in order to achieve better diagnosis and especially better post-partum follow-up and treatment.

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This review is focused on the fate of dietary glucose under conditions of chronically high energy (largely fat) intake, evolving into the metabolic syndrome. We are adapted to carbohydrate-rich diets similar to those of our ancestors. Glucose is the main energy staple, but fats are our main energy reserves. Starvation drastically reduces glucose availability, forcing the body to shift to fatty acids as main energy substrate, sparing glucose and amino acids. We are not prepared for excess dietary energy, our main defenses being decreased food intake and increased energy expenditure, largely enhanced metabolic activity and thermogenesis. High lipid availability is a powerful factor decreasing glucose and amino acid oxidation. Present-day diets are often hyperenergetic, high on lipids, with abundant protein and limited amounts of starchy carbohydrates. Dietary lipids favor their metabolic processing, saving glucose, which additionally spares amino acids. The glucose excess elicits hyperinsulinemia, which may derive, in the end, into insulin resistance. The available systems of energy disposal could not cope with the excess of substrates, since they are geared for saving not for spendthrift, which results in an unbearable overload of the storage mechanisms. Adipose tissue is the last energy sink, it has to store the energy that cannot be used otherwise. However, adipose tissue growth also has limits, and the excess of energy induces inflammation, helped by the ineffective intervention of the immune system. However, even under this acute situation, the excess of glucose remains, favoring its final conversion to fat. The sum of inflammatory signals and deranged substrate handling induce most of the metabolic syndrome traits: insulin resistance, obesity, diabetes, liver steatosis, hyperlipidemia and their compounded combined effects. Thus, a maintained excess of energy in the diet may result in difficulties in the disposal of glucose, eliciting inflammation and the development of the metabolic syndrome

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1. The relation between dietary carbohydrate: lipid ratio and the fuel mixture oxidized during 24 h was investigated in eleven healthy volunteers (six females, and five males) in a respiration chamber. Values of the fuel mixture oxidized were estimated by continuous indirect calorimetry and urinary nitrogen measurements. 2. The subjects, were first given a mixed diet for 7 d and spent the last 24 h of the 7 d period in a respiration chamber for continuous gas-exchange measurement. The fuels oxidized during 2.5 h or moderate exercise were also measured in the respiration chamber. After an interval of 2 weeks from the end of the mixed-diet period, the same subjects were given an isoenergetic high-carbohydrate low-fat diet for 7 d, and the same experimental regimen was repeated. 3. Dietary composition markedly influenced the fuel mixture oxidized during 24 h and this effect was still present 12 h after the last meal in the postabsorptive state. However, the diets had no influence on the substrates oxidized above resting levels during exercise. With both diets, the 24 h energy balance was slightly negative and the energy deficit was covered by lipid oxidation. 4. With the high-carbohydrate low-fat diet, the energy expenditure during sleep was found to be higher than that with the mixed diet. 5. It is concluded that: (a) the composition of the diet did not influence the fuel mixture utilized for moderate exercise, (b) the energy deficit calculated for a 24 h period was compensated by lipid oxidation irrespective of the carbohydrate content of the diet, (c) energy expenditure during sleep was found to be higher with the high-carbohydrate low-fat diet than with the mixed diet.

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Background: Network reconstructions at the cell level are a major development in Systems Biology. However, we are far from fully exploiting its potentialities. Often, the incremental complexity of the pursued systems overrides experimental capabilities, or increasingly sophisticated protocols are underutilized to merely refine confidence levels of already established interactions. For metabolic networks, the currently employed confidence scoring system rates reactions discretely according to nested categories of experimental evidence or model-based likelihood. Results: Here, we propose a complementary network-based scoring system that exploits the statistical regularities of a metabolic network as a bipartite graph. As an illustration, we apply it to the metabolism of Escherichia coli. The model is adjusted to the observations to derive connection probabilities between individual metabolite-reaction pairs and, after validation, to assess the reliability of each reaction in probabilistic terms. This network-based scoring system uncovers very specific reactions that could be functionally or evolutionary important, identifies prominent experimental targets, and enables further confirmation of modeling results. Conclusions: We foresee a wide range of potential applications at different sub-cellular or supra-cellular levels of biological interactions given the natural bipartivity of many biological networks.

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Metabolic syndrome represents a grouping of risk factors closely linked to cardiovascular diseases and diabetes. At first, nuclear medicine has no direct application in cardiology at the level of primary prevention, but positron emission tomography is a non invasive imaging technique that can assess myocardial perfusion as well as the endothelium-dependent coronary vasomotion--a surrogate marker of cardiovascular event rate--thus finding an application in studying coronary physiopathology. As the prevalence of the metabolic syndrome is still unknown in Switzerland, we will estimate it from data available in the frame of a health promotion program. Based on the deleterious effect on the endothelium already observed with two components, we will estimate the number of persons at risk in Switzerland.

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Numerous algorithms originating from evidence-based medicine already exist; in spite of this, metabolic syndrome management remains problematical and needs to be improved. Specialists, working interactively and referring to clinical scenarios, pooled their specific areas of expertise in a transverse perspective of the metabolic syndrome management by the primary care physician. This concerted multidisciplinary approach has clearly revealed that a bio-psycho-social approach is absolutely essential in the management of this type of patients.

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Over the last three decades genetic and biochemical studies have revealed the pleiotropic effects of the Myc oncoprotein. While cell line studies have defined the intracellular processes regulated by Myc such as proliferation, differentiation, and metabolic growth, in vivo studies have confirmed these functions, and revealed roles in acquisition and maintenance of stem cell properties. These roles may be partially mediated by Myc's capacity to modify the chromatin landscape on a global scale. Myc also regulates numerous protein-coding transcripts, and many noncoding RNAs (rRNAs, tRNAs, and miRNAs). As Myc activity directly correlates with protein expression, further complexity is provided by post-translational modifications that regulate Myc in normal stem cells or deregulate it in malignant stem cells.

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Objectives: Acetate brain metabolism has the particularity to occur specifically in glial cells. Labeling studies, using acetate labeled either with 13C (NMR) or 11C (PET), are governed by the same biochemical reactions and thus follow the same mathematical principles. In this study, the objective was to adapt an NMR acetate brain metabolism model to analyse [1-11C]acetate infusion in rats. Methods: Brain acetate infusion experiments were modeled using a two-compartment model approach used in NMR.1-3 The [1-11C]acetate labeling study was done using a beta scintillator.4 The measured radioactive signal represents the time evolution of the sum of all labeled metabolites in the brain. Using a coincidence counter in parallel, an arterial input curve was measured. The 11C at position C-1 of acetate is metabolized in the first turn of the TCA cycle to the position 5 of glutamate (Figure 1A). Through the neurotransmission process, it is further transported to the position 5 of glutamine and the position 5 of neuronal glutamate. After the second turn of the TCA cycle, tracer from [1-11C]acetate (and also a part from glial [5-11C]glutamate) is transferred to glial [1-11C]glutamate and further to [1-11C]glutamine and neuronal glutamate through the neurotransmission cycle. Brain poster session: oxidative mechanisms S460 Journal of Cerebral Blood Flow & Metabolism (2009) 29, S455-S466 Results: The standard acetate two-pool PET model describes the system by a plasma pool and a tissue pool linked by rate constants. Experimental data are not fully described with only one tissue compartment (Figure 1B). The modified NMR model was fitted successfully to tissue time-activity curves from 6 single animals, by varying the glial mitochondrial fluxes and the neurotransmission flux Vnt. A glial composite rate constant Kgtg=Vgtg/[Ace]plasma was extracted. Considering an average acetate concentration in plasma of 1 mmol/g5 and the negligible additional amount injected, we found an average Vgtg = 0.08±0.02 (n = 6), in agreement with previous NMR measurements.1 The tissue time-activity curve is dominated by glial glutamate and later by glutamine (Figure 1B). Labeling of neuronal pools has a low influence, at least for the 20 mins of beta-probe acquisition. Based on the high diffusivity of CO2 across the blood-brain barrier; 11CO2 is not predominant in the total tissue curve, even if the brain CO2 pool is big compared with other metabolites, due to its strong dilution through unlabeled CO2 from neuronal metabolism and diffusion from plasma. Conclusion: The two-compartment model presented here is also able to fit data of positron emission experiments and to extract specific glial metabolic fluxes. 11C-labeled acetate presents an alternative for faster measurements of glial oxidative metabolism compared to NMR, potentially applicable to human PET imaging. However, to quantify the relative value of the TCA cycle flux compared to the transmitochondrial flux, the chemical sensitivity of NMR is required. PET and NMR are thus complementary.

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RESUME EN FRANÇAIS BUTS. Étudier les relations entre le diabète gestationnel (GDM) et le syndrome métabolique (MS), comme la résistance à l'insuline est une des caractéristiques des 'deux conditions. Analyser le dépistage du diabète dans le post-partum pour identifier les facteurs de risque associés au développement d'un diabète de type 2 ultérieur. MÉTHODES. Étude rétrospective de toutes les grossesses uniques diagnostiquées avec un diabète gestationnel à l'hôpital universitaire de Lausanne, pendant une durée de trois ans. La présence d'une obésité, d'une hypertension ou d'une dyslipidémie avant la grossesse définissent les composants du syndrome métabolique. RÉSULTATS. Sur 5788 grossesses, 159 patientes (2.7%) présentaient un diabète gestationnel. Des composants du syndrome métabolique étaient présents avant la grossesse chez 26% des patientes (n=37/144) : 84% (n=31/37) étaient obèses, 38% (n=14/37) présentaient une hypertension et 22% (n=8/37) une dyslipidémie. Le développement d'une hypertension gravidique était associé à l'obésité (OR=3.2, p=0.02) et à la dyslipidémie (OR=5.4, p=0.002). Septante-quatre patientes (47%) sont revenues pour l'HGPO dans le post-partum. Celle-ci était anormale chez 20 femmes (27%): 11 % (n=8) présentaient un diabète de type 2 et 16% (n=12) avaient une intolérance au glucose. Les facteurs de risque indépendants associés à une anomalie de la tolérance au glucose dans le post-partum étaient d'avoir plus de 2 valeurs anormales au test diagnostique durant la grossesse et présenter des composants du syndrome métabolique (OR=5.2, CI 1.8-23.2 et OR=5.3, CI 1.3-22.2). CONCLUSIONS. Dans un quart des grossesses avec un diabète gestationnel, des anomalies métaboliques précèdent l'apparition de l'intolérance au glucose. Ces patientes présentent un haut risque de développer un syndrome métabolique et un diabète de type 2 ultérieurement. Là où le dépistage du diabète gestationnel n'est pas systématique, les praticiens devraient être avertis de ces risques métaboliques chez les patiente se présentant avec une obésité, une hypertension ou une dyslipidémie, afin de mieux les diagnostiquer et surtout de mieux les suivre et traiter après leur grossesse.