CACNA1E Variants Affect Beta Cell Function in Patients with Newly Diagnosed Type 2 Diabetes. The Verona Newly Diagnosed Type 2 Diabetes Study (VNDS) 3

Background: Genetic variability of the major subunit (CACNA1E) of the voltage-dependent Ca 2+ channel Ca V2.3 is associated to risk of type 2 diabetes, insulin resistance and impaired insulin secretion in nondiabetic subjects. The aim of the study was to test whether CACNA1E common variability affects beta cell function and/or insulin sensitivity in patients with newly diagnosed type 2 diabetes. Methodology/Principal Findings: In 595 GAD-negative, drug naïve patients (mean6SD; age: 58.5610.2 yrs; BMI: 29.965 kg/m 2, HbA1c: 7.061.3) with newly diagnosed type 2 diabetes we: 1. genotyped 10 tag SNPs in CACNA1E region reportedly covering,93 % of CACNA1E common variability: rs558994, rs679931, rs2184945, rs10797728, rs3905011, rs12071300, rs175338, rs3753737, rs2253388 and rs4652679; 2. assessed clinical phenotypes, insulin sensitivity by the euglycemic insulin clamp and beta cell function by state-of-art modelling of glucose/C-peptide curves during OGTT. Five CACNA1E tag SNPs (rs10797728, rs175338, rs2184945, rs3905011 and rs4652679) were associated with specific aspects of beta cell function (p,0.0520.01). Both major alleles of rs2184945 and rs3905011 were each (p,0.01 and p,0.005, respectively) associated to reduced proportional control with a demonstrable additive effect (p,0.005). In contrast, only the major allele of rs2253388 was related weakly to more severe insulin resistance (p,0.05). Conclusions/Significance: In patients with newly diagnosed type 2 diabetes CACNA1E common variability is strongl

Structural identifiability of dynamic systems biology models

22 páginas, 5 figuras, 2 tablas.-- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.A powerful way of gaining insight into biological systems is by creating a nonlinear differential equation model, which usually contains many unknown parameters. Such a model is called structurally identifiable if it is possible to determine the values of its parameters from measurements of the model outputs. Structural identifiability is a prerequisite for parameter estimation, and should be assessed before exploiting a model. However, this analysis is seldom performed due to the high computational cost involved in the necessary symbolic calculations, which quickly becomes prohibitive as the problem size increases. In this paper we show how to analyse the structural identifiability of a very general class of nonlinear models by extending methods originally developed for studying observability. We present results about models whose identifiability had not been previously determined, report unidentifiabilities that had not been found before, and show how to modify those unidentifiable models to make them identifiable. This method helps prevent problems caused by lack of identifiability analysis, which can compromise the success of tasks such as experiment design, parameter estimation, and model-based optimization. The procedure is called STRIKE-GOLDD (STRuctural Identifiability taKen as Extended-Generalized Observability with Lie Derivatives and Decomposition), and it is implemented in a MATLAB toolbox which is available as open source software. The broad applicability of this approach facilitates the analysis of the increasingly complex models used in systems biology and other areasAFV acknowledges funding from the Galician government (Xunta de Galiza, Consellería de Cultura, Educación e Ordenación Universitaria http://www.edu.xunta.es/portal/taxonomy/term/206) through the I2C postdoctoral program, fellowship ED481B2014/133-0. AB and AFV were partially supported by grant DPI2013-47100-C2-2-P from the Spanish Ministry of Economy and Competitiveness (MINECO). AFV acknowledges additional funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 686282 (CanPathPro). AP was partially supported through EPSRC projects EP/M002454/1 and EP/J012041/1.Peer reviewe

A New Version of DAISY to Test Structural Identifiability of Biological Models

Often ODE models in systems biology, medical research, epidemiology, ecology and many other areas, contain unknown parameters which need to be estimated from experimental data. Identifiability deals with the uniqueness of the relation between model parameters and ODE solution thus being a prerequisite for the well-posedness of parameter estimation. In this paper a novel extension of the software tool DAISY (Differential Algebra for Identifiability of SYstems) is presented. DAISY performs structural identifiability analysis for linear and nonlinear dynamic models described by polynomial or rational ODE\u2019s. The major upgrades of this new version regard the ability to include in the identifiability analysis either known and unknown model initial conditions, the possibility of entering a parameter estimate to calculate all the equivalent parameter solutions, the portability to MacOS platforms and an user-friendly interface. These upgrades make DAISY surely more general and easy to use. Practical examples are presented. DAISY is available at the web site daisy.dei.unipd.it

Bicarbonate kinetics in humans: identification and validation of a three-compartment model

none5A model of bicarbonate kinetics is crucial to a correct interpretation of experiments for measuring oxidation in vivo of carbon-labeled compounds. The aim of this study is to develop a compartmental model of bicarbonate kinetics in humans from tracer data by devoting particular attention to model identification and validation. The data base consisted of impulse-dose studies of 14C-labeled bicarbonate in nine normal subjects. The decay curve of specific activity of CO2 in expired air (saRCO2) was frequently sampled for 4-7 h. In addition, endogenous production of CO2, VCO2, was measured by indirect calorimetry. A model of data, i.e., an exponential model, analysis of decay curves of saRCO2 showed first that three compartments are necessary and sufficient to describe bicarbonate tracer kinetics. Compartmental models were then used as models of system. To correctly describe the input-output configuration, labeled CO2 flux in the expired air, phi RCO2 (= saRCO2.VCO2), has been used as measurement variable in tracer model identification. A mammillary three-compartment model with a respiratory and a nonrespiratory loss has been studied. Whereas there is good evidence that respiratory loss takes place in the central compartment, whether nonrespiratory loss is taking place in the central compartment or in one of the two peripheral compartments is uncertain. Thus three competing tracer models were considered. Using a model-independent analysis of data, based on the body activity variable, to calculate mean residence time in the system, we have been able to validate a specific model structure, i.e., with the two irreversible losses taking place in the central compartment. This validated tracer model was then used to quantitate bicarbonate masses in the system. Because there is uncertainty about where endogenous production enters the system, lower and upper bounds of masses of bicarbonate in the body are derived.noneM.P. Saccomani; R.C. Bonadonna; E. Caveggion; R.A. DeFronzo; C. Cobelli.Saccomani, Mariapia; R. C., Bonadonna; E., Caveggion; R. A., Defronzo; Cobelli, Claudi

Role of tissue-specific blood flow and tissue recruitment in insulin-mediated glucose uptake of human skeletal muscle

BACKGROUND: Conflicting evidence exists concerning whether insulin-induced vasodilation plays a mechanistic role in the regulation of limb glucose uptake. It can be predicted that if insulin augments blood flow by causing tissue recruitment, this mechanism would enhance limb glucose uptake. METHODS AND RESULTS: Twenty healthy subjects were studied with the forearm perfusion technique in combination with the euglycemic insulin clamp technique. Ten subjects were studied at physiological insulin concentrations (approximately 400 pmol/L) and the other 10 at supraphysiological insulin concentrations (approximately 5600 pmol/L). Four additional subjects underwent a saline control study. Pulse injections of a nonmetabolizable extracellular marker (1-[3H]-L-glucose) were administered into the brachial artery, and its washout curves were measured in one ipsilateral deep forearm vein and used to estimate the extracellular volume of distribution and hence the amount of muscle tissue drained by the deep forearm vein. Both during saline infusion and at physiological levels of hyperinsulinemia we observed no changes in blood flow and/or muscle tissue drained by the deep forearm vein. However, supraphysiological hyperinsulinemia accelerated total forearm blood flow (45.0+/-1.8 versus 36.5+/-1.3 mL x min(-1) x kg(-1), P<0.01) and increased the amount of muscle tissue drained by the deep forearm vein (305+/-46 versus 229+/-32 g, P<0.05). The amount of tissue newly recruited by insulin was strongly correlated to the concomitant increase in tissue glucose uptake (r=0.789, P<0.01). CONCLUSIONS: Acceleration of forearm blood flow mediated by supraphysiological hyperinsulinemia is accompanied by tissue recruitment, which may be a relevant determinant of forearm (muscle) glucose uptake

Particle observers for contracting dynamical systems

International audienc

Transmembrane glucose transport in skeletal muscle of patients with non-insulin-dependent diabetes

Insulin resistance for glucose metabolism in skeletal muscle is a key feature in non-insulin-dependent diabetes mellitus (NIDDM). Which cellular effectors of glucose metabolism are involved is still unknown. We investigated whether transmembrane glucose transport in vivo is impaired in skeletal muscle in nonobese NIDDM patients. We performed euglycemic insulin clamp studies in combination with the forearm balance technique (brachial artery and deep forearm vein catheterization) in six nonobese NIDDM patients and five age- and weight-matched controls. Unlabeled D-mannitol (a nontransportable molecule) and radioactive 3-O-methyl-D-glucose (the reference molecular probe to assess glucose transport activity) were simultaneously injected into the brachial artery, and the washout curves were measured in the deep venous effluent blood. In vivo transmembrane transport of 3-O-methyl-D-glucose in forearm muscle was determined by computerized analysis of the washout curves. At similar steady-state plasma concentrations of insulin (approximately 500 pmol/liter) and glucose (approximately 5.15 mmol/liter), transmembrane inward transport of 3-O-methyl-D-glucose in skeletal muscle was markedly reduced in the NIDDM patients (6.5 x 10(-2) +/- 0.56 x 10(-2).min-1) compared with controls (12.5 x 10(-2) +/- 1.5 x 10(-2).min-1, P &lt; 0.005). Mean glucose uptake was also reduced in the diabetics both at the whole body level (9.25 +/- 1.84 vs. 28.3 +/- 2.44 mumol/min per kg, P &lt; 0.02) and in the forearm tissues (5.84 +/- 1.51 vs. 37.5 +/- 7.95 mumol/min per kg, P &lt; 0.02). When the latter rates were extrapolated to the whole body level, skeletal muscle accounted for approximately 80% of the defect in insulin action seen in NIDDM patients. We conclude that transmembrane glucose transport, when assessed in vivo in skeletal muscle, is insensitive to insulin in nonobese NIDDM patients, and plays a major role in determining whole body insulin resistance