Systemic investigation of a brain-centered model of the human energy metabolism

Göbel, Britta; Langemann, Dirk

doi:10.1007/s12064-010-0105-9

Cited by 7 publications

(7 citation statements)

References 22 publications

(18 reference statements)

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“…Herein, we have contributed with a link to intracellular knowledge from adipocyte insulin signaling, but there are models of liver metabolism [214,215], pancreatic insulin release [216,217], and brain control of glucose homeostasis [218,219], which could potentially further expand the presented multi-level model. Of great interest are, of course, also models of control of skeletal muscle insulin signaling and metabolism.…”

Section: General Discussion and Future Perspectivesmentioning

confidence: 99%

Insulin signaling dynamics in human adipocytes : Mathematical modeling reveals mechanisms of insulin resistance in type 2 diabetes

Nyman¹

2014

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Type 2 diabetes is characterized by raised blood glucose levels caused by an insufficient insulin control of glucose homeostasis. This lack of control is expressed both through insufficient release of insulin by the pancreatic beta-cells, and through insulin resistance in the insulin-responding tissues. We find insulin resistance of the adipose tissue particularly interesting since it appears to influence other insulin-responding tissues, such as muscle and liver, to also become insulin resistant.The insulin signaling network is highly complex with cross-interacting intermediaries, positive and negative feedbacks, etc. To facilitate the mechanistic understanding of this network, we obtain dynamic, information-rich data and use model-based analysis as a tool to formally test different hypotheses that arise from the experimental observations. With dynamic mathematical models, we are able to combine knowledge and experimental data into mechanistic hypotheses, and draw conclusions such as rejection of hypotheses and prediction of outcomes of new experiments.We aim for an increased understanding of adipocyte insulin signaling and the underlying mechanisms of the insulin resistance that we observe in adipocytes from subjects diagnosed with type 2 diabetes. We also aim for a complete picture of the insulin signaling network in primary human adipocytes from normal and diabetic subjects with a link to relevant clinical parameters: plasma glucose and insulin. Such a complete picture of insulin signaling has not been presented before. Not for adipocytes and not for other types of cells.In this thesis, I present the development of the first comprehensive insulin signaling model that can simulate both normal and diabetic data from adipocytes -and that is linked to a whole-body glucose-insulin model. In the linking process we conclude that at least two glucose uptake parameters differ between the in vivo and in vitro conditions (Paper I). We also perform a model analysis of the early insulin signaling dynamics in rat adipocytes and conclude that internalization is important for an apparent reversed order of phosphorylation seen in these cells (Paper II). In the development of the first version of the comprehensive insulin signaling model, we introduce a key parameter for the diabetic state -an attenuated feedback (Paper III). We finally continue to build on the comprehensive model and include signaling to nuclear transcription via ERK and report substantial crosstalk in the insulin signaling network (Paper IV). Populärvetenskaplig sammanfattningTyp 2-diabetes är en vanligt förekommande sjukdom där kroppens vävnader förlorar sin känslighet mot hormonet insulin. Insulinets uppgift är att hålla en jämn blodsockernivå dygnet runt. Insulin utsöndras i samband med måltider och påverkar muskel-och fettvävnader att ta upp socker och levern att sluta producera socker. Det är viktigt att hålla en jämn blodsockernivå eftersom låga nivåer kan vara direkt dödligt och höga nivåer är skadligt för blodkärlen, vilket i sin tur kan led...

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Section: General Discussion and Future Perspectivesmentioning

confidence: 99%

Insulin signaling dynamics in human adipocytes : Mathematical modeling reveals mechanisms of insulin resistance in type 2 diabetes

Nyman¹

2014

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“…Notice that all parameters, constants, and states are non-negative. Model properties he been investigated in detail and it has been shown that the model realistically reproduces qualitative and quantitative behavior of the whole body energy metabolism even for a large class of physiological interventions (see [11,12] for details).…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, we combine mathematical modeling and experimental data. In our novel approach, the integrative behavior of the human whole body energy metabolism is mathematically modeled in a compact dynamical system [11,12]. This model takes into account the central roles of the brain with respect to the systemic energy homeostasis.…”

Section: Introductionmentioning

confidence: 99%

Linking neuronal brain activity to the glucose metabolism

Göbel

Oltmanns

Chung

2013

Theor Biol Med Model

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BackgroundEnergy homeostasis ensures the functionality of the entire organism. The human brain as a missing link in the global regulation of the complex whole body energy metabolism is subject to recent investigation. The goal of this study is to gain insight into the influence of neuronal brain activity on cerebral and peripheral energy metabolism. In particular, the tight link between brain energy supply and metabolic responses of the organism is of interest. We aim to identifying regulatory elements of the human brain in the whole body energy homeostasis.MethodsFirst, we introduce a general mathematical model describing the human whole body energy metabolism. It takes into account the two central roles of the brain in terms of energy metabolism. The brain is considered as energy consumer as well as regulatory instance. Secondly, we validate our mathematical model by experimental data. Cerebral high-energy phosphate content and peripheral glucose metabolism are measured in healthy men upon neuronal activation induced by transcranial direct current stimulation versus sham stimulation. By parameter estimation we identify model parameters that provide insight into underlying neurophysiological processes. Identified parameters reveal effects of neuronal activity on regulatory mechanisms of systemic glucose metabolism.ResultsOur examinations support the view that the brain increases its glucose supply upon neuronal activation. The results indicate that the brain supplies itself with energy according to its needs, and preeminence of cerebral energy supply is reflected. This mechanism ensures balanced cerebral energy homeostasis.ConclusionsThe hypothesis of the central role of the brain in whole body energy homeostasis as active controller is supported.

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“…When it comes to such control systems that have been studied using mathematical models, the selfish-brain theory, as one example, comes to mind, whereby the brain ensures its own glucose supply. This selfish-brain theory has been modelled in a series of papers [47][48][49], based on experimental data including direct neural stimulation. Another theory about such a control system is known as the set-point theory, and it is described in the last review section below.…”

Section: Other Regulatory Systemsmentioning

confidence: 99%

Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes

et al. 2016

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One contribution of 12 to a theme issue 'The Human Physiome: a necessary key to the creative destruction of medicine'. We are currently in the middle of a major shift in biomedical research: unprecedented and rapidly growing amounts of data may be obtained today, from in vitro, in vivo and clinical studies, at molecular, physiological and clinical levels. To make use of these large-scale, multi-level datasets, corresponding multi-level mathematical models are needed, i.e. models that simultaneously capture multiple layers of the biological, physiological and disease-level organization (also referred to as quantitative systems pharmacology-QSP-models). However, today's multi-level models are not yet embedded in end-usage applications, neither in drug research and development nor in the clinic. Given the expectations and claims made historically, this seemingly slow adoption may seem surprising. Therefore, we herein consider a specific example-type 2 diabetes-and critically review the current status and identify key remaining steps for these models to become mainstream in the future. This overview reveals how, today, we may use models to ask scientific questions concerning, e.g., the cellular origin of insulin resistance, and how this translates to the whole-body level and short-term meal responses. However, before these multi-level models can become truly useful, they need to be linked with the capabilities of other important existing models, in order to make them 'personalized' (e.g. specific to certain patient phenotypes) and capable of describing long-term disease progression. To be useful in drug development, it is also critical that the developed models and their underlying data and assumptions are easily accessible. For clinical end-usage, in addition, model links to decisionsupport systems combined with the engagement of other disciplines are needed to create user-friendly and cost-efficient software packages.

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Systemic investigation of a brain-centered model of the human energy metabolism

Cited by 7 publications

References 22 publications

Insulin signaling dynamics in human adipocytes : Mathematical modeling reveals mechanisms of insulin resistance in type 2 diabetes

Insulin signaling dynamics in human adipocytes : Mathematical modeling reveals mechanisms of insulin resistance in type 2 diabetes

Linking neuronal brain activity to the glucose metabolism

Requirements for multi-level systems pharmacology models to reach end-usage: the case of type 2 diabetes

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