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

Bioenergetic adaptations to HIV infection. Could modulation of energy substrate utilization improve brain health in people living with HIV-1?

The human brain consumes more energy than any other organ in the body and it relies on an uninterrupted supply of energy in the form of adenosine triphosphate (ATP) to maintain normal cognitive function. This constant supply of energy is made available through an interdependent system of metabolic pathways in neurons, glia and endothelial cells that each have specialized roles in the delivery and metabolism of multiple energetic substrates. Perturbations in brain energy metabolism is associated with a number of different neurodegenerative conditions including impairments in cognition associated with infection by the Human Immunodeficiency Type 1 Virus (HIV-1). Adaptive changes in brain energy metabolism are apparent early following infection, do not fully normalize with the initiation of antiretroviral therapy (ART), and often worsen with length of infection and duration of anti-retroviral therapeutic use. There is now a considerable amount of cumulative evidence that suggests mild forms of cognitive impairments in people living with HIV-1 (PLWH) may be reversible and are associated with specific modifications in brain energy metabolism. In this review we discuss brain energy metabolism with an emphasis on adaptations that occur in response to HIV-1 infection. The potential for interventions that target brain energy metabolism to preserve or restore cognition in PLWH are also discussed.

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

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 decision-support systems combined with the engagement of other disciplines are needed to create user-friendly and cost-efficient software packages.

Linking neuronal brain activity to the glucose metabolism

BACKGROUND

Energy 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.

METHODS

First, 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.

RESULTS

Our 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.

CONCLUSIONS

The hypothesis of the central role of the brain in whole body energy homeostasis as active controller is supported.

Mathematical modeling of the human energy metabolism based on the Selfish Brain Theory

Deregulations in the human energy metabolism may cause diseases such as obesity and type 2 diabetes mellitus. The origins of these pathologies are fairly unknown. The key role of the brain is the regulation of the complex whole body energy metabolism. The Selfish Brain Theory identifies the priority of brain energy supply in the competition for available energy resources within the organism. Here, we review mathematical models of the human energy metabolism supporting central aspects of the Selfish Brain Theory. First, we present a dynamical system modeling the whole body energy metabolism. This model takes into account the two central control mechanisms of the brain, i.e., allocation and appetite. Moreover, we present mathematical models of regulatory subsystems. We examine a neuronal model which specifies potential elements of the brain to sense and regulate cerebral energy content. We investigate a model of the HPA system regulating the allocation of energy within the organism. Finally, we present a robust modeling approach of appetite regulation. All models account for a systemic understanding of the human energy metabolism and thus do shed light onto defects causing metabolic diseases.