The onset of type 2 diabetes: proposal for a multi-scale model

Abstract

Background: Type 2 diabetes mellitus (T2D) is a common age-related disease, and is a major health concern, particularly in developed countries where the population is aging, including Europe. The multi-scale immune system simulator for the onset of type 2 diabetes (MISSION-T2D) is a European Union-funded project that aims to develop and validate an integrated, multilevel, and patient-specific model, incorporating genetic, metabolic, and nutritional data for the simulation and prediction of metabolic and inflammatory processes in the onset and progression of T2D. The project will ultimately provide a tool for diagnosis and clinical decision making that can estimate the risk of developing T2D and predict its progression in response to possible therapies. Recent data showed that T2D and its complications, specifically in the heart, kidney, retina, and feet, should be considered a systemic disease that is sustained by a pervasive, metabolically-driven state of inflammation. Accordingly, there is an urgent need (1) to understand the complex mechanisms underpinning the onset of this disease, and (2) to identify early patient-specific diagnostic parameters and related inflammatory indicators.

Objective: We aim to accomplish this mission by setting up a multi-scale model to study the systemic interactions of the biological mechanisms involved in response to a variety of nutritional and metabolic stimuli and stressors.

Methods: Specifically, we will be studying the biological mechanisms of immunological/inflammatory processes, energy intake/expenditure ratio, and cell cycle rate. The overall architecture of the model will exploit an already established immune system simulator as well as several discrete and continuous mathematical methods for modeling of the processes critically involved in the onset and progression of T2D. We aim to validate the predictions of our models using actual biological and clinical data.

Results: This study was initiated in March 2013 and is expected to be completed by February 2016.

Conclusions: MISSION-T2D aims to pave the way for translating validated multilevel immune-metabolic models into the clinical setting of T2D. This approach will eventually generate predictive biomarkers for this disease from the integration of clinical data with metabolic, nutritional, immune/inflammatory, genetic, and gut microbiota profiles. Eventually, it should prove possible to translate these into cost-effective and mobile-based diagnostic tools.

Keywords: computational biology; data integration; metabolism; metaflammation; multiscale modeling; physical activity; simulation; type 2 diabetes.

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1

Left: Excessive levels of nutrients, including glucose and free fatty acids, stress the pancreatic islets and insulin-sensitive tissues such as adipose tissue, leading to the local production and release of cytokines and chemokines (eg, IL-1β, TNF, CCL2, CCL3, and CXCL8). Furthermore, production of IL-1 receptor antagonist (IL-1RA) by β-cells is decreased. As a result, immune cells will be recruited, which contribute to tissue inflammation [14]. Right: Hallmarks of metaflammation. The first feature of this type of inflammation in obese individuals is that it originates from signals within metabolic cells such as adipocytes. Second, the metabolic signals trigger inflammatory intracellular signaling pathways that mediate downstream inflammatory responses (eg, JNK, IKK, or PKR pathways). The activation of these mediators induces a low level of chronic inflammation in response to the excess nutrients. Over time, this may induce the recruitment and activation of specialized immune cells [1].

Figure 2

Nutrient overload signals spill from metabolic pathways to immune-response pathways. Nutrient input under normal or healthy conditions should engage metabolic pathways within the cells, leaving immune-response pathways inactive. With increased nutrient intake, the levels of nutrients flooding the system may rise enough that the overflow stimulates pathogen-sensing pathways. Because these pathways recognize biological molecules such as specific fatty acids, excessive amounts of nutrient moieties may also be able to activate such sensors. Once the immune sensors are activated, they may be antagonistic to the metabolic pathways, in effect blocking the drain of nutrient metabolism. If the nutrient excess persists to an extreme state, immune-response pathways of specialized immune cells may also be activated. The involvement of these pathways will intensify the inhibition of metabolic pathways and contribute to the backlog of nutrients in the system [14].

Figure 3

Left: Relationships between the concepts to be modeled in MISSION-T2D: Each aspect will be taken into account either through empirical data or via modeling, with submodels built up into a single integrated model. This will take as input information from genetics, nutrition, age, physical activity habits, and gut microbiota to elaborate a patient-specific risk assessment for the onset of T2D. Right: The pulsatile inflammatory response during feeding, showing differences between the responses of normal and obese individuals’ reactions over time: Fasting/feeding cycles induce low-level inflammatory responses in the metabolic cells of average-weight, healthy individuals that are easily resolved. During the high-fat diet or excess feeding that results in obesity, responses to food become more intense and frequent, and the resolution of the inflammatory response becomes less efficient, raising the baseline level of inflammation in metabolic tissues. Once the level of inflammatory response reaches a certain threshold in the metabolic cells, professional immune cells are recruited and activated. The participation of these cells in the inflammatory response alters the tissue environment toward a proinflammatory milieu and exacerbates the inflammation even further [14].

Figure 4

T2D is a complex disease and its onset and progression cover different space-time scales, from molecular events (milliseconds) up to organ deterioration (years), taking into account the contribution of the individual genetic traits. MISSION-T2D project aims to cover and integrate models at all these levels, fully supporting the VPH initiative that aims to develop a computational framework to investigate the human body as a whole in health and disease [2].

Figure 5

A simplified systemic view of the models to be developed within MISSION-T2D and the interdependencies between them. Input-output relationships among modules of these models are depicted. Feedback (eg, IL-6 from the immune system to the stress-induced model) is not shown for simplicity.

Figure 6

Left: Each helper T lymphocyte (Th cell) is equipped with an intra-cellular dynamics consisting of a gene regulatory network to describe the dynamical rule for the differentiation from Th0 to Th1/Th2 phenotype. Right: The regulatory network dynamics is a function of the cytokine environment [22].

Figure 7

Sensor technology and the use of portable communication devices offer the possibility of storing and accessing data from our daily life to improve self-knowledge. Insights gained by performing these measurements can be used, for example, to change life-threatening habits, adopt a healthier lifestyle, or take more informed treatment decisions.