Call: FP7-ICT-2011-9

Type of project: STREP


Project: MISSION-T2D

Multiscale Immune System SImulator for the Onset of Type 2 Diabetes integrating genetic, metabolic and nutritional data


Consiglio Nazionale delle Ricerche (IT, coordinator)

Università di Bologna (IT)

University of Cambridge (UK)

Università degli Studi di Roma "Foro Italico” (IT)

Toegepast Natuurwetenschappelijk Onderzoek (NL)

Medisana Space Technologies GMbH (DE)

University of Sheffield (UK)

Type 2 Diabetes Mellitus (T2D) is a metabolic disorder characterized by high blood glucose in the context of insulin resistance and relative insulin deficiency. T2D entails severe consequences in the long term: macro-vascular complications (including atherosclerosis, cardiovascular diseases, and amputations) and micro-vascular complications (including retinopathy, nephropathy and neuropathy).

Europe’s growing obesity “epidemic”, its ageing population and often-sedentary lifestyle have led to an explosion in the incidence of type 2 diabetes. Based on the report assumption that ~50% of affected people are unaware of their disease, it can be estimated that about 60 million people are at present affected by T2D in the EU.

MISSION-T2D aims at developing and validating an integrated, multilevel patient-specific model for the simulation and prediction of metabolic and inflammatory processes in the onset and progress of the type 2 diabetes.

This mission will be accomplished by setting up a multi-scale model to study the systemic interactions of the involved biological mechanisms (immunological/inflammatory processes, energy intake/expenditure ratio and cell cycle rate) in response to a variety of nutritional and metabolic stimuli/stressors.

MISSION-T2D aims at paving the way for translating validated multilevel immune-metabolic models into the clinical setting of T2D. Indeed, this approach will eventually generate predictive biomarkers from the integration of metabolic, nutritional, immune/inflammatory, genetic and gut microbiota profiles, as well as of clinical data, suitable to be translated into cost-effective mobile-based diagnostic tools.


Check for open positions on the project’s theme at: call for postdocs