MULTI-KNOWLEDGE

The MULTI-KNOWLEDGE Project aims to integrate different biomedical information from heterogeneous sources (clinical, laboratory and metabolic) with data on gene and protein expression provided by new high throughput technologies in a system committed to cardiovascular risk profiling.

The classical approach in global cardiovascular (CV) risk assessment can be faulty: classical risk factors (such as high cholesterol, high blood pressure, smoking, etc) are able to explain only 50% cases of CV events; it is furthermore not possible to assess the differential impact of risk factors in different subjects and it is still unclear whether the correction of risk factors can fetch CV risk to zero. There arises the need to to get a better prediction of the clinical events and a more efficient prevention strategy.

The MULTI-KNOWLEDGE Project's general goal is therefore the construction and implementation of a predictive algorithm combining clinical, laboratory, metabolic, gene and protein expression data to identify the presence of early signs of vessel wall atherosclerotic disease in subjects at different degree of cardiovascular disease (CVD) risk on the basis of traditional risk factors and insulin resistance level.

Scientific-medical objectives:

To investigate the impact of CV risk factors on systemic inflammation using gene expression profiling
To integrate clinical and molecular data to predict the presence of early signs of atherosclerosis

Technical aim: