Predictive disease modeling for personalized and preventive medicine
Journal Title: Biomedicine & Prevention - Year 2016, Vol 2016, Issue 0
Abstract
The past two decades have witnessed enormous advances in terms of high-throughput techniques and technologies in molecular biology fields like genomics, which could potentially provide the terrain for investigations targeting the polygenic and multifactorial nature of complex diseases such as neurodegenerative disorders, chronic inflammatory diseases, or cancer. The highly heterogeneous clinical states of such disorders reflect the uncharacterized interaction of numerous genes, lifestyle and environmental factors. Accordingly, highly coordinated and multicentric research efforts are also underway to collect data at the other end of the spectrum with respect to genomics, e.g. multimodal magnetic resonance imaging (MRI) and positron emission tomography (PET) data in thousands healthy subjects (Human Connectome Project) or Alzheimer patients (Alzheimer’s Disease Neuroimaging Initiative). This is expected to increase overall power and accessibility to detect previously inaccessible disease-related biomarkers and mechanisms. In turn, this could provide better disease understanding, hence possibly leading to improved diagnosis, prognosis and prevention.
Authors and Affiliations
Nicola Toschi, Andrea Duggento, Maria Guerrisi
Keywords
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- EP ID EP334301
- DOI 10.19252/00000001A
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