Lung transplantation (LT) is the standard of care for selected patients with chronic respiratory failure. Chronic lung allograft dysfunction (CLAD) (i.e. “Bronchiolitis obliterans syndrome” (BOS) and “Restrictive Allograft Syndrome” (RAS)) represents a major health risk for LT recipients, requiring the use of heavy treatments and possible retransplantation. Observed in almost 50% of patients after 5 years post LT, it is currently impossible to predict the appearance of CLAD before the onset of first symptoms. This project aims to develop the SysCLAD model which will allow to predict, within the 1st year post LT, the recipients at risk of developing CLAD by 3 years post LT. Building upon available data from the cohort of lung transplantation (COLT, recruited since mid-2009), this project will integrate new LT recipients to form the European cohort of lung transplantation (ECOLT). The SysCLAD prediction tool will be based on a mathematical model developed through a system biology approach integrating both clinical and biological data collected from a total of 400 LT recipients. The model will be validated on the first 200 LT recipients (3 years follow-up at project start) and refined using the new set of 200 LT data with 3 years follow-up by 2014. The aim is to identify and validate the signature of CLAD both at the clinical and molecular levels to allow for an early recognition and specific interventions in patients at risk of CLAD. The implementation of the model is expected to significantly improve the cost-effectiveness of post-LT treatments, limit the risk of graft rejection in LT recipients and, ultimately lead to an improved quality of life and a prolonged life expectancy of patients following LT. Finally, the SysCLAD model holds further great promises in the context of other chronic bronchial inflammatory diseases of major incidence such as severe asthma and Chronic Obstructive Pulmonary Disease (COPD) to predict decline in lung function.
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System finansowaniaCP-FP - Small or medium-scale focused research project