Descripción del proyecto
Presentar los efectos de los factores medioambientales en enfermedades pulmonares debilitantes
El concepto de exposoma refleja la medida acumulativa de las influencias medioambientales y las respuestas biológicas asociadas desde el período perinatal en adelante, e incluye las exposiciones a los procesos medioambientales, dietéticos, conductuales y endógenos. Su importancia en la salud y la enfermedad es innegable, especialmente para las enfermedades respiratorias crónicas, ya que son las principales causas de muerte relacionadas con el medio ambiente. La enfermedad pulmonar obstructiva crónica (EPOC) y la fibrosis quística son dos enfermedades respiratorias crónicas debilitantes que comparten características comunes, aunque presentan orígenes opuestos: la primera parece estar intrínsecamente relacionada con el exposoma, mientras que la segunda, no. A fin de estudiar el efecto del exposoma en el curso de estas dos enfermedades, el proyecto REMEDIA, financiado con fondos europeos, está desarrollando unos métodos que combinan la recopilación de datos clínicos y sobre el exposoma, el aprendizaje automático avanzado, el uso de cámaras de simulación atmosférica y el desarrollo de dispositivos de detección individuales. Estos métodos podrían marcar el camino hacia una prevención y un tratamiento eficaces.
Objetivo
Chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF) are two very debilitating non-communicable diseases that are of particular interest to consider in parallel in a human exposome study. Their roots are opposite: COPD is currently considered to be mainly related to the external exposome, while factors outside of the exposome play a major role in CF. However, COPD and CF share common characteristics such as high phenotypic variability of unknown origin, which prevents good therapeutic efficacy. It is therefore clear that the overall picture must be supplemented by taking into account additional components of the exposome than those currently considered in COPD and CF. Thus, the overall objective of the REMEDIA project is to extend the understanding of the contribution of the exposome, taken as a complex set of different components, to COPD and CF diseases. We will exploit data from existing cohorts and population registries in order to create a unified global database gathering phenotype and exposome information; we will develop a flexible individual sensor device combining environmental and biomarker toolkits; and use a versatile atmospheric simulation chamber to simulate the health effects of complex exposomes. We will use machine learning supervised analyses and causal inference models to identify relevant risk factors; and econometric and cost-effectiveness models to assess the costs, performance and cost-effectiveness of a selection of prevention strategies. The results will be used to develop guidelines to better predict disease risks and constitute the elements of the REMEDIA toolbox (global unified database, sensor device, versatile atmospheric simulation chamber, machine learning supervised analyses, causal inference model, Pan-European multi-criteria risk assessment tool, econometric models, cost-effectiveness models, new guidelines and recommendations). Deciphering the impact of environmental components throughout life on the phenotypic variability of COPD and CF could represent a major breakthrough in reducing morbidity and mortality associated with these two non-curable diseases and would lead to the identification of modifiable risk factors on which preventive action could be implemented. REMEDIA will be part of the European Human Exposome Network established between the 9 projects funded within the Human Exposome programme call H2020-SC1-BHC-2018-2020.
Ámbito científico
- social scienceseconomics and businesseconomicseconometrics
- social sciencessociologydemographymortality
- natural sciencescomputer and information sciencesdatabases
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SC1-2019-Single-Stage-RTD
Régimen de financiación
RIA - Research and Innovation actionCoordinador
75654 Paris
Francia