Descripción del proyecto
Identificación de los mecanismos moleculares de los trastornos relacionados con el dolor
Los pacientes con dolor crónico tienden a padecer numerosas comorbilidades que incluyen ansiedad, depresión, fatiga, enfermedades cardiovasculares y mortalidad prematura. El alcance total de esta agrupación de enfermedades, y de los mecanismos que las provocan, están todavía por identificar. A través del análisis de los datos de pacientes de todo un país, el proyecto financiado con fondos europeos PainFACT pretende caracterizar grupos de afecciones médicas asociadas con el dolor crónico. Mediante el uso de datos de imágenes genómicas, proteómicas y encefálicas de última generación de humanos y ratones, PainFACT identificará mecanismos moleculares y desarrollará algoritmos predictivos para el dolor crónico de reciente aparición y la comorbilidad relacionada con el dolor. Se espera que los resultados del proyecto tengan un gran impacto en la clasificación diagnóstica del dolor, la identificación temprana de pacientes con riesgo de multimorbilidad y la identificación de dianas terapéuticas para el desarrollo de nuevos medicamentos.
Objetivo
Chronic pain (CP) is the leading cause of disability, and is strongly associated with fatigue, anxiety and depression ─ also major contributors to disability, and with cardiovascular disease (CVD) and mortality. Twin studies indicate that these associations are a consequence of common causal mechanisms. The main objective of PainFACT is to identify these mechanisms. Using hypothesis-free genomic, proteomic, transcriptomic and brain-imaging discovery in available human studies and in a large cohort of outbred mice with multiple comorbidities, we aim to identify biomarkers that are associated across conditions. Predictive algorithms will be developed through machine learning techniques and tested in prospective analysis. Mendelian randomization approaches will be applied to test for causality. Mechanistic studies will be carried out in validated behavioral and atherosclerotic mouse models. Predictive markers will be tested as possible mediators of effects of lifestyle and obesity. Unique features of this program of research is the strong emphasis on experimental pain models and brain imaging techniques, facilitating translation of findings between mice and humans, and exploitation of the largest study of experimental pain worldwide and of multiple clinical datasets ranging in size from tens of thousands to 1.1 million. A custom protein panel will be developed together with sex and age stratified algorithms, with expected impact for the prediction and monitoring of disease and comorbidity, and for tracking effects of life-style changes. It is also expected that PainFACT results will have major impact on the diagnostic criteria and classification of affective disorders and CP. The identification of novel causal biomarkers will provide new targets for development of medicines and yield new insight into the causes of comorbidity.
Ámbito científico
- social sciencessociologydemographymortality
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- medical and health scienceshealth sciencesnutritionobesity
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SC1-2019-Two-Stage-RTD
Régimen de financiación
RIA - Research and Innovation actionCoordinador
0456 Oslo
Noruega