Descrizione del progetto
Individuare i meccanismi molecolari dei disturbi legati al dolore
I pazienti affetti da dolore cronico tendono a soffrire di numerose condizioni patologiche concomitanti, tra cui ansia, depressione, affaticamento e malattie cardiovascolari, oltre ad essere vittime di mortalità prematura. Restano tuttora da individuare la piena portata della combinazione di queste malattie e i meccanismi alla sua base. Analizzando dati di pazienti relativi a un intero paese, il progetto PainFACT, finanziato dall’UE, intende caratterizzare le patologie mediche associate al dolore cronico. Avvalendosi di dati su esseri umani e topi concernenti vari campi all’avanguardia, quali genomica, proteomica e immaginografia cerebrale, PainFACT individuerà i meccanismi molecolari e svilupperà algoritmi predittivi per il dolore cronico di nuova insorgenza e la comorbilità legata al dolore. Si prevede che i risultati del progetto avranno un importante impatto sulla classificazione diagnostica del dolore, sull’individuazione precoce dei pazienti a rischio di multimorbilità e sull’identificazione di obiettivi di trattamento per lo sviluppo di nuovi farmaci.
Obiettivo
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.
Campo scientifico
- social sciencessociologydemographymortality
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- medical and health scienceshealth sciencesnutritionobesity
Parole chiave
Programma(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-SC1-2019-Two-Stage-RTD
Meccanismo di finanziamento
RIA - Research and Innovation actionCoordinatore
0456 Oslo
Norvegia