Christophe Tanguay-Sabourin, Matt Fillingim, Gianluca V Guglietti, Azin Zare, Marc Parisien, Jax Norman, Hilary Sweatman, Ronrick Da-ano, Eveliina Heikkala, PREVENT-AD Research Group, Jordi Perez, Jaro Karppinen, Sylvia Villeneuve, Scott J Thompson, Marc O Martel, Mathieu Roy, Luda Diatchenko, Etienne Vachon-Presseau
This paper is a comprehensive effort to integrate features from different disciplines to better understand, characterize, and predict chronic pain conditions.
Study highlights:
- We developed a psychosocial model using data from the UK Biobank (n= ~ 500k) capable of predicting and characterizing the longitudinal development of chronic pain in healthy individuals and its spreading or recovery in patients.
- The psychosocial model was found to be more closely linked to biological components (functional neuroimaging, genetic and inflammatory risk factors) than pain itself, suggesting that biological factors are more strongly expressed in the psychosocial condition predisposing pain than in the subsequent pain outcomes.
- We show that a variety of chronic pain conditions can be studied from a common psychosocial risk, providing support for the framework of a general chronic pain syndrome.
- We found that the aggregated risk in the biopsychosocial framework may predispose individuals to develop pain at multiple sites, with greater risk associated with a wider spreading of pain across body sites.
If you have any questions, please email Christophe or Matt