About
Chronic pain is the leading cause of disability worldwide. Patients who live with chronic pain are comorbid with or vulnerable to develop other neuropsychiatric disorders. These disabling conditions are closely correlated in terms of occurrence and development, and can mutually promote their own severity progress. To date, the corresponding pathophysiological mechanisms of their relationships have not been identified, posing a huge challenge for effective treatments.
This project aims to identify the underlying mechanisms of comorbidities of chronic pain and other neuropsychiatric disorders from a multilevel perspective. This project will include three phases. In the first phase (years 1), we will leverage the social, behavioral, psychological and health-related fields collected by the UK Biobank to find the key overlapped factors of chronic pain and common neuropsychiatric disorders including depression, anxiety, schizophrenia, dementia, addiction, obsessive-compulsive disorder, and insomnia. In the second phase (years 2), we will underpin the neurophysiological factors, including brain MRI patterns, genetic variants, and molecular biomarkers, contributing to the comorbidities of chronic pain and these neuropsychiatric disorders. In the third phase (year 3), we will build machine learning models based on the findings in the first two phases to identify chronic pain patients who are vulnerable to develop neuropsychiatric disorder.
Both chronic pain and neuropsychiatric disorders are enormous public health problems. This project will allow us to provide multiple levels of description for the linked abnormalities in chronic pain and neuropsychiatric disorders, and provide potential biomarkers for the diagnosis and prognosis of complex symptoms. Findings from this project would also serve as therapeutic targets for developing effective treatments.