Chronic pain conditions are complex syndromes characterized by a mosaic of biological, psychological, and social factors. We derived predictive models for the number of co-existing pain sites in the UK Biobank and identified a common risk score that classified different chronic pain conditions in cross-sectional data, predicted the development of chronic pain in pain-free individuals, and determined the spreading of chronic pain to multiple sites or its recovery nine years later. The features with the strongest prognosis included sleeplessness, feeling 'fed-up', tiredness, stressful life events, and a BMI > 30. The risk score for pain was associated with an inflammatory blood marker, a polygenic risk score for pain, and a neuroimaging-based marker for sustained pain. The demonstration of a common biopsychosocial risk factor for different clinical pain conditions may help better characterize a general chronic pain syndrome, tailor research protocols, optimize patient randomization in clinical trials, and improve pain management.

The authors have declared no competing interest.

This work was primarily supported by the Canadian Institutes of Health Research (CIHR), #RN441786 - 45309. This research has been conducted in part using the UK Biobank Resource under Application Number 20802.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All participants provided written, informed consent, and the study was approved by the North West Multi-centre Research Ethics Committee (REC number 11/NW/0382) to obtain and disseminate data and samples from the participants (http://www.ukbiobank.ac.uk/ethics/), and these ethical regulations cover the work in this study. Written informed consent was obtained from all participants.

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All data are provided from the UK Biobank and available to other investigators online upon permission granted by www.ukbiobank.ac.uk. Restrictions apply to the availability of these data, which were used under license for the current study (Project ID: 20802).