ArticleNature human behaviour2025
Biological markers and psychosocial factors predict chronic pain conditions.
Article in Nature human behaviour, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A transdisciplinary framework for chronic illness and chronic pain: a sequential qualitative meta-synthesis.Frontiers in public health · 2026Pooled it
- Unmet needs in functional neurological disorder related to digital healthcare.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2026Review
- Peritraumatic C-reactive protein levels predict pain outcomes following traumatic stress exposure in a sex-dependent manner.The journal of pain · 2026Article
- From Association to Prediction: Translational Barriers in Pain Biomarker Research.Journal of personalized medicine · 2026Article
- Development and validation of a clinical prediction model for acupuncture response in community-dwelling patients with chronic low back pain: a retrospective cohort study.BMC health services research · 2026Article
- Linking the exposome to the brain-behaviour phenotype.Nature reviews. Neuroscience · 2026Review
- Differential brain response to a highly palatable drink in chronic low back pain patients.Journal of neurophysiology · 2026Article
- Molecular mechanism of allosteric modulation of opioid receptors.Signal transduction and targeted therapy · 2026Article
- Presurgical immune biomarkers associated with pain intensity and pain interference recovery after total knee arthroplasty: findings from the PRIME-KNEE study.medRxiv : the preprint server for health sciences · 2026Article
- Physiological Adaptations and Serum-Based Biomarker Dynamics During Multimodal Rehabilitation in Chronic Pain: Analysis of a Prospective Cohort Study.Biomolecules · 2026Article
- Targeting Microglia-Neuron Crosstalk to Regulate Neuronal Excitability: Novel Translational Approaches for Chronic Pain Intervention.International journal of molecular sciences · 2026Review
- Predicting the course of high-impact chronic pain using machine learning algorithms.The journal of pain · 2026Article
- Article
- From pain mechanisms to functioning: a rehabilitation perspective on fibromyalgia.European journal of physical and rehabilitation medicine · 2026Article
- Threading the Needle: Practical Considerations for Merging Theory-Driven Computational Psychiatry With Data-Driven Analytics to Enhance Precision Health at Scale.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Review
- Neuroimaging-Guided Insights into the Molecular and Network Mechanisms of Chronic Pain and Neuromodulation.International journal of molecular sciences · 2026Review
- Multisite Chronic Pain Reveals Neuro-Immune-Metabolic Dysregulation across Rheumatoid Arthritis and Depression.Research (Washington, D.C.) · 2026Article
- New insight into RNA biomarkers in neuropathic pain: a clinician-neuroscientist roadmap to translational testing and treatment monitoring a clinical review.Frontiers in pain research (Lausanne, Switzerland) · 2026Review
- Recent advances in biomarkers for cardiac fibrosis.Frontiers in cardiovascular medicine · 2026Review
- The emergence of sex differences in primary pain during adolescence: a conceptual developmentally-oriented biopsychosocial model and opportunities for further investigation.BMC pediatrics · 2025Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Chronic pain is a multifactorial condition presenting significant diagnostic and prognostic challenges. Biomarkers for the classification and the prediction of chronic pain are therefore critically needed. Here, in this multidataset study of over 523,000 participants, we applied machine learning to multidimensional biological data from the UK Biobank to identify biomarkers for 35 medical conditions associated with pain (for example, rheumatoid arthritis and gout) or self-reported chronic pain (for example, back pain and knee pain). Biomarkers derived from blood immunoassays, brain and bone imaging, and genetics were effective in predicting medical conditions associated with chronic pain (area under the curve (AUC) 0.62-0.87) but not self-reported pain (AUC 0.50-0.62). Notably, all biomarkers worked in synergy with psychosocial factors, accurately predicting both medical conditions (AUC 0.69-0.91) and self-reported pain (AUC 0.71-0.92). These findings underscore the necessity of adopting a holistic approach in the development of biomarkers to enhance their clinical utility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.