| Title: | Brain signatures of nociplastic pain: Fibromyalgia Index and descending modulation at population level |
| Journal: | Brain |
| Published: | 17 Aug 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40819274/ |
| DOI: | https://doi.org/10.1093/brain/awaf307 |
| URL: | https://academic.oup.com/brain/advance-article-pdf/doi/10.1093/brain/awaf307/64068935/awaf307.pdf |
Publication 19730
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Abstract
Nociplastic pain is defined by altered nociceptive processing in the absence of clear peripheral damage or somatosensory lesions. The Fibromyalgia Index (FMI), derived from the 2016 diagnostic criteria, is increasingly used as a marker of nociplastic pain severity in clinical studies, yet its neurobiological validity remains untested at scale. Using multimodal neuroimaging data from over 40 000 participants in UK Biobank, we examined whether FMI scores were associated with altered functional and structural connectivity within the descending pain modulatory system (DPMS), a brain network involved in endogenous pain control and implicated in nociplastic pain conditions. Functional connectivity was assessed using resting-state functional MRI (rfMRI), and structural connectivity using diffusion-weighted MRI (dMRI) tractography. Connectivity was quantified between seven DPMS regions: periaqueductal grey (PAG), rostral ventromedial medulla (RVM), hypothalamus, amygdala, rostral and subgenual anterior cingulate cortex (rACC, sgACC), and dorsolateral prefrontal cortex (dlPFC). Multi-group structural equation models tested associations between FMI scores and connectivity, stratified by chronic pain status. Mediation models evaluated which aspects of nociplastic pain accounted for the observed associations: widespread pain and SPACE symptoms (sleep disturbance, pain, affect, cognitive problems, and low energy). To assess specificity, we repeated analyses using the Douleur Neuropathique 4 (DN4), a measure of neuropathic pain, and average pain intensity as comparison outcomes. In 22 139 individuals with chronic pain (58% female; mean age 64.8, standard deviation 7.59), FMI scores were associated with altered structural connectivity between the PAG and amygdala [β = 0.023, 95% confidence interval (CI): 0.0087 to 0.039; Pcorr = 0.0125] and between the PAG and hypothalamus (β = -0.029, 95% CI: -0.043 to -0.015; Pcorr = 0.0013). Functional connectivity in the same circuits showed smaller effects. These associations were not observed in individuals without chronic pain. Mediation analyses revealed that PAG-amygdala and PAG-hypothalamus connectivity were partially explained by fatigue, sleep duration, and widespread pain. DPMS connectivity was not significantly associated with neuropathic pain or average pain intensity. These findings suggest that FMI scores reflect biologically meaningful changes in brain connectivity, particularly in subcortical DPMS circuits implicated in affective and homeostatic dimensions of pain. Structural connectivity was more strongly associated with FMI than functional measures, possibly reflecting cumulative effects of chronic pain on white matter architecture. The absence of similar associations for other pain outcomes supports the specificity of FMI as a marker of nociplastic pain severity. These results provide a neurobiological basis for the FMI and support its use in population research and biomarker development for nociplastic pain.</p>
13 Keywords
- Adult
- Aged
- Brain
- Chronic Pain
- Female
- Fibromyalgia
- Humans
- Magnetic Resonance Imaging
- Male
- Middle Aged
- Neural Pathways
- Nociplastic Pain
- Pain Measurement
9 Authors
- Eoin Maurice Kelleher
- Frederik Lange
- Vishvarani Wanigasekera
- Trishna Rathod-Mistry
- Thomas Nichols
- Ben Seymour
- Irene Tracey
- Andrew Reilly Segerdahl
- Anushka Irani
1 Application
| Application ID | Title |
|---|---|
| 45465 | Deep phenotyping of patients with a range of chronic pain conditions in the UK Biobank using a machine-learning approach. |
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