Fibromyalgia in the UK Biobank: a confirmatory study on the relationship between multimodal neuroimaging and nociplastic pain

**Title **: Fibromyalgia in the UK Biobank: a confirmatory study on the relationship between multimodal neuroimaging and nociplastic pain

Introduction

It is increasingly recognised that pain can be centrally generated, even in the absence of clear evidence of peripheral causes. This phenomenon has been termed nociplastic pain and fibromyalgia is considered its archetypal manifestation. However, many different central mechanisms leading to fibromyalgia and nociplastic pain have been proposed, and it remains unclear whether fibromyalgia represents a heterogenous population or whether it may be characterized by shared CNS changes. Non-invasive neuroimaging techniques have the potential to shed light on this question and to derive brain-based biomarkers for nociplastic pain conditions. Small-scale neuroimaging studies of fibromyalgia patients have yielded mostly conflicting results, reporting increases and decreases in functional connectivity in different studies. A recent study (Fillingim et al., 2025, Nat. Human Behav.) has harnessed a larger population of fibromyalgia patients from the UK Biobank to resolve these discrepancies and identified widespread decreases in functional connectivity in fibromyalgia.

Aims

We aim to (a) directly replicate a previous study (Fillingim et a., 2025, Nat. Human Behav.) reporting changes in functional neuroimaging metrics in UK Biobank participants with a fibromyalgia diagnosis (n = 404) compared to matched controls; (b) extend these analyses to a broader set of UK Biobank participants (n = 41,411) with available information on nociplastic pain experience as part of the UK Biobank’s web-based pain questionnaire.

Methods

We utilised multimodal imaging-derived phenotypes (IDPs), diagnosis information, and pain questionnaires from participants in the UK Biobank. IDPs of interest included structural metrics (e.g. region grey matter volumes), microstructural metrics (e.g. diffusion-weighted imaging metrics from each white matter tract) and functional metrics (e.g. connectivity between nodes). We then applied linear regression to each IDP, testing for the effects of fibromyalgia diagnosis on each of the IDPs in the fibromyalgia-diagnosed cohort; and for associations with the Fibromyalgia Index (Kelleher et al., 2025, Brain) derived from pain questionnaires in the broader set of nociplastic pain participants. Given the limited number of fibromyalgia patients in UK Biobank, covariates were used conservatively to correct only for age, gender and head size. A hierarchical FDR‐correction procedure was used by first computing omnibus p‐values for each modality with a Simes test and then applying a more stringent FDR threshold to modalities that are significant in the Simes test.

Results

Preliminary results recapitulate neuroimaging phenotypes from the published literature.

Conclusions

Using large and openly available biobank neuroimaging datasets has the potential to strengthen confidence in biomarkers for patient cohorts and facilitate translation into impact on clinical trials. Initial results suggest that multimodal neuroimaging has the potential to enable patient segmentation, contributing to improved drug discovery and the progression of precision medicine in pharmaceutical industry.

References

Fillingim, M., Tanguay-Sabourin, C., Parisien, M., Zare, A., Guglietti, G.V., Norman, J., Petre, B., Bortsov, A., Ware, M., Perez, J. and Roy, M., 2025. Biological markers and psychosocial factors predict chronic pain conditions. Nature Human Behaviour, 9(8), pp.1710-1725. Kelleher, E.M., Lange, F., Wanigasekera, V., Rathod-Mistry, T., Nichols, T., Seymour, B., Tracey, I., Segerdahl, A.R. and Irani, A., 2026. Brain signatures of nociplastic pain: Fibromyalgia Index and descending modulation at population level. Brain, 149(4), pp.1365-1380.