Background: Effectively managing chronic widespread pain (CWP) remains a clinical challenge.

Objectives: This study aimed to uncover proteomic biomarkers that could improve the diagnosis and prognosis of different CWP types.

Methods: We analyzed 2,923 plasma proteins from 29,254 participants in the UK Biobank, with 1.6% reporting CWP, defined as pain all over the body. We first modelled univariate association of each protein with CWP using logistic regression. We then created a spare proteomic score (S-ProtS) and a comprehensive proteomic score (C-ProtS) by combing the top 10 and all significant proteins, respectively, using XGBoosting machine learning algorithms. Both scores were compared with a clinical score (CS) derived from key factors, including sleeplessness, feelings of being “fed-up,” tiredness, stressful life events, and a body mass index >30, identified from previous literature [1]. The prospective association of the ProtS (quantile 5 vs quantile 1) and various pain mechanisms was estimated using Poisson regression.

Results: Overall, 811 proteins were associated with CWP after Bonferroni correction. Both S-ProtS and C-ProtS performed similarly to the CS in terms of discrimination, with AUCs of 0.82 (95% CI: 0.77–0.87), 0.88 (95% CI: 0.83–0.92) and 0.81(95% CI: 0.76–0.86), respectively. Incorporating S-ProtS into the CS model enhanced discrimination, yielding an AUC of 0.87 (95% CI: 0.83–0.91) for WCP. A model combining C-ProtS and CS reached the highest discrimination, with an AUC of 0.92 (95% CI: 0.88–0.94). Prospective associations were observed with nociplastic pain (RR of S-ProtS per 1 SD: 1.68 [95%CI:1.52-1.85]; RR of C-ProtS: 1.67 [1.52-1.84]) and particularly with fibromyalgia (RR of S-ProtS: 5.84 [4.29-7.94]; RR of C-ProtS: 5.53 [4.09-7.49]). In contrast, no associations were observed with nociceptive (RR of S-ProtS: 1.06 [0.81-1.38]; RR of C-ProtS: 0.80 [0.60-1.07]) or neuropathic pain (RR of S-ProtS: 1.78 [0.90-3.54]; RR of C-ProtS: 1.47 [0.70-3.07]).

Conclusion: Proteomic signatures improve clinical discrimination to classify and prospectively predict CWP overall and phenotypes. More research is needed to unravel the mechanistic effects of these proteins on the development and progression of CWP.

REFERENCES: [1] Tanguay-Sabourin C, Fillingim M, Guglietti GV, Zare A, Parisien M, Norman J, Sweatman H, Da-Ano R, Heikkala E; PREVENT-AD Research Group; Perez J, Karppinen J, Villeneuve S, Thompson SJ, Martel MO, Roy M, Diatchenko L, Vachon-Presseau E. A prognostic risk score for development and spread of chronic pain. Nat Med. 2023 Jul;29(7):1821-1831. doi: 10.1038/s41591-023-02430-4. Epub 2023 Jul 6. PMID: 37414898; PMCID: PMC10353938.

Acknowledgements: NIL.

Disclosure of Interests: None declared.

© The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.