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. 2025 Jan 21;15(2):155.
doi: 10.3390/biom15020155.

A Genetic and Environmental Analysis of Inflammatory Factors in Chronic Widespread Pain Using the TwinsUK Cohort

Stacey S Cherny  1 , Gregory Livshits  2 , Frances M K Williams  3
Affiliations

A Genetic and Environmental Analysis of Inflammatory Factors in Chronic Widespread Pain Using the TwinsUK Cohort

Stacey S Cherny et al. Biomolecules. .

Abstract

Chronic widespread musculoskeletal pain (CWP), a significant health issue affecting individuals and society, is often diagnosed as part of fibromyalgia but is not generally considered inflammatory. This study investigated the relationship between blood-based inflammatory factors and CWP in 904 individuals from the TwinsUK cohort. Participants, free of major inflammatory conditions, completed questionnaires to assess CWP. Plasma samples were analysed using the Olink panel, alongside assays for C-reactive protein (CRP) and Apolipoproteins A1 and B. No significant associations were observed between CWP and inflammatory factors after adjusting for multiple testing. Twin modelling revealed significant heritability for both CWP and inflammatory factors, with genetic covariance observed between CWP and several inflammatory factors. Additive Bayesian network modelling suggested that any association between CWP and inflammatory factors is mediated by body mass index (BMI). These findings emphasize the complexity of CWP and its potential reliance on factors beyond inflammation, such as BMI, which strongly correlates with CRP and other inflammatory markers. Future research should explore additional molecular, genetic, and environmental contributors to CWP variability and investigate clinical factors or covariates that may obscure relationships with inflammation, providing a more comprehensive understanding of this multifaceted condition.

Keywords: CWP; Olink; TwinsUK; chronic widespread pain; fibromyalgia; inflammation.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Four QQ plots of p-values for CWP regressed on 73 inflammatory factors, grouped by function (pro-inflammatory, anti-inflammatory, immunoregulatory, and multifunctional), controlling for age and age-squared, as well as family membership. This demonstrates lack of signal detected when considering multiple testing of four sets of inflammatory factors, with all observed p-values not differing much from that expected under the null hypothesis.
Figure 2
Figure 2
Phenotypic correlation matrix among 10 variables obtained from estimating genetic, shared environmental, and nonshared environmental covariances in a multivariate twin model.
Figure 3
Figure 3
Phenotypically standardized genetic covariance matrix in the upper triangle, genetic correlation matrix in the lower triangle, with heritabilities along the diagonal in bold.
Figure 4
Figure 4
Phenotypically standardized shared environmental covariance matrix in the upper triangle, shared environmental correlation matrix in the lower triangle, with shared environmental variances along the diagonal in bold.
Figure 5
Figure 5
Phenotypically standardized nonshared environmental covariance matrix in the upper triangle, nonshared environmental correlation matrix in the lower triangle, with nonshared environmental variances along the diagonal in bold.
Figure 6
Figure 6
Directed acyclic graph resulting from fitting an additive Bayesian network model to six inflammatory factors plus log(BMI) and log(CWP).
Figure 7
Figure 7
Directed acyclic graph resulting from fitting an additive Bayesian network model to log(CRP), log(BMI), ApoA1, ApoB, and CWP.
See this image and copyright information in PMC

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