Epigenetic Aging Mediates the Association between Pain Impact and Brain Aging in Middle to Older Age Individuals with Knee Pain

ABSTRACT

Chronic musculoskeletal pain is a health burden that may accelerate the aging process. Accelerated brain aging and epigenetic aging have separately been observed in those with chronic pain. However, it is unknown whether these biological markers of aging are associated with each other in those with chronic pain. We aimed to explore the association of epigenetic aging and brain aging in middle-to-older age individuals with varying degrees of knee pain. Participants (57.91 ± 8.04 y) with low impact knee pain (n = 95), high impact knee pain (n = 53), and pain-free controls (n = 26) completed self-reported pain, a blood draw, and an MRI scan. We used an epigenetic clock previously associated with knee pain (DNAmGrimAge), the subsequent difference of predicted epigenetic and brain age from chronological age (DNAmGrimAge-Difference and Brain-PAD, respectively). There was a significant main effect for pain impact group (F (2,167) = 3.847, P = 0.023, $\mathrm{r}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{a}\mathrm{l}\mathrm{e}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y}=1/2\mathrm{I}{\omega }^2$ = 0.038, ANCOVA) on Brain-PAD and DNAmGrimAge-difference (F (2,167) = 6.800, P = 0.001, $\mathrm{I}=\mathrm{m}{\mathrm{k}}^2$ = 0.075, ANCOVA) after controlling for covariates. DNAmGrimAge-Difference and Brain-PAD were modestly correlated (r =0.198; P =0.010). Exploratory analysis revealed that DNAmGrimAge-difference mediated GCPS pain impact, GCPS pain severity, and pain-related disability scores on Brain-PAD. Based upon the current study findings, we suggest that pain could be a driver for accelerated brain aging via epigenome interactions.

KEYWORDS:

• Epigenetics
• chronic pain
• brain aging
• aging
• musculoskeletal pain

Acknowledgements

The authors would like to thank the research team and the participants for their time to help complete this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

J. Peterson and L. Strath contributed to the writing of the manuscript equally and share first authorship. J. Peterson and Y. Cruz-Almeida conceptualized the research question and J. Peterson drafted the introduction, computed the statistical analysis, and drafted the results. J. Peterson, L. Strath and Y. Cruz-Almeida interpreted the data and critically discussed findings. C. Laffitte-Nodarse performed and interpreted brain aging calculations from the MRI scans and reviewed the manuscript. A. Rani and S. Yoda were actively involved in obtaining and deriving the epigenetic data and reviewed the manuscript. L. Meng and Z. Huo performed epigenetic aging calculations, their interpretations and reviewed the manuscript. J. Cole, T.C. Foster, R.B. Fillingim edited and reviewed the manuscript for critical feedback. Y. Cruz-Almeida obtained funding, guided the papers’ progress, edited and reviewed the manuscript for critical feedback. All authors contributed to the paper and approved paper for submission for peer review.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Notes

1. https://github.com/james-cole/brainageR

Additional information

Funding

This work was supported by the National Institutes of Health [R37AG033906, R01AG067757, R01AG059809].