Yujun Ke,1,2,* Chunlan Wu,3,4,* Zhangren Cheng,5 Min Liang2 

1Department of Anesthesiology, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 2Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, People’s Republic of China; 3Department of Oncology, Molecular Oncology Research Institute, the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People’s Republic of China; 4Department of Oncology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, People’s Republic of China; 5Department of Anesthesiology, Nanping First Hospital Affiliated to Fujian Medical University, Nanping, 353000, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Zhangren Cheng, Department of Anesthesiology, Nanping First Hospital Affiliated to Fujian Medical University, Nanping, 353000, People’s Republic of China, Email 37566794@qq.com Min Liang, Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, People’s Republic of China, Email min.liang@fjmu.edu.cn

Background: Chronic pain is a prevalent and debilitating disorder. However, whether it accelerates aging remains contentious. Epigenetic clocks serve as robust instruments for evaluating biological aging. This study aims to examine the relationship between chronic pain and epigenetic clocks in a nationally representative US sample and discover potential shared systemic mechanisms.
Methods: This research comprised 2,532 individuals aged 50 and above from the 1999– 2002 National Health and Nutrition Examination Survey (NHANES) database. Multivariable logistic regression combined with the propensity score matching (PSM) method was employed to investigate the relationship between chronic pain and six epigenetic clocks across three generations.
Results: There was a substantial correlation between chronic pain and epigenetic age acceleration before adjusting for confounders. This association slightly weakened upon adjustment for sociodemographic characteristics, drug uses, and comorbidities, and was utterly nullified after accounting for lifestyle behaviors. In the PSM model, which employed chronic pain as the dependent variable and included all covariates as predictors, no evidence of epigenetic age acceleration was detected. However, in the PSM model that excluded lifestyle behaviors as predictors, individuals experiencing chronic pain showed faster epigenetic age acceleration on GrimAge [β = 0.94, 95% confidence interval (CI): 0.05 to 1.83] and GrimAge2 [β = 1.14, 95% CI: 0.17 to 2.10].
Conclusion: Our findings highlight the role of lifestyle behaviors as confounders of the pain-aging relationship as potentially alterable risk factors for epigenetic age acceleration. It provides vital guidance for developing public health strategies to promote healthy aging among chronic pain patients.

Keywords: chronic pain, epigenetic clocks, propensity score matching, GrimAge2, NHANES