The Function of Lifestyle Behaviors in Shaping the Relationship between Ch

Introduction

Chronic ache, outlined as ache persisting for 3 months or longer, is a prevalent and debilitating dysfunction affecting an estimated 11% to 40% of the worldwide inhabitants,¹ leading to important incapacity and socio-economic challenges globally.² Advanced age is acknowledged as an unbiased threat issue for persistent ache,³ but the notion that persistent ache accelerates growing older stays contentious. Particular lecturers have famous indicators of expedited growing older in people with persistent ache, corresponding to diminished life expectancy,⁴ elevated mortality charges,⁵ shortened telomere lengths,⁶ and accelerated mind growing older.⁷ However, different students haven’t recognized such a correlation.^8,9

Epigenetic clocks, derived from DNA methylation (DNAm) patterns, successfully quantify a person’s organic age and exhibit robust correlations with the prevalence of age-related persistent ailments and the chance of age-associated mortality, providing a strong instrument for assessing the organic growing older course of.¹⁰ The development of epigenetic clocks offers novel insights for a complete examination of the correlation between ache and growing older. The Yenisel Cruz-Almeida’s group^11,12 and Edwin N. Aroke’s group¹³ recognized connections between epigenetic age acceleration and pain-related metrics, corresponding to ache standing, depth, incapacity, and pain-associated depressive signs. However, sure analysis has indicated that various ache phenotypes don’t lead to expedited alterations in epigenetic age.¹⁴ Nonetheless, these cohort research exhibited restricted pattern numbers and inadequate inhabitants selection for comparative evaluation.

Furthermore, quite a few research point out that confounders linked to persistent ache, together with sociodemographics,^15,16 analgesic consumption,¹⁷ comorbidities,¹⁸ and way of life behaviors,^19,20 additionally exert some affect on the epigenetic clock. A complete examination of pertinent confounders within the relationship between persistent ache and epigenetic growing older may facilitate the invention of shared systemic mechanisms that will function targets for intervention or therapy. Additionally, researchers have just lately developed an enhanced model of GrimAge, termed GrimAge2. GrimAge2 has demonstrated enhanced efficacy in forecasting mortality charges throughout multi-ethnic teams and age-related problems relative to GrimAge.²¹ To our information, no analysis has but employed GrimAge2, this potent epigenetic clock, to analyze the correlation between persistent ache and epigenetic age acceleration. Therefore, the target of this examine was to make use of the National Health and Nutrition Examination Survey (NHANES) database, incorporating three generations of six epigenetic clocks, together with GrimAge2, to totally study the intricate relationships between persistent ache and epigenetic clocks in a nationally consultant US pattern, with the intent of figuring out potential shared systemic processes and figuring out probably the most appropriate persistent pain-related epigenetic clocks.

Methods

Study Population

NHANES is a major public well being survey administered by the National Centre for Health Statistics (NCHS) that gives important information for analyzing the well being and dietary standing of the US non-institutionalized inhabitants. NHANES makes use of a stratified multistage sampling approach to accumulate a consultant pattern of US inhabitants. All individuals submitted written knowledgeable permission on the time of recruitment. This examine utilized de-identified NHANES information, and the Ethics Committee of the First Affiliated Hospital of Fujian Medical University exempted additional Institutional Review Board evaluation of those information, adhering to the rules of the US Department of Health and Human Services.²² This examine used information from two successive NHANES cycles (1999–2000, 2001–2002) to look at the connection between persistent ache and epigenetic clocks. Participants have been chosen based mostly on the provision of each blood DNAm information and completion of the Miscellaneous Pain Questionnaire (MPQ). The remaining cohort comprised 2,532 people aged 50 or older, with the recruitment course of illustrated in Figure 1.

Figure 1 Flow chart of participants selection. Abbreviation: NHANES, National Health and Nutrition Examination Survey.

Assessment of Chronic Pain

Information regarding the duration and location of self-reported pain was gathered from respondents aged 20 and older through a series of home interview questions. Participants who had endured pain exceeding 24 hours in the preceding month were subsequently inquired about the duration of their discomfort. The 11th version of the International Classification of Diseases (ICD-11) defines chronic pain as pain persisting for over three months.²³ Consequently, individuals enduring discomfort for over three months (MPQ100 = 1, MPQ110 = 3 or 4) have been designated because the persistent ache group, and the rest have been labeled because the non-chronic ache group.

Epigenetic Age and Epigenetic Age Acceleration

Samples from people aged 50 and above who had undergone whole-blood DNA purification, have been obtained for DNAm evaluation. The evaluation was carried out at Duke University laboratory utilizing Illumina EPIC microbead chip arrays. Raw methylation information in IDAT format was processed for preprocessing and normalization. Details of the DNAm epigenetic clocks are documented within the DNA Methylation Array and Epigenetic Biomarkers Data Documentation. We calculated six epigenetic clocks throughout three generations, comprising the primary era (Horvath’s epigenetic age,²⁴ Hannum’s epigenetic age²⁵), the second era (PhenoAge,²⁶ GrimAge,²⁷ GrimAge2),²¹ and the third era [Dunedin Pace of Aging methylation (DunedinPoAm)²⁸]. For the primary and second generations, we decided age-adjusted epigenetic age acceleration, which is the residual from the linear regression of epigenetic age on chronological age. This algorithm encompassed Horvath’s epigenetic age acceleration, Hannum’s epigenetic age acceleration, PhenoAge acceleration (PhenoAgeAccel), GrimAge acceleration (GrimAgeAccel), and GrimAge2 acceleration (GrimAge2Accel), all quantified in items of years. Epigenetic age acceleration, slightly than uncooked epigenetic age, is extra strongly linked to the chance of age-related problems and mortality. The distinction between a person’s epigenetic age and chronological age might higher predict well being outcomes associated to growing older. Therefore, we targeted on the correlation between persistent ache and epigenetic age acceleration.

Covariate Information

This examine categorized the covariates that will affected the connection between persistent ache and epigenetic clocks into sociodemographic traits, drug makes use of, comorbidities, and way of life behaviors. Sociodemographic traits included age (years); intercourse (female and male); ethnicity (non-Hispanic Black, non-Hispanic White, Mexican American, and different races); training degree (lower than highschool, highschool graduate, some faculty, and faculty graduate); poverty revenue ratio (PIR; PIR < 1, and PIR ≥ 1); and marital standing (married and different standing). Drug makes use of included analgesic use and antidepressant use. Analgesic use was outlined as taking prescription or over-the-counter ache relievers nearly each day for a month, and antidepressant use was outlined as taking no less than one prescribed antidepressant treatment prior to now 30 days. Comorbidities encompassed hypertension, diabetes, coronary heart illness, most cancers, bronchial asthma, and arthritis. Hypertension, diabetes, most cancers, bronchial asthma, and arthritis have been characterised as circumstances recognized by a doctor. Heart illness was characterised by a analysis of congestive coronary heart failure, coronary coronary heart illness, angina, or myocardial infarction, any of which certified as a sort. Lifestyle behaviors encompassed smoking standing (by no means: < 100 cigarettes/life; former: ≥ 100 cigarettes/life and ceased smoking; present: ≥ 100 cigarettes/life and nonetheless smoking); alcohol consumption (non-drinker: < 12 alcoholic drinks/12 months; drinker: ≥ 12 alcoholic drinks/12 months); physique mass index (BMI; underweight: < 18.5 kg/m², regular weight: 18.5–24.9 kg/m², chubby: 25.0–29.9 kg/m², and overweight: ≥ 30.0 kg/m²); and bodily exercise (PA). The PA degree was assessed based mostly on individuals’ involvement in average and vigorous bodily actions throughout leisure time over the previous 30 days. It was divided into no PA, inadequate PA for these below 150 minutes per week, and enough PA for these over 150 minutes per week.²⁹

Statistical Analyses

Statistical analyses have been carried out utilizing R (model 4.3.3). Due to the intricate multistage likelihood sampling design of NHANES, all analyses utilized weights, strata, and first sampling items as stipulated by the NHANES Analytic Guidelines. A small share of individuals on this examine displayed lacking information for variables. Examining the absent information sorts with the R’s “mi” package deal (model 1.1) revealed a “Clustered by missingness” sample, suggesting that the information deficiency was not wholly random. Therefore, we employed the Multiple Imputation by Chained Equations technique to generate a number of imputations of the lacking information throughout 5 separate datasets, with every interpolated dataset analyzed independently and consolidated the outcomes.

Categorical variables have been illustrated as weighted percentages, whereas steady variables have been offered as means with normal deviations. Categorical variables have been in contrast utilizing Chi-squared assessments, whereas steady variables have been in contrast utilizing the Complex Samples General Linear Model. Five weighted linear regression fashions have been developed to guage the connection between persistent ache and epigenetic clocks. Model 1 was the crude mannequin. Model 2 included changes for sociodemographic traits derived from Model 1. Model 3 additional accounted for drug makes use of constructing upon Model 2. Model 4 enhanced Model 3 by incorporating changes for comorbidities. The remaining totally adjusted mannequin (Model 5) enhanced Model 4 by incorporating way of life habits variables.

To improve the validity of the outcomes, we employed the propensity rating matching (PSM) technique for sensitivity evaluation. We fitted two PSM fashions, every using persistent ache because the dependent variable however encompassing distinct predictor variables. PSM Model 1 encompassed all covariates, together with sociodemographic traits, drug makes use of, comorbidities, and way of life behaviors as predictors, whereas PSM Model 2 excluded way of life behaviors as predictors. We calculated every participant’s propensity rating utilizing multivariable logistic regression and matched persistent and non-chronic ache individuals at a 1:1 ratio utilizing nearest neighbor matching with a caliper width of 0.2 normal deviations. Balance was assessed by absolutely the standardized imply distinction (ASMD), with an ASMD worth lower than 0.1 signifying ample covariate stability.³⁰ Simultaneously, we produced kernel density estimation to visualise the distribution of propensity scores earlier than and after matching. Considering NHANES’s advanced pattern design, we created a brand new sampling weight by dividing every participant’s weight by the examine’s common weight and included it into the evaluation. These PSM procedures have been carried out utilizing R’s “MatchIt” package deal (model 4.5.5).

Results

Characteristics of the Study Population

The examine encompassed 2,532 people, with 396 assigned to the persistent ache cohort and a couple of,136 to the non-pain cohort (Table 1). Notable variations in baseline traits between the 2 teams have been evident, as indicated by their ASMD exceeding 0.1. The most pronounced discrepancies have been within the prevalence of arthritis (ASMD = 0.629), adopted by weight problems (ASMD = 0.355), and using analgesics (ASMD = 0.269). Chronic ache victims tended to be youthful, have a decrease revenue ratio, exhibit greater charges of analgesic antidepressant utilization, exhibit weight problems, have interaction in minimal PA, smoke presently, and endure from comorbidities related to hypertension, heart problems, and arthritis (all P < 0.05).

Table 1 Baseline Characteristics of the Study Population by Chronic Pain Status (n = 2532)

Association Between Chronic Pain and Epigenetic Age Acceleration

Table 2 presents a collection of weighted linear regression fashions that discover the hyperlink between persistent ache and 6 epigenetic clocks throughout three generations. No important variations have been recognized between persistent ache and the first-generation clocks (Horvath and Hannum) and the second-generation PhenoAge clock in any of the fashions. By distinction, people with persistent ache have been noticed to have considerably quicker epigenetic age acceleration on GrimAgeAccel (β = 1.46, 95% CI: 0.65 to 2.27, P < 0.001), GrimAge2Accel (β = 1.67, 95% CI: 0.81 to 2.50, P < 0.001), and DunedinPoAm (β = 0.03, 95% CI: 0.01 to 0.04, P < 0.01) within the crude mannequin in comparison with these with out persistent ache. However, when incremental changes have been made for sociodemographic traits, drug makes use of, and comorbidities, the power of those associations weakened. In Model 4, the affiliation was diminished to 1.15 years for GrimAgeAccel (95% CI: 0.27 to 2.03, P < 0.05), 1.24 years for GrimAge2Accel (95% CI: 0.30 to 2.19, P < 0.05), and the acceleration for DunedinPoAm grew to become almost negligible (95% CI: 0 to 0.04, P < 0.05). Finally, additional changes for way of life habits variables in Model 5 fully attenuated the noticed associations throughout all epigenetic clocks.

Table 2 Weighted Linear Regression Analysis of the Association Between Chronic Pain and Epigenetic Age Acceleration (n = 2532)

Sensitivity Analyses

The PSM Model 1 matched 389 pairs (totaling 778 individuals) between those with chronic pain and those without, while PSM Model 2 matched 395 pairs (totaling 790 individuals). Both PSM models achieved a balanced distribution across all covariates, as demonstrated by the kernel density plots in eFigure 1, which delineates the distribution of propensity scores before and after matching, alongside the sample characteristics and standardized mean differences detailed in eTable 1 and eTable 2.

Figure 2 presents the correlations between persistent ache and 6 epigenetic clocks throughout three generations after matching. In PSM Model 1, there was no important correlation between persistent ache and any of the epigenetic clocks. However, in PSM Model 2, people experiencing persistent ache confirmed quicker epigenetic age acceleration on GrimAgeAccel (β = 0.94, 95% CI: 0.05 to 1.83) and GrimAge2Accel (β = 1.14, 95% CI: 0.17 to 2.10). Notably, the affiliation between persistent ache and DunedinPoAm didn’t attain statistical significance.

Figure 2 Forest plots of the association between chronic pain and epigenetic age acceleration after matching in different models. Abbreviations: PSM, propensity score matching; CI, confidence interval; DunedinPoAm, Dunedin Pace of Aging methylation. Notes: (A) PSM Model 1 (n = 778): employed chronic pain as the dependent variable and encompassed sociodemographic characteristics, drug uses, comorbidities, and lifestyle behaviors as predictors; (B) PSM Model 2 (n = 790): employed chronic pain as the dependent variable and excluded lifestyle behaviors as predictors. ΔHorvath: Horvath’s epigenetic age acceleration; ΔHannum: Hannum’s epigenetic age acceleration; ΔPhenoAge: PhenoAge acceleration; ΔGrimAge: GrimAge acceleration; ΔGrimAge2: GrimAge2 acceleration.

Discussion

This study employed multivariable logistic regression combined with the PSM method to investigate the presence of epigenetic age acceleration in middle-aged and older Americans suffering from chronic pain between 1999 and 2002. Our findings yielded two significant insights. Firstly, no correlation was observed between chronic pain and epigenetic age acceleration after controlling for sociodemographic characteristics, drug uses, comorbidities, and lifestyle behaviors, with lifestyle behaviors identified as potentially modifiable risk factors. Secondly, among the various epigenetic clocks developed, the GrimAge2 clock demonstrated the highest sensitivity to epigenetic alterations linked to chronic pain.

The current study demonstrated notable differences between the chronic pain and non-chronic pain cohorts for various baseline variables. Patients with chronic pain were typically younger, possessed a lower socioeconomic status, were more likely to take analgesics and antidepressants, engaged in less healthy lifestyle behaviors, and were accompanied by related comorbidities. These findings were primarily congruent with prior epidemiological research on chronic pain, aside from the age covariate.^31–34 Chronic ache is extra prevalent within the aged in comparison with youthful people; nonetheless, this examine targeted on middle-aged and older individuals aged 50 and above, rendering the age distinction clinically insignificant. Epigenetic growing older, like persistent ache, is a multifaceted course of formed by numerous inside and exterior elements. Research on persistent ache and epigenetic growing older might uncover shared systemic mechanisms that could possibly be focused for intervention or therapy.

Consequently, the collection of covariates within the present examine was undertaken extra remarkably than in prior analysis, together with the examine by Edwin N. Aroke’s group,¹³ which adjusted solely for gender, race, and BMI, and the latest examine by Yenisel Cruz-Almeida’s group,³⁵ which ignored comorbidities within the aged inhabitants. Furthermore, in distinction to different analysis, the present examine employed the PSM technique mixed with multivariable regression correction to mitigate choice bias from confounding elements. In observational research, the PSM technique is superior to conventional regression adjustment because it mitigates confounding by using propensity scores unbiased of the examine final result. This distinction permits for a extra exact separation between examine design and evaluation, thereby extra precisely simulating a randomized managed trial. At the identical time, conventional regression adjustment might contain subjective selections relating to the variable choice and mannequin specification.³⁶ In our examine, sensitivity evaluation enhanced the reliability of the findings, the attenuation of the affiliation underscores the importance of way of life behaviors within the hyperlink between persistent ache and epigenetic age acceleration as probably alterable threat elements.

Prior analysis has demonstrated a organic connection between persistent ache and epigenetic growing older. Epigenetic alterations, particularly DNAm, might affect damage and ache notion by modulating the expression of pro-injurious and anti-injurious genes inside the damage pathway;³⁷ concurrently, accelerated DNAm reprogramming might contribute to the chronicity of ache.³⁸ Additionally, persistent stress and neuroinflammation linked to persistent ache might promote DNA harm and mobile senescence accumulation, expediting epigenetic growing older.³⁹ Our analysis indicated that, alongside direct organic connections, confounding variables, significantly way of life behaviors, considerably affect the connection between persistent ache and epigenetic growing older. This discovery aligned with latest analysis indicating that epigenetic growing older is a multifaceted organic phenomenon intricately linked to the subjective expertise of ache and influenced by an amalgamation of organic, psychological, social, and environmental components.⁴⁰ Lifestyle behaviors supply a extra accessible goal for change amongst persistent ache sufferers than different confounders, significantly relating to unhealthy behaviors corresponding to smoking, alcohol abuse, bodily inactivity, and weight problems.⁴¹ Consequently, this examine offers important steerage for growing personalised public well being interventions to advertise wholesome growing older amongst sufferers with persistent ache.

This examine assessed the hyperlink between persistent ache and three generations of epigenetic clocks, our findings revealed that the second-generation clock, GrimAge, and its spinoff, GrimAge2, exhibited heightened sensitivity to pain-related epigenetic alterations, supporting the findings of prior researchers.^11,35 Developed utilizing 1,030 distinct CpG websites close to genes in numerous gene units, together with MHC class II genes, cytokine-mediated signaling pathways, and genes from the GO, KEGG, and PANTHER databases, the GrimAge-associated clock covers extra CpG websites than different epigenetic clocks. The genes adjoining to those websites contain a wider vary of organic processes and features. Additionally, the GrimAge-associated clock additionally exhibits a stronger reference to psychological temper fluctuations, corresponding to autism⁴² and despair,⁴³ suggesting its potential effectiveness in comprehending the epigenetic growing older related to persistent ache, which is influenced by a posh interaction of organic, psychological, social, and environmental elements. More importantly, our examine demonstrated for the primary time that GrimAge2 surpasses the unique GrimAge in evaluating epigenetic alterations in persistent ache. GrimAge2 employs the equivalent 1030 CpG websites and, along with the unique GrimAge’s incorporation of chronological age, feminine intercourse indicator, and eight DNAm biomarkers, add two novel biomarkers: high-sensitivity C-reactive protein and hemoglobin A₁C. These further biomarkers improve the evaluation of a person’s organic age and well being standing, probably resulting in a extra strong correlation with age-related phenotypes. Further analysis is required to completely consider GrimAge2’s function in epigenetic modifications related to persistent ache.

Our work possesses a number of options. Firstly, within the examine design, we meticulously examined the intricate relationship between persistent ache and epigenetic clocks, and the collection of covariates was rigorously evaluated, rendering it extra full than prior research. For the primary time, this work included six epigenetic clocks spanning three generations, together with the novel GrimAge2 clock, thereby enhancing the information out there for elucidating the connection between persistent ache and epigenetic growing older. We employed multivariable logistic regression mixed with the PSM technique, thereby augmenting the robustness and trustworthiness of our findings. Indeed, our examine has a number of limitations. Like different cross-sectional research, this analysis can solely set up associations, not causations. The connection between persistent ache and epigenetic age acceleration might be bidirectional, necessitating future longitudinal investigations. Additionally, regardless of the examine accounting for organic, social, and environmental confounders, unrecognized or uncontrolled confounders influencing the outcomes should exist, corresponding to psychological well being points. The 1999–2002 NHANES completely evaluated the psychological well being situation of adults aged 20 to 39, and the shortage of psychological well being information might affect our evaluation of the connection between persistent ache and epigenetic clocks within the middle-aged and older demographic. In addition, the NHANES database’s limitations precluded the analysis of extra granular information regarding ache length, ache depth, and practical interference, thus constraining our capability to analyze the dose-response relationship between persistent ache and accelerated epigenetic growing older. Future investigations on the dose-response relationship are important. Furthermore, for the third-generation epigenetic clock, the prevailing NHANES database offers information solely on DunedinPoAm, limiting our potential to look at it with the extra superior Dunedin Pace of Aging Calculated from the Epigenome (DunedinPACE) clock. Subsequent analysis on persistent ache and DunedinPACE is important.

Conclusions

In middle-aged and older individuals within the United States affected by persistent ache, way of life behaviors function confounders within the pain-aging affiliation and symbolize modifiable threat elements for epigenetic age acceleration. This provides important path for formulating public well being insurance policies to reinforce wholesome growing older in people with persistent ache. Moreover, among the many numerous epigenetic clocks developed, the GrimAge2 clock has probably the most sensitivity to epigenetic alterations linked to persistent ache, positioning it as a promising biomarker within the epigenetic investigation of ache.

Data Sharing Statement

The datasets generated and/or analyzed for this examine could be discovered within the NHANES web site (https://www.cdc.gov/nchs/nhanes/).

Acknowledgments

The authors specific their gratitude to the National Health and Nutrition Examination Survey volunteers.

Funding

This analysis was supported by Nanping Science and Technology Innovation Joint Funding Project [grant number N2024LH022].

Disclosure

The authors report no conflicts of curiosity on this work.

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