[Association between DNA methylation clock and obesity-related indicators: A longitudinal twin study].

Objective: To explore the relationship between obesity indicators and DNA methylation clocks acceleration, and to analyze their temporal sequence.

Methods: Data were obtained from two surveys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry. Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip. DNA methylation clocks/acceleration metrics (GrimAA, PCGrimAA and DunedinPACE) were calculated using the DNA methylation online tool (https://dnamage.

Genetics: ucla.edu/) or R code provided by researchers. Obesity indicators included weight, body mass index (BMI), waist circumference, waist-hip ratio, and waist-height ratio. A total of 1 070 twin individuals were included in the cross-sectional analysis, comprising 378 monozygotic (MZ) twin pairs and 155 dizygotic (DZ) twin pairs for within-pair analysis. Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks, as well as their acceleration measures. The longitudinal analysis included 314 twin individuals, comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analysis. Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators. All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.

Results: In the cross-sectional analysis population, monozygotic twins accounted for 71.0%, males for 68.0%, and the mean chronological age was (49.9±12.1) years. In the longitudinal analysis population, monozygotic twins accounted for 60.5%, males for 60.8%, with a mean baseline chronological age of (50.4±10.2) years and a mean follow-up duration of (4.6±0.6) years. Except for the waist-to-hip ratio, which was significantly higher at follow-up compared with baseline, no statistically significant differences were observed in the means of other obesity indicators between baseline and follow-up. Correlation analysis revealed that weight, BMI, waist circumfe-rence, waist-hip ratio (WHR), and waist-height ratio (WHtR) were positively correlated with DunedinPACE in all the twins, with WHtR showing the strongest association (β=0.21, 95%CI: 0.11 to 0.31). Weight and BMI were negatively associated with GrimAA (β=-0.03, 95%CI: -0.05 to -0.01; β=-0.07, 95%CI: -0.12 to -0.02), while weight was negatively associated with PCGrim- AA (β=-0.02, 95%CI: -0.03 to 0.00). However, within-twin-pair analyses showed no statistically significant correlations. Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up, while elevated baseline weight, BMI, and waist circumference might increase PCGrimAA. Higher baseline WHR was associated with increased DunedinPACE at follow-up.

Conclusion: Obesity indicators correlate with DNA methylation clock acceleration metrics. Baseline obesity may influence changes in certain DNA methylation clock indicators over time, suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging. However, these associations may be confounded by shared genetic or environmental factors among the twins.