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Journal of Peking University (Health Sciences) ›› 2025, Vol. 57 ›› Issue (3): 456-464. doi: 10.19723/j.issn.1671-167X.2025.03.008

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

Shunkai LIU1,2, Weihua CAO1,2, Jun LV1,2, Canqing YU1,2, Tao HUANG1,2, Dianjianyi SUN1,2, Chunxiao LIAO1,2, Yuanjie PANG1,2, Runhua HU1,2, Ruqin GAO3, Min YU4, Jinyi ZHOU5, Xianping WU6, Yu LIU7, Wenjing GAO1,2,*(), Liming LI1,2   

  1. 1. Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
    2. Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
    3. Qingdao Center for Disease Control and Prevention, Qingdao 266033, Shandong, China
    4. Zhejiang Center for Disease Control and Prevention, Hangzhou 310051, China
    5. Jiangsu Center for Disease Control and Prevention, Nanjing 210008, China
    6. Sichuan Center for Disease Control and Prevention, Chengdu 610041, China
    7. Heilongjiang Center for Disease Control and Prevention, Harbin 150090, China
  • Received:2025-02-08 Online:2025-06-18 Published:2025-06-13
  • Contact: Wenjing GAO
  • Supported by:
    National Natural Science Foundation of China(82373659); National Natural Science Foundation of China(82073633); National Natural Science Foundation of China(81573223); Special Fund for Health Science Research in the Public Welfare(201502006); Special Fund for Health Science Research in the Public Welfare(201002007)

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Abstract:

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.

Key words: Obesity, DNA methylation, Aging, Twin study, Genetic epigenesis

CLC Number: 

  • R181.33

Table 1

The characteristics of study participants"

Characteristics Overall samples (n=1 070) Baseline (n=314) Follow-up (n=314) P value
Demographic characteristics
  Chronological age/years, ${\bar x}$±s 49.9±12.2 50.4±10.2 55.0±10.1 < 0.001
  Gender, n(%)
    Male 728 (68.0) 191 (60.8)
    Female 342 (32.0) 123 (39.2)
  Zygosity, n(%)
    MZ 760 (71.0) 190 (60.5)
    DZ 310 (29.0) 124 (39.5)
  Smoking status, n(%) 0.450
    Never smoked 585 (54.7) 190 (60.5) 188 (59.9)
    Former smoker 138 (12.9) 26 (8.3) 35 (11.1)
    Current smoker 347 (32.4) 98 (31.2) 91 (29.0)
  Alcohol consumption, n(%) < 0.001
    Never drank 549 (51.3) 148 (47.1) 89 (28.3)
    Former drinker 71 (6.6) 10 (3.2) 139 (44.3)
    Current drinker 450 (42.1) 156 (49.7) 86 (27.4)
  Physical activity level, n(%) < 0.001
    High 519 (48.5) 43 (13.7) 117 (37.3)
    Moderate 186 (17.4) 79 (25.2) 69 (22.0)
    Low 365 (34.1) 192 (61.1) 128 (40.8)
Obesity indicators
  Weight/kg, ${\bar x}$±s 65.0±12.1 62.3±11.6 62.4±11.4 0.899
  BMI/(kg/m2), ${\bar x}$±s 24.8±3.7 24.3±3.5 24.3±3.5 0.782
  Waist circumference/cm, ${\bar x}$±s 87.0±10.1 85.4±9.7 86.2±9.4 0.292
  Waist-hip ratio, ${\bar x}$±s 0.9 ±0.1 0.9±0.1 0.9±0.1 0.001
  Waist-height ratio, ${\bar x}$±s 0.5±0.1 0.5±0.1 0.5±0.1 0.260
  BMI classification, n(%) 0.962
    Underweight 35 (3.3) 14 (4.5) 16 (5.1)
    Normal 539 (50.9) 168 (54.4) 165 (52.9)
    Overweight 404 (38.2) 112 (36.2) 117 (37.5)
    Obese 80 (7.6) 15 (4.9) 14 (4.5)
  Central obesity, n(%) 1.000
    Yes 485 (45.5) 124 (39.5) 123 (39.2)
    No 582 (54.5) 190 (60.5) 191 (60.8)
DNAm clock
  GrimAA/years, ${\bar x}$±s 0.00±3.86 0.02±4.10 0.04±3.73 0.941
  DunedinPACE, ${\bar x}$±s 1.13±0.11 1.13±0.10 1.14±0.11 0.232
  PCGrimAA/years, ${\bar x}$±s 0.00±2.62 -0.15±2.71 0.15±2.71 0.175

Table 2

Cross-sectional associations between obesity indicators and GrimAA or PCGrimAA"

Characteristics GrimAA (Model 1) GrimAA (Model 2) PCGrimAA (Model 3)
β(95%CI) PFDR β(95%CI) PFDR β(95%CI) PFDR
Weight -0.03 (-0.05, -0.01) 0.005 -0.03 (-0.05, -0.01) 0.006 -0.02 (-0.03, -0.00) 0.043
BMI -0.09 (-0.14, -0.03) 0.007 -0.07 (-0.12, -0.02) 0.024 -0.03 (-0.06, 0.01) 0.273
Waist circumference -0.02 (-0.04, 0.00) 0.071 -0.02 (-0.04, 0.00) 0.077 -0.01 (-0.02, 0.01) 0.512
Waist-hip ratio -0.87 (-3.93, 2.19) 0.577 -0.79 (-3.69, 2.11) 0.595 0.28 (-1.66, 2.22) 0.820
Waist-height ratio -2.69 (-5.91, 0.53) 0.119 -2.20 (-5.26, 0.85) 0.183 -0.24 (-2.28, 1.81) 0.820
Obesity -0.75 (-1.27, -0.24) 0.009 -0.58 (-1.07, -0.10) 0.044 -0.23 (-0.55, 0.09) 0.273
Central obesity -0.60 (-1.18, -0.03) 0.068 -0.56 (-1.11, -0.01) 0.077 -0.28 (-0.64, 0.08) 0.273

Table 3

Cross-sectional associations between obesity indicators and DunedinPACE"

Characteristic Model 1 Model 2
β(95%CI) PFDR β(95%CI) PFDR
Weight 0.000 7 (0.000 1, 0.001 3) 0.028 0.000 7 (0.000 1, 0.001 3) 0.026
BMI 0.003 0 (0.001 4, 0.004 7) < 0.001 0.003 2 (0.001 5, 0.004 8) < 0.001
Waist circumference 0.001 1 (0.000 5, 0.001 7) < 0.001 0.001 1 (0.000 5, 0.001 7) 0.001
Waist-hip ratio 0.168 8 (0.073 9, 0.263 7) < 0.001 0.162 4 (0.068 0, 0.256 9) 0.001
Waist-height ratio 0.208 2 (0.108 4, 0.307 9) < 0.001 0.208 7 (0.109 5, 0.307 9) < 0.001
Obesity 0.033 4 (0.017 9, 0.048 9) < 0.001 0.035 8 (0.020 5, 0.051 0) < 0.001
Central obesity 0.024 8 (0.006 9, 0.042 7) 0.008 0.026 4 (0.008 8, 0.044 0) 0.004

Figure 1

Cross-sectional correlation between GrimAA, PCGrimAA, DunedinPACE and obesity indicators in all twins and within-pair analysis WEI, weight; BMI, body mass index; WAI, waist circumference; WHR, waist-hip ratio; WHtR, waist-height ratio; MZ, monozygotic twins; DZ, dizygotic twins; GrimAA, GrimAge acceleration; PCGrimAA, principle component GrimAA; β, regression coefficient; CI, confidence interval; FDR, false discovery rate."

Table 4

Cross-lagged relationships between obesity indicators and DNAm clock metrics"

Characteristics Obesity indicators at baseline → DNAm clock metrics at follow-up DNAm clock metrics at baseline → Obesity indicators at follow-up Fit statistics
ρ1 PFDR ρ2 PFDR SRMR CFI
GrimAA
Weight 0.04 0.035 0.02 0.996 0.04 0.96
BMI 0.05 0.414 0.01 0.996 0.05 0.94
Waist circumference 0.03 0.250 0.01 0.996 0.05 0.92
Waist-hip ratio 2.46 0.414 0.00 0.996 0.05 0.88
Waist-height ratio 0.08 0.974 0.00 0.996 0.05 0.92
PCGrimAA
Weight 0.03 < 0.001 0.00 0.966 0.01 1.00
BMI 0.07 0.022 0.01 0.966 0.02 0.99
Waist circumference 0.02 0.040 0.02 0.966 0.02 0.98
Waist-hip ratio 0.95 0.542 0.00 0.966 0.03 0.97
Waist-height ratio 1.99 0.226 0.00 0.966 0.02 0.99
DunedinPACE
Weight 0.00 0.310 -1.06 0.999 0.02 1.00
BMI 0.00 0.310 0.14 0.999 0.02 1.00
Waist circumference 0.00 0.088 0.01 0.999 0.02 0.99
Waist-hip ratio 0.17 0.030 0.02 0.999 0.03 0.98
Waist-height ratio 0.12 0.088 0.01 0.999 0.02 1.00
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