Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design
Abstract Background Both obesity and DNA methylation (DNAm) are influenced by genetic factors. Despite more than a thousand of obesity-related DNAm sites (CpGs) being identified, studies that account for genetic influences in these associations are limited. Results Using data from 1,074 twins in the...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-07-01
|
| Series: | Cell & Bioscience |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13578-025-01446-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849331954548211712 |
|---|---|
| author | Xuanming Hong Hui Cao Weihua Cao Jun Lv Canqing Yu Tao Huang Dianjianyi Sun Chunxiao Liao Yuanjie Pang Runhua Hu Ruqin Gao Min Yu Jinyi Zhou Xianping Wu Yu Liu Shengli Yin Wenjing Gao Liming Li |
| author_facet | Xuanming Hong Hui Cao Weihua Cao Jun Lv Canqing Yu Tao Huang Dianjianyi Sun Chunxiao Liao Yuanjie Pang Runhua Hu Ruqin Gao Min Yu Jinyi Zhou Xianping Wu Yu Liu Shengli Yin Wenjing Gao Liming Li |
| author_sort | Xuanming Hong |
| collection | DOAJ |
| description | Abstract Background Both obesity and DNA methylation (DNAm) are influenced by genetic factors. Despite more than a thousand of obesity-related DNAm sites (CpGs) being identified, studies that account for genetic influences in these associations are limited. Results Using data from 1,074 twins in the Chinese National Twin Registry and bivariate structural equation models (SEMs), we investigated the phenotypic (Rph), genetic (Ra), and environmental (Re) correlations between genome-wide DNAm and three obesity indices: BMI, waist circumference (WC), and waist-to-hip ratio (WHR). Genome-wide, correlations between DNAm and obesity were small (Rph = 0.04, Ra = 0.08–0.09, Re = 0.02–0.03). For CpGs with high phenotypic correlation (Rph > 0.1), the mean genetic and environmental correlations were 0.23–0.24 and 0.03–0.05, respectively, indicating significant genetic influence on the DNAm-obesity associations. To further investigate the role of genetic influences, we then categorized the CpGs into different groups: high phenotypic correlation (Rph ≥ 0.2); high phenotypic and genetic correlations (Rph > 0.1 and Ra > 0.5); high phenotypic and low genetic correlations (Rph > 0.1 and Ra < 0.5). Association studies were conducted in the full population and in the monozygotic (MZ) twin-paired design, where genetic influences were controlled. For CpGs with Rph ≥ 0.2, 9, 8, and 22 were associated with BMI, WC, and WHR in the full population, but only 6, 1, and 1 CpGs remained significant after controlling for genetic effects in MZ twin-pair analyses. For CpGs with Rph > 0.1 and Ra > 0.5, genetic factors predominantly drove the association, and none of the 155/155/189 CpGs associated with BMI/WC/WHR in the full population were significant in MZ-paired analyses. For CpGs with Rph > 0.1 and Ra < 0.1, genetic effects were minimal or confounding, with 89, 4, and 17 significant in both full population and MZ-paired analyses. Conclusions Our results highlight the significant genetic influences on the DNAm-obesity relationships, which may explain the low replicability of obesity-related DNAm markers. This indicates that genetic influences should be carefully considered in DNAm-related studies. |
| format | Article |
| id | doaj-art-3131237d48e640e0bb9fff5562df8f63 |
| institution | Kabale University |
| issn | 2045-3701 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Cell & Bioscience |
| spelling | doaj-art-3131237d48e640e0bb9fff5562df8f632025-08-20T03:46:21ZengBMCCell & Bioscience2045-37012025-07-0115111610.1186/s13578-025-01446-2Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study designXuanming Hong0Hui Cao1Weihua Cao2Jun Lv3Canqing Yu4Tao Huang5Dianjianyi Sun6Chunxiao Liao7Yuanjie Pang8Runhua Hu9Ruqin Gao10Min Yu11Jinyi Zhou12Xianping Wu13Yu Liu14Shengli Yin15Wenjing Gao16Liming Li17Department of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityQingdao Center for Disease Control and PreventionZhejiang Center for Disease Control and PreventionJiangsu Center for Disease Control and PreventionSichuan Center for Disease Control and PreventionHeilongjiang Center for Disease Control and PreventionDezhou Center for Disease Control and PreventionDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, Peking UniversityAbstract Background Both obesity and DNA methylation (DNAm) are influenced by genetic factors. Despite more than a thousand of obesity-related DNAm sites (CpGs) being identified, studies that account for genetic influences in these associations are limited. Results Using data from 1,074 twins in the Chinese National Twin Registry and bivariate structural equation models (SEMs), we investigated the phenotypic (Rph), genetic (Ra), and environmental (Re) correlations between genome-wide DNAm and three obesity indices: BMI, waist circumference (WC), and waist-to-hip ratio (WHR). Genome-wide, correlations between DNAm and obesity were small (Rph = 0.04, Ra = 0.08–0.09, Re = 0.02–0.03). For CpGs with high phenotypic correlation (Rph > 0.1), the mean genetic and environmental correlations were 0.23–0.24 and 0.03–0.05, respectively, indicating significant genetic influence on the DNAm-obesity associations. To further investigate the role of genetic influences, we then categorized the CpGs into different groups: high phenotypic correlation (Rph ≥ 0.2); high phenotypic and genetic correlations (Rph > 0.1 and Ra > 0.5); high phenotypic and low genetic correlations (Rph > 0.1 and Ra < 0.5). Association studies were conducted in the full population and in the monozygotic (MZ) twin-paired design, where genetic influences were controlled. For CpGs with Rph ≥ 0.2, 9, 8, and 22 were associated with BMI, WC, and WHR in the full population, but only 6, 1, and 1 CpGs remained significant after controlling for genetic effects in MZ twin-pair analyses. For CpGs with Rph > 0.1 and Ra > 0.5, genetic factors predominantly drove the association, and none of the 155/155/189 CpGs associated with BMI/WC/WHR in the full population were significant in MZ-paired analyses. For CpGs with Rph > 0.1 and Ra < 0.1, genetic effects were minimal or confounding, with 89, 4, and 17 significant in both full population and MZ-paired analyses. Conclusions Our results highlight the significant genetic influences on the DNAm-obesity relationships, which may explain the low replicability of obesity-related DNAm markers. This indicates that genetic influences should be carefully considered in DNAm-related studies.https://doi.org/10.1186/s13578-025-01446-2DNA methylationObesityGenetic correlationsTwin study |
| spellingShingle | Xuanming Hong Hui Cao Weihua Cao Jun Lv Canqing Yu Tao Huang Dianjianyi Sun Chunxiao Liao Yuanjie Pang Runhua Hu Ruqin Gao Min Yu Jinyi Zhou Xianping Wu Yu Liu Shengli Yin Wenjing Gao Liming Li Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design Cell & Bioscience DNA methylation Obesity Genetic correlations Twin study |
| title | Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design |
| title_full | Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design |
| title_fullStr | Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design |
| title_full_unstemmed | Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design |
| title_short | Genetic influences on the association between DNA methylation and obesity measures: insights from a twin study design |
| title_sort | genetic influences on the association between dna methylation and obesity measures insights from a twin study design |
| topic | DNA methylation Obesity Genetic correlations Twin study |
| url | https://doi.org/10.1186/s13578-025-01446-2 |
| work_keys_str_mv | AT xuanminghong geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT huicao geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT weihuacao geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT junlv geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT canqingyu geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT taohuang geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT dianjianyisun geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT chunxiaoliao geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT yuanjiepang geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT runhuahu geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT ruqingao geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT minyu geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT jinyizhou geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT xianpingwu geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT yuliu geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT shengliyin geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT wenjinggao geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign AT limingli geneticinfluencesontheassociationbetweendnamethylationandobesitymeasuresinsightsfromatwinstudydesign |