DNA methylation and waist-to-hip ratio: an epigenome-wide association study in Chinese monozygotic twins

Wu, Yili; Tian, Huimin; Wang, W; Li, W; Duan, Haiping; Zhang, D

doi:10.1007/s40618-022-01878-4

Cited by 8 publications

(3 citation statements)

References 63 publications

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“…DNA methylation (DNAm) is a commonly studied epigenetic modification that is responsive to both genetics and the environment, making it an ideal target for studying the consequences of modifiable health factors, such as obesity. The relationship between DNAm and BMI, as well as other body fat and adiposityrelated biochemical traits, has been extensively studied [1][2][3][4][5][6][7][8][9]. However, the shared associations of DNAm variation across such traits represents an important gap in our understanding of the biological processes pertaining to obesity.…”

Section: Introductionmentioning

confidence: 99%

“…The epigenetic modification DNA methylation (DNAm) may help to explore this as it is sensitive to both genetic and environmental exposures. While the relationship between DNAm and body fat traits has been extensively studied [1][2][3][4][5][6][7][8][9], there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, which measure the degree of common genetic control between two traits, here we introduce an approach to evaluate the similarities in DNAm associations between traits, DNAm correlations.…”

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confidence: 99%

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Blood-based genome-wide DNA methylation correlations across body fat and adiposity-related biochemical traits

Hatton¹,

Hillary

Bernabeu

et al. 2023

Preprint

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The recent increase in obesity levels across many countries is likely to be driven by nongenetic factors. The epigenetic modification DNA methylation (DNAm) may help to explore this as it is sensitive to both genetic and environmental exposures. While the relationship between DNAm and body fat traits has been extensively studied [1–9], there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, which measure the degree of common genetic control between two traits, here we introduce an approach to evaluate the similarities in DNAm associations between traits, DNAm correlations. As DNAm can be both a cause and consequence of complex traits [5, 10, 11], DNAm correlations have the potential to provide novel insights into trait relationships above that currently obtained from genetic and phenotypic correlations. Utilising 7,519 unrelated individuals from Generation Scotland (GS), we calculated DNAm correlations using the bivariate OREML framework in the OSCA software [12] to investigate the shared associations of DNAm variation between traits. For each trait we also estimated the shared contribution of DNAm between sexes. We identified strong, positive DNAm correlations between each of the body fat traits (BMI, body fat % and waist to hip ratio; ranging from 0.96 to 1.00), finding larger associations than those identified by genetic and phenotypic correlations. We identified a significant deviation from 1 in the rDNAmfor BMI between males and females, with sex-specific DNAm changes associated with BMI identified at eight DNAm probes. Employing genome-wide DNAm correlations to evaluate the similarities in the associations of DNAm with complex traits has provided novel insight into obesity related traits beyond that provided by genetic correlations.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Blood-based genome-wide DNA methylation correlations across body fat and adiposity-related biochemical traits

Hatton¹,

Hillary

Bernabeu

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition to intrinsic defects in adipocyte function and variations in hormonal responses, genetic and epigenetic factors contribute to body fat patterning [ 6 , 7 , 8 ]. Notably, our lab and others previously identified in ABD and GF adipose tissues specific transcriptional signatures associated with body shape along with epigenetic patterns [ 9 , 10 ] that were partially maintained in adipose-derived stem cells (ADSCs) expanded in culture [ 9 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Transcriptional Control of Subcutaneous Adipose Tissue by the Transcription Factor CTCF Modulates Heterogeneity in Fat Distribution in Women

Erdos,

Sandor,

Young-Erdos

et al. 2023

Cells

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Determining the mechanism driving body fat distribution will provide insights into obesity-related health risks. We used functional genomics tools to profile the epigenomic landscape to help infer the differential transcriptional potential of apple- and pear-shaped women’s subcutaneous adipose-derived stem cells (ADSCs). We found that CCCTC-binding factor (CTCF) expression and its chromatin binding were increased in ADSCs from pear donors compared to those from apple donors. Interestingly, the pear enriched CTCF binding sites were located predominantly at the active transcription start sites (TSSs) of genes with active histone marks and YY1 motifs and were also associated with pear enriched RNAPII binding. In contrast, apple enriched CTCF binding sites were mainly found at intergenic regions and when identified at TSS, they were enriched with the bivalent chromatin signatures. Altogether, we provide evidence that CTCF plays an important role in differential regulation of subcutaneous ADSCs gene expression and may influence the development of apple vs. pear body shape.

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Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses

Li,

Dite,

MacInnis

et al. 2024

Genetic Epidemiology

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A polygenic risk score (PRS) combines the associations of multiple genetic variants that could be due to direct causal effects, indirect genetic effects, or other sources of familial confounding. We have developed new approaches to assess evidence for and against causation by using family data for pairs of relatives (Inference about Causation from Examination of FAmiliaL CONfounding [ICE FALCON]) or measures of family history (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLyses [ICE CRISTAL]). Inference is made from the changes in regression coefficients of relatives' PRSs or PRS and family history before and after adjusting for each other. We applied these approaches to two breast cancer PRSs and multiple studies and found that (a) for breast cancer diagnosed at a young age, for example, <50 years, there was no evidence that the PRSs were causal, while (b) for breast cancer diagnosed at later ages, there was consistent evidence for causation explaining increasing amounts of the PRS‐disease association. The genetic variants in the PRS might be in linkage disequilibrium with truly causal variants and not causal themselves. These PRSs cause minimal heritability of breast cancer at younger ages. There is also evidence for nongenetic factors shared by first‐degree relatives that explain breast cancer familial aggregation. Familial associations are not necessarily due to genes, and genetic associations are not necessarily causal.

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DNA methylation and waist-to-hip ratio: an epigenome-wide association study in Chinese monozygotic twins

Cited by 8 publications

References 63 publications

Blood-based genome-wide DNA methylation correlations across body fat and adiposity-related biochemical traits

Blood-based genome-wide DNA methylation correlations across body fat and adiposity-related biochemical traits

Transcriptional Control of Subcutaneous Adipose Tissue by the Transcription Factor CTCF Modulates Heterogeneity in Fat Distribution in Women

Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses

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