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Blood-based genome-wide DNA methylation correlations across body-fat- and adiposity-related biochemical traits.
Hatton, Alesha A; Hillary, Robert F; Bernabeu, Elena; McCartney, Daniel L; Marioni, Riccardo E; McRae, Allan F.
Afiliación
  • Hatton AA; Institute for Molecular Bioscience, Brisbane, Australia.
  • Hillary RF; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
  • Bernabeu E; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
  • McCartney DL; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
  • Marioni RE; Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
  • McRae AF; Institute for Molecular Bioscience, Brisbane, Australia. Electronic address: a.mcrae@uq.edu.au.
Am J Hum Genet ; 110(9): 1564-1573, 2023 09 07.
Article en En | MEDLINE | ID: mdl-37652023
ABSTRACT
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, there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, 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, DNAm correlations have the potential to provide insights into trait relationships above that currently obtained from genetic and phenotypic correlations. Utilizing 7,519 unrelated individuals from Generation Scotland with DNAm from the EPIC array, we calculated DNAm correlations between body-fat- and adiposity-related traits by using the bivariate OREML framework in the OSCA software. 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 percentage, 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 DNAm correlations for 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 insight into obesity-related traits beyond that provided by genetic correlations.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Metilación de ADN / Adiposidad Tipo de estudio: Prognostic_studies Límite: Female / Humans / Male Idioma: En Revista: Am J Hum Genet Año: 2023 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Metilación de ADN / Adiposidad Tipo de estudio: Prognostic_studies Límite: Female / Humans / Male Idioma: En Revista: Am J Hum Genet Año: 2023 Tipo del documento: Article País de afiliación: Australia