DNA methylation, cardiovascular risk and myocardial infarction : an epigenome-wide approach

Cardiovascular diseases are a major challenge for public health. DNA methylation is a mechanism regulating gene expression, and it is linked to complex diseases and related traits. Therefore, it is a potential source of biomarkers of cardiovascular risk. We have tackled the associations of DNA methy...

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Detalles Bibliográficos
Autor: Fernández Sanlés, Alba
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:CBUC, CESCA
Repositorio:TDR. Tesis Doctorales en Red
OAI Identifier:oai:www.tdx.cat:10803/668498
Acceso en línea:http://hdl.handle.net/10803/668498
Access Level:acceso abierto
Palabra clave:DNA methylation
Epigenomics
Cardiovascular risk
Cardiovascular disease
Observational studies
Metilación del ADN
Epigenòmica
Riesgo cardiovascular
Enfermedad cardiovascular
Estudios observacionales
616.1
Descripción
Sumario:Cardiovascular diseases are a major challenge for public health. DNA methylation is a mechanism regulating gene expression, and it is linked to complex diseases and related traits. Therefore, it is a potential source of biomarkers of cardiovascular risk. We have tackled the associations of DNA methylation with cardiovascular diseases and related traits in population-based observational studies. We analysed the association between this mechanism in peripheral blood cells and both cardiovascular disease related exposures and outcomes, and further investigated the clinical relevance of some of those findings. For this purpose, we conducted epigenome-wide and candidate loci association studies, evaluated their predictive value for future cardiovascular risk and used Mendelian Randomisation to infer causality. We used three cohorts: REgistre GIroní del COR, Framingham Offspring Study and Women’s Health Initiative. As a general conclusion, DNA methylation is associated with cardiovascular disease related traits and outcomes, although its role in the underlying biological networks is complex and remains to be explored in further studies.