Summary
Epigenetic mechanisms might be involved in linking environmental and lifestyle factors and CVD development. Several studies suggest that changes in DNA methylation contribute to the regulation of biological processes underlying CVD, such as atherosclerosis, hypertension and inflammation. The recent increased digitalization, collection and storage of vast quantities of data in combination with advances in data science, has opened up a new era of big data. Although these approaches are gradually implemented in a number of clinical settings, they still lack the integration with environmental individual data, strongly affecting several multifactorial diseases such as cardiovascular disease (CVD). Classical risk factor approaches still fail in correctly estimating CVD risk in women compared to men, therefore there is a need for novel strategies to identify signs of reversible early disease or disease risk factors in this population.
We plan to generate and analyse epigenetic data in the context of a very large number of environmental and lifestyle variables (big data) in a group of women and men with traditional CVD risk factors (and age-matched controls) selected from the MOLI-SANI cohort. With this approach we hope to shed light into the controversial aspects of CVD prediction and prevention in women, independently of traditional CV risk factors.
We plan to generate and analyse epigenetic data in the context of a very large number of environmental and lifestyle variables (big data) in a group of women and men with traditional CVD risk factors (and age-matched controls) selected from the MOLI-SANI cohort. With this approach we hope to shed light into the controversial aspects of CVD prediction and prevention in women, independently of traditional CV risk factors.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/798841 |
Start date: | 01-04-2019 |
End date: | 01-09-2021 |
Total budget - Public funding: | 168 277,20 Euro - 168 277,00 Euro |
Cordis data
Original description
Epigenetic mechanisms might be involved in linking environmental and lifestyle factors and CVD development. Several studies suggest that changes in DNA methylation contribute to the regulation of biological processes underlying CVD, such as atherosclerosis, hypertension and inflammation. The recent increased digitalization, collection and storage of vast quantities of data in combination with advances in data science, has opened up a new era of big data. Although these approaches are gradually implemented in a number of clinical settings, they still lack the integration with environmental individual data, strongly affecting several multifactorial diseases such as cardiovascular disease (CVD). Classical risk factor approaches still fail in correctly estimating CVD risk in women compared to men, therefore there is a need for novel strategies to identify signs of reversible early disease or disease risk factors in this population.We plan to generate and analyse epigenetic data in the context of a very large number of environmental and lifestyle variables (big data) in a group of women and men with traditional CVD risk factors (and age-matched controls) selected from the MOLI-SANI cohort. With this approach we hope to shed light into the controversial aspects of CVD prediction and prevention in women, independently of traditional CV risk factors.
Status
CLOSEDCall topic
MSCA-IF-2017Update Date
28-04-2024
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