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EpiBigDatainWomen SIGNED

Epigenetic Data Integrated in a Big Data Approach to Unravel Novel Pathzays of CV Risk independent of classical CVD Risk Factors in Women.

Total Cost €

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EC-Contrib. €

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Partnership

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Project "EpiBigDatainWomen" data sheet

The following table provides information about the project.

Coordinator
INSTITUTO NEUROLOGICO MEDITERRANEO- NEUROMED SRL 

Organization address
address: VIA ATINENSE 18
city: POZZILLI IS
postcode: 86077
website: www.neuromed.it

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Total cost 168˙277 €
 EC max contribution 168˙277 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-SE
 Starting year 2019
 Duration (year-month-day) from 2019-04-01   to  2021-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUTO NEUROLOGICO MEDITERRANEO- NEUROMED SRL IT (POZZILLI IS) coordinator 168˙277.00

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 Project objective

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.

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The information about "EPIBIGDATAINWOMEN" are provided by the European Opendata Portal: CORDIS opendata.

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