Project description
Improving heart disease prediction for women
Heart disease is the world’s leading killer, yet predicting who is at risk remains a challenge. Current models rely on conventional risk factors and genetic scores, but their accuracy is limited, particularly for women. Protein markers offer a powerful alternative, reflecting both inherited traits and environmental influences on heart health. Research suggests that integrating these markers with existing methods could vastly improve risk prediction. Supported by the Marie Skłodowska-Curie Actions programme, the ProtectHearts is tackling this challenge by developing innovative protein-based risk scores. Using machine learning and Europe’s largest biobank-linked proteomics datasets, the project will create sex-specific models that better capture the risk women face. By refining cardiovascular disease prediction, ProtectHearts aims to revolutionise prevention and clinical care, saving lives through earlier and more accurate diagnosis.
Objective
Cardiovascular disease (CVD) remains the leading cause of death globally for men and women. State-of-the art clinical risk prediction models for CVD use conventional risk factors and polygenic scores (PGS)—a measure of an individuals’ inherited CVD risk. However, the accuracy of current models is moderate and worse in women than men. Protein markers of CVD represent an individual’s current health state and both inherited and environmental disease risk. Indeed, there is evidence that combining conventional risk factors, PGS, and protein markers of CVD may facilitate vast improvements in CVD risk prediction. Furthermore, by modelling inflammation-specific protein markers missing from sex-specific CVD risk models, ProtectHearts will specifically capture excess risk in women.
ProtectHearts will use the world’s largest population-biobank-linked proteomics datasets to 1) develop a novel protein-based risk score (ProtRS); 2) develop an inflammation-specific ProtRS (i-ProtRS); and 3) estimate the clinical utility of these scores when modelled with clinical risk scores and PGS. Cutting-edge machine learning algorithms will be used to establish target proteins for CVD prediction in 100,000 individuals across four European biobanks.
ProtectHearts brings together a physician-scientist Supervisor with proteomics expertise and a Fellow with experience modelling CVD risk prediction using PGS in biobanks. Through a secondment and non-academic placement, the Fellow will gain intersectoral experience. Activities of the training and dissemination work packages will build her competencies in machine learning, advanced statistics and science communication. ProtectHearts will engage clinicians in exploitation of the new sex-specific, comprehensive CVD risk prediction model.
ProtectHearts has the potential to move CVD risk prediction beyond state-of-the-art by improving risk prediction accuracy, specifically in women, using protein-based markers for CVD and CVD-related inflammation.
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2022-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
7491 TRONDHEIM
Norway
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.