Researchers Use Artificial Intelligence to Identify Genes Associated with Heart Failure

Researchers at the Queen Mary University of London have assessed the heart MRI images of 17,000 healthy UK Biobank volunteers using an artificial intelligence (AI) method.

The human heart (Image credit: Queen Mary University of London)

The scientists observed that 22%–39% of changes in the function and size of the heart’s left ventricle are caused by genetic factors. The left ventricle is the main pumping chamber of the heart. Therefore, reduced pumping function or enlargement of the left ventricle can result in heart failure.

The study, which was funded in part by the British Heart Foundation and the Wellcome Trust, has been reported in the journal Circulation. It indicates that the variation in the structure and function of the heart is considerably influenced by genetic factors.

The scientists were able to detect or confirm as much as 14 regions in the human genome linked to the left ventricle’s function and size; each region contains genes that are responsible for regulating the contraction of the heart muscle and also the early development of heart chambers.

Early Identification of Heart Disease and Potential New Treatments

According to lead researcher Dr Nay Aung from the William Harvey Research Unit (WHRU) at Queen Mary University of London, “It is exciting that the state-of-the-art AI techniques now allow rapid and accurate measurement of the tens of thousands of heart MRI images required for genetic studies. The findings open up the possibility of earlier identification of those at risk of heart failure and of new targeted treatments. The genetic risk scores established from this study could be tested in future studies to create an integrated and personalised risk assessment tool for heart failure.”

The AI tool allowed us to analyse images in a fraction of the time it would otherwise have taken. Our academic and commercial partners are further developing these AI algorithms to analyse other aspects of cardiac structure and function. This should translate to time and cost savings for the NHS and could potentially improve the efficiency of patient care.

Dr Nay Aung, Lead Researcher, William Harvey Research Unit, Queen Mary University of London

Evolution of Heart Failure

According to Steffen Petersen, Professor of Cardiovascular Medicine at William Harvey Research Unit (WHRU) at Queen Mary University of London, “Previous studies have shown that differences in the size and function of the heart are partly influenced by genes but we have not really understood the extent of that genetic influence.”

This study has shown that several genes known to be important in heart failure also appear to regulate the heart size and function in healthy people.

Steffen Petersen, Professor of Cardiovascular Medicine, William Harvey Research Unit, Queen Mary University of London

That understanding of the genetic basis of heart structure and function in the general population improves our knowledge of how heart failure evolves. The study provides a blueprint for future genetic research involving the heart MRI images in the UK Biobank and beyond,” added Petersen, who also worked on the project.

High fidelity MRI measures combined with genetics is reassuringly validating many known heart structural proteins, but our work also finds new genes from more heritable functional measures that are associated with ventricular remodelling and fibrosis. Further genetic studies including analyses of additional heart MRI chambers are expected to provide deeper insights into heart biology.

Patricia Munroe, Professor of Molecular Medicine, Queen Mary University of London

Munroe was also involved in the project.

With the growth of the UK Biobank database, more numbers of genetic markers for cardiac conditions are expected to be identified. UK Biobank announced earlier this month that sequencing of the whole human genome of 450,000 participants will be initiated once the pilot sequencing program in 50,000 participants is successfully completed.

Source: https://www.qmul.ac.uk/

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