Genes Linked to Heart Failure Uncovered Using AI

A team from the Queen Mary University of London has used an artificial intelligence (AI) system to identify genes linked to heart failure. This work, funded in part by the Wellcome Trust and the British Heart Foundation and published September 25 in the journal Circulation, could potentially lead to earlier detection of patients with heart failure risks as well as the development of new treatments.

This research team used AI to analyze heart MRI images from 17,000 healthy UK Biobank volunteers, finding that 22-39% of the variation in size and function of the left ventricle was determined by genetic factors. Enlargement and decreased contractility of the heart’s left ventricle are both strong contributors to heart failure.

Genotyping was performed using Affymetrix arrays, with genome-wide association studies being performed for the following six left ventricular characteristics:

• End-diastolic volume
• End-systolic volume
• Stroke volume
• Ejection fraction
• Left ventricular mass
• Left ventricular mass to end-diastolic volume ratio

This work suggests that genes significantly influence the variations in cardiovascular structure and function that lead to failure. The Queen Mary team identified 14 regions in the genome that are associated with the size and function of the left ventricle, containing specific genes that regulate early development of the heart’s chambers and contractility.

“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,” said lead researcher Nay Aung from the University. “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.”

Project researcher Patricia Munroe, Professor of Molecular Medicine at Queen Mary University of London, noted that their work has found “new genes from more heritable functional measures that are associated with ventricular remodelling and fibrosis.” She concluded that “further genetic studies including analyses of additional heart MRI chambers are expected to provide deeper insights into heart biology.”

The team expects that many other genetic markers for cardiovascular health will be uncovered as the UK Biobank gains more data. The database recently announced that it will sequence the full genomes of 450,000 individuals. This announcement comes in the wake of a successful pilot sequencing project involving 50,000 participants.

“The AI tool allowed us to analyse images in a fraction of the time it would otherwise have taken,” explained Aung. “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.”

“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,” said corresponding author Steffen Petersen, Professor of Cardiovascular Medicine at Queen Mary University of London. “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. 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.”

AI identifies genes linked to heart failure https://t.co/x4Jd7l8IHB #QAcycle pic.twitter.com/R3jATL2VHL

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