AI Identifies Genes Linked to Heart Failure

One of the most beneficial aspects of AI in healthcare is its ability to understand vast amounts of genetic data and provide novel insights on these data sets.

A team of researchers from Queen Mary University of London have harnessed the power of AI to identify genes linked to heart failure.The team used AI to analyze heart MRI images from 17,000 healthy UK Biobank volunteers.They found that 22 to 39 % of the variation in size and function of the left ventricle, which is the main chamber of the heart that pumps blood to the rest of the body, were due to certain genetic factors. The investigators were able to identify 14 specific areas (loci) in the human genome linked to the size and function of the left ventricle which regulates the embryonic development of the heart and its contractile mechanism.

The incidence and prevalence of heart failure are increasing due to improved survival from other cardiovascular diseases in an ageing population. These findings can help in early identification of people at risk of heart failure. Further studies on these genes can also aid the development of potential novel therapies for people with heart failure.

“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 personalized risk assessment tool for heart failure.” said Dr Nay Aung, the lead researcher

“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 said. This study is the largest individual-level genome-wide association study investigating the genetic architecture of prognostically important left ventricular phenotypes derived from Cardiovascular magnetic resonance imaging (CMR).

“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. That understanding of the genetic basis of heart structure and function in the general population improves our knowledge of how heart failure evolves.” added co-investigator Steffen Petersen, Professor of Cardiovascular Medicine at Queen Mary University of London.

This study shows the power of AI systems to uncover major insights from large scale data which can lead to the development of new guidelines in early detection of existing conditions. With widespread adoption of these AI techniques in research, and ever growing database, it is expected that many more genetic bio markers will be identified.