AI Pinpoints Genes Associated With Heart Failure – Forbes

Posted: October 5, 2019 at 4:42 am

While AI may increase speed and efficiency of medical care on the front lines, one of its most powerful benefits is the ability to search vast amounts of data to learn about genetic aspects of various diseases.

Cardiomegaly Is An Enlargement Of The Heart Due To Dilatation Of The Heart Cavities. This Can Result From Many Conditions Including A Disease Of The Heart Muscle Myocardial Disease, Defective Valve Function, Or Hypertrophy Of The Heart Muscle Due To

Earlier identification of persons at risk for heart failure or a genetic cardiomyopathy is a prime example. This could enable persons to be more closely monitored by health care providers and even placed on lists for transplant before they decompensate and develop heart failure leading to cardiogenic shock, which can be ultimately be fatal if not treated and identified in a timely fashion.

Researchers at Queen Mary University of London have now harnessed the power of AI to identify patients who are at risk for heart failure, enabling earlier identification, management and treatment of these high-risk individuals.

The research team used an artificial intelligence (AI) technique to analyze cardiac MRI images of 17,000 healthy UK Biobank volunteers. They noted that genetic factors accounted for 22-39% of variation in the size and function of the left ventricle (LV), the main chamber in the heart that pumps blood to the rest of the body. Reduced pumping ability and increase in size of the left ventricle leads to heart failure.

The research, recently published in the journalCirculation, highlights the importance of genetic factors and their role in the contribution to structural heart disease. The investigators discovered 14 specific areas (loci) linked to the dimensions, structure and function of the left ventricle containing genes that control the embryonic development of heart chambers and the contraction of heart muscle.

"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 Dr. Nay Aung from Queen Mary University of London in a press release. 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.

"The AI tool allowed us to analyze images in a fraction of the time it would otherwise have taken; this should translate to time and cost savings for the NHS and could potentially improve the efficiency of patient care, he added.

"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,explained co-investigator 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, he added.

"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 remodeling and fibrosis, added co-investigator Patricia Munroe, Professor of Molecular Medicine at Queen Mary University of London. Further genetic studies including analyses of additional heart MRI chambers are expected to provide deeper insights into heart biology."

In fact, identification of specific genes that play a role in determining left ventricular volume, a key marker of survival in the setting of heart failure (resulting from LV remodeling in the setting of a cardiomyopathy), would be quite valuable. The advent of gene therapy, progenitor cell therapy (stem cells) and emerging molecular genetic approaches to address these genetic anomalies may offer promise.

With the expansion of the UK Biobank database, the expectation is that more genes for cardiac abnormalities will be notified in the future. In fact, UK Biobank announced earlier this month that it will begin sequencing the entire human genome of 450,000 participants, after success of a pilot sequencing trial in 50,000 participants.

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AI Pinpoints Genes Associated With Heart Failure - Forbes

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