AI uncovers genes linked to heart failure

heart
By analyzing MRI images from UK Biobank, scientists at Queen Mary University of London have found genetic features associated with heart failure. (Bryan Brandenburg/CC by-SA 3.0)

Artificial intelligence has been embraced for its ability to offer insight from big data. By applying the technology to genetics, a research team led by Queen Mary University of London has found clues that they say could aid the development of new drugs for heart failure and identify people at risk of the disease.

Based on an AI analysis of heart MRI images from 17,000 volunteers in UK Biobank, the researchers linked genetic factors to 22% to 39% of abnormalities in the size and function of the heart’s left ventricle, which pumps blood into the aorta. They published the findings in the journal Circulation.

The team identified or confirmed 14 regions in the human genome that play a part in determining the size and function of the left ventricle, because they contain genes that regulate the early development of heart chambers and the contraction of heart muscle. Enlargement of left ventricle is a condition that can hamper the heart muscle’s ability to contract and pump blood, putting the patient at high risk of heart attack.

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“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,” said study co-author Steffen Petersen of Queen Mary in a statement. “That understanding of the genetic basis of heart structure and function in the general population improves our knowledge of how heart failure evolves.”

RELATED: Bayer teams up with AI firm Sensyne Health to mine NHS data for its heart disease pipeline

There is a growing interest in using AI to gain insights into cardiovascular disease. Bayer recently partnered up with Sensyne Health, which uses AI to mine patient data from the U.K. National Health Service, including genomic sequencing data and real-world evidence, to help design clinical studies and accelerate drug discovery.

Many research teams having been looking at different ways to treat heart disease, including using immune therapies and regenerative approaches. Scientists at the University of Pennsylvania, for example, developed genetically modified T cells to attack and remove cardiac fibroblasts, which can lead to cardiac fibrosis. Vanderbilt University researchers identified Roche’s SYN0012, originally designed to treat rheumatoid arthritis, as a promising candidate that could dampen inflammation of heart tissue after a heart attack. Such inflammation can progress to acute episodes and chronic heart failure.

To help repair damaged cardiac tissue after a heart attack, scientists at the University of Cambridge in the United Kingdom and the University of Washington combined two types of cells derived from human stem cells—heart muscle cells and supportive epicardial cells that help the muscle cells live longer. A team at the the Morgridge Institute for Research previously added a drug called RepSox to stem cells to build better smooth muscle cells that can grow into functional arterial cells.

The Queen Mary researchers believe the 14 regions of the genome they fingered in their new study could be just the beginning of a larger story about genes and heart disease.  “Our academic and commercial partners are further developing these AI algorithms to analyze other aspects of cardiac structure and function,” lead researcher Nay Aung said in the statement.

Aung and colleagues argue the genetic markers they’ve already uncovered could help identify those at high risk of developing heart disease or open up new avenues for 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,” Aung said.

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