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AI Tool Identifies 17 Gene Variants Linked to Heart Disease

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Scientists at Icahn School of Medicine at Mount Sinai have discovered uncommon DNA changes in 17 heart disease-related genes with the help of a new AI tool. Heart disease is the number one cause of death worldwide.

The study, published June 11th in Nature Genetics, explains how these genetic findings could lead to more effective treatments and individualized care for those with heart disease.

A rare variant association study using exome sequencing data was performed on a machine learning-based marker for coronary artery disease (CAD). This identified rare coding variants in 17 genes, revealing insights into the molecular basis of CAD. Credit: Ron Do, PhD, and Ben Omega Petrazzini, BS, at Icahn Mount Sinai.

The team used an acronym called ISCAD as a computer-based score for coronary artery disease (CAD). The score was created by examining EHRs from over half a million patients. In order to generate the ISCAD score, the AI tool considered different health data such as lab results, symptoms and medications among others.

After that, the scientists cross-checked this number against rare genetic alterations located within participant’s DNA. Out of them were several genes previously unknown to affect cardiac issues – altogether they found seventeen.

Dr Ron Do senior author explained that knowing about these genes teaches us more about heart diseases; some are novel while others were known already shown influencing cardiovascular health states. What sets apart this research from other ones is that it uses artificial intelligence which may find genetic insights overlooked by typical methods leading potentially to innovative therapies.

Although only seen in few individuals, infrequent substitutions can greatly alter susceptibility towards illnesses. This research investigated these types of changes so as to elucidate on genetic foundations underlying heart diseases as well identify fresh targets for treatment Interventional Cardiologists-Omaha NE said.

Moreover, it builds upon previous studies demonstrating how machine learning can create a holistic heart disease score using electronic health records. Such an approach helped researchers discover additional rare genetic variations tied to heart diseases.

Accordingly, authors plan to further examine these genes while employing AI systems into investigation surrounding other complicated ailments too. They aim at deepening our knowledge on illnesses origins discovering new remedies and enhancing care provision for patients suffering from various conditions medical school interview questions

Source: dicardiology