Researchers use artificial intelligence to predict cardiovascular disease

Utilizing artificial intelligence, researchers can potentially forecast cardiovascular diseases, including arterial fibrillation and heart failure, by analyzing the genetic information within patients’ DNA, as indicated by a recent study conducted at Rutgers. Zeeshan Ahmed, a key member of the Rutgers Institute for Health, Health Care Policy, and Aging Research (IFH), and the lead author of the study published in Genomics, stated, “Through the successful implementation of our model, we were able to predict the correlation of highly significant cardiovascular disease genes with demographic factors such as race, gender, and age.

As per the World Health Organization, cardiovascular disease stands as the primary global cause of mortality, with over 75 percent of premature cases deemed preventable. Atrial fibrillation and heart failure jointly contribute to approximately 45 percent of all cardiovascular disease-related deaths.

Despite notable progress in cardiovascular disease diagnostics, prevention, and treatment, an alarming statistic persists – about half of diagnosed patients reportedly succumb within five years, owing to diverse factors encompassing both genetic and environmental influences. Researchers emphasize that the integration of artificial intelligence (AI) and machine learning holds the potential to expedite the identification of crucial genes implicated in cardiovascular disease, offering prospects for enhanced diagnostic procedures and treatment strategies.

In a study conducted by the Rutgers Institute for Health, Health Care Policy, and Aging Research (IFH), researchers scrutinized both healthy individuals and those diagnosed with cardiovascular disease. Employing AI and machine-learning models, they delved into genes associated with prevalent cardiovascular disease manifestations, including atrial fibrillation and heart failure. This approach aims to deepen our understanding and pave the way for advancements in the diagnosis and treatment of cardiovascular diseases.

The research revealed a cluster of genes strongly linked to the presence of cardiovascular disease. Moreover, the investigators observed notable distinctions concerning cardiovascular disease based on factors such as race, gender, and age. Specifically, heart failure demonstrated correlations with age and gender, while atrial fibrillation exhibited associations with age and race. For instance, in the examined patient population, a higher age corresponded to an increased likelihood of having cardiovascular disease.

Zeeshan Ahmed, an assistant professor in the Department of Medicine at Rutgers Robert Wood Johnson Medical School, and a core faculty member at the Rutgers Institute for Health, emphasized the importance of timely comprehension and accurate treatment of cardiovascular disease. He asserted that such advancements would ultimately benefit millions by diminishing the elevated risk of mortality and enhancing overall quality of life.

The researchers suggested that future investigations should expand upon this methodology by examining the entire set of genes in individuals with cardiovascular disease. Such an approach may unveil crucial biomarkers and risk factors linked to susceptibility to cardiovascular disease.

Contributors to the study include Vignesh Venkat, Habiba Abdelhalim, and William DeGroat from the Rutgers Institute for Health (IFH), as well as Saman Zeeshan from the Rutgers Cancer Institute of New Jersey.

More information: Vignesh Venkat et al, Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for translational research and precision medicine, Genomics (2023). DOI: 10.1016/j.ygeno.2023.110584