What's Happening?
An international team of researchers has developed plasma proteomic signatures to quantify atherosclerotic burden, offering a potential alternative to imaging techniques. Using machine learning, they identified four distinct proteomic signatures that effectively discriminate individuals with known atherosclerotic disease and predict future cardiovascular events. These findings were presented at the ASHG Conference, highlighting the potential of plasma proteomics in cardiovascular risk assessment.
Why It's Important?
This advancement in biomarker identification could revolutionize cardiovascular disease prevention by providing a scalable and accessible method for detecting subclinical atherosclerosis. It may lead to improved risk prediction and personalized prevention strategies, potentially reducing the incidence of major adverse cardiovascular events. This could have significant implications for healthcare systems and public health policies focused on cardiovascular disease management.
