Despite significant lifesaving advances, cardiovascular disease (CVD) remains the world’s leading cause of death, claiming an estimated 17.9 million lives each year. Most CVD-related deaths are due to heart attacks and strokes, with the majority occurring early in people under 70 years of age.

Among CVDs, atherosclerotic cardiovascular disease (ASCVD) ranks as the most prevalent. Atherosclerosis is a general term for a variety of diseases caused by thickening and loss of elasticity of artery walls. It is a severe disease and a major cause of morbidity and mortality in most developed countries. Atherosclerosis is caused by high blood pressure, smoking, or high cholesterol. That damage leads to the formation of plaque. Plaques can cause ASCVD, which includes stroke, heart attack, damage to peripheral arteries (legs), and can be fatal if left untreated.

To develop a personalized ASCVD strategy, it is critical to go beyond traditional risk factors. By identifying new pathophysiological players that can modulate an individual’s CVD risk, we can make the most of it through integrative bioinformatics algorithms.

Multi-omics approach

Recent advances in omic technologies (a scientific field that involves the measurement of biomolecules in a high-throughput manner) have made it possible to correlate genetic, epigenetic, transcriptomic, proteomic, and metabolomic data with various disease processes. This led to important discoveries. This wealth of data has facilitated the development of personalized medicine, primarily found in oncology, to improve disease management and outcomes. There is increasing evidence that omic technologies may offer new solutions in ASCVD. However, the clinical application of omic data is hampered by the lack of evidence from large-scale multicenter studies, the complexity of the techniques, the lack of data integration pipelines, the standards of experimental protocols, and the limitations of omic approaches for daily clinical practice. Challenges such as skilled professionals remain.

Introducing COST Action AtheroNET

A new network for implementing multi-omics approaches in atherosclerotic cardiovascular disease prevention and research (AtheroNET) brings together experts from different fields and focuses on the use of multi-omics, imaging techniques, and data integration. The aim is to integrate into a pan-European and international network dedicated to Through an artificial intelligence (AI)/machine learning (ML) approach.

AI and ML have the potential to revolutionize approaches to ASCVD research and treatment, enabling personalized medicine, early detection, optimized treatments, and accelerated drug discovery. As these technologies continue to advance, they are expected to play an increasingly important role in improving outcomes for patients with ASCVD. This network brings together his 365 people from 33 countries, including many young researchers.

AtheroNET aims to use these new tools to address these challenges. Its main goal is to create a platform where people can collaborate to see how an omic approach can help them better understand her ASCVD. This network will develop new and reliable methods for predicting and diagnosing ASCVD that can be used in hospitals and clinics. Ultimately, these new methods will be combined with advanced imaging techniques and AI to better predict and manage heart disease risk in the short and long term.

COST Action AtheroNET’s cutting-edge mission is to foster discussion on the role of multi-omic technologies and AI/ML strategies to accelerate ASCVD research. To achieve this, AtheroNET currently includes outstanding young male and female researchers and top senior researchers from 33 European countries, pursuing research excellence and promoting We are building an interdisciplinary network that can train the next generation of scientists for the transfer of new omic technologies. Place a bench next to your bed. ”

Professor Paolo Magni, Chairman of AtheroNET

AtheroNET was founded with unique and comprehensive expertise to address the urgent need for new approaches in the prevention, diagnosis, and treatment of CVD. Given the multi-causal nature of ASCVD, this action will involve experts from different fields to address these challenges through research and education concepts, bringing interdisciplinary views and vision to the network. By combining basic research with clinical expertise and complex bioinformatics, AtheroNET will move beyond the state of the art and, more importantly, develop a new generation of scientists capable of utilizing omics in clinically relevant settings. Masu. This COST action will also foster efforts towards harmonization of different methodologies and research protocols between laboratories, ensuring that new discoveries are robust, reproducible, and appropriately disseminated.

branch out

The next AtheroNET Management Committee (MC) meeting will be held in Valencia, Spain on February 28 and March 1, 2024, in conjunction with the working group meeting.

“The upcoming conference will promote excellence in AI/ML-based research to combat ASCVD, scientific discussion, and readiness for dissemination efforts to the scientific community, patients, and the general public.” Professor George Kararigas, Science Communication Coordinator at AtheroNET, explains: