Despite considerable life-saving progress, cardiovascular diseases (CVDs) remain the leading cause of death globally, claiming an estimated 17.9 million lives each year. Most CVD-related deaths are from heart attacks and strokes, with a significant portion occurring prematurely in people under 70 years of age.
Among CVDs, atherosclerotic cardiovascular disease (ASCVD) ranks as the most prevalent. Atherosclerosis is a general term for many different disorders that result from thickening and loss of elasticity in the arterial wall. It is a severe disorder and the leading 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. The plaque may cause ASCVD, which includes stroke, heart attack, and damage to peripheral arteries (in the legs), all of which can lead to death if left untreated.
To develop personalized ASCVD strategies, it is pivotal to go beyond the traditional risk factors. By identifying new pathophysiological players that can modulate the individual CVD risk, it can be fully exploited through integrative bioinformatic algorithms.
Multi-omics approach
Recent advancements in omic technologies (the scientific fields associated with measuring biological molecules in a high-throughput manner) have led to significant discoveries, uncovering connections between genetic, epigenetic, transcriptomic, proteomic, and metabolomic data with various disease processes. This wealth of data has fuelled the development of personalized medicine, primarily seen in oncology, improving disease management and outcomes. There is growing evidence that omic technologies could offer new solutions in ASCVD. However, challenges remain in the clinical application of omic data, including insufficient evidence from large multi-center studies, technological complexity, lack of data integration pipelines, and standards in lab protocols, as well as specialists proficient in omic approaches for everyday clinical practice.
Introducing COST Action AtheroNET
The new Network for implementing multiomics approaches in atherosclerotic cardiovascular disease prevention and research (AtheroNET) intends to consolidate and connect experts from different fields into a pan-European and international network that will focus on the use of multi-omics and imagining technologies and data integration through Artificial Intelligence (AI)/Machine Learning (ML) approaches.
AI and ML have the potential to revolutionise the approach to ASCVD research and treatment by enabling personalised medicine, early detection, optimised therapies, and accelerated drug discovery. As these technologies continue to advance, they are expected to play an increasingly prominent role in improving outcomes for patients with ASCVD. The network gathers 365 individuals from 33 countries and includes a high proportion of Young Researchers.
AtheroNET aims to tackle challenges by using these new tools. Its main goal is to create a platform where people can work together to see how omic approaches can help understand ASCVD better. The network will develop new, reliable ways to predict and diagnose ASCVD, which can be used in hospitals and clinics. Eventually, these new methods will be combined with advanced imaging technologies and AI to better predict and manage heart disease risks in the short and long term.
The cutting-edge mission of the COST Action AtheroNET is to promote a discussion on the role of multiomic technologies and AI/ML strategies to accelerate research on ASCVD. To achieve this, AtheroNET includes outstanding male and female junior investigators and top-level senior researchers, currently from 33 European countries, building an interdisciplinary network able to pursue research excellence and to train the next generation of scientists for the transfer of novel omic technologies from bench to bedside."
Prof. Paolo Magni, Chair of AtheroNET
AtheroNET has been established with its unique and comprehensive expertise to address urgent needs for new approaches in CVD prevention, diagnosis, and therapy. Considering the multifactorial nature of ASCVD, the Action involves experts from different fields to tackle these challenges through research and educational concepts, bringing interdisciplinary views and vision to the network. By combining basic research with clinical expertise and complex bioinformatics, AtheroNET will go beyond the state-of-the-art, and more importantly, will foster a new generation of scientists competent for the utilisation of omics in clinically-relevant settings. This COST Action will also facilitate the work on harmonisation of different methodologies and research protocols between laboratories making sure that novel discoveries are solid, replicable, and properly disseminated.
Branching out
The next Management Committee (MC) meeting of AtheroNET, coupled with a Working Group meeting, will be taking place in Valencia, Spain on 28th February and 1st March 2024.
"The upcoming meeting will foster excellence in AI/ML-based research to combat ASCVD, scientific discussions, as well as the preparation of dissemination activities for the scientific community, patients, and the lay public" explains Prof. George Kararigas, Science Communication Coordinator of AtheroNET.
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