Multiomics tools for improved atherosclerotic cardiovascular disease management

Miron Sopic; Baiba Vilne; Eva Gerdts; Fábio Trindade; Shizuka Uchida; Soliman Khatib; Stephanie Bezzina Wettinger; Yvan Devaux; Paolo Magni; EU-AtheroNET COST Action CA21153

doi:10.1016/j.molmed.2023.09.004

Multiomics tools for improved atherosclerotic cardiovascular disease management

Trends Mol Med. 2023 Dec;29(12):983-995. doi: 10.1016/j.molmed.2023.09.004. Epub 2023 Oct 6.

Authors

Miron Sopic¹, Baiba Vilne², Eva Gerdts³, Fábio Trindade⁴, Shizuka Uchida⁵, Soliman Khatib⁶, Stephanie Bezzina Wettinger⁷, Yvan Devaux⁸, Paolo Magni⁹; EU-AtheroNET COST Action CA21153

Affiliations

¹ Cardiovascular Research Unit, Department of Precision Health, 1A-B rue Edison, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg; Department of Medical Biochemistry, Faculty of Pharmacy, University of Belgrade, Belgrade, 11000, Serbia.
² Bioinformatics Laboratory, Rīga Stradiņš University, Rīga, LV-1007, Latvia.
³ Center for Research on Cardiac Disease in Women, Department of Clinical Science, University of Bergen, Bergen, 5020, Norway.
⁴ Cardiovascular R&D Centre - UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, 4099-002, Portugal.
⁵ Center for RNA Medicine, Department of Clinical Medicine, Aalborg University, Copenhagen, SV, DK-2450, Denmark.
⁶ Natural Compounds and Analytical Chemistry Laboratory, MIGAL-Galilee Research Institute, Kiryat Shemona, 11016, Israel; Department of Biotechnology, Tel-Hai College, Upper Galilee 12210, Israel.
⁷ Department of Applied Biomedical Science, Faculty of Health Sciences, University of Malta, Msida, 2080, Malta.
⁸ Cardiovascular Research Unit, Department of Precision Health, 1A-B rue Edison, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg. Electronic address: Yvan.devaux@lih.lu.
⁹ Department of Pharmacological and Biomolecular Sciences 'Rodolfo Paoletti', Università degli Studi di Milano, Via G. Balzaretti 9, 20133 Milano, Italy; IRCCS MultiMedica, Via Milanese 300, 20099 Sesto S. Giovanni, Milan, Italy. Electronic address: paolo.magni@unimi.it.

PMID: 37806854
DOI: 10.1016/j.molmed.2023.09.004

Abstract

Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care.

Keywords: artificial intelligence; atherosclerotic cardiovascular disease; data integration; machine learning; multiomics.

Publication types

Review
Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence
Atherosclerosis* / diagnosis
Atherosclerosis* / genetics
Atherosclerosis* / therapy
Cardiovascular Diseases* / diagnosis
Cardiovascular Diseases* / genetics
Cardiovascular Diseases* / therapy
Humans
Machine Learning
Multiomics