Unravelling molecular mechanisms in atherosclerosis using cellular models and omics technologies

Despite the discovery and prevalent clinical use of potent lipid-lowering therapies, including statins and PCSK9 inhibitors, cardiovascular diseases (CVD) caused by atherosclerosis remain a large unmet clinical need, accounting for frequent deaths worldwide. The pathogenesis of atherosclerosis is a...

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Veröffentlicht in:Vascular pharmacology 2024-12, p.107452
Hauptverfasser: Kardassis, Dimitris, Vindis, Cécile, Stancu, Camelia Sorina, Toma, Laura, Gafencu, Anca Violeta, Georgescu, Adriana, Alexandru-Moise, Nicoleta, Molica, Filippo, Kwak, Brenda R, Burlacu, Alexandrina, Hall, Ignacio Fernando, Butoi, Elena, Magni, Paolo, Wu, Junxi, Novella, Susana, Gamon, Luke F, Davies, Michael J, Caporali, Andrea, de la Cuesta, Fernando, Mitić, Tijana
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Sprache:eng
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Zusammenfassung:Despite the discovery and prevalent clinical use of potent lipid-lowering therapies, including statins and PCSK9 inhibitors, cardiovascular diseases (CVD) caused by atherosclerosis remain a large unmet clinical need, accounting for frequent deaths worldwide. The pathogenesis of atherosclerosis is a complex process underlying the presence of modifiable and non-modifiable risk factors affecting several cell types including endothelial cells (ECs), monocytes/macrophages, smooth muscle cells (SMCs) and T cells. Heterogeneous composition of the plaque and its morphology could lead to rupture or erosion causing thrombosis, even a sudden death. To decipher this complexity, various cell model systems have been developed. With recent advances in systems biology approaches and single or multi-omics methods researchers can elucidate specific cell types, molecules and signalling pathways contributing to certain stages of disease progression. Compared with animals, in vitro models are economical, easily adjusted for high-throughput work, offering mechanistic insights. Hereby, we review the latest work performed employing the cellular models of atherosclerosis to generate a variety of omics data. We summarize their outputs and the impact they had in the field. Challenges in the translatability of the omics data obtained from the cell models will be discussed along with future perspectives.
ISSN:1879-3649