Abstract
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.
Originalsprog | Engelsk |
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Artikelnummer | 107452 |
Tidsskrift | Vascular Pharmacology |
Vol/bind | 158 |
Antal sider | 19 |
ISSN | 1537-1891 |
DOI | |
Status | Udgivet - 2025 |
Bibliografisk note
Funding Information:The present review paper discusses the advantages and disadvantages of in vitro models currently used for the study of atherosclerosis. Review is supported by the COST Action CA21153 \u201CNetwork for implementing multiomic approaches in atherosclerotic cardiovascular disease prevention and research (AtheroNET)\u201D and is the joint effort of its members. AtheroNET is aimed at providing a comprehensive framework for researchers interested in cellular and molecular research in the field of atherosclerosis as well as for clinical researchers in this area, empowering translational links between them. The network is focusing on the use of multiple omics technologies and data integration through machine learning/artificial intelligence ML/AI approached to bridge the novel paradigms in prevention, diagnosis, and treatment of atherosclerotic cardiovascular disease (ASCVD). The AtheroNET COST Action (https://atheronet.eu/) promotes specific initiatives such as the creation of inventories for in vitro and in vivo experimental models of atherosclerosis, in order to facilitate knowledge transfer; generation of technical notes, relating to the use of the models reported in the above-mentioned inventories; and review articles addressing the specific topics arising from this Action (Fig. 2).This article is based upon work from COST Action AtheroNET, CA21153, supported by COST (European Cooperation in Science and Technology). Dimitris Kardassis is supported by the Hellenic Foundation for Research and Innovation (HFRI) Research Program \u201CFunding Projects in Leading-Edge Sectors \u2013 RRFQ: Basic Research Financing (Horizontal support for all Sciences) grant No 15529 and MSCA Staff Exchanges program CardioSCOPE Grant No 101086397. Camelia Sorina Stancu is supported by the Romanian Academy, and Ministry of Research, Innovation, and Digitization, CNCS-UEFISCDI grant number: PN-III-P4-PCE-2021-0831., Laura Toma is supported by the Romanian Academy, and Ministry of Research, Innovation, and Digitization, CNCS-UEFISCDI, grant number PN-III-P2-2.1-PED-2021-1929., Anca Gafencu is supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS - UEFISCDI, project number PN-III-P4-PCE-2021-1755, within PNCDI III. Adriana Georgescu and Nicoleta Alexandru-Moise are supported by the Romania's National Recovery and Resilience Plan, \u201CEuropean Union - NextGenerationEU\", PNRR-III-C9-2022-I8, CF 93/15.11.2022, Financing Contract no.760063/23.05.2023, and by the Romanian Academy. Brenda R. Kwak is supported by the Swiss National Science Foundation, grant numbers 310030_212291/1 and 310030_182573). Ignacio Fernando Hall is supported by a British Heart Foundation (BHF) individual fellowship award (FS/IPBSRF/22/27050). The work of Paolo Magni is supported in part by the European Union (CardioSCOPE 10108639 - HORIZON-MSCA-2021-SE-01-01 MSCA Staff Exchanges 2021, AtheroNET COST Action CA21153), the Italian Space Agency (ASI; N. 2023-7-HH.0 CUP F13C23000050005 MicroFunExpo) and the Italian Ministry of Health (project PNRR-MCNT2-2023-12377808, PNRR: M6/C2_CALL 2023). Junxi Wu is supported by UKRI MRC New Investigator Research Grant (NIRG) (Ref: MR/V029827/1). Susana Novella is supported by the Spanish Ministry of Science and Innovation (ISCIII) (PI19/01714; PI22/1083) co-financed by the European Regional Development Fund (ERDF) and by the Generalitat Valenciana (CIAICO 2021/211), Luke F. Gamon is supported by a HALRIC grant (20230616_PP01). Michael J. Davies is supported by the Novo Nordisk Foundation (Laureate grant NNF20SA0064214). Fernando de la Cuesta is supported by Programa de Atracci\u00F3n de Talento (Modalidad 1), Comunidad Aut\u00F3noma de Madrid 2023-5AIND-28938 and Ministerio de Ciencia, e Innovaci\u00F3n y Universidades y Fondo Europeo de Desarrollo Regional (PID2021-126274OB-I00; CNS2022-135368). Andrea Caporali and Tijana Miti\u0107 acknowledge the support of the British Heart Foundation (BHF) Project Grant (PG/22/10916). Tijana Miti\u0107 is supported by the University of Edinburgh and British Heart Foundation (BHF) Research Excellence Award REA3 (RE/18/5/34216).
Funding Information:
Susana Novella is supported by the Spanish Ministry of Science and Innovation (ISCIII) ( PI19/01714 ; PI22/1083 ) co-financed by the European Regional Development Fund (ERDF) and by the Generalitat Valenciana ( CIAICO 2021/211 ).
Funding Information:
Tijana Miti\u0107 is supported by the University of Edinburgh and British Heart Foundation (BHF) Research Excellence Award REA3 ( RE/18/5/34216 ).
Funding Information:
Dimitris Kardassis is supported by the Hellenic Foundation for Research and Innovation (HFRI) Research Program \u201CFunding Projects in Leading-Edge Sectors \u2013 RRFQ: Basic Research Financing (Horizontal support for all Sciences) grant No 15529 and MSCA Staff Exchanges program CardioSCOPE Grant No 101086397 .
Funding Information:
Adriana Georgescu is supported by the Romania's National Recovery and Resilience Plan , PNRR-III-C9-2022-I8 , CF 93/15.11.2022 , Financing Contract no. 760063/23.05.2023 , and by the Romanian Academy .
Funding Information:
This article is based upon work from COST Action AtheroNET, CA21153 , supported by COST (European Cooperation in Science and Technology).
Funding Information:
Luke F. Gamon is supported by a HALRIC grant ( 20230616_PP01 ).
Funding Information:
Anca Gafencu is supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS - UEFISCDI , project number PN-III-P4-PCE-2021-1755 , within PNCDI III.
Funding Information:
Laura Toma is supported by the Romanian Academy, and Ministry of Research, Innovation, and Digitization, CNCS-UEFISCDI, grant number PN-III-P2-2.1-PED-2021-1929 .
Funding Information:
Michael J. Davies is supported by the Novo Nordisk Foundation (Laureate grant NNF20SA0064214 ).
Funding Information:
Camelia Sorina Stancu is supported by the Romanian Academy, and Ministry of Research, Innovation, and Digitization, CNCS-UEFISCDI grant number: PN-III-P4-PCE-2021-0831 .
Funding Information:
Paolo Magni is supported by HORIZON-MSCA-2021-SE-01-01 , MSCA Staff Exchanges CardioSCOPE 101086397) and by the Italian Space Agency (ASI; N. 2023-7-HH.0 CUP F13C23000050005 MicroFunExpo).
Funding Information:
Brenda R. Kwak is supported by the Swiss National Science Foundation , grant numbers 310030_212291/1 and 310030_182573 ).
Funding Information:
Ignacio Fernando Hall is supported by a British Heart Foundation (BHF) individual fellowship award ( FS/IPBSRF/22/27050 ).
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