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Transcriptomic research in atherosclerosis: Unravelling plaque phenotype and overcoming methodological challenges

Articolo
Data di Pubblicazione:
2023
Citazione:
Transcriptomic research in atherosclerosis: Unravelling plaque phenotype and overcoming methodological challenges / M. Sopić, K. Karaduzovic-Hadziabdic, D. Kardassis, L. Maegdefessel, F. Martelli, A. Meerson, J. Munjas, L.S. Niculescu, M. Stoll, P. Magni, Y. Devaux. - In: JOURNAL OF MOLECULAR AND CELLULAR CARDIOLOGY PLUS. - ISSN 2772-9761. - 6:(2023), pp. 100048.1-100048.10. [10.1016/j.jmccpl.2023.100048]
Abstract:
Atherosclerotic disease is a major cause of acute cardiovascular events. A deeper understanding of its underlying mechanisms will allow advancing personalized and patient-centered healthcare. Transcriptomic research has proven to be a powerful tool for unravelling the complex molecular pathways that drive atherosclerosis. However, low reproducibility of research findings and lack of standardization of procedures pose significant challenges in this field. In this review, we discuss how transcriptomic research can help in understanding the different phenotypes of the atherosclerotic plaque that contribute to the development and progression of atherosclerosis. We highlight the methodological challenges that need to be addressed to improve research outputs, and emphasize the importance of research protocols harmonization. We also discuss recent advances in transcriptomic research, including bulk or single-cell sequencing, and their added value in plaque phenotyping. Finally, we explore how integrated multiomics data and machine learning improve understanding of atherosclerosis and provide directions for future research.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
Atherosclerotic plaque; Transcriptomics; Data integration; Machine learning
Elenco autori:
M. Sopić, K. Karaduzovic-Hadziabdic, D. Kardassis, L. Maegdefessel, F. Martelli, A. Meerson, J. Munjas, L.S. Niculescu, M. Stoll, P. Magni, Y. Devaux
Autori di Ateneo:
MAGNI PAOLO ( autore )
Link alla scheda completa:
https://air.unimi.it/handle/2434/1018190
Link al Full Text:
https://air.unimi.it/retrieve/handle/2434/1018190/2326905/1-s2.0-S2772976123000181-main-2.pdf
Progetto:
Comprehensive and personalized assessment of acute coronary syndrome by multiomic approach and artificial intelligence strategy (CardioSCOPE)
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Aree Di Ricerca

Settori (3)


Settore MED/04 - Patologia Generale

Settore MED/05 - Patologia Clinica

Settore MED/13 - Endocrinologia
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Realizzato con VIVO | Progettato da Cineca | 25.11.5.0