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Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches

Luyao Jia et al · BMC · 2026

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Abstract Background Carotid atherosclerosis is a kind of systemic atherosclerosis in the carotid arteries. It remains one of the leading causes of ischemic stroke. However, the efficiency of treatment is insufficient. Thus, it is urgent to deepen the understanding of the underlying mechanisms in carotid atherosclerosis, which may facilitate the development of effective therapeutic interventions. Phenotypic switching of vascular smooth muscle cells (VSMCs) is recognized as a central process in atherosclerosis progression. However, the key regulatory genes involved in this process during carotid atherosclerosis are not fully understood. Methods Three gene expression datasets, GSE43292, GSE100927, and GSE28829 were downloaded from Gene Expression Omnibus (GEO) database, covering carotid atherosclerosis and control groups. we integrated bioinformatics analysis with three machine learning algorithms to identify the hub genes associated with carotid atherosclerosis. Subsequent validation using clinical specimens and murine atherosclerosis confirmed the expression of the hub genes at both the mRNA and protein levels. Furthermore, in vitro phenotypic switching model using human aortic smooth muscle cells (HASMCs) treated with pro‑atherogenic stimuli was established to identify the expression of hub genes and to investigate how knockdown of these hub genes in HASMCs influences VSMCs phenotypic switching. Results Through the integration of bioinformatics analysis and three machine learning algorithms, we identified PALS2 and CASQ2 as consistently downregulated genes in carotid atherosclerotic plaques compared to normal tissues. Gene interaction network analysis suggested that PALS2 and CASQ2 may cooperatively regulate calcium homeostasis and calcification in VSMCs. This finding was further supported by consistent downregulation of both genes in clinical atherosclerotic samples, murine atherosclerosis, and in HASMCs exposed to pro‑atherogenic stimuli. Functionally, knockdown of either gene enhanced VSMCs phenotypic switching, calcium deposition and amplifies CREB1 phosphorylation, collectively demonstrating their protective role in mitigating atherosclerosis. Conclusions This study identifies PALS2 and CASQ2 as novel regulators involved in the VSMCs phenotypic switching and calcification in carotid atherosclerosis. Both genes are consistently downregulated in atherosclerotic plaques and function as upstream suppressors of a calcium-CREB1 calcification axis. These findings provide novel insights into the molecular mechanisms of atherosclerosis and highlight PALS2 and CASQ2 as potential therapeutic targets for intervention.

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APA 7

al, L. J. E. (2026). Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches. https://doi.org/10.1186/s12872-026-05748-2

MLA

al, Luyao Jia et. "Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches." 2026. https://doi.org/10.1186/s12872-026-05748-2.

Chicago

al, Luyao Jia et. 2026. "Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches.". https://doi.org/10.1186/s12872-026-05748-2.

Harvard

al, L. J. E. 2026, Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches, BMC, available at: https://doi.org/10.1186/s12872-026-05748-2 [Accessed 29 Jun. 2026].

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Título
Identification of hub targets involved in carotid atherosclerosis through bioinformatics and machine learning approaches
Autor / colaboradores
Luyao Jia et al
Editorial
BMC
Año de publicación
2026
ISSN
1471-2261
ISSN
1471-2261
Idioma
eng

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