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Background <p>Carotid atherosclerotic plaque is the primary cause of cardiovascular and cerebrovascular diseases. It is closely related to oxidative stress and immune inflammation. This bioinformatic study was conducted to identify key oxidative stress-related genes and key immune cell infiltration involved in the formation, progression, and stabilization of plaques and investigate the relationship between them.</p> Results <p>We show that the up-regulation of oxidative stress-related genes such as <i>IDH1</i> and <i>CD36</i> in resident-like macrophages and foam macrophages play a key role in the formation and progression of carotid atherosclerotic plaques.</p> Conclusions <p>We discuss the role of oxidative stress and immune inflammation in the formation, progression, and stabilization of plaques by combining predictive models with analysis of single-cell data. It introduced novel insights into the mechanisms underlying carotid atherosclerosis formation and plaque progression and may assist in identifying potential therapeutic targets for their treatment.</p>

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Exploring the role of oxidative stress in carotid atherosclerosis: insights from transcriptomic data and single-cell sequencing combined with machine learning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月29日

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  • Yiqin Yang,
  • Mei Dong

摘要

Background

Carotid atherosclerotic plaque is the primary cause of cardiovascular and cerebrovascular diseases. It is closely related to oxidative stress and immune inflammation. This bioinformatic study was conducted to identify key oxidative stress-related genes and key immune cell infiltration involved in the formation, progression, and stabilization of plaques and investigate the relationship between them.

Results

We show that the up-regulation of oxidative stress-related genes such as IDH1 and CD36 in resident-like macrophages and foam macrophages play a key role in the formation and progression of carotid atherosclerotic plaques.

Conclusions

We discuss the role of oxidative stress and immune inflammation in the formation, progression, and stabilization of plaques by combining predictive models with analysis of single-cell data. It introduced novel insights into the mechanisms underlying carotid atherosclerosis formation and plaque progression and may assist in identifying potential therapeutic targets for their treatment.