ArticleFrontiers in cardiovascular medicine2022
Screening for key genes in circadian regulation in advanced atherosclerosis: A bioinformatic analysis.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
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- Review
- Identifying and Diagnosing Lytic Cell Death Genes in Atherosclerosis Using Machine Learning and Bioinformatics.Journal of inflammation research · 2025Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
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Abstract
Background: Atherosclerosis (AS) is the most important cardiovascular disease threatening human health, leading to adverse events such as myocardial infarction and stroke. The research on the pathogenesis and causes of AS is being improved step by step, and many factors are associated with AS. However, the relationship between circadian regulation and the pathogenesis of AS is still unclear. Our study identified 2 key genes of circadian regulation in AS by bioinformatics analysis, which provides new perspectives to understand the relationship between circadian rhythm and AS. Methods: We downloaded samples of early and advanced AS from public databases, screened key genes by weighted gene co-expression network analysis (WGCNA) and Lasso, calculated the immune cell content of the samples using "CIBERSORT," and analyzed the relationship between key genes and immune cells. Results: We obtained the most relevant core modules for advanced AS and analyzed the functions of these modules. Two circadian rhythm-related genes were obtained, which influence the immune infiltration of this late AS. ROC curves demonstrated the efficacy of key genes to differentiate between early and advanced AS. Conclusion: We identified 2 genes most associated with circadian rhythms in advanced AS, whose association with AS has not been elucidated and may become the next therapeutic target.
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