ArticleBMC medical genomics2023
Identification of potential diagnostic biomarkers of atherosclerosis based on bioinformatics strategy.
Article in BMC medical genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Anti-Inflammatory Interleukins in the Pathogenesis of Atherosclerosis.International journal of molecular sciences · 2026Review
- Multi-omics data mining combined with experimental validation reveals ferroptosis- and autophagy-associated hub genes as diagnostic candidates and immune modulators in atherosclerosis.Animal models and experimental medicine · 2026Article
- γδ T Cells in Autoinflammatory Diseases.Cells · 2026Review
- Causal Implication of CD52-Driven Immune Dysregulation in Sarcopenic Obesity: Integrating Mendelian Randomization and Multiomics Profiling.Clinical interventions in aging · 2026Article
- Exploring the causal links between inflammation-related genes and atherosclerosis through Mendelian randomization analysis.Medicine · 2025Article
- Investigation of hub-shared genes and regulatory mechanisms of rheumatoid arthritis and atherosclerosis.Clinical rheumatology · 2025Article
- Comprehensive bioinformatics analysis identifies hub genes associated with immune cell infiltration in early-onset schizophrenia.BMC psychiatry · 2025Article
- Recent Advances in the Mutual Regulation of m6A Modification and Non-Coding RNAs in Atherosclerosis.International journal of general medicine · 2025Review
- Identification of Potential Diagnostic Biomarkers of Carotid Atherosclerosis in Obese Populations.Journal of inflammation research · 2025Article
- Article
- Identification and validation of hub genes involved in foam cell formation and atherosclerosis developmentPeerJ · 2023Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAtherosclerosis is the main pathological change in atherosclerotic cardiovascular disease, and its underlying mechanisms are not well understood. The aim of this study was to explore the hub genes involved in atherosclerosis and their potential mechanisms through bioinformatics analysis.
methodsThree microarray datasets from Gene Expression Omnibus (GEO) identified robust differentially expressed genes (DEGs) by robust rank aggregation (RRA). We performed connectivity map (CMap) analysis and functional enrichment analysis on robust DEGs and constructed a protein‒protein interaction (PPI) network using the STRING database to identify the hub gene using 12 algorithms of cytoHubba in Cytoscape. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic potency of the hub genes.The CIBERSORT algorithm was used to perform immunocyte infiltration analysis and explore the association between the identified biomarkers and infiltrating immunocytes using Spearman's rank correlation analysis in R software. Finally, we evaluated the expression of the hub gene in foam cells.
resultsA total of 155 robust DEGs were screened by RRA and were revealed to be mainly associated with cytokines and chemokines by functional enrichment analysis. CD52 and IL1RN were identified as hub genes and were validated in the GSE40231 dataset. Immunocyte infiltration analysis showed that CD52 was positively correlated with gamma delta T cells, M1 macrophages and CD4 memory resting T cells, while IL1RN was positively correlated with monocytes and activated mast cells. RT-qPCR results indicate that CD52 and IL1RN were highly expressed in foam cells, in agreement with bioinformatics analysis.
conclusionsThis study has established that CD52 and IL1RN may play a key role in the occurrence and development of atherosclerosis, which opens new lines of thought for further research on the pathogenesis of atherosclerosis.
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