ArticleHeliyon2023
Integrated analysis of C3AR1 and CD163 associated with immune infiltration in intracranial aneurysms pathogenesis.
Article in Heliyon, 2023. 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Exploration of Immune-Related Transcription Control/Regulation in Intracranial Aneurysm Through KEGG Analysis and in-vivo Validation.Journal of inflammation research · 2025Article
- Causal association between circulating inflammatory cytokines and intracranial aneurysm and subarachnoid hemorrhage.European journal of neurology · 2024Article
- Bioinformatics analysis revealed the potential crosstalk genes and molecular mechanisms between intracranial aneurysms and periodontitis.BMC medical genomics · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: To identify potential immune-related biomarkers, molecular mechanism, and therapeutic agents of intracranial aneurysms (IAs). Methods: We identified the differentially expressed genes (DEGs) between IAs and control samples from GSE75436, GSE26969, GSE6551, and GSE13353 datasets. We used weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) analysis to identify immune-related hub genes. We evaluated the expression of hub genes by using qRT-PCR analysis. Using miRNet, NetworkAnalyst, and DGIdb databases, we analyzed the regulatory networks and potential therapeutic agents targeting hub genes. Least absolute shrinkage and selection operator (LASSO) logistic regression was performed to identify optimal biomarkers among hub genes. The diagnostic value was validated by external GSE15629 dataset. Results: We identified 227 DEGs and 22 differentially infiltrating immune cells between IAs and control samples from GSE75436, GSE26969, GSE6551, and GSE13353 datasets. We further identified 41 differentially expressed immune-related genes (DEIRGs), which were primarily enriched in the chemokine-mediated signaling pathway, myeloid leukocyte migration, endocytic vesicle membrane, chemokine receptor binding, chemokine activity, and viral protein interactions with cytokines and their receptors. Among 41 DEIRGs, 10 hub genes including C3AR1, CD163, CCL4, CXCL8, CCL3, TLR2, TYROBP, C1QB, FCGR3A, and FCGR1A were identified with good diagnostic values (AUC >0.7). Hsa-mir-27a-3p and transcription factors, including YY1 and GATA2, were identified the primary regulators of hub genes. 92 potential therapeutic agents targeting hub genes were predicted. C3AR1 and CD163 were finally identified as the best diagnostic biomarkers using LASSO logistic regression (AUC = 0.994). The diagnostic value of C3AR1 and CD163 was validated by the external GSE15629 dataset (AUC = 0.914). Conclusions: This study revealed the importance of C3AR1 and CD163 in immune infiltration in IAs pathogenesis. Our finding provided a valuable reference for subsequent research on the potential targets for molecular mechanisms and intervention of IAs.
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