Identification of immune-related biomarkers and immune infiltrations of intracranial aneurysm with subarachnoid hemorrhage by machine-learning strategies
<b>Background:</b> Subarachnoid hemorrhage (SAH) risk increases with intracranial aneurysms (IA), but their relationship remains unclear. <b>Methods:</b> We explored SAH-IA links using machine learning and bioinformatics, identifying 66 IA-related SAH genes. KEGG analysis highlighted pathways like NF-κB, TNF, and COVID-19. <b>Results:</b> Two immune-related genes (ZNF281, LRRN3) were identified, and a ceRNA network was constructed. Ten potential SAH-IA drugs were screened via CMAP. <b>Conclusion:</b> ZNF281 and LRRN3 may regulate immune pathways (T cells, NK cells, macrophages), influencing IA-related SAH development, and could serve as therapeutic targets.
Authors
- Xiao Jin (ORCID: https://orcid.org/0000-0002-4676-1062)
- Xiang Zhao (ORCID: https://orcid.org/0000-0002-9353-6896)
Institutions
- Beijing University of Chinese Medicine (CN)
- China Medical University (CN)
Publication Details
- Journal
- Computer Methods in Biomechanics & Biomedical Engineering
- Published
- 2025-04-23
- DOI
- https://doi.org/10.1080/10255842.2025.2495250
- Primary Topic
- Intracranial Aneurysms: Treatment and Complications
- Type
- article
- Field-Weighted Citation Impact
- 0.00