Exploring the shared biomarkers between cardioembolic stroke and atrial fibrillation by WGCNA and machine learning
In our study, we utilized WGCNA, PPI network analysis, and machine learning to identify four hub genes significantly associated with CS and AF. Functional annotation outcomes revealed that inherent pathways related to the immune response connected to the recognized genes might could pave the way for further research on the etiological mechanisms and therapeutic targets for CS and AF.
Authors
- Qi Zhu (ORCID: https://orcid.org/0000-0001-8393-9360)
- Xiting Wang (ORCID: https://orcid.org/0000-0002-1846-1118)
- Yibo Li (ORCID: https://orcid.org/0000-0002-4174-8600)
- Bingbing Zhang (ORCID: https://orcid.org/0000-0002-1334-5812)
- Tengteng Li (ORCID: https://orcid.org/0009-0008-2416-1788)
- Tao Lu (ORCID: https://orcid.org/0000-0001-6749-1674)
- Jingxin Zhang (ORCID: https://orcid.org/0009-0009-3111-5963)
Institutions
- Beijing University of Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Cardiovascular Medicine
- Published
- 2024-08-29
- DOI
- https://doi.org/10.3389/fcvm.2024.1375768
- Citations
- 7
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.81