Diagnostic biomarkers and immune infiltration profiles common to COVID-19, acute myocardial infarction and acute ischaemic stroke using bioinformatics methods and machine learning
We employed bioinformatics methods and machine learning to investigate common diagnostic biomarkers and immune infiltration characteristics of COVID-19, AMI and AIS. Functional and pathway analyses indicated that the co-DEGs were primarily enriched in immune inflammatory responses related to leukocytes and neutrophils. Through two machine learning approaches and the PPI network, and subsequent validation and evaluation, we identified S100A12 as a potential common therapeutic target and biomarker related to immune response that may influence these three diseases.
Authors
- Qi Wu (ORCID: https://orcid.org/0000-0003-0499-0577)
- Juan Wu
- Yanan Ma (ORCID: https://orcid.org/0000-0003-0385-8929)
- Li Yang (ORCID: https://orcid.org/0000-0002-2299-0258)
- Lan Bao (ORCID: https://orcid.org/0000-0001-9269-9565)
- Li Ma (ORCID: https://orcid.org/0000-0002-5444-5262)
- Si-Rong Ma
- Zhenhai Wang (ORCID: https://orcid.org/0000-0002-3677-0985)
- Yarong Wang (ORCID: https://orcid.org/0000-0002-4777-5730)
Institutions
- Ningxia Medical University (CN)
- Ningxia Medical University General Hospital (CN)
Publication Details
- Journal
- BMC Neurology
- Published
- 2025-05-08
- DOI
- https://doi.org/10.1186/s12883-025-04212-6
- Citations
- 1
- Primary Topic
- COVID-19 Clinical Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- Ningxia Medical University