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ABSTRACT: Background
Myocardial infarction (MI) is one of the leading causes of death worldwide. Finding reliable diagnostic biomarkers and gaining a deeper understanding of their role in the immune microenvironment is of great significance for improving clinical prognosis.Method
This study integrated multiple datasets from GEO (GSE141512, GSE95368, GSE269269) and TCGA data, and used various bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), immune cell infiltration analysis, and single-cell RNA sequencing analysis to screen key genes related to the occurrence and development of myocardial infarction. We initially validated the results using a proteomic dataset (GSE95368) and clinical samples analyzed by qPCR. Critically, the dysregulation and diagno
SUBMITTER: Xu H
PROVIDER: S-EPMC12602245 | biostudies-literature | 2025
REPOSITORIES: biostudies-literature