Expression pattern and diagnostic value of ferroptosis-related genes in acute myocardial infarction
0301 basic medicine
bioinformatics analysis
03 medical and health sciences
RC666-701
acute myocardial infarction
biomarker
Diseases of the circulatory (Cardiovascular) system
Cardiovascular Medicine
ROC analysis
ferroptosis
3. Good health
DOI:
10.3389/fcvm.2022.993592
Publication Date:
2022-11-03T05:59:55Z
AUTHORS (10)
ABSTRACT
Background Ferroptosis is a form of regulatory cell death (RCD) caused by iron-dependent lipid peroxidation. The role ferroptosis in the process acute myocardial infarction (AMI) still unclear and requires further study. Therefore, it helpful to identify related genes (FRGs) involved AMI explore their expression patterns molecular mechanisms. Methods AMI-related microarray datasets GSE66360 GSE61144 were obtained using Gene Expression Omnibus (GEO) online database. GO annotation, KEGG pathway enrichment analysis Protein-protein interaction (PPI) performed for common significant differential (CoDEGs) these two datasets. FRGs from FerrDb V2 differentially expressed used potential biomarkers receiver operating characteristic (ROC) analysis. was verified external dataset GSE60993 GSE775. Finally, hypoxia model. Results A total 131 CoDEGs identified mainly enriched pathways “inflammatory response,” “immune “plasma membrane,” “receptor activity,” “protein homodimerization “calcium ion binding,” “Phagosome,” “Cytokine-cytokine receptor interaction,” “Toll-like signaling pathway.” top 7 hub ITGAM, S100A12, S100A9, TLR2, TLR4, TLR8, TREM1 PPI network. 45 14 GSE61144, respectively. ACSL1, ATG7, CAMKK2, GABARAPL1, KDM6B, LAMP2, PANX2, PGD, PTEN, SAT1, STAT3, ZFP36 significantly with AUC ≥ 0.7. ALOX5, PTGS2, ULK1 as based on time-gradient transcriptome mice cellular Conclusion In this study, existing datasets, we blood samples patients validated mouse This study explored pattern mechanism AMI, providing basis accurate diagnosis selection new therapeutic targets.
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