Frontiers in immunology · 2026
Potential of SP1 as a prognostic marker and therapeutic target in acute myocardial infarction: a bioinformatics, Mendelian randomization and experimental validation study.
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Li Zhongyan, Cheng Huan, Li Jingru, Guan Xue, Wen Najie, Wang Luqiao
Аннотация
BACKGROUND: Acute myocardial infarction (AMI) is a global health burden. Ferroptosis drives cardiomyocyte death, but specific ferroptosis-related genes (FRGs) and pathways underlying ischemic injury remain unclear.
METHODS: First, differentially expressed mRNAs (DE-mRNAs) from GSE61144 were intersected with FRGs to obtain differentially expressed ferroptosis-related genes (DE-FRGs). Subsequently, GO/KEGG functional enrichment, PPI network construction, expression heatmap visualization and tissue-specific expression were performed on DE-FRGs to clarify their biological characteristics. To explore the potential causal relationship between DE-FRGs and AMI, we conducted summary-data-based Mendelian randomization (SMR) analysis in four cardiovascular-related tissues and performed Bayesian colocalization analysis, ultimately identifying a key transcription factor (TF). With this TF as the hub, a miRNA-TF-mRNA regulatory network was constructed. Based on this pathway, we conducted a series of analyses, including prediction of transcription factor binding sites, GSEA and GeneMANIA analysis, prediction of gene-diseases and gene-drugs associations, phenome-wide association study (PheWAS), ROC curve assessment and RT-qPCR validation, thereby systematically elucidating the molecular mechanisms of this pathway in AMI.
RESULTS: The SMR analysis showed that one key TF-SP1 were significantly associated with AMI risk among the four types of tissues [coronary artery, atrial appendage, left ventricle and whole blood (pSMR < 0.05, pHEIDI > 0.05, OR > 1)] in the GTEx database. Bayesian colocalization analysis indicated a strong colocalization relationship between SP1 and AMI (PPH4 = 0.81). Using SP1 as the key TF, a miRNA-TF-mRNA network was constructed, including 132 mRNAs and 358 miRNAs. Further narrow down to 2 miRNAs (miR-327 and miR-133b) and 7 mRNAs (EGR1, IL6, MYC, NR4A1, P4HA1, PLAUR and VEGFA) through validated by the GSE76604 and GSE4648 datasets. Bayesian colocalization analysis further confirmed that PLAUR is the key mRNA and has a strong colocalization relationship with AMI (PPH4 = 0.99). Ultimately, we successfully established the miR-133b/SP1/PLAUR-ferroptosis signaling pathway. Further analyses provided additional validation for the possibility of SP1 and miR-133b/SP1/PLAUR axis as a prognostic marker and therapeutic target in AMI.
CONCLUSIONS: In this study, by integrating transcriptomic, SMR and PheWAS analysis, we first established a robust causal association between SP1 and AMI risk across four cardiovascular tissues, and subsequently delineated a miR-133b/SP1/PLAUR ferroptosis pathway in AMI.
METHODS: First, differentially expressed mRNAs (DE-mRNAs) from GSE61144 were intersected with FRGs to obtain differentially expressed ferroptosis-related genes (DE-FRGs). Subsequently, GO/KEGG functional enrichment, PPI network construction, expression heatmap visualization and tissue-specific expression were performed on DE-FRGs to clarify their biological characteristics. To explore the potential causal relationship between DE-FRGs and AMI, we conducted summary-data-based Mendelian randomization (SMR) analysis in four cardiovascular-related tissues and performed Bayesian colocalization analysis, ultimately identifying a key transcription factor (TF). With this TF as the hub, a miRNA-TF-mRNA regulatory network was constructed. Based on this pathway, we conducted a series of analyses, including prediction of transcription factor binding sites, GSEA and GeneMANIA analysis, prediction of gene-diseases and gene-drugs associations, phenome-wide association study (PheWAS), ROC curve assessment and RT-qPCR validation, thereby systematically elucidating the molecular mechanisms of this pathway in AMI.
RESULTS: The SMR analysis showed that one key TF-SP1 were significantly associated with AMI risk among the four types of tissues [coronary artery, atrial appendage, left ventricle and whole blood (pSMR < 0.05, pHEIDI > 0.05, OR > 1)] in the GTEx database. Bayesian colocalization analysis indicated a strong colocalization relationship between SP1 and AMI (PPH4 = 0.81). Using SP1 as the key TF, a miRNA-TF-mRNA network was constructed, including 132 mRNAs and 358 miRNAs. Further narrow down to 2 miRNAs (miR-327 and miR-133b) and 7 mRNAs (EGR1, IL6, MYC, NR4A1, P4HA1, PLAUR and VEGFA) through validated by the GSE76604 and GSE4648 datasets. Bayesian colocalization analysis further confirmed that PLAUR is the key mRNA and has a strong colocalization relationship with AMI (PPH4 = 0.99). Ultimately, we successfully established the miR-133b/SP1/PLAUR-ferroptosis signaling pathway. Further analyses provided additional validation for the possibility of SP1 and miR-133b/SP1/PLAUR axis as a prognostic marker and therapeutic target in AMI.
CONCLUSIONS: In this study, by integrating transcriptomic, SMR and PheWAS analysis, we first established a robust causal association between SP1 and AMI risk across four cardiovascular tissues, and subsequently delineated a miR-133b/SP1/PLAUR ferroptosis pathway in AMI.