Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: Integrated analysis of bulk RNA-seq, expression quantitative trait loci, and Mendelian randomization

Guoqing Liu¹Xiangwen Lv²Jiahui Qin¹Xingqing Long³Miaomiao Zhu³Chuwen Fu¹Jian Xie^1*Peichun He^4*

• ¹Department of Cardiology, First Affiliated Hospital, Guangxi Medical University, Nanning, Guangxi Zhuang Region, China
• ²Department of Rehabilitation, Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Region, China
• ³The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China., Nanning, China
• ⁴Guangxi Medical University, Nanning, China

Background: Immune infiltration is closely related to the progression of acute myocardial infarction (AMI), among which neutrophils have received extensive attention. However, the concrete association between AMI and neutrophils remains uncertain. Methods: Bulk RNA-seq data for patients with AMI were downloaded from the Gene Expression Omnibus (GEO) database. CIBERSORT was utilized to measure 22 degrees of immune cell composition. The causal link between neutrophils and AMI was determined by Mendelian randomization (MR) analysis. Genes with correlation coefficients > 0.7 with neutrophils were selected, and their representativeness was confirmed by functional enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was performed to screen for AMI-related modular genes. Robust molecular clusters linked to neutrophils were recognized via consensus clustering methodology. Hub genes were screened using the least absolute shrinkage and selection operator (LASSO) and random forest (RF) algorithms. A cellular model of AMI was established using oxygen- and glucose-deprived AC16 cells. Quantitative reverse transcription‒polymerase chain reaction (RT‒qPCR) was used to validate the gene expression levels. The expression quantitative trait loci (eQTL) analysis is used to identify genetic variations in the expression of regulatory genes in AMI. Results: MR results demonstrated a significant causal relationship between neutrophils and AMI. The consensus clustering method delineated two gene subclusters, and the expression of AMI-related neutrophil coexpressed genes was consistent with innate immune cell infiltration. Three hub neutrophil coexpressed genes (BCL6, CDA, and IL1R2) were identified. The receiver operating characteristic (ROC) curves indicated that the three genes were valuable for diagnosing AMI in the training and validation sets, and the RT‒qPCR results verified the gene expression data. A prediction model was constructed based on three hub neutrophil coexpressed genes in AMI, and the results revealed good accuracy. The eQTL analysis further confirmed that BCL6 plays a pivotal role as a key risk gene in neutrophil-mediated damage in AMI. Conclusion: There is a causal relationship between neutrophils and AMI. BCL6 plays a pivotal role as a key risk gene in neutrophil-mediated damage in AMI. However, more comprehensive studies are needed to determine the molecular mechanism of AMI-related neutrophil coexpressed genes.