AUTHOR=Wu Yanze , Jiang Ting , Hua Jinghai , Xiong Zhiping , Chen Hui , Li Lei , Peng Jingtian , Xiong Wenjun 

TITLE=Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2022.831605

DOI=10.3389/fcvm.2022.831605

ISSN=2297-055X

ABSTRACT=Background: Acute myocardial infarction (AMI) is a fatal disease that results in high morbidity and mortality. It has been reported that AMI is associated with immune cell infiltration. Herein, we aimed to identify the potential diagnostic biomarkers for AMI and uncover the immune cell infiltration profile of AMI.
Methods: From the Gene Expression Omnibus (GEO) dataset, three datasets (GSE48060, GSE60993, GSE66360) were downloaded. Differentially expressed genes (DEGs) were screened from AMI and healthy control samples. Furthermore, DEGs were performed via Gene ontology (GO) functional and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analyses. Gene Set Enrichment Analysis (GSEA) was used to analyze GO terms and KEGG pathways. Utilizing the Search Tool for Retrieval of Interacting Genes/Proteins (STRING) database, a protein-protein interaction (PPI) network was constructed, and we identified the hub genes. Then, the receiver operating characteristic (ROC) curves were constructed to analyze the diagnostic value of hub genes. Finally, CIBERSORT was used to represent the compositional patterns of the 22 types of immune cell fraction in AMI. 
Results: Seventy-one DEGs were identified. These DEGs were mainly enriched in immune response and immune-related pathways. TLR2, IL1B, LILRB2, FCER1G, FPR1 and MMP9 were identified as diagnostic markers with p-value < 0.05. Also, immune cell infiltration analysis indicated that TLR2, IL1B, LILRB2, FCER1G, FPR1 and MMP9 were correlated with neutrophils, monocytes, resting NK cells, gamma delta T cells and CD4 memory resting T cells. The fractions of monocytes and neutrophils were significantly higher in AMI tissues than in control tissues.
Conclusion: LR2, IL1B, LILRB2, FCER1G, FPR1 and MMP9 are involved in the process of AMI, which can be used as molecular biomarkers for AMI screen and diagnosis. Besides, the immune system plays a vital role in the occurrence and progression of AMI.