FCER1GandPTGS2Serve as Potential Diagnostic Biomarkers of Acute Myocardial Infarction Based on Integrated Bioinformatics Analyses

Abstract

This study aimed to explore the potential diagnostic biomarkers and mechanisms underlying acute myocardial infarction (AMI). We downloaded four datasets (GSE19339, GSE48060, GSE66360, and GSE97320) from the Gene Expression Omnibus database and combined them as an integrated dataset. A total of 153 differentially expressed genes (DEGs) were analyzed by the linear models for microarray analysis (LIMMA) package. Weighted gene co-expression network analysis was used to screen for the significant gene modules. The intersection of DEGs and genes in the most significant module was termed ''common genes'' (CGs). CGs were mainly enriched in ''inflammatory response,'' ''neutrophil chemotaxis,'' and ''IL-17 signaling pathway'' through functional enrichment analyses. Subsequently, 15 genes were identified as the hub genes in the proteinprotein interaction network. The Fc fragment of IgE receptor Ig (FCER1G) and prostaglandin-endoperoxide synthase 2 (PTGS2) showed significantly increased expression in AMI patients and mice at the 12-h time point in our experiments. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of FCER1G and PTGS2. The area under ROC curve of FCER1G and PTGS2 was 77.6% and 80.7%, respectively. Moreover, the micro (mi)RNA-messenger (m)RNA network was also visualized; the results showed that miRNA-143, miRNA-144, and miRNA-26 could target PTGS2 in AMI progression.

Construction and Bioinformatics Analysis of circRNA-miRNA-mRNA Network in Acute Myocardial Infarction

“…PTGS2, prostaglandin-endoperoxide synthase 2, also known as COX2, is an enzyme involved in prostaglandin synthesis, which is associated with cardiovascular disease risk. Its expression was increased in MI ( Ge et al, 2019 ; Xiao et al, 2021 ). It was reported that PTGS2 genetic variant, may be important risk factors for the development of cardiovascular disease events ( Lee et al, 2008 ).…”

“…Studies have shown that miRNA-26b alleviates the inflammatory response and remodeling of the heart in MI by targeting PTGS2 ( Ge et al, 2019 ). Recently, PTGS2 was reported that can serve as potential diagnostic biomarkers of AMI ( Xiao et al, 2021 ). So, PTGS2 was an important gene in MI.…”

Identification and Interaction Analysis of Molecular Markers in Myocardial Infarction by Integrated Bioinformatics Analysis

“…PLA2G2A [61], CCL23 [62], CD53 [63], TREML4 [64], TREM2 [65], CD180 [66], HPSE (heparanase) [67], CELA2A [68], TNFRSF4 [69], AMBP (alpha-1-microglobulin/bikunin precursor) [70], SOX18 [71], PANX2 [72], RSPO2 [73], COMP (cartilage oligomeric matrix protein) [74], ASGR1 [75] and NOXA1 [76] are involved in progression of atherosclerosis. A previous study reported that S100A9 [77], ADORA3 [78], IL1R2 [79], FPR1 [80], CCL20 [81], CD163 [82], S100A8 [83], TLR2 [84], HAS2 [85], PTX3 [86], TIMP4 [87], AREG (amphiregulin) [88], LBP (lipopolysaccharide binding protein) [89], IL18R1 [90], ALOX5AP [91], RETN (resistin) [92], F13A1 [93], FPR2 [94], SAA1 [95], FLT3 [96], AQP4 [97], FCER1G [98], CCL18 [99], HP (haptoglobin) [100], CDK1 [101], SLC7A11 [102], CFTR (CF transmembrane conductance regulator) [103], F8 [104], STC1[44], IL18RAP [90], TIMP3 [105], PDE4D [106], CYP4A11 [107], SCN10A [108], APOB (apolipoprotein B) [109], ACE (angiotensin I converting enzyme) [110], PENK (proenkephalin) [111], HSPB6 [112], TLR9 [113], EGR1 [114], CACNG8 [115], FOXD3 [116], DBH (dopamine beta-hydroxylase) [117], FOXP3 [118], GLP1R [119], IL34 [120], CCN1 [121], ADRA2A [122], BGN (biglycan) [123], NOS2 [124], AGRN (agrin) [125], DRD1 [126], GNB3 [127], EGR2 [128], MDK (midkine) [129], NOTCH3 [130], AZIN2 [131], NOTCH1 [132], LOX...…”

“…7, CFTR, CDK1, RPS13, RPS15A, RPS27, NOTCH1, MRPL12, NOS2, CCDC85B and ATN1 achieved an AUC value of >0.88, demonstrating NOXA1 [76] are involved in progression of atherosclerosis. A previous study reported that S100A9 [77], ADORA3 [78], IL1R2 [79], FPR1 [80], CCL20 [ [96], AQP4 [97], FCER1G [98], CCL18 [99], HP (haptoglobin) [100], CDK1 [101], SLC7A11 [102], CFTR (CF transmembrane conductance regulator) [103], F8 [104], STC1 [44], IL18RAP [90], TIMP3 [105], PDE4D [106], CYP4A11 [107], SCN10A [108], APOB (apolipoprotein B) [109], ACE (angiotensin I converting enzyme) [110], PENK (proenkephalin) [111], HSPB6 [112], TLR9 [113], EGR1 [114], CACNG8 [115], FOXD3 [116], DBH (dopamine beta-hydroxylase) [117], FOXP3 [118] [189], MAOA (monoamine oxidase A) [190], BMPR1B (bone morphogenetic protein receptor type 1B) [191], FGF7 [192], CALCRL (calcitonin receptor like receptor) [193], MARK3 [194], ADH1B [195], AMH (anti-Mullerian hormone) [196], RET (ret proto-oncogene) [197], IGF2 [198], SLC6A9 [199], NPPA (natriuretic peptide A) [200], SCT (secretin) [201], DCX (doublecortin) [202...…”

Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction

“…It can describe the pattern of gene association and explore the interactions between gene expression profiles and potential functional relationships. It is increasingly used to identify hub genes associated with cardiovascular diseases ( 14 , 15 ).…”