Identifying Long Non-Coding RNAs Associated with Acute Myocardial Infarction Volume 2 - Issue 3

Fanyan Luo¹*, Lizhi Lv¹, Weijie Ye² and Rong Liu²

• ¹Department of Cardiothoracic Surgery, Central South University, PR China
• ²Department of Clinical Pharmacology, Central South University, PR China

Received: October 01, 2019;   Published: October 11, 2019

Corresponding author: Fanyan Luo, Department of Cardiothoracic Surgery, Xiangya Hospital, Central South University, Changsha 410008, PR China

DOI: 10.32474/ACR.2019.02.000139

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Abstract

Background: Accumulated evidence suggests that dysregulated expression of long non-coding RNAs (lnc RNAs) may participate in the development of cardiovascular diseases. In this study, we aim at identifying circulating lnc RNAs associated with acute myocardial infarction (AMI).

Materials and methods: By repurposing microarray probes from two public datasets (GSE48080, GSE66360) from gene expression omnibus database, an array-based transcriptional analysis of lnc RNAs in AMI patients and controls were conducted by us. Data analyses with R and Bioconductor.

Results: Six lnc RNAs (MIR22HG, RP11-296O14.3, IDI2-AS1, RP11-539L10.2, MIR3945HG, RP11-96D1.11) were identified to be expression differently in AMI (Bonferroni p value <0.01), and a distinguish score was constructed based on the expression data of two lnc RNAs (RP11-539L10.2 and MIR22HG). This distinguish score showed predictive power in distinguishing AMI from controls in the training (AUC=0.92) and validating (AUC=0.70) datasets. Functional enrichment analyses revealed potential functional roles of MIR3945HG in immune response.

Conclusion: Taken together, our newly identified circulating lnc RNAs may have a potential role in the development of AMI.

Keywords: long non-coding RNA, myocardial infarction; data mining, biomarker, prediction model.

List of Abbreviations: Lnc RNAs: Long Non-coding RNAs; AMI: Acute Myocardial Infarction; CVD: Cardiovascular Disease; MI: Myocardial Infarction; GEO: Gene Expression Omnibus; AUC: Area Under The Curve; PCGs: Protein Coding Genes; ROC: Receiver Operating Characteristic Curve; GO: Gene Ontology

Abstract| Background| Materials and Methods| Statistical Analysis| Functional Prediction of Lnc RNAs| Results| Functional Annotation| Discussion| Study limitations| Conclusion| References|