ABHD4-Regulating RNA Panel: Novel Biomarkers in Acute Coronary Syndrome Diagnosis

Abstract

Background: Acute coronary syndrome (ACS) is a major cause of death all over the world. STEMI represents a type of myocardial infarction with acute ST elevation. We aimed to assess the predictive power of potential RNA panel expression in acute coronary syndrome.

Method: We used in silico data analysis to retrieve RNAs related to glycerophospholipid metabolism dysregulation and specific to ACS that results in the selection of Alpha/Beta hydrolase fold domain4 (ABHD4) mRNA and its epigenetic regulators (Foxf1 adjacent noncoding developmental regulatory RNA (FENDRR) lncRNA, miRNA-221, and miRNA-197). We assessed the expression of the serum RNA panel in 68 patients with ACS, 21 patients with chest pain due to non-cardiac causes, and 21 healthy volunteers by quantitative real-time polymerase chain reaction.

Results: The study data showed significant down regulation in the expression of the serum levels of FENDRR lncRNA and miRNA-221-3p by 120-fold and 22-fold in Unstable angina (UA) in comparison with healthy volunteers, and by 8.6-fold and 2-fold in ST segment elevation myocardial infarction (STEMI) patients versus UA; concomitant upregulation in the expression of ABHD4 mRNA and miRNA-197-5p by 444-fold and 10-fold in UA compared with healthy volunteers, and by 1.54-fold and 4.5-fold in STEMI versus unstable angina. Performance characteristics analysis showed that the ABHD4-regulating RNA panel were potential biomarkers for prediction of ACS. Moreover, there was a significant association between the 2 miRNAs and ABHD4 mRNA and the regulating FENDRR lncRNA.

Conclusion: Collectively, ABHD4 mRNA regulating RNA panel based on putative interactions seems to be novel non-invasive biomarkers that could detect ACS early and stratify severity of the condition that could improve health outcome.

Keywords: RNA; acute coronary syndrome; bioinformatics; diagnosis; glycerophospholipid; serum; troponin.

Figure 1

Differential analysis of the results in BOXPLOT represents serum RNA panel expression based on fold change in gene expression at logarithmic scale as measured by qRT-PCR among the groups of the study. (A) ABHD4 mRNA, (B) MiRNA-197-5p, (C) miRNA-221-3p, and (D) FENDRR lncRNA. The median is represented by line inside the box while the 1st and 3rd quartiles are represented by the top and bottom lines of the box, respectively, and the 5th and 95th percentiles are at the top and bottom whiskers, respectively. *, ° different markers for “out” values (small circle) and “far out” or as SPSS calls them “Extreme values” (marked with a star). SPSS uses a step of 1.5 × IQR (Interquartile range).

Figure 2

Receiver operator characteristics (ROC) curve presents the diagnostic accuracy of the ABHD4 RNA panel discriminating between ACS and control. (A) ABHD4 mRNA, (B) MiRNA-197-5p, (C) miRNA-221-3p, and (D) FENDRR lncRNA, (E) CK-MB, and (F) cardiac troponin.

Figure 3

Bar chart shows the positivity rate of the studied parameter: (A) between ACS patients and control (non-cardiac and healthy controls), and (B) the diagnostic value of the studied parameters in discriminating UA from STEMI and NSTEMI.

Figure 4

Receiver operator characteristics (ROC) curve presents the diagnostic accuracy of the ABHD4 RNA panel discriminating between UA and STEMI: (A) ABHD4 mRNA and miRNA-197-5p a (B) FENDRR lncRNA.

Figure 5

Summary of the molecular signaling of ABHD4-regulating RNA panel in ACS based on putative interactions: (A) ABHD4 interacting with both hsa-miRNA-221 and hsa-miRNA-197 as retrieved from miRWalk database, (B) Mechanistic signaling of ABHD4-regulating RNA panel in ACS. Based on the interaction between ABHD4 and retrieved RNAs network, we hypothesized that down-regulation of FENDRR lncRNA in ischemic heart results in the release of free miR-197 with subsequent downregulation of miR-221 accompanied with the activation of ABHD4.