Identification and verification of circRNA biomarkers for coronary artery disease based on WGCNA and the LASSO algorithm

Abstract

Background: The role of circular RNAs (circRNAs) as biomarkers of coronary artery disease (CAD) remains poorly explored. This study aimed to identify and validate potential circulating circRNAs as biomarkers for the diagnosis of CAD.

Methods: The expression profile of circRNAs associated with CAD was obtained from Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operation (LASSO) were employed to identify CAD-related hub circRNAs. The expression levels of these hub circRNAs were validated using qRT-PCR in blood samples from 100 CAD patients and 100 controls. The diagnostic performance of these circRNAs was evaluated through logistic regression analysis, receiver operator characteristic (ROC) analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Functional enrichment analyses were performed to predict the possible mechanisms of circRNAs in CAD.

Results: A total of ten CAD-related hub circRNAs were identified through WGCNA and LASSO analysis. Among them, hsa_circ_0069972 and hsa_circ_0021509 were highly expressed in blood samples of CAD patients, and they were identified as independent predictors after adjustment for relevant confounders. The area under the ROC curve for hsa_circ_0069972 and hsa_circ_0021509 was 0.760 and 0.717, respectively. The classification of patients was improved with the incorporation of circRNAs into the clinical model composed of conventional cardiovascular risk factors, showing an IDI of 0.131 and NRI of 0.170 for hsa_circ_0069972, and an IDI of 0.111 and NRI of 0.150 for hsa_circ_0021509. Functional enrichment analyses revealed that the hsa_circ_0069972-miRNA-mRNA network was enriched in TGF-β、FoxO and Hippo signaling pathways, while the hsa_circ_0021509-miRNA-mRNA network was enriched in PI3K/Akt and MAPK signaling pathways.

Conclusion: Hsa_circ_0069972 and hsa_circ_0021509 were identified by integrated analysis, and they are highly expressed in CAD patients. They may serve as novel biomarkers for CAD.

Keywords: Biomarker; Circular RNA; Coronary artery disease; LASSO; WGCNA.

Fig. 1

The WGCNA analysis of GSE115733. (A) Scale-free networks of scale independence and mean connectivity. (B) The cluster dendrogram of WGCNA. (C) A heatmap showing the correlation between each module eigengene and phenotype. (D) Scatter plots of gene significance (GS) vs. module membership (MM) in the red and blue modules. WGCNA, weighted gene co-expression network analysis; CAD, coronary artery disease

Fig. 2

Identification of CAD related hub circRNAs. (A) Volcano showed expression of DEcircRNAs between the CADs and controls. (B) The veen plot showed the interaction between DEcircRNAs and circRNAs in red and blue modules. (C) LASSO coefficient profiles of the 10 circRNAs in CAD. (D) The log (lambda) sequence was used to construct a coefficient profile diagram. WGCNA, weighted gene co-expression network analysis; DEcircRNA, differentially expressed circRNA

Fig. 3

Circulating expression levels of five circular RNAs of CAD patients and controls. Quantitative real time polymerase chain reaction analysis of the circulating expression levels of (A) hsa_circ_0069972, (B) hsa_circ_0021509, (C) hsa_circ_0081915, (D) hsa_circ_0031891, and (E) hsa_circ_0005691 in the controls (n = 100) and CAD patients (n = 100). Data represent the median ± interquartile range, Mann-Whitney U test. CAD, coronary artery disease; ***, P < 0.001; ns, no significance

Fig. 4

The ROC curve and AUC of circRNAs expression. ROC, receiver operating characteristic; AUC, area under the curve; CI: confidence interval

Fig. 5

The circRNA-miRNA-mRNA regulatory network and functional enrichment analysis. (A) The hsa_circ_0069972-miRNA-mRNA regulatory network. The red triangle, yellow rhomboids and blue circles represent circRNAs, miRNAs and mRNAs, respectively. (B) The hsa_circ_0021509-miRNA-mRNA regulatory network. (C) Functional enrichment analysis of hsa_circ_0069972-miRNA-mRNA regulatory network. (D) Functional enrichment analysis of hsa_circ_0021509-miRNA-mRNA regulatory network. The P-value of terms was transformed to -log10(P-value)