Diagnostic value of circRNAs as effective biomarkers in human cardiovascular disease: an updated meta-analysis

• Published in: International journal of medical sciences Vol. 19; no. 3; pp. 446 - 459
• Main Authors: Zhang, Zhexiao, Guo, Runmin, Wang, Yuhui, Huang, Hairong, Liu, Jie, Wang, Chenfei, Wu, Hongfu, Zou, Tangbin
• Format: Journal Article
• Language: English
• Published: Australia Ivyspring International Publisher Pty Ltd 01.01.2022; Ivyspring International Publisher
• Subjects: Biomarkers; Biomarkers, Tumor; Cardiovascular disease; Cardiovascular Diseases - diagnosis; Cardiovascular Diseases - genetics; Heart attacks; Humans; Meta-analysis; Mortality; Odds Ratio; Review; RNA, Circular - genetics; Sensitivity and Specificity; meta-analysis; cardiovascular disease; circRNAs; diagnosis; biomarker
• ISSN: 1449-1907; 1449-1907
• DOI: 10.7150/ijms.67094

A growing body of literature has demonstrated that circular RNAs (circRNAs) are the potential biomarkers in human cardiovascular disease (CVD). Therefore, a meta-analysis based on current studies was accomplished to appraise the role of circRNAs in the diagnostic of CVD patients. Studies before October 30, 2021, were searched using PubMed, EMBASE, the Web of Science, and Cochrane Library. The diagnostic odds ratio (DOR) with a confidence interval (CI) of 95% was used to investigate the associations between circRNAs and CVDs. A total of 27 eligible articles were selected, including 47 studies, with 6833 participants meeting the criteria standard constrain. The pooled overall sensitivity and specificity for circRNAs expression profile in differentiating CVD patients from controls (non-CVDs or healthy subjects) were 0.81 (95%CI 0.78-0.83) and 0.74 (95%CI 0.68-0.78), respectively; the overall positive likelihood ratio was 3.1 (95%CI 2.5-3.7); the negative likelihood ratio was 0.26 (95%CI 0.22-0.31); the overall diagnostic odds ratio corresponding to an area under the curve of 0.85 (95%CI 0.81-0.88) was 12 (95%CI 9-16). Subgroup analysis indicated that the serum rather than blood has higher diagnostic accuracy. Likewise, meta-regression analysis demonstrated that the specimen, detection method, sample size, and publication year were the main sources of heterogeneity. Sensitivity analysis and Deeks' funnel plot revealed that our results are relatively robust. Our evidence-based analysis results suggested that circRNAs provide higher diagnostic accuracy in the prediction of CVDs. Thus, circRNAs might be potential biomarkers in CVDs.