Diagnostic Accuracy of Circular Rna for Diabetes Mellitus: A Systematic Review and Diagnostic Meta-Analysis Publisher Pubmed



Dehghanbanadaki H¹ ; Asili P¹ ; Haji Ghadery A² ; Mirahmad M¹ ; Dehnavi AZ¹ ; Parsaei A¹ ; Baradaran HR³ ; Azami M⁴ ; Jose Justo Da Silva G⁵ ; Parvan R⁶ ; Moradi Y⁷ Show Affiliations
Source: BMC Medical Genomics Published:2023

Abstract

Background: This study aimed to investigate the pooled diagnostic ability of circular RNA (circRNA) molecules for diabetes mellitus. Methods: We searched PubMed, Scopus, and Web of Science for relevant studies. A total of 2070 participants, including 775 diabetic patients and 1295 healthy individuals, from five studies were included in this meta-analysis. True positive, true negative, false positive, and false negative data were extracted to calculate pooled sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and area under the receiver operating characteristics curve. The Deeks’ funnel plot was applied for publication bias assessment, Cochran’s Q test and I2 index were applied for inter-study heterogeneity assessment. Besides, a subgroup analysis was performed for determining the source of heterogeneity between studies. P value < 0.05 was considered significance. All analysis were done by STATA version 14. Results: CircRNA presented a sensitivity of 76% (95% confidence interval [95%CI]: 66-84%), specificity of 77% (95%CI: 58-89%), positive LR of 3.25 (95%CI: 1.69–6.23), negative LR of 0.31 (95%CI: 0.21–0.46), DOR of 10.41 (95%CI: 4.26–25.41), and AUC of 0.82 (95%CI: 0.79–0.85) for diabetes mellitus detection. More specifically, hsa_circ_0054633 showed a sensitivity of 67% (95%CI: 53-81%) and a specificity of 82% (95%CI: 63-100%). Conclusion: CircRNAs show highly accurate diagnostic capability for type 2 diabetes mellitus and gestational diabetes mellitus. High sensitivity of circRNAs introduces them as potential noninvasive biomarkers for early diagnosis of diabetes mellitus and their high specificity introduces them as potential therapeutic targets by regulation of their expression. © 2023, The Author(s).