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Review
. 2022 Feb 7:8:782561.
doi: 10.3389/fmed.2021.782561. eCollection 2021.

MicroRNAs as Potential Biomarkers for the Diagnosis of Chronic Kidney Disease: A Systematic Review and Meta-Analysis

Jing Li  1 , Leilei Ma  1 , Hangxing Yu  1 , Yahong Yao  1 , Zhiyuan Xu  1 , Wei Lin  1 , Lin Wang  1 , Xuejun Wang  1 , Hongtao Yang  1
Affiliations
Review

MicroRNAs as Potential Biomarkers for the Diagnosis of Chronic Kidney Disease: A Systematic Review and Meta-Analysis

Jing Li et al. Front Med (Lausanne). .

Abstract

For Chronic Kidney Disease (CKD), the study of microRNA as a biomarker has become an exciting area, so we carried out a meta-analysis to investigate the potential diagnostic values of miRNAs in CKD. We searched Pubmed, Cochrane Library, Embase, and Web of science databases to identify relevant publications published from the establishment of the database to April 30, 2021. We included a total of 26 articles containing 56 studies. There were 4,098 patients with CKD and 2,450 patients without CKD. We found that the overall sensitivity and specificity of miRNAs in CKD diagnosis were 0.86 (95% CI: 0.83-0.89) and 0.79 (95% CI: 0.75-0.83), respectively. In addition, we plotted the summary receiver operator characteristic (SROC) curve to assess diagnostic accuracy, with the area under the curve (AUC) of 0.90 (95% CI: 0.87-0.92). Subgroup analysis showed that sensitivity, specificity, and AUC of miRNAs in plasma and serum were 0.84, 0.78, 0.88; and 0.79, 0.76, 0.83, respectively, while miRNAs in urine were 0.89 for sensitivity, 0.82 for specificity, and 0.92 for AUC. Moreover, we found that the panel of microRNAs (miRNAs) could improve the pooled sensitivity (0.88, 0.81, and 0.91 for sensitivity, specificity, and AUC, respectively). We believe that miRNAs have great potential to become an effective diagnostic biomarker for CKD. Panels of miRNA have higher accuracy than single miRNAs. Additionally, miRNAs in both blood and urine have significant accuracy in the diagnosis of CKD; nevertheless, urine is superior.

Keywords: CKD; biomarkers; diagnosis; meta-analysis; miRNA.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow diagram of the study selection.
Figure 2
Figure 2
QUADAS-2 assessment of risk of bias and applicability concerns.
Figure 3
Figure 3
Forest plots of sensitivity and specificity on overall miRNA used in the diagnosis of CKD.
Figure 4
Figure 4
SROC curves based on all miRNAs.
Figure 5
Figure 5
Diagram of sensitivity analysis (A) goodness-of-fit; (B) bivariate normality; (C) influence analysis; (D) outlier detection sensitivity analysis.
Figure 6
Figure 6
Sensitivity and specificity after deheterogeny.
Figure 7
Figure 7
Univariable meta-reqression and subgroup analyses for sensitivity and specificity of miRNA for diagnosis of CKD.
Figure 8
Figure 8
ROC curves based on miRNAs. (A) Single miRNA; (B) miRNAs panel; (C) miRNAs detected in urine; (D) miRNA-30.
Figure 9
Figure 9
Funnel plot of publication bias.
See this image and copyright information in PMC

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