A systematic review and meta-analysis of circulating serum and plasma microRNAs in TB diagnosis

Tuberculosis (TB) ranks as the second leading cause of death globally among all infectious diseases. This problem is likely due to the lack of biomarkers to differentiate the heterogeneous spectrum of infection. Therefore, the first step in solving this problem is to identify biomarkers to distinguish the different disease states of an individual and treat them accordingly. Circulating microRNA (miRNA) biomarkers are promising candidates for various diseases. In fact, we are yet to conceptualize how miRNA expression influences and predicts TB disease outcomes. Thus, this systematic review and meta-analysis aimed to assess the diagnostic efficacy of circulating miRNAs in Latent TB (LTB) and Active Pulmonary TB (PTB).

Literature published between 2012 and 2021 was retrieved from PubMed, Web of Science, Cochrane, Scopus, Embase, and Google Scholar. Articles were screened based on inclusion and exclusion criteria, and their quality was assessed using the QUADAS-2 tool. Funnel plots and forest plots were generated to assess the likelihood of study bias and heterogeneity, respectively.

After the screening process, seven articles were selected for qualitative analysis. The study groups, which consisted of Healthy Control (HC) vs. TB and LTB vs. TB, exhibited an overall sensitivity of 81.9% (95% CI: 74.2, 87.7) and specificity of 68.3% (95% CI: 57.8, 77.2), respectively. However, our meta-analysis results highlighted two potentially valuable miRNA candidates, miR-197 and miR-144, for discriminating TB from HC. The miRNA signature model (miR197-3p, miR-let-7e-5p, and miR-223-3p) has also been shown to diagnose DR-TB with a sensitivity of 100%, but with a compromised specificity of only 75%.

miRNA biomarkers show a promising future for TB diagnostics. Further multicentre studies without biases are required to identify clinically valid biomarkers for different states of the TB disease spectrum.

PROSPERO (CRD42022302729).