Systematic evaluation, verification and comparison of tuberculosis-related non-coding RNA diagnostic panels.

We systematically summarized tuberculosis (TB)-related non-coding RNA (ncRNA) diagnostic panels, validated and compared panel performance. We searched TB-related ncRNA panels in PubMed, OVID and Web of Science up to 28 February 2020, and available datasets in GEO, SRA and EBI ArrayExpress up to 1 March 2020. We rebuilt models and synthesized the results of each model in validation sets by bivariate mixed models. Specificity at 90% sensitivity, area under curve (AUC) and inconsistence index (I2 ) were calculated. NcRNA biofunctions were analysed. Nineteen models based on 18 ncRNA panels (miRNA, lncRNA, circRNA and snoRNA panels) and 18 datasets were included. Limited available datasets only allowed to evaluate miRNA panels further. Cui 2017 and Latorre 2015 exhibited specificity >70% at 90% sensitivity and AUC >80% in all validation sets. Cui 2017 showed higher specificity at 90% sensitivity (92%) and AUC (95%) and lower heterogeneity (I2  = 0%) in ethological-confirmation validation sets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis indicated that most ncRNAs in panels involved in immune cell activation, oxidative stress, and Wnt and MAPK signalling pathway. Cui 2017 outperformed other models in both all available and aetiological-confirmed validation sets, meeting the criteria of target product profile of WHO. This work provided a basis for clinical choice of TB-related ncRNA diagnostic panels to a certain extent.