Open AccessSystematic evaluation, verification and comparison of tuberculosis‐related non‐coding RNA diagnostic panels
Author(s) -
Lyu Mengyuan,
Cheng Yuhui,
Zhou Jian,
Chong Weelic,
Wang Yili,
Xu Wei,
Ying Binwu
Publication year - 2021
Publication title -
journal of cellular and molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.44
H-Index - 130
eISSN - 1582-4934
pISSN - 1582-1838
DOI - 10.1111/jcmm.15903
Subject(s) - non coding rna , computational biology , biology , in silico , kegg , bivariate analysis , rna , gene , bioinformatics , gene ontology , computer science , genetics , machine learning , gene expression
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 ( I 2 ) 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 ( I 2 = 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.