Machine learning identifies MiRNA biomarkers and immune mechanisms in active tuberculosis.

ABSTRACT: Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a major global public health threat. The rising prevalence of HIV/TB co-infection and multidrug-resistant tuberculosis (MDR-TB) has further intensified this challenge. This study aims to explore the role of microRNAs (miRNAs) in the immune response to Mtb infection and to identify potential miRNA biomarkers for active TB diagnosis using machine learning techniques. miRNA expression profiles were retrieved from the Gene Expression Omnibus (GEO) database (accession number: GSE70425). Differential expression analysis between active TB and latent TB infection (LTBI) patients was conducted using the "limma" package, with a screening threshold of |logFC| > 0.25 and p-value < 0.05. Key differentially expressed miRNAs (DE-miRNA

SUBMITTER: Cai Z 

PROVIDER: S-EPMC12533189 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature