INTEGRATING MICROBIOLOGY AND CLINICAL RESEARCH: MOLECULAR MECHANISMS AND BIOMARKERS IN INFECTIOUS DISEASE DIAGNOSIS

Abstract

The problem of tuberculosis, as one of the major infectious disease issues, is frequently restricted by the accessibility and sensitivity. Host-Response transcriptomic biomarkers, especially plasma cell-free RNA, have a promising non-sputum-based method of infectious disease diagnosis. This study aimed to integrate clinical metadata and transcriptomic profiles to identify molecular mechanisms and candidate biomarkers associated with tuberculosis. A retrospective computational analysis was conducted using plasma cfRNA RNA-sequencing data from a validation cohort of 60 individuals classified as TB-positive or TB-negative. Gene expression data were filtered, log-normalized, and integrated with clinical variables. Differential expression analysis, gene ontology enrichment, and supervised logistic regression modeling were applied to identify candidate biomarkers, characterize biological pathways, and evaluate diagnostic performance. TB-positive individuals exhibited upregulation of immune-related genes, including BATF2, GBP5, GBP1, IFITM3, IFIT3, MMP8, SERPING1, and STAT1. Enrichment analysis revealed significant involvement of interferon-gamma response, type I interferon signalling, cytokine-mediated pathways, and host defense processes. The classification model demonstrated moderate diagnostic performance, achieving an area under the curve of approximately 0.78. These findings indicate that plasma cfRNA profiles capture a coordinated interferon-driven host-response signature associated with tuberculosis. The results support the potential of transcriptomic biomarkers as complementary tools for non-sputum-based infectious disease diagnosis, although validation in larger and independent cohorts is necessary for clinical translation.