Insights into latent tuberculosis biomarkers from differential gene expression analysis in CD8 memory cells using secondary data Insilico approach

Atmadi, Atmadi
Rahayu, Tiara
Wardani, Indah Kusuma
Elsadi, Reihana Marsha Cahyani
Milasari, Azizah Eka
Witadi, M. Ridwan Amarullah

International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Vol 2, No 3 (2024): International Journal of Applied Mathematics, Sciences, and Technology for Natio

Tuberculosis (TB) remains a global health challenge, significantly impacting infectious disease mortality and morbidity. In the quest for effective diagnostic tools and precise treatment strategies, differential gene expression (DEG)-based biomarkers offer a promising avenue. These biomarkers provide specific insights into disease states and treatment responses by deciphering gene alterations within body cells. In this study, we aimed to identify immunological signatures associated with latent Mycobacterium tuberculosis infection in memory T cells. Leveraging transcriptomic analysis, we examined memory CD8 T cells from individuals with latent TB (NCBI-GEO GSM2643205) and healthy controls (NCBI-GEO GSM2643198). Our findings highlight candidate biomarker genes—LDB1, ZNF121, and STAT6—whose differential expression could significantly enhance our understanding of CD8 T cell genetic regulation during latent TB infection. These results hold promise for the development of more accurate biomarkers for diagnosing latent tuberculosis.