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

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.

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Publication Details

Journal
International Journal of Applied Mathematics Sciences and Technology for National Defense
Published
2024-12-30
DOI
https://doi.org/10.58524/app.sci.def..v2i3.362
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

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

Tiara Rahayu, Indah Kusuma Wardani, Atmadi Atmadi, Reihana Marsha Cahyani Elsadi et al.
International Journal of Applied Mathematics Sciences and Technology for National Defense
Tuberculosis Research and Epidemiology
article

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

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

Abstract

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.

International Journal of Applied Mathematics Sciences and Technology for National DefenseVol. 2(3)
United States Department of the Army (US), United States Army (US), Indonesia Defense University (ID)
Good health and well-being
Openalex Percentile: Top 69%
Tuberculosis Research and Epidemiology
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