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

Authors

  • Atmadi Indonesia Defense University
  • Tiara Rahayu The Indonesian Army
  • Indah Kusuma Wardani The Indonesian Army
  • Reihana Marsha Cahyani Elsadi Indonesia Defense University
  • Azizah Eka Milasari The Indonesian Army
  • M. Ridwan Amarullah Witadi The Indonesian Army

DOI:

https://doi.org/10.58524/app.sci.def..v2i3.362

Keywords:

Biomarkers, CD8 T cells, latent tuberculosis, RNA sequencing, TB diagnostics

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.

References

An, Y., Teo, A. K. J., Huot, C. Y., Tieng, S., Khun, K. E., Pheng, S. H., Leng, C., Deng, S., Song, N., Nop, S., Nonaka, D., & Yi, S. (2022). Knowledge, attitude, and practices regarding childhood tuberculosis detection and management among health care providers in Cambodia: a cross-sectional study. BMC Infectious Diseases, 22(1), 317. https://doi.org/10.1186/s12879-022-07245-1

Arthamin, Z, Didiet, T, & Fransisca. (2015) Immunogenicity test of the 38 kDa mycobacterium tuberculosis Malang strain recombinant fusion protein on the expression of IL-2 and IL-4 on CD3+ T lymphocytes in PBMC culture. Indonesian Journal of Clinical Pathology and Medical, 21(3), 244-9. https://doi.org/10.24293/ijcpml.v21i3.1275

Blischak, J. D., Tailleux, L., Myrthil, M., Charlois, C., Bergot, E., Dinh, A., & Gilad, Y. (2017). Predicting susceptibility to tuberculosis based on gene expression profiling in dendritic cells. Scientific Reports, 7(1), 5702. https://doi.org/10.1038/s41598-017-05878-w

Cho, Y., Park, Y., Sim, B., Kim, J., Lee, H., Cho, S. N., Kang, Y. A., & Lee, S. G. (2020). Identification of serum biomarkers for active pulmonary tuberculosis using a targeted metabolomics approach. Scientific Reports, 10(3825), 1-11. https://doi.org/10.1038/s41598-020-60669-0

Dewi, N. P. (2020). Pengaruh pelatihan transcendental meditation terhadap jumlah sel limfosit t (CD4+% DAN CD8+%) pada siswa kelas X angkatan 2019 SMA Bali Mandara, Singaraja. https://api.semanticscholar.org/CorpusID:229396979

Ewald, J., Zhou, G., Lu, Y., & Xia, J. (2023). Using expressanalyst for comprehensive gene expression analysis in model and non‐model organisms. Current Protocols, 3(11), e922. https://doi.org/10.1002/cpz1.922

Infante, J. R., Peran, F., Rayo, J. I., Serrano, J., Dominguez, M. L., Garcia, L., Duran, C., & Roldan, A. (2014). Levels of immune cells in transcendental meditation practitioners. International Journal of Yoga, 7(2), 147-151. https://doi.org/10.4103/0973-6131.133899

Laycock, K. M., Enane, L. A., & Steenhoff, A. P. (2021). Tuberculosis in adolescents and young adults: emerging data on tb transmission and prevention among vulnerable young people. Tropical Medicine and Infectious Disease, 6(3), 148. https://doi.org/10.3390/tropicalmed6030148

Liu, P., Ewald, J., Pang, Z., Legrand, E., Jeon, Y. S., Sangiovanni, J., Hacariz, O., Zhou, G., Head, J. A., Basu, N., & Xia, J. (2023) ExpressAnalyst: A unified platform for RNA-sequencing analysis in non-model species. Nature Communication. 14, 2995 (2023). https://doi.org/10.1038/s41467-023-38785-y

McNerney, R., Maeurer, M., Abubakar, I., Marais, B., Mchugh, T. D., Ford, N., Weyer, K., Lawn, S., Grobusch, M. P., Memish, Z., Squire, S. B., Pantaleo, G., Chakaya, J., Casenghi, M., Migliori, G., Mwaba, P., Zijenah, L., Hoelscher, M., Cox, H., Swaminathan, S., Kim, P. S., Schito, M., Harari, A., Bates, M., Schwank, S., O’Grady, J., Pletschette, M., Ditui, L., Atun, R., & Zumla, A. (2012). Tuberculosis diagnostics and biomarkers: needs, challenges, recent advances, and opportunities. The Journal of Infectious Diseases, 2012(205), S147-58. https://doi.org/10.1093/infdis/jir860

Nabilah, R., Sangging, P. R. A., & Wulan, A. J. (2023). Relationship between the incidence of extra pulmonary tuberculosis with lymphocyte and monocyte levels in RSUD Dr. H. Abdul Moeloek. Medical Profession Journal of Lampung, 13(5), 768-777. https://doi.org/10.53089/medula.v13i5.745

National TB Program. National strategy of tuberculosis care and prevention in Indonesia 2020-2024. Retrieved from https://www.usaid.gov/sites/default/files/2022-12/Indonesia_Narrative_TBRM22_Version_Final.pdf

Nogueira, B. M., Krishnan, S., Barreto‐Duarte, B., Araújo‐Pereira, M., Queiroz, A. T., Ellner, J. J., & Andrade, B.B. (2022). Diagnostic biomarkers for active tuberculosis: progress and challenges. EMBO Molecular Medicine, 14(12), e14088. https://doi.org/10.15252/emmm.202114088

Park, S. T. & Kim, J. (2016). Trends in Next-Generation Sequencing and a New Era for Whole Genome Sequencing. International Neuroulogy Journal, 20(2), S76-83. https://doi.org/10.5213/inj.1632742.371

Satam, H., Joshi, K., Mangrolia, U., Waghoo, S., Zaidi, G., Rawool, S., Thakare, R. P., Banday, S., Mishra, A. K., Das, G., et al. Next Generation Sequencing Technologies: Current Trends and Advances. Biology. 2023; 12(7):997. https://doi.org/10.3390/biology12070997 .

Setyawan, H. H. (2015). Interferon gamma for multidrug-resistant tuberculosis (mdr-tb) patients at dr regional general hospital. Moewardi in Surakarta. Nexus Biomedika, 4(3).

Syafaah, N. I. (2016). Relationship Between Sputum Ifn-Γ Levels and Degree of Smoking in Bta Positive Pulmonary TB Patients (Thesis). Universitas Airlangga.

Wibowo, R. Y., Tambunan, B. A., Nugraha, J., Srioetami, F., & Tanoerahardjo. (2017). Expression of interferon gammafrom CD4+ and CD8+ T-cells after ESAT-6-CFP-10 fusion antigen stimulation on active pulmonary tuberculosis patients. Buletin Penelitian Kesehatan, 45(4), 223-226. http://dx.doi.org/10.22435/bpk.v45i4.6874.223-226

World Health Organization. Global tuberculosis report 2021 [Internet]. 2021. Available from https://www.who.int/publications/digital/globaltuberculosis-report-2021/tb-disease-burden/incidence

Wykowski, J. H., Phillips, C., Ngo, T., & Drain, P. K. (2021). A systematic review of potential screening biomarkers for active TB disease. Journal of Clinical Tuberculosis and Other Mycobacterial Diseases, 25(2021), 100284. https://doi.org/10.1016/j.jctube.2021.100284

Downloads

Published

2024-12-30

How to Cite

Atmadi, Rahayu, T., Wardani, I. K., Elsadi, R. M. C., Milasari, A. E., & Witadi, M. R. A. (2024). Insights into latent tuberculosis biomarkers from differential gene expression analysis in CD8 memory cells using secondary data Insilico approach. International Journal of Applied Mathematics, Sciences, and Technology for National Defense, 2(3), 135-146. https://doi.org/10.58524/app.sci.def..v2i3.362