dc.contributor.author | Namuganga, Anna Ritah | |
dc.date.accessioned | 2014-08-06T05:45:21Z | |
dc.date.available | 2014-08-06T05:45:21Z | |
dc.date.issued | 2013-02 | |
dc.identifier.citation | Namuganga, A.R. (2013). Cytokine profiles to differentiate between active and latent tuberculosis infections in patients attending the Tuberculosis Clinic at Mulago Hospital (Unpublished master's thesis). Makerere University, Kampala, Uganda | en_US |
dc.identifier.uri | http://hdl.handle.net/10570/3475 | |
dc.description | A Thesis submitted to the Graduate School in partial fulfillment of the requirements for the award of the Degree of Master of Science in Molecular Biology and Biotechnology of Makerere University | en_US |
dc.description.abstract | Quantiferon based Interferon Gamma release Assays can diagnose exposure to Mycobacterium tuberculosis (M.tb). These however do not differentiate between active and latent tuberculosis infection (LTBI). This study aimed at identifying quantiferon supernatant cytokine marker sensitivity in differentiating active tuberculosis from latent infection by analyzing 12 cytokines that have shown promising ability in detecting active TB. This involved using the luminex platform assay. MGIT positivity was used as the Gold standard for diagnosis of active tuberculosis disease while positive quantiferon indicated latent tuberculosis infection. Sixty seven subjects with clinical suspicion of pulmonary tuberculosis were recruited in Kampala, Uganda under the AETBC study and their blood was cultured in Quantiferon Gold tubes. Baseline levels of TGFα, sCD40L, MMP2, antigen stimulated levels of TGFα, sCD40L, MMP2, MMP9, IFNγ, IP-10 and corrected antigen stimulated levels of IFNγ, IP-10 and MMP9 showed potential to differentiate between active disease and latent infection as well as diagnosing disease with significant p values ranging between <0.0001 to 0.03. Combinations between sCD40L, VEGF, EGF, MMP2 and 9, IP-10 showed promising prediction accuracy in distinguishing latent and active disease states. This data suggests that active TB may be differentiated from LTBI and from healthy individuals by analyzing IFNγ, IP-10, TGFα, sCD40L, MMP2 & TNFα in Quantiferon supernatants. This has a potential of being used to develop a new diagnostic tool for tuberculosis. | en_US |
dc.description.sponsorship | African European Tuberculosis Consortium | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Tuberculosis patients | en_US |
dc.subject | Cytokine profiles | en_US |
dc.subject | Active infections | en_US |
dc.subject | Latent infections | en_US |
dc.subject | Differentiation | en_US |
dc.subject | Tuberculosis Clinic, Mulago Hospital, Uganda | en_US |
dc.title | Cytokine profiles to differentiate between active and latent tuberculosis infections in patients attending the Tuberculosis Clinic at Mulago Hospital | en_US |
dc.type | Thesis | en_US |