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Title: Protemic discovery and validation of diagnostic plasma biomarkers for pulmonary tuberculosis
Author: Garay Baquero, Diana Jazmín
ISNI:       0000 0004 8501 8989
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2018
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Despite more than a century fighting against tuberculosis, the World Health Organisation has estimated that around 1.7 million people died of tuberculosis in 2016 and over a quarter of the world's population is infected (1). One of the critical hurdles for stopping tuberculosis transmission is early and effective diagnosis of patients with the active pulmonary disease. Although important innovations in molecular diagnosis have been recently developed (e.g. Xpert MTB/RIF, Cepheid Inc., USA), there are no suitable tests for population screening at point-of-care (2, 3). The current tuberculosis diagnosis pipeline presents a highly variable performance and requires access to reference laboratory facilities (3). A non-sputum based rapid test with high specificity and sensitivity could save ~400,000 lives per year (4). Therefore, new biomarkers for diagnosis are urgently required for identifying patients with early symptoms and to expedite treatment. Variable sensitivity and specificity can be overcome using a combination of multiple biomarkers (5). Proteins, as ultimate biological effectors, are ideal candidates for diagnostic biomarkers; consequently, proteomic studies are a crucial platform for biomarker discovery in tuberculosis. This work aims to develop a multi-marker panel for tuberculosis diagnosis with high performance capable of differentiating tuberculosis patients from relevant controls. Quantitative Multidimensional Protein Identification Technology (qMudPIT) is applied for biomarker discovery identifying candidates for early diagnosis of tuberculosis. The multidimensional method optimised in this work led to the identification of 5022 plasma proteins and 3577 quantified proteins using iTRAQ labelling. Known and completely novel markers for active tuberculosis in plasma were identified including a peptide derived from Mycobacterium tuberculosis. Complementary statistical and bioinformatic analysis were applied to prioritise candidates for validation in one or two independent cohorts. The plasma proteomic profile here described represents a power strategy for biomarker discovery and the panel proposed has the potential to be translated to a rapid test and which might contribute to tuberculosis control.
Supervisor: Elkington, Paul ; Garbis, Spiros ; Woelk, Christopher H. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral