Investigating biomarkers of tuberculosis and their variation by clinical phenotype
Investigating biomarkers of tuberculosis and their variation by clinical phenotype
Mycobacterium tuberculosis (Mtb) is a globally important infectious agent that continues to kill 1.5 million people a year and is transmitted when individuals with pulmonary tuberculosis (TB) disease cough. Four million cases of the estimated 10.6 million new tuberculosis (TB) disease cases annually remain undiagnosed and there are no non-sputum-based diagnostic tests specifically for pulmonary tuberculosis. Non-sputum-based biomarkers that can identify people with transmissible pulmonary TB are urgently needed. I investigated the hypothesis that proteins released into the plasma during active pulmonary TB will be clinically useful biomarkers, which will exhibit variance according to host phenotypic characteristics. I undertook non-depletion tandem mass spectrometry to investigate plasma protein expression in active pulmonary tuberculosis patients compared to uninfected patients from a male South African and Peruvian cohort. I performed bioinformatic analysis using linear modelling and network correlation analysis to identify differentially expressed proteins. Additionally, I investigated the biology of the plasma proteome of pulmonary tuberculosis using gene ontology and protein variance analysis tools. I subsequently validated candidate protein biomarkers using complementary antibody-based protein detection methods in a separate mixed sex patient cohort from diverse ethnic backgrounds. I explored the ability of validated biomarkers to discriminate individuals with TB from healthy controls and individuals with symptoms of pulmonary TB with an alternative diagnosis, termed respiratory symptomatics. Following combinatorial analysis, I identified a six-protein panel that could distinguish TB from both healthy individuals and respiratory symptomatics with extremely high sensitivity, specificity, and accuracy, indicating that this panel could be used to facilitate the diagnosis of TB and help close the case-detection gap that is fuelling the pandemic.
University of Southampton
Schiff, Hannah
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September 2023
Schiff, Hannah
59bd19d1-4547-4807-941b-cc273f6ebf9b
Elkington, Paul
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Garay Baquero, Diana
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Tezera, Liku Bekele
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Schiff, Hannah
(2023)
Investigating biomarkers of tuberculosis and their variation by clinical phenotype.
University of Southampton, Doctoral Thesis, 277pp.
Record type:
Thesis
(Doctoral)
Abstract
Mycobacterium tuberculosis (Mtb) is a globally important infectious agent that continues to kill 1.5 million people a year and is transmitted when individuals with pulmonary tuberculosis (TB) disease cough. Four million cases of the estimated 10.6 million new tuberculosis (TB) disease cases annually remain undiagnosed and there are no non-sputum-based diagnostic tests specifically for pulmonary tuberculosis. Non-sputum-based biomarkers that can identify people with transmissible pulmonary TB are urgently needed. I investigated the hypothesis that proteins released into the plasma during active pulmonary TB will be clinically useful biomarkers, which will exhibit variance according to host phenotypic characteristics. I undertook non-depletion tandem mass spectrometry to investigate plasma protein expression in active pulmonary tuberculosis patients compared to uninfected patients from a male South African and Peruvian cohort. I performed bioinformatic analysis using linear modelling and network correlation analysis to identify differentially expressed proteins. Additionally, I investigated the biology of the plasma proteome of pulmonary tuberculosis using gene ontology and protein variance analysis tools. I subsequently validated candidate protein biomarkers using complementary antibody-based protein detection methods in a separate mixed sex patient cohort from diverse ethnic backgrounds. I explored the ability of validated biomarkers to discriminate individuals with TB from healthy controls and individuals with symptoms of pulmonary TB with an alternative diagnosis, termed respiratory symptomatics. Following combinatorial analysis, I identified a six-protein panel that could distinguish TB from both healthy individuals and respiratory symptomatics with extremely high sensitivity, specificity, and accuracy, indicating that this panel could be used to facilitate the diagnosis of TB and help close the case-detection gap that is fuelling the pandemic.
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Published date: September 2023
Identifiers
Local EPrints ID: 482091
URI: http://eprints.soton.ac.uk/id/eprint/482091
PURE UUID: 54de0691-c7bd-4945-8b0b-da03bbe08f97
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Date deposited: 19 Sep 2023 16:34
Last modified: 05 Feb 2025 05:01
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Contributors
Author:
Hannah Schiff
Thesis advisor:
Diana Garay Baquero
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