Host blood RNA transcript and protein signatures for sputum-independent diagnostics of tuberculosis in adults
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Host blood RNA transcript and protein signatures for sputum-independent diagnostics of tuberculosis in adults. / Sivakumaran, Dhanasekaran; Ritz, Christian; Gjøen, John Espen; Vaz, Mario; Selvam, Sumithra; Ottenhoff, Tom H M; Doherty, Timothy Mark; Jenum, Synne; Grewal, Harleen M S.
In: Frontiers in Immunology, Vol. 11, 626049, 2021.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Host blood RNA transcript and protein signatures for sputum-independent diagnostics of tuberculosis in adults
AU - Sivakumaran, Dhanasekaran
AU - Ritz, Christian
AU - Gjøen, John Espen
AU - Vaz, Mario
AU - Selvam, Sumithra
AU - Ottenhoff, Tom H M
AU - Doherty, Timothy Mark
AU - Jenum, Synne
AU - Grewal, Harleen M S
N1 - Copyright © 2021 Sivakumaran, Ritz, Gjøen, Vaz, Selvam, Ottenhoff, Doherty, Jenum and Grewal.
PY - 2021
Y1 - 2021
N2 - To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of ≥0.98 (95% CIs: 0.94-1.00), and a 4-protein signature (IFNγ, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of ≥0.87 (95% CIs: 0.75-1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91-0.98) and 0.94 (95% CI: 0.89-0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87-0.99) and 0.73 (95% CI: 0.56-0.89). These criteria meet the WHO TTP benchmarks for a non-sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.
AB - To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of ≥0.98 (95% CIs: 0.94-1.00), and a 4-protein signature (IFNγ, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of ≥0.87 (95% CIs: 0.75-1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91-0.98) and 0.94 (95% CI: 0.89-0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87-0.99) and 0.73 (95% CI: 0.56-0.89). These criteria meet the WHO TTP benchmarks for a non-sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.
KW - Faculty of Science
KW - Transcript signature
KW - Protein signature
KW - Tuberculosis
KW - Adult
KW - Non-sputum
U2 - 10.3389/fimmu.2020.626049
DO - 10.3389/fimmu.2020.626049
M3 - Journal article
C2 - 33613569
VL - 11
JO - Frontiers in Immunology
JF - Frontiers in Immunology
SN - 1664-3224
M1 - 626049
ER -
ID: 257241354