Identification of Reduced Host Transcriptomic Signatures for Tuberculosis Disease and Digital PCR-Based Validation and Quantification
Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript sign...
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| Published in | Frontiers in immunology Vol. 12; p. 637164 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Switzerland
Frontiers Media S.A
02.03.2021
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1664-3224 1664-3224 |
| DOI | 10.3389/fimmu.2021.637164 |
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| Abstract | Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)—digital PCR (dPCR). A four-transcript signature (
GBP6, TMCC1, PRDM1
, and
ARG1
) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI
95%
82.2–100%). A three-transcript signature (
FCGR1A, ZNF296, and C1QB
) differentiated TB from LTBI (AUC 97.3%, CI
95%
: 93.3–100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB. |
|---|---|
| AbstractList | Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)—digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2–100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3–100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB. Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB.Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature (GBP6, TMCC1, PRDM1, and ARG1) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI95% 82.2-100%). A three-transcript signature (FCGR1A, ZNF296, and C1QB) differentiated TB from LTBI (AUC 97.3%, CI95%: 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB. Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)-digital PCR (dPCR). A four-transcript signature ( , and ) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI 82.2-100%). A three-transcript signature ( ) differentiated TB from LTBI (AUC 97.3%, CI : 93.3-100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB. Recently, host whole blood gene expression signatures have been identified for diagnosis of tuberculosis (TB). Absolute quantification of the concentrations of signature transcripts in blood have not been reported, but would facilitate diagnostic test development. To identify minimal transcript signatures, we applied a transcript selection procedure to microarray data from African adults comprising 536 patients with TB, other diseases (OD) and latent TB (LTBI), divided into training and test sets. Signatures were further investigated using reverse transcriptase (RT)—digital PCR (dPCR). A four-transcript signature ( GBP6, TMCC1, PRDM1 , and ARG1 ) measured using RT-dPCR distinguished TB patients from those with OD (area under the curve (AUC) 93.8% (CI 95% 82.2–100%). A three-transcript signature ( FCGR1A, ZNF296, and C1QB ) differentiated TB from LTBI (AUC 97.3%, CI 95% : 93.3–100%), regardless of HIV. These signatures have been validated across platforms and across samples offering strong, quantitative support for their use as diagnostic biomarkers for TB. |
| Author | Crampin, Amelia C. Hibberd, Martin L. Wilkinson, Robert J. Eley, Brian Dockrell, Hazel M. Ottenhoff, Tom H. M. Kaforou, Myrsini Langford, Paul R. Coin, Lachlan J. French, Neil Oni, Tolu Gliddon, Harriet D. Habgood-Coote, Dominic Brent, Andrew J. Levin, Michael Zhou, Chenxi Wright, Victoria J. Kern, Florian Alikian, Mary Anderson, Suzanne T. Heyderman, Robert |
| AuthorAffiliation | 23 Department of Immunology and Infection, and Tuberculosis (TB) Centre, London School of Hygiene and Tropical Medicine , London , United Kingdom 25 Department of Medicine, Imperial College London , London , United Kingdom 9 Nuffield Department of Medicine, University of Oxford , Oxford , United Kingdom 20 Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London , United Kingdom 1 Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London , London , United Kingdom 6 School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town , Cape Town , South Africa 16 Division of Infection and Immunity, Faculty of Medical Sciences, University College London , London , United Kingdom 24 The Francis Crick Institute , London , United Kingdom 26 Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town , Ca |
| AuthorAffiliation_xml | – name: 6 School of Public Health and Family Medicine, Faculty of Health Sciences, University of Cape Town , Cape Town , South Africa – name: 24 The Francis Crick Institute , London , United Kingdom – name: 5 Institute for Molecular Bioscience, University of Queensland , Brisbane, QLD , Australia – name: 4 Centre for Haematology, Faculty of Medicine, Imperial College London , London , United Kingdom – name: 26 Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town , Cape Town , South Africa – name: 18 Brighton and Sussex University Hospitals National Health Service (NHS) Trust , Brighton , United Kingdom – name: 17 Brighton and Sussex Medical School, University of Sussex , Brighton , United Kingdom – name: 19 Department of Infectious Diseases, Leiden University Medical Center , Leiden , Netherlands – name: 10 Oxford University Hospitals National Health Service (NHS) Foundation Trust , Oxford , United Kingdom – name: 23 Department of Immunology and Infection, and Tuberculosis (TB) Centre, London School of Hygiene and Tropical Medicine , London , United Kingdom – name: 1 Section of Paediatrics, Department of Infectious Disease, Faculty of Medicine, Imperial College London , London , United Kingdom – name: 7 Brighton and Sussex Medical School , Brighton , United Kingdom – name: 2 National Public Health Speciality Training Programme , South West , United Kingdom – name: 16 Division of Infection and Immunity, Faculty of Medical Sciences, University College London , London , United Kingdom – name: 9 Nuffield Department of Medicine, University of Oxford , Oxford , United Kingdom – name: 3 Imperial Molecular Pathology, Imperial Healthcare Trust, Hammersmith Hospital , London , United Kingdom – name: 11 Malawi Epidemiology and Intervention Research Unit , Chilumba , Malawi – name: 13 Karonga Prevention Study , Chilumba , Malawi – name: 14 Paediatric Infectious Diseases Unit, Red Cross War Memorial Children's Hospital , Cape Town , South Africa – name: 22 Centre for Global Vaccine Research, Institute of Infection & Global Health, University of Liverpool , Liverpool , United Kingdom – name: 25 Department of Medicine, Imperial College London , London , United Kingdom – name: 21 Tropical and Infectious Disease Unit, Royal Liverpool and Broadgreen University Hospitals National Health Service (NHS) Trust , Liverpool , United Kingdom – name: 8 Brighton and Malawi Liverpool Wellcome Trust Unit , Blantyre , Malawi – name: 20 Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine , London , United Kingdom – name: 12 London School of Hygiene & Tropical Medicine , London , United Kingdom – name: 15 Department of Paediatrics and Child Health, University of Cape Town , Cape Town , South Africa |
| Author_xml | – sequence: 1 givenname: Harriet D. surname: Gliddon fullname: Gliddon, Harriet D. – sequence: 2 givenname: Myrsini surname: Kaforou fullname: Kaforou, Myrsini – sequence: 3 givenname: Mary surname: Alikian fullname: Alikian, Mary – sequence: 4 givenname: Dominic surname: Habgood-Coote fullname: Habgood-Coote, Dominic – sequence: 5 givenname: Chenxi surname: Zhou fullname: Zhou, Chenxi – sequence: 6 givenname: Tolu surname: Oni fullname: Oni, Tolu – sequence: 7 givenname: Suzanne T. surname: Anderson fullname: Anderson, Suzanne T. – sequence: 8 givenname: Andrew J. surname: Brent fullname: Brent, Andrew J. – sequence: 9 givenname: Amelia C. surname: Crampin fullname: Crampin, Amelia C. – sequence: 10 givenname: Brian surname: Eley fullname: Eley, Brian – sequence: 11 givenname: Robert surname: Heyderman fullname: Heyderman, Robert – sequence: 12 givenname: Florian surname: Kern fullname: Kern, Florian – sequence: 13 givenname: Paul R. surname: Langford fullname: Langford, Paul R. – sequence: 14 givenname: Tom H. M. surname: Ottenhoff fullname: Ottenhoff, Tom H. M. – sequence: 15 givenname: Martin L. surname: Hibberd fullname: Hibberd, Martin L. – sequence: 16 givenname: Neil surname: French fullname: French, Neil – sequence: 17 givenname: Victoria J. surname: Wright fullname: Wright, Victoria J. – sequence: 18 givenname: Hazel M. surname: Dockrell fullname: Dockrell, Hazel M. – sequence: 19 givenname: Lachlan J. surname: Coin fullname: Coin, Lachlan J. – sequence: 20 givenname: Robert J. surname: Wilkinson fullname: Wilkinson, Robert J. – sequence: 21 givenname: Michael surname: Levin fullname: Levin, Michael |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33763081$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | Copyright © 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin. Copyright © 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin. 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin |
| Copyright_xml | – notice: Copyright © 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin. – notice: Copyright © 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin. 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin |
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| Keywords | transcriptomics dPCR biomarkers gene expression signatures tuberculosis |
| Language | English |
| License | Copyright © 2021 Gliddon, Kaforou, Alikian, Habgood-Coote, Zhou, Oni, Anderson, Brent, Crampin, Eley, Heyderman, Kern, Langford, Ottenhoff, Hibberd, French, Wright, Dockrell, Coin, Wilkinson and Levin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. cc-by |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 This article was submitted to Microbial Immunology, a section of the journal Frontiers in Immunology Reviewed by: Simon C. Mendelsohn, South African Tuberculosis Vaccine Initiative SATVI, South Africa; Jiezuan Yang, Zhejiang University, China These authors have contributed equally to this work Edited by: Malcolm Scott Duthie, HDT Biotech Corporation, United States |
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| Title | Identification of Reduced Host Transcriptomic Signatures for Tuberculosis Disease and Digital PCR-Based Validation and Quantification |
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