Detection of tuberculosis in HIV-infected and -uninfected African adults using whole blood RNA expression signatures: a case-control study
A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninf...
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Published in: | PLoS medicine Vol. 10; no. 10; p. e1001538 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
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Public Library of Science
01-10-2013
Public Library of Science (PLoS) |
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Abstract | A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test.
Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group.
In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary. |
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AbstractList | BackgroundA major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test.Methods and findingsAdult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group.ConclusionsIn our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary. A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group. In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary. Please see later in the article for the Editors' Summary. Background A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Methods and Findings Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or -uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group. Conclusions In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV-infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary Using a microarray-based approach, Michael Levin and colleagues develop a disease risk score to distinguish active from latent tuberculosis, as well as tuberculosis from other diseases, using whole blood samples. Please see later in the article for the Editors' Summary Background: A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We hypothesized that a unique host blood RNA transcriptional signature would distinguish TB from other diseases (OD) in HIV-infected and -uninfected patients, and that this could be the basis of a simple diagnostic test. Methods and Findings: Adult case-control cohorts were established in South Africa and Malawi of HIV-infected or uninfected individuals consisting of 584 patients with either TB (confirmed by culture of Mycobacterium tuberculosis [M.TB] from sputum or tissue sample in a patient under investigation for TB), OD (i.e., TB was considered in the differential diagnosis but then excluded), or healthy individuals with latent TB infection (LTBI). Individuals were randomized into training (80%) and test (20%) cohorts. Blood transcriptional profiles were assessed and minimal sets of significantly differentially expressed transcripts distinguishing TB from LTBI and OD were identified in the training cohort. A 27 transcript signature distinguished TB from LTBI and a 44 transcript signature distinguished TB from OD. To evaluate our signatures, we used a novel computational method to calculate a disease risk score (DRS) for each patient. The classification based on this score was first evaluated in the test cohort, and then validated in an independent publically available dataset (GSE19491). In our test cohort, the DRS classified TB from LTBI (sensitivity 95%, 95% CI [87-100]; specificity 90%, 95% CI [80-97]) and TB from OD (sensitivity 93%, 95% CI [83-100]; specificity 88%, 95% CI [74-97]). In the independent validation cohort, TB patients were distinguished both from LTBI individuals (sensitivity 95%, 95% CI [85-100]; specificity 94%, 95% CI [84-100]) and OD patients (sensitivity 100%, 95% CI [100-100]; specificity 96%, 95% CI [93-100]). Limitations of our study include the use of only culture confirmed TB patients, and the potential that TB may have been misdiagnosed in a small proportion of OD patients despite the extensive clinical investigation used to assign each patient to their diagnostic group. Conclusions: In our study, blood transcriptional signatures distinguished TB from other conditions prevalent in HIV- infected and -uninfected African adults. Our DRS, based on these signatures, could be developed as a test for TB suitable for use in HIV endemic countries. Further evaluation of the performance of the signatures and DRS in prospective populations of patients with symptoms consistent with TB will be needed to define their clinical value under operational conditions. Please see later in the article for the Editors' Summary. |
Audience | Academic |
Author | Anderson, Suzanne T Eley, Brian Mendelson, Marc Kaforou, Myrsini French, Neil Banwell, Claire M Zgambo, Femia Wilkinson, Robert J Coin, Lachlan J Oni, Tolu Wright, Victoria J Crampin, Amelia C Levin, Michael Langford, Paul R Ottenhoff, Tom H Hibberd, Martin L Brent, Andrew J Bangani, Nonzwakazi Kern, Florian Dockrell, Hazel M Heyderman, Robert S Ling, Ling |
AuthorAffiliation | 10 Department of Immunology and Infection, London School of Hygiene & Tropical Medicine, London, United Kingdom 14 Division of Infectious Diseases and HIV Medicine, Department of Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa San Francisco General Hospital, University of California San Francisco, United States of America 7 Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom 15 Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands 16 MRC National Institute for Medical Research, London, United Kingdom 2 Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom 4 Karonga Prevention Study, Chilumba, Karonga District, Malawi 8 Malawi-Liverpool-Wellcome Trust Clinical Research Programme, University of Malawi College of Medicine, Blantyre, Malawi 6 Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, L |
AuthorAffiliation_xml | – name: 3 Clinical Infectious Diseases Research Initiative, Institute of Infectious Diseases & Molecular Medicine, University of Cape Town, Cape Town, South Africa – name: 7 Brighton and Sussex Medical School, University of Sussex, Brighton, United Kingdom – name: 16 MRC National Institute for Medical Research, London, United Kingdom – name: 9 KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya – name: 12 Liverpool School of Tropical Medicine, Liverpool, United Kingdom – name: 14 Division of Infectious Diseases and HIV Medicine, Department of Medicine, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa – name: 17 Institute for Molecular Bioscience, University of Queensland, St Lucia, Queensland, Australia – name: 15 Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands – name: 2 Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom – name: 8 Malawi-Liverpool-Wellcome Trust Clinical Research Programme, University of Malawi College of Medicine, Blantyre, Malawi – name: 4 Karonga Prevention Study, Chilumba, Karonga District, Malawi – name: 6 Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom – name: 10 Department of Immunology and Infection, London School of Hygiene & Tropical Medicine, London, United Kingdom – name: 5 Institute of Infection & Global Health, University of Liverpool, Liverpool, United Kingdom – name: 13 Infectious Disease, Genome Institute of Singapore, Singapore – name: 1 Section of Paediatrics and Wellcome Trust Centre for Clinical Tropical Medicine, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, United Kingdom – name: 11 Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa – name: San Francisco General Hospital, University of California San Francisco, United States of America |
Author_xml | – sequence: 1 givenname: Myrsini surname: Kaforou fullname: Kaforou, Myrsini organization: Section of Paediatrics and Wellcome Trust Centre for Clinical Tropical Medicine, Division of Infectious Diseases, Department of Medicine, Imperial College London, London, United Kingdom ; Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, United Kingdom – sequence: 2 givenname: Victoria J surname: Wright fullname: Wright, Victoria J – sequence: 3 givenname: Tolu surname: Oni fullname: Oni, Tolu – sequence: 4 givenname: Neil surname: French fullname: French, Neil – sequence: 5 givenname: Suzanne T surname: Anderson fullname: Anderson, Suzanne T – sequence: 6 givenname: Nonzwakazi surname: Bangani fullname: Bangani, Nonzwakazi – sequence: 7 givenname: Claire M surname: Banwell fullname: Banwell, Claire M – 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: Hazel M surname: Dockrell fullname: Dockrell, Hazel M – sequence: 11 givenname: Brian surname: Eley fullname: Eley, Brian – sequence: 12 givenname: Robert S surname: Heyderman fullname: Heyderman, Robert S – sequence: 13 givenname: Martin L surname: Hibberd fullname: Hibberd, Martin L – sequence: 14 givenname: Florian surname: Kern fullname: Kern, Florian – sequence: 15 givenname: Paul R surname: Langford fullname: Langford, Paul R – sequence: 16 givenname: Ling surname: Ling fullname: Ling, Ling – sequence: 17 givenname: Marc surname: Mendelson fullname: Mendelson, Marc – sequence: 18 givenname: Tom H surname: Ottenhoff fullname: Ottenhoff, Tom H – sequence: 19 givenname: Femia surname: Zgambo fullname: Zgambo, Femia – sequence: 20 givenname: Robert J surname: Wilkinson fullname: Wilkinson, Robert J – sequence: 21 givenname: Lachlan J surname: Coin fullname: Coin, Lachlan J – sequence: 22 givenname: Michael surname: Levin fullname: Levin, Michael |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24167453$$D View this record in MEDLINE/PubMed |
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Keywords | HIV Infections Tuberculosis Mycobacterium tuberculosis Sensitivity & Specificity Humans Africa Adult RNA, Bacterial Case-Control Studies |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 The authors have declared that patent applications have been filed for the Disease Risk score (GB1201766.1) and TB/LTBI and TB/OD signatures (GB1213636.2). Conceived and designed the experiments: MK VJW NF STA AJB HMD BE RSH MLH FK PRL MM RJW LJC ML. Performed the experiments: MK VJW TO NB CMB LL FZ. Analyzed the data: MK VJW TO NF ACC RJW LJC ML. Contributed reagents/materials/analysis tools: MLH THO. Wrote the first draft of the manuscript: MK VJW NF RJW LJC ML. Contributed to the writing of the manuscript: MK VJW TO NF ACC HMD RSH RJW LJC ML. ICMJE criteria for authorship read and met: MK VJW TO NF STA NB CMB AJB ACC HMD BE RSH MLH FK PRL LL MM THO FZ RJW LJC ML. Agree with manuscript results and conclusions: MK VJW TO NF STA NB CMB AJB ACC HMD BE RSH MLH FK PRL LL MM THO FZ RJW LJC ML. Enrolled patients: TO NF NB FZ RJW. Contributed equally to this work with: Robert J. Wilkinson, Lachlan J. Coin, Michael Levin |
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Snippet | A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV infection. We... Background: A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV... Please see later in the article for the Editors' Summary. BACKGROUNDA major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV... Using a microarray-based approach, Michael Levin and colleagues develop a disease risk score to distinguish active from latent tuberculosis, as well as... BackgroundA major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV... Background A major impediment to tuberculosis control in Africa is the difficulty in diagnosing active tuberculosis (TB), particularly in the context of HIV... |
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SubjectTerms | Adult Africa Africans Case-Control Studies Diagnosis Gene expression Genetic aspects Health aspects HIV HIV infection HIV Infections - complications HIV Infections - microbiology Human immunodeficiency virus Humans Infections Medical research Mycobacterium tuberculosis - genetics Mycobacterium tuberculosis - isolation & purification RNA sequencing RNA, Bacterial - blood Sensitivity and Specificity Studies Tuberculosis Tuberculosis - diagnosis Tuberculosis - genetics |
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Title | Detection of tuberculosis in HIV-infected and -uninfected African adults using whole blood RNA expression signatures: a case-control study |
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