A blood RNA signature for tuberculosis disease risk: a prospective cohort study.

BACKGROUND: Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease might lead to interventions that combat the tuberculosis epidemic. We aimed to assess whether global gene expression measured in whole blood of healthy people allowed identification of prospective signatures of risk of active tuberculosis disease. METHODS: In this prospective cohort study, we followed up healthy, South African adolescents aged 12-18 years from the adolescent cohort study (ACS) who were infected with M tuberculosis for 2 years. We collected blood samples from study participants every 6 months and monitored the adolescents for progression to tuberculosis disease. A prospective signature of risk was derived from whole blood RNA sequencing data by comparing participants who developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex quantitative real-time PCR (qRT-PCR), the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. Participants of the independent cohorts were household contacts of adults with active pulmonary tuberculosis disease. FINDINGS: Between July 6, 2005, and April 23, 2007, we enrolled 6363 participants from the ACS study and 4466 from independent South African and Gambian cohorts. 46 progressors and 107 matched controls were identified in the ACS cohort. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% CI 63·2-68·9) and a specificity of 80·6% (79·2-82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA sequencing and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6-64·3) and a specificity of 82·8% (76·7-86) in the 12 months preceding tuberculosis. INTERPRETATION: The whole blood tuberculosis risk signature prospectively identified people at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. FUNDING: Bill & Melinda Gates Foundation, the National Institutes of Health, Aeras, the European Union, and the South African Medical Research Council

Four-Gene Pan-African Blood Signature Predicts Progression to Tuberculosis.

Rationale: Contacts of patients with tuberculosis (TB) constitute an important target population for preventive measures because they are at high risk of infection with Mycobacterium tuberculosis and progression to disease.Objectives: We investigated biosignatures with predictive ability for incident TB.Methods: In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, PCR, and the pair ratio algorithm in a training/test set approach. Overall, 79 progressors who developed TB between 3 and 24 months after diagnosis of index case and 328 matched nonprogressors who remained healthy during 24 months of follow-up were investigated.Measurements and Main Results: A four-transcript signature derived from samples in a South African and Gambian training set predicted progression up to two years before onset of disease in blinded test set samples from South Africa, the Gambia, and Ethiopia with little population-associated variability, and it was also validated in an external cohort of South African adolescents with latent M. tuberculosis infection. By contrast, published diagnostic or prognostic TB signatures were predicted in samples from some but not all three countries, indicating site-specific variability. Post hoc meta-analysis identified a single gene pair, C1QC/TRAV27 (complement C1q C-chain / T-cell receptor-α variable gene 27) that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events.Conclusions: Collectively, we developed a simple whole blood-based PCR test to predict TB in recently exposed household contacts from diverse African populations. This test has potential for implementation in national TB contact investigation programs

Sequential inflammatory processes define human progression from <i>M</i>. <i>tuberculosis </i> infection to tuberculosis disease

<div><p>Our understanding of mechanisms underlying progression from <i>Mycobacterium tuberculosis</i> infection to pulmonary tuberculosis disease in humans remains limited. To define such mechanisms, we followed <i>M</i>. <i>tuberculosis</i>-infected adolescents longitudinally. Blood samples from forty-four adolescents who ultimately developed tuberculosis disease (“progressors”) were compared with those from 106 matched controls, who remained healthy during two years of follow up. We performed longitudinal whole blood transcriptomic analyses by RNA sequencing and plasma proteome analyses using multiplexed slow off-rate modified DNA aptamers. Tuberculosis progression was associated with sequential modulation of immunological processes. Type I/II interferon signalling and complement cascade were elevated 18 months before tuberculosis disease diagnosis, while changes in myeloid inflammation, lymphoid, monocyte and neutrophil gene modules occurred more proximally to tuberculosis disease. Analysis of gene expression in purified T cells also revealed early suppression of Th17 responses in progressors, relative to <i>M</i>. <i>tuberculosis</i>-infected controls. This was confirmed in an independent adult cohort who received BCG re-vaccination; transcript expression of interferon response genes in blood prior to BCG administration was associated with suppression of IL-17 expression by BCG-specific CD4 T cells 3 weeks post-vaccination. Our findings provide a timeline to the different immunological stages of disease progression which comprise sequential inflammatory dynamics and immune alterations that precede disease manifestations and diagnosis of tuberculosis disease. These findings have important implications for developing diagnostics, vaccination and host-directed therapies for tuberculosis.</p><p>Trial registration</p><p>Clincialtrials.gov, <a href="https://clinicaltrials.gov/ct2/show/Clincialtrials.gov, NCT01119521" target="_blank">NCT01119521</a></p></div

Demographic details of TB progressor and control participants.

<p>Participants and sample numbers available for each analysis are also shown.</p

Changes in proportions of peripheral blood cell subsets during progression from infection to TB disease.

<p>(<b>A</b>) Kinetics of mRNA expression, expressed as log₂ fold change between bin-matched progressors and controls and modeled as non-linear splines (dotted lines) for genes representing granulocytes, monocytes, T cells and B cells. Light green shading represents 99% CI and dark green shading 95% CI for the temporal trends, computed by performing 2000 spline fitting iterations after bootstrap resampling from the full dataset. The magnitude for each gene, representing the log₂ fold change at TB diagnosis, is shown in green text. The deviation time, calculated as the time point at which the 99% CI deviates from a log₂ fold change of 0, is indicated in red text. Data from 38 progressors and 104 controls were included in the analysis. (<b>B</b>) Temporal trends of gene modules representing granulocytes (genes with significant kinetic response from BIOCARTA_GRANULOCYTES_PATHWAY), monocytes (genes from M11.0_enriched in monocytes (II)), T cells (genes from M4.1_T-cells, M6.15_T-cells, M7.1_T cell activation (I) and M7.4_T cell activation (III)) and B cells (genes from M4.10_B-cells, M47.0_enriched in B cells (I), M47.1_enriched in B cells (II) and M69_enriched in B cells (VI)), modeled as non-linear splines during progression. The deviation time for the interferon module shown in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#ppat.1006687.g003" target="_blank">Fig 3B</a> is denoted by the vertical red line. (<b>C</b>) Temporal trends of relative mean (dotted lines) proportions of monocytes and T cells (<b>D</b>) or activated HLA-DR+ CD4 T cells, CCR7+CD45RA- central memory CD4 or CD8 T cells, measured by flow cytometry from cryopreserved PBMC and modeled as non-linear splines during progression. Shown are log₂ cell proportions for progressors relative to bin-matched controls. Data from 33 progressors and 71 controls were included in the analysis. Shading denotes 99% CI computed by performing 2000 spline fitting iterations after bootstrap resampling from the full dataset.</p

Sequential changes in distinct transcriptional modules during progression from <i>M</i>.<i>tb</i> infection to TB disease.

<p><b>(A</b>) Gene modules, pre-defined by Chaussabel and BTM, found to be significantly enriched in progressors, compared with controls, and ranked in descending order according to median deviation time points (indicated by bars) of genes differentially expressed between progressors and controls. Data from 38 progressors and 104 controls were included in the analysis. Error bars denote IQR of median deviation time points of differentially expressed genes within each module. Assignment of each module to known immunological responses or processes or cellular subsets, according to differentially expressed genes, is indicated by the colored squares. The full list of significantly enriched modules is in <b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#ppat.1006687.s008" target="_blank">S4 Table</a></b>. (<b>B</b>) Kinetics of type I/II interferon response or inflammation transcriptional gene modules, as well as the 16 genes in the ACS signature of risk of TB. For interferon responses we included genes with significant kinetic response from modules: M127_type I interferon response, M5.12_Interferon Response, M3.4_Interferon Response and M1.2_Interferon Response. For inflammation we included genes with significant kinetic response from modules: M6.13_Inflammation, M4.2_Inflammation, M5.1_Inflammation, M16_TLR and inflammatory signaling, M33_inflammatory response and M53_inflammasome receptors and signaling. Module kinetics during progression were modeled as non-linear splines and 99% CI (shaded areas) were computed by performing 2000 spline fitting iterations after bootstrap resampling from the full dataset. (<b>C</b>) Scatter plot showing fold change (log₂ FC) plotted versus the time point at which the 99% CI deviates from a log₂ fold change of 0 (log₂ days before TB diagnosis) for genes in the IFN response and inflammation modules and the 16 genes in the ACS signature of risk of TB.</p

Kinetics of whole blood transcriptional responses during progression from infection to TB disease.

<p>(A) Consort diagram showing participant selection of the progressor and control substudy from the Adolescent Cohort Study (ACS). A total of 6,363 adolescents (12–18 years of age) were enrolled into the ACS. Participants were stratified according to their baseline <i>M</i>.<i>tb-</i>infection status according to either QFT-positive (≥0.35 IU/ml) and/or TST induration ≥ 10mm. Individuals with unknown QFT and TST test results were excluded. Participants with baseline <i>M</i>.<i>tb</i>-infection or who were QFT-negative and TST-negative at baseline but converted their tests at a later time point were eligible for inclusion as progressors or controls. Progressors developed intrathoracic TB disease, defined as TB diagnosis by at least two consecutive sputum smear positive tests, or at least one microbiologically confirmed culture positive test, at least 6 months after detection of <i>M</i>.<i>tb-</i>infection. Progressors were matched to healthy <i>M</i>.<i>tb-</i>infected “controls” based on age, gender, ethnicity, school, and any prior history of TB disease at a ~1:2 ratio. (B) Genes found to be significantly up (red) or down (blue) regulated in progressors relative to controls, ranked according to the time to TB disease at which expression in progressors (n = 38) is significantly different to controls (n = 104) (see <b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#ppat.1006687.s001" target="_blank">S1 Fig</a></b>). The full list of significantly regulated genes is in <b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#ppat.1006687.s006" target="_blank">S2 Table</a></b>.</p

Changes in T cell function associated with whole blood IFN responses in progressors.

<p>(<b>A</b>) Differentially expressed Th17-associated mRNA transcripts in sorted T cells from progressors with positive ACS signature of risk of TB compared with controls with negative signature of risk of TB. T cells were sorted after stimulation of PBMC with medium alone or peptide pools and data from these stimulation conditions were combined for analysis (see <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#sec012" target="_blank">methods</a>). Data from 31 progressors (138 progressor samples were signature-positive, 67 were negative) and 90 controls (299 control samples were signature-negative, 40 were positive) were included in the analysis and time to TB was not considered. Representative genes significantly enriched in the Th17 module by modular analysis, at a p-value < 0.05 and an FDR <0.2, are shown. The full set of differentially expressed T cell genes is in <b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#ppat.1006687.s010" target="_blank">S6 Table</a></b> and gene modules enriched in genes differentially expressed between progressors with positive ACS signature of risk of TB and controls with negative ACS signature of risk of TB are listed in <b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006687#ppat.1006687.s011" target="_blank">S7 Table</a></b>. (<b>B</b>) Flow cytometry plots depicting CD4 T cells co-expressing IFNγ and IL-17 after stimulation of whole blood with BCG or medium (unstimulated) from an adult in the BCG revaccination study. Shown is a representative sample taken 3 weeks after BCG-revaccination. (<b>C</b>) Associations between cytokine expressing CD4 T cells after stimulation of whole blood with BCG or medium (unstimulated) and the ACS signature of risk of TB (COR score), in adults from the BCG revaccination study. Type I/II IFN response was measured by the ACS signature of risk of TB. Shown are frequencies of BCG-specific CD4 T cells co-expressing IFNγ and IL-17 and relative proportions of BCG-specific IFNγ⁺ CD4 T cells co-expressing IL-17. Spearman R and p-values are shown in each plot.</p

Four-gene pan-African blood signature predicts progression to tuberculosis

Rationale: Contacts of patients with tuberculosis (TB) constitute an important target population for preventive measures because they are at high risk of infection with Mycobacterium tuberculosis and progression to disease. Objectives: We investigated bio-signatures with predictive ability for incident TB. Methods: In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, PCR, and the pair ratio algorithm in a training/test set approach. Overall, 79 progressors who developed TB between 3 and 24 months after diagnosis of index case and 328 matched nonprogressors who remained healthy during 24 months of follow-up were investigated. Measurements and Main Results: A four-transcript signature derived from samples in a South African and Gambian training set predicted progression up to two years before onset of disease in blinded test set samples from South Africa, the Gambia, and Ethiopia with little population-associated variability, and it was also validated in an external cohort of South African adolescents with latent M. tuberculosis infection. By contrast, published diagnostic or prognostic TB signatures were predicted in samples from some but not all three countries, indicating site-specific variability. Post hoc meta-analysis identified a single gene pair, C1QC/TRAV27 (complement C1q C-chain / T-cell receptor-a variable gene 27) that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events. Conclusions: Collectively, we developed a simple whole blood-based PCR test to predict TB in recently exposed household contacts from diverse African populations. This test has potential for implementation in national TB contact investigation programs

Four-Gene Pan-African Blood Signature Predicts Progression to Tuberculosis

Rationale: Contacts of patients with tuberculosis (TB) constitute an important target population for preventive measures because they are at high risk of infection with Mycobacterium tuberculosis and progression to disease.Objectives: We investigated biosignatures with predictive ability for incident TB.Methods: In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, PCR, and the pair ratio algorithm in a training/test set approach. Overall, 79 progressors who developed TB between 3 and 24 months after diagnosis of index case and 328 matched nonprogressors who remained healthy during 24 months of follow-up were investigated.Measurements and Main Results: A four-transcript signature derived from samples in a South African and Gambian training set predicted progression up to two years before onset of disease in blinded test set samples from South Africa, the Gambia, and Ethiopia with little population-associated variability, and it was also validated in an external cohort of South African adolescents with latent M. tuberculosis infection. By contrast, published diagnostic or prognostic TB signatures were predicted in samples from some but not all three countries, indicating site-specific variability. Post hoc meta-analysis identified a single gene pair, C1QC/TRAV27 (complement C1q C-chain / T-cell receptor-α variable gene 27) that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events.Conclusions: Collectively, we developed a simple whole blood-based PCR test to predict TB in recently exposed household contacts from diverse African populations. This test has potential for implementation in national TB contact investigation programs