A blood RNA signature for tuberculosis disease risk: a prospective cohort study (original) (raw)
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Four-gene Pan-African Blood Signature Predicts Progression to Tuberculosis
American journal of respiratory and critical care medicine, 2018
Contacts of tuberculosis (TB) patients constitute an important target population for preventative measures as they are at high risk of infection with Mycobacterium tuberculosis and progression to disease. We investigated biosignatures with predictive ability for incident tuberculosis. 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, polymerase chain reaction (PCR) and the Pair Ratio algorithm in a training/test set approach. Overall, 79 progressors, who developed tuberculosis between 3 and 24 months following exposure, and 328 matched non-progressors, who remained healthy during 24 months of follow-up, were investigated. A four-transcript signature (RISK4), 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 popul...
PLOS ONE, 2020
Introduction Host blood transcriptomic biomarkers have potential as rapid point-of-care triage, diagnostic, and predictive tests for Tuberculosis disease. We aimed to summarise the performance of host blood transcriptomic signatures for diagnosis of and prediction of progression to Tuberculosis disease; and compare their performance to the recommended World Health Organisation target product profile. Methods A systematic review and meta-analysis of the performance of host blood mRNA signatures for diagnosing and predicting progression to Tuberculosis disease in HIV-negative adults and adolescents, in studies with an independent validation cohort. Medline, Scopus, Web of Science, and EBSCO libraries were searched for articles published between January 2005 and May 2019, complemented by a search of bibliographies. Study selection, data extraction and quality assessment were done independently by two reviewers. Meta-analysis was performed for signatures that were validated in �3 comparable cohorts, using a bivariate random effects model. Results Twenty studies evaluating 25 signatures for diagnosis of or prediction of progression to TB disease in a total of 68 cohorts were included. Eighteen studies evaluated 24 signatures for TB diagnosis and 17 signatures met at least one TPP minimum performance criterion. Three diagnostic signatures were validated in clinically relevant cohorts to differentiate TB from other diseases, with pooled sensitivity 84%, 87% and 90% and pooled specificity 79%,
Communications Medicine
Background Sensitive point-of-care screening tests are urgently needed to identify individuals at highest risk of tuberculosis. We prospectively tested performance of host-blood transcriptomic tuberculosis signatures. Methods Adults without suspicion of tuberculosis were recruited from five endemic South African communities. Eight parsimonious host-blood transcriptomic tuberculosis signatures were measured by microfluidic RT-qPCR at enrolment. Upper respiratory swab specimens were tested with a multiplex bacterial-viral RT-qPCR panel in a subset of participants. Diagnostic and prognostic performance for microbiologically confirmed prevalent and incident pulmonary tuberculosis was tested in all participants at baseline and during active surveillance through 15 months follow-up, respectively. Results Among 20,207 HIV-uninfected and 963 HIV-infected adults screened; 2923 and 861 were enroled. There were 61 HIV-uninfected (weighted prevalence 1.1%) and 10 HIV-infected (prevalence 1.2%) ...
Gene‐Expression Patterns in Whole Blood Identify Subjects at Risk for Recurrent Tuberculosis
The Journal of Infectious Diseases, 2007
Background. The majority of patients with tuberculosis who comply with appropriate treatment are cured. However, ∼5% subsequently have a repeat disease episode, usually within 2 years of successful combination therapy. Presently, there is no way of predicting which patients will experience a relapse. Methods. We identified 10 subjects who had previously experienced recurrent tuberculosis and carefully matched them to cured subjects who had had only 1 episode of tuberculosis, to patients with active tuberculosis, and to latently infected healthy subjects. We compared their ex vivo whole-blood gene-expression profiles by use of DNA array technology and confirmed the results by use of quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). Results. The 4 clinical tuberculosis groups exhibited distinct patterns of gene expression. The gene-transcript profiles of the patients with recurrent tuberculosis were more similar to those of the patients with active tuberculosis than to those of the cured or latently infected subjects. Discriminant analysis of a training data set showed that 9 genes were sufficient to classify the subjects. We confirmed that measurement of the expression of these genes by qRT-PCR can accurately discriminate between subjects in a test set of samples. Conclusions. A simple test based on gene-expression patterns may be used as a biomarker of cure while identifying patients who are at risk for relapse. This would facilitate the introduction of new tuberculosis drugs. The response to infection with Mycobacterium tuberculosis in humans is multifactorial and includes genetically determined host factors [1, 2], the virulence of the infecting strain of M. tuberculosis [3], and environmental factors, such as prior exposure to nonpathogenic mycobacteria [4, 5]. The majority (90%) of subjects infected with M. tuberculosis contain the infection
Longitudinal Dynamics of a Blood Transcriptomic Signature of Tuberculosis
American Journal of Respiratory and Critical Care Medicine, 2021
Rationale: Performance of blood transcriptomic tuberculosis (TB) signatures in longitudinal studies and effects of TB-preventive therapy and coinfection with HIV or respiratory organisms on transcriptomic signatures has not been systematically studied. Objectives: We evaluated longitudinal kinetics of an 11-gene blood transcriptomic TB signature, RISK11, and effects of TB-preventive therapy (TPT) and respiratory organisms on RISK11 signature score, in HIV-uninfected and HIV-infected individuals. Methods: RISK11 was measured in a longitudinal study of RISK11-guided TPT in HIV-uninfected adults, a cross-sectional respiratory organisms cohort, or a longitudinal study in people living with HIV (PLHIV). HIV-uninfected RISK11 1 participants were randomized to TPT or no TPT; RISK11 2 participants received no TPT. PLHIV received standard-of-care antiretroviral therapy and TPT. In the cross-sectional respiratory organisms cohort, viruses and bacteria in nasopharyngeal and oropharyngeal swabs were quantified by real-time quantitative PCR. Measurements and Main Results: RISK11 1 status was transient in most of the 128 HIV-negative participants with longitudinal samples; more than 70% of RISK11 1 participants reverted to RISK11 2 by 3 months, irrespective of TPT. By comparison, reversion from a RISK11 1 state was less common in 645 PLHIV (42.1%). Non-HIV viral and nontuberculous bacterial organisms were detected in 7.2% and 38.9% of the 1,000 respiratory organisms cohort participants, respectively, and among those investigated for TB, 3.8% had prevalent disease. Median RISK11 scores (%) were higher in participants with viral organisms alone (46.7%), viral and bacterial organisms (42.8%), or prevalent TB (85.7%) than those with bacterial organisms other than TB (13.4%) or no organisms (14.2%). RISK11 could not discriminate between prevalent TB and viral organisms. Conclusions: Positive RISK11 signature status is often transient, possibly due to intercurrent viral infection, highlighting potentially important challenges for implementation of these biomarkers as new tools for TB control.
Frontiers in Immunology, 2021
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, ...
The Lancet Global Health, 2021
Background A rapid, blood-based triage test that allows targeted investigation for tuberculosis at the point of care could shorten the time to tuberculosis treatment and reduce mortality. We aimed to test the performance of a host blood transcriptomic signature (RISK11) in diagnosing tuberculosis and predicting progression to active pulmonary disease (prognosis) in people with HIV in a community setting. Methods In this prospective diagnostic and prognostic accuracy study, adults (aged 18-59 years) with HIV were recruited from five communities in South Africa. Individuals with a history of tuberculosis or household exposure to multidrug-resistant tuberculosis within the past 3 years, comorbid risk factors for tuberculosis, or any condition that would interfere with the study were excluded. RISK11 status was assessed at baseline by real-time PCR; participants and study staff were masked to the result. Participants underwent active surveillance for microbiologically confirmed tuberculosis by providing spontaneously expectorated sputum samples at baseline, if symptomatic during 15 months of follow-up, and at 15 months (the end of the study). The coprimary outcomes were the prevalence and cumulative incidence of tuberculosis disease confirmed by a positive Xpert MTB/RIF, Xpert Ultra, or Mycobacteria Growth Indicator Tube culture, or a combination of such, on at least two separate sputum samples collected within any 30-day period.
The Journal of Infectious Diseases
Background Gene expression profiling is emerging as a tool for tuberculosis diagnosis and treatment response monitoring, but limited data specific to Indian children and incident tuberculosis infection (TBI) exist. Methods 16 pediatric Indian tuberculosis cases were age- and sex-matched to 32 tuberculosis-exposed controls (13 developed incident TBI without subsequent active tuberculosis). Longitudinal samples were collected for RNAseq. Differential expression analysis generated gene lists that identify tuberculosis diagnosis and tuberculosis treatment response. Data were compared with published gene lists. Population-specific risk score thresholds were calculated. Results 71 genes identified tuberculosis diagnosis and 25 treatment response. Within-group expression was partially explained by age, sex, and incident TBI. Transient changes in gene expression were identified after both infection and treatment. Application of 27 published gene lists to our data found variable performance ...
Scientific Reports
There is a crucial need for non-sputum-based TB tests. Here, we evaluate the performance of RISK6, a human-blood transcriptomic signature, for TB screening, triage and treatment monitoring. RISK6 performance was also compared to that of two IGRAs: one based on RD1 antigens (QuantiFERON-TB Gold Plus, QFT-P, Qiagen) and one on recombinant M. tuberculosis HBHA expressed in Mycobacterium smegmatis (IGRA-rmsHBHA). In this multicenter prospective nested case–control study conducted in Bangladesh, Georgia, Lebanon and Madagascar, adult non-immunocompromised patients with bacteriologically confirmed active pulmonary TB (ATB), latent TB infection (LTBI) and healthy donors (HD) were enrolled. ATB patients were followed-up during and after treatment. Blood RISK6 scores were assessed using quantitative real-time PCR and evaluated by area under the receiver-operating characteristic curve (ROC AUC). RISK6 performance to discriminate ATB from HD reached an AUC of 0.94 (95% CI 0.89–0.99), with 90.9...