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Performance of diagnostic and predictive host blood transcriptomic signatures for Tuberculosis disease: A systematic review and meta-analysis.

ABSTRACT: 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%, 88% and 74%, respectively. Four studies evaluated signatures for progression to TB disease and performance of one signature, assessed within six months of TB diagnosis, met the minimal TPP for a predictive test for progression to TB disease. CONCLUSION:Host blood mRNA signatures hold promise as triage tests for TB. Further optimisation is needed if mRNA signatures are to be used as standalone diagnostic or predictive tests for therapeutic decision-making.

SUBMITTER: Mulenga H

PROVIDER: S-EPMC7442252 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Performance of diagnostic and predictive host blood transcriptomic signatures for Tuberculosis disease: A systematic review and meta-analysis.

Mulenga Humphrey H Zauchenberger Chambrez-Zita CZ Bunyasi Erick W EW Mbandi Stanley Kimbung SK Mendelsohn Simon C SC Kagina Benjamin B Penn-Nicholson Adam A Scriba Thomas J TJ Hatherill Mark M

PloS one 20200821 8

<h4>Introduction</h4>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.<h4>Methods</h4>A systematic review and meta-analysis of the performance of host blood mR ...[more]

PMID: 32822359

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Project description:IntroductionOne-quarter of the global population, including the majority of adults in tuberculosis (TB) endemic countries, are estimated to be Mycobacterium tuberculosis (MTB) infected. An estimated 10 million new TB cases occurred in 2017. One of the biggest challenges confronting TB control is the lack of accurate diagnosis and prediction of prevalent and incident TB disease, respectively. Several host blood transcriptomic messenger RNA (mRNA) signatures that reflect the host immune response following infection with MTB and progression to TB disease in different study populations have recently been published, but these TB biomarkers have not been systematically described. We will conduct a systematic review of the performance of host blood transcriptional signatures for TB diagnosis and prediction of progression to TB disease.Methods and analysisThis systematic review will involve conducting a comprehensive literature search of cohort, case-control, cross-sectional and randomised-controlled studies of the performance of host blood transcriptomic signatures for TB diagnosis and prediction of progression to TB disease. We will search Medline via PubMed, Scopus, Web of Science and EBSCO libraries, complemented by a search of bibliographies of selected articles for other relevant articles. The literature search will be restricted to studies published in English from 2005 to 2018 and conducted in HIV-uninfected adults and adolescents (≥12 years old). Forest plots and a narrative synthesis of the findings will be provided. The primary outcomes will be sensitivity, specificity, as well as true/false positives and true/false negatives. Heterogeneity resulting from differences in the design, composition and structure of individual signatures will preclude meta-analysis and pooling of results.Ethics and disseminationEthics approval is not required for this systematic review protocol. The results of this review will be disseminated through a peer-reviewed journal as well as conference presentations.Prospero registration numberCRD42017073817.

Project description:IntroductionCurrent tuberculosis triage and predictive tools offer poor accuracy and are ineffective for detecting asymptomatic disease in people living with HIV (PLHIV). Host tuberculosis transcriptomic biomarkers hold promise for diagnosing prevalent and predicting progression to incident tuberculosis and guiding further investigation, preventive therapy and follow-up. We aim to conduct a systematic review of performance of transcriptomic signatures of tuberculosis in PLHIV.Methods and analysisWe will search MEDLINE (PubMed), WOS Core Collection, Biological Abstracts, and SciELO Citation Index (Web of Science), Africa-Wide Information and General Science Abstracts (EBSCOhost), Scopus, and Cochrane Central Register of Controlled Trials databases for articles published in English between 1990 and 2020. Case-control, cross-sectional, cohort and randomised controlled studies evaluating performance of diagnostic and prognostic host-response transcriptomic signatures in PLHIV of all ages and settings will be included. Eligible studies will include PLHIV in signature test or validation cohorts, and use microbiological, clinical, or composite reference standards for pulmonary or extrapulmonary tuberculosis diagnosis. Study quality will be evaluated using the 'Quality Assessment of Diagnostic Accuracy Studies-2' tool and cumulative review evidence assessed using the 'Grading of Recommendations Assessment, Development and Evaluation' approach. Study selection, quality appraisal and data extraction will be performed independently by two reviewers. Study, cohort and signature characteristics of included studies will be tabulated, and a narrative synthesis of findings presented. Primary outcomes of interest, biomarker sensitivity and specificity with estimate precision, will be summarised in forest plots. Expected heterogeneity in signature characteristics, study settings, and study designs precludes meta-analysis and pooling of results. Review reporting will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies guidelines.Ethics and disseminationFormal ethics approval is not required as primary human participant data will not be collected. Results will be disseminated through peer-reviewed publication and conference presentation.Prospero registration numberCRD42021224155.

Project description:BackgroundThe World Health Organization (WHO) and Foundation for Innovative New Diagnostics (FIND) have published target product profiles (TPPs) calling for non-sputum-based diagnostic tests for the diagnosis of active tuberculosis (ATB) disease and for predicting the progression from latent tuberculosis infection (LTBI) to ATB. A large number of host-derived blood-based gene-expression biomarkers for diagnosis of patients with ATB have been proposed to date, but none have been implemented in clinical settings. The focus of this study is to directly compare published gene signatures for diagnosis of patients with ATB across a large, diverse list of publicly available gene expression datasets, and evaluate their performance against the WHO/FIND TPPs.Methods and findingsWe searched PubMed, Gene Expression Omnibus (GEO), and ArrayExpress in June 2018. We included all studies irrespective of study design and enrollment criteria. We found 16 gene signatures for the diagnosis of ATB compared to other clinical conditions in PubMed. For each signature, we implemented a classification model as described in the corresponding original publication of the signature. We identified 24 datasets containing 3,083 transcriptome profiles from whole blood or peripheral blood mononuclear cell samples of healthy controls or patients with ATB, LTBI, or other diseases from 14 countries in GEO. Using these datasets, we calculated weighted mean area under the receiver operating characteristic curve (AUROC), specificity at 90% sensitivity, and negative predictive value (NPV) for each gene signature across all datasets. We also compared the diagnostic odds ratio (DOR), heterogeneity in DOR, and false positive rate (FPR) for each signature using bivariate meta-analysis. Across 9 datasets of patients with culture-confirmed diagnosis of ATB, 11 signatures had weighted mean AUROC > 0.8, and 2 signatures had weighted mean AUROC ≤ 0.6. All but 2 signatures had high NPV (>98% at 2% prevalence). Two gene signatures achieved the minimal WHO TPP for a non-sputum-based triage test. When including datasets with clinical diagnosis of ATB, there was minimal reduction in the weighted mean AUROC and specificity of all but 3 signatures compared to when using only culture-confirmed ATB data. Only 4 signatures had homogeneous DOR and lower FPR when datasets with clinical diagnosis of ATB were included; other signatures either had heterogeneous DOR or higher FPR or both. Finally, 7 of 16 gene signatures predicted progression from LTBI to ATB 6 months prior to sputum conversion with positive predictive value > 6% at 2% prevalence. Our analyses may have under- or overestimated the performance of certain ATB diagnostic signatures because our implementation may be different from the published models for those signatures. We re-implemented published models because the exact models were not publicly available.ConclusionsWe found that host-response-based diagnostics could accurately identify patients with ATB and predict individuals with high risk of progression from LTBI to ATB prior to sputum conversion. We found that a higher number of genes in a signature did not increase the accuracy of the signature. Overall, the Sweeney3 signature performed robustly across all comparisons. Our results provide strong evidence for the potential of host-response-based diagnostics in achieving the WHO goal of ending tuberculosis by 2035, and host-response-based diagnostics should be pursued for clinical implementation.

Project description:BackgroundMultiple blood transcriptional signatures have been proposed for identification of active and incipient tuberculosis. We aimed to compare the performance of systematically identified candidate signatures for incipient tuberculosis and to benchmark these against WHO targets.MethodsWe did a systematic review and individual participant data meta-analysis. We searched Medline and Embase for candidate whole blood mRNA signatures discovered with the primary objective of diagnosis of active or incipient tuberculosis, compared with controls who were healthy or had latent tuberculosis infection. We tested the performance of eligible signatures in whole blood transcriptomic datasets, in which sampling before tuberculosis diagnosis was done and time to disease was available. Culture-confirmed and clinically or radiologically diagnosed pulmonary or extrapulmonary tuberculosis cases were included. Non-progressor (individuals who remained tuberculosis-free during follow-up) samples with less than 6 months of follow-up from the date of sample collection were excluded, as were participants with prevalent tuberculosis and those who received preventive therapy. Scores were calculated for candidate signatures for each participant in the pooled dataset. Receiver operating characteristic curves, sensitivities, and specificities were examined using prespecified intervals to tuberculosis (<3 months, <6 months, <1 year, and <2 years) from sample collection. This study is registered with PROSPERO, number CRD42019135618.ResultsWe tested 17 candidate mRNA signatures in a pooled dataset from four eligible studies comprising 1126 samples. This dataset included 183 samples from 127 incipient tuberculosis cases in South Africa, Ethiopia, The Gambia, and the UK. Eight signatures (comprising 1-25 transcripts) that predominantly reflect interferon and tumour necrosis factor-inducible gene expression, had equivalent diagnostic accuracy for incipient tuberculosis over a 2-year period with areas under the receiver operating characteristic curves ranging from 0·70 (95% CI 0·64-0·76) to 0·77 (0·71-0·82). The sensitivity of all eight signatures declined with increasing disease-free time interval. Using a threshold derived from two SDs above the mean of uninfected controls to prioritise specificity and positive-predictive value, the eight signatures achieved sensitivities of 24·7-39·9% over 24 months and of 47·1-81·0% over 3 months, with corresponding specificities of more than 90%. Based on pre-test probability of 2%, the eight signatures achieved positive-predictive values ranging from 6·8-9·4% over 24 months and 11·2-14·4% over 3 months. When using biomarker thresholds maximising sensitivity and specificity with equal weighting to both, no signature met the minimum WHO target product profile parameters for incipient tuberculosis biomarkers over a 2-year period.InterpretationBlood transcriptional biomarkers reflect short-term risk of tuberculosis and only exceed WHO benchmarks if applied to 3-6-month intervals. Serial testing among carefully selected target groups might be required for optimal implementation of these biomarkers.FundingWellcome Trust and National Institute for Health Research.

Project description:BackgroundA 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.MethodsIn 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.FindingsBetween March 22, 2017, and May 15, 2018, 963 participants were assessed for eligibility and 861 were enrolled. Among 820 participants with valid RISK11 results, eight (1%) had prevalent tuberculosis at baseline: seven (2·5%; 95% CI 1·2-5·0) of 285 RISK11-positive participants and one (0·2%; 0·0-1·1) of 535 RISK11-negative participants. The relative risk (RR) of prevalent tuberculosis was 13·1 times (95% CI 2·1-81·6) greater in RISK11-positive participants than in RISK11-negative participants. RISK11 had a diagnostic area under the receiver operating characteristic curve (AUC) of 88·2% (95% CI 77·6-96·7), and a sensitivity of 87·5% (58·3-100·0) and specificity of 65·8% (62·5-69·0) at a predefined score threshold (60%). Of those with RISK11 results, eight had primary endpoint incident tuberculosis during 15 months of follow-up. Tuberculosis incidence was 2·5 per 100 person-years (95% CI 0·7-4·4) in the RISK11-positive group and 0·2 per 100 person-years (0·0-0·5) in the RISK11-negative group. The probability of primary endpoint incident tuberculosis was greater in the RISK11-positive group than in the RISK11-negative group (cumulative incidence ratio 16·0 [95% CI 2·0-129·5]). RISK11 had a prognostic AUC of 80·0% (95% CI 70·6-86·9), and a sensitivity of 88·6% (43·5-98·7) and a specificity of 68·9% (65·3-72·3) for incident tuberculosis at the 60% threshold.InterpretationRISK11 identified prevalent tuberculosis and predicted risk of progression to incident tuberculosis within 15 months in ambulant people living with HIV. RISK11's performance approached, but did not meet, WHO's target product profile benchmarks for screening and prognostic tests for tuberculosis.FundingBill & Melinda Gates Foundation and the South African Medical Research Council.

Project description:Background: The novel coronavirus, SARS-CoV-2, has increased the burden on healthcare systems already strained by a high incidence of tuberculosis (TB) as co-infection and dual presentation are occurring in syndemic settings. We aimed to understand the interaction between these diseases by profiling COVID-19 gene expression signatures on RNA-sequencing data from TB-infected individuals.Methods: We performed a systematic review and patient-level meta-analysis by querying PubMed and pre-print servers to derive eligible COVID-19 gene expression signatures from human whole blood (WB), PBMCs or BALF studies. A WB influenza dataset served as a control respiratory disease signature. Three large TB RNA-seq datasets, comprising multiple cohorts from the UK and Africa and consisting of TB patients across the disease spectrum, were chosen to profile these signatures. Putative "COVID-19 risk scores" were generated for each sample in the TB datasets using the TBSignatureProfiler package. Risk was stratified by time to TB diagnosis in progressors and contacts of pulmonary and extra-pulmonary TB. An integrative analysis between TB and COVID-19 single-cell RNA-seq data was performed and a population-level meta-analysis was conducted to identify shared gene ontologies between the diseases and their relative enrichment in COVID-19 disease severity states.Results: 35 COVID-19 gene signatures from nine eligible studies comprising 98 samples were profiled on TB RNA-seq data from 1181 samples from 853 individuals. 25 signatures had significantly higher COVID-19 risk in active TB (ATB) compared with latent TB infection (p <0·005), 13 of which were validated in two independent datasets. FCN1 - and SPP1 -expressing macrophages enriched in BALF during severe COVID-19 were identified in circulation during ATB. Shared perturbed ontologies included antigen presentation, epigenetic regulation, platelet activation, and ROS/RNS production were enriched with increasing COVID-19 severity. Finally, we demonstrate that the overlapping transcriptional responses may complicate development of blood-based diagnostic signatures of co-infection.Interpretation: Our results identify shared dysregulation of immune responses in COVID-19 and TB as a dual risk posed by co-infection to COVID-19 severity and TB disease progression. These individuals should be followed up for TB in the months subsequent to SARS-CoV-2 diagnosis.

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Performance of diagnostic and predictive host blood transcriptomic signatures for Tuberculosis disease: A systematic review and meta-analysis.

Publications

Performance of diagnostic and predictive host blood transcriptomic signatures for Tuberculosis disease: A systematic review and meta-analysis.

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