Transcriptomic Profiles of Confirmed Pediatric Tuberculosis Patients and Household Contacts Identifies Active Tuberculosis, Infection, and Treatment Response Among Indian Children

Sex-specific blood-derived RNA biomarkers for childhood tuberculosis

Confirmatory diagnosis of childhood tuberculosis (TB) remains a challenge mainly due to its dependence on sputum samples and the paucibacillary nature of the disease. Thus, only ~ 30% of suspected cases in children are diagnosed and the need for minimally invasive, non-sputum-based biomarkers remains unmet. Understanding host molecular changes by measuring blood-based transcriptomic markers has shown promise as a diagnostic tool for TB. However, the implication of sex contributing to disease heterogeneity and therefore diagnosis remains to be understood. Using publicly available gene expression data (GSE39939, GSE39940; n = 370), we report a sex-specific RNA biomarker signature that could improve the diagnosis of TB disease in children. We found four gene biomarker signatures for male (SLAMF8, GBP2, WARS, and FCGR1C) and female pediatric patients (GBP6, CELSR3, ALDH1A1, and GBP4) from Kenya, South Africa, and Malawi. Both signatures achieved a sensitivity of 85% and a specificity of 70%, which approaches the WHO-recommended target product profile for a triage test. Our gene signatures outperform most other gene signatures reported previously for childhood TB diagnosis.

Classification and characterisation of extracellular vesicles-related tuberculosis subgroups and immune cell profiles

Around the world, tuberculosis (TB) remains one of the most common causes of morbidity and mortality. The molecular mechanism of Mycobacterium tuberculosis (Mtb) infection is still unclear. Extracellular vesicles (EVs) play a key role in the onset and progression of many disease states and can serve as effective biomarkers or therapeutic targets for the identification and treatment of TB patients. We analysed the expression profile to better clarify the EVs characteristics of TB and explored potential diagnostic markers to distinguish TB from healthy control (HC). Twenty EVs-related differentially expressed genes (DEGs) were identified, and 17 EVs-related DEGs were up-regulated and three DEGs were down-regulated in TB samples, which were related to immune cells. Using machine learning, a nine EVs-related gene signature was identified and two EVs-related subclusters were defined. The single-cell RNA sequence (scRNA-seq) analysis further confirmed that these hub genes might play important roles in TB pathogenesis. The nine EVs-related hub genes had excellent diagnostic values and accurately estimated TB progression. TB's high-risk group had significantly enriched immune-related pathways, and there were substantial variations in immunity across different groups. Furthermore, five potential drugs were predicted for TB using CMap database. Based on the EVs-related gene signature, the TB risk model was established through a comprehensive analysis of different EV patterns, which can accurately predict TB. These genes could be used as novel biomarkers to distinguish TB from HC. These findings lay the foundation for further research and design of new therapeutic interventions aimed at treating this deadly infectious disease.

Gene Expression in Cord Blood and Tuberculosis in Early Childhood: A Nested Case-Control Study in a South African Birth Cohort

BACKGROUND

Transcriptomic profiling of adults with tuberculosis (TB) has become increasingly common, predominantly for diagnostic and risk prediction purposes. However, few studies have evaluated signatures in children, particularly in identifying those at risk for developing TB disease. We investigated the relationship between gene expression obtained from umbilical cord blood and both tuberculin skin test conversion and incident TB disease through the first 5 years of life.

METHODS

We conducted a nested case-control study in the Drakenstein Child Health Study, a longitudinal, population-based birth cohort in South Africa. We applied transcriptome-wide screens to umbilical cord blood samples from neonates born to a subset of selected mothers (N = 131). Signatures identifying tuberculin conversion and risk of subsequent TB disease were identified from genome-wide analysis of RNA expression.

RESULTS

Gene expression signatures revealed clear differences predictive of tuberculin conversion (n = 26) and TB disease (n = 10); 114 genes were associated with tuberculin conversion and 30 genes were associated with the progression to TB disease among children with early infection. Coexpression network analysis revealed 6 modules associated with risk of TB infection or disease, including a module associated with neutrophil activation in immune response (P < .0001) and defense response to bacterium (P < .0001).

CONCLUSIONS

These findings suggest multiple detectable differences in gene expression at birth that were associated with risk of TB infection or disease throughout early childhood. Such measures may provide novel insights into TB pathogenesis and susceptibility.

Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV

Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.

Systematic review of diagnostic and prognostic host blood transcriptomic signatures of tuberculosis disease in people living with HIV

Background HIV-associated tuberculosis (TB) has high mortality; however, current triage and prognostic tools offer poor sensitivity and specificity, respectively. We conducted a systematic review of diagnostic and prognostic host-blood transcriptomic signatures of TB in people living with HIV (PLHIV). Methods We systematically searched online databases for studies published in English between 1990-2020. Eligible studies included PLHIV of any age in test or validation cohorts, and used microbiological or composite reference standards for TB diagnosis. Inclusion was not restricted by setting or participant age. Study selection, quality appraisal using the QUADAS-2 tool, and data extraction were conducted independently by two reviewers. Thereafter, narrative synthesis of included studies, and comparison of signatures performance, was performed. Results We screened 1,580 records and included 12 studies evaluating 31 host-blood transcriptomic signatures in 10 test or validation cohorts of PLHIV that differentiated individuals with TB from those with HIV alone, latent Mycobacterium tuberculosis infection, or other diseases (OD). Two (2/10; 20%) cohorts were prospective (29 TB cases; 51 OD) and 8 (80%) case-control (353 TB cases; 606 controls) design. All cohorts (10/10) were recruited in Sub-Saharan Africa and 9/10 (90%) had a high risk of bias. Ten signatures (10/31; 32%) met minimum WHO Target Product Profile (TPP) criteria for TB triage tests. Only one study (1/12; 8%) evaluated prognostic performance of a transcriptomic signature for progression to TB in PLHIV, which did not meet the minimum WHO prognostic TPP. Conclusions Generalisability of reported findings is limited by few studies enrolling PLHIV, limited geographical diversity, and predominantly case-control design, which also introduces spectrum bias. New prospective cohort studies are needed that include PLHIV and are conducted in diverse settings. Further research exploring the effect of HIV clinical, virological, and immunological factors on diagnostic performance is necessary for development and implementation of TB transcriptomic signatures in PLHIV.

Diagnostic biomarkers for active tuberculosis: progress and challenges

Tuberculosis (TB) is a leading cause of morbidity and mortality from a single infectious agent, despite being preventable and curable. Early and accurate diagnosis of active TB is critical to both enhance patient care, improve patient outcomes, and break Mycobacterium tuberculosis (Mtb) transmission cycles. In 2020 an estimated 9.9 million people fell ill from Mtb, but only a little over half (5.8 million) received an active TB diagnosis and treatment. The World Health Organization has proposed target product profiles for biomarker- or biosignature-based diagnostics using point-of-care tests from easily accessible specimens such as urine or blood. Here we review and summarize progress made in the development of pathogen- and host-based biomarkers for active TB diagnosis. We describe several unique patient populations that have posed challenges to development of a universal diagnostic TB biomarker, such as people living with HIV, extrapulmonary TB, and children. We also review additional limitations to widespread validation and utilization of published biomarkers. We conclude with proposed solutions to enhance TB diagnostic biomarker validation and uptake.

Are mRNA based transcriptomic signatures ready for diagnosing tuberculosis in the clinic? - A review of evidence and the technological landscape

Funding

Transcriptomics for child and adolescent tuberculosis

Tuberculosis (TB) in humans is caused by Mycobacterium tuberculosis (Mtb). It is estimated that 70 million children (<15 years) are currently infected with Mtb, with 1.2 million each year progressing to disease. Of these, a quarter die. The risk of progression from Mtb infection to disease and from disease to death is dependent on multiple pathogen and host factors. Age is a central component in all these transitions. The natural history of TB in children and adolescents is different to adults, leading to unique challenges in the development of diagnostics, therapeutics, and vaccines. The quantification of RNA transcripts in specific cells or in the peripheral blood, using high-throughput methods, such as microarray analysis or RNA-Sequencing, can shed light into the host immune response to Mtb during infection and disease, as well as understanding treatment response, disease severity, and vaccination, in a global hypothesis-free manner. Additionally, gene expression profiling can be used for biomarker discovery, to diagnose disease, predict future disease progression and to monitor response to treatment. Here, we review the role of transcriptomics in children and adolescents, focused mainly on work done in blood, to understand disease biology, and to discriminate disease states to assist clinical decision-making. In recent years, studies with a specific pediatric and adolescent focus have identified blood gene expression markers with diagnostic or prognostic potential that meet or exceed the current sensitivity and specificity targets for diagnostic tools. Diagnostic and prognostic gene expression signatures identified through high-throughput methods are currently being translated into diagnostic tests.

Systematic review of host genomic biomarkers of invasive bacterial disease: Distinguishing bacterial from non-bacterial causes of acute febrile illness

Background

Infectious diseases play a significant role in the global burden of disease. The gold standard for the diagnosis of bacterial infection, bacterial culture, can lead to diagnostic delays and inappropriate antibiotic use. The advent of high- throughput technologies has led to the discovery of host-based genomic biomarkers of infection, capable of differentiating bacterial from other causes of infection, but few have achieved validation for use in a clinical setting.

Methods

A systematic review was performed. PubMed/Ovid Medline, Ovid Embase and Scopus databases were searched for relevant studies from inception up to 30/03/2022 with forward and backward citation searching of key references. Studies assessing the diagnostic performance of human host genomic biomarkers of bacterial infection were included. Study selection and assessment of quality were conducted by two independent reviewers. A meta-analysis was undertaken using a diagnostic random-effects model. The review was registered with PROSPERO (ID: CRD42021208462).

Findings

Seventy-two studies evaluating the performance of 116 biomarkers in 16,216 patients were included. Forty-six studies examined TB-specific biomarker performance and twenty-four studies assessed biomarker performance in a paediatric population. The results of pooled sensitivity, specificity, negative and positive likelihood ratio, and diagnostic odds ratio of genomic biomarkers of bacterial infection were 0.80 (95% CI 0.78 to 0.82), 0.86 (95% CI 0.84 to 0.88), 0.18 (95% CI 0.16 to 0.21), 5.5 (95% CI 4.9 to 6.3), 30.1 (95% CI 24 to 37), respectively. Significant between-study heterogeneity (I² 77%) was present.

Interpretation

Host derived genomic biomarkers show significant potential for clinical use as diagnostic tests of bacterial infection however, further validation and attention to test platform is warranted before clinical implementation can be achieved.

Funding

No funding received.

The Kynurenine/Tryptophan Ratio Is a Sensitive Biomarker for the Diagnosis of Pediatric Tuberculosis Among Indian Children

Objectives

Pediatric tuberculosis (TB) remains difficult to diagnose. The plasma kynurenine to tryptophan ratio (K/T ratio) is a potential biomarker for TB diagnosis and treatment response but has not been assessed in children.

Methods

We performed a targeted diagnostic accuracy analysis of four biomarkers: kynurenine abundance, tryptophan abundance, the K/T ratio, and IDO-1 gene expression. Data were obtained from transcriptome and metabolome profiling of children with confirmed tuberculosis and age- and sex-matched uninfected household contacts of pulmonary tuberculosis patients. Each biomarker was assessed as a baseline diagnostic and in response to successful TB treatment.

Results

Despite non-significant between-group differences in unbiased analysis, the K/T ratio achieved an area under the receiver operator characteristic curve (AUC) of 0.667 and 81.5% sensitivity for TB diagnosis. Kynurenine, tryptophan, and IDO-1 demonstrated diagnostic AUCs of 0.667, 0.602, and 0.463, respectively. None of these biomarkers demonstrated high AUCs for treatment response. The AUC of the K/T ratio was lower than biomarkers identified in unbiased analysis, but improved sensitivity over existing commercial assays for pediatric TB diagnosis.

Conclusions

Plasma kynurenine and the K/T ratio may be useful biomarkers for pediatric TB. Ongoing studies in geographically diverse populations will determine optimal use of these biomarkers worldwide.

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

BACKGROUND

The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.

METHODS

In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.

RESULTS

Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.

CONCLUSIONS

Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients

BACKGROUND

The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system.

METHODS

In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings.

RESULTS

Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host.

CONCLUSIONS

Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.

Integration of metabolomics and transcriptomics reveals novel biomarkers in the blood for tuberculosis diagnosis in children

Pediatric tuberculosis (TB) remains a major global health problem. Improved pediatric diagnostics using readily available biosources are urgently needed. We used liquid chromatography-mass spectrometry to analyze plasma metabolite profiles of Indian children with active TB (n = 16) and age- and sex-matched, Mycobacterium tuberculosis-exposed but uninfected household contacts (n = 32). Metabolomic data were integrated with whole blood transcriptomic data for each participant at diagnosis and throughout treatment for drug-susceptible TB. A decision tree algorithm identified 3 metabolites that correctly identified TB status at distinct times during treatment. N-acetylneuraminate achieved an area under the receiver operating characteristic curve (AUC) of 0.66 at diagnosis. Quinolinate achieved an AUC of 0.77 after 1 month of treatment, and pyridoxate achieved an AUC of 0.87 after successful treatment completion. A set of 4 metabolites (gamma-glutamylalanine, gamma-glutamylglycine, glutamine, and pyridoxate) identified treatment response with an AUC of 0.86. Pathway enrichment analyses of these metabolites and corresponding transcriptional data correlated N-acetylneuraminate with immunoregulatory interactions between lymphoid and non-lymphoid cells, and correlated pyridoxate with p53-regulated metabolic genes and mitochondrial translation. Our findings shed new light on metabolic dysregulation in children with TB and pave the way for new diagnostic and treatment response markers in pediatric TB.

Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.