Diagnostic value of blood gene expression signatures in active tuberculosis in Thais: a pilot study

A host blood transcriptional signature differentiates multi-drug/rifampin-resistant tuberculosis (MDR/RR-TB) from drug susceptible tuberculosis: a pilot study

BACKGROUND

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis is one of the top thirteen causes of death worldwide. The major challenge to control TB is the emergence of drug-resistant tuberculosis (DR-TB); specifically, multi-drug resistant TB which are resistant to the most potent drugs; rifampin and isoniazid. Owing to the inconsistencies of the current diagnostic methods, a single test cannot identify the whole spectrum of DR-TB associated mutations. Recently, host blood transcriptomics has gained attention as a promising technique that develops disease-specific RNA signatures/biomarkers. However, studies on host transcriptomics infected with DR-TB is limited. Herein, we intended to identify genes/pathways that are differentially expressed in multi-drug/rifampin resistant TB (MDR/RR-TB) in contrast to drug susceptible TB.

METHOD AND RESULTS

We conducted blood RNA sequencing of 10 pulmonary TB patients (4; drug susceptible and 6; DR-TB) and 55 genes that were differentially expressed in MDR/RR-TB from drug-susceptible/mono-resistant TB were identified. CD300LD, MYL9, VAMP5, CARD17, CLEC2B, GBP6, BATF2, ETV7, IFI27 and FCGR1CP were found to be upregulated in MDR/RR-TB in all comparisons, among which CLEC2B and CD300LD were not previously linked to TB. In comparison pathway analysis, interferon alpha/gamma response was upregulated while Wnt/beta catenin signaling, lysosome, microtubule nucleation and notch signaling were downregulated.

CONCLUSION

Up/down-regulation of immunity related genes/pathways speculate the collective effect of hosts' attempt to fight against continuously multiplying DR-TB bacteria and the bacterial factors to fight against the host defense. The identified genes/pathways could act as MDR/RR-TB biomarkers, hence, further research on their clinical use should be encouraged.

Transcription factor MAFB controls type I and II interferon response-mediated host immunity in Mycobacterium tuberculosis-infected macrophages

MAFB, v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog B, has been identified as a candidate gene for early tuberculosis (TB) onset in Thai and Japanese populations. Here, we investigated the genome-wide transcriptional profiles of MAFB-knockdown (KD) macrophages infected with Mycobacterium tuberculosis (Mtb) to highlight the potential role of MAFB in host immunity against TB. Gene expression analysis revealed impaired type I and type II interferon (IFN) responses and enhanced oxidative phosphorylation in MAFB-KD macrophages infected with Mtb. The expression of inflammatory chemokines, including IFN-γ-inducible genes, was confirmed to be significantly reduced by knockdown of MAFB during Mtb infection. A similar effect of MAFB knockdown on type I and type II IFN responses and oxidative phosphorylation was also observed when Mtb-infected macrophages were activated by IFN-γ. Taken together, our results demonstrate that MAFB is involved in the immune response and metabolism in Mtb-infected macrophages, providing new insight into MAFB as a candidate gene to guide further study to control TB.

Meta-analysis of active tuberculosis gene expression ascertains host directed drug targets

Multi-drug resistant tuberculosis still remains a major public health crisis globally. With the emergence of newer active tuberculosis disease, the requirement of prolonged treatment time and adherence to therapy till its completion necessitates the search of newer therapeutics, targeting human host factors. The current work utilized statistical meta-analysis of human gene transcriptomes of active pulmonary tuberculosis disease obtained from six public datasets. The meta-analysis resulted in the identification of 2038 significantly differentially expressed genes (DEGs) in the active tuberculosis disease. The gene ontology (GO) analysis revealed that these genes were major contributors in immune responses. The pathway enrichment analyses identified from various human canonical pathways are related to other infectious diseases. In addition, the comparison of the DEGs with the tuberculosis genome wide association study (GWAS) datasets revealed the presence of few genetic variants in their proximity. The analysis of protein interaction networks (human and Mycobacterium tuberculosis) and host directed drug-target interaction network led to new candidate drug targets for drug repurposing studies. The current work sheds light on host genes and pathways enriched in active tuberculosis disease and suggest potential drug repurposing targets for host-directed therapies.

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.

Using TBAg/PHA Ratio for Monitoring TB Treatment: A Prospective Multicenter Study

The way to monitor tuberculosis (TB) treatment is extremely lacking in clinical practice. The aim of the study is to assess the role of the TBAg/PHA ratio in the treatment monitoring of TB. TB patients were followed up for 6 months and serial T-SPOT.TB (T-SPOT) assays were performed. In patients with successful treatment outcomes, the ESAT-6 sfc, CFP-10 sfc, and TBAg/PHA ratio all showed a decreased trend after the initiation of treatment. Conversely, PHA sfc showed an increased trend after 2 months of treatment. However, these indicators had moderate performance in distinguishing between before and after 6 months of treatment, and the AUC ranged from 0.702 to 0.839. Notably, the TBAg/PHA ratio in patients without risk factors was of important value in differentiation between before and after treatment. The optimal AUC of TBAg/PHA ratio reached up to 0.890. Patients with unsuccessful treatment outcomes showed persistently high levels of TBAg/PHA ratio. The TBAg/PHA ratio in patients after 6 months of treatment showed a certain potential in distinguishing between patients with successful and unsuccessful treatment outcomes. A further calculation of the TBAg/PHA ratio in T-SPOT assay has potential value in the treatment monitoring of TB, but further confirmation is needed.

Latent Tuberculosis Infection Diagnosis among Household Contacts in a High Tuberculosis-Burden Area: a Comparison between Transcript Signature and Interferon Gamma Release Assay

Diagnosis of latent tuberculosis infection (LTBI) using biomarkers in order to identify the risk of progressing to active TB and therefore predicting a preventive therapy has been the main bottleneck in eradication of tuberculosis. We compared two assays for the diagnosis of LTBI: transcript signatures and interferon gamma release assay (IGRA), among household contacts (HHCs) in a high tuberculosis-burden population. HHCs of active TB cases were recruited for our study; these were confirmed to be clinically negative for active TB disease. Eighty HHCs were screened by IGRA using QuantiFERON-TB Gold Plus (QFT-Plus) to identify LTBI and uninfected cohorts; further, quantitative levels of transcript for selected six genes (TNFRSF10C, ASUN, NEMF, FCGR1B, GBP1, and GBP5) were determined. Machine learning (ML) was used to construct models of different gene combinations, with a view to identify hidden but significant underlying patterns of their transcript levels. Forty-three HHCs were found to be IGRA positive (LTBI) and thirty-seven were IGRA negative (uninfected). FCGR1B, GBP1, and GBP5 transcripts differentiated LTBI from uninfected among HHCs using Livak method. ML and ROC (Receiver Operator Characteristic) analysis validated this transcript signature to have a specificity of 72.7%. In this study, we compared a quantitative transcript signature with IGRA to assess the diagnostic ability of the two, for detection of LTBI cases among HHCs of a high-TB burden population; we concluded that a three gene (FCGR1B, GBP1, and GBP5) transcript signature can be used as a biomarker for rapid screening.

IMPORTANCE The study compares potential of transcript signature and IGRA to diagnose LTBI. It is first of its kind study to screen household contacts (HHCs) in high TB burden area of India. A transcript signature (FCGR1B, GBP1, & GBP5) is identified as potential biomarker for LTBI. These results can lead to development of point-of-care (POC) like device for LTBI screening in a high TB burdened area.

Histone acetylome-wide associations in immune cells from individuals with active Mycobacterium tuberculosis infection

Host cell chromatin changes are thought to play an important role in the pathogenesis of infectious diseases. Here we describe a histone acetylome-wide association study (HAWAS) of an infectious disease, on the basis of genome-wide H3K27 acetylation profiling of peripheral blood granulocytes and monocytes from persons with active Mycobacterium tuberculosis (Mtb) infection and healthy controls. We detected >2,000 differentially acetylated loci in either cell type in a Singapore Chinese discovery cohort (n = 46), which were validated in a subsequent multi-ethnic Singapore cohort (n = 29), as well as a longitudinal cohort from South Africa (n = 26), thus demonstrating that HAWAS can be independently corroborated. Acetylation changes were correlated with differential gene expression. Differential acetylation was enriched near potassium channel genes, including KCNJ15, which modulates apoptosis and promotes Mtb clearance in vitro. We performed histone acetylation quantitative trait locus (haQTL) analysis on the dataset and identified 69 candidate causal variants for immune phenotypes among granulocyte haQTLs and 83 among monocyte haQTLs. Our study provides proof-of-principle for HAWAS to infer mechanisms of host response to pathogens.

Genome-wide histone acetylation profiling in cohorts of patients with active and latent tuberculosis reveals acetylation changes in host immune cells modulating potassium channel expression and apoptosis response.

Multi-country evaluation of RISK6, a 6-gene blood transcriptomic signature, for tuberculosis diagnosis and treatment monitoring

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% sensitivity and 87.8% specificity, thus achieving the minimal WHO target product profile for a non-sputum-based TB screening test. Besides, RISK6 yielded an AUC of 0.93 (95% CI 0.85-1) with 90.9% sensitivity and 88.5% specificity for discriminating ATB from LTBI. Moreover, RISK6 showed higher performance (AUC 0.90, 95% CI 0.85-0.94) than IGRA-rmsHBHA (AUC 0.75, 95% CI 0.69-0.82) to differentiate TB infection stages. Finally, RISK6 signature scores significantly decreased after 2 months of TB treatment and continued to decrease gradually until the end of treatment reaching scores obtained in HD. We confirmed the performance of RISK6 signature as a triage TB test and its utility for treatment monitoring.

Role of the F-BAR Family Member PSTPIP2 in Autoinflammatory Diseases

Proline-serine-threonine-phosphatase-interacting protein 2 (PSTPIP2) belongs to the Fes/CIP4 homology-Bin/Amphiphysin/Rvs (F-BAR) domain family. It exhibits lipid-binding, membrane deformation, and F-actin binding activity, suggesting broader roles at the membrane–cytoskeleton interface. PSTPIP2 is known to participate in macrophage activation, neutrophil migration, cytokine production, and osteoclast differentiation. In recent years, it has been observed to play important roles in innate immune diseases and autoinflammatory diseases (AIDs). Current research indicates that the protein tyrosine phosphatase PTP-PEST, Src homology domain-containing inositol 5’-phosphatase 1 (SHIP1), and C‐terminal Src kinase (CSK) can bind to PSTPIP2 and inhibit the development of AIDs. However, the mechanisms underlying the function of PSTPIP2 have not been fully elucidated. This article reviews the research progress and mechanisms of PSTPIP2 in AIDs. PSTPIP2 also provides a new therapeutic target for the treatment of AIDs.

Integrative genomics of the mammalian alveolar macrophage response to intracellular mycobacteria

Background

Bovine TB (bTB), caused by infection with Mycobacterium bovis, is a major endemic disease affecting global cattle production. The key innate immune cell that first encounters the pathogen is the alveolar macrophage, previously shown to be substantially reprogrammed during intracellular infection by the pathogen. Here we use differential expression, and correlation- and interaction-based network approaches to analyse the host response to infection with M. bovis at the transcriptome level to identify core infection response pathways and gene modules. These outputs were then integrated with genome-wide association study (GWAS) data sets to enhance detection of genomic variants for susceptibility/resistance to M. bovis infection.

Results

The host gene expression data consisted of RNA-seq data from bovine alveolar macrophages (bAM) infected with M. bovis at 24 and 48 h post-infection (hpi) compared to non-infected control bAM. These RNA-seq data were analysed using three distinct computational pipelines to produce six separate gene sets: 1) DE genes filtered using stringent fold-change and P-value thresholds (DEG-24: 378 genes, DEG-48: 390 genes); 2) genes obtained from expression correlation networks (CON-24: 460 genes, CON-48: 416 genes); and 3) genes obtained from differential expression networks (DEN-24: 339 genes, DEN-48: 495 genes). These six gene sets were integrated with three bTB breed GWAS data sets by employing a new genomics data integration tool—gwinteR. Using GWAS summary statistics, this methodology enabled detection of 36, 102 and 921 prioritised SNPs for Charolais, Limousin and Holstein-Friesian, respectively.

Conclusions

The results from the three parallel analyses showed that the three computational approaches could identify genes significantly enriched for SNPs associated with susceptibility/resistance to M. bovis infection. Results indicate distinct and significant overlap in SNP discovery, demonstrating that network-based integration of biologically relevant transcriptomics data can leverage substantial additional information from GWAS data sets. These analyses also demonstrated significant differences among breeds, with the Holstein-Friesian breed GWAS proving most useful for prioritising SNPS through data integration. Because the functional genomics data were generated using bAM from this population, this suggests that the genomic architecture of bTB resilience traits may be more breed-specific than previously assumed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07643-w.

Silencing of LINC00284 inhibits cell proliferation and migration in oral squamous cell carcinoma by the miR-211-3p/MAFG axis and FUS/KAZN axis

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies worldwide. Emerging evidence has suggested that long noncoding RNAs (lncRNAs) play vital roles in various biological processes of cancers, such as cell proliferation, migration, invasion, and apoptosis. As reported previously, long intergenic non-protein coding RNA 284 (LINC00284) is an important regulator in multiple cancers. However, the biological role, as well as regulatory mechanism of LINC00284 in OSCC, has not been investigated. In our study, RT-qPCR results indicated that LINC00284 was significantly upregulated in OSCC tissues and cells. Moreover, loss-of-function experiments demonstrated that LINC00284 downregulation suppressed cell proliferation and migration and facilitated cell apoptosis. Mechanistically, we found that LINC00284 sponged microRNA 211-3p (miR-211-3p) to upregulate MAF bZIP transcription factor G (MAFG) expression in OSCC cells. Additionally, LINC00284 interacted with FUS protein to increase KAZN mRNA stability. Functional assays showed that either MAFG or KAZN overexpression promoted the malignant behaviors of OSCC cells. Through a series of rescue assays, we found that the inhibitory effect of silencing LINC00284 on OSCC cells can be reversed by upregulated MAFG and KAZN. Overall, silencing LINC00284 inhibits the malignant characteristics of OSCC cells by downregulating MAFG and inhibiting the binding of FUS to KAZN mRNA.

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

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.

A transcriptional blood signature distinguishes early tuberculosis disease from latent tuberculosis infection and uninfected individuals in a Vietnamese cohort

OBJECTIVES

Global tuberculosis (TB) control is restricted by the failure to detect an estimated 3.3 million TB cases annually. In the majority of TB endemic settings, sputum smear microscopy is used to diagnose TB, but this test is insensitive for TB in its early stages. The objective of this study is to establish a concise gene signature that discriminates between individuals with early TB disease, latent TB infection (LTBI) and those without infection.

METHODS

This is a case control study nested within a cluster-randomised trial of population screening for active TB using Xpert MTB/RIF. Whole blood samples from 303 participants with active TB (97), LTBI (92) and uninfected individuals (114) were subject to transcriptomic analysis of selected target genes based on a systematic review of previous studies.

RESULTS

Analysis of 82 genes identified a pattern of differentially expressed genes in TB disease. A seven gene signature was identified that distinguished between TB disease and no TB disease with an AUC of 0.86 (95% CI: 0.80-0.91), and between TB disease from LTBI with an AUC of 0.88 (95% CI: 0.82-0.93).

CONCLUSION

This gene signature accurately distinguishes early TB disease from those without TB disease or infection, in the context of community-wide TB screening. It could be used as a non-sputum based screening tool or triage test to detect prevalent cases of TB in the community.

Global Transcriptome Analysis Identifies a Diagnostic Signature for Early Disseminated Lyme Disease and Its Resolution

A bioinformatics approach was employed to identify transcriptome alterations in the peripheral blood mononuclear cells of well-characterized human subjects who were diagnosed with early disseminated Lyme disease (LD) based on stringent microbiological and clinical criteria. Transcriptomes were assessed at the time of presentation and also at approximately 1 month (early convalescence) and 6 months (late convalescence) after initiation of an appropriate antibiotic regimen. Comparative transcriptomics identified 335 transcripts, representing 233 unique genes, with significant alterations of at least 2-fold expression in acute- or convalescent-phase blood samples from LD subjects relative to healthy donors. Acute-phase blood samples from LD subjects had the largest number of differentially expressed transcripts (187 induced, 54 repressed). This transcriptional profile, which was dominated by interferon-regulated genes, was sustained during early convalescence. 6 months after antibiotic treatment the transcriptome of LD subjects was indistinguishable from that of healthy controls based on two separate methods of analysis. Return of the LD expression profile to levels found in control subjects was concordant with disease outcome; 82% of subjects with LD experienced at least one symptom at the baseline visit compared to 43% at the early convalescence time point and only a single patient (9%) at the 6-month convalescence time point. Using the random forest machine learning algorithm, we developed an efficient computational framework to identify sets of 20 classifier genes that discriminated LD from other bacterial and viral infections. These novel LD biomarkers not only differentiated subjects with acute disseminated LD from healthy controls with 96% accuracy but also distinguished between subjects with acute and resolved (late convalescent) disease with 97% accuracy.IMPORTANCE Lyme disease (LD), caused by Borrelia burgdorferi, is the most common tick-borne infectious disease in the United States. We examined gene expression patterns in the blood of individuals with early disseminated LD at the time of diagnosis (acute) and also at approximately 1 month and 6 months following antibiotic treatment. A distinct acute LD profile was observed that was sustained during early convalescence (1 month) but returned to control levels 6 months after treatment. Using a computer learning algorithm, we identified sets of 20 classifier genes that discriminate LD from other bacterial and viral infections. In addition, these novel LD biomarkers are highly accurate in distinguishing patients with acute LD from healthy subjects and in discriminating between individuals with active and resolved infection. This computational approach offers the potential for more accurate diagnosis of early disseminated Lyme disease. It may also allow improved monitoring of treatment efficacy and disease resolution.

A Common Variant of ASAP1 Is Associated with Tuberculosis Susceptibility in the Han Chinese Population

Background

ASAP1 (also known as AMAP1 or DDEF1) encodes an Arf GTPase-activating protein (Arf GAP), a multifunctional scaffold protein that induces hydrolysis of GTP bound to the ADP-ribosylation factor (Arf) family GTP-binding proteins. Reduction of ASAP1 expression in vitro was related to suppression of cell migration and invasiveness. The genetic variant rs4733781 of the ASAP1 gene was revealed as a significant locus for tuberculosis (TB) susceptibility, but the results still need to be validated.

Methods

Blood samples from a total of 1914 active TB and healthy controls (HC) were collected to evaluate rs4733781 and the risk of TB. Meanwhile, a total of 48 noninfected HC, latent TB-infected (LTBI) controls, and active TB were collected to assay ASAP1 expression difference among the three groups. The QuantiFERON-TB Gold In-Tube was adopted to identify noninfected HC and LTBI.

Results

The genetic variant of rs4733781 was found to be significantly associated with TB, and the A allele of rs4733781 (C>A) was 0.38 and 0.43 among TB cases and HC, respectively (P = 0.0035). Meanwhile, the peripheral blood monocyte RNA fold changes for the ASAP1 gene among the 16 HC, 16 LTBI, and 16 active TB were 1.088 ± 0.4919, 2.237 ± 0.6505, and 10.12 ± 10.98 (F = 9.559, P = 0.0003), respectively, and the expression of ASAP1 was increased by 2.06-fold (P < 0.0001) and 9.30-fold (P < 0.0052) for LTBI and active TB, when compared to the HC.

Conclusions

Our data indicated that the A allele of rs4733781 for the ASAP1 gene was in association with a decreased risk of TB. But not only that, the overexpression of the ASAP1 gene among LTBI and TB was related to the progression of TB, which further implies that the expression of ASAP1 would be a potential biomarker for LTBI and TB diagnoses.

Incipient and Subclinical Tuberculosis: a Clinical Review of Early Stages and Progression of Infection

Tuberculosis (TB) is the leading infectious cause of mortality worldwide, due in part to a limited understanding of its clinical pathogenic spectrum of infection and disease. Historically, scientific research, diagnostic testing, and drug treatment have focused on addressing one of two disease states: latent TB infection or active TB disease. Recent research has clearly demonstrated that human TB infection, from latent infection to active disease, exists within a continuous spectrum of metabolic bacterial activity and antagonistic immunological responses. This revised understanding leads us to propose two additional clinical states: incipient and subclinical TB. The recognition of incipient and subclinical TB, which helps divide latent and active TB along the clinical disease spectrum, provides opportunities for the development of diagnostic and therapeutic interventions to prevent progression to active TB disease and transmission of TB bacilli. In this report, we review the current understanding of the pathogenesis, immunology, clinical epidemiology, diagnosis, treatment, and prevention of both incipient and subclinical TB, two emerging clinical states of an ancient bacterium.

The role of human host genetics in tuberculosis resistance

INTRODUCTION

Tuberculosis (TB) remains a public health problem: the latest estimate of new incident cases per year is a staggering 10.4 million. Despite this overwhelming number, the majority of the immunocompetent population can control infection with Mycobacterium tuberculosis. The human genome underlies the immune response and contributes to the outcome of TB infection. Areas covered: Investigations of TB resistance in the general population have closely mirrored those of other infectious diseases and initially involved epidemiological observations. Linkage and association studies, including studies of VDR, SLC11A1 and HLA-DRB1 followed. Genome-wide association studies of common variants, not necessarily sufficient for disease, became possible after technological advancements. Other approaches involved the identification of those individuals with rare disease-causing mutations that strongly predispose to TB, epistasis and the role of ethnicity in disease. Despite these efforts, infection outcome, on an individual basis, cannot yet be predicted. Expert commentary: The early identification of future disease progressors is necessary to stem the TB epidemic. Human genetics may contribute to this endeavour and could in future suggest pathways to target for disease prevention. This will however require concerted efforts to establish large, well-phenotyped cohorts from different ethnicities, improved genomic resources and a better understanding of the human genome architecture.

Construction and analysis of the transcription factor-microRNA co-regulatory network response to Mycobacterium tuberculosis: a view from the blood

Mycobacterium tuberculosis (Mtb) infection has been regional outbreak, recently. The traditional focus on the patterns of "reductionism" which was associated with single molecular changes has been unable to meet the demand of early diagnosis and clinical application when current tuberculosis infection happened. In this study, we employed a systems biology approach to collect large microarray data sets including mRNAs and microRNAs (miRNAs) to identify the differentially expressed mRNAs and miRNAs in the whole blood of TB patients. The aim was to identify key genes associated with the immune response in the pathogenic process of tuberculosis by analyzing the co-regulatory network that was consisted of transcription factors and miRNAs as well as their target genes. The network along with their co-regulatory genes was analyzed utilizing Transcriptional Regulatory Element Database (TRED) and Database for Annotation, Visualization and Integrated Discovery (DAVID). We got 21 (19 up-regulated and 2 down-regulated) differentially expressed genes that were co-regulated by transcription factors and miRNAs. KEGG pathway enrichment analysis showed that the 21 differentially expressed genes were predominantly involved in Tuberculosis signaling pathway, which may play a major role in tuberculosis biological process. Quantitative real-time PCR was performed to verify the over expression of co-regulatory genes (FCGR1A and CEBPB). The genetic expression was correlated with clinicopathological characteristics in TB patients and inferences drawn. Our results suggest the TF-miRNA gene co-regulatory network may help us further understand the molecular mechanism of immune response to tuberculosis and provide us a new angle of future biomarker and therapeutic targets.

Concise gene signature for point-of-care classification of tuberculosis

There is an urgent need for new tools to combat the ongoing tuberculosis (TB) pandemic. Gene expression profiles based on blood signatures have proved useful in identifying genes that enable classification of TB patients, but have thus far been complex. Using real‐time PCR analysis, we evaluated the expression profiles from a large panel of genes in TB patients and healthy individuals in an Indian cohort. Classification models were built and validated for their capacity to discriminate samples from TB patients and controls within this cohort and on external independent gene expression datasets. A combination of only four genes distinguished TB patients from healthy individuals in both cross‐validations and on separate validation datasets with very high accuracy. An external validation on two distinct cohorts using a real‐time PCR setting confirmed the predictive power of this 4‐gene tool reaching sensitivity scores of 88% with a specificity of around 75%. Moreover, this gene signature demonstrated good classification power in HIV⁺ populations and also between TB and several other pulmonary diseases. Here we present proof of concept that our 4‐gene signature and the top classifier genes from our models provide excellent candidates for the development of molecular point‐of‐care TB diagnosis in endemic areas.

A rare variant at 11p13 is associated with tuberculosis susceptibility in the Han Chinese population

Genome-wide association studies (GWASs) have yet to be conducted for tuberculosis (TB) susceptibility in China. Two previously identified single nucleotide polymorphisms (SNPs) from tuberculosis GWASs, rs2057178 and rs4331426, were evaluated for TB predisposition. The associations between SNPs and gene expression levels were analyzed using the genomic data and corresponding whole-genome expression of the Han Chinese in Beijing, China. Genotyping was successfully completed for 763 pulmonary TB patients and 763 healthy controls. The T allele of the rare variant rs2057178 was significantly associated with TB predisposition (χ² = 14.07, P = 0.0002). Meanwhile, the CT genotype of rs2057178 was associated with a decreased risk of TB (adjusted OR = 0.52, 95% CI, 0.34–0.78). The CT genotype of rs2057178 was also associated with decreased expression levels of infection-related gene, suppressor of cytokine signaling 2 (SOCS2), and increased expression levels of v-maf avian musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB). No gene expression levels were found to be associated with the genotype of rs4331426. We found that the rare variant rs2057178 was significantly associated with TB in the Han Chinese population. Moreover, the expression levels of MAFB and SOCS2 correlated with rs2057178 and might be potential candidates for assessing TB susceptibility.

Blood Transcriptional Biomarkers for Active Tuberculosis among Patients in the United States: a Case-Control Study with Systematic Cross-Classifier Evaluation

Blood transcriptional signatures are promising for tuberculosis (TB) diagnosis but have not been evaluated among U.S.

PATIENTS

To be used clinically, transcriptional classifiers need reproducible accuracy in diverse populations that vary in genetic composition, disease spectrum and severity, and comorbidities. In a prospective case-control study, we identified novel transcriptional classifiers for active TB among U.S. patients and systematically compared their accuracy to classifiers from published studies. Blood samples from HIV-uninfected U.S. adults with active TB, pneumonia, or latent TB infection underwent whole-transcriptome microarray. We used support vector machines to classify disease state based on transcriptional patterns. We externally validated our classifiers using data from sub-Saharan African cohorts and evaluated previously published transcriptional classifiers in our population. Our classifier distinguishing active TB from pneumonia had an area under the concentration-time curve (AUC) of 96.5% (95.4% to 97.6%) among U.S. patients, but the AUC was lower (90.6% [89.6% to 91.7%]) in HIV-uninfected Sub-Saharan Africans. Previously published comparable classifiers had AUC values of 90.0% (87.7% to 92.3%) and 82.9% (80.8% to 85.1%) when tested in U.S.

PATIENTS

Our classifier distinguishing active TB from latent TB had AUC values of 95.9% (95.2% to 96.6%) among U.S. patients and 95.3% (94.7% to 96.0%) among Sub-Saharan Africans. Previously published comparable classifiers had AUC values of 98.0% (97.4% to 98.7%) and 94.8% (92.9% to 96.8%) when tested in U.S.

PATIENTS

Blood transcriptional classifiers accurately detected active TB among U.S. adults. The accuracy of classifiers for active TB versus that of other diseases decreased when tested in new populations with different disease controls, suggesting additional studies are required to enhance generalizability. Classifiers that distinguish active TB from latent TB are accurate and generalizable across populations and can be explored as screening assays.