Common patterns and disease-related signatures in tuberculosis and sarcoidosis

Innovative electrochemical biosensors for tuberculosis detection

Tuberculosis (TB) continues to pose a significant global health threat, highlighting the urgent need for the development of rapid, precise, and accessible diagnostic tools to effectively manage its transmission. Conventional diagnostic techniques, such as sputum microscopy and culture-based assays, face several drawbacks, including lengthy processing times, limited sensitivity, and the requirement for specialized laboratory facilities. In this landscape, electrochemical biosensors have emerged as promising alternatives, offering improved sensitivity, specificity, and rapid detection capabilities. This review presents a thorough overview of recent advancements in the development and application of innovative electrochemical biosensors for TB detection. It explores the integration of nanomaterials such as graphene, gold nanoparticles, and carbon nanotubes, focusing on their contributions to enhanced sensor performance in terms of signal amplification and biorecognition efficacy. By synthesizing current research and technological developments, this review emphasizes the considerable potential of electrochemical biosensors to transform TB diagnostics, ultimately assisting in better disease management and control strategies worldwide.

Comparison of 18F-FDG-PET/CT scans in patients diagnosed with sarcoidosis and tuberculosis

Positron emission tomography/computed tomography (PET/CT) is widely used to differentiate benign and malignant lesions. However, increased fluorodeoxyglucose (FDG) uptake may occur under certain benign conditions, leading to potential false positives in malignancy assessments. Tuberculosis and sarcoidosis are 2 conditions that can exhibit FDG uptake, presenting with both lymph node and extrathoracic involvement, alongside pulmonary manifestations. This study aimed to explore the utility of PET/CT in distinguishing between thoracic and extrathoracic involvement in patients with sarcoidosis and tuberculosis. A retrospective analysis was conducted on patients diagnosed with sarcoidosis or tuberculosis, either pathologically or microbiologically, who underwent 18F-FDG-PET/CT as part of their diagnostic process. This study evaluated demographic data, PET/CT findings, involvement sites, and maximum standardized uptake values (SUVmax) in patients with tuberculosis and sarcoidosis. PET/CT images of 62 patients (44 with tuberculosis and 18 with sarcoidosis) were analyzed. The median patient age was 55 years. Lymph node involvement in the cervical, abdominal, retro-pancreatic, inguinal, and extrathoracic regions was significantly more prevalent in patients with sarcoidosis than in those with tuberculosis (50% vs 20.5%, P = .0031; 27.8% vs 4.5%, P = .018; 22.2% vs 0%, P = .005; 27.8% vs 6.8%, P = .039; and 66.7% vs 27.3%, P = .009, respectively). No statistically significant difference was found in SUV values between patients with tuberculosis and those with sarcoidosis with regard to mediastinal lymph node, extrathoracic lymph node, lung, and bone PET/CT involvement. In conclusion, 18F-FDG-PET/CT imaging does not appear to be a reliable method for differentiating sarcoidosis and tuberculosis from malignant lesions, as it is not feasible to distinguish between sarcoidosis and tuberculosis solely based on 18F-FDG-PET/CT SUVmax values. Nevertheless, the increased prevalence of extrathoracic lymph node involvement in sarcoidosis compared to tuberculosis may offer valuable insights for clinicians in differential diagnosis.

Harnessing miRNAs: A Novel Approach to Diagnosis and Treatment of Tuberculosis

Mycobacterium tuberculosis (Mtb) complex, responsible for tuberculosis (TB) infection, continues to be a predominant global cause of mortality due to intricate host-pathogen interactions that affect disease progression. MicroRNAs (miRNAs), essential posttranscriptional regulators, have become pivotal modulators of these relationships. Recent findings indicate that miRNAs actively regulate immunological responses to Mtb complex by modulating autophagy, apoptosis, and immune cell activities. This has resulted in increased interest in miRNAs as prospective diagnostic indicators for TB, especially in differentiating active infection from latent or inactive stages. Variations in miRNA expression during Mtb infection indicate disease progression and offer insights into the immune response. Furthermore, miRNAs present potential as therapeutic targets in host-directed therapy (HDT) techniques for TB infection. This work examines the function of miRNAs in TB pathogenesis, with the objective of identifying particular miRNAs that regulate the immune response to the Mtb complex, evaluating their diagnostic value and exploring their therapeutic implications in host-directed therapy for TB infection. The objective is to enhance comprehension of how miRNAs can facilitate improved diagnosis and treatment of TB.

Chronic Sarcoidosis: Diagnostic Difficulties and Search for New Criteria of Inflammatory Activity (A Case Report and Literature Review)

Sarcoidosis is a systemic inflammatory disease with an unknown etiology and a wide range of clinical manifestations. The incidence of sarcoidosis ranges from approximately 1 to 15 cases per 100,000 individuals per year worldwide. The significant variability in clinical presentations and target organs, as well as concomitant diseases, greatly complicates diagnosis. We analyzed articles in PubMed, Scopus, Cochrane Library, and Embase, where databases were searched using the keywords "chronic sarcoidosis", "diagnosis of sarcoidosis", "course of sarcoidosis", "pulmonary sarcoidosis", "cardiac sarcoidosis", "skin sarcoidosis", "neurosarcoidosis", "ocular sarcoidosis", and "autoimmune inflammation". Studies on the course and diagnosis of sarcoidosis with a deep search of ten years were included. In this review, we present an analysis of publications on the course and diagnosis of chronic sarcoidosis, as well as a clinical case. We have noted that the diagnosis of chronic sarcoidosis is particularly difficult due to the lack of specific biomarkers or their combination. The development and introduction of new diagnostic criteria for this disease will contribute to increasing the level of efficiency, not only of the diagnostic complex, but also the prognosis of the development and course of the pathological process. Conclusion: For the most accurate diagnosis and determination of prognosis, the existence of a single immunological or imaging marker with sufficient sensitivity and specificity is necessary.

Effects of Azithromycin on Blood Inflammatory Gene Expression and Cytokine Production in Sarcoidosis

INTRODUCTION

In sarcoidosis granulomas, monocyte-derived macrophages are activated by pro-inflammatory cytokines including TNF and IL-6. Current drug treatment for sarcoidosis aims to suppress inflammation but disabling side effects can ensue. The macrolide azithromycin may be anti-inflammatory. We aimed to determine whether treatment with azithromycin affects blood inflammatory gene expression and monocyte functions in sarcoidosis.

METHODS

Blood samples were collected from patients with chronic pulmonary sarcoidosis enrolled in a single arm, open label clinical trial who received oral azithromycin 250 mg once daily for 3 months. Whole blood inflammatory gene expression with or without LPS stimulation was measured using a 770-mRNA panel. Phenotypic analysis and cytokine production were conducted by flow cytometry and ELISA after 24h stimulation with growth factors and TLR ligands. mTOR activity was assessed by measuring phosphorylated S6RP.

RESULTS

Differential gene expression analysis indicated a state of heightened myeloid cell activation in sarcoidosis. Compared with controls, sarcoidosis patients showed increased LPS responses for several cytokines and chemokines. Treatment with azithromycin had minimal effect on blood gene expression overall, but supervised clustering analysis identified several chemokine genes that were upregulated. At the protein level, azithromycin treatment increased LPS-stimulated TNF and unstimulated IL-8 production. No other cytokines showed significant changes following azithromycin. Blood neutrophil counts fell during azithromycin treatment whereas mononuclear cells remained stable. Azithromycin had no detectable effects on mTOR activity or activation markers.

CONCLUSION

Blood myeloid cells are activated in sarcoidosis, but azithromycin therapy did not suppress inflammatory gene expression or cytokine production in blood.

TRIAL REGISTRATION

EudraCT 2019-000580-24 (17 May 2019).

Discovery of Two Novel Immunoepitopes and Development of a Peptide-based Sarcoidosis Immunoassay

Rationale: Sarcoidosis is a systemic granulomatous disorder associated with hypergammaglobulinemia and the presence of autoantibodies. The specific antigens initiating granulomatous inflammation in sarcoidosis are unknown, and there is no specific test available to diagnose sarcoidosis. To discover novel sarcoidosis antigens, we developed a high-throughput T7 phage display library derived from the sarcoidosis cDNA and identified numerous clones differentiating sarcoidosis from other respiratory diseases. After clone sequencing and a homology search, we identified two epitopes (cofilin μ and chain A) that specifically bind to serum IgGs of patients with sarcoidosis. Objectives: To develop and validate an epitope-specific IgG-based immunoassay specific for sarcoidosis. Methods: We chemically synthesized both immunoepitopes (cofilin μ and chain A) and generated rabbit polyclonal antibodies against both neoantigens. After extensive standardization, we developed a direct peptide ELISA and measured epitope-specific IgG in the sera of 386 subjects, including healthy control subjects (n = 100), three sarcoidosis cohorts (n = 186), pulmonary tuberculosis (n = 70), and lung cancer (n = 30). Measurements and Main Results: To develop a model to classify sarcoidosis distinctly from other groups, data were analyzed using fivefold cross-validation when adjusting for confounders. The cofilin μ IgG model yielded a mean sensitivity, specificity, and positive and negative predictive value of 0.97, 0.9, 0.9, and 0.96, respectively. Those same measures for chain A IgG antibody were 0.9, 0.83, 0.84, and 0.9, respectively. Combining both biomarkers improved the area under the curve, sensitivity, specificity, and positive and negative predictive value. Conclusions: These results provide a novel immunoassay for sarcoidosis. The discovery of two neoantigens facilitates the development of biospecific drug discovery and the sarcoidosis-specific model.

Increased serum interferon activity in sarcoidosis compared to that in tuberculosis: Implication for diagnosis?

Objectives

In this study, we measured serum interferon (IFN) levels and activity in patients with sarcoidosis and tuberculosis (TB) with and without uveitis. We aimed to understand the role of IFN in the pathophysiology of both conditions and explore its potential as a discriminating marker for these clinically similar diseases.

Methods

Sera from an Indonesian TB and a Dutch sarcoidosis cohort were used in the analysis. IFNα2 and IFNγ concentrations were measured using Simoa® and Luminex assays, respectively. Serum IFN activity was assessed by incubating THP-1 cells with patient serum and measuring IFN-stimulated gene transcription using qPCR. Anti-IFNα2 and IFNγ autoantibodies were detected via Luminex assay and tested for neutralizing capacity using a flow cytometry-based signal transducer and activator of transcription (STAT) 1 phosphorylation inhibition assay.

Results

IFNα2 was detected in 74 % and 64 % of patients with sarcoidosis and pulmonary TB, respectively, while IFNγ was found in 78 % and 23 % of patients with sarcoidosis and TB, respectively. For uveitis cases specifically, IFNα2 was detected in 85 % of sarcoid uveitis (SU) and 33 % of tubercular uveitis (TBU) cases. Similarly, IFNγ was detected in 69 % of SU and 17 % of TBU cases. IFNγ serum concentrations were higher in sarcoidosis than that in TB patients (p < 0.0001). Focusing on patients with uveitis, SU showed increased IFNα2 (p = 0.004) and IFNγ (p < 0.002) serum concentrations compared to that in TBU. Notably, TBU displayed significantly reduced IFNα2 concentrations compared to that in healthy controls (p = 0.006). These results align with the increased interferon stimulated gene (ISG) transcriptional upregulation observed in THP-1 cells stimulated with serum from patients with sarcoidosis. Elevated levels of non-neutralizing anti-IFN autoantibodies were observed in patients with TB; however, these levels were similar to those observed in geographically matched healthy Indonesian controls.

Conclusion

Our results suggest decreased serum levels and activity of type I and II IFN in TB compared to those in sarcoidosis. This is indicative of distinct pathophysiological processes in these highly clinically similar diseases. We propose that the assessment of serum IFN levels and IFN activity has the potential to distinguish between sarcoidosis/SU and TB/TBU.

Transcriptomics-based anti-tuberculous mechanism of traditional Chinese polyherbal preparation NiuBeiXiaoHe intermediates

Background

Integrated traditional Chinese medicine and biomedicine is an effective method to treat tuberculosis (TB). In our previous research, traditional Chinese medicine preparation NiuBeiXiaoHe (NBXH) achieved obvious anti-TB effects in animal experiments and clinical practice. However, the action mechanism of NBXH has not been elucidated.

Method

Peripheral blood mononuclear cells (PBMCs) were collected to extract mRNA and differentially expressed (DE) genes were obtained using gene microarray technology. Finally, GEO databases and RT-qPCR were used to verify the results of expression profile.

Result

After MTB infection, most upregulated DE genes in mice were immune-related genes, including cxcl9, camp, cfb, c4b, serpina3g, and ngp. Downregulated DE genes included lrrc74b, sult1d1, cxxc4, and grip2. After treatment with NBXH, especially high-dose NBXH, the abnormal gene expression was significantly corrected. Some DE genes have been confirmed in multiple GEO datasets or in pulmonary TB patients through RT-qPCR.

Conclusion

MTB infection led to extensive changes in host gene expression and mainly caused the host's anti-TB immune responses. The treatment using high-dose NBXH partially repaired the abnormal gene expression, further enhanced the anti-TB immunity included autophagy and NK cell-mediated cytotoxicity, and had a certain inhibitory effect on overactivated immune responses.

A serum B-lymphocyte activation signature is a key distinguishing feature of the immune response in sarcoidosis compared to tuberculosis

Sarcoidosis and tuberculosis (TB) are two granulomatous diseases that often share overlapping clinical features, including uveitis. We measured 368 inflammation-related proteins in serum in both diseases, with and without uveitis from two distinct geographically separated cohorts: sarcoidosis from the Netherlands and TB from Indonesia. A total of 192 and 102 differentially expressed proteins were found in sarcoidosis and active pulmonary TB compared to their geographical healthy controls, respectively. While substantial overlap exists in the immune-related pathways involved in both diseases, activation of B cell activating factor (BAFF) signaling and proliferation-inducing ligand (APRIL) mediated signaling pathways was specifically associated with sarcoidosis. We identified a B-lymphocyte activation signature consisting of BAFF, TNFRSF13B/TACI, TRAF2, IKBKG, MAPK9, NFATC1, and DAPP1 that was associated with sarcoidosis, regardless of the presence of uveitis. In summary, a difference in B-lymphocyte activation is a key discriminative immunological feature between sarcoidosis/ocular sarcoidosis (OS) and TB/ocular TB (OTB).

Single molecule measurements of microRNAs in the serum of patients with pulmonary tuberculosis

Background

microRNAs (miRNAs) were recognized as a promising source of diagnostic biomarker. Herein, we aim to evaluate the performance of an ultrasensitive method for detecting serum miRNAs using single molecule arrays (Simoa).

Methods

In this study, candidate miRNAs were trained and tested by RT-qPCR in a cohort of PTB patients. Besides that, ultrasensitive serum miRNA detection were developed using the Single Molecule Array (Simoa) platform. In this ultra-sensitive sandwich assay, two target-specific LNA-modified oligonucleotide probes can be simply designed to be complementary to the half-sequence of the target miRNA respectively. We characterized its analytical performance and measured miRNAs in the serum of patients with pulmonary tuberculosis and healthy individuals.

Results

We identified a five signature including three upregulated (miR-101, miR-196b, miR-29a) and two downregulated (miR-320b, miR-99b) miRNAs for distinguishing PTB patients from HCs, and validated in our 104 PTB patients. On the basis of Simoa technology, we developed a novel, fully automated digital analyser, which can be used to directly detect miRNAs in serum samples without pre-amplification. We successfully detected miRNAs at femtomolar concentrations (with limits of detection [LODs] ranging from 0.449 to 1.889 fM). Simoa-determined serum miR-29a and miR-99b concentrations in patients with PTB ((median 6.06 fM [range 0.00-75.22]), (median 2.53 fM [range 0.00-24.95]), respectively) were significantly higher than those in HCs ((median 2.42 fM [range 0.00-28.64]) (P < 0.05), (median 0.54 fM [range 0.00-9.12] (P < 0.0001), respectively). Serum levels of miR-320b were significantly reduced in patients with PTB (median 2.11 fM [range 0.00-39.30]) compared with those in the HCs (median 4.76 fM [range 0.00-25.10]) (P < 0.001). A combination of three miRNAs (miR-29a, miR-99b, and miR-320b) exhibited a good capacity to distinguish PTB from HCs, with an area under the curve (AUC) of 0.818 (sensitivity: 83.9%; specificity: 79.7%).

Conclusions

This study benchmarks the role of Simoa as a promising tool for monitoring miRNAs in serum and offers considerable potential as a non-invasive platform for the early diagnosis of PTB.

Computational reassessment of RNA-seq data reveals key genes in active tuberculosis

BACKGROUND

Tuberculosis is a serious life-threatening disease among the top global health challenges and rapid and effective diagnostic biomarkers are vital for early diagnosis especially given the increasing prevalence of multidrug resistance.

METHODS

Two human whole blood microarray datasets, GSE42826 and GSE42830 were retrieved from publicly available gene expression omnibus (GEO) database. Deregulated genes (DEGs) were identified using GEO2R online tool and Gene Ontology (GO), protein-protein interaction (PPI) network analysis was performed using Metascape and STRING databases. Significant genes (n = 8) were identified using T-test/ANOVA and Molecular Complex Detection (MCODE) score ≥10, which was validated in GSE34608 dataset. The diagnostic potential of three biomarkers was assessed using Area Under Curve (AUC) of Receiver Operating Characteristic (ROC) plot. The transcriptional levels of these genes were also examined in a separate dataset GSE31348, to monitor the patterns of variation during tuberculosis treatment.

RESULTS

A total of 62 common DEGs (57 upregulated, 7 downregulated genes) were identified in two discovery datasets. GO functions and pathway enrichment analysis shed light on the functional roles of these DEGs in immune response and type-II interferon signaling. The genes in Module-1 (n = 18) were linked to innate immune response, interferon-gamma signaling. The common genes (n = 8) were validated in GSE34608 dataset, that corroborates the results obtained from discovery sets. The gene expression levels demonstrated responsiveness to Mtb infection during anti-TB therapy in GSE31348 dataset. In GSE34608 dataset, the expression levels of three specific genes, GBP5, IFITM3, and EPSTI1, emerged as potential diagnostic makers. In combination, these genes scored remarkable diagnostic performance with 100% sensitivity and 89% specificity, resulting in an impressive Area Under Curve (AUC) of 0.958. However, GBP5 alone showed the highest AUC of 0.986 with 100% sensitivity and 89% specificity.

CONCLUSIONS

The study presents valuable insights into the critical gene network perturbed during tuberculosis. These genes are determinants for assessing the effectiveness of an anti-TB response and distinguishing between active TB and healthy individuals. GBP5, IFITM3 and EPSTI1 emerged as candidate core genes in TB and holds potential as novel molecular targets for the development of interventions in the treatment of TB.

Bioinformatic meta-analysis reveals novel differentially expressed genes and pathways in sarcoidosis

Introduction

Sarcoidosis is a multi-system inflammatory disease of unknown origin with heterogeneous clinical manifestations varying from a single organ non-caseating granuloma site to chronic systemic inflammation and fibrosis. Gene expression studies have suggested several genes and pathways implicated in the pathogenesis of sarcoidosis, however, due to differences in study design and variable statistical approaches, results were frequently not reproducible or concordant. Therefore, meta-analysis of sarcoidosis gene-expression datasets is of great importance to robustly establish differentially expressed genes and signalling pathways.

Methods

We performed meta-analysis on 22 published gene-expression studies on sarcoidosis. Datasets were analysed systematically using same statistical cut-offs. Differentially expressed genes were identified by pooling of p-values using Edgington's method and analysed for pathways using Ingenuity Pathway Analysis software.

Results

A consistent and significant signature of novel and well-known genes was identified, those collectively implicated both type I and type II interferon mediated signalling pathways in sarcoidosis. In silico functional analysis showed consistent downregulation of eukaryotic initiation factor 2 signalling, whereas cytokines like interferons and transcription factor STAT1 were upregulated. Furthermore, we analysed affected tissues to detect differentially expressed genes likely to be involved in granuloma biology. This revealed that matrix metallopeptidase 12 was exclusively upregulated in affected tissues, suggesting a crucial role in disease pathogenesis.

Discussion

Our analysis provides a concise gene signature in sarcoidosis and expands our knowledge about the pathogenesis. Our results are of importance to improve current diagnostic approaches and monitoring strategies as well as in the development of targeted therapeutics.

Reanalysis and validation of the transcriptional pleural fluid signature in pleural tuberculosis

Introduction

Pleural tuberculosis (PlTB), the most common site of extrapulmonary TB, is characterized by a paucibacillary nature and a compartmentalized inflammatory response in the pleural cavity, both of which make diagnosis and management extremely challenging. Although transcriptional signatures for pulmonary TB have already been described, data obtained by using this approach for extrapulmonary tuberculosis and, specifically, for pleural tuberculosis are scarce and heterogeneous. In the present study, a set of candidate genes previously described in pulmonary TB was evaluated to identify and validate a transcriptional signature in clinical samples from a Brazilian cohort of PlTB patients and those with other exudative causes of pleural effusion.

Methods

As a first step, target genes were selected by a random forest algorithm with recursive feature elimination (RFE) from public microarray datasets. Then, peripheral blood (PB) and pleural fluid (PF) samples from recruited patients presenting exudative pleural effusion were collected during the thoracentesis procedure. Transcriptional analysis of the selected top 10 genes was performed by quantitative RT-PCR (RT-qPCR).

Results

Reanalysis of the public datasets identified a set of candidate genes (CARD17, BHLHE40, FCGR1A, BATF2, STAT1, BTN3A1, ANKRD22, C1QB, GBP2, and SEPTIN4) that demonstrated a global accuracy of 89.5% in discriminating pulmonary TB cases from other respiratory diseases. Our validation cohort consisted of PlTB (n = 35) patients and non-TB (n = 34) ones. The gene expressions of CARD17, GBP2, and C1QB in PF at diagnosis were significantly different between the two (PlTB and non-TB) groups (p < 0.0001). It was observed that the gene expressions of CARD17 and GBP2 were higher in PlTB PF than in non-TB patients. C1QB showed the opposite behavior, being higher in the non-TB PF. After anti-TB therapy, however, GBP2 gene expression was significantly reduced in PlTB patients (p < 0.001). Finally, the accuracy of the three above-cited highlighted genes in the PF was analyzed, showing AUCs of 91%, 90%, and 85%, respectively. GBP2 was above 80% (sensitivity = 0.89/specificity = 0.81), and CARD17 showed significant specificity (Se = 0.69/Sp = 0.95) in its capacity to discriminate the groups.

Conclusion

CARD17, GBP2, and C1QB showed promise in discriminating PlTB from other causes of exudative pleural effusion by providing accurate diagnoses, thus accelerating the initiation of anti-TB therapy.

Biomarkers and molecular endotypes of sarcoidosis: lessons from omics and non-omics studies

Sarcoidosis is a chronic granulomatous disorder characterized by unknown etiology, undetermined mechanisms, and non-specific therapies except TNF blockade. To improve our understanding of the pathogenicity and to predict the outcomes of the disease, the identification of new biomarkers and molecular endotypes is sorely needed. In this study, we systematically evaluate the biomarkers identified through Omics and non-Omics approaches in sarcoidosis. Most of the currently documented biomarkers for sarcoidosis are mainly identified through conventional "one-for-all" non-Omics targeted studies. Although the application of machine learning algorithms to identify biomarkers and endotypes from unbiased comprehensive Omics studies is still in its infancy, a series of biomarkers, overwhelmingly for diagnosis to differentiate sarcoidosis from healthy controls have been reported. In view of the fact that current biomarker profiles in sarcoidosis are scarce, fragmented and mostly not validated, there is an urgent need to identify novel sarcoidosis biomarkers and molecular endotypes using more advanced Omics approaches to facilitate disease diagnosis and prognosis, resolve disease heterogeneity, and facilitate personalized medicine.

Immune mechanisms of granuloma formation in sarcoidosis and tuberculosis

Sarcoidosis is a complex immune-mediated disease characterized by clusters of immune cells called granulomas. Despite major steps in understanding the cause of this disease, many questions remain. In this Review, we perform a mechanistic interrogation of the immune activities that contribute to granuloma formation in sarcoidosis and compare these processes with its closest mimic, tuberculosis, highlighting shared and divergent immune activities. We examine how Mycobacterium tuberculosis is sensed by the immune system; how the granuloma is initiated, formed, and perpetuated in tuberculosis compared with sarcoidosis; and the role of major innate and adaptive immune cells in shaping these processes. Finally, we draw these findings together around several recent high-resolution studies of the granuloma in situ that utilized the latest advances in single-cell technology combined with spatial methods to analyze plausible disease mechanisms. We conclude with an overall view of granuloma formation in sarcoidosis.

Sarcoidosis or Tuberculosis: Should Corticosteroids Be Used?

Sarcoidosis shows high similarity with tuberculosis in clinical manifestations and imaging features. It is rarely reported whether sarcoidosis patients with suspected latent tuberculosis can be treated safely with immunosuppressive therapy. We reported on a 54-year-old man who presented with enlarged lymph nodes persisting for decades, accompanied by renal impairment and refractory hypercalcemia. The patient was diagnosed with sarcoidosis and suspected latent tuberculosis (as suggested by a positive tuberculin test and tuberculosis interferon-gamma release assays) and received prednisone under follow-up. The patient showed significant amelioration in hypercalcemia and shrinkage of lymph nodes, without evidence of developing active tuberculosis. For sarcoidosis patients with suspected latent tuberculosis, immunosuppressive agents can be utilized safely based on close monitoring. Further efforts are required to reveal whether sarcoidosis and tuberculosis can trigger similar immune responses and what the clinical implications are.

T-cell signature cytokines distinguish pulmonary sarcoidosis from pulmonary tuberculosis

Sarcoidosis is a systemic inflammatory disorder characterized by tissue infiltration due to mononuclear phagocytes and lymphocytes and associated noncaseating granuloma formation. Pulmonary sarcoidosis (PS) shares a number of clinical, radiological, and histopathological characteristics with that of pulmonary tuberculosis (PTB). Due to this, clinicians face issues in differentiating between PS and PTB in a substantial number of cases. There is a lack of any specific biomarker that can diagnose PS distinctively from PTB. We compared T-cell-based signature cytokines in patients with PS and PTB. In this study, we proposed a serum biomarker panel consisting of cytokines from cells: T helper (Th) 1 [interferon-gamma (IFN-γ); tumor necrosis factor-alpha (TNF-α)], Th9 [interleukin (IL)-9], Th17 [IL-17], and T regulatory (Treg) [IL-10; transforming growth factor-beta (TGF-β)]. We performed the principal component analysis that demonstrated that our serum cytokine panel has a significant predictive ability to differentiate PS from PTB. Our results could aid clinicians to improve the diagnostic workflow for patients with PS in TB endemic settings where the diagnosis between PS and PTB is often ambiguous.

Altered microRNA expression in patients with sarcoidosis

Background Sarcoidosis is a granulomatous multisystem disease of uncertain aetiology. The disease has major inflammatory and immune components; however, the immunopathogenesis is not well understood. Micro ribonucleic acids (microRNAs) are classes of miniature, single-stranded, non-coding RNAs. Their key recognised role includes mediating the silencing of target genes post-transcriptionally. Recently, the role of miRNAs has gained interest in numerous disorders, suggested as being involved in pathogenesis of those diseases and acting as disease markers. Very little is known about the role of miRNAs in sarcoidosis, with nothing known regarding miRNAs in South African patients. The main objective, therefore, was to investigate the serum expression of approximately 800 miRNAs in patients with sarcoidosis compared with race-, age- and gender-matched healthy controls. Methods A total of six patients and six matched controls participated in this study. Whole blood samples were collected in EDTA tubes, processed and the plasma retained. RNA was extracted from the stored plasma samples using the QIAGEN miRNeasy Mini Kit® and concentrated using a salt-ethanol precipitation. The extracted miRNA was profiled using an nCounter® miRNA human v3 expression assay and data analysed using the nSolver™ Analysis Software. Results After excluding one sample/control pair because of cellular RNA contamination, the remaining five patient and five matched control samples were analysed, and 145 miRNAs were found to be potentially differentially expressed. On applying a Bonferroni correction, the only miRNA that was significantly different was miRNA let-7a-5p, which was significantly overexpressed (141-fold change; p<0.0003) in patients compared with controls. Conclusion This is the first miRNA report of differentially expressed miRNAs in the serum of patients with sarcoidosis and matched healthy controls in South Africa. The results obtained suggest that miRNAs may play a role in sarcoidosis pathogenesis. Whether these molecules have diagnostic or prognostic implications, needs future studies recruiting larger patient cohorts.

The role of systemic immune-inflammation index (SII) in the differential diagnosis of granulomatous and reactive LAP diagnosed by endobronchial ultrasonography

BACKGROUND AND AIM

Tuberculosis and sarcoidosis are the two most important granulomatous diseases that physicians have difficulty in differential diagnosis. In our study, we aimed to observe the place of systemic immune-inflammation index (SII) level in the differentiation of patients diagnosed with endoboronchial ultrasonography (EBUS).

METHODS

Our study included 494 patients who applied to our hospital's chest diseases outpatient clinic between 2015 and 2020 and underwent endobronchial ultrasonography (EBUS) for mediastinal lymphadenopathy (LAP). Patients' follow-up for at least 2 years after diagnosis and pre-procedural hematologic parameters were retrospectively recorded.

RESULTS

In the comparison of SII between groups, it was observed that SII was statistically significantly higher in patients followed up for tuberculous lymphadenitis compared to patients with sarcoidosis and reactive LAP (p=0.01, <0.001). In sarcoidosis patients, SII levels were statistically significantly higher than in patients with reactive LAP (p=0.002). Platelet, sedimentation and SII levels were statistically significantly higher in stage 2 patients compared to stage 1 patients, while lymphocyte levels were lower (p=0.009, 0.001, 0.001, 0.001, 0.001 respectively). In the ROC curve analysis of the SII level of patients with sarcoidosis and tuberculosis LAP, the AUC was 0.668 and when the cut-off value for the SII level was 890.667, the sensitivity was 70% and the specificity was 66% in the differentiation of tuberculosis and sarcoidosis lymphadenitis.

CONCLUSION

SII may be an easily applicable parameter in the differentiation of tuberculosis and sarcoidosis LAP with granuloma and in the differentiation of granulomatous diseases from reactive LAP.

Discovery of Novel Transketolase Epitopes and the Development of IgG-Based Tuberculosis Serodiagnostics

Despite advances in rapid molecular techniques for tuberculosis (TB) diagnostics, there is an unmet need for a point-of-care, nonsputum-based test. Previously, through a T7 phage antigen display platform and immunoscreening, we identified that the serum IgGs of active TB patients differentially bind to several antigen-clones and that this immunoreactivity discriminates TB from other respiratory diseases. One of these high-performance clones has some homology to the transketolase of Mycobacterium tuberculosis (M.tb TKT). In this study, we developed a direct enzyme-linked immunosorbent assay (ELISA) detecting IgG against the TKT antigen-clone (TKTμ). Through sequence alignment and in silico analysis, we designed two more peptides with potential antigenicity that correspond to M.tb-specific transketolase (M.tb TKT1 and M.tb TKT3) epitopes. After the development and standardization of a direct peptide ELISA for three peptides, we tested 292 subjects, including TB (n = 101), latent tuberculosis infection (LTBI) (n = 49), healthy controls (n = 66), and sarcoidosis (n = 76). We randomly assigned 60% of the subjects to a training set to create optimal models to distinguish positive TB samples, and the remaining 40% were used to validate the diagnostic power of the IgG-based assays that were developed in the training set. Antibodies against M.tb TKT3 yielded the highest sensitivity (0.845), and these were followed by TKTμ (0.817) and M.tb TKT1 (0.732). The specificities obtained by TKTμ, M.tb TKT3, and M.tb TKT1 on the test sets were 1, 0.95, and 0.875, respectively. The model using TKTμ obtained a perfect positive predictive value (PPV) of 1, and this was followed by M.tb TKT3 (0.968) and M.tb TKT1 (0.912). These results show that IgG antibodies against transketolase can discriminate active TB against LTBI, sarcoidosis, and controls. IMPORTANCE There is an unmet need for a point-of-care, nonsputum-based TB test. Through the immunoscreening of a novel T7 phage library, we identified classifiers that specifically bind to IgGs in active TB sera. We discovered that one of these clones is aligned with Mycobacterium tuberculosis transketolase (TKT). TKT is an essential enzyme for Mycobacterium tuberculosis growth. We designed three TKT epitopes (TKTμ, TKT1, and TKT3) to detect TKT-specific IgGs. After the development and standardization of three different ELISA-utilizing TKT peptides, we tested 292 subjects, including active TB, LTBI, healthy controls, and sarcoidosis. Rigorous statistical analyses using training and validation sets showed that ELISA-based detections of specific IgGs against TKT3 and TKTμ have the greatest sensitivity, specificity, and accuracy to distinguish active TB subjects from others, even LTBI. Our work provides a novel scientific platform from which to further develop a point-of-care test, thereby aiding in faster TB diagnoses.

Integrated bioinformatic analyses investigate macrophage-M1-related biomarkers and tuberculosis therapeutic drugs

Tuberculosis (TB) is a common infectious disease linked to host genetics and the innate immune response. It is vital to investigate new molecular mechanisms and efficient biomarkers for Tuberculosis because the pathophysiology of the disease is still unclear, and there aren't any precise diagnostic tools. This study downloaded three blood datasets from the GEO database, two of which (GSE19435 and 83456) were used to build a weighted gene co-expression network for searching hub genes associated with macrophage M1 by the CIBERSORT and WGCNA algorithms. Furthermore, 994 differentially expressed genes (DEGs) were extracted from healthy and TB samples, four of which were associated with macrophage M1, naming RTP4, CXCL10, CD38, and IFI44. They were confirmed as upregulation in TB samples by external dataset validation (GSE34608) and quantitative real-time PCR analysis (qRT-PCR). CMap was used to predict potential therapeutic compounds for tuberculosis using 300 differentially expressed genes (150 downregulated and 150 upregulated genes), and six small molecules (RWJ-21757, phenamil, benzanthrone, TG-101348, metyrapone, and WT-161) with a higher confidence value were extracted. We used in-depth bioinformatics analysis to investigate significant macrophage M1-related genes and promising anti-Tuberculosis therapeutic compounds. However, more clinical trials were necessary to determine their effect on Tuberculosis.

Comparison of gene set scoring methods for reproducible evaluation of multiple tuberculosis gene signatures

Rationale

Many blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease, predict risk of progression from infection to disease, and monitor TB treatment outcomes. However, an unresolved issue is whether gene set enrichment analysis (GSEA) of the signature transcripts alone is sufficient for prediction and differentiation, or whether it is necessary to use the original statistical model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data, missing details about the original trained model, and inadequate publicly-available software tools or source code implementing models. To facilitate these signatures' replicability and appropriate utilization in TB research, comprehensive comparisons between gene set scoring methods with cross-data validation of original model implementations are needed.

Objectives

We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both re-rebuilt original models and gene set scoring methods to evaluate whether gene set scoring is a reasonable proxy to the performance of the original trained model. We have provided an open-access software implementation of the original models for all 19 signatures for future use.

Methods

We considered existing gene set scoring and machine learning methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, as alternative approaches to profile gene signature performance. The sample-size-weighted mean area under the curve (AUC) value was computed to measure each signature's performance across datasets. Correlation analysis and Wilcoxon paired tests were used to analyze the performance of enrichment methods with the original models.

Measurement and Main Results

For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original diagnostic models. PLAGE outperformed all other gene scoring methods. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies.

Conclusion

Gene set enrichment scoring of existing blood-based biomarker gene sets can distinguish patients with active TB disease from latent TB infection and other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

Utility of a three-gene transcriptomic signature in the diagnosis of tuberculosis in a low-endemic hospital setting

BACKGROUND

Host transcriptomic blood signatures have demonstrated diagnostic potential for tuberculosis (TB), requiring further validation across different geographical settings. Discriminating TB from other diseases with similar clinical manifestations is crucial for the development of an accurate immunodiagnostic tool. In this exploratory cohort study, we evaluated the performance of potential blood-based transcriptomic signatures in distinguishing TB disease from non-TB lower respiratory tract infections in hospitalised patients in a TB low-endemic country.

METHOD

Quantitative real-time polymerase chain reaction qPCR) was used to evaluate 26 previously published genes in blood from 31 patients (14 TB and 17 lower respiratory tract infection cases) admitted to Oslo University Hospital in Norway. The diagnostic accuracies of differentially expressed genes were determined by receiver operating characteristic curves.

RESULTS

A significant difference (p < .01) in the age distribution was observed between patients with TB (mean age, 40 ± 15 years) and lower respiratory tract infection (mean age 59 ± 12 years). Following adjustment for age, ETV7, GBP1, GBP5, P2RY14 and BLK were significantly differentially expressed between patients with TB and those with LRI. A general discriminant analysis generated a three-gene signature (BAFT2, ETV7 and CD1C), which diagnosed TB with an area under the receiver operating characteristic curve (AUC) of 0.86 (95% CI, 0.69 - 1.00), sensitivity of 69.23% (95% CI, 38.57%-90.91%) and specificity of 94.12% (95% CI, 71.31%-99.85%).

CONCLUSION

The three-genes signature may have potential to improve diagnosis of TB in a hospitalised low-burden setting. However, the influence of confounding variables or covariates such as age requires further evaluation in larger studies.

A robust host-response-based signature distinguishes bacterial and viral infections across diverse global populations

Limited sensitivity and specificity of current diagnostics lead to the erroneous prescription of antibiotics. Host-response-based diagnostics could address these challenges. However, using 4,200 samples across 69 blood transcriptome datasets from 20 countries from patients with bacterial or viral infections representing a broad spectrum of biological, clinical, and technical heterogeneity, we show current host-response-based gene signatures have lower accuracy to distinguish intracellular bacterial infections from viral infections than extracellular bacterial infections. Using these 69 datasets, we identify an 8-gene signature to distinguish intracellular or extracellular bacterial infections from viral infections with an area under the receiver operating characteristic curve (AUROC) > 0.91 (85.9% specificity and 90.2% sensitivity). In prospective cohorts from Nepal and Laos, the 8-gene classifier distinguished bacterial infections from viral infections with an AUROC of 0.94 (87.9% specificity and 91% sensitivity). The 8-gene signature meets the target product profile proposed by the World Health Organization and others for distinguishing bacterial and viral infections.

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.

MicroRNAs as immune regulators and biomarkers in tuberculosis

Tuberculosis (TB), which is caused by Mycobacterium tuberculosis (Mtb), is one of the most lethal infectious disease worldwide, and it greatly affects human health. Some diagnostic and therapeutic methods are available to effectively prevent and treat TB; however, only a few systematic studies have described the roles of microRNAs (miRNAs) in TB. Combining multiple clinical datasets and previous studies on Mtb and miRNAs, we state that pathogens can exploit interactions between miRNAs and other biomolecules to avoid host mechanisms of immune-mediated clearance and survive in host cells for a long time. During the interaction between Mtb and host cells, miRNA expression levels are altered, resulting in the changes in the miRNA-mediated regulation of host cell metabolism, inflammatory responses, apoptosis, and autophagy. In addition, differential miRNA expression can be used to distinguish healthy individuals, patients with TB, and patients with latent TB. This review summarizes the roles of miRNAs in immune regulation and their application as biomarkers in TB. These findings could provide new opportunities for the diagnosis and treatment of TB.

Altered transcription factor targeting is associated with differential peripheral blood mononuclear cell proportions in sarcoidosis

Introduction

In sarcoidosis, peripheral lymphopenia and anergy have been associated with increased inflammation and maladaptive immune activity, likely promoting development of chronic and progressive disease. However, the molecular mechanisms that lead to reduced lymphocyte proportions, particularly CD4+ T-cells, have not been fully elucidated. We posit that paradoxical peripheral lymphopenia is characterized by a dysregulated transcriptomic network associated with cell function and fate that results from altered transcription factor targeting activity.

Methods

Messenger RNA-sequencing (mRNA-seq) was performed on peripheral blood mononuclear cells (PBMCs) from ACCESS study subjects with sarcoidosis and matched controls and findings validated on a sarcoidosis case-control cohort and a sarcoidosis case series. Preserved PBMC transcriptomic networks between case-control cohorts were assessed to establish cellular associations with gene modules and define regulatory targeting involved in sarcoidosis immune dysregulation utilizing weighted gene co-expression network analysis and differential transcription factor involvement analysis. Network centrality measures identified master transcriptional regulators of subnetworks related to cell proliferation and death. Predictive models of differential PBMC proportions constructed from ACCESS target gene expression corroborated the relationship between aberrant transcription factor regulatory activity and imputed and clinical PBMC populations in the validation cohorts.

Results

We identified two unique and preserved gene modules significantly associated with sarcoidosis immune dysregulation. Strikingly, increased expression of a monocyte-driven, and not a lymphocyte-driven, gene module related to innate immunity and cell death was the best predictor of peripheral CD4+ T-cell proportions. Within the gene network of this monocyte-driven module, TLE3 and CBX8 were determined to be master regulators of the cell death subnetwork. A core gene signature of differentially over-expressed target genes of TLE3 and CBX8 involved in cellular communication and immune response regulation accurately predicted imputed and clinical monocyte expansion and CD4+ T-cell depletion.

Conclusions

Altered transcriptional regulation associated with aberrant gene expression of a monocyte-driven transcriptional network likely influences lymphocyte function and survival. Although further investigation is warranted, this indicates that crosstalk between hyperactive monocytes and lymphocytes may instigate peripheral lymphopenia and underlie sarcoidosis immune dysregulation and pathogenesis. Future therapies selectively targeting master regulators, or their targets, may mitigate dysregulated immune processes in sarcoidosis and disease progression.

Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform

BACKGROUND

Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers.

METHODS

The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker.

RESULTS

Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB.

CONCLUSIONS

The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.

Interrelation between extracellular vesicles miRNAs with chronic lung diseases

Extracellular vehicles (EVs) are nanoscale lipid bilayer vesicles that carry biologically active biomolecule cargos like proteins, lipids, and nucleic acids (DNA, RNA) outside of the cell. Blood (serum/plasma), urine, and bronchoalveolar lavage fluid are all examples of biofluids from which they may be collected. EVs play a vital role in intracellular communication. The molecular signature of EVs largely depends on the parental cell's status. EVs are classified into two groups, (1) exosomes (originated by endogenous route) and (2) microvesicles (originated from the plasma membrane, also known as ectosomes). The quantity and types of EV cargo vary during normal conditions compared to pathological conditions (chronic inflammatory lung diseases or lung cancer). Consequently, EVs contain novel biomarkers that differ based on the cell type of origin and during lung diseases. Small RNAs (e.g., microRNAs) are transported by EVs, which is one of the most rapidly evolving research areas in the field of EVs biology. EV-mediated cargos transport small RNAs that can result in reprograming the target/recipient cells. Multiple chronic inflammatory lung illnesses, such as chronic obstructive pulmonary disease, asthma, pulmonary hypertension, pulmonary fibrosis, cystic fibrosis, acute lung injury, and lung cancer, have been demonstrated to be regulated by EV. In this review, we will consolidate the current knowledge and literature on the novel role of EVs and their small RNAs concerning chronic lung diseases (CLDs). Additionally, we will also provide better insight into the clinical and translational impact of mesenchymal stem cells-derived EVs as novel therapeutic agents in treating CLDs.

Isoniazid preventive therapy and tuberculosis transcriptional signatures in people with HIV

OBJECTIVES

To examine the association between isoniazid preventive therapy (IPT) or nontuberculous mycobacteria (NTM) sputum culture positivity and tuberculosis (TB) transcriptional signatures in people with HIV.

DESIGN

Cross-sectional study.

METHODS

We enrolled adults living with HIV who were IPT-naive or had completed IPT more than 6 months prior at HIV care clinics in western Kenya. We calculated TB signatures using gene expression data from qRT-PCR. We used multivariable linear regression to analyze the association between prior receipt of IPT or NTM sputum culture positivity with a transcriptional TB risk score, RISK6 (range 0-1). In secondary analyses, we explored the association between IPT or NTM positivity and four other TB transcriptional signatures.

RESULTS

Among 381 participants, 99.7% were receiving antiretroviral therapy and 86.6% had received IPT (completed median of 1.1 years prior). RISK6 scores were lower (mean difference 0.10; 95% confidence interval (CI): 0.06-0.15; P  < 0.001) among participants who received IPT than those who did not. In a model that adjusted for age, sex, duration of ART, and plasma HIV RNA, the RISK6 score was 52.8% lower in those with a history of IPT ( P  < 0.001). No significant association between year of IPT receipt and RISK6 scores was detected. There was no association between NTM sputum culture positivity and RISK6 scores.

CONCLUSION

In people with HIV, IPT was associated with significantly lower RISK6 scores compared with persons who did not receive IPT. These data support investigations of its performance as a TB preventive therapy response biomarker.

Amyloid-containing biofilms and autoimmunity

Bacteria are microscopic, single-celled organisms known for their ability to adapt to their environment. In response to stressful environmental conditions or in the presence of a contact surface, they commonly form multicellular aggregates called biofilms. Biofilms form on various abiotic or biotic surfaces through a dynamic stepwise process involving adhesion, growth, and extracellular matrix production. Biofilms develop on tissues as well as on implanted devices during infections, providing the bacteria with a mechanism for survival under harsh conditions including targeting by the immune system and antimicrobial therapy. Like pathogenic bacteria, members of the human microbiota can form biofilms. Biofilms formed by enteric bacteria contribute to several human diseases including autoimmune diseases and cancer. However, until recently the interactions of immune cells with biofilms had been mostly uncharacterized. Here, we will discuss how components of the enteric biofilm produced in vivo, specifically amyloid curli and extracellular DNA, could be interacting with the host's immune system causing an unpredicted immune response.

Increasing reproducibility, robustness, and generalizability of biomarker selection from meta-analysis using Bayesian methodology

A major limitation of gene expression biomarker studies is that they are not reproducible as they simply do not generalize to larger, real-world, heterogeneous populations. Frequentist multi-cohort gene expression meta-analysis has been frequently used as a solution to this problem to identify biomarkers that are truly differentially expressed. However, the frequentist meta-analysis framework has its limitations-it needs at least 4-5 datasets with hundreds of samples, is prone to confounding from outliers and relies on multiple-hypothesis corrected p-values. To address these shortcomings, we have created a Bayesian meta-analysis framework for the analysis of gene expression data. Using real-world data from three different diseases, we show that the Bayesian method is more robust to outliers, creates more informative estimates of between-study heterogeneity, reduces the number of false positive and false negative biomarkers and selects more generalizable biomarkers with less data. We have compared the Bayesian framework to a previously published frequentist framework and have developed a publicly available R package for use.

Mycobacterium tuberculosis infection, immune activation, and risk of HIV acquisition

BACKGROUND

Although immune activation is associated with HIV acquisition, the nature of inflammatory profiles that increase HIV risk, which may include responses to M. tuberculosis (Mtb) infection, are not well characterized.

METHODS

We conducted a nested case-control study using cryopreserved samples from persons who did and did not acquire HIV during the multinational Step clinical trial of the MRKAd5 HIV-1 vaccine. PBMCs from the last HIV-negative sample from incident HIV cases and controls were stimulated with Mtb-specific antigens (ESAT-6/CFP-10) and analyzed by flow cytometry with intracellular cytokine staining and scored with COMPASS. We measured inflammatory profiles with five Correlates of TB Risk (CoR) transcriptomic signatures. Our primary analysis examined the association of latent Mtb infection (LTBI; IFNγ+CD4+ T cell frequency) or RISK6 CoR signature with HIV acquisition. Conditional logistic regression analyses, adjusted for known predictors of HIV acquisition, were employed to assess whether TB-associated immune markers were associated with HIV acquisition.

RESULTS

Among 465 participants, LTBI prevalence (21.5% controls vs 19.1% cases, p = 0.51) and the RISK6 signature were not higher in those who acquired HIV. In exploratory analyses, Mtb antigen-specific polyfunctional CD4+ T cell COMPASS scores (aOR 0.96, 95% CI 0.77, 1.20) were not higher in those who acquired HIV. Two CoR signatures, Sweeney3 (aOR 1.38 (1.07, 1.78) per SD change) and RESPONSE5 (0.78 (0.61, 0.98)), were associated with HIV acquisition. The transcriptomic pattern used to differentiate active vs latent TB (Sweeney3) was most strongly associated with acquiring HIV.

CONCLUSIONS

LTBI, Mtb polyfunctional antigen-specific CD4+ T cell activation, and RISK6 were not identified as risks for HIV acquisition. In exploratory transcriptomic analyses, two CoR signatures were associated with HIV risk after adjustment for known behavioral and clinical risk factors. We identified host gene expression signatures associated with HIV acquisition, but the observed effects are likely not mediated through Mtb infection.

Non-Coding RNAs in Tuberculosis Epidemiology: Platforms and Approaches for Investigating the Genome's Dark Matter

A growing amount of information about the different types, functions, and roles played by non-coding RNAs (ncRNAs) is becoming available, as more and more research is done. ncRNAs have been identified as potential therapeutic targets in the treatment of tuberculosis (TB), because they may be essential regulators of the gene network. ncRNA profiling and sequencing has recently revealed significant dysregulation in tuberculosis, primarily due to aberrant processes of ncRNA synthesis, including amplification, deletion, improper epigenetic regulation, or abnormal transcription. Despite the fact that ncRNAs may have a role in TB characteristics, the detailed mechanisms behind these occurrences are still unknown. The dark matter of the genome can only be explored through the development of cutting-edge bioinformatics and molecular technologies. In this review, ncRNAs' synthesis and functions are discussed in detail, with an emphasis on the potential role of ncRNAs in tuberculosis. We also focus on current platforms, experimental strategies, and computational analyses to explore ncRNAs in TB. Finally, a viewpoint is presented on the key challenges and novel techniques for the future and for a wide-ranging therapeutic application of ncRNAs.

Contribution and Future of High-Throughput Transcriptomics in Battling Tuberculosis

While Tuberculosis (TB) infection remains a serious challenge worldwide, big data and “omic” approaches have greatly contributed to the understanding of the disease. Transcriptomics have been used to tackle a wide variety of queries including diagnosis, treatment evolution, latency and reactivation, novel target discovery, vaccine response or biomarkers of protection. Although a powerful tool, the elevated cost and difficulties in data interpretation may hinder transcriptomics complete potential. Technology evolution and collaborative efforts among multidisciplinary groups might be key in its exploitation. Here, we discuss the main fields explored in TB using transcriptomics, and identify the challenges that need to be addressed for a real implementation in TB diagnosis, prevention and therapy.

Micro RNAs as potential biomarkers in tuberculosis: A systematic review

Tuberculosis (TB) remains a major infectious disease across the globe. With increasing TB infections and a rise in multi-drug resistance, rapid diagnostic modalities are required to achieve TB control. Radiological investigations and microbiological tests (microscopic examination, cartridge-based nucleic acid amplification tests, and cultures) are most commonly used to diagnose TB. Histopathological/cytopathological examinations are also required for an accurate diagnosis in many patients. The causative agent, Mycobacterium tuberculosis (Mtb), is known to circumvent the host's immune system. Circulating microRNAs (miRNAs) play a crucial role in biological pathways and can be used as a potential biomarker to detect tuberculosis. miRNAs are small non-coding RNAs and negatively regulate gene expression during post-transcriptional regulation. The differential expression of miRNAs in multiple clinical samples in tuberculosis patients may be helpful as potential disease biomarkers. This review summarizes the literature on miRNAs in various clinical samples as biomarkers for TB diagnosis.

The immunoregulatory landscape of human tuberculosis granulomas

Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-β, regulatory T cells and IDO1⁺ PD-L1⁺ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.

Transcriptomics of bronchoalveolar lavage cells identifies new molecular endotypes of sarcoidosis

BACKGROUND

Sarcoidosis is a multisystem granulomatous disease of unknown origin with a variable and often unpredictable course and pattern of organ involvement. In this study we sought to identify specific bronchoalveolar lavage (BAL) cell gene expression patterns indicative of distinct disease phenotypic traits.

METHODS

RNA sequencing by Ion Torrent Proton was performed on BAL cells obtained from 215 well-characterised patients with pulmonary sarcoidosis enrolled in the multicentre Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study. Weighted gene co-expression network analysis and nonparametric statistics were used to analyse genome-wide BAL transcriptome. Validation of results was performed using a microarray expression dataset of an independent sarcoidosis cohort (Freiburg, Germany; n=50).

RESULTS

Our supervised analysis found associations between distinct transcriptional programmes and major pulmonary phenotypic manifestations of sarcoidosis including T-helper type 1 (Th1) and Th17 pathways associated with hilar lymphadenopathy, transforming growth factor-β1 (TGFB1) and mechanistic target of rapamycin (MTOR) signalling with parenchymal involvement, and interleukin (IL)-7 and IL-2 with airway involvement. Our unsupervised analysis revealed gene modules that uncovered four potential sarcoidosis endotypes including hilar lymphadenopathy with increased acute T-cell immune response; extraocular organ involvement with PI3K activation pathways; chronic and multiorgan disease with increased immune response pathways; and multiorgan involvement, with increased IL-1 and IL-18 immune and inflammatory responses. We validated the occurrence of these endotypes using gene expression, pulmonary function tests and cell differentials from Freiburg.

CONCLUSION

Taken together, our results identify BAL gene expression programmes that characterise major pulmonary sarcoidosis phenotypes and suggest the presence of distinct disease molecular endotypes.

Selecting Hub Genes and Predicting Target Genes of microRNAs in Tuberculosis via the Bioinformatics Analysis

Tuberculosis (TB) is the world's most prevalently infectious disease. Molecular mechanisms behind tuberculosis remain unknown. microRNA (miRNA) is involved in a wide variety of diseases. To validate the significant genes and miRNAs in the current sample, two messenger RNA (mRNA) expression profile datasets and three miRNA expression profile datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed (DE) genes (DEGs) and miRNAs (DE miRNAs) between healthy and TB patients were filtered out. Enrichment analysis was executed, and a protein-protein interaction (PPI) network was developed to understand the enrich pathways and hub genes of TB. Additionally, the target genes of miRNA were predicted and overlapping target genes were identified. We studied a total of 181 DEGs (135 downregulated and 46 upregulated genes) and two DE miRNAs (2 downregulated miRNAs) from two gene profile datasets and three miRNA profile datasets, respectively. 10 hub genes were defined based on high degree of connectivity. A PPI network's top module was constructed. The 23 DEGs identified have a significant relationship with miRNAs. 25 critically significant Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were discovered. The detailed study revealed that, in tuberculosis, the DE miRNA and DEGs form an interaction network. The identification of novel target genes and main pathways would aid with our understanding of miRNA's function in tuberculosis progression.

Weaker protection against tuberculosis in BCG-vaccinated male 129 S2 mice compared to females

BCG - the only available vaccine against tuberculosis (TB) - was first given to babies 100 years ago in 1921. While it is effective against TB meningitis and disseminated TB, its efficacy against pulmonary TB is variable, notably in adults and adolescents. TB remains one of the world's leading health problems, with a higher prevalence among men. Male sex is associated with increased susceptibility to Mycobacterium tuberculosis in mice, but sex-specific responses to BCG vaccination have not been examined. In this study we vaccinated TB-susceptible 129 S2 mice with BCG and challenged with low-dose M. tuberculosis H37Rv by aerosol infection. BCG was protective against TB in both sexes, as unvaccinated mice lost weight more rapidly than vaccinated ones and suffered from worse lung pathology. However, female mice were better protected than males, showing lower lung bacterial burdens and less weight loss. Overall, vaccinated female mice had increased numbers of T cells and less myeloid cells in the lungs compared to vaccinated males. Principal component analysis of measured features revealed that mice grouped according to timepoint, sex and vaccination status. The features that had the biggest impact on grouping overall included numbers of CD8 T cells, CD8 central memory T cells and CD4 T effector cells, with neutrophil and CD11b⁺GR-1^- cell numbers having a big impact at day 29. Hierarchical clustering confirmed that the main difference in global immune response was due to mouse sex, with only a few misgrouped mice. In conclusion, we found sex-specific differences in response to M. tuberculosis H37Rv -challenge in BCG-vaccinated 129 S2 mice. This highlights the need to include both male and female mice in preclinical testing of vaccine candidates.

Transcriptional Profiling of Human Peripheral Blood Mononuclear Cells Stimulated by Mycobacterium tuberculosis PPE57 Identifies Characteristic Genes Associated With Type I Interferon Signaling

Proline-glutamic acid (PE)- and proline-proline-glutamic acid (PPE)-containing proteins are exclusive to Mycobacterium tuberculosis (MTB), the leading cause of tuberculosis (TB). In this study, we performed global transcriptome sequencing (RNA-Seq) on PPE57-stimulated peripheral blood mononuclear cells (PBMCs) and control samples to quantitatively measure the expression level of key transcripts of interest. A total of 1367 differentially expressed genes (DEGs) were observed in response to a 6 h exposure to PPE57, with 685 being up-regulated and 682 down-regulated. Immune-related gene functions and pathways associated with these genes were evaluated, revealing that the type I IFN signaling pathway was the most significantly enriched pathway in our RNA-seq dataset, with 14 DEGs identified therein including ISG15, MX2, IRF9, IFIT3, IFIT2, OAS3, IFIT1, IFI6, OAS2, OASL, RSAD2, OAS1, IRF7, and MX1. These PPE57-related transcriptomic profiles have implications for a better understanding of host global immune mechanisms underlying MTB infection outcomes. However, more studies regarding these DEGs and type I IFN signaling in this infectious context are necessary to more fully clarify the underlying mechanisms that arise in response to PPE57 during MTB infection.

Prediction of Multidrug-Resistant Tuberculosis Using Machine Learning Algorithms in SWAT, Pakistan

In this paper, we have focused on machine learning (ML) feature selection (FS) algorithms for identifying and diagnosing multidrug-resistant (MDR) tuberculosis (TB). MDR-TB is a universal public health problem, and its early detection has been one of the burning issues. The present study has been conducted in the Malakand Division of Khyber Pakhtunkhwa, Pakistan, to further add to the knowledge on the disease and to deal with the issues of identification and early detection of MDR-TB by ML algorithms. These models also identify the most important factors causing MDR-TB infection whose study gives additional insights into the matter. ML algorithms such as random forest, k-nearest neighbors, support vector machine, logistic regression, leaset absolute shrinkage and selection operator (LASSO), artificial neural networks (ANNs), and decision trees are applied to analyse the case-control dataset. This study reveals that close contacts of MDR-TB patients, smoking, depression, previous TB history, improper treatment, and interruption in first-line TB treatment have a great impact on the status of MDR. Accordingly, weight loss, chest pain, hemoptysis, and fatigue are important symptoms. Based on accuracy, sensitivity, and specificity, SVM and RF are the suggested models to be used for patients' classifications.

Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients

Group-aggregated responses to tuberculosis (TB) have been well characterized on a molecular level. However, human beings differ and individual responses to infection vary. We have combined a novel approach to individual gene set analysis (GSA) with the clustering of transcriptomic profiles of TB patients from seven datasets in order to identify individual molecular endotypes of transcriptomic responses to TB. We found that TB patients differ with respect to the intensity of their hallmark interferon (IFN) responses, but they also show variability in their complement system, metabolic responses and multiple other pathways. This variability cannot be sufficiently explained with covariates such as gender or age, and the molecular endotypes are found across studies and populations. Using datasets from a Cynomolgus macaque model of TB, we revealed that transcriptional signatures of different molecular TB endotypes did not depend on TB progression post-infection. Moreover, we provide evidence that patients with molecular endotypes characterized by high levels of IFN responses (IFN-rich), suffered from more severe lung pathology than those with lower levels of IFN responses (IFN-low). Harnessing machine learning (ML) models, we derived gene signatures classifying IFN-rich and IFN-low TB endotypes and revealed that the IFN-low signature allowed slightly more reliable overall classification of TB patients from non-TB patients than the IFN-rich one. Using the paradigm of molecular endotypes and the ML-based predictions allows more precisely tailored treatment regimens, predicting treatment-outcome with higher accuracy and therefore bridging the gap between conventional treatment and precision medicine.

Comprehensive analyses of potential key genes in active tuberculosis: A systematic review

BACKGROUND

Tuberculosis (TB) is a global health problem that brings us numerous difficulties. Diverse genetic factors play a significant role in the progress of TB disease. However, still no key genes for TB susceptibility have been reported. This study aimed to identify the key genes of TB through comprehensive bioinformatics analysis.

METHODS

The series microarray datasets from the gene expression omnibus (GEO) database were analyzed. We used the online tool GEO2R to filtrate differentially expressed genes (DEGs) between TB and health control. Database for annotation can complete gene ontology function analysis as well as Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein-protein interaction (PPI) networks of DEGs were established by STRING online tool and visualized by Cytoscape software. Molecular Complex Detection can complete the analysis of modules in the PPI networks. Finally, the significant hub genes were confirmed by plug-in Genemania of Cytoscape, and verified by the verification cohort and protein test.

RESULTS

There are a total of 143 genes were confirmed as DEGs, containing 48 up-regulated genes and 50 down-regulated genes. The gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis show that upregulated DEGs were associated with cancer and phylogenetic, whereas downregulated DEGs mainly concentrate on inflammatory immunity. PPI networks show that signal transducer and activator of transcription 1 (STAT1), guanylate binding protein 5 (GBP5), 2'-5'-oligoadenylate synthetase 1 (OAS1), catenin beta 1 (CTNNB1), and guanylate binding protein 1 (GBP1) were identified as significantly different hub genes.

CONCLUSION

We conclude that these genes, including TAT1, GBP5, OAS1, CTNNB1, GBP1 are a candidate as potential core genes in TB and treatment of TB in the future.

The Evaluation and Validation of Blood-Derived Novel Biomarkers for Precise and Rapid Diagnosis of Tuberculosis in Areas With High-TB Burden

Tuberculosis (TB) remains a highly contagious public health threat. Precise and prompt diagnosis and monitoring of treatment responses are urgently needed for clinics. To pursue novel and satisfied host blood-derived biomarkers, we streamlined a bioinformatic pipeline by integrating differentially expressed genes, a gene co-expression network, and short time-series analysis to mine the published transcriptomes derived from whole blood of TB patients in the GEO database, followed by validating the diagnostic performance of biomarkers in both independent datasets and blood samples of Chinese patients using quantitative real-time PCR (qRT-PCR). We found that four genes, namely UBE2L6 (Ubiquitin/ISG15-conjugating enzyme E2 L6), BATF2 (Basic leucine zipper transcriptional factor ATF-like), SERPING1 (Plasma protease C1 inhibitor), and VAMP5 (Vesicle-associated membrane protein 5), had high diagnostic value for active TB. The transcription levels of these four gene combinations can reach up to 88% sensitivity and 78% specificity (average) for the diagnosis of active TB; the highest sensitivity can achieve 100% by parallel of BATF2 and VAMP5, and the highest specificity can reach 89.5% through a combination of SERPIG1, UBE2L6, and VAMP5, which were significantly higher than 75.3% sensitivity and 69.1% specificity by T-SPOT.TB in the same patients. Quite unexpectedly, the gene set can assess the efficacy of anti-TB response and differentiate active TB from Latent TB infection. The data demonstrated these four biomarkers might have great potency and advantage over IGRAs in the diagnosis of TB.

RNA-Seq Transcriptome Analysis of Peripheral Blood From Cattle Infected With Mycobacterium bovis Across an Experimental Time Course

Bovine tuberculosis, caused by infection with members of the Mycobacterium tuberculosis complex, particularly Mycobacterium bovis, is a major endemic disease affecting cattle populations worldwide, despite the implementation of stringent surveillance and control programs in many countries. The development of high-throughput functional genomics technologies, including RNA sequencing, has enabled detailed analysis of the host transcriptome to M. bovis infection, particularly at the macrophage and peripheral blood level. In the present study, we have analysed the transcriptome of bovine whole peripheral blood samples collected at −1 week pre-infection and +1, +2, +6, +10, and +12 weeks post-infection time points. Differentially expressed genes were catalogued and evaluated at each post-infection time point relative to the −1 week pre-infection time point and used for the identification of putative candidate host transcriptional biomarkers for M. bovis infection. Differentially expressed gene sets were also used for examination of cellular pathways associated with the host response to M. bovis infection, construction of de novo gene interaction networks enriched for host differentially expressed genes, and time-series analyses to identify functionally important groups of genes displaying similar patterns of expression across the infection time course. A notable outcome of these analyses was identification of a 19-gene transcriptional biosignature of infection consisting of genes increased in expression across the time course from +1 week to +12 weeks post-infection.

Rapid discrimination between tuberculosis and sarcoidosis using next-generation sequencing

OBJECTIVES

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (MTB), has similar clinical, radiological, and histopathological characteristics to sarcoidosis (SA). Accurately distinguishing SA from TB remains a clinical challenge.

METHODS

A total of 44 TB patients and 47 SA patients who were clinically diagnosed using chest radiography, pathological examination, routine smear microscopy, and microbial culture were enrolled in this study. The MTB genome was captured and sequenced directly from tissue specimens obtained upon operation or biopsy, and the feasibility of next-generation sequencing (NGS) for the MTB genome in the differential diagnosis of TB from SA was evaluated.

RESULTS

Using a depth >10× and coverage >15% of the sequencing data, TB patients were identified via the NGS approach directly using operation or biopsy specimens without clinical pretreatment. The sensitivity, specificity, and concordance of the NGS method were 81.8% (36/44), 95.7% (45/47), and 89.0% (81/91), respectively (kappa = 0.78, 95% confidence interval 0.65-0.91; P<0.001).

CONCLUSIONS

This study established an improved NGS strategy for rapidly distinguishing patients with TB from those with SA and has potential clinical benefits.

Phagosome-regulated mTOR signalling during sarcoidosis granuloma biogenesis

INTRODUCTION

Sarcoidosis and tuberculosis are granulomatous pulmonary diseases characterised by heightened immune reactivity to Mycobacterium tuberculosis antigens. We hypothesised that an unsupervised analysis comparing the molecular characteristics of granulomas formed in response to M. tuberculosis antigens in patients with sarcoidosis or latent tuberculosis infection (LTBI) would provide novel insights into the pathogenesis of sarcoidosis.

METHODS

A genomic analysis identified differentially expressed genes in granuloma-like cell aggregates formed by sarcoidosis (n=12) or LTBI patients (n=5) in an established in vitro human granuloma model wherein peripheral blood mononuclear cells were exposed to M. tuberculosis antigens (beads coated with purified protein derivative) and cultured for 7 days. Pathway analysis of differentially expressed genes identified canonical pathways, most notably antigen processing and presentation via phagolysosomes, as a prominent pathway in sarcoidosis granuloma formation. The phagolysosomal pathway promoted mechanistic target of rapamycin complex 1 (mTORc1)/STAT3 signal transduction. Thus, granuloma formation and related immune mediators were evaluated in the absence or presence of various pre-treatments known to prevent phagolysosome formation (chloroquine) or phagosome acidification (bafilomycin A1) or directly inhibit mTORc1 activation (rapamycin).

RESULTS

In keeping with genomic analyses indicating enhanced phagolysosomal activation and predicted mTORc1 signalling, it was determined that sarcoidosis granuloma formation and related inflammatory mediator release was dependent upon phagolysosome assembly and acidification and mTORc1/S6/STAT3 signal transduction.

CONCLUSIONS

Sarcoidosis granulomas exhibit enhanced and sustained intracellular antigen processing and presentation capacities, and related phagolysosome assembly and acidification are required to support mTORc1 signalling to promote sarcoidosis granuloma formation.

Host transcriptional response to TB preventive therapy differentiates two sub-groups of IGRA-positive individuals

We hypothesised that individuals with immunological sensitisation to Mycobacterium tuberculosis (Mtb), conventionally regarded as evidence of latent tuberculosis infection (LTBI), would demonstrate binary responses to preventive therapy (PT), reflecting the differential immunological consequences of the sterilisation of viable infection in those with active Mtb infection versus no Mtb killing in those who did not harbour viable bacilli. We investigated longitudinal whole blood transcriptional profile responses to PT of Interferon gamma release assay (IGRA)-positive tuberculosis contacts and IGRA-negative, tuberculosis-unexposed controls. Longitudinal unsupervised clustering analysis with a subset of 474 most variable genes in antigen-stimulated blood separated the IGRA-positive participants into two distinct subgroups, one of which clustered with the IGRA-negative controls. 117 probes were differentially expressed over time between the two cluster groups, many of them associated with immunological pathways important in mycobacterial control. We contend that the differential host RNA response reflects lack of Mtb viability in the group that clustered with the IGRA-negative unexposed controls, and Mtb viability in the group (1/3 of IGRA-positives) that clustered away. Gene expression patterns in the blood of IGRA-positive individuals emerging during the course of PT, which reflect Mtb viability, could have major implications in the identification of risk of progression, treatment stratification and biomarker development.