Suppression of host gene expression is associated with latent TB infection: a possible diagnostic biomarker.

The World Health Organization End TB strategy aims for a 90% reduction of tuberculosis (TB) incidence by 2035. Systematic testing and treatment of latent TB infection (LTBI) among contacts of active TB patients is recommended as one of the ways to curtail TB incidence. However, there is a shortage of tools to accurately diagnose LTBI. We assessed the appropriateness of whole blood host transcriptomic markers (TM) to diagnose LTBI among household contacts of bacteriologically confirmed index cases compared to HIV negative healthy controls (HC). QuantiFERON-TB Gold Plus Interferon gamma release assay (IGRA) and reverse-transcriptase quantitative PCR were used to determine LTBI and quantify TM expression respectively. Association between TM expression and LTBI was evaluated by logistic regression modelling. A total of 100 participants, 49 TB exposed (TBEx) household contacts and 51 HC, were enrolled. Twenty-five (51%) TBEx individuals tested positive by IGRA, and were denoted as LTBI individuals, and 37 (72.5%) HC were IGRA-negative. Expression of 11 evaluated TM was significantly suppressed among LTBI compared to HC. Out of the 11 TM, ZNF296 and KLF2 expression were strongly associated with LTBI and successfully differentiated LTBI from HC. Paradoxically, 21 (49%) TBEx participants who tested IGRA negative exhibited the same pattern of suppressed TM expression as IGRA positive (LTBI-confirmed individuals). Results suggest that suppression of gene expression underlies LTBI and may be a more sensitive diagnostic biomarker than standard-of-care IGRA.

Autophagy-related molecular clusters identified as indicators for distinguishing active and latent TB infection in pediatric patients.

BACKGROUND: Autophagy is crucial for controlling the manifestation of tuberculosis. This study intends to discover autophagy-related molecular clusters as biomarkers for discriminating between latent tuberculosis (LTBI) and active tuberculosis (ATB) in children through gene expression profile analysis. METHODS: The expression of autophagy modulators was examined in pediatric patients with LTBI and ATB utilizing public datasets from the Gene Expression Omnibus (GEO) collection (GSE39939 and GSE39940). RESULTS: In a training dataset (GSE39939), patients with LTBI and ATB exhibited the expression of autophagy-related genes connected with their active immune responses. Two molecular clusters associated with autophagy were identified. Compared to Cluster 1, Cluster 2 was distinguished through decreased adaptive cellular immune response and enhanced inflammatory activation, according to single-sample gene set enrichment analysis (ssGSEA). Per the study of gene set variation, Cluster 2's differentially expressed genes (DEGs) played a role in synthesizing transfer RNA, DNA repair and recombination, and primary immunodeficiency. The peak variation efficiency, root mean square error, and area under the curve (AUC) (AUC = 0.950) were all lowered in random forest models. Finally, a seven-gene-dependent random forest profile was created utilizing the CD247, MAN1C1, FAM84B, HSZFP36, SLC16A10, DTX3, and SIRT4 genes, which performed well against the validation dataset GSE139940 (AUC = 0.888). The nomogram calibration and decision curves performed well in identifying ATB from LTBI. CONCLUSIONS: In summary, according to the present investigation, autophagy and the immunopathology of TB might be correlated. Furthermore, this investigation established a compelling prediction expression profile for measuring autophagy subtype development risks, which might be employed as possible biomarkers in children to differentiate ATB from LTBI.

Whole-transcriptome sequencing of phagocytes reveals a ceRNA network contributing to natural resistance to tuberculosis infection.

Tuberculosis (TB) is a major fatal infectious disease globally, exhibiting high morbidity rates and impacting public health and other socio-economic factors. However, some individuals are resistant to TB infection and are referred to as "Resisters". Resisters remain uninfected even after exposure to high load of Mycobacterium tuberculosis (Mtb). To delineate this further, this study aimed to investigate the factors and mechanisms influencing the Mtb resistance phenotype. We assayed the phagocytic capacity of peripheral blood mononuclear cells (PBMCs) collected from Resisters, patients with latent TB infection (LTBI), and patients with active TB (ATB), following infection with fluorescent Mycobacterium bovis Bacillus Calmette-Guérin (BCG). Phagocytosis was stronger in PBMCs from ATB patients, and comparable in LTBI patients and Resisters. Subsequently, phagocytes were isolated and subjected to whole transcriptome sequencing and small RNA sequencing to analyze transcriptional expression profiles and identify potential targets associated with the resistance phenotype. The results revealed that a total of 277 mRNAs, 589 long non-coding RNAs, 523 circular RNAs, and 35 microRNAs were differentially expressed in Resisters and LTBI patients. Further, the endogenous competitive RNA (ceRNA) network was constructed from differentially expressed genes after screening. Bioinformatics, statistical analysis, and quantitative real-time polymerase chain reaction were used for the identification and validation of potential crucial targets in the ceRNA network. As a result, we obtained a ceRNA network that contributes to the resistance phenotype. TCONS_00034796-F3, ENST00000629441-DDX43, hsa-ATAD3A_0003-CYP17A1, and XR_932996.2-CERS1 may be crucial association pairs for resistance to TB infection. Overall, this study demonstrated that the phagocytic capacity of PBMCs was not a determinant of the resistance phenotype and that some non-coding RNAs could be involved in the natural resistance to TB infection through a ceRNA mechanism.

Transcriptional profiling of human peripheral blood mononuclear cells in household contacts of pulmonary tuberculosis patients provides insights into mechanisms of Mycobacterium tuberculosis control and elimination.

Household contacts (HHCs) of patients with active tuberculosis (ATB) are at higher risk of Mycobacterium tuberculosis (M. tuberculosis) infection. However, the immune factors responsible for different defense responses in HHCs are unknown. Hence, we aimed to evaluate transcriptome signatures in human peripheral blood mononuclear cells (PBMCs) of HHCs to aid risk stratification. We recruited 112 HHCs of ATB patients and followed them for 6 years. Among the HHCs, only 2 developed ATB, while the remaining HHCs were classified into three groups: (1) HHC-1 group (n = 23): HHCs with consistently positive T-SPOT.TB test, negative chest radiograph, and no clinical symptoms or evidence of ATB during the 6-year follow-up period; (2) HHC-2 group (n = 15): HHCs with an initial positive T-SPOT result that later became negative without evidence of ATB; (3) HHC-3 group (n = 14): HHCs with a consistently negative T-SPOT.TB test and no clinical or radiological evidence of ATB. HHC-2 and HHC-3 were combined as HHC-23 group for analysis. RNA sequencing (RNA-seq) in PBMCs, with and without purified protein derivative (PPD) stimulation, identified significant differences in gene signatures between HHC-1 and HHC-23. Gene ontology analysis revealed functions related to bacterial pathogens, leukocyte chemotaxis, and inflammatory and cytokine responses. Modules associated with clinical features in the HHC-23 group were linked to the IL-17 signaling pathway, ferroptosis, complement and coagulation cascades, and the TNF signaling pathway. Validation using real-time PCR confirmed key genes like ATG-7, CXCL-3, and TNFRSF1B associated with infection outcomes in HHCs. Our research enhances understanding of disease mechanisms in HHCs. HHCs with persistent latent tuberculosis infection (HHC-1) showed significantly different gene expression compared to HHCs with no M. tuberculosis infection (HHC-23). These findings can help identify HHCs at risk of developing ATB and guide targeted public health interventions.

A diagnostic model for distinguishing between active tuberculosis and latent tuberculosis infection based on the blood expression profiles of autophagy-related genes.

BACKGROUND: Autophagy is closely involved in the control of mycobacterial infection. OBJECTIVES: Here, a diagnostic model was developed using the levels of autophagy-related genes (ARGs) in the blood to differentiate active tuberculosis (ATB) and latent tuberculosis infection (LTBI). DESIGN: Secondary data analysis of three prospective cohorts. METHODS: The expression of ARGs in patients with ATB and LTBI were analyzed using the GSE37250, GSE19491, and GSE28623 datasets from the GEO database. RESULTS: Twenty-two differentially expressed ARGs were identified in the training dataset GSE37250. Using least absolute shrinkage and selection operator and multivariate logistic regression, three ARGs (FOXO1, CCL2, and ITGA3) were found that were positively associated with adaptive immune-related lymphocytes and negatively associated with myeloid and inflammatory cells. A nomogram was constructed using the three ARGs. The accuracy, consistency, and clinical relevance of the nomogram were evaluated using receiver operating characteristic curves, the C-index, calibration curves, and validation in the datasets GSE19491 and GSE28623. The nomogram showed good predictive performance. CONCLUSION: The nomogram was able to accurately differentiate between ATB and LTBI patients. These findings provide evidence for future study on the pathology of autophagy in tuberculosis infection.

Association of Cytokine Gene Polymorphisms and Their Impact on Active and Latent Tuberculosis in Brazil's Amazon Region.

Some genetic variations in cytokine genes can alter their expression and influence the evolution of Mycobacterium tuberculosis (Mtb) infection. This study aimed to investigate the association of polymorphisms in cytokine genes and variability in plasma levels of cytokines with the development of tuberculosis (TB) and latent tuberculosis infection (LTBI). Blood samples from 245 patients with TB, 80 with LTBI, and healthy controls (n = 100) were included. Genotyping of the IFNG +874A/T, IL6 -174G/C, IL4 -590C/T, and IL10 -1082A/G polymorphisms was performed by real-time PCR, and cytokine levels were determined by flow cytometry. Higher frequencies of genotypes AA (IFNG +874A/T), GG (IL6 -174G/C), TT (IL4 -590C/T), and GG (IL10 -1082A/G) were associated with an increased risk of TB compared to that of LTBI (p = 0.0027; p = 0.0557; p = 0.0286; p = 0.0361, respectively) and the control (p = <0.0001, p = 0.0021; p = 0.01655; p = 0.0132, respectively). In combination, the A allele for IFNG +874A/T and the T allele for IL4 -590C/T were associated with a higher chance of TB (p = 0.0080; OR = 2.753 and p < 0.0001; OR = 3.273, respectively). The TB group had lower levels of IFN-γ and higher concentrations of IL-6, IL-4, and IL-10. Cytokine levels were different between the genotypes based on the polymorphisms investigated (p < 0.05). The genotype and wild-type allele for IFNG +874A/T and the genotype and polymorphic allele for IL4 -590C/T appear to be more relevant in the context of Mtb infection, which has been associated with the development of TB among individuals infected by the bacillus and with susceptibility to active infection but not with susceptibility to latent infection.

Type I interferons and Mycobacterium tuberculosis whole cell lysate induce distinct transcriptional responses in M. tuberculosis infection.

Type I interferon (IFN)-induced genes have the potential for distinguishing active tuberculosis (ATB) from latent TB infection (LTBI) and healthy controls (HC), monitoring treatment, and detection of individuals at risk of progression to active disease. We examined the differential effects of IFN-α, IFN-ß and Mycobacterium tuberculosis whole cell lysate (Mtb WCL) stimulation on the expression of selected IFN-stimulated genes in peripheral blood mononuclear cells from individuals with either LTBI, ATB, and healthy controls. Stimulation with IFN-α and IFN-ß induced a higher expression of the interrogated genes while Mtb WCL stimulation induced expression similar to that observed at baseline, with the exception of IL-1A and IL-1B genes that were downregulated. The expression of IFN-α-induced FCGR1A gene, IFN-ß-induced FCGR1A, FCGR1B, and SOCS3 genes, and Mtb WCL-induced IFI44, IFI44L, IFIT1, and IFITM3 genes differed significantly between LTBI and ATB. These findings suggest stimulation-driven gene expression patterns could potentially discriminate LTBI and ATB. Mechanistic studies are necessary to define the processes through which distinct type I IFNs and downstream ISGs determine infection outcomes and identify potential host-directed therapeutic strategies.

Identification of cuproptosis-related molecular subtypes as a biomarker for differentiating active from latent tuberculosis in children.

BACKGROUND: Cell death plays a crucial role in the progression of active tuberculosis (ATB) from latent infection (LTBI). Cuproptosis, a novel programmed cell death, has been reported to be associated with the pathology of various diseases. We aimed to identify cuproptosis-related molecular subtypes as biomarkers for distinguishing ATB from LTBI in pediatric patients. METHOD: The expression profiles of cuproptosis regulators and immune characteristics in pediatric patients with ATB and LTBI were analyzed based on GSE39939 downloaded from the Gene Expression Omnibus. From the 52 ATB samples, we investigated the molecular subtypes based on differentially expressed cuproptosis-related genes (DE-CRGs) via consensus clustering and related immune cell infiltration. Subtype-specific differentially expressed genes (DEGs) were found using the weighted gene co-expression network analysis. The optimum machine model was then determined by comparing the performance of the eXtreme Gradient Boost (XGB), the random forest model (RF), the general linear model (GLM), and the support vector machine model (SVM). Nomogram and test datasets (GSE39940) were used to verify the prediction accuracy. RESULTS: Nine DE-CRGs (NFE2L2, NLRP3, FDX1, LIPT1, PDHB, MTF1, GLS, DBT, and DLST) associated with active immune responses were ascertained between ATB and LTBI patients. Two cuproptosis-related molecular subtypes were defined in ATB pediatrics. Single sample gene set enrichment analysis suggested that compared with Subtype 2, Subtype 1 was characterized by decreased lymphocytes and increased inflammatory activation. Gene set variation analysis showed that cluster-specific DEGs in Subtype 1 were closely associated with immune and inflammation responses and energy and amino acids metabolism. The SVM model exhibited the best discriminative performance with a higher area under the curve (AUC = 0.983) and relatively lower root mean square and residual error. A final 5-gene-based (MAN1C1, DKFZP434N035, SIRT4, BPGM, and APBA2) SVM model was created, demonstrating satisfactory performance in the test datasets (AUC = 0.905). The decision curve analysis and nomogram calibration curve also revealed the accuracy of differentiating ATB from LTBI in children. CONCLUSION: Our study suggested that cuproptosis might be associated with the immunopathology of Mycobacterium tuberculosis infection in children. Additionally, we built a satisfactory prediction model to assess the cuproptosis subtype risk in ATB, which can be used as a reliable biomarker for the distinguishment between pediatric ATB and LTBI.

Predicting the Progress of Tuberculosis by Inflammatory Response-Related Genes Based on Multiple Machine Learning Comprehensive Analysis.

Background: Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis, affects approximately one-quarter of the global population and is considered one of the most lethal infectious diseases worldwide. The prevention of latent tuberculosis infection (LTBI) from progressing into active tuberculosis (ATB) is crucial for controlling and eradicating TB. Unfortunately, currently available biomarkers have limited effectiveness in identifying subpopulations that are at risk of developing ATB. Hence, it is imperative to develop advanced molecular tools for TB risk stratification. Methods: The TB datasets were downloaded from the GEO database. Three machine learning models, namely LASSO, RF, and SVM-RFE, were used to identify the key characteristic genes related to inflammation during the progression of LTBI to ATB. The expression and diagnostic accuracy of these characteristic genes were subsequently verified. These genes were then used to develop diagnostic nomograms. In addition, single-cell expression clustering analysis, immune cell expression clustering analysis, GSVA analysis, immune cell correlation, and immune checkpoint correlation of characteristic genes were conducted. Furthermore, the upstream shared miRNA was predicted, and a miRNA-genes network was constructed. Candidate drugs were also analyzed and predicted. Results: In comparison to LTBI, a total of 96 upregulated and 26 downregulated genes related to the inflammatory response were identified in ATB. These characteristic genes have demonstrated excellent diagnostic performance and significant correlation with many immune cells and immune sites. The results of the miRNA-genes network analysis suggested a potential role of hsa-miR-3163 in the molecular mechanism of LTBI progressing into ATB. Moreover, retinoic acid may offer a potential avenue for the prevention of LTBI progression to ATB and for the treatment of ATB. Conclusion: Our research has identified key inflammatory response-related genes that are characteristic of LTBI progression to ATB and hsa-miR-3163 as a significant node in the molecular mechanism of this progression. Our analyses have demonstrated the excellent diagnostic performance of these characteristic genes and their significant correlation with many immune cells and immune checkpoints. The CD274 immune checkpoint presents a promising target for the prevention and treatment of ATB. Furthermore, our findings suggest that retinoic acid may have a role in preventing LTBI from progressing to ATB and in treating ATB. This study provides a new perspective for differential diagnosis of LTBI and ATB and may uncover potential inflammatory immune mechanisms, biomarkers, therapeutic targets, and effective drugs in the progression of LTBI into ATB.

Differentially expressed transcript isoforms associate with resistance to tuberculin skin test and interferon gamma release assay conversion.

BACKGROUND: A mechanistic understanding of uncommon immune outcomes such as resistance to infection has led to the development of novel therapies. Using gene level analytic methods, we previously found distinct monocyte transcriptional responses associated with resistance to Mycobacterium tuberculosis (Mtb) infection defined as persistently negative tuberculin skin test (TST) and interferon gamma release assay (IGRA) reactivity among highly exposed contacts (RSTR phenotype). OBJECTIVE: Using transcript isoform analyses, we aimed to identify novel RSTR-associated genes hypothesizing that previous gene-level differential expression analysis obscures isoform-specific differences that contribute to phenotype. MATERIALS AND METHODS: Monocytes from 49 RSTR versus 52 subjects with latent Mtb infection (LTBI) were infected with M. tuberculosis (H37Rv) or left unstimulated (media) prior to RNA isolation and sequencing. RSTR-associated gene expression was then identified using differential transcript isoform analysis. RESULTS: We identified 81 differentially expressed transcripts (DETs) in 70 genes (FDR <0.05) comparing RSTR and LTBI phenotypes with the majority (n = 79 DETs) identified under Mtb-stimulated conditions. Seventeen of these genes were previously identified with gene-level bulk RNAseq analyses including genes in the IFNγ response that had increased expression among LTBI subjects, findings consistent with a clinical phenotype based on IGRA reactivity. Among the subset of 23 genes with positive differential expression among Mtb-infected RSTR monocytes, 13 were not previously identified. These novel DET genes included PDE4A and ZEB2, which each had multiple DETs with higher expression among RSTR subjects, and ACSL4 and GAPDH that each had a single transcript isoform associated with RSTR. CONCLUSION AND LIMITATIONS: Transcript isoform-specific analyses identify transcriptional associations, such as those associated with resistance to TST/IGRA conversion, that are obscured when using gene-level approaches. These findings should be validated with additional RSTR cohorts and whether the newly identified candidate resistance genes directly influence the monocyte Mtb response requires functional study.

Evaluation of IFIT3 and ORM1 as Biomarkers for Discriminating Active Tuberculosis from Latent Infection.

OBJECTIVE: Current commercially available immunological tests cannot be used for discriminating active tuberculosis (TB) from latent TB infection. To evaluate the value of biomarker candidates in the diagnosis of active TB, this study aimed to identify differentially expressed genes in peripheral blood mononuclear cells (PBMCs) between patients with active TB and individuals with latent TB infection by transcriptome sequencing. METHODS: The differentially expressed genes in unstimulated PBMCs and in Mycobacterium tuberculosis (Mtb) antigen-stimulated PBMCs from patients with active TB and individuals with latent TB infection were identified by transcriptome sequencing. Selected candidate genes were evaluated in cohorts consisting of 110 patients with TB, 30 individuals with latent TB infections, and 50 healthy controls by quantitative real-time RT-PCR. Receiver operating characteristic (ROC) curve analysis was performed to calculate the diagnostic value of the biomarker candidates. RESULTS: Among the differentially expressed genes in PBMCs without Mtb antigen stimulation, interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) had the highest area under curve (AUC) value (0.918, 95% CI: 0.852-0.984, P<0.0001) in discriminating patients with active TB from individuals with latent TB infection, with a sensitivity of 91.86% and a specificity of 84.00%. In Mtb antigen-stimulated PBMCs, orosomucoid 1 (ORM1) had a high AUC value (0.833, 95% CI: 0.752-0.915, P<0.0001), with a sensitivity of 81.94% and a specificity of 70.00%. CONCLUSION: IFIT3 and ORM1 might be potential biomarkers for discriminating active TB from latent TB infection.

Circulating mitochondrial cell-free DNA dynamics in patients with mycobacterial pulmonary infections: Potential for a novel biomarker of disease.

Objectives: Human mitochondrial cell-free DNA (Mt-cfDNA) may serve as a useful biomarker for infectious processes. We investigated Mt-cfDNA dynamics in patients with pulmonary mycobacterial infections to determine if this novel biomarker could be used to differentiate disease states and severity. Methods: Patients with pulmonary tuberculosis (PTB), latent tuberculosis infection (LTBI), and nontuberculous mycobacterial-lung disease (NTM-LD) were enrolled at a tertiary care hospital in Taiwan between June 2018 and August 2021. Human Mt-cfDNA and nuclear-cfDNA (Nu-cfDNA) copy numbers were estimated by quantitative polymerase chain reaction. Variables associated with PTB and 2-month sputum culture-positivity, indicating poor treatment response, were assessed using logistic regression. Results: Among 97 patients with PTB, 64 with LTBI, and 51 with NTM-LD, Mt-cfDNA levels were higher in patients with PTB than in LTBI (p=0.001) or NTM-LD (p=0.006). In the Mycobacterium tuberculosis-infected population, Mt-cfDNA levels were highest in smear-positive PTB patients, followed by smear-negative PTB (p<0.001), and were lowest in LTBI persons (p=0.009). A Mt-cfDNA, but not Nu-cfDNA, level higher than the median helped differentiate culture-positive PTB from culture-negative PTB and LTBI (adjusted OR 2.430 [95% CI 1.139-5.186], p=0.022) and differentiate PTB from NTM-LD (adjusted OR 4.007 [1.382-12.031], p=0.011). Mt-cfDNA levels decreased after 2 months of treatment in PTB patients (p=0.010). A cutoff Mt-cfDNA level greater than 62.62 x 106 copies/µL-plasma was associated with a 10-fold risk of 2-month culture-positivity (adjusted OR 9.691 [1.046-89.813], p=0.046). Conclusion: Elevated Mt-cfDNA levels were associated with PTB disease and failed sputum conversion at 2 months in PTB patients, and decreased after treatment.

Investigation of miRNA and cytokine expressions in latent tuberculosis infection and active tuberculosis.

BACKGROUND: In tuberculsosis (TB), miRNA has been used as a biomarker to distinguish between healthy individuals and TB patients. The aim of this study was to investigate (i) the association of the miRNA and cytokine expression levels, the course of tuberculosis infection, clinical forms and response to treatment, and (ii) the effects of genotypic features of bacteria on the course of tuberculosis and the relationship between miRNA and cytokine expressions and bacterial genotypes. METHODS: A total of 200 cases (100: culture positive active tuberculosis, 50: quantiferon positive latent tuberculosis infection and 50: quantiferon negative healthy controls) were included in the study. For the tuberculosis group at the time of admission and after treatment, for the latent tuberculosis infection and healthy control groups at the time of admission, miRNA and cytokine expressions were determined. Genotyping of M.tuberculosis isolates was performed by spoligotyping method. RESULTS: While, in the comparison of miRNA expressions between the pretreatment patient group and the healthy control group, there was a statistically significant decrease in the expression of miR-454-3p, miR-15a-5p, miR-590-5p, miR-381, and miR-449a in the Pulmonary TB group, there was no significant change in miRNA expression in extrapulmonary TB patients. When the cytokine expressions of the patient group and the healthy control group were compared before treatment, the expressions of all cytokines in the patient group decreased. However, the only cytokine that showed a significantly lower expression was IL12A in PTB patients. DISCUSSION: There is no significant relationship between the clinical course of the disease, cytokine and miRNA expression, and the genotype of the bacteria.

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.

Malnutrition leads to increased inflammation and expression of tuberculosis risk signatures in recently exposed household contacts of pulmonary tuberculosis.

Background: Most individuals exposed to Mycobacterium tuberculosis (Mtb) develop latent tuberculosis infection (LTBI) and remain at risk for progressing to active tuberculosis disease (TB). Malnutrition is an important risk factor driving progression from LTBI to TB. However, the performance of blood-based TB risk signatures in malnourished individuals with LTBI remains unexplored. The aim of this study was to determine if malnourished and control individuals had differences in gene expression, immune pathways and TB risk signatures. Methods: We utilized data from 50 tuberculin skin test positive household contacts of persons with TB - 18 malnourished participants (body mass index [BMI] < 18.5 kg/m2) and 32 controls (individuals with BMI ≥ 18.5 kg/m2). Whole blood RNA-sequencing was conducted to identify differentially expressed genes (DEGs). Ingenuity Pathway Analysis was applied to the DEGs to identify top canonical pathways and gene regulators. Gene enrichment methods were then employed to score the performance of published gene signatures associated with progression from LTBI to TB. Results: Malnourished individuals had increased activation of inflammatory pathways, including pathways involved in neutrophil activation, T-cell activation and proinflammatory IL-1 and IL-6 cytokine signaling. Consistent with known association of inflammatory pathway activation with progression to TB disease, we found significantly increased expression of the RISK4 (area under the curve [AUC] = 0.734) and PREDICT29 (AUC = 0.736) progression signatures in malnourished individuals. Conclusion: Malnourished individuals display a peripheral immune response profile reflective of increased inflammation and a concomitant increased expression of risk signatures predicting progression to TB. With validation in prospective clinical cohorts, TB risk biomarkers have the potential to identify malnourished LTBI for targeted therapy.

Aberrant expression of long non-coding RNAs in peripheral blood mononuclear cells response to tuberculosis in children.

We aimed to identify long non-coding RNAs (lncRNAs) aberrantly expressed in peripheral blood mononuclear cells (PBMCs) triggered by active tuberculosis (ATB), latent tuberculosis infection (LTBI), and healthy controls (HC). We examined lncRNAs expression in PBMCs isolated from children with ATB and LTBI, and from HC using RNA sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to explore the biological processes and signaling pathways of aberrantly expressed mRNAs. A total of 348 and 205 lncRNAs were differentially expressed in the ATB and LTBI groups, respectively, compared to the HC group. Compared to the LTBI group, 125 lncRNAs were differentially expressed in the ATB group. Compared to the HC group, 2317 mRNAs were differentially expressed in the ATB group, and 1093 mRNAs were differentially expressed in the LTBI group. Compared to the LTBI group, 2328 mRNAs were differentially expressed in the ATB group. The upregulated mRNAs were mainly enriched in neutrophil activation, neutrophil-mediated biological processes, and positive regulation of immune response in tuberculosis (TB), whereas the downregulated mRNAs were enriched in signaling pathways and structural processes, such as the Wnt signaling pathway and rDNA heterochromatin assembly. This is the first study on the differential expression of lncRNAs in PBMCs of children with TB. We identified significant differences in the expression profiles of lncRNAs and mRNAs in the PBMCs of children with ATB, LTBI, and HC, which has important implications for exploring lncRNAs as novel biomarkers for the diagnosis of TB. In addition, further experimental identification and validation of lncRNA roles could help elucidate the underlying mechanisms of Mycobacterium tuberculosis infection in children.

Polymorphisms of the BCL2 gene associated with susceptibility to tuberculosis.

Although tuberculosis (TB) is a serious public health concern, we still don't understand why only 10% of people infected will develop the disease. Apoptosis plays a role in the interaction of Mycobacterium tuberculosis (Mtb) with the human host and it may be modified by subtle alterations in the B-cell lymphoma 2 (BCL2) gene, an anti-apoptotic regulatory element. Therefore, we investigated whether there is an association between BCL2 polymorphisms and susceptibility to TB by analyzing 130 TB cases, 108 subjects with latent TB infection (LTBI), and 163 healthy controls (HC). Logistic regression was used to calculate odds ratios (ORs) and 95% confidential intervals (95% CIs) for possible associations between single nucleotide polymorphisms (SNPs) in BCL2 and the risk of tuberculosis. We found that the G allele of rs80030866 (OR=0.62, 95%CI:0.42-0.91, P=0.015), and also the G allele of rs9955190 (OR=0.58, 95%CI:0.38-0.88, P=0.011) were less frequent in the TB group compared with the LTBI group. In addition, individuals with rs2551402 CC genotype were more likely to have LTBI than those with AA genotype (OR=2.166, 95%CI:1.046-4.484, P=0.037). Our study suggests that BCL2 gene polymorphisms may be correlated with susceptibility to both TB and LTBI.

Gene expression profiling identifies candidate biomarkers for new latent tuberculosis infections. A cohort study.

OBJECTIVE: To determine the gene expression profile in individuals with new latent tuberculosis infection (LTBI), and to compare them with people with active tuberculosis (TB) and those exposed to TB but not infected. DESIGN: A prospective cohort study. Recruitment and follow-up were conducted between September 2016 to December 2018. Gene expression and data processing and analysis from April 2019 to April 2021. SETTING: Two male Colombian prisons. PARTICIPANTS: 15 new tuberculin skin test (TST) converters (negative TST at baseline that became positive during follow-up), 11 people that continued with a negative TST after two years of follow-up, and 10 people with pulmonary ATB. MAIN OUTCOME MEASURES: Gene expression profile using RNA sequencing from PBMC samples. The differential expression was assessed using the DESeq2 package in Bioconductor. Genes with |logFC| >1.0 and an adjusted p-value < 0.1 were differentially expressed. We analyzed the differences in the enrichment of KEGG pathways in each group using InterMiner. RESULTS: The gene expression was affected by the time of incarceration. We identified group-specific differentially expressed genes between the groups: 289 genes in people with a new LTBI and short incarceration (less than three months of incarceration), 117 in those with LTBI and long incarceration (one or more years of incarceration), 26 in ATB, and 276 in the exposed but non-infected individuals. Four pathways encompassed the largest number of down and up-regulated genes among individuals with LTBI and short incarceration: cytokine signaling, signal transduction, neutrophil degranulation, and innate immune system. In individuals with LTBI and long incarceration, the only enriched pathway within up-regulated genes was Emi1 phosphorylation. CONCLUSIONS: Recent infection with MTB is associated with an identifiable RNA pattern related to innate immune system pathways that can be used to prioritize LTBI treatment for those at greatest risk for developing active TB.

Whole transcriptome sequencing reveals neutrophils' transcriptional landscape associated with active tuberculosis.

Neutrophils have been recognized to play an important role in the pathogenesis of tuberculosis in recent years. Interferon-induced blood transcriptional signatures in ATB are predominantly driven by neutrophils. In this study, we performed global RNA-seq on peripheral blood neutrophils from active tuberculosis patients (ATB, n=15); latent tuberculosis infections (LTBI, n=22); and healthy controls (HC, n=21). The results showed that greater perturbations of gene expression patterns happened in neutrophils from ATB individuals than HC or those with LTBI, and a total of 344 differentially expressed genes (DEGs) were observed. Functional enrichment analysis showed that besides the interferon signaling pathway, multiple pattern recognition receptor pathways were significantly activated in ATB, such as NOD-like receptors and Toll-like receptors. Meanwhile, we also observed that the expression of genes related to endocytosis, secretory granules, and neutrophils degranulation were downregulated. Our data also showed that the NF-κB signaling pathway might be inhibited in patients with ATB, which could increase Mycobacterium tuberculosis survival and lead to active tuberculosis status. Furthermore, we validated the accuracy of some differentially expressed genes in an independent cohort using quantitative PCR, and obtained three novel genes (RBM3, CSRNP1, SRSF5) with the ability to discriminate active tuberculosis from LTBI and HC.

Comprehensive identification of immuno-related transcriptional signature for active pulmonary tuberculosis by integrated analysis of array and single cell RNA-seq.

BACKGROUND: Tuberculosis (TB) continues to be a major cause of morbidity and mortality worldwide. However, the molecular mechanism underlying immune response to human infection with Mycobacterium tuberculosis (Mtb) remains unclear. Assessing changes in transcript abundance in blood between health and disease on a genome-wide scale affords a comprehensive view of the impact of Mtb infection on the host defense and a reliable way to identify novel TB biomarkers. METHODS: We combined expression profiling by array and single cell RNA-sequencing (scRNA-seq) via 10X Genomics platform to better illustrate the immuno-related transcriptional signature of TB and explore potential diagnostic markers for differentiating TB from latent tuberculosis infection (LTBI) and healthy control (HC). FINDINGS: Pathway analysis based on differential expressed genes (DEGs) revealed that immune transcriptional profiling could effectively differ TB with LTBI and HC. Following WGCNA and PPI network analysis based on DEGs, we screened out three key immuno-related hub genes (ADM, IFIT3 and SERPING1) highly associated with TB. Further validation found only ADM expression significantly increased in TB patients in both adult and children's datasets. By comparing the scRNA-seq datasets from TB, LTBI and HC, we observed a remarkable elevated expression level and proportion of ADM in TB Myeloid cells, further supporting that ADM expression changes could distinguish patients with TB from LTBI and HC. Besides, the hsa-miR-24-3p-NEAT1-ADM-CEBPB regulation pathway might be one of the critical networks regulating the pathogenesis of TB. Although further investigation in a larger cohort is warranted, we provide useful and novel insight to explore the potential candidate genes for TB diagnosis and intervention. INTERPRETATION: We propose that the expression of ADM in peripheral blood could be used as a novel biomarker for differentiating TB with LTBI and HC.