Sex-specific blood-derived RNA biomarkers for childhood tuberculosis.

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

Effects of SNPs on TNF-α and IL-10 cytokine expression in TB and HIV patients in the Capricorn district, Limpopo Province, South Africa.

Background: The impact of Tuberculosis (TB) places an immense burden on the health care system. Infection with Human Immunodeficiency Virus (HIV) is a significant risk factor in the development and progression of TB disease. Single Nucleotide Polymorphisms (SNPs) in the promoter region of Interleukin-10 (IL-10) and Tumour Necrotic Factor-Alpha (TNF-α) may play a major role in the disease mechanism and understanding these mechanisms might prove to be a useful diagnostic tool in evaluating the immune regulation and progression of the disease. Objective: This study aimed to determine the relationship between cytokine levels and gene variants of Interleukin-10 and Tumour Necrotic Factor Alpha in TB and HIV-infected participants. Methods: Cytokine levels were determined by ELISA, and SNPs were determined by MassArray®. Results: The levels of TNF-α were higher in the TB group than the HIV (p < 0.001) and TB-HIV (p = 0.011) groups, but similar to the TNF-α levels in the control group. In the HIV group, IL-10 levels were higher than those of the TB (p < 0.001) and control groups (p = 0.039), whereas there was no difference between the IL-10 levels in the HIV and the TB-HIV infection groups. The ratio was determined and there were no differences between the four infection groups. In this study, no associations were detected between the circulating plasma levels of TNF-α and IL-10 and their genotypes. Conclusion: Our data showed that the gene variants were not associated with circulating plasma levels of TNF-α and IL-10 in our study population. A pro-inflammatory environment was found in the TB and TB-HIV groups, which is suggesting of bacterial clearance, while an anti-inflammatory environment was found in the HIV group, which suggests the suppression of viral replication.

Phylogenetic Survival Analysis.

Going back in time through a phylogenetic tree makes it possible to evaluate ancestral genomes and assess their potential to acquire key polymorphisms of interest over evolutionary time. Knowledge of this kind may allow for the emergence of key traits to be predicted and pre-empted from currently circulating strains in the future. Here, we present a novel genome-wide survival analysis and use the emergence of drug resistance in Mycobacterium tuberculosis as an example to demonstrate the potential and utility of the technique.

Betaine and I-LG may have a predictive value for ATB: A causal study in a large European population.

PURPOSE: To analyze the causal relationship between 486 human serum metabolites and the active tuberculosis (ATB) in European population. METHODS: In this study, the causal relationship between human serum metabolites and the ATB was analyzed by integrating the genome-wide association study (GWAS). The 486 human serum metabolites were used as the exposure variable, three different ATB GWAS databases in the European population were set as outcome variables, and single nucleotide polymorphisms were used as instrumental variables for Mendelian Randomization. The inverse variance weighting was estimated causality, the MR-Egger intercept to estimate horizontal pleiotropy, and the combined effects of metabolites were also considered in the meta-analysis. Furthermore, the web-based MetaboAnalyst 6.0 was engaged for enrichment pathway analysis, while R (version 4.3.2) software and Review Manager 5.3 were employed for statistical analysis. RESULTS: A total of 21, 17, and 19 metabolites strongly associated with ATB were found in the three databases after preliminary screening (P < 0.05). The intersecting metabolites across these databases included tryptophan, betaine, 1-linoleoylglycerol (1-monolinolein) (1-LG), 1-eicosatrienoylglycerophosphocholine, and oleoylcarnitine. Among them, betaine (I2 = 24%, P = 0.27) and 1-LG (I2 = 0%, P = 0.62) showed the lowest heterogeneity among the different ATB databases. In addition, the metabolic pathways of phosphatidylethanolamine biosynthesis (P = 0.0068), methionine metabolism (P = 0.0089), betaine metabolism (P = 0.0205) and oxidation of branched-chain fatty acids (P = 0.0309) were also associated with ATB. CONCLUSION: Betaine and 1-LG may be biomarkers or auxiliary diagnostic tools for ATB. They may provide new guidance for medical practice in the early diagnosis and surveillance of ATB. In addition, by interfering with phosphatidylethanolamine biosynthesis, methionine metabolism, betaine metabolism, oxidation of branched-chain fatty acids, and other pathways, it is helpful to develop new anti-tuberculosis drugs and explore the virulence or pathogenesis of ATB at a deeper level, providing an effective reference for future studies.

Data Harmonization Guidelines to Combine Multi-platform Genomic Data from Admixed Populations and Boost Power in Genome-Wide Association Studies.

Data harmonization involves combining data from multiple independent sources and processing the data to produce one uniform dataset. Merging separate genotypes or whole-genome sequencing datasets has been proposed as a strategy to increase the statistical power of association tests by increasing the effective sample size. However, data harmonization is not a widely adopted strategy due to the difficulties with merging data (including confounding produced by batch effects and population stratification). Detailed data harmonization protocols are scarce and are often conflicting. Moreover, data harmonization protocols that accommodate samples of admixed ancestry are practically non-existent. Existing data harmonization procedures must be modified to ensure the heterogeneous ancestry of admixed individuals is incorporated into additional downstream analyses without confounding results. Here, we propose a set of guidelines for merging multi-platform genetic data from admixed samples that can be adopted by any investigator with elementary bioinformatics experience. We have applied these guidelines to aggregate 1544 tuberculosis (TB) case-control samples from six separate in-house datasets and conducted a genome-wide association study (GWAS) of TB susceptibility. The GWAS performed on the merged dataset had improved power over analyzing the datasets individually and produced summary statistics free from bias introduced by batch effects and population stratification. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Processing separate datasets comprising array genotype data Alternate Protocol 1: Processing separate datasets comprising array genotype and whole-genome sequencing data Alternate Protocol 2: Performing imputation using a local reference panel Basic Protocol 2: Merging separate datasets Basic Protocol 3: Ancestry inference using ADMIXTURE and RFMix Basic Protocol 4: Batch effect correction using pseudo-case-control comparisons.

Circular RNAs in tuberculosis and lung cancer.

This review signifies the role of circular RNAs (circRNAs) in tuberculosis (TB) and lung cancer (LC), focusing on pathogenesis, diagnosis, and treatment. CircRNAs, a newly discovered type of non-coding RNA, have emerged as key regulators of gene expression and promising biomarkers in various bodily fluids due to their stability. The current review discusses circRNA biogenesis, highlighting their RNase-R resistance due to their loop forming structure, making them effective biomarkers. It details their roles in gene regulation, including splicing, transcription control, and miRNA interactions, and their impact on cellular processes and diseases. For LC, the review identifies circRNA dysregulation affecting cell growth, motility, and survival, and their potential as therapeutic targets and biomarkers. In TB, it addresses circRNAs' influence on host anti-TB immune responses, proposing their use as early diagnostic markers. The paper also explores the interplay between TB and LC, emphasizing circRNAs as dual biosignatures, and the necessity for differential diagnosis. It concludes that no single circRNA biomarker is universally applicable for both TB and LC. Ultimately, the review highlights the pivotal role of circRNAs in TB and LC, encouraging further research in biomarker identification and therapeutic development concomitant for both diseases.

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

BACKGROUND: Blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease. However, an unresolved issue is whether gene set enrichment analysis of the signature transcripts alone is sufficient for prediction and differentiation or whether it is necessary to use the original model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data and missing details about the original trained model. To facilitate the utilization of these signatures in TB research, comparisons between gene set scoring methods cross-data validation of original model implementations are needed. METHODS: We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both rrebuilt original models and gene set scoring methods. Existing gene set scoring methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, were used as alternative approaches to obtain the profile scores. The area under the ROC curve (AUC) value was computed to measure performance. Correlation analysis and Wilcoxon paired tests were used to compare the performance of enrichment methods with the original models. RESULTS: For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original models. 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 gene sets can distinguish patients with active TB disease from 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.

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.

History of tuberculosis disease is associated with genetic regulatory variation in Peruvians.

A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.

Mycobacterial biofilms: Understanding the genetic factors playing significant role in pathogenesis, resistance and diagnosis.

Even though the genus Mycobacterium is a diverse group consisting of a majority of environmental bacteria known as non-tuberculous mycobacteria (NTM), it also contains some of the deadliest pathogens (Mycobacterium tuberculosis) in history associated with chronic disease called tuberculosis (TB). Formation of biofilm is one of the unique strategies employed by mycobacteria to enhance their ability to survive in hostile conditions. Biofilm formation by Mycobacterium species is an emerging area of research with significant implications for understanding its pathogenesis and treatment of related infections, specifically TB. This review provides an overview of the biofilm-forming abilities of different species of Mycobacterium and the genetic factors influencing biofilm formation with a detailed focus on M. tuberculosis. Biofilm-mediated resistance is a significant challenge as it can limit antibiotic penetration and promote the survival of dormant mycobacterial cells. Key genetic factors promoting biofilm formation have been explored such as the mmpL genes involved in lipid transport and cell wall integrity as well as the groEL gene essential for mature biofilm formation. Additionally, biofilm-mediated antibiotic resistance and pathogenesis highlighting the specific niches, sites of infection along with the possible mechanisms of biofilm dissemination have been discussed. Furthermore, drug targets within mycobacterial biofilm and their role as potential biomarkers in the development of rapid diagnostic tools have been highlighted. The review summarises the current understanding of the complex nature of Mycobacterium biofilm and its clinical implications, paving the way for advancements in the field of disease diagnosis, management and treatment against its multi-drug resistant species.

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.

Thinking Beyond Disease Silos: Dysregulated Genes Common in Tuberculosis and Lung Cancer as Identified by Systems Biology and Machine Learning.

The traditional way of thinking about human diseases across clinical and narrow phenomics silos often masks the underlying shared molecular substrates across human diseases. One Health and planetary health fields particularly address such complexities and invite us to think across the conventional disease nosologies. For example, tuberculosis (TB) and lung cancer (LC) are major pulmonary diseases with significant planetary health implications. Despite distinct etiologies, they can coexist in a given community or patient. This is both a challenge and an opportunity for preventive medicine, diagnostics, and therapeutics innovation. This study reports a bioinformatics analysis of publicly available gene expression data, identifying overlapping dysregulated genes, downstream regulators, and pathways in TB and LC. Analysis of NCBI-GEO datasets (GSE83456 and GSE103888) unveiled differential expression of CEACAM6, MUC1, ADM, DYSF, PLOD2, and GAS6 genes in both diseases, with pathway analysis indicating association with lysine degradation pathway. Random forest, a machine-learning-based classification, achieved accuracies of 84% for distinguishing TB from controls and 83% for discriminating LC from controls using these specific genes. Additionally, potential drug targets were identified, with molecular docking confirming the binding affinity of warfarin to GAS6. Taken together, the present study speaks of the pressing need to rethink clinical diagnostic categories of human diseases and that TB and LC might potentially share molecular substrates. Going forward, planetary health and One Health scholarship are poised to cultivate new ways of thinking about diseases not only across medicine and ecology but also across traditional diagnostic conventions.

Pharmacogenetic Study of Drugs Affecting Mycobacterium tuberculosis.

BACKGROUND: Pharmacogenetic research has led to significant progress in understanding how genetic factors influence drug response in tuberculosis (TB) treatment. One ongoing challenge is the variable occurrence of adverse drug reactions in some TB patients. Previous studies have indicated that genetic variations in the N-acetyltransferase 2 (NAT2) and solute carrier organic anion transporter family member 1B1 (SLCO1B1) genes can impact the blood concentrations of the first-line anti-TB drugs isoniazid (INH) and rifampicin (RIF), respectively. This study aimed to investigate the influence of pharmacogenetic markers in the NAT2 and SLCO1B1 genes on TB treatment outcomes using whole-exome sequencing (WES) analysis. METHODS: DNA samples were collected from 30 healthy Iranian adults aged 18-40 years. The allelic frequencies of single-nucleotide polymorphisms (SNPs) in the NAT2 and SLCO1B1 genes were determined through WES. RESULTS: Seven frequent SNPs were identified in the NAT2 gene (rs1041983, rs1801280, rs1799929, rs1799930, rs1208, rs1799931, rs2552), along with 16 frequent SNPs in the SLCO1B1 gene (rs2306283, rs11045818, rs11045819, rs4149056, rs4149057, rs2291075, rs201722521, rs11045852, rs11045854, rs756393362, rs11045859, rs74064211, rs201556175, rs34671512, rs71581985, rs4149085). CONCLUSION: Genetic variations in NAT2 and SLCO1B1 can affect the metabolism of INH and RIF, respectively. A better understanding of the pharmacogenetic profile in the study population may facilitate the design of more personalized and effective TB treatment strategies. Further research is needed to directly correlate these genetic markers with clinical outcomes in TB patients.

SNPs in genes related to the repair of damage to DNA in clinical isolates of M. tuberculosis: A transversal and longitudinal approach.

The presence of SNPs in genes related to DNA damage repair in M. tuberculosis can trigger hypermutagenic phenotypes with a higher probability of generating drug resistance. The aim of this research was to compare the presence of SNPs in genes related to DNA damage repair between sensitive and DR isolates, as well as to describe the dynamics in the presence of SNPs in M. tuberculosis isolated from recently diagnosed TB patients of the state of Veracruz, Mexico. The presence of SNPs in the coding regions of 65 genes related to DNA damage repair was analyzed. Eighty-six isolates from 67 patients from central Veracruz state, Mexico, were sequenced. The results showed several SNPs in 14 genes that were only present in drug-resistant genomes. In addition, by following of 15 patients, it was possible to describe three different dynamics of appearance and evolution of non-synonymous SNPs in genes related to DNA damage repair: 1) constant fixed SNPs, 2) population substitution, and 3) gain of fixed SNPs. Further research is required to discern the biological significance of each of these pathways and their utility as markers of DR or for treatment prognosis.

[Research progress on Toll-like receptor 2 (TLR2) with Mycobacterium tuberculosis infection].

Toll-like receptor 2 (TLR2) is a pattern recognition receptor expressed on the surface of leukocytes. Various ligands can activate or inhibit TLR2, therefore regulating the inflammation and apoptosis of immune cells. Mycobacterium tuberculosis (MTB) typically parasitizes macrophages. Further, after infecting the body, MTB can interact with TLR2 on the surface of various immune cells, including macrophages, leading to the release of cytokines that can affect the state and proliferation of MTB in the body. Additional research is needed to understand the polymorphism of TLR2 at the molecular level. Current studies indicate that the majority of TLR2 polymorphisms are not associated with susceptibility to MTB infection. This review provides an overview of the researches related to TLR2 and its ligands, the immune regulation activities of TLR2 following MTB infection, and the association of TLR2 polymorphism with susceptibility to MTB.

Aberrant adaptive immune response underlies genetic susceptibility to tuberculosis.

Mycobacterium tuberculosis (Mtb) remains a major threat worldwide, although only a fraction of infected individuals develops tuberculosis (TB). TB susceptibility is shaped by multiple genetic factors, and we performed comparative immunological analysis of two mouse strains to uncover relevant mechanisms underlying susceptibility and resistance. C57BL/6 mice are relatively TB-resistant, whereas I/St mice are prone to develop severe TB, partly due to the MHC-II allelic variant that shapes suboptimal CD4+ T cell receptor repertoire. We investigated the repertoires of lung-infiltrating helper T cells and B cells at the progressed stage in both strains. We found that lung CD4+ T cell repertoires of infected C57BL/6 but not I/St mice contained convergent TCR clusters with functionally confirmed Mtb specificity. Transcriptomic analysis revealed a more prominent Th1 signature in C57BL/6, and expression of pro-inflammatory IL-16 in I/St lung-infiltrating helper T cells. The two strains also showed distinct Th2 signatures. Furthermore, the humoral response of I/St mice was delayed, less focused, and dominated by IgG/IgM isotypes, whereas C57BL/6 mice generated more Mtb antigen-focused IgA response. We conclude that the inability of I/St mice to produce a timely and efficient anti-Mtb adaptive immune responses arises from a suboptimal helper T cell landscape that also impacts the humoral response, leading to diffuse inflammation and severe disease.

Impact of PD-L1 Gene Polymorphisms and Interactions with Cooking with Solid Fuel Exposure on Tuberculosis.

INTRODUCTION: Given that PD-L1 is a crucial immune checkpoint in regulating T-cell responses, the aim of this study was to explore the impact of PD-L1 gene polymorphisms and the interaction with cooking with solid fuel on susceptibility to tuberculosis (TB) in Chinese Han populations. METHODS: A total of 503 TB patients and 494 healthy controls were enrolled in this case-control study. Mass spectrometry technology was applied to genotype rs2297136 and rs4143815 of PD-L1 genes. The associations between single nucleotide polymorphism (SNPs) and TB were assessed using unconditional logistic regression analysis. Marginal structural linear odds models were used to estimate the gene-environment interactions. RESULTS: Compared with genotype CC, genotypes GG and CG+GG at rs4143815 locus were significantly associated with susceptibility to TB (OR: 3.074 and 1.506, respectively, p < 0.05). However, no statistical association was found between rs2297136 SNP and TB risk. Moreover, the relative excess risk of interaction between rs4143815 of the PD-L1 gene and cooking with solid fuel was 2.365 (95% CI: 1.922-2.809), suggesting positive interactions with TB susceptibility. CONCLUSION: The rs4143815 polymorphism of the PD-L1 gene was associated with susceptibility to TB in Chinese Han populations. There were significantly positive interactions between rs4143815 and cooking with solid fuel.