Search Results (142)

Background and Objectives: Blood-borne inflammatory ratios have been proposed as inexpensive prognostic tools across a range of diseases, but their role in pulmonary tuberculosis (TB) remains uncertain. In this retrospective case–control analysis, we explored whether composite indices derived from routine haematology—namely the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), the systemic immune–inflammation index (SII) and a novel CRP–Fibrinogen Index (CFI)—could enhance risk stratification beyond established cytokine measurements among Romanian adults with culture-confirmed pulmonary T. Materials and Methods: Data were drawn from 80 consecutive TB in-patients and 50 community controls. Full blood counts, C-reactive protein, fibrinogen, and four multiplex cytokines were extracted from electronic records, and composite indices were calculated according to standard formulas. The primary outcomes were in-hospital mortality within 90 days and length of stay (LOS). Results: Among TB patients, the median NLR was 3.70 (IQR 2.54–6.14), PLR was 200 (140–277) and SII was 1.36 × 10⁶ µL⁻¹ (0.74–2.34 × 10⁶), compared with 1.8 (1.4–2.3), 117 (95–140) and 0.46 × 10⁶ µL⁻¹ (0.30–0.60 × 10⁶) in controls. Those with SII above the cohort median exhibited more pronounced acute-phase responses (median CRP 96 vs. 12 mg L⁻¹; fibrinogen 578 vs. 458 mg dL⁻¹), yet median LOS remained virtually identical (29 vs. 28 days) and early mortality was low in both groups (8% vs. 2%). The CFI showed no clear gradient in hospital stay across its quartiles, and composite ratios—while tightly inter-correlated—demonstrated only minimal association with cytokine levels and LOS. Conclusions: Composite cell-count indices were markedly elevated but did not predict early death or prolonged admission. In low-event European cohorts, their chief value may lie in serving as cost-free gatekeepers, flagging those who should proceed to more advanced cytokine or genomic testing. Although routine reporting of NLR and SII may support low-cost surveillance, validation in larger, multicentre cohorts with serial sampling is needed before these indices can be integrated into clinical decision-making. Full article

The identification of a type I interferon-induced transcriptomic signature in active tuberculosis suggests a potential role for these interferons in the pathogenesis of tuberculosis. Comorbidities such as human immunodeficiency virus, diabetes, systemic lupus erythematosus, end-stage renal disease, and coronavirus disease are epidemiologically linked to an increased risk for reactivation of latent tuberculosis infection. Notably, type I interferons are also implicated in the pathogenesis of these conditions, with a recognizable type I interferon transcriptomic signature. The mechanisms by which type I interferons in tuberculosis-risk-associated comorbidities may drive the progression of tuberculosis or maintenance of latent infection however remain largely unknown. This review summarizes the existing literature on the increased association between type I interferons, focusing on interferon-α and -β, and the heightened risk of tuberculosis reactivation. It also underscores the similarities in the immunopathogenesis of these comorbidities. A better understanding of these mechanisms is essential to guide the development of host-directed interferon therapies and improving diagnostic biomarkers in M. tuberculosis infection. Full article

Background: Tuberculosis (TB) remains a major global public health challenge, and diagnosing it can be difficult due to issues such as distinguishing active TB from latent TB infection (LTBI), as well as the sample collection process, which is often time-consuming and lacks sensitivity and specificity. Ferroptosis is emerging as an important factor in TB pathogenesis; however, its underlying molecular mechanisms are not fully understood. Thus, there is a critical need to establish ferroptosis-related diagnostic biomarkers for tuberculosis (TB). Methods: This study aimed to identify and validate potential ferroptosis-related genes in TB infection while enhancing clinical diagnostic accuracy through bioinformatics-driven gene identification. The microarray expression profile dataset GSE28623 from the Gene Expression Omnibus (GEO) database was used to identify ferroptosis-related differentially expressed genes (FR-DEGs) associated with TB. Subsequently, these genes were used for immune cell infiltration, Gene Set Enrichment Analysis (GSEA), functional enrichment and correlation analyses. Hub genes were identified using Weighted Gene Co-expression Network Analysis (WGCNA) and validated in independent datasets GSE37250, GSE39940, GSE19437, and GSE31348. Results: A total of 21 FR-DEGs were identified. Among them, four hub genes (ACSL1, PARP9, TLR4, and ATG3) were identified as diagnostic biomarkers. These biomarkers were enriched in immune-response related pathways and were validated. Immune cell infiltration, GSEA, functional enrichment and correlation analyses revealed that multiple immune cell types could be activated by FR-DEGs. Throughout anti-TB therapy, the expression of the four hub gene signatures significantly decreased in patients cured of TB. Conclusions: In conclusion, ferroptosis plays a key role in TB pathogenesis. These four hub gene signatures are linked with TB treatment effectiveness and show promise as biomarkers for differentiating TB from LTBI. Full article

Latent tuberculosis infection (LTBi) affects nearly a quarter of the global population, yet current diagnostic methods are limited by low sensitivity and specificity. This study applied an integrative bioinformatics framework, incorporating machine learning techniques, to identify robust gene expression biomarkers associated with LTBi. We analyzed four publicly available transcriptomic datasets from peripheral blood mononuclear cells (PBMCs), representing latent, active, and healthy states. Differentially expressed genes (DEGs) were identified, followed by gene ontology (GO) enrichment, functional clustering, and miRNA interaction analysis. Semantic similarity, unsupervised clustering, and pathway enrichment were applied to refine the gene list. Key biomarkers were prioritized using receiver operating characteristic (ROC) curve analysis, with CCL2 and CXCL10 emerging as top candidates (AUC > 0.85). This multi-step approach demonstrates the potential of combining transcriptomic profiling with established machine learning and bioinformatics tools to uncover candidate biomarkers for improved LTBi detection, and it also provides a foundation for future experimental validation. Full article

Background and Objectives: The role of adenosine deaminase (ADA) in pulmonary tuberculosis (PTB) remains insufficiently defined in advanced forms of disease. Likewise, the systemic immune inflammatory index (SII) has not been validated in severe PTB. This 6-year prospective observational study aims to evaluate biomarker signatures of serum ADA and SII. Materials and Methods: According to the PTB case definition, 232 adult patients were divided into group 1, with a positive bacteriologic exam (n = 168), and group 2, without bacteriological confirmation (n = 64). ADA serum levels were compared by age, gender, nutritional status, morphologic and bacteriological pattern of PTB lesions, survival status, along with serum levels of other inflammatory biomarkers. All patients with comorbidities, interfering with the level of ADA, were excluded to avoid bias. Results: A total cohort of 208 PTB adults, aged 54.37 ± 14.365 years, included 156 males. The overall mortality was 11.53%. Death occurred after a mean interval of 1.63 ± 3.228 months after PTB diagnosis. ADA serum mean levels were 32.94 ± 9.146 IU/L, significantly higher in G1 (p = 0.002), in patients with delayed diagnosis of PTB (p = 0.000), with lung cavitation (p = 0.003), and death as a poor outcome (p ˂ 0.02). SII had a mean value of 1752.226 ± 2704.150, significantly increased in bacteriologically confirmed PTB cases (p = 0.018), delayed diagnosis (p = 0.002), cavitary advanced pulmonary tuberculosis (APT) (p = 0.002), and deceased (p = 0.003). Both an ADA cut-off elevated risk value of over 30 IU/L and SII of over 902 were fulfilled by 73 patients, with 2.10 higher risk of advanced PTB (p = 0.006) and 4.49 higher risk of mortality (p = 0.000). Conclusions: Serum ADA and SII are recommended as predictors of advanced and severe pulmonary TB. These findings indicate that ADA and SII, when elevated together, delineate a high-risk PTB phenotype with greater disease severity and early mortality. The combination offers a pragmatic, biomarker-based approach to risk stratification in PTB. Full article

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. Despite the improvements in diagnostic techniques, the accuracy of TB diagnosis is still low. In recent years, the development of artificial intelligence (AI) has opened up new possibilities in diagnosing and treating TB with high accuracy compared to traditional methods. Traditional diagnostic techniques, such as sputum smear microscopy, culture tests, and chest X-rays, are time-consuming, with less sensitivity for the detection of TB in patients. Due to the new developments in AI, advanced diagnostic and treatment techniques have been developed with high accessibility, speed, and accuracy. AI, including various specific methodologies, is becoming vital in managing TB. Machine learning (ML) methodologies, such as support vector machines (SVMs) and random forests (RF), alongside deep learning (DL) technologies, particularly convolutional neural networks (CNNs) for image analysis, are employed to analyze diverse patient data, including medical images and biomarkers, to enhance the accuracy and speed of tuberculosis diagnosis. This study summarized the benefits and drawbacks of both traditional and AI-driven TB diagnosis, highlighting how AI can support traditional techniques to increase early detection, lower misdiagnosis, and strengthen international TB control initiatives. Full article

Diagnosing tuberculosis (TB) in children presents significant challenges, necessitating the identification of reliable biomarkers for accurate diagnosis. In this study, we investigated plasma matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) as potential diagnostic markers. A prospective case–control study involved 167 children classified into confirmed TB, unconfirmed TB, and unlikely TB control groups. Plasma levels of MMPs (MMP 1, 2, 3, 7, 8, 9, 12, and 13) and TIMPs (TIMP 1, 2, 3, and 4) were measured using multiplex assays. Elevated baseline levels of MMP-1, MMP-2, MMP-7, MMP-9, TIMP-1, TIMP-2, TIMP-3, and TIMP-4 were observed in active TB cases compared to unlikely TB controls. Receiver operating characteristics (ROC) analysis identified MMP-1, MMP-2, MMP-9, and TIMP-1 as potential biomarkers with over 80% sensitivity and specificity. A three-MMP signature (MMP-1, MMP-2, and MMP-9) demonstrated 100% sensitivity and specificity. The findings suggest that a baseline MMP signature could serve as an accurate biomarker for diagnosing pediatric TB, enabling early intervention and effective management. Full article

Background: Pulmonary tuberculosis (TB) frequently leads to long-term lung complications that contribute to increased mortality. Understanding the pathogenesis of post-TB lung impairments is crucial for improving long-term outcomes in TB patients; yet this area remains poorly researched. Methods: Our study assessed circulatory inflammatory markers in patients who completed TB treatment more than one year before enrolment (population 1) and patients receiving in-hospital treatment for active drug-sensitive TB (population 2). Results: IL-6 was seven times higher in both populations compared to the normal range. IL-8 was below the limit of detection (LOD) in population 1, while it was approximately 2.5 times higher in population 2 compared to the normal range. TNF-α was 21 times higher in population 1 and 19 times higher in population 2 compared to the normal range. CRP was almost 49 times higher in both populations, and IL-1Ra was below the LOD in population 1, while it was ~1.5 times higher in population 2 compared to the normal range. Conclusions: These inflammatory biomarkers correlated well with lung function in the post-TB state, and their high levels suggest a persistent pro-inflammatory state post-TB, which may contribute to post-TB lung disease. More research is warranted to better understand this phenomenon, but these findings may highlight a need to consider anti-inflammatory therapy for patients with post-TB lung disease, especially since these high levels of cytokines can directly contribute to lung damage. Full article

Background: Tuberculosis (TB) and diabetes mellitus (DM) comorbidity (TB-DM) presents a significant global health challenge, with diabetes increasing susceptibility to TB, worsening clinical outcomes, and impairing immune responses. Among these dysfunctions, macrophages—the primary immune cells responsible for pathogen recognition, phagocytosis, and bacterial clearance—exhibit profound alterations in TB-DM. However, the complex interplay between metabolic dysregulation, immune impairment, and macrophage dysfunction remains poorly defined. Objective: This scoping review systematically maps the literature on macrophage dysfunction in TB-DM, identifying key immunological impairments affecting phagocytosis, cytokine production, antigen presentation, macrophage polarisation, reactive oxygen species (ROS) and nitric oxide (NO) regulation, and chronic inflammation. Methods: A systematic search was conducted in PubMed, Web of Science, and Embase, covering studies from 2014 to 2024. Inclusion criteria focused on human studies investigating macrophage-specific mechanisms in TB-DM. Data extraction and synthesis were performed using Covidence, with findings grouped into key immunological themes. Results: A total of 44 studies were included, revealing significant impairments in macrophage function in TB-DM. Findings indicate reduced NO production, variable ROS dysregulation, altered M1/M2 polarisation, defective antigen presentation, and chronic inflammation. Elevated IL-10 and VEGF were associated with immune suppression and granuloma destabilisation, while eicosanoids (PGE2, LXA4) contributed to sustained inflammation. Conclusions: Macrophage dysfunction emerges as a central driver of immune failure in TB-DM, creating a self-perpetuating cycle of inflammation, immune exhaustion, and bacterial persistence. Understanding these mechanisms is essential for developing biomarker-driven diagnostics, host-directed therapies, targeted immunomodulation, and improving TB outcomes in diabetic populations. Future research should explore macrophage-targeted interventions to enhance immune function and mitigate TB-DM burden. Full article

Sarcoidosis is a rare multisystem inflammatory disease characterized by non-necrotizing granulomas, typically affecting the lungs, lymph nodes, skin, and bones. Due to its extreme clinical heterogeneity, diagnosis remains challenging. Within the skeletal system, the thoracic spine, ankles, and knees are the most commonly involved joints. We report a rare case of non-articular osseous sarcoidosis with progressive pulmonary lesions and persistently normal inflammatory biomarkers (ACE, CRP, ESR, IL-2, and TNF-α) that required differentiation from metastatic bone tumors and tuberculosis. Prior to presentation at our hospital, the patient did not respond to six months of anti-tuberculosis treatment and one month of systemic glucocorticoid therapy in three other hospitals. Based on lung and bone biopsies, she was finally diagnosed as having active sarcoidosis in our hospital. Despite 3 months of prednisone, pulmonary consolidation and bone lesions persisted until methotrexate was added. This case highlights the preference of combined glucocorticoid and methotrexate therapy for sarcoidosis with atypical osseous involvement and normal biomarkers, underscoring the urgent need for novel diagnostic tools to mitigate misdiagnosis. Full article

Since the World Health Organization (WHO) issued guidelines for developing a non-sputum test for active tuberculosis (TB) diagnosis that exhibits similar performance characteristics to sputum-based diagnosis, salivary diagnostic techniques have gained prominence as potential screening tools or adjuncts to existing diagnostics. We searched online databases for studies that looked at salivary diagnostic techniques. Afterwards, duplicates were removed, titles and abstracts were screened, and full-text studies were assessed for eligibility based on inclusion and exclusion criteria. The studies chosen for final analysis underwent a rigorous quality assessment following a QUADAS-2 template, and data were extracted. The primary outcome assessed the difference in mean levels of interleukins between TB+ patients and TB-controls (Hedges’ g). We then conducted two subgroup analyses: the first segregated the control group into healthy patients, and those with other respiratory diseases (ORD), and the second addressed three different interleukins separately (IL-6, IL-5, IL-17). The secondary outcome involved comparing salivary molecular diagnostic assays to WHO guidelines. This study is registered with PROSPERO, CRD42024536884. A total of 17 studies, out of an initial 1010, were chosen for the final analysis, but one was then excluded for being of poor quality. Our meta-analyses for the primary outcome revealed minimal diagnostic potential for interleukins. Our first subgroup analysis showed that interleukins were incapable of differentiating active TB patients from both healthy controls and ORD patients. Our second subgroup analysis showed that IL-17 was reduced in active TB patients. Assessment of the secondary outcome revealed that most studies relied on a GeneXpert MTB/RIF assay on saliva, but none fulfilled WHO guidelines for a non-sputum test. Individual biomarkers currently lack sufficient discriminatory power to definitively distinguish active tuberculosis from healthy individuals or those with other respiratory diseases (ORD), reinforcing the need for multi-biomarker panels. Interleukins may be alternatively used as markers for prognosis, severity, or treatment response. Our findings also suggest that assays are unable to meet WHO guidelines. Full article

Diabetes mellitus (DM) and tuberculosis (TB) are two global health challenges that significantly impact population health, with DM increasing susceptibility to TB infections. However, early risk prediction methods for DM patients complicated with TB (DM–TB) are lacking. This study mined transcriptome data of DM–TB patients from the GEO database (GSE181143 and GSE114192) and used differential analysis, weighted gene co-expression network analysis (WGCNA), intersecting immune databases, combined with ten machine learning algorithms, to identify immune biomarkers associated with DM–TB. An early alert model for DM–TB was constructed based on the identified core differentially expressed genes (DEGs) and validated through a prospective cohort study and reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) for gene expression levels. Furthermore, we performed a detailed immune status analysis of DM–TB patients using the CIBERSORT algorithm. We identified 1090 DEGs associated with DM–TB and further pinpointed CETP (cholesteryl ester transfer protein) (AUC = 0.804, CI: 0.744–0.864), TYROBP (TYRO protein tyrosine kinase binding protein) (AUC = 0.810, CI: 0.752–0.867), and SECTM1 (secreted and transmembrane protein 1) (AUC = 0.811, CI: 0.757–0.864) as immune-related biomarkers for DM–TB patients. An early alert model was developed based on these three genes (AUC = 0.86, CI: 0.813–0.907), with a sensitivity of 0.80829 and a specificity of 0.75758 at a Youden index of 0.56587. External validation using the GSE114192 dataset showed an AUC of 0.901 (CI: 0.847–0.955). Population cohort research and RT-qPCR verified the expression levels of these three genes, demonstrating consistency with trends seen in the training set. KEGG enrichment analysis revealed that NF-κB and MAPK signaling pathways play crucial roles in the DM–TB pathogenic mechanism, and immune infiltration analysis showed significant suppression of certain adaptive immune cells and activation of inflammatory cells in DM–TB patients. This study identified three potential immune-related biomarkers for DM–TB, and the constructed risk assessment model demonstrated significant predictive efficiency, providing an early screening strategy for DM–TB. Full article

Mycobacterium tuberculosis (Mtb) vaccines are designed to prevent infection, prevent reactivation of latent infection, and/or provide adjuvant therapy to standard TB treatment for active Mtb. Emerging vaccine technologies include reverse vaccinology, DNA and RNA vaccines, subunit vaccines, and multi-epitope vaccines. Currently, many different types of vaccine candidates are in clinical trials, though, to date, BCG remains the only approved Mtb vaccine. Mtb has a complex genome with numerous antigens, but not all are equally effective in eliciting immunity, so a critical challenge is the selection of antigens and epitopes that are most likely to induce a long-term, broad-spectrum protective immune response. Multi-epitope vaccines (MEVs) represent a new event horizon in vaccine development. Bioinformatic computer modeling is being used to maximize efficacy and minimalize adverse effects. Although no multi-epitope vaccines have proceeded to in vivo clinical trials, three candidate MEVs have made it through in silico tests. Multi-epitope vaccine candidate PP13138R, containing 13 HTL epitopes, 13 CTL epitopes, and 8 B cell epitopes in addition to both TLR2 and TLR4 agonists, aims to elicit a broad immune response that could address both active and latent Mtb infection. Similarly, immunoinformatic data were used to design and validate another MEV candidate based on the biomarker PE_PGRS17 with four B cell, nine HTL, and six CTL linked epitopes, with a griselimycin sequence as the adjuvant. A third novel prophylactic and therapeutic MEV was developed that targets Ag85A, AG85B, ESAT-6, and CFP-10 proteins with 12 CTL, 25 HTL, and 21 LBL epitopes with a CpG adjuvant. Full article

Background/Objectives: Mitochondrial dysfunction has been implicated in the pathogenesis of tuberculosis (TB). Despite emerging evidence of the importance of mitochondrial gene regulation in the immune response, the specific role of mitochondrial-related genes in TB susceptibility remains to be fully elucidated. Methods: We employed a multi-omics approach integrating genetic, methylation, and protein-level data. Mendelian randomization (MR) and colocalization analyses were conducted to explore causal associations between mitochondrial gene features—expression quantitative trait loci (eQTL), methylation quantitative trait loci (mQTL), and protein quantitative trait loci (pQTL)—and TB susceptibility. Data were obtained from the FinnGen cohort and validated using independent datasets. Results: Our analyses identified several key mitochondrial genes (e.g., ACSF3, AK3, LYRM4, and PDHB) significantly associated with TB susceptibility. Random forest analysis and gene set enrichment analysis (GSEA) supported the predictive power of these genes. Furthermore, we observed significant correlations between mitochondrial gene expression and immune cell infiltration in TB patients, suggesting a role of these genes in modulating immune responses during infection. Receiver operating characteristic (ROC) analysis confirmed strong predictive accuracy for the identified feature genes, with area under the curve (AUC) values exceeding 0.7. Conclusions: This study demonstrates that mitochondrial-related gene regulation influences TB susceptibility across genetic, methylation, and protein levels. The integration of multi-omics data provides valuable insight into the molecular mechanisms underlying TB, highlighting the potential of mitochondrial genes as biomarkers and therapeutic targets. Full article

Background: Despite “successful” treatment, some lung tuberculosis (TB) patients develop long-term lung impairments that includes damage to the parenchyma and reduced function, which may predispose them to diseases like pulmonary hypertension. However, this is not well understood. Therefore, we investigated whether previous or current TB patients would display elevated biomarkers of endothelial dysfunction and vascular remodeling. Methods: We performed assays for ADMA, VCAM-1, VEGF, angiopoietin-1, TBARS, NT-pro-BNP, and cardiac troponin-I. We further stratified the patients based on 1, 2, 3, and >3 previous TB episodes, and 1–5 yrs, 5–10 yrs, 10–15 yrs and >15 yrs after the last TB treatment completion. We also assessed correlations between the biomarkers and the number of previous TB episodes or the time since the completion of the last TB treatment. Results: ADMA was 70 times higher, VEGF was 2000 times higher and angiopoietin-1 was 6500 times higher than the normal range. NT-pro-BNP and cardiac troponin-I were undetected, and TBARS levels were low. There was a positive linear relationship between the number of previous TB episodes and angiopoietin-1, and between VEGF and the number of previous TB episodes. ADMA, VCAM-1 and TBARS exhibited a weak and negative linear association with the number of previous TB episodes. A negligible negative linear association was observed between the time since the completion of the last TB treatment and angiopoietin-1, VEGF and ADMA. Conclusions: Therefore, having >1 previous TB episode, despite the successful completion of TB treatment, associates with an increased risk of endothelial dysfunction/angiogenesis or vascular remodeling. Full article