Discovery of serum biomarkers for diagnosis of tuberculosis by NMR metabolomics including cross-validation with a second cohort

Biomarkers in diagnosing and therapeutic monitoring of tuberculosis: a review

Tuberculosis (TB) continues to pose a significant health challenge worldwide, emphasizing the importance of prompt diagnosis and efficient monitoring of treatment outcomes for effective disease control. Biomarkers have become increasingly important in the realm of TB diagnoses and treatment. The objective of this comprehensive review is to examine the present state of biomarkers employed in the diagnosis of TB, monitoring the response to treatment, and predicting treatment outcomes. In this study, we undertake a comprehensive examination of the diverse biomarkers utilized in TB diagnoses, spanning molecular, immunological, and other novel methodologies. Furthermore, we examine the potential of biomarkers in the context of therapeutic monitoring, assessment of treatment effectiveness, and anticipation of drug resistance. Additionally, this paper presents future prospects regarding the utilization of biomarkers in the therapy of tuberculosis.

Integrating untargeted and targeted LC-MS-based metabolomics to identify the serum metabolite biomarkers for tuberculosis

Given the limitations of untargeted metabolomics in precise metabolite quantification, our current research employed a novel approach by integrating untargeted and targeted metabolomics utilizing ultra-high-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS) to analyze the metabolic profile and potential biomarkers for tuberculosis (TB). A cohort of 36 TB patients and 36 healthy controls (HC) was enlisted to obtain serum samples. Multivariate pattern recognition and univariate statistical analysis were employed to screen and elucidate the differential metabolites, whereas dot plots and receiver operating characteristic (ROC) curves were established for the identification of potential biomarkers of TB. The results indicated a distinct differentiation between the two groups, identifying 99 metabolites associated with five primary metabolic pathways in relation to TB. Of these, 19 metabolites exhibited high levels of sensitivity and specificity, as evidenced by the area under curve values approaching 1. Following targeted quantitative analysis, three potential metabolites, namely, L-asparagine, L-glutamic acid, and arachidonic acid, were demonstrated excellent discriminatory ability as evidenced by the results of the ROC curve, dot plots, and random forest model. Particularly noteworthy was the enhanced diagnostic efficacy of the combination of these three metabolites compared to singular biomarkers, suggesting their potential utility as serum biomarkers for TB diagnosis.

HPLC for simultaneous quantification of free mannose and glucose concentrations in serum: use in detection of ovarian cancer

Background: Abnormal levels of monosaccharides in blood have been linked to tumorigenesis. In this study, a novel high-performance liquid chromatography (HPLC) method was established for the simultaneous determination of free mannose and glucose in the serum. Methods: The serum was directly derivatized by 1-phenyl-3-methyl-5-pyrazolone under alkaline conditions using L-rhamnose as an internal standard. The chromatographic separation was then performed on a Poroshell EC-C18 chromatographic column (4.6 × 100 mm, particle size 2.7 μm, Agilent) with gradient elution using NH4Ac-HAc and acetonitrile as the mobile phases. The method was thereafter validated according to international guidelines. The serum samples obtained from 200 healthy individuals and 200 ovarian cancer (OC) patients were analyzed for free mannose and glucose. Results: The method was found to be reproducible for quantification within 20 min and included online sample purification. The method displayed excellent linearity in the concentration range (for mannose: 0.5-500 μg/mL; glucose: 0.5-1500 μg/mL). The precision, recovery, and stability met the FDA bioanalytical method validation acceptance criteria. Overall, the measurement of glucose content by HPLC correlated well with the different enzymatic methods. Ovarian cancer mannose levels in the serum were significantly higher in the advanced stage (61.22 μmol/L, p < 0.0001) than those in healthy volunteers and early-stage patients (44.51 μmol/L versus 50.09 μmol/L, p < 0.0001). The AUC for the ratio of serum free glucose to mannose (G/M) was 0.98 (p < 0.0001), with a sensitivity of 91.46% and a specificity of 98.50%, which served as a biomarker for OC diagnosis. Conclusion: We report a simple, repeatable, and attractive analytical method by HPLC, which can be used for quantitative estimation of free mannose and glucose simultaneously in human serum. Our results indicate that the serum level of mannose could be used as a potential biomarker of ovarian cancer.

Clinical metabolomics by NMR revealed serum metabolic signatures for differentiating sarcoidosis from tuberculosis

BACKGROUND

Pulmonary sarcoidosis (SAR) and tuberculosis (TB) are two granulomatous lung-diseases and often pose a diagnostic challenge to a treating physicians.

OBJECTIVE

The present study aims to explore the diagnostic potential of NMR based serum metabolomics approach to differentiate SAR from TB.

MATERIALS AND METHOD

The blood samples were obtained from three study groups: SAR (N = 35), TB (N = 28) and healthy normal subjects (NC, N = 56) and their serum metabolic profiles were measured using 1D 1H CPMG (Carr-Purcell-Meiboom-Gill) NMR spectra recorded at 800 MHz NMR spectrometer. The quantitative metabolic profiles were compared employing a combination of univariate and multivariate statistical analysis methods and evaluated for their diagnostic potential using receiver operating characteristic (ROC) curve analysis.

RESULTS

Compared to SAR, the sera of TB patients were characterized by (a) elevated levels of lactate, acetate, 3-hydroxybutyrate (3HB), glutamate and succinate (b) decreased levels of glucose, citrate, pyruvate, glutamine, and several lipid and membrane metabolites (such as very-low/low density lipoproteins (VLDL/LDL), polyunsaturated fatty acids, etc.).

CONCLUSION

The metabolic disturbances not only found to be well in concordance with various previous reports, these further demonstrated very high sensitivity and specificity to distinguish SAR from TB patients suggesting serum metabolomics analysis can serve as surrogate method in the diagnosis and clinical management of SAR.

Advances in Diagnostics and Drug Discovery against Resistant and Latent Tuberculosis Infection

Latent tuberculosis infection (LTBI) represents a subclinical, asymptomatic mycobacterial state affecting approximately 25% of the global population. The substantial prevalence of LTBI, combined with the risk of progressing to active tuberculosis, underscores its central role in the increasing incidence of tuberculosis (TB). Accurate identification and timely treatment are vital to contain and reduce the spread of the disease, forming a critical component of the global strategy known as "End TB." This review aims to examine and highlight the most recent scientific evidence related to new diagnostic approaches and emerging therapeutic treatments for LTBI. While prevalent diagnostic methods include the tuberculin skin test (TST) and interferon gamma release assay (IGRA), WHO's approval of two specific IGRAs for Mycobacterium tuberculosis (MTB) marked a significant advancement. However, the need for a specific test with global application viability has propelled research into diagnostic tests based on molecular diagnostics, pulmonary immunity, epigenetics, metabolomics, and a current focus on next-generation MTB antigen-based skin test (TBST). It is within these emerging methods that the potential for accurate distinction between LTBI and active TB has been demonstrated. Therapeutically, in addition to traditional first-line therapies, anti-LTBI drugs, anti-resistant TB drugs, and innovative candidates in preclinical and clinical stages are being explored. Although the advancements are promising, it is crucial to recognize that further research and clinical evidence are needed to solidify the effectiveness and safety of these new approaches, in addition to ensuring access to new drugs and diagnostic methods across all health centers. The fight against TB is evolving with the development of more precise diagnostic tools that differentiate the various stages of the infection and with more effective and targeted treatments. Once consolidated, current advancements have the potential to transform the prevention and treatment landscape of TB, reinforcing the global mission to eradicate this disease.

Untargeted Metabolomics of Feces Reveals Diagnostic and Prognostic Biomarkers for Active Tuberculosis and Latent Tuberculosis Infection: Potential Application for Precise and Non-Invasive Identification

Purpose

Distinguishing latent tuberculosis infection (LTBI) from active tuberculosis (ATB) is important to control the prevalence of tuberculosis; however, there is currently no effective method. The aim of this study was to discover specific metabolites through fecal untargeted metabolomics to discriminate ATB, individuals with LTBI, and healthy controls (HC) and to probe the metabolic perturbation associated with the progression of tuberculosis.

Patients and Methods

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to comprehensively detect compounds in fecal samples from HC, LTBI, and ATB patients. Differential metabolites between the two groups were screened, and their underlying biological functions were explored. Candidate metabolites were selected and enrolled in LASSO regression analysis to construct diagnostic signatures for discriminating between HC, LTBI, and ATB. A receiver operating characteristic (ROC) curve was applied to evaluate diagnostic value. A nomogram was constructed to predict the risk of progression of LTBI.

Results

A total of 35 metabolites were found to exist differentially in HC, LTBI, and ATB, and eight biomarkers were selected. Three diagnostic signatures based on the eight biomarkers were constructed to distinguish between HC, LTBI, and ATB, demonstrating excellent discrimination performance in ROC analysis. A nomogram was successfully constructed to evaluate the risk of progression of LTBI to ATB. Moreover, 3,4-dimethylbenzoic acid has been shown to distinguish ATB patients with different responses to etiological tests.

Conclusion

This study constructed diagnostic signatures based on fecal metabolic biomarkers that effectively discriminated HC, LTBI, and ATB, and established a predictive model to evaluate the risk of progression of LTBI to ATB. The results provide scientific evidence for establishing an accurate, sensitive, and noninvasive differential diagnosis scheme for tuberculosis.

L-Tyrosine Limits Mycobacterial Survival in Tuberculous Granuloma

Caused by the intracellular pathogen Mycobacterium tuberculosis (Mtb), tuberculosis (TB) remains a massive global public health issue. A well-known and key TB trait is caseous necrotic granuloma, which allows mycobacteria to reactivate and disseminate, thus confounding TB eradication programs. Amino acid (AA) metabolism is key to regulating immune responses in Mtb infections; however, it is currently unclear if AAs can be used to treat tuberculous granulomas. Here, we screened 20 proteinogenic AAs using a Mycobacterium marinum-infected zebrafish granuloma model. Only L-tyrosine simultaneously reduced Mycobacterium marinum (M. marinum) levels in zebrafish larvae and adults and inhibited intracellular pathogen survival levels. Mechanistically, L-tyrosine significantly upregulated interferon-γ (IFN-γ) expression in M. marinum -infected zebrafish adults but not in larvae. Using N-acetylcysteine (NAC) to inhibit reactive oxygen species (ROS), L-tyrosine appeared to inhibit Mtb intracellular survival by promoting ROS production. Thus, L-tyrosine as a non-essential AA may reduce mycobacterial survival in both macrophages and tuberculous granulomas. Our research provides a platform for the clinical development of AAs for active or latent TB patients infected with drug-sensitive or drug-resistant Mtb.

Multimodal plasma metabolomics and lipidomics in elucidating metabolic perturbations in tuberculosis patients with concurrent type 2 diabetes

Type 2 diabetes mellitus (DM) poses a major burden for the treatment and control of tuberculosis (TB). Characterization of the underlying metabolic perturbations in DM patients with TB infection would yield insights into the pathophysiology of TB-DM, thus potentially leading to improvements in TB treatment. In this study, a multimodal metabolomics and lipidomics workflow was applied to investigate plasma metabolic profiles of patients with TB and TB-DM. Significantly different biological processes and biomarkers in TB-DM vs. TB were identified using a data-driven, knowledge-based framework. Changes in metabolic and signaling pathways related to carbohydrate and amino acid metabolism were mainly captured by amide HILIC column metabolomics analysis, while perturbations in lipid metabolism were identified by the C18 metabolomics and lipidomics analysis. Compared to TB, TB-DM exhibited elevated levels of bile acids and molecules related to carbohydrate metabolism, as well as the depletion of glutamine, retinol, lysophosphatidylcholine, and phosphatidylcholine. Moreover, arachidonic acid metabolism was determined as a potential important factor in the interaction between TB and DM pathophysiology. In a correlation network of the significantly altered molecules, among the central nodes, chenodeoxycholic acid was robustly associated with TB and DM. Fatty acid (22:4) was a component of all significant modules. In conclusion, the integration of multimodal metabolomics and lipidomics provides a thorough picture of the metabolic changes associated with TB-DM. The results obtained from this comprehensive profiling of TB patients with DM advance the current understanding of DM comorbidity in TB infection and contribute to the development of more effective treatment.

Metabolic biological markers for diagnosing and monitoring the course of tuberculosis

The international biomedical community has been currently facing a need to find a simple and most accessible type of analysis that helps to diagnose tuberculosis (TB) with the maximum reliability even before the onset of clinical manifestations. Tuberculosis results in more deaths than any other pathogen, second only to pneumonia caused by the SARS-CoV-2 virus, but the majority of infected people remain asymptomatic. In addition, it is important to develop methods to distinguish various forms of tuberculosis infection course at early stages and to reliably stratify patients into appropriate groups (persons with a rapidly progressing infection, chronic course, latent infection carriers). Immunometabolism investigates a relationship between bioenergetic pathways and specific functions of immune cells that has recently become increasingly important in scientific research. The host anti-mycobacteria immune response in tuberculosis is regulated by a number of metabolic networks that can interact both cooperatively and antagonistically, influencing an outcome of the disease. The balance between inflammatory and immune reactions limits the spread of mycobacteria in vivo and protects from developing tuberculosis. Cytokines are essential for host defense, but if uncontrolled, some mediators may contribute to developing disease and pathology. Differences in plasma levels of metabolites between individuals with advanced infection, LTBI and healthy individuals can be detected long before the onset of the major related clinical signs. Changes in amino acid and cortisol level may be detected as early as 12 months before the onset of the disease and become more prominent at verifying clinical diagnosis. Assessing serum level of certain amino acids and their ratios may be used as additional diagnostic markers of active pulmonary TB. Metabolites, including serum fatty acids, amino acids and lipids may contribute to detecting active TB. Metabolic profiles indicate about increased indolamine 2.3-dioxygenase 1 (IDO1) activity, decreased phospholipase activity, increased adenosine metabolite level, and fibrous lesions in active vs. latent infection. TB treatment can be adjusted based on individual patient metabolism and biomarker profiles. Thus, exploring immunometabolism in tuberculosis is necessary for development of new therapeutic strategies.

Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature

Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.

Diagnostic biomarkers for active tuberculosis: progress and challenges

Tuberculosis (TB) is a leading cause of morbidity and mortality from a single infectious agent, despite being preventable and curable. Early and accurate diagnosis of active TB is critical to both enhance patient care, improve patient outcomes, and break Mycobacterium tuberculosis (Mtb) transmission cycles. In 2020 an estimated 9.9 million people fell ill from Mtb, but only a little over half (5.8 million) received an active TB diagnosis and treatment. The World Health Organization has proposed target product profiles for biomarker- or biosignature-based diagnostics using point-of-care tests from easily accessible specimens such as urine or blood. Here we review and summarize progress made in the development of pathogen- and host-based biomarkers for active TB diagnosis. We describe several unique patient populations that have posed challenges to development of a universal diagnostic TB biomarker, such as people living with HIV, extrapulmonary TB, and children. We also review additional limitations to widespread validation and utilization of published biomarkers. We conclude with proposed solutions to enhance TB diagnostic biomarker validation and uptake.

The Role of Amino Acids in Tuberculosis Infection: A Literature Review

Recently, there was an abundance of studies being conducted on the metabolomic profiling of tuberculosis patients. Amino acids are critical metabolites for the immune system, as they might contribute to providing nutrients for the host intracellular pathway. In tuberculosis, several amino acids play important roles in both the mycobacteria infection mechanism and the host. Individual studies showed how the dynamics of metabolite products that result from interactions between Mycobacterium tuberculosis (Mtb) and the host play important roles in different stages of infection. In this review, we focus on the dynamics of amino-acid metabolism and identify the prominent roles of amino acids in the diagnostics and treatment of tuberculosis infection. Online resources, including PubMed, ScienceDirect, Scopus, and Clinical Key, were used to search for articles with combination keywords of amino acids and TB. The inclusion criteria were full-text articles in English published in the last 10 years. Most amino acids were decreased in patients with active TB compared with those with latent TB and healthy controls. However, some amino acids, including leucine, isoleucine, valine, phenylalanine, aspartate, and glutamate, were found to be at higher levels in TB patients. Additionally, the biomarkers of Mtb infection included the ratios of kynurenine to tryptophan, phenylalanine to histidine, and citrulline to arginine. Most amino acids were present at different levels in different stages of infection and disease progression. The search for additional roles played by those metabolomic biomarkers in each stage of infection might facilitate diagnostic tools for staging TB infection.

TNF and HNRNPL Related Immunoregulatory Long non-coding RNA (THRIL) and long intergenic noncoding RNA-p21 (lincRNA-p21) as potential useful biomarkers for the diagnosis of tuberculosis

Early diagnosis is crucial in controlling tuberculosis globally and in developing countries with the emergence of drug-resistant Mycobacterium tuberculosis strains. Long non-coding RNAs (lncRNAs) are promising tuberculosis diagnostic biomarkers. Two lncRNA diagnostic markers, lncRNA THRIL and lincRNA-p21, were studied as tuberculosis diagnostic biomarkers. This cross-sectional study was conducted at the Center of Respiratory Diseases of LAQUINTINIE hospital and the National Veterinary Laboratory of Douala from December 2020 to August 2021. The ability of lncRNAs to distinguish between 19 healthy controls, 15 latent tuberculosis, and 21 active tuberculosis was estimated using quantitative polymerase chain reaction and Receiver Operating Characteristic curve analysis. Our analysis showed that lncRNA THRIL and lincRNA-p21 were significantly upregulated (P &lt;0.05) in active and latent tuberculosis compared with healthy controls. LincRNA-p21 expression was significantly increased (P &lt;0.05) in active tuberculosis compared with latent tuberculosis, whereas lncRNA THRIL was not significantly affected (P ≥0.05). Both lncRNA THRIL and lincRNA-p21 showed excellent performance in classifying latent tuberculosis and healthy controls (AUC = 92.86%). Furthermore, lncRNA THRIL was good at discriminating active tuberculosis from healthy controls (AUC = 89.79%), while lincRNA-p21 showed excellent discriminating performance (AUC = 100%). LncRNA THRIL was identified as a poor discriminator of latent tuberculosis from active tuberculosis (AUC = 64.28%), while lincRNA-p21 showed excellent diagnostic performance in this distinction (AUC = 92.86%). Our cross-sectional study suggests that lncRNA THRIL and lincRNA-p21 are promising tuberculosis diagnostic biomarkers that can differentiate between latent and active infection.

Untargeted serum metabolomic profiling for early detection of Schistosoma mekongi infection in mouse model

Mekong schistosomiasis is a parasitic disease caused by blood flukes in the Lao People’s Democratic Republic and in Cambodia. The standard method for diagnosis of schistosomiasis is detection of parasite eggs from patient samples. However, this method is not sufficient to detect asymptomatic patients, low egg numbers, or early infection. Therefore, diagnostic methods with higher sensitivity at the early stage of the disease are needed to fill this gap. The aim of this study was to identify potential biomarkers of early schistosomiasis using an untargeted metabolomics approach. Serum of uninfected and S. mekongi-infected mice was collected at 2, 4, and 8 weeks post-infection. Samples were extracted for metabolites and analyzed with a liquid chromatography-tandem mass spectrometer. Metabolites were annotated with the MS-DIAL platform and analyzed with Metaboanalyst bioinformatic tools. Multivariate analysis distinguished between metabolites from the different experimental conditions. Biomarker screening was performed using three methods: correlation coefficient analysis; feature important detection with a random forest algorithm; and receiver operating characteristic (ROC) curve analysis. Three compounds were identified as potential biomarkers at the early stage of the disease: heptadecanoyl ethanolamide; picrotin; and theophylline. The levels of these three compounds changed significantly during early-stage infection, and therefore these molecules may be promising schistosomiasis markers. These findings may help to improve early diagnosis of schistosomiasis, thus reducing the burden on patients and limiting spread of the disease in endemic areas.

An area of greatest vulnerability - recent advances in kidney injury

In this issue of the Biomedical Journal the reader is provided with an insight into the latest observations and advances in acute kidney injury as well as chronic kidney disease. The current SARS-CoV-2 variants are reviewed, and the role of long non-coding RNA in HIV therapy is explored. Furthermore, the potential of metabolomics as means to diagnose multiple sclerosis as well as tuberculosis is presented. Other topics of this issue include the restoration of the spermatogonial stem cell niche; atherosclerosis and the use of improved ultrasound images; and the effect of transcranial magnetic stimulation in patients with autism spectrum disorder. Finally, it is shown how continuous passive motion can be used as supportive therapeutic approach in children with cerebral palsy, and minimally invasive surgery is presented as valid alternative in cases of spine metastasis.