Validation and Optimization of Host Immunological Bio-Signatures for a Point-of-Care Test for TB Disease

Baseline and end-of-treatment host serum biomarkers predict relapse in adults with pulmonary tuberculosis

BACKGROUND

There is a need for new tools for monitoring of the response to TB treatment. Such tools may allow for tailored treatment regimens, and stratify patients initiating TB treatment into different risk groups. We evaluated combinations between previously published host biomarkers and new candidates, as tools for monitoring TB treatment response, and prediction of relapse.

METHODS

Serum samples were collected at multiple time points, from patients initiating TB treatment at research sites situated in South Africa (ActionTB study), Brazil and Uganda (TBRU study). Using a multiplex immunoassay platform, we evaluated the concentrations of selected host inflammatory biomarkers in sera obtained from clinically cured patients with and without subsequent relapse within 2 years of TB treatment completion.

RESULTS

A total of 130 TB patients, 30 (23%) of whom had confirmed relapse were included in the study. The median time to relapse was 9.7 months in the ActionTB study (n = 12 patients who relapsed), and 5 months (n = 18 patients who relapsed) in the TBRU study. Serum concentrations of several host biomarkers changed during TB treatment with IL-6, IP-10, IL-22 and complement C3 showing potential individually, in predicting relapse. A six-marker signature comprising of TTP, BMI, sICAM-1, IL-22, IL-1β and complement C3, predicted relapse, prior to the onset of TB treatment with 89% sensitivity and 94% specificity. Furthermore, a 3-marker signature (Apo-CIII, IP-10 and sIL-6R) predicted relapse in samples collected at the end of TB treatment with sensitivity of 71% and specificity of 74%. A previously identified baseline relapse prediction signature (TTP, BMI, TNF-β, sIL-6R, IL-12p40 and IP-10) also showed potential in the current study.

CONCLUSION

Serum host inflammatory biomarkers may be useful in predicting relapse in TB patients prior to the initiation of treatment. Our findings have implications for tailored patient management and require prospective evaluation in larger studies.

Integrated plasma proteomics identifies tuberculosis-specific diagnostic biomarkers

BACKGROUNDNovel biomarkers to identify infectious patients transmitting Mycobacterium tuberculosis are urgently needed to control the global tuberculosis (TB) pandemic. We hypothesized that proteins released into the plasma in active pulmonary TB are clinically useful biomarkers to distinguish TB cases from healthy individuals and patients with other respiratory infections.METHODSWe applied a highly sensitive non-depletion tandem mass spectrometry discovery approach to investigate plasma protein expression in pulmonary TB cases compared to healthy controls in South African and Peruvian cohorts. Bioinformatic analysis using linear modeling and network correlation analyses identified 118 differentially expressed proteins, significant through 3 complementary analytical pipelines. Candidate biomarkers were subsequently analyzed in 2 validation cohorts of differing ethnicity using antibody-based proximity extension assays.RESULTSTB-specific host biomarkers were confirmed. A 6-protein diagnostic panel, comprising FETUB, FCGR3B, LRG1, SELL, CD14, and ADA2, differentiated patients with pulmonary TB from healthy controls and patients with other respiratory infections with high sensitivity and specificity in both cohorts.CONCLUSIONThis biomarker panel exceeds the World Health Organization Target Product Profile specificity criteria for a triage test for TB. The new biomarkers have potential for further development as near-patient TB screening assays, thereby helping to close the case-detection gap that fuels the global pandemic.FUNDINGMedical Research Council (MRC) (MR/R001065/1, MR/S024220/1, MR/P023754/1, and MR/W025728/1); the MRC and the UK Foreign Commonwealth and Development Office; the UK National Institute for Health Research (NIHR); the Wellcome Trust (094000, 203135, and CC2112); Starter Grant for Clinical Lecturers (Academy of Medical Sciences UK); the British Infection Association; the Program for Advanced Research Capacities for AIDS in Peru at Universidad Peruana Cayetano Heredia (D43TW00976301) from the Fogarty International Center at the US NIH; the UK Technology Strategy Board/Innovate UK (101556); the Francis Crick Institute, which receives funding from UKRI-MRC (CC2112); Cancer Research UK (CC2112); and the NIHR Biomedical Research Centre of Imperial College NHS.

From simple to complex: Protein-based biomarker discovery in tuberculosis

Tuberculosis (TB) is a deadly infectious disease that affects millions of people globally. TB proteomics signature discovery has been a rapidly growing area of research that aims to identify protein biomarkers for the early detection, diagnosis, and treatment monitoring of TB. In this review, we have highlighted recent advances in this field and how it is moving from the study of single proteins to high-throughput profiling and from only using proteomics to include additional types of data in multi-omics studies. We have further covered the different sample types and experimental technologies used in TB proteomics signature discovery, focusing on studies of HIV-negative adults. The published signatures were defined as either coming from hypothesis-based protein targeting or from unbiased discovery approaches. The methodological approaches influenced the type of proteins identified and were associated with the circulating protein abundance. However, both approaches largely identified proteins involved in similar biological pathways, including acute-phase responses and T-helper type 1 and type 17 responses. By analysing the frequency of proteins in the different signatures, we could also highlight potential robust biomarker candidates. Finally, we discuss the potential value of integration of multi-omics data and the importance of control cohorts and signature validation.

Diagnostic performance of host protein signatures as a triage test for active pulmonary TB

The current four-symptom screen recommended by the World Health Organization (WHO) is widely used as screen to initiate diagnostic testing for active pulmonary tuberculosis (TB), yet the performance is poor especially when TB prevalence is low. In contrast, more sensitive molecular tests are less suitable for placement at primary care level in low-resource settings. In order to meet the WHO End TB targets, new diagnostic approaches are urgently needed to find the missing undiagnosed cases. Proteomics-derived blood host biomarkers have been explored because protein detection technologies are suitable for the point-of-care setting and could meet cost targets. This study aimed to find a biomarker signature that fulfills WHO's target product profile (TPP) for a TB screening. Twelve blood-based protein biomarkers from three sample populations (Vietnam, Peru, and South Africa) were analyzed individually and in combinations via advanced statistical methods and machine learning algorithms. The combination of I-309, SYWC and kallistatin showed the most promising results to discern active TB throughout the data sets meeting the TPP for a triage test in adults from two countries (Peru and South Africa). The top-performing individual markers identified at the global level (I-309 and SYWC) were also among the best-performing markers at country level in South Africa and Vietnam. This analysis clearly shows that a host protein biomarker assay is feasible in adults for certain geographical regions based on one or two biomarkers with a performance that meets minimal WHO TPP criteria.

Field evaluation of a point-of-care triage test for active tuberculosis (TriageTB)

BACKGROUND

To improve tuberculosis (TB) diagnosis, the World Health Organisation (WHO) has called for a non-sputum based triage test to focus TB testing on people with a high likelihood of having active pulmonary tuberculosis (TB). Various host or pathogen biomarker-based testing devices are in design stage and require validity assessment. Host biomarkers have shown promise to accurately rule out active TB, but further research is required to determine generalisability. The TriageTB diagnostic test study aims to assess the accuracy of diagnostic test candidates, as well as field-test, finalise the design and biomarker signature, and validate a point-of-care multi-biomarker test (MBT).

METHODS

This observational diagnostic study will evaluate sensitivity and specificity of biomarker-based diagnostic candidates including the MBT and Xpert® TB Fingerstick cartridge compared with a gold-standard composite TB outcome classification defined by symptoms, sputum GeneXpert® Ultra, smear and culture, radiological features, response to TB therapy and presence of an alternative diagnosis. The study will be conducted in research sites in South Africa, Uganda, The Gambia and Vietnam which all have high TB prevalence. The two-phase design allows for finalisation of the MBT in Phase 1 in which candidate host proteins will be evaluated on stored serum from Asia, South Africa and South America and on fingerstick blood from 50 newly recruited participants per site. The MBT test will then be locked down and validated in Phase 2 on 250 participants per site.

DISCUSSION

By targeting confirmatory TB testing to those with a positive triage test, 75% of negative GXPU may be avoided, thereby reducing diagnostic costs and patient losses during the care cascade. This study builds on previous biomarker research and aims to identify a point-of-care test meeting or exceeding the minimum World Health Organisation target product profile of a 90% sensitivity and 70% specificity. Streamlining TB testing by identifying individuals with a high likelihood of TB should improve TB resources use and, in so doing, improve TB care.

TRIAL REGISTRATION

NCT04232618 (clinicaltrials.gov) Date of registration: 16 January 2020.

Point-of-care test for tuberculosis: a boon in diagnosis

Rapid diagnosis of tuberculosis (TB) is an effective measure to eradicate this infectious disease worldwide. Traditional methods for screening TB patients do not provide an immediate diagnosis and thus delay treatment. There is an urgent need for the early detection of TB through point-of-care tests (POCTs). Several POCTs are widely available at primary healthcare facilities that assist in TB screening. In addition to the currently used POCTs, advancements in technology have led to the discovery of newer methods that provide accurate and fast information independent of access to laboratory facilities. In the present article, the authors tried to include and describe the potential POCTs for screening TB in patients. Several molecular diagnostic tests, such as nucleic acid amplification tests, including GeneXpert and TB-loop-mediated isothermal amplification, are currently being used as POCTs. Besides these methods, the pathogenic component of Mycobacterium tuberculosis can also be utilized as a biomarker for screening purposes through immunological assays. Similarly, the host immune response to infection has also been utilized as a marker for the diagnosis of TB. These novel biomarkers might include Mtb85, interferon-γ inducible protein-10, volatile organic compounds, acute-phase proteins, etc. Radiological tests have also been observed as POCTs in the TB screening POCT panel. Various POCTs are performed on samples other than sputum, which further eases the screening process. These POCTs should not require large-scale manpower and infrastructure. Hence, POCT should be able to identify patients with M. tuberculosis infection at the primary healthcare level only. There are several other advanced techniques that have been proposed as future POCTs and have been discussed in the present article.

Advancing personalized medicine for tuberculosis through the application of immune profiling

While early and precise diagnosis is the key to eliminating tuberculosis (TB), conventional methods using culture conversion or sputum smear microscopy have failed to meet demand. This is especially true in high-epidemic developing countries and during pandemic-associated social restrictions. Suboptimal biomarkers have restricted the improvement of TB management and eradication strategies. Therefore, the research and development of new affordable and accessible methods are required. Following the emergence of many high-throughput quantification TB studies, immunomics has the advantages of directly targeting responsive immune molecules and significantly simplifying workloads. In particular, immune profiling has been demonstrated to be a versatile tool that potentially unlocks many options for application in TB management. Herein, we review the current approaches for TB control with regard to the potentials and limitations of immunomics. Multiple directions are also proposed to hopefully unleash immunomics' potential in TB research, not least in revealing representative immune biomarkers to correctly diagnose TB. The immune profiles of patients can be valuable covariates for model-informed precision dosing-based treatment monitoring, prediction of outcome, and the optimal dose prediction of anti-TB drugs.

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

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

Immunologic Biomarkers in Peripheral Blood of Persons With Tuberculosis and Advanced HIV

Introduction

Tuberculosis (TB) is a common opportunistic infection among people living with HIV. Diagnostic tests such as culture, Xpert-MTB-RIF, and ULTRA have low sensitivity in paucibacillary TB disease; a blood biomarker could improve TB diagnostic capabilities. We assessed soluble factors to identify biomarkers associated with TB among persons with advanced HIV.

Methods

A case-control (1:1) study was conducted, with participants from Rio de Janeiro and Manaus, Brazil. People living with HIV presenting with CD4 count ≤100 cells/mm3 were eligible to participate. Cases had culture-confirmed TB (N=15) (positive for Mycobacterium tuberculosis [Mtb]); controls had HIV-infection only (N=15). Study visits included baseline, month 2 and end of TB therapy, during which samples of peripheral blood were obtained. A panel containing 29 biomarkers including cytokines, chemokines and growth factors was utilized to assess candidate biomarkers using Luminex technology in cryopreserved EDTA plasma samples. We used neural network analysis, based on machine learning, to identify biomarkers (single or in combination) that best distinguished cases from controls. Additional multi-dimensional analyses provided detailed profiling of the systemic inflammatory environment in cases and controls.

Results

Median CD4 count and HIV-1 RNA load values were similar between groups at all timepoints. Persons with TB had lower body mass index (BMI) (median=19.6, Interquartile Range [IQR]=18.6-22.3) than controls (23.7; IQR: 21.8 = 25.5, p=0.004). TB coinfection was also associated with increased frequency of other comorbidities. The overall profile of plasma cytokines, chemokines and growth factors were distinct between the study groups at all timepoints. Plasma concentrations of IL-15 and IL-10 were on average lower in TB cases than in controls. When used in combination, such markers were able to discriminate between TB cases and controls with the highest degree of accuracy at each study timepoint.

Conclusion

Among persons with advanced HIV, plasma concentrations of IL-15 and IL-10 can be used in combination to identify TB disease regardless of time on anti-TB treatment.

Evaluation of Host Protein Biomarkers by ELISA From Whole Lysed Peripheral Blood for Development of Diagnostic Tests for Active Tuberculosis

Tuberculosis (TB) remains a significant global health crisis and the number one cause of death for an infectious disease. The health consequences in high-burden countries are significant. Barriers to TB control and eradication are in part caused by difficulties in diagnosis. Improvements in diagnosis are required for organisations like the World Health Organisation (WHO) to meet their ambitious target of reducing the incidence of TB by 50% by the year 2025, which has become hard to reach due to the COVID-19 pandemic. Development of new tests for TB are key priorities of the WHO, as defined in their 2014 report for target product profiles (TPPs). Rapid triage and biomarker-based confirmatory tests would greatly enhance the diagnostic capability for identifying and diagnosing TB-infected individuals. Protein-based test methods e.g. lateral flow devices (LFDs) have a significant advantage over other technologies with regard to assay turnaround time (minutes as opposed to hours) field-ability, ease of use by relatively untrained staff and without the need for supporting laboratory infrastructure. Here we evaluate the diagnostic performance of nine biomarkers from our previously published biomarker qPCR validation study; CALCOCO2, CD274, CD52, GBP1, IFIT3, IFITM3, SAMD9L, SNX10 and TMEM49, as protein targets assayed by ELISA. This preliminary evaluation study was conducted to quantify the level of biomarker protein expression across latent, extra-pulmonary or pulmonary TB groups and negative controls, collected across the UK and India, in whole lysed blood samples (WLB). We also investigated associative correlations between the biomarkers and assessed their suitability for ongoing diagnostic test development, using receiver operating characteristic/area under the curve (ROC) analyses, singly and in panel combinations. The top performing single biomarkers for pulmonary TB versus controls were CALCOCO2, SAMD9L, GBP1, IFITM3, IFIT3 and SNX10. TMEM49 was also significantly differentially expressed but downregulated in TB groups. CD52 expression was not highly differentially expressed across most of the groups but may provide additional patient stratification information and some limited use for incipient latent TB infection. These show therefore great potential for diagnostic test development either in minimal configuration panels for rapid triage or more complex formulations to capture the diversity of disease presentations.

Validation of host cerebrospinal fluid protein biomarkers for early diagnosis of tuberculous meningitis in children: a replication and new biosignature discovery study

The diagnosis of tuberculous meningitis (TBM) in children is often delayed due to diagnostic difficulties. New tools are urgently needed to improve the diagnosis of the disease in this vulnerable group. The present study aimed to validate the accuracy of recently identified host cerebrospinal (CSF) biomarkers as candidates for the diagnosis of TBM in children. We collected CSF samples from 87 children aged 3 months to 13 years, that were consecutively admitted at a tertiary hospital in Cape Town, South Africa, on suspicion of having TBM. We evaluated the concentrations of 67 selected host protein biomarkers using a multiplex platform. Previously identified 3-marker (VEGF-A + IFN-γ + MPO) and 4-marker (IFN-γ + MPO + ICAM-1 + IL-8) signatures diagnosed TBM with AUCs of 0.89 (95% CI, 0.81-0.97) and 0.87 (95% CI, 0.79-0.95) respectively; sensitivities of 80.6% (95% CI, 62.5-92.5%) and 81.6% (95% CI, 65.7-92.3%), and specificities of 86.8% (71.9-95.6%) and 83.7% (70.4-92.7%) respectively. Furthermore, a new combination between the analytes (CC4b + CC4 + procalcitonin + CCL1) showed promise, with an AUC of 0.98 (95% CI, 0.94-1.00). We have shown that the accuracies of previously identified candidate CSF biomarkers for childhood TBM was reproducible. Our findings augur well for the future development of a simple bedside test for the rapid diagnosis of TBM in children.

Machine learning based on routine laboratory indicators promoting the discrimination between active tuberculosis and latent tuberculosis infection

BACKGROUND

Discriminating active tuberculosis (ATB) from latent tuberculosis infection (LTBI) remains challenging. The present study aims to evaluate the performance of diagnostic models established using machine learning based on routine laboratory indicators in differentiating ATB from LTBI.

METHODS

Participants were respectively enrolled at Tongji Hospital (discovery cohort) and Sino-French New City Hospital (validation cohort). Diagnostic models were established based on routine laboratory indicators using machine learning.

RESULTS

A total of 2619 participants (1025 ATB and 1594 LTBI) were enrolled in discovery cohort and another 942 subjects (388 ATB and 554 LTBI) were recruited in validation cohort. ATB patients had significantly higher levels of tuberculosis-specific antigen/phytohemagglutinin ratio and coefficient variation of red blood cell volume distribution width, and lower levels of albumin and lymphocyte count than those of LTBI individuals. Six models were built and the optimal performance was obtained from GBM model. GBM model derived from training set (n = 1965) differentiated ATB from LTBI in the test set (n = 654) with a sensitivity of 84.38% (95% CI, 79.42%-88.31%) and a specificity of 92.71% (95% CI, 89.73%-94.88%). Further validation by an independent cohort confirmed its encouraging value with a sensitivity of 87.63% (95% CI, 83.98%-90.54%) and specificity of 91.34% (95% CI, 88.70%-93.40%), respectively.

CONCLUSIONS

We successfully developed a model with promising diagnostic value based on machine learning for the first time. Our study proposed that GBM model may be of great benefit served as a tool for the accurate identification of ATB.

Concurrent evaluation of cytokines improves the accuracy of antibodies against Mycobacterium tuberculosis antigens in the diagnosis of active tuberculosis

BACKGROUND

Antibodies against mycobacterial proteins are highly specific, but lack sensitivity, whereas cytokines have been shown to be sensitive but not very specific in the diagnosis of tuberculosis (TB). We assessed combinations between antibodies and cytokines for diagnosing TB.

METHODS

Immuoglubulin (Ig) A and IgM antibody titres against selected mycobacterial antigens including Apa, NarL, Rv3019c, PstS1, LAM, "Kit 1" (MTP64 and Tpx)", and "Kit 2" (MPT64, Tpx and 19 kDa) were evaluated by ELISA in plasma samples obtained from individuals under clinical suspicion for TB. Combinations between the antibody titres and previously published cytokine responses in the same participants were assessed for diagnosing active TB.

RESULTS

Antibody responses were more promising when used in combination (AUC of 0.80), when all seven antibodies were combined. When anti-"Kit 1"-IgA levels were combined with five host cytokine biomarkers, the AUC increased to 97% (92-100%) with a sensitivity of 95% (95% CI, 73-100%), and specificity of 88.5% (95% CI, 68.7-97%) achieved after leave-one-out cross validation.

CONCLUSION

When used in combination, IgA titres measured with ELISA against multiple Mycobacterium tuberculosis antigens may be useful in the diagnosis of TB. However, diagnostic accuracy may be improved if the antibodies are used in combination with cytokines.

Combination of HLA-DR on Mycobacterium tuberculosis-Specific Cells and Tuberculosis Antigen/Phytohemagglutinin Ratio for Discriminating Active Tuberculosis From Latent Tuberculosis Infection

Background

Novel approaches for tuberculosis (TB) diagnosis, especially for distinguishing active TB (ATB) from latent TB infection (LTBI), are urgently warranted. The present study aims to determine whether the combination of HLA-DR on Mycobacterium tuberculosis (MTB)-specific cells and TB antigen/phytohemagglutinin (TBAg/PHA) ratio could facilitate MTB infection status discrimination.

Methods

Between June 2020 and June 2021, participants with ATB and LTBI were recruited from Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort), respectively. The detection of HLA-DR on MTB-specific cells upon TB antigen stimulation and T-SPOT assay were simultaneously performed on all subjects.

Results

A total of 116 (54 ATB and 62 LTBI) and another 84 (43 ATB and 41 LTBI) cases were respectively enrolled from Qiaokou cohort and Caidian cohort. Both HLA-DR on IFN-γ⁺TNF-α⁺ cells and TBAg/PHA ratio showed discriminatory value in distinguishing between ATB and LTBI. Receiver operator characteristic (ROC) curve analysis showed that HLA-DR on IFN-γ⁺TNF-α⁺ cells produced an area under the ROC curve (AUC) of 0.886. Besides, TBAg/PHA ratio yield an AUC of 0.736. Furthermore, the combination of these two indicators resulted in the accurate discrimination with an AUC of 0.937. When the threshold was set as 0.36, the diagnostic model could differentiate ATB from LTBI with a sensitivity of 92.00% and a specificity of 81.82%. The performance obtained in Qiaokou cohort was further validated in Caidian cohort.

Conclusions

The combination of HLA-DR on MTB-specific cells and TBAg/PHA ratio could serve as a robust tool to determine TB disease states.

Quantitative Rapid Test for Detection and Monitoring of Active Pulmonary Tuberculosis in Nonhuman Primates

Nonhuman primates (NHPs) are relevant models to study the pathogenesis of tuberculosis (TB) and evaluate the potential of TB therapies, but rapid tools allowing diagnosis of active pulmonary TB in NHPs are lacking. This study investigates whether low complexity lateral flow assays utilizing upconverting reporter particles (UCP-LFAs) developed for rapid detection of human serum proteins can be applied to detect and monitor active pulmonary TB in NHPs. UCP-LFAs were used to assess serum proteins levels and changes in relation to the MTB challenge dosage, lung pathology, treatment, and disease outcome in experimentally MTB-infected macaques. Serum levels of SAA1, IP-10, and IL-6 showed a significant increase after MTB infection in rhesus macaques and correlated with disease severity as determined by pathology scoring. Moreover, these biomarkers could sensitively detect the reduction of bacterial levels in the lungs of macaques due to BCG vaccination or drug treatment. Quantitative measurements by rapid UCP-LFAs specific for SAA1, IP-10, and IL-6 in serum can be utilized to detect active progressive pulmonary TB in macaques. The UCP-LFAs thus offer a low-cost, convenient, and minimally invasive diagnostic tool that can be applied in studies on TB vaccine and drug development involving macaques.

Candidate Biomarkers to Distinguish Spinal Tuberculosis From Mechanical Back Pain in a Tuberculosis Endemic Setting

Background

Spinal tuberculosis (TB) may have a variable, non-specific presentation including back pain with- or without- constitutional symptoms. Further tools are needed to aid early diagnosis of this potentially severe form of TB and immunological biomarkers may show potential in this regard. The aim of this study was to investigate the utility of host serum biomarkers to distinguish spinal TB from mechanical back pain.

Methods

Patients with suspected spinal TB or suspected mechanical back pain were recruited from a tertiary hospital in the Western Cape, South Africa, and provided a blood sample for biomarker analysis. Diagnosis was subsequently confirmed using bacteriological testing, advanced imaging and/or clinical evaluation, as appropriate. The concentrations of 19 host biomarkers were evaluated in serum samples using the Luminex platform. Receiver Operating Characteristic (ROC) curves and General Discriminant Analysis were used to identify biomarkers with the potential to distinguish spinal TB from mechanical back pain.

Results

Twenty-six patients with spinal TB and 17 with mechanical back pain were recruited. Seven out of 19 biomarkers were significantly different between groups, of which Fibrinogen, CRP, IFN-γ and NCAM were the individual markers with the highest discrimination utility (Area Under Curve ROC plot 0.88-0.99). A five-marker biosignature (CRP, NCAM, Ferritin, CXCL8 and GDF-15) correctly classified all study participants after leave-one-out cross-validation.

Conclusion

This study identified host serum biomarkers with the potential to diagnose spinal TB, including a five-marker biosignature. These preliminary findings require validation in larger studies.

Serum Biomarker Profile Including CCL1, CXCL10, VEGF, and Adenosine Deaminase Activity Distinguishes Active From Remotely Acquired Latent Tuberculosis

Introduction

There is an urgent medical need to differentiate active tuberculosis (ATB) from latent tuberculosis infection (LTBI) and prevent undertreatment and overtreatment. The aim of this study was to identify biomarker profiles that may support the differentiation between ATB and LTBI and to validate these signatures.

Materials and Methods

The discovery cohort included adult individuals classified in four groups: ATB (n = 20), LTBI without prophylaxis (untreated LTBI; n = 20), LTBI after completion of prophylaxis (treated LTBI; n = 20), and healthy controls (HC; n = 20). Their sera were analyzed for 40 cytokines/chemokines and activity of adenosine deaminase (ADA) isozymes. A prediction model was designed to differentiate ATB from untreated LTBI using sparse partial least squares (sPLS) and logistic regression analyses. Serum samples of two independent cohorts (national and international) were used for validation.

Results

sPLS regression analyses identified C-C motif chemokine ligand 1 (CCL1), C-reactive protein (CRP), C-X-C motif chemokine ligand 10 (CXCL10), and vascular endothelial growth factor (VEGF) as the most discriminating biomarkers. These markers and ADA(2) activity were significantly increased in ATB compared to untreated LTBI (p ≤ 0.007). Combining CCL1, CXCL10, VEGF, and ADA2 activity yielded a sensitivity and specificity of 95% and 90%, respectively, in differentiating ATB from untreated LTBI. These findings were confirmed in the validation cohort including remotely acquired untreated LTBI participants.

Conclusion

The biomarker signature of CCL1, CXCL10, VEGF, and ADA2 activity provides a promising tool for differentiating patients with ATB from non-treated LTBI individuals.

Past and Present Approaches to Diagnosis of Active Pulmonary Tuberculosis

Tuberculosis disease continues to contribute to the mortality burden globally. Due to the several shortcomings of the available diagnostic methods, tuberculosis disease continues to spread. The difficulty to obtain sputum among the very ill patients and the children also affects the quick diagnosis of tuberculosis disease. These challenges warrant investigating different sample types that can provide results in a short time. Highlighted in this review are the approved pulmonary tuberculosis diagnostic methods and ongoing research to improve its diagnosis. We used the PRISMA guidelines for systematic reviews to search for studies that met the selection criteria for this review. In this review we found out that enormous biosignature research is ongoing to identify host biomarkers that can be used as predictors of active PTB disease. On top of this, more research was also being done to improve already existing diagnostic tests. Host markers required more optimization for use in different settings given their varying sensitivity and specificity in PTB endemic and non-endemic settings.

Activation Phenotype of Mycobacterium tuberculosis-Specific CD4+ T Cells Promoting the Discrimination Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Rapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue.

Methods

Participants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4⁺ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation.

Results

A total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α⁺ or IL-2⁺ cells had superiority over that on IFN-γ⁺ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α⁺IL-2⁺ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α⁺IL-2⁺ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity.

Conclusions

We demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

CCL1 and IL-2Ra differentiate Tuberculosis disease from latent infection Irrespective of HIV infection in low TB burden countries

OBJECTIVES

To evaluate the performance of selected host immunological biomarkers in differentiating tuberculosis (TB) disease from latent TB infection (LTBI) in HIV uninfected and infected individuals enrolled in TB low-burden countries.

DESIGN

Participants with TB disease (N = 85) and LTBI (N = 150) were recruited from prospective cohorts at hospitals in Norway and Denmark. Plasma concentrations of 54 host markers were assessed by Luminex multiplex immunoassays. Using receiver operator characteristic curves and general discriminant analysis, we determined the abilities of individual and combined biomarkers to discriminate between TB disease and LTBI including when patients were stratified according to HIV infection status.

RESULTS

Regardless of the groups compared, CCL1 and IL-2Ra were the most accurate single biomarkers in differentiating TB disease from LTBI. Regardless of HIV status, a 4-marker signature (CCL1+RANTES+CRP+MIP-1α) derived from a training set (n = 155) differentiated TB disease from LTBI in the test set (n = 67) with a sensitivity of 56.0% (95% CI, 34.9-75.6) and a specificity of 85.7% (95% CI, 71.5-94.6). A 5-marker signature derived from the HIV uninfected group (CCL1+RANTES+MIP-1α+procalcitonin+IP-10) performed in HIV-infected individuals with a sensitivity of 75.0% and a specificity of 96.7% after leave-one-out cross validation. A 2-marker signature (CCL1+TNF-α) identified in HIV-infected persons performed in HIV-uninfected with a sensitivity and specificity of 66.7% and 100% respectively in the test set.

CONCLUSIONS

Plasma CCL1 and IL-2Ra have potential as biomarkers for differentiating TB disease from LTBI in low TB burden settings unaffected by HIV infection. Combinations between these and other biomarkers in bio-signatures for global use warrant further exploration.