Diagnostic Performance of a Cytokine and IFN-γ–Induced Chemokine mRNA Assay after Mycobacterium tuberculosis–Specific Antigen Stimulation in Whole Blood from Infected Individuals

Effect of tuberculosis-specific antigen stimulation on the diagnostic accuracy of interferon-γ inducible protein-10 in distinguishing active and latent tuberculosis infection: a meta-analysis

BACKGROUND

Identifying active tuberculosis (ATB) from latent tuberculosis infection (LTBI) persists as a challenge, and interferon-γ inducible protein-10 (IP-10) has been employed as the solution. To further improve its diagnostic performance, the sample can be stimulated with TB specific antigen (TBAg).

AIM

To perform meta-analysis on diagnostic accuracy of unstimulated and TBAg-stimulated IP-10 in differentiating ATB from LTBI.

METHODS

Systematic search was performed on five major scientific databases as of 29 November 2023. Observational studies reporting diagnostic values of unstimulated or TBAg-stimulated IP-10 in identifying ATB from LTBI were included. Meta-analysis was carried out using two-level mixed-effect logistic regression model.

RESULTS

Twenty-five studies recruiting 2301 patients (1137 ATB versus 1164 LTBI) were included in the quantitative analysis. The pooled sensitivity and specifity of IP-10 were 72% (95%CI: 0.59-0.82) and 78% (95%CI: 0.63-0.88), respectively. As for TBAg-stimulated IP-10, the sensitivity and specifity were 82% (95%CI: 0.76-0.87) and 85% (95%CI: 0.73-0.92), respectively. The senstivity was reduced signiticantly (p < 0.01) when the patients with human immunodeficiency virus infection were included, except after the TBAg stimulation.

CONCLUSION

Stimulating IP-10 with TBAg could improve the diagnostic accuracy in differentiating ATB from LTBI.

Performance of T-Track® TB, a Novel Dual Marker RT-qPCR-Based Whole-Blood Test for Improved Detection of Active Tuberculosis

Tuberculosis (TB) is one of the leading causes of death by an infectious disease. It remains a major health burden worldwide, in part due to misdiagnosis. Therefore, improved diagnostic tests allowing the faster and more reliable diagnosis of patients with active TB are urgently needed. This prospective study examined the performance of the new molecular whole-blood test T-Track^® TB, which relies on the combined evaluation of IFNG and CXCL10 mRNA levels, and compared it to that of the QuantiFERON^®-TB Gold Plus (QFT-Plus) enzyme-linked immunosorbent assay (ELISA). Diagnostic accuracy and agreement analyses were conducted on the whole blood of 181 active TB patients and 163 non-TB controls. T-Track^® TB presented sensitivity of 94.9% and specificity of 93.8% for the detection of active TB vs. non-TB controls. In comparison, the QFT-Plus ELISA showed sensitivity of 84.3%. The sensitivity of T-Track^® TB was significantly higher (p < 0.001) than that of QFT-Plus. The overall agreement of T-Track^® TB with QFT-Plus to diagnose active TB was 87.9%. Out of 21 samples with discordant results, 19 were correctly classified by T-Track^® TB while misclassified by QFT-Plus (T-Track^® TB-positive/QFT-Plus-negative), and two samples were misclassified by T-Track^® TB while correctly classified by QFT-Plus (T-Track^® TB-negative/QFT-Plus-positive). Our results demonstrate the excellent performance of the T-Track^® TB molecular assay and its suitability to accurately detect TB infection and discriminate active TB patients from non-infected controls.

Challenges and the Way forward in Diagnosis and Treatment of Tuberculosis Infection

Globally, it is estimated that one-quarter of the world's population is latently infected with Mycobacterium tuberculosis (Mtb), also known as latent tuberculosis infection (LTBI). Recently, this condition has been referred to as tuberculosis infection (TBI), considering the dynamic spectrum of the infection, as 5-10% of the latently infected population will develop active TB (ATB). The chances of TBI development increase due to close contact with index TB patients. The emergence of multidrug-resistant TB (MDR-TB) and the risk of development of latent MDR-TB has further complicated the situation. Detection of TBI is challenging as the infected individual does not present symptoms. Currently, there is no gold standard for TBI diagnosis, and the only screening tests are tuberculin skin test (TST) and interferon gamma release assays (IGRAs). However, these tests have several limitations, including the inability to differentiate between ATB and TBI, false-positive results in BCG-vaccinated individuals (only for TST), false-negative results in children, elderly, and immunocompromised patients, and the inability to predict the progression to ATB, among others. Thus, new host markers and Mtb-specific antigens are being tested to develop new diagnostic methods. Besides screening, TBI therapy is a key intervention for TB control. However, the long-course treatment and associated side effects result in non-adherence to the treatment. Additionally, the latent MDR strains are not susceptible to the current TBI treatments, which add an additional challenge. This review discusses the current situation of TBI, as well as the challenges and efforts involved in its control.

Identification of MicroRNAs as Potential Blood-Based Biomarkers for Diagnosis and Therapeutic Monitoring of Active Tuberculosis

Early diagnosis increases the treatment success rate for active tuberculosis (ATB) and decreases mortality. MicroRNAs (miRNAs) have been studied as blood-based markers of several infectious diseases. We performed miRNA profiling to identify differentially expressed (DE) miRNAs using whole blood samples from 10 healthy controls (HCs), 15 subjects with latent tuberculosis infection (LTBI), and 12 patients with ATB, and investigated the expression of the top six miRNAs at diagnosis and over the treatment period in addition to performing miRNA-target gene network and gene ontology analyses. miRNA profiling identified 84 DE miRNAs in patients with ATB, including 80 upregulated and four downregulated miRNAs. Receiver operating characteristic curves of the top six miRNAs exhibited excellent distinguishing efficiency with an area under curve (AUC) value > 0.85. Among them, miR-199a-3p and miR-6886-3p can differentiate between ATB and LTBI. Anti-TB treatment restored the levels of miR-199b-3p, miR-199a-3p, miR-16-5p, and miR-374c-5p to HC levels. Furthermore, 108 predicted target genes were related to the regulation of cellular amide metabolism, intrinsic apoptotic signaling, translation, transforming growth factor beta receptor signaling, and cysteine-type endopeptidase activity. The DE miRNAs identified herein are potential biomarkers for diagnosis and therapeutic monitoring in ATB.

STAT1 and CXCL10 involve in M1 macrophage polarization that may affect osteolysis and bone remodeling in extrapulmonary tuberculosis

OBJECTIVE

This study was aimed to reveal the molecular mechanism of bone destruction due to macrophage polarization leading to during extrapulmonary tuberculosis (EPTB) infection.

METHODS

The dataset GSE83456 was downloaded from the GEO database, and the xCell tool was used to obtain the 64 types of immune cells. The flow cytometry was performed to identified the differences between M1 and M2 macrophages between EPTB and the healthy controls (HCs). The enrichment analyses were performed on the differentially expressed genes (DEGs) and their functionally related modules. The hub genes were screened out, and their relationships with EPTB and the immune cell subtypes were further analyzed.

RESULTS

The flow cytometric analysis validated this hypothesis of M1-macrophage polarization correlated with the pathogenesis of EPTB. Of the obtained 103 DEGs, 97 genes were upregulated, and 6 genes were downregulated. The GO and KEGG pathway analyses showed that the DEGs were particularly involved in the immune-related processes. The hub genes (STAT1 and CXCL10) might be involved in M1-macrophage polarization and correlated with the pathogenesis of EPTB. STAT1 and CXCL10 could also behave as biomarkers for EPTB.

CONCLUSION

STAT1 and CXCL10 were involved in the M1-macrophage polarization and correlated with the pathogenesis of EPTB. Besides, both of them could also behave as biomarkers for EPTB diagnosis and provide the required clues for targeted therapy in the future.

Assessment of Interferon Gamma-Induced Protein 10 mRNA Release Assay for Detection of Latent Tuberculosis Infection in Egyptian Pediatric Household Contacts

OBJECTIVES

Current diagnostic tests for tuberculosis (TB) in children living in low-endemic countries are limited by low specificity and the inability of the current tests to differentiate between active TB and latent TB infection (LTBI). This study aimed to evaluate the blood IP-10 mRNA expression level to detect LTBI in Egyptian pediatric household contacts (PHC).

METHODS

TB-specific IP-10 and IFN-γ mRNA levels were assessed by real-time quantitative PCR (RT-qPCR) in 72 Egyptian PHC of active pulmonary TB cases. All study participants were also assessed by Tuberculin Skin Test (TST) and Quantiferon gold in tube (QFN-GIT) assay.

RESULTS

IP-10 and IFN-γ mRNA expression levels were significantly higher in PHC with active TB or LTBI than TB negative (p < 0.0001). The level of IP-10 mRNA expression was significantly higher in PHC with active TB than LTBI (p = 0.0008). In contrast, there was no significant differences in the IFN-γ mRNA expression between PHC with active TB compared to LTBI (p = 0.49). The sensitivity and specificity of the IP-10 RT-qPCR were 94.2% and 95.2%, respectively, in PHC with active TB compared to 85.7% and 81.8% in PHC with LTBI. The negative and positive predictive values and accuracy of IP-10 RT-qPCR for distinguishing active TB from LTBI were 85.2%, 58.3%, and 72.6% respectively.

CONCLUSION

Blood IP-10 mRNA expression level may be a potential diagnostic marker to help distinguish active TB from LTBI in PHC.

Engineered Mycobacterium tuberculosis antigen assembly into core-shell nanobeads for diagnosis of tuberculosis

Despite recent advances in diagnosis, tuberculosis (TB) remains one of the ten leading causes of death worldwide. Here, we engineered Mycobacterium tuberculosis (Mtb) proteins (ESAT6, CFP10, and MTB7.7) to self-assemble into core-shell nanobeads for enhanced TB diagnosis. Respective purified Mtb antigen-coated polyester beads were characterized and their functionality in TB diagnosis was tested in whole blood cytokine release assays. Sensitivity and specificity were studied in 11 pulmonary TB patients (PTB) and 26 healthy individuals composed of 14 Tuberculin Skin Test negative (TSTn) and 12 TST positive (TSTp). The production of 6 cytokines was determined (IFNγ, IP10, IL2, TNFα, CCL3, and CCL11). To differentiate PTB from healthy individuals (TSTp + TSTn), the best individual cytokines were IL2 and CCL11 (>80% sensitivity and specificity) and the best combination was IP10 + IL2 (>90% sensitivity and specificity). We describe an innovative approach using full-length antigens attached to biopolyester nanobeads enabling sensitive and specific detection of human TB.

Monokine induced by gamma interferon for detecting pulmonary tuberculosis: A diagnostic meta-analysis

BACKGROUNDS

Pulmonary tuberculosis (PTB) is an oldest-known and most formidable disease. The standard microbiology culture is time-wasting. Monokine induced by gamma interferon (MIG) has been reported as a new biomarker to auxiliarily detect PTB. In our study, we used meta-analysis to assess the diagnostic value of MIG for PTB.

METHODS

PubMed, Embase, Web of Science, and Cochrane Library were searched for relative records up to April 2, 2020. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, area under the curve, and summary receiver operating characteristic curve were estimated.

RESULTS

Eight studies including 1487 participants were included. The pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of MIG for detecting PTB were 84%, 84%, 5.19, and 0.19, respectively. The diagnostic odds ratio and area under the curve were 27.88 and 0.90, respectively, indicating a good diagnostic ability of MIG. Meta-regression analysis showed that human immunodeficiency virus status might be a source of heterogeneity (P = .02).

CONCLUSIONS

Our results showed that MIG had a good diagnostic value for PTB.

Evaluation of cytokines as a biomarker to distinguish active tuberculosis from latent tuberculosis infection: a diagnostic meta-analysis

OBJECTIVES

With a marginally effective vaccine and no significant breakthroughs in new treatments, a sensitive and specific method to distinguish active tuberculosis from latent tuberculosis infection (LTBI) would allow for early diagnosis and limit the spread of the pathogen. The analysis of multiple cytokine profiles provides the possibility to differentiate the two diseases.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

PubMed, Cochrane Library, Clinical Key and EMBASE databases were searched on 31 December 2019.

ELIGIBILITY CRITERIA

We included case-control studies, cohort studies and randomised controlled trials considering IFN-γ, TNF-α, IP-10, IL-2, IL-10, IL-12 and VEGF as biomarkers to distinguish active tuberculosis and LTBI.

DATA EXTRACTION AND SYNTHESIS

Two students independently extracted data and assessed the risk of bias. Diagnostic OR, sensitivity, specificity, positive and negative likelihood ratios and area under the curve (AUC) together with 95% CI were used to estimate the diagnostic value.

RESULTS

Of 1315 records identified, 14 studies were considered eligible. IL-2 had the highest sensitivity (0.84, 95% CI: 0.72 to 0.92), while VEGF had the highest specificity (0.87, 95% CI: 0.73 to 0.94). The highest AUC was observed for VEGF (0.85, 95% CI: 0.81 to 0.88), followed by IFN-γ (0.84, 95% CI: 0.80 to 0.87) and IL-2 (0.84, 95% CI: 0.81 to 0.87).

CONCLUSION

Cytokines, such as IL-2, IFN-γ and VEGF, can be utilised as promising biomarkers to distinguish active tuberculosis from LTBI.

PROSPERO REGISTRATION NUMBER

CRD42020170725.

Diagnostic Accuracy of Interferon Gamma-Induced Protein 10 mRNA Release Assay for Tuberculosis

Interferon gamma (IFN-γ) release assays (IGRAs) are increasingly used to test for latent tuberculosis (TB) infection. Although highly specific, IGRAs have a relatively high false-negative rate in active TB patients. A more sensitive assay is needed. IFN-γ-induced protein 10 (IP-10) is an alternative biomarker with a 100-fold-higher expression level than IFN-γ, allowing for different analysis platforms, including molecular detection. The PCR technique is already an integrated tool in most TB laboratories and, thus, an obvious platform to turn to. In this case-control study, we investigated the diagnostic sensitivity and specificity of a molecular assay detecting IP-10 mRNA expression following antigen stimulation of a blood sample. We included 89 TB patients and 99 healthy controls. Blood was drawn in QuantiFeron-TB gold in-tube (QFT) assay tubes. Eight hours poststimulation, IP-10 mRNA expression was analyzed, and 20 h poststimulation, IP-10 and IFN-γ protein plasma levels were analyzed using an in-house IP-10 enzyme-linked immunosorbent assay (ELISA) and the official QFT ELISA, respectively. The IP-10 mRNA assay provided high specificity (98%), sensitivity (80%), and area under the concentration-time curve (AUC) (0.97); however, the QFT assay provided a higher overall diagnostic potential, with specificity of 100%, sensitivity of 90%, and AUC of 0.99. The IP-10 protein assay performed on par with the QFT assay, with specificity of 98%, sensitivity of 87%, and AUC of 0.98. We have provided proof of high technical performance of a molecular assay detecting IP-10 mRNA expression. As a diagnostic tool, this assay would gain from further optimization, especially on the kinetics of IP-10 mRNA expression.

The meta-analysis for ideal cytokines to distinguish the latent and active TB infection

Background

One forth whole-world population is infected with Mycobacterium tuberculosis (Mtb), but 90% of them are asymptotic latent infection without any symptoms but positive result in IFN-γ release assay. There is lack of ideal strategy to distinguish active tuberculosis (TB) and latent tuberculosis infection (LTBI). Some scientist had focused on a set of cytokines as biomarkers besides interferon- gamma (IFN-γ) to distinguish active TB and LTBI, but with considerable variance of results. This meta-analysis aimed to evaluate the overall discriminative ability of potential immune molecules to distinguish active TB and LTBI.

Methods

PubMed, the Cochrane Library, and Web of Science databases were searched to identify studies assessing diagnostic roles of cytokines for distinguishing active TB and LTBI published up to August 2018. The quality of enrolled studies was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled diagnostic sensitivity and specificity of each cytokine was calculated by using Meta-DiSc software. Area under the summary receiver operating characteristic curve (AUC) was used to summarize the overall diagnostic performance of each biomarker.

Results

Fourteen studies with 982 subjects met the inclusion criteria, including 526 active TB and 456 LTBI patients. Pooled sensitivity, specificity and AUC for discriminating between active TB and LTBI were analyzed for IL-2 (0.87, 0.61 and 0.9093), IP-10 (0.77, 0.73 and 0.8609), IL-5 (0.64, 0.75 and 0.8533), IL-13 (0.75, 0.71 and 0.8491), IFN-γ (0.67, 0.75 and 0.8031), IL-10 (0.68, 0.74 and 0.7957) and TNF-α (0.67, 0.64 and 0.7783). The heterogeneous subgroup analysis showed that cytokine detection assays, TB incidence, and stimulator with Mtb antigens are main influence factors for their diagnostic performance.

Conclusions

The meta-analysis showed cytokine production could assist the distinction between active TB and LTBI, IL-2 with the highest overall accuracy. No single biomarker is likely to show sufficiently diagnostic performance due to limited sensitivity and specificity. Further prospective studies are needed to identify the optimal combination of biomarkers to enhanced diagnostic capacity in clinical practice.

Antigen-Specific Cytokine and Chemokine Gene Expression for Diagnosing Latent and Active Tuberculosis

Tuberculosis infection exhibits different forms, namely, pulmonary, extrapulmonary, and latent. Here, diagnostic markers based on the gene expression of cytokines and chemokines for differentiating between tuberculosis infection state(s) were identified. Gene expression of seven cytokines (Interferon gamma (IFN-γ), Interferon gamma-induced protein 10 (IP-10), Interleukin-2 receptor (IL-2R), C-X-C Motif Chemokine Ligand 9 (CXCL-9), Interleukin 10 (IL-10), Interleukin 4 (IL-4), and Tumor Necrosis Factor alpha (TNF-α)) in response to tuberculosis antigen was analyzed using real-time polymerase reaction. The sensitivity and specificity of relative quantification (2^^-ΔΔCt) of mRNA expression were analyzed by constructing receiver operating characteristic curves and measuring the area under the curve (AUC) values. Combinations of cytokines were analyzed using the R statistical software package. IFN-γ, IP-10, IL2R, and CXCL-9 showed high expression in latent and active tuberculosis patients (p = 0.001), with a decrease in IL10 expression, and no statistical difference in IL-4 levels among all the groups (p = 0.999). IL-10 differentiated pulmonary tuberculosis patients from latent cases with an AUC of 0.731. IL10 combined with CXCL-9 distinguished pulmonary tuberculosis patients from extrapulmonary cases with a sensitivity, specificity, and accuracy of 85.7%, 73.9%, and 81.0%, respectively. IL-10 together with IP-10 and IL-4 differentiated pulmonary tuberculosis from latent cases with a sensitivity and specificity of 77.1% and 88.1%, respectively. Decision tree analysis demonstrated that IFN-γ IL-2R, and IL-4 can diagnose tuberculosis infection with a sensitivity, specificity, and accuracy of 89.7%, 96.1%, and 92.7%, respectively. A combination of gene expression of cytokines and chemokines might serve as an effective marker to differentiate tuberculosis infection state(s).

Gene network in pulmonary tuberculosis based on bioinformatic analysis

BACKGROUND

Pulmonary tuberculosis (PTB) is one of the serious infectious diseases worldwide; however, the gene network involved in the host response remain largely unclear.

METHODS

This study integrated two cohorts profile datasets GSE34608 and GSE83456 to elucidate the potential gene network and signaling pathways in PTB. Differentially expressed genes (DEGs) were obtained for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis using Metascape database. Protein-Protein Interaction (PPI) network of DEGs was constructed by the online database the Search Tool for the Retrieval of Interacting Genes (STRING). Modules were identified by the plug-in APP Molecular Complex Detection (MCODE) in Cytoscape. GO and KEGG pathway of Module 1 were further analyzed by STRING. Hub genes were selected for further expression validation in dataset GSE19439. The gene expression level was also investigated in the dataset GSE31348 to display the change pattern during the PTB treatment.

RESULTS

Totally, 180 shared DEGs were identified from two datasets. Gene function and KEGG pathway enrichment revealed that DEGs mainly enriched in defense response to other organism, response to bacterium, myeloid leukocyte activation, cytokine production, etc. Seven modules were clustered based on PPI network. Module 1 contained 35 genes related to cytokine associated functions, among which 14 genes, including chemokine receptors, interferon-induced proteins and Toll-like receptors, were identified as hub genes. Expression levels of the hub genes were validated with a third dataset GSE19439. The signature of this core gene network showed significant response to Mycobacterium tuberculosis (Mtb) infection, and correlated with the gene network pattern during anti-PTB therapy.

CONCLUSIONS

Our study unveils the coordination of causal genes during PTB infection, and provides a promising gene panel for PTB diagnosis. As major regulators of the host immune response to Mtb infection, the 14 hub genes are also potential molecular targets for developing PTB drugs.

Gaps in Study Design for Immune Parameter Research for Latent Tuberculosis Infection: A Systematic Review

Background

Immune parameters (IP) have been extensively studied to distinguish between latent tuberculosis (LTBI) and active tuberculosis (TB).

Objective

To determine the IP associated with LTBI, compared to active TB and individuals not infected by M. tuberculosis published in literature.

Methods

We conducted a systematic search using Google Scholar and PubMed databases, combining the MeSH terms latent tuberculosis, Mycobacterium tuberculosis, cytokines, and biological markers, with the free terms, biomarkers and cytokines. Spanish, English, and Portuguese articles comparing the concentration of IP associated with LTBI, either in plasma/serum or in vitro, in adults and nonimmunocompromised versus individuals with TB or without M. tuberculosis infection between 2006 July and 2018 July were included. Two blinded reviewers carried out the searches, read the abstracts, and selected the articles for analysis. Participants' information, diagnostic criteria, IP, detection methods, and biases were collected.

Results

We analyzed 36 articles (of 637 abstracts) with 93 different biomarkers in different samples. We found 24 parameters that were increased only in active TB (TGF-α, CSF3, CSF2, CCL1 [I-309], IL-7, TGF-β1, CCL3 [MIP-1α], sIL-2R, TNF-β, CCL7 [MCP-3], IFN-α, fractalkine, I-TAG, CCL8 [MCP-2], CCL21 [6Ckine], PDGF, IL-22, VEGF-A, LXA4, PGE2, PGF2α, sCD163, sCD14, and 15-Epi-LXA4), five were elevated in LTBI (IL-5, IL-17F, IL-1, CCL20 [MIP-3α], and ICAM-1), and two substances were increased among uninfected individuals (IL-23 and basic FGF). We found high heterogeneity between studies including failure to account for the time/illness of the individuals studied; varied samples and protocols; different clinical classification of TB; different laboratory methods for IP detection, which in turn leads to variable units of measurement and assay sensitivities; and selection bias regarding TST and booster effect. None of the studies adjusted the analysis for the effect of ethnicity.

Conclusions

It is mandatory to harmonize the study of immune parameters for LTBI diagnosis. This systematic review is registered with PROSPERO CRD42017073289.

CXCL9 and CXCL10 are differentially associated with systemic organ involvement and pulmonary disease severity in sarcoidosis

BACKGROUND

Sarcoidosis is a granulomatous inflammatory disease with limited blood markers to predict outcomes. The interferon-gamma (IFN-γ)-inducible chemotactic cytokines (chemokines), CXCL9 and CXCL10, are both increased in sarcoidosis patients, yet they possess important molecular differences. Our study determined if serum chemokines correlated with different aspects of disease severity.

METHODS

We measured CXCL9 and CXCL10 serum levels at initial study visits and longitudinally in sarcoidosis subjects using ELISA. We examined these chemokines' relationships with pulmonary and organ involvement outcomes, their gene expression, peripheral blood immune cell populations, and immunosuppression use.

RESULTS

Higher CXCL10 levels negatively correlated with FVC, TLC, and DLCO at subjects' initial visit and when measured repeatedly over two years. CXCL10 also positively correlated with longitudinal respiratory symptom severity. Additionally, for every log₁₀(CXCL10) increase, the risk of longitudinal pulmonary function decline increased 8.8 times over the 5-year study period (95% CI 1.6-50, p = 0.014, log₁₀(CXCL0) range 0.84-2.7). In contrast, CXCL9 levels positively correlated with systemic organ involvement at initial study visit (1.5 additional organs involved for every log₁₀(CXCL9) increase, 95% CI 1.1-2.0, p = 0.022, log₁₀(CXCL9) range 1.3-3.3). CXCL10, not CXCL9, positively correlated with its own blood gene expression and monocyte level. Immunosuppressive treatment was associated with lower levels of both chemokines.

CONCLUSIONS

In sarcoidosis subjects, serum CXCL9 levels correlated with systemic organ involvement and CXCL10 levels strongly correlated with respiratory outcomes, which may ultimately prove helpful in clinical management. These differing associations may be due to differences in cellular regulation and tissue origin.

Serum CXCL11 correlates with pulmonary outcomes and disease burden in sarcoidosis

BACKGROUND

Sarcoidosis is a systemic granulomatous disease of unknown etiology that affects the lungs in 90% of patients, but has a wide range of disease manifestations and outcomes including chronic and progressive courses. Noninvasive biomarkers are needed to assess these outcomes and guide decisions for long term monitoring and treatment. Interferon-gamma (IFN-γ)-inducible chemotactic cytokines (chemokines), CXCL9, CXCL10 and CXCL11, show promise in this regard because they have been implicated in the pathogenesis of and reflect the burden of granulomatous inflammation. CXCL11 has been reported to have unique functional properties in modulating adaptive immunity in model systems so our goal was to examine serum levels of CXCL11 in relation to clinical outcomes in a heterogeneous cohort of sarcoidosis subjects.

METHODS

CXCL19, CXCL10, and CXCL11 serum levels were measured in sarcoidosis and healthy subjects using ELISA assay. We determined relationships between CXCL11 and standard clinical inflammatory markers, expression of IFN-γ-related genes in whole blood, organ involvement, dyspnea scores, and measures of pulmonary function.

RESULTS

In a cross-sectional analysis of 104 sarcoidosis subjects, serum CXCL11 was significantly elevated compared to 49 healthy controls (p < 0.001). CXCL11 was positively correlated with CXCL9 and CXCL10 (p < 0.001), sedimentation rate (p < 0.01), and mean expression of three IFN-γ-related genes in whole blood (GBP1, STAT1, and STAT2) (p < 0.001). CXCL11 was inversely correlated with FVC %predicted (%pred) and FEV1 %pred and higher levels were associated with higher patient-reported dyspnea scores. We found positive correlations between CXCL11 and number of organs involved. Using survival analyses, we found that CXCL11 levels were predictive of future pulmonary function test (PFT) decline (log rank <0.001 and HR of log10(CXCL11) = 5.1, 95% CI 1.2-21, p = 0.026).

CONCLUSIONS

The pattern of expression of serum CXCL11 in sarcoidosis patients suggests that this blood measure could be helpful in identifying patients that need longer-term monitoring for progressive thoracic and extra-thoracic sarcoidosis.

Accuracy of interferon-γ-induced protein 10 for diagnosing latent tuberculosis infection: a systematic review and meta-analysis

BACKGROUND

Effective diagnostic methods for detecting latent tuberculosis infection (LTBI) are important for its eradication. A number of studies have evaluated the use of interferon-γ-induced protein 10 (IP-10), which is elevated after tuberculosis infection, as a biomarker for LTBI, but conclusive results regarding its effectiveness have not been reported.

OBJECTIVES

Our objective was to assess the diagnostic value of IP-10 for LTBI.

DATA SOURCES

We searched the PubMed, Embase, the Cochrane Library and Web of Science databases to find eligible studies.

STUDY ELIGIBILITY CRITERIA

We included cohort, case-control and cross-sectional studies that evaluated IP-10 in LTBI participants in comparison with tuberculin skin tests (TST) and interferon-γ release assays (IGRA).

PARTICIPANTS

Individuals with LTBI and uninfected participants.

INTERVENTIONS

IP-10 (index test) compared with TST and IGRA (reference standard) for diagnosing LTBI.

METHODS

PubMed, Embase, the Cochrane Library, and Web of Science databases were searched up to June 2018. A hierarchical summary receiver operating characteristic (HSROC) model was used to evaluate the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and HSROC curve for the diagnostic efficiency of IP-10.

RESULTS

Twelve studies including 1023 participants and 1122 samples were included. The overall pooled sensitivity was 0.85 (95% CI 0.80-0.88), specificity was 0.89 (95% CI 0.84-0.92), PLR was 7.55 (95% CI 5.20-10.97), NLR was 0.17 (95% CI 0.13-0.22) and DOR was 44.23 (95% CI 28.86-67.79), indicating a high accuracy for diagnosing LTBI. Based on a meta-regression analysis, high-burden countries, study design, IP-10 method, reference standard and the IP-10 cut-off could not explain the heterogeneity (p >0.05).

CONCLUSIONS

Our results suggested that IP-10 is a promising biomarker for the diagnosis of LTBI.

Unique Chemokine Profiles of Lung Tissues Distinguish Post-chemotherapeutic Persistent and Chronic Tuberculosis in a Mouse Model

There is a substantial need for biomarkers to distinguish latent stage from active Mycobacterium tuberculosis infections, for predicting disease progression. To induce the reactivation of tuberculosis, we present a new experimental animal model modified based on the previous model established by our group. In the new model, the reactivation of tuberculosis is induced without administration of immunosuppressive agents, which might disturb immune responses. To identify the immunological status of the persistent and chronic stages, we analyzed immunological genes in lung tissues from mice infected with M. tuberculosis. Gene expression was screened using cDNA microarray analysis and confirmed by quantitative RT-PCR. Based on the cDNA microarray results, 11 candidate cytokines genes, which were obviously up-regulated during the chronic stage compared with those during the persistent stage, were selected and clustered into three groups: (1) chemokine genes, except those of monocyte chemoattractant proteins (MCPs; CXCL9, CXCL10, CXCL11, CCL5, CCL19); (2) MCP genes (CCL2, CCL7, CCL8, CCL12); and (3) TNF and IFN-γ genes. Results from the cDNA microarray and quantitative RT-PCR analyses revealed that the mRNA expression of the selected cytokine genes was significantly higher in lung tissues of the chronic stage than of the persistent stage. Three chemokines (CCL5, CCL19, and CXCL9) and three MCPs (CCL7, CCL2, and CCL12) were noticeably increased in the chronic stage compared with the persistent stage by cDNA microarray (p < 0.01, except CCL12) or RT-PCR (p < 0.01). Therefore, these six significantly increased cytokines in lung tissue from the mouse tuberculosis model might be candidates for biomarkers to distinguish the two disease stages. This information can be combined with already reported potential biomarkers to construct a network of more efficient tuberculosis markers.

High IFN-γ Release and Impaired Capacity of Multi-Cytokine Secretion in IGRA Supernatants Are Associated with Active Tuberculosis

Interferon gamma (IFN-γ) release assays (IGRAs) detect Mycobacterium tuberculosis (Mtb) infection regardless of the active (ATB) or latent (LTBI) forms of tuberculosis (TB). In this study, Mtb-specific T cell response against region of deletion 1 (RD1) antigens were explored by a microbead multiplex assay performed in T-SPOT TB assay (T-SPOT) supernatants from 35 patients with ATB and 115 patients with LTBI. T-SPOT is positive when over 7 IFN-γ secreting cells (SC)/250 000 peripheral blood mononuclear cells (PBMC) are enumerated. However, over 100 IFN-γ SC /250 000 PBMC were more frequently observed in the ATB group compared to the LTBI group. By contrast, lower cytokine concentrations and lower cytokine productions relative to IFN-γ secretion were observed for IL 4, IL-12, TNF-α, GM-CSF, Eotaxin and IFN-α when compared to LTBI. Thus, high IFN-γ release and low cytokine secretions in relation with IFN-γ production appeared as signatures of ATB, corroborating that multicytokine Mtb-specific response against RD1 antigens reflects host capacity to contain TB reactivation. In this way, testing cytokine profile in IGRA supernatants would be helpful to improve ATB screening strategy including immunologic tests.