Validation of Differentially Expressed Immune Biomarkers in Latent and Active Tuberculosis by Real-Time PCR

Perumal, Prem; Abdullatif, Mohamed Bilal; Garlant, Harriet; Honeyborne, Isobella; Lipman, Marc; McHugh, Timothy D.; Southern, Jo; Breen, Ronan; Santis, George; Kalaiarasan, Ellappan; Kumar, Senthil; Belgode, Harish Narasimha; Abubakar, Ibrahim; Sinha, Sanjeev; Vasan, Seshadri S.; Joseph, Noyal Mariya; Kempsell, Karen E.

doi:10.3389/fimmu.2020.612564

Cited by 22 publications

(36 citation statements)

References 149 publications

(244 reference statements)

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“…Although many advances have been achieved, especially in omics field (60-62), there were some practical limitations for their clinical application, including expensive laboratory facilities and sophisticated operating procedures. Meanwhile, immunodiagnostics has received considerable attention as an alternative for discrimination of MTB infection status in recent years (63)(64)(65)(66)(67)(68)(69)(70). Nevertheless, the identified biomarkers including proteins and cytokines in serum or plasma for diagnostic aim may not be specific for TB due to the influence brought by other immune related diseases such as infection and autoimmune diseases (71)(72)(73)(74)(75)(76)(77).…”

Section: Discussionmentioning

confidence: 99%

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

Luo

Xue

et al. 2021

Front. Immunol.

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

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Section: Discussionmentioning

confidence: 99%

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

Luo

Xue

et al. 2021

Front. Immunol.

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“…The specificity of our marker panel for distinguishing ATB from HC in such cases was high (96.3%), however, its sensitivity (71.2%) falls short of that specified in the WHO’s optimal Target Product Profile (TPP) for non-sputum-based TB diagnosis tests (98%) 47 . Nonetheless, like other biomarker studies published that similarly did not reach these standards 9 , 48 , 49 , our study has useful reference value for those engaged in biomarker discovery. Further work on optimizing this panel will be necessary.…”

Section: Discussionmentioning

confidence: 48%

Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB

Liu

et al. 2021

Sci Rep

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Bacterial culture of M. tuberculosis (MTB), the causative agent of tuberculosis (TB), from clinical specimens is the gold standard for laboratory diagnosis of TB, but is slow and culture-negative TB cases are common. Alternative immune-based and molecular approaches have been developed, but cannot discriminate between active TB (ATB) and latent TB (LTBI). Here, to identify biomarkers that can discriminate between ATB and LTBI/healthy individuals (HC), we profiled 116 serum samples (HC, LTBI and ATB) using a protein microarray containing 257 MTB secreted proteins, identifying 23 antibodies against MTB antigens that were present at significantly higher levels in patients with ATB than in those with LTBI and HC (Fold change > 1.2; p < 0.05). A 4-protein biomarker panel (Rv0934, Rv3881c, Rv1860 and Rv1827), optimized using SAM and ROC analysis, had a sensitivity of 67.3% and specificity of 91.2% for distinguishing ATB from LTBI, and 71.2% sensitivity and 96.3% specificity for distinguishing ATB from HC. Validation of the four candidate biomarkers in ELISA assays using 440 serum samples gave consistent results. The promising sensitivity and specificity of this biomarker panel suggest it merits further investigation for its potential as a diagnostic for discriminating between latent and active TB.

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“…The NCF1 gene colocalizes with two pseudogenes (NCF1B and NCF1C), where NCF1C expression responded robustly to PMA induction during macrophage differentiation (Bakry et al, 2021;Brunson et al, 2010). A recent study from England and India indicated NCF1C can be an immune biomarker to differentiate active tuberculosis and latent tuberculosis (Perumal et al, 2020). Our study has shown that the expression of NCF1C was 3.4-fold higher among household healthy controls than that of leprosy patients (Table 2 and Figure 6).…”

Section: Discussionmentioning

confidence: 51%

Transcriptomic Analysis of Mycobacterium leprae-Stimulated Response in Peripheral Blood Mononuclear Cells Reveal Potential Biomarkers for Early Diagnosis of Leprosy

Yuan

Liu

You

et al. 2021

Front. Cell. Infect. Microbiol.

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We aimed to identify an unique host transcriptional signature in peripheral blood mononuclear cells (PBMCs) in response to Mycobacterium leprae antigens to distinguish between patients with leprosy and non-leprosy controls for early diagnosis of the disease. Sixteen individuals were enrolled in the discovery cohort [eight patients with leprosy, comprising four multibacillary (MB) and four paucibacillary (PB); and eight non-leprosy controls, comprising four healthy house contacts (HHCs) and four endemic controls (ECs)]. The differences in the transcriptome response of PBMCs to M. leprae sonicate antigen were evaluated between leprosy patients and non-leprosy controls, and 12 differentially expressed genes (CCL2/MCP-1, IL-8, JAKM, ATP, ND1, SERP, FLJ10489, LINC00659, LOC34487, LOC101928143, MIR22, and NCF1C) were identified. The accuracy of the 12 differentially expressed genes was further validated for the diagnosis of leprosy using real-time quantitative PCR in 82 individuals (13 MB, 10 PB, 37 HHCs, and 22 ECs) in the validation cohort. We found that a 5 gene signature set IL-8, CCL2/MCP-1, SERP, LINC00659 and FLJ10489 had a suitable performance in discriminating leprosy from ECs. In addition, elevated expression of IL-8, CCL2/MCP-1, SERP and LINC00659 was associated with MB diagnosis compared with ECs, whereas increased expression of IL-8, CCL2/MCP-1, SERP and FLJ10489 was found to be useful biomarkers for PB diagnosis from ECs. Moreover, we found decreased expression of NCF1C among leprosy patients could distinguish leprosy from HHCs, whereas higher expression of CCL2 among MB than PB could distinguish different leprosy patients. In conclusion, among the 12 candidate host genes identified, a three gene signature IL-8, CCL2/MCP-1, and SERP showed the best performance in distinguishing leprosy patients from healthy controls. These findings may have implications for developing a rapid blood-based test for early diagnosis of leprosy.

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Validation of Differentially Expressed Immune Biomarkers in Latent and Active Tuberculosis by Real-Time PCR

Cited by 22 publications

References 149 publications

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

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

Microarray-based selection of a serum biomarker panel that can discriminate between latent and active pulmonary TB

Transcriptomic Analysis of Mycobacterium leprae-Stimulated Response in Peripheral Blood Mononuclear Cells Reveal Potential Biomarkers for Early Diagnosis of Leprosy

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