QuantiFERON supernatant-based host biomarkers predicting progression to active tuberculosis disease among household contacts of tuberculosis patients

Construction of novel multi-epitope-based diagnostic biomarker HP16118P and its application in the differential diagnosis of Mycobacterium tuberculosis latent infection

Tuberculosis (TB) is an infectious disease that significantly threatens human health. However, the differential diagnosis of latent tuberculosis infection (LTBI) and active tuberculosis (ATB) remains a challenge for clinicians in early detection and preventive intervention. In this study, we developed a novel biomarker named HP16118P, utilizing 16 helper T lymphocyte (HTL) epitopes, 11 cytotoxic T lymphocyte (CTL) epitopes, and 8 B cell epitopes identified from 15 antigens associated with LTBI-RD using the IEDB database. We analyzed the physicochemical properties, spatial structure, and immunological characteristics of HP16118P using various tools, which indicated that it is a hydrophilic and relatively stable alkaline protein. Furthermore, HP16118P exhibited good antigenicity and immunogenicity, while being non-toxic and non-allergenic, with the potential to induce immune responses. We observed that HP16118P can stimulate the production of high levels of IFN-γ+ T lymphocytes in individuals with ATB, LTBI, and health controls. IL-5 induced by HP16118P demonstrated potential in distinguishing LTBI individuals and ATB patients (p=0.0372, AUC=0.8214, 95% CI [0.5843 to 1.000]) with a sensitivity of 100% and specificity of 71.43%. Furthermore, we incorporated the GM-CSF, IL-23, IL-5, and MCP-3 induced by HP16118P into 15 machine learning algorithms to construct a model. It was found that the Quadratic discriminant analysis model exhibited the best diagnostic performance for discriminating between LTBI and ATB, with a sensitivity of 1.00, specificity of 0.86, and accuracy of 0.93. In summary, HP16118P has demonstrated strong antigenicity and immunogenicity, with the induction of GM-CSF, IL-23, IL-5, and MCP-3, suggesting their potential for the differential diagnosis of LTBI and ATB.

IP-10 for the Diagnosis and Treatment Monitoring of Tuberculosis in Children

PURPOSE

To determine the utility of interferon-gamma-inducible protein 10 (IP-10) for identifying active tuberculosis (TB) and TB infection (TBI) in children in BCG-vaccinated populations, establish its diagnostic performance characteristics, and evaluate changes in IP-10 level during anti-TB chemotherapy.

METHODS

Concentrations of IP-10 and IFN-γ were measured in QuantiFERON-TB Gold (QFT) supernatants in children with suspected TB or due to recent TB contact. A total of 225 children were investigated: 33 with active TB, 48 with TBI, 83 TB contacts, 20 with suspected TB but other final diagnoses, and 41 controls. In 60 children, cytokine responses were evaluated at a follow-up visit after 2 months of anti-TB treatment.

RESULTS

IP-10 expression was significantly higher in infected children (active TB and TBI cases) than in uninfected individuals. IP-10 proved effective in identifying TB infection at its optimal cut-off (>1084.5 pg/mL) but was incapable of differentiating between children with active TB and TBI. Combining IP-10 and IFN-γ increased the QFT sensitivity. IP-10 but not IFN-γ decreased significantly during anti-TB treatment in children with active TB (p = 0.003).

CONCLUSION

IP-10 identifies TB infection and declines during anti-TB chemotherapy in children. Incorporating IP-10 into new immunodiagnostic assays could improve TB diagnosis and allow for treatment monitoring.

A novel chemokine biomarker to distinguish active tuberculosis from latent tuberculosis: a cohort study

BACKGROUND

Interferon-γ release assays (IGRAs), which are widely used to diagnose tuberculosis (TB), cannot effectively discriminate latent TB infection (LTBI) from active TB (ATB). This study aimed to identify potential antigen-specific biomarkers for differentiating LTBI cases from ATB cases.

METHODS

Ongoing recruitment was conducted of individuals meeting study inclusion criteria at Beijing Chest Hospital from May 2020 to April 2022; 208 participants were enrolled and assigned to three groups: HC (60 healthy controls), LTBI (52 subjects with LTBI) and ATB (96 ATB patients). After participants were assigned to the discovery cohort (20 or 21 subjects/group), all others were assigned to the verification cohort. Discovery cohort blood levels of 40 chemokines were measured using Luminex assays to identify chemokines that could be used to discriminate LTBI cases from ATB cases; candidate biomarkers were verified using enzyme-linked immunosorbent assay-based testing of validation cohort samples.

RESULTS

Luminex results revealed highest ATB group levels of numerous cytokines, growth factors and chemokines. Receiving operating characteristic curve-based analysis of 40 biomarkers revealed CCL8 (AUC = 0.890) and CXCL9 (AUC = 0.883) effectively discriminated between LTBI and TB cases; greatest diagnostic efficiency was obtained using both markers together (AUC = 0.929). Interpretation of CCL8 and CXCL9 levels for validation cohort IGRA-positive subjects (based on a 0.658-ng/ml cutoff) revealed ATB group CCL8-based sensitivity and specificity rates approaching 90.79% and 100.00%, respectively.

CONCLUSION

TB-specific chemokines hold promise as ATB diagnostic biomarkers. Additional laboratory confirmation is needed to establish whether CCL8-based assays can differentiate between ATB and LTBI cases, especially for bacteriologically unconfirmed TB cases.