Active tuberculosis patients have high systemic IgG levels and B-cell fingerprinting, characterized by a reduced capacity to produce IFN-γ or IL-10 as a response to M.tb antigens

Flores-Gonzalez, Julio; Urbán-Solano, Alexia; Ramón-Luing, Lucero A.; Cancino-Diaz, Juan Carlos; Contreras-Rodriguez, Araceli; Curiel-Quesada, Everardo; Hernández-Pando, Rogelio; Chavez-Galan, Leslie

doi:10.3389/fimmu.2023.1263458

Cited by 2 publications

(1 citation statement)

References 51 publications

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“… 30 Studies have reported increased IL-10 levels in TB patients, suggesting its role in the suppression of the protective immune response. 31 , 32 Our findings are consistent with these reports, demonstrating significantly higher IL-10 levels in SNPT patients compared to SPPT patients, with an AUC of 0.686. The chemokine CXCL8/IL-8 is linked to neutrophil recruitment and granuloma formation in TB.…”

Section: Discussionsupporting

confidence: 92%

Retrospective analysis of the clinical utility of multi-cytokine profiles in smear-negative pulmonary tuberculosis

Li,

Zhao,

Han

et al. 2024

SMJ

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Objectives: To evaluate cytokine profiles and interferon-gamma release assay (IGRA) for their diagnostic capabilities in the differentiation of tuberculosis (TB) from non-TB conditions, as well as smear-negative pulmonary tuberculosis (SNPT) from smear-positive pulmonary tuberculosis (SPPT). Methods: A total of 125 participants were included, 77 of whom had TB and 48 who didn’t, and demographic, clinical, and laboratory data were collected, including cytokine levels and IGRA results. The TB patients were further divided into 2 subgroups: SNPT (n=42) and SPPT (n=35). Results: Compared to non-TB, the TB group had lower BMI, higher WBC, neutrophils, monocytes, ESR and CRP ( p <0.05). TB patients showed higher IL-2, IL-6, IFN-γ, IL-8 ( p <0.001) and higher IGRA positivity (88.3% versus [vs.] 29.2%, p <0.001). Between SNPT and SPPT, moderate effect sizes were observed for IFN-α, IL-2, IL-10, IL-8 (Cohen’s d 0.59-0.76), with lower IGRA positivity in SNPT (81.0% vs. 97.1%, p =0.015). ROC analysis indicated IFN-α, IL-2, IL-10, IL-8 had moderate accuracy for SNPT diagnosis (AUCs 0.668-0.734), and combining these improved accuracy (AUC 0.759, 80% sensitivity, 64.2% specificity). Conclusion: A multi-biomarker approach combining these cytokines demonstrates enhanced diagnostic accuracy for tuberculosis.

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Section: Discussionsupporting

confidence: 92%

Retrospective analysis of the clinical utility of multi-cytokine profiles in smear-negative pulmonary tuberculosis

Li,

Zhao,

Han

et al. 2024

SMJ

View full text Add to dashboard Cite

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Differential Diagnosis of Tuberculosis and Sarcoidosis by Immunological Features Using Machine Learning

Osipov,

Kudryavtsev,

Spelnikov

et al. 2024

Diagnostics

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Despite the achievements of modern medicine, tuberculosis remains one of the leading causes of mortality globally. The difficulties in differential diagnosis have particular relevance in the case of suspicion of tuberculosis with other granulomatous diseases. The most similar clinical and radiologic changes are sarcoidosis. The aim of this study is to apply mathematical modeling to determine diagnostically significant immunological parameters and an algorithm for the differential diagnosis of tuberculosis and sarcoidosis. Materials and methods: The serum samples of patients with sarcoidosis (SD) (n = 29), patients with pulmonary tuberculosis (TB) (n = 32) and the control group (n = 31) (healthy subjects) collected from 2017 to 2022 (the average age 43.4 ± 5.3 years) were examined. Circulating ‘polarized’ T-helper cell subsets were analyzed by multicolor flow cytometry. A symbolic regression method was used to find general mathematical relations between cell concentrations and diagnosis. The parameters of the selected model were finally fitted through multi-objective optimization applied to two conflicting indices: sensitivity to sarcoidosis and sensitivity to tuberculosis. Results: The difference in Bm2 and CD5−CD27− concentrations was found to be more significant for the differential diagnosis of sarcoidosis and tuberculosis than any individual concentrations: the combined feature Bm2 − [CD5−CD27−] differentiates sarcoidosis and tuberculosis with p < 0.00001 and AUC = 0.823. An algorithm for differential diagnosis was developed. It is based on the linear model with two variables: the first variable is the difference Bm2 − [CD5−CD27−] mentioned above, and the second is the naïve-Tregs concentration. The algorithm uses the model twice and returns “dubious” in 26.7% of cases for patients with sarcoidosis and in 16.1% of cases for patients with tuberculosis. For the remaining patients with one of these two diagnoses, its sensitivity to sarcoidosis is 90.5%, and its sensitivity to tuberculosis is 88.5%. Conclusions: A simple algorithm was developed that can distinguish, by certain immunological features, the cases in which sarcoidosis is likely to be present instead of tuberculosis. Such cases may be further investigated to rule out tuberculosis conclusively. The mathematical model underlying the algorithm is based on the analysis of “naive” T-regulatory cells and “naive” B-cells. This may be a promising approach for differential diagnosis between pulmonary sarcoidosis and pulmonary tuberculosis. The findings may be useful in the absence of clear differential diagnostic criteria between pulmonary tuberculosis and sarcoidosis.

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Active tuberculosis patients have high systemic IgG levels and B-cell fingerprinting, characterized by a reduced capacity to produce IFN-γ or IL-10 as a response to M.tb antigens

Cited by 2 publications

References 51 publications

Retrospective analysis of the clinical utility of multi-cytokine profiles in smear-negative pulmonary tuberculosis

Retrospective analysis of the clinical utility of multi-cytokine profiles in smear-negative pulmonary tuberculosis

Differential Diagnosis of Tuberculosis and Sarcoidosis by Immunological Features Using Machine Learning

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