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DOI 10.3389/fimmu.2025.1713654

Медицинская библиотека · Frontiers in immunology · 2026

Identification of biomarkers and construction of discriminating model for tuberculosis patients with diabetes mellitus based on proteomics: a cross-sectional study.

Li Yufeng, Cheng Peng, An Yajing, Ni Ruizi, Ye Zhaoyang, Yang Ling, Zhuang Li, Li Linsheng, Wang Liang, Gong Wenping

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Аннотация

BACKGROUND

Tuberculosis-diabetes mellitus (TB-DM) comorbidity presents significant clinical challenges due to poor treatment outcomes. This study investigated peripheral blood lymphocyte profiles and cytokine dynamics in TB-DM patients compared to healthy controls (HCs) and DM patients.

METHODS

Subjects from the healthy controls (HCs), DM, and TB-DM were recruited, and peripheral blood samples were collected. The absolute counts of lymphocyte subsets were detected by flow cytometry, and the cytokines were quantitatively analyzed using the Olink ultra-sensitive targeted protein detection technology for micro-samples. Methods such as differential expression analysis, principal component analysis (PCA), correlation analysis, KEGG pathway enrichment analysis, and GO functional annotation were used to screen out the biomarkers related to TB-DM. Based on this, a TB-DM internal model performance was constructed, and the receiver operating characteristic (ROC) curve was used to evaluate its diagnostic efficacy.

RESULTS

The study demonstrated significantly reduced NK cells (PTB-DM vs. HC < 0.0001 and PTB-DM vs. DM = 0.0292), total T cells (PTB-DM vs. HC = 0.0018 and PTB-DM vs. DM < 0.0001), and CD8+ T cells (PTB-DM vs. HC = 0.0009 and PTB-DM vs. DM = 0.0072) in TB-DM versus HCs and DM groups. TB-DM patients showed decreased CD4+ T (PTB-DM vs. DM < 0.0001) and B cells (PTB-DM vs. DM = 0.0004) compared to DM controls. Cytokine profiling revealed 5 upregulated and 17 downregulated factors in TB-DM. Three biomarkers (IL-6, IFN-γ, CXCL10) demonstrated superior diagnostic performance (AUC = 0.9841, sensitivity=88.89%, specificity=92.86%) when combined.

CONCLUSION

Our findings identify distinct immunological alterations in TB-DM and propose a novel cytokine-based diagnostic panel for this high-risk population.

Для цитирования: Li Yufeng, Cheng Peng, An Yajing, Ni Ruizi, Ye Zhaoyang, Yang Ling, Zhuang Li, Li Linsheng, Wang Liang, Gong Wenping. Identification of biomarkers and construction of discriminating model for tuberculosis patients with diabetes mellitus based on proteomics: a cross-sectional study.. Frontiers in immunology. 2026. DOI: 10.3389/fimmu.2025.1713654.

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