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

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

Published 2026 in Frontiers in Immunology

ABSTRACT

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.

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