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

基于蛋白质组学鉴定糖尿病合并结核病患者的生物标志物并构建鉴别模型:一项横断面研究

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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 (P(TB-DM vs. HC) < 0.0001 and P(TB-DM vs. DM) = 0.0292), total T cells (P(TB-DM vs. HC) = 0.0018 and P(TB-DM vs. DM) < 0.0001), and CD8+ T cells (P(TB-DM vs. HC) = 0.0009 and P(TB-DM vs. DM) = 0.0072) in TB-DM versus HCs and DM groups. TB-DM patients showed decreased CD4+ T (P(TB-DM vs. DM) < 0.0001) and B cells (P(TB-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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