儿童过敏性鼻炎中T细胞耗竭基因的生物信息学分析及其临床诊断意义

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中文摘要

背景： 儿童过敏性鼻炎（PAR）是一种慢性炎症性疾病。T细胞耗竭（TCE）导致免疫功能障碍。本研究探讨了PAR中与TCE相关的基因，并构建了诊断模型。
方法： 对GSE19187数据（14例PAR，11例对照）进行差异表达分析。与TCE相关基因取交集，得到TCE相关的差异表达基因（TCERDEGs）。应用功能富集、逻辑回归、支持向量机递归特征消除（SVM-RFE）和最小绝对收缩和选择算子（LASSO）构建诊断模型并识别枢纽基因。还进行了免疫浸润分析。
结果： 鉴定出22个TCERDEGs。IFNG和CD96显示出最强的正相关（r = 0.89），而FSTL3和MTOR显示出最强的负相关（r = -0.70）。许多TCERDEGs定位于3号和9号染色体。建立了包含三个枢纽基因的诊断模型：CD96、CD200R1和TRAF1。免疫分析显示，活化的CD4记忆T细胞与静息树突状细胞之间呈强正相关（r = 1），静息NK细胞与活化NK细胞之间呈负相关（r = -0.78）。CD96与初始B细胞正相关（r = 0.58），而TRAF1与静息肥大细胞负相关（r = -0.57）。
讨论： 本研究从T细胞耗竭相关基因中开发了由CD96、CD200R1和TRAF1组成的PAR诊断特征，突出了T细胞耗竭介导的免疫失调在儿童过敏性鼻炎中的重要作用。枢纽基因与多种浸润免疫细胞之间的独特相关性进一步表明，这些生物标志物可能通过调节局部免疫微环境参与PAR的发病机制。然而，这些结果来源于公共转录组数据集，需要前瞻性临床样本来验证三个候选基因的诊断性能和生物学功能。
结论： CD96、CD200R1和TRAF1的异常表达与免疫浸润相关，表明TCE相关的免疫变化可能是PAR发病机制的基础。这些基因显示出作为诊断生物标志物的潜力，尽管需要进一步的临床验证。我们的发现提供了一个有用的诊断模型，并对PAR免疫状态提供了见解。

英文摘要

BACKGROUND: Pediatric Allergic Rhinitis (PAR) is a chronic inflammatory condition. TCell Exhaustion (TCE) contributes to immune dysfunction. This study explored TCE-related genes in PAR and constructed a diagnostic model.
METHODS: Differential expression analysis was performed on GSE19187 data (14 PAR, 11 controls). Intersection with TCE-associated genes yielded TCE-related Differentially Expressed Genes (TCERDEGs). Functional enrichment, logistic regression, the Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Least Absolute Shrinkage and Selection Operator (LASSO) were applied to build a diagnostic model and identify hub genes. Immune infiltration was also analyzed.
RESULTS: Twenty-two TCERDEGs were identified. IFNG and CD96 showed the strongest positive correlation (r = 0.89), while FSTL3 and MTOR showed the strongest negative correlation (r = -0.70). Many TCERDEGs localized to chromosomes 3 and 9. A diagnostic model was established with three hub genes: CD96, CD200R1, and TRAF1. Immune analysis revealed strong positive correlations between activated CD4 memory T cells and resting dendritic cells (r = 1), and negative correlations between resting and activated NK cells (r = -0.78). CD96 positively correlated with naive B cells (r = 0.58), while TRAF1 negatively correlated with resting mast cells (r = -0.57).
DISCUSSION: This study developed a PAR diagnostic signature consisting of CD96, CD200R1, and TRAF1 from T‑cell‑exhaustion‑related genes, highlighting the vital role of T‑cell exhaustion‑mediated immune dysregulation in pediatric allergic rhinitis. The distinct correlations between hub genes and multiple infiltrated immune cells further suggested that these biomarkers might contribute to PAR pathogenesis by modulating the local immune microenvironment. Nevertheless, these results are derived from public transcriptomic datasets, and prospective clinical samples are required to verify the diagnostic performance and biological function of the three candidate genes.
CONCLUSION: Aberrant expression of CD96, CD200R1, and TRAF1, linked to immune infiltration, suggests TCE-related immune changes may underlie PAR pathogenesis. These genes show potential as diagnostic biomarkers, though further clinical validation is needed. Our findings provide a useful diagnostic model and insights into PAR immune status.