双腔室蛋白质组学分析揭示过敏性鼻炎睡眠障碍的炎症特征

文献信息

中文摘要

引言： 过敏性鼻炎（AR）常伴有睡眠障碍，而睡眠相关鼻部症状加重的分子机制仍知之甚少。本研究旨在采用双腔室蛋白质组学方法，探讨与AR患者睡眠不佳相关的炎症蛋白特征。方法：我们首先分析了2005-2006年全国健康与营养调查（NHANES）周期的3,731名成年参与者，以验证睡眠时长与AR之间的关联。随后，我们招募了40名AR患者（20名睡眠不佳者，匹兹堡睡眠质量指数[PSQI] > 5；20名睡眠正常者，PSQI ≤ 5），并对配对的血清和鼻分泌物（NS）样本进行了Olink蛋白质组学分析。进行了差异表达分析、功能富集、跨腔室相关性分析、最小绝对收缩和选择算子（LASSO）回归、受试者工作特征（ROC）分析以及序贯多变量线性回归。结果：在NHANES中，短睡眠时长（<6小时）与AR的比值比（OR）增加显著相关（OR = 1.27，95%置信区间[CI] 1.05-1.54，P = 0.013），并且与血清总免疫球蛋白E（IgE）升高相关。在临床队列中，睡眠不佳者的总鼻症状评分（TNSS）（P < 0.001）、多维疲劳量表（MFI）（P < 0.001）和血嗜酸性粒细胞计数（P = 0.011）更高。蛋白质组学鉴定出27种血清和20种NS差异表达蛋白（DEPs），其中9种重叠DEPs富集于白细胞介素-17（IL-17）、肿瘤坏死因子（TNF）和趋化因子信号通路。一个四标志物组合（血清β-神经生长因子[β-NGF]、血清转化生长因子-β1[TGF-β1]、NS白细胞介素-8[IL-8]、NS基质金属蛋白酶-1[MMP-1]）在区分睡眠不佳者与睡眠正常者方面达到了0.88的曲线下面积（AUC）（95% CI 0.76-0.97，P < 0.001）。跨腔室相关性分析显示血清-NS蛋白显著一致，与全身-局部炎症串扰一致。序贯多变量回归显示，即使在调整PSQI后，血清β-NGF仍独立预测TNSS严重程度（β = 2.22，P = 0.044），而鼻IL-8则完全减弱（β = 0.58，P = 0.391）。结论：睡眠不佳通过协调的全身和局部炎症反应与AR加重相关。血清β-NGF与鼻部症状独立相关，而NS IL-8与症状的关联似乎可由睡眠障碍解释。整合两个腔室的标志物可增强对睡眠不佳AR患者的识别。

英文摘要

Introduction Allergic rhinitis (AR) is often accompanied by sleep disturbance, while the molecular mechanisms underlying sleep-related exacerbation of nasal symptoms remain poorly understood. This study aimed to investigate the inflammatory protein signatures associated with poor sleep in AR using a dual-compartment proteomic approach. Methods We first analyzed 3,731 adult participants from the 2005-2006 National Health and Nutrition Examination Survey (NHANES) cycle to validate the association between sleep duration and AR. We then enrolled 40 AR patients (20 poor sleepers, Pittsburgh Sleep Quality Index [PSQI] > 5; 20 normal sleepers, PSQI ≤ 5) and performed Olink proteomic profiling in paired serum and nasal secretion (NS) samples. Differential expression analysis, functional enrichment, cross-compartment correlation, Least Absolute Shrinkage and Selection Operator (LASSO) regression, receiver operating characteristic (ROC) analysis, and sequential multivariable linear regression were conducted. Results In NHANES, short sleep duration (<6 h) was significantly associated with increased odds ratio (OR) of AR (OR = 1.27, 95% confidence interval [CI] 1.05-1.54, P = 0.013) and elevated serum total immunoglobulin E (IgE). In the clinical cohort, poor sleepers had higher Total Nasal Symptom Score (TNSS) (P < 0.001), Multidimensional Fatigue Inventory (MFI) (P < 0.001), and blood eosinophil counts (P = 0.011). Proteomics identified 27 serum and 20 NS differentially expressed proteins (DEPs), with 9 overlapping DEPs enriched in interleukin-17 (IL-17), tumor necrosis factor (TNF), and chemokine signaling pathways. A four-marker panel (serum beta-nerve growth factor [β-NGF], serum transforming growth factor-beta 1 [TGF-β1], NS interleukin-8 [IL-8], NS matrix metalloproteinase-1 [MMP-1]) achieved an area under the curve (AUC) of 0.88 (95% CI 0.76-0.97, P < 0.001) for distinguishing poor from normal sleepers. Cross-compartment correlation analysis revealed significant serum-NS protein concordance, consistent with systemic-local inflammatory crosstalk. Sequential multivariable regression showed that serum β-NGF independently predicted TNSS severity even after PSQI adjustment (β = 2.22, P = 0.044), whereas nasal IL-8 was fully attenuated (β = 0.58, P = 0.391). Conclusion Poor sleep is associated with exacerbated AR through coordinated systemic and local inflammatory responses. Serum β-NGF is independently associated with nasal symptoms, whereas the association of NS IL-8 with symptoms appears to be explained by sleep disturbance. Integrating markers from both compartments enhances the identification of AR patients with poor sleep.