COPD is a complex respiratory disorder with high morbidity and mortality rates. Even with the current conventional diagnostic methods, including circulating inflammatory biomarkers, underdiagnosis rates in COPD remain as high as 70%. Our study was a comparative cross-sectional study that aimed to address the diagnostic challenges by identifying future biomarker candidates in COPD variants. This study used a label-free plasma proteomics approach that combined mass spectrometric data with bioinformatics to shed light on the functional roles of differentially expressed proteins in the COPD lung microenvironment. The predictive capacity of the screened proteins was assessed using Receiver Operating Characteristic (ROC) curves, with Western blot analysis validating protein expression patterns in an independent cohort. Our study identified three DEPs—reticulocalbin-1, sideroflexin-4, and liprinα-3 that consistently exhibited altered expression in COPD exacerbation. ROC analysis indicated strong predictive potential, with AUC values of 0.908, 0.715, and 0.856 for RCN1, SFXN4, and LIPα-3, respectively. Validation through Western blot analysis confirmed their expression patterns in an independent validation cohort. Our study discovered a novel duo of proteins reticulocalbin-1, and sideroflexin-4 that showed potential as valuable future biomarkers for the diagnosis and clinical management of COPD exacerbations.

中文翻译：

---

探索 Reticulocalbin 和 Sideroflexin 的新型组合作为未来加重慢性阻塞性肺疾病的候选生物标志物

慢性阻塞性肺病是一种复杂的呼吸系统疾病，发病率和死亡率很高。即使采用当前的常规诊断方法，包括循环炎症生物标志物，COPD 的漏诊率仍高达 70%。我们的研究是一项比较横断面研究，旨在通过识别 COPD 变异中的未来候选生物标志物来解决诊断挑战。本研究采用无标记血浆蛋白质组学方法，将质谱数据与生物信息学相结合，以阐明差异表达蛋白质在慢性阻塞性肺病肺微环境中的功能作用。使用受试者操作特征（ROC）曲线评估筛选蛋白质的预测能力，并通过蛋白质印迹分析验证独立队列中的蛋白质表达模式。我们的研究发现了三种 DEP：reticulocalbin-1、sideroflexin-4 和 liprinα-3，它们在 COPD 恶化时始终表现出表达改变。 ROC 分析显示出很强的预测潜力，RCN1、SFXN4 和 LIPα-3 的 AUC 值分别为 0.908、0.715 和 0.856。通过蛋白质印迹分析验证证实了它们在独立验证队列中的表达模式。我们的研究发现了一种新的蛋白组合 reticulocalbin-1 和 sideroflexin-4，它们显示出作为 COPD 恶化的诊断和临床管理的有价值的未来生物标志物的潜力。