Das Sonu, Adiody Supriya, Varghese Jinsu, Vanditha M, Maria Evelyn, John Mathew
Biochemistry and Phytochemistry Research Division, Jubilee Centre for Medical Research, Jubilee Mission Medical College and Research Institute, Thrissur, Kerala, India.
Department of Zoology, St. Thomas College, Kozhencherry, Affiliated to Mahatma Gandhi University, Kerala, India.
Clin Proteomics. 2024 Feb 14;21(1):10. doi: 10.1186/s12014-024-09459-8.
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.
慢性阻塞性肺疾病（COPD）是一种具有高发病率和死亡率的复杂呼吸系统疾病。即使采用当前的传统诊断方法，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变异体中的未来生物标志物候选物来应对诊断挑战。
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COPD肺微环境中差异表达蛋白质的功能作用。使用受试者工作特征（ROC）曲线评估筛选出的蛋白质的预测能力，并通过蛋白质印迹分析在独立队列中验证蛋白质表达模式。
我们的研究确定了三种差异表达蛋白——网织钙结合蛋白-1、铁转运蛋白-4和脂锚定蛋白α-3，它们在COPD急性加重期持续表现出表达改变。ROC分析表明具有很强的预测潜力，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进行的验证在独立验证队列中证实了它们的表达模式。
我们的研究发现了一种新的蛋白质组合——网织钙结合蛋白-1和铁转运蛋白-4，它们显示出作为未来COPD急性加重期诊断和临床管理中有价值生物标志物的潜力。
