通过质谱分析找出区分脓毒症与非感染性炎症反应的蛋白标志物。
Exploring proteomic signatures in sepsis and non-infectious systemic inflammatory response syndrome
- 用质谱检测血浆蛋白，结合特征筛选与分类模型识别差异表达蛋白。
- 25个蛋白组合可精准区分脓毒症与非感染性炎症，准确率达96%。
- 发现14种脓毒症特异蛋白，适合临床早期诊断研究者参考。
背景：脓毒症早期诊断亟需新生物标志物。本研究旨在识别脓毒症与非感染性全身炎症反应综合征（NISIRS）之间差异表达的潜在蛋白标志物。方法：2016–2017年开展前瞻性观察性队列研究，纳入接受脓毒症代码激活的患者及NISIRS住院患者。采用基于质谱的方法分析受试者血浆蛋白，随后使用递归特征消除（RFE）分类与向量分类器交叉验证，构建脓毒症与NISIRS患者的蛋白关联模型。利用String软件分析蛋白-蛋白相互作用网络。结果：共纳入277例患者（脓毒症141例，NISIRS 136例）。经RFE筛选后，25个蛋白在研究队列中具有统计学意义，模型准确率为0.960，特异性0.920，敏感性0.973，AUC为0.985。其中14个蛋白（vWF、PPBP、C5、C1RL、FCN3、SAA2、ORM1、ITIH3、GSN、C1QA、CA1、CFB、C3、LBP）与脓毒症关系更密切；11个蛋白（FN1、IGFALS、SERPINA4、APOE、APOH、C6、SERPINA3、AHSG、LUM、ITIH2、SAA1）在NISIRS中表达更高。
原文摘要 · Abstract (English)
Background: The search for new biomarkers that allow an early diagnosis in sepsis has become a necessity in medicine. The objective of this study is to identify potential protein biomarkers of differential expression between sepsis and non-infectious systemic inflammatory response syndrome (NISIRS). Methods: Prospective observational study of a cohort of septic patients activated by the Sepsis Code and patients admitted with NISIRS, during the period 2016-2017. A mass spectrometry-based approach was used to analyze the plasma proteins in the enrolled subjects. Subsequently, using recursive feature elimination (RFE) classification and cross-validation with a vector classifier, an association of these proteins in patients with sepsis compared to patients with NISIRS. The protein-protein interaction network was analyzed with String software. Results: A total of 277 patients (141 with sepsis and 136 with NISIRS) were included. After performing RFE, 25 proteins in the study patient cohort showed statistical significance, with an accuracy of 0.960, specificity of 0.920, sensitivity of 0.973, and an AUC of 0.985. Of these, 14 proteins (vWF, PPBP, C5, C1RL, FCN3, SAA2, ORM1, ITIH3, GSN, C1QA, CA1, CFB, C3, LBP) have a greater relationship with sepsis while 11 proteins (FN1, IGFALS, SERPINA4, APOE, APOH, C6, SERPINA3, AHSG, LUM, ITIH2, SAA1) are more expressed in NISIRS.
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