蛋白质飞行质谱技术在严重急性呼吸综合征(SARS)早期诊断中的应用价值(英文)

目的探索蛋白质飞行质谱技术在严重急性呼吸综合征(SARS)早期诊断中的应用价值。方法用表面加强激光解吸电离质谱技术检测急性SARS组和对照组的血清,首先建立诊断模型,然后单盲进行模型验证。结果通过检测急性SARS组(74例)和对照组(147例)的血清,发现了早期SARS患者血清中质谱峰(M/Z)为3939.08、4137.71、8136.64、11514.20的4种特异蛋白指纹标志物,并建立诊断模型,此模型敏感性98.6%(73/74),特异性94.6%(139/147)。结论早期SARS患者有特异的蛋白指纹图谱,利用表面加强激光解吸电离质谱技术检测SARS患者或疑似SARS患者血清,可更好地协助临床进行SARS的早期诊治。

Establishment of the proteomic fingerprints for potential application to early diagnosis of SARS

Background Severe acute respiratory syndrome (SARS) is still a diagnosis of exclusion despite that a number of laboratory tests have been used to complement clinical features and epidemiological data in case definition. Definitive early-stage diagnosis of SARS is in paramount demand. Pathological changes in response to viral infections might be reflected in proteomic patterns in sera of SARS patients. Methods We have developed a mass spectrometric decision tree classification algorithm using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry(SELDI-MS). Sera samples were grouped into acute SARS (n=74, <7 days of onset of fever), and non-SARS [n=147, fever and Flu-A (n=33), pneumonia (n=16), lung cancer (n=19) and healthy controls(n=79)] cohorts. Diluted samples were applied to WCX-2 ProteinChip arrays (Ciphergen), the bound proteins were assessed on a ProteinChip Reader (Model PBS II) and the bioinformatic calculations were performed using Biomarker Wizard software 3.1.1(Ciphergen). Results The discriminatory classifier with a panel of four biomarkers precisely classified 73 of 74 SARS at early stage(<7 days) of onset of fever and 139 of 147 non-SARS and permitted a sensitivity of 98.6% and specificity of 94.6% for the study population. More important, this classifier accurately distinguished SARS acute from fever and Flu with specificity reaching 100%(33 of 33). Conclusion Therefore, the SELDI method establishes a preliminary population-based assessment that could potentially serve as a useful early diagnostic and prognostic tool for SARS.