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應(yīng)用蛋白質(zhì)指紋技術(shù)篩選強(qiáng)直性脊柱炎血清特異性標(biāo)志物的臨床研究

發(fā)布時(shí)間:2019-01-10 09:38
【摘要】:目的應(yīng)用表面增強(qiáng)激光解析離子化-飛行時(shí)間質(zhì)譜技術(shù)(surface-enhanced laser desorption ioni zation/time of flight mass spectrometry,SELDI-TOF-MS)和蛋白質(zhì)芯片篩選強(qiáng)直性脊柱炎(ankylosing spondylitis,AS)患者血清特異性標(biāo)志物,用于疾病診斷、評(píng)估及預(yù)測(cè)病情進(jìn)展。方法采用SELDI-TOF-MS技術(shù)和弱陽(yáng)離子交換(weak cation exchange)芯片檢測(cè)2008年4月至2009年1月山西醫(yī)科大學(xué)第二醫(yī)院風(fēng)濕免疫科收治的69例AS患者及12名健康對(duì)照者、10例類風(fēng)濕關(guān)節(jié)炎(rheumatoid arthritis,RA)患者血清蛋白質(zhì)表達(dá),進(jìn)一步將AS患者分為活動(dòng)期與非活動(dòng)期,中軸關(guān)節(jié)受累及中軸、外周關(guān)節(jié)均受累,HLA-B27陽(yáng)性與陰性組,比較不同分組之間患者血清蛋白質(zhì)指紋圖譜,采用SELDI質(zhì)譜儀自帶的Biomarker Wizard和Biomarker Pattern軟件篩選,初步建立疾病診斷預(yù)測(cè)模型。結(jié)果由8085、2640和2932建立的診斷預(yù)測(cè)模型Ⅰ診斷AS的敏感度為94.23%,特異度為100%。由3677、3880、2539、3159和3242建立的診斷預(yù)測(cè)模型Ⅱ判斷病情活動(dòng)的敏感度為98.11%,特異度為100%。由4700、8687和18538建立的診斷預(yù)測(cè)模型Ⅲ預(yù)測(cè)AS同時(shí)有中軸及外周關(guān)節(jié)受累的敏感度為80.00%,特異度為82.35%。由10259、7972、2048、2154和2954建立的診斷模型Ⅳ區(qū)分AS和RA的敏感度為100%(69/69),特異度為100%(10/10)。結(jié)論通過(guò)SELDI-TOF-MS技術(shù)建立的血清蛋白質(zhì)指紋圖譜可以篩選AS患者血清中的特異性蛋白質(zhì)標(biāo)志物,有望成為診斷疾病及評(píng)估病情的一種初篩平臺(tái)。
[Abstract]:Objective to screen serum specific markers in patients with ankylosing spondylitis (ankylosing spondylitis,AS) by surface enhanced laser desorption ionization time of flight mass spectrometry (surface-enhanced laser desorption ioni zation/time of flight mass spectrometry,SELDI-TOF-MS) and protein chip. Used for disease diagnosis, assessment and prediction of disease progression. Methods from April 2008 to January 2009, 69 patients with AS and 12 healthy controls in the Department of Rheumatological Immunology, second Hospital of Shanxi Medical University, were detected by SELDI-TOF-MS technique and weak cation exchange (weak cation exchange) chip. The expression of serum protein in 10 patients with rheumatoid arthritis (rheumatoid arthritis,RA) was further divided into active phase and inactive stage, central axis joint involvement and central axis, peripheral joint involvement, HLA-B27 positive and negative group. The serum protein fingerprints of different groups of patients were compared and the disease diagnosis and prediction models were preliminarily established by Biomarker Wizard and Biomarker Pattern software of SELDI mass spectrometer. Results the sensitivity and specificity of the predictive model I for diagnosis of AS were 94.23 and 100 respectively. The sensitivity and specificity of the diagnostic prediction model 鈪,

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