本文選題：重型肝炎 + 預(yù)后　； 參考：《西南醫(yī)科大學(xué)》2017年碩士論文

【摘要】：目的:本研究旨在通過(guò)應(yīng)用SELDI-TOF-MS(surface enhanced laser desorption/ionization time-of flight mass spectrometry)技術(shù)獲得HBV相關(guān)重型肝炎不同臨床結(jié)局患者和正常人血漿中的蛋白質(zhì)指紋圖譜,篩選出與重型肝炎患者預(yù)后相關(guān)的差異蛋白,并利用這些差異蛋白初步構(gòu)建重型肝炎的預(yù)后預(yù)測(cè)模型,為重型肝炎預(yù)后判斷提供可靠的、敏感的指標(biāo)。方法:收集西南醫(yī)科大學(xué)附屬醫(yī)院感染科住院部HBV相關(guān)重型肝炎患者35例和我院體檢中心健康志愿者15例的血漿標(biāo)本,分別作為實(shí)驗(yàn)組和對(duì)照組。同時(shí)收集患者的人口學(xué)資料和臨床資料(包括肝功能、凝血功能等)。實(shí)驗(yàn)組患者隨訪時(shí)間至少12周。根據(jù)隨訪患者病情的轉(zhuǎn)歸不同分為死亡組和存活組。應(yīng)用SELDI-TOF-MS蛋白質(zhì)芯片技術(shù)檢測(cè)HBV相關(guān)重型肝炎患者和正常健康人血漿樣本,獲得弱陽(yáng)離子交換芯片CM10的蛋白質(zhì)指紋圖譜。使用ProteinChip 3.2軟件和Biomarker Wizard軟件識(shí)別蛋白指紋圖譜,并利用SPSS 16.0軟件對(duì)所采集的數(shù)據(jù)進(jìn)行統(tǒng)計(jì)學(xué)分析,利用Biomarker Patterns(BPS 5.0)軟件采用樹(shù)形分類(lèi)方法對(duì)HBV相關(guān)重型肝炎患者初步建立預(yù)后預(yù)測(cè)模型,并計(jì)算該模型對(duì)HBV相關(guān)重型肝炎患者預(yù)后判斷的敏感性和特異性。計(jì)量資料采用均數(shù)±標(biāo)準(zhǔn)差(x±s)描述。組間比較采用兩個(gè)獨(dú)立樣本t檢驗(yàn)。以P0.05示有統(tǒng)計(jì)學(xué)意義。結(jié)果:CM10蛋白芯片檢測(cè)結(jié)果顯示,HBV相關(guān)重型肝炎患者和健康對(duì)照組血漿樣本在蛋白分子量1000Da-50000Da的范圍內(nèi)一共檢測(cè)出57個(gè)蛋白峰表達(dá)水平有差異,其中與健康對(duì)照組相比較,重型肝炎存活組有25個(gè)蛋白峰表達(dá)有顯著差異(p0.05),其中有6個(gè)蛋白峰顯著升高,它們是m2017_57、m7568_86、m7937_87、m15109_0、m15268_2、m15845_0;有19個(gè)蛋白峰顯著降低,它們是m2196_71、m2235_78、m2747_23、m2796_85、m2881_48、m2913_26、m3224_17、m3322_84、m4309_41、m6437_01、m6634_84、m6839_64、m8601_12、m9185_56、m28057_7、m33395_2、m34404_9、m44842_1、m45146_8。重型肝炎死亡組有24個(gè)蛋白峰表達(dá)有顯著差異(p0.05),其中有6個(gè)蛋白峰顯著升高,它們是m2017_57、m6634_84、m7568_86、m7937_87、m15268_2、m15845_0;有18個(gè)蛋白峰顯著降低,它們是m2235_78、m2747_23、m2881_48、m2913_26、m3224_17、m3322_84、m3376_49、m4309_41、m5908_26、m6437_01、m6584_63、m6839_64、m8601_12、m14670_8、m15109_0、m28057_7、m33395_2、m34404_9。重型肝炎存活組和死亡組比較發(fā)現(xiàn)有16個(gè)蛋白峰表達(dá)有顯著差異(p0.05),它們分別是m3376_49、m3479_65、m3492_79、m3936_56、m5649_11、m7568_86、m7766_46、m7937_87、m8601_12、m9290_44、m11692_6、m14670_8、m15109_0、m15268_2、m15845_0、m45146_8。應(yīng)用biomarkerpatterns軟件對(duì)重型肝炎存活組和死亡組之間有統(tǒng)計(jì)學(xué)意義的蛋白峰進(jìn)行比較分析,并最終篩選出5個(gè)差異蛋白峰組成樹(shù)形決策模型。這5個(gè)差異蛋白峰分別是m3492_79、m5649_11、m3936_56、m7568_86和m8601_12,所建立的模型對(duì)重型肝炎預(yù)后判斷的敏感性為72.00%,特異性為100.00%。結(jié)論:1.應(yīng)用seldi-tof-ms技術(shù)可以發(fā)現(xiàn)hbv相關(guān)重型肝炎發(fā)生、發(fā)展過(guò)程中某些蛋白質(zhì)表達(dá)水平有差異,不同臨床結(jié)局的重型肝炎患者血漿蛋白峰表達(dá)差異比較顯著。2.利用這些差異蛋白峰構(gòu)建的預(yù)后預(yù)測(cè)模型對(duì)HBV相關(guān)重型肝炎患者的臨床結(jié)局判斷有著重要的意義,并提示這些差異表達(dá)的蛋白質(zhì)可能和HBV相關(guān)重型肝炎預(yù)后關(guān)系密切,但尚需進(jìn)一步研究證實(shí)。
[Abstract]:Objective: the purpose of this study was to obtain the protein fingerprints in the plasma of patients with different clinical outcomes of severe hepatitis and normal human plasma by using SELDI-TOF-MS (surface enhanced laser desorption/ionization time-of flight mass spectrometry) technology, and to screen out the differential proteins associated with the prognosis of patients with severe hepatitis and use this method. Some differential proteins were initially constructed to predict the prognosis of severe hepatitis and provide a reliable and sensitive indicator for the prognosis of severe hepatitis. Methods: 35 cases of severe hepatitis in the hospital department of infection department of the Affiliated Hospital of Southwest Medical University were collected in 35 cases of severe hepatitis patients and 15 cases of healthy volunteers in the medical center of our hospital. The patients' demographic and clinical data (including liver function, coagulation function, etc.) were collected at the same time. The patients in the experimental group were followed up for at least 12 weeks. According to the prognosis of the patients, the patients were divided into the death group and the survival group according to the prognosis of the patients. The SELDI-TOF-MS protein chip technique was used to detect the plasma samples of patients with severe hepatitis HBV and normal health. The protein fingerprint of the weak cation exchange chip CM10 was obtained. The ProteinChip 3.2 software and Biomarker Wizard software were used to identify the protein fingerprints, and the data collected by the SPSS 16 software were statistically analyzed. The Biomarker Patterns (BPS 5) soft parts were used to use the tree classification method for the severe hepatitis associated with HBV. The prognosis prediction model was preliminarily established, and the sensitivity and specificity of the model to the prognosis of patients with HBV related severe hepatitis were calculated. The measurement data were described with mean number + standard deviation (x + s). Two independent sample t tests were used among the groups. The results of P0.05 were statistically significant. Results: the results of CM10 protein chip detection showed that HBV related heavy duty was heavy. The plasma samples of the hepatitis patients and the healthy control group detected 57 protein peaks in the range of protein molecular weight 1000Da-50000Da. Compared with the healthy control group, there were 25 protein peaks in the survival group of severe hepatitis (P0.05), of which 6 protein peaks were significantly increased, they were m2017_57, m7568_86 M7937_87, m15109_0, m15268_2, m15845_0, which have 19 protein peaks, which are m2196_71, m2235_78, m2747_23, m2796_85, m2881_48, m2913_26, m3224_17, there are 24 protein peaks in the severe hepatitis death group. There are 6 protein peaks in P0.05, which are m2017_57, m6634_84, m7568_86, m7937_87, m15268_2, m15845_0, and there are 18 protein peaks, which are m2235_78, m2747_23, m2881_48, m2913_26. It is found that there are 16 protein peaks in the survival group and the death group of the severe hepatitis m34404_9. (P0.05). They are m3376_49, m3479_65, m3492_79, m3936_56, m5649_11, m7568_86, m7766_46, m7937_87. A statistically significant protein peak was compared between the survival group of severe hepatitis and the death group, and 5 differential protein peaks were selected to form a tree decision model. The 5 differential protein peaks were m3492_79, m5649_11, m3936_56, m7568_86 and m8601_12, and the sensitivity of the established model to the prognosis of severe hepatitis was 72%. The opposite sex is 100.00%. conclusion: 1. SELDI-TOF-MS technique can be used to detect the occurrence of severe hepatitis associated with HBV. There is a difference in the expression level of some proteins in the course of development. The difference of the expression of protein peak in the plasma of severe hepatitis patients with different clinical outcomes is more significant than that of.2., and the prognosis prediction model constructed by these differential protein peaks for HBV related severe liver disease It is important to judge the clinical outcome of inflammatory patients and suggest that these differentially expressed proteins may be closely related to the prognosis of HBV related severe hepatitis, but further research is needed.
【學(xué)位授予單位】：西南醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R512.62

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