【作者】 刘伟；

【导师】 翁亚光； 王世鑫；

【作者基本信息】 重庆医科大学 ， 临床检验诊断学， 2010， 硕士

【摘要】 矽肺（silicosis）是由于长期吸入大量游离二氧化硅（SiO2）粉尘引起的以肺间质纤维化为主的全身性疾病,在我国是危害最严重的职业病之一。在我国平均每例尘肺病人每年经济损失约为3.41万元,每年仅因尘肺病造成的直接经济损失达140多亿元,每年新增尘肺病例造成的经济损失达6亿元。近年来矽肺病的流行呈现出群发性、低龄化以及致残率高的新特点,这给矽肺的防治工作带来了新的挑战。目前已发现许多对矽肺的诊断有价值的血清生物标志物,如肺特异性的克拉拉细胞蛋白（CC16）、肺表面活性物质D（SP-D）作为诊断指标仍存在敏感性、特异性不足的缺点,不同类型的肺间质病之间这些指标重叠较大;而支气管肺泡灌洗液的化学及细胞学检查仅能作为影像学诊断的补充。运用新技术手段筛选高特异性、敏感性的标志物将对矽肺的早期防治起到重要的推动。液体芯片飞行时间质谱技术是一种基于磁珠分选与基质辅助激光解吸离子化飞行时间质谱（MALDI-TOF-MS）联合应用的蛋白质鉴定技术,可直接检测临床未经特殊处理的血清、尿液、脑脊液或浆膜腔积液等标本,对疾病（特别是肿瘤）的诊断有较高的敏感性和特异性。本研究采用液体芯片飞行时间质谱技术检测矽尘暴露人群血清蛋白的表达,筛选出矽肺发病早期的生物标志物建立矽肺早期诊断的人工神经网络诊断模型并对鉴定出的标志物进行相关功能的初步研究。研究目的应用液体芯片飞行时间质谱技术筛选矽尘暴露人群早期诊断血清生物标志物,并对鉴定出的生物标志物进行初步功能研究。研究方法矽尘暴露人群85例为山西省阳泉市某耐火材料厂接触游离二氧化硅粉尘的工人,统一摄高千伏X射线后前位胸片（120-150KV、100mA、0.03-0.05s）,由具有诊断资格的诊断专家组按照《尘肺病诊断标准GBZ70-2002》进行诊断,分为矽尘暴露组（无尘肺0期）、可疑矽肺组（无尘肺0+期）和I期矽肺组;30例非暴露正常对照组为某单位年度体检人员,均无矽尘暴露史。本研究首先应用invitrogen公司生产的Dynabeads RPC18磁珠,对矽尘暴露人群和非暴露正常对照组的血清进行蛋白质（多肽）的分选,然后对分选后的蛋白（多肽）采用MALDI-TOF-MS的一级质谱技术和ClinProTools分析软件进行差异蛋白峰的筛选,同时应用Matlab分析软件建立人工神经网络诊断模型,最后对筛选出的差异蛋白质峰采用MALDI-TOF-MS二级质谱技术进行氨基酸序列鉴定。按照二级质谱鉴定出来的氨基酸序列人工合成差异蛋白,并用不同浓度的蛋白溶液作为刺激物,观察其对矽肺形成过程中的靶细胞人胚肺成纤维细胞（MRC-5）的影响。研究结果1.一级质谱寻找差异显著峰结果:利用神经网络算法（SNN）建立模型进行各组间两两比较,发现0期与0+期、0期与I期、0+期与I期比较,其识别率分别为64.35%、84.38%和73.49%,其交叉验证能力分别为63.14%、52.82%和69.07%;而正常对照组（control）与0期、正常对照组与0+期、正常对照组与I期比较,其识别率分别为89.23%、98.52%和98.96%交叉验证能力分别为87.66%、94.20%和85.53%。由上可知,0期与0+期、0期与I期、0+期与I期比较,其识别率和交叉验证能力都较差;而正常对照组（control）与0期、正常对照组与0+期、正常对照组与I期比较,其识别率和交叉验证能力都较好。因此,仅对0期、0+期、I期与正常对照组的差异显著峰进行提取,共得到5个差异峰（P<0.01）,其中5081Da和5066Da为表达上调的蛋白峰,2021da、3954da和1777da为表达下调的蛋白峰。2.二级质谱鉴定差异显著峰氨基酸序列结果:根据二级质谱仪器要求,选择分子量<3KDa的峰2021Da和1777Da进行二级质谱鉴定其氨基酸序列结果两蛋白质峰同为补体C3的一个片段C3f。3.矽尘暴露人群接尘量与差异峰强度相关性分析:接尘量与5081Da、5066Da、3954Da、2021Da和1777Da 5个差异显著峰的峰强的相关系数依次为r5081=0.039（P=0.614）、r5066=0.104（P=0.180）、r3954=-0.047（P=0.543）、r2021=-0.028（P=0.714）、r1777=-0.016 （P=0.853）,5个差异蛋白峰强度与接尘量均不存在相关性。4.矽尘暴露人群人工神经网络诊断模型的建立:筛选出峰效果较好的2021Da、2554Da、5066Da、8600Da 4个P<0.001的共同差异蛋白质峰建立矽尘暴露人群诊断模型,其区分矽尘暴露人群与正常对照组的特异性为100%,敏感性为90%,准确率为92.3%;该模型诊断0期、0+期和I期的识别率分别为100%、93%和96%。5.不同浓度C3f刺激对MRC-5细胞上清液中Ⅰ、Ⅲ型胶原及TGF-β₁表达量变化的影响:随着C3f浓度的增加,Ⅰ、Ⅲ型胶原及TGF-β₁的表达量均呈进行性降低。与对照组相比,各浓度点均有显著差异（P<0.05）。6.不同浓度C3f刺激对MRC-5胞质中TGF-β₁表达量变化的影响:随着C3f浓度的增加,MRC-5胞质中TGF-β₁的积分光密度值呈进行性降低,各浓度点均有显著差异（P<0.05）研究结论1.运用液体芯片飞行时间质谱技术的一级质谱寻找矽尘暴露人群差异蛋白,并成功建立了矽尘暴露人群人工神经网络诊断模型。2.运用液体飞行时间质谱技术的二级质谱技术鉴定出1777Da和2021Da同为C3f,后续的细胞功能研究证明C3f能够减少MRC-5细胞中Ⅰ、Ⅲ型胶原和TGF-β₁的形成。综上所述,本研究成功建立的矽尘暴露人群人工神经网络诊断模型为矽肺的早期诊断提供了一种全新而有效的方法,后续对差异蛋白C3f功能的初步研究结果也为进一步探讨矽肺发病的免疫机制提供了研究线索。更多还原

【Abstract】 Slilicosis, with the characteristics of pulmonary interstitial fibrosis, is caused by long-term inhalation of a large number of free slilica dust .It is one of the most serious occupational diseases in China.The average annual economic losses of each pneumoconiosis case was about 34.1 thousand yuan and the direct economic losses caused by silicosis alone were more than 140 billion yuan each year.An annual increase of cases of pneumoconiosis could cause economic losses of 600 million yuan.In recent years,the prevalence of silicosis showing new features of group incidence, lower-aged tendency and high-disabled rate,which brings new chanllenges for prevetion and treatment of silicosis.Recently,many of the valuable serum biomarkers have been found for the diagnosis of silicosis, such as the lung-specific Clara cell protein（CC16） and pulmonary surfactant D（SP-D）.As the diagnostic indicators, they still exist disadvantages of sentisitivity and specificity and different types of interstitial lung disease exist large overlap of these indicators.However,bronchoalveolar lavage fluid chemistry and cytology can only add or exclude from imaging diagnosis.The use of new technology to screen high specific and sensitive biomarkers will play an important force in prevention and treatment of silicosis.Liquid-chip time of flight mass spectrometry is one of the protein identification techniques that bases on magnetic beads separation combined with matrix-assisted laser desorption ionization time of flight mass spectrometry（MALDI-TOF-MS）.It can directly detect clinical specimens without special treatment,such as serum,urine fluid,cerebrospinal fluid, serous effusion or others but with high sensitivity and specificity for diagnosis.The aim of this study is to screen serum biomarkers of silica-exposed population by Liquid-chip time of flight mass spectrometry,then estabilish an artifical neural network model for early diagnosis and identify some associated functions of the markers which may contribute to a further study of the pathogenesis of silicosis mechanisms.ObjectivesTo screen serum biomarkers of silica-exposed population for early diagnosis by liquid-chip time of flight mass spectrometry,and identify some associated functions of the markers.MethodsEighty-five workers were selected from refractory plant of YangQuan City,ShanXi Province. All the silica-exposed population were diagnosed as having phase 0,phase 0+,or phase I of silicosis using radiograph（120-150KV, 100mA, 0.03-0.05s）, following the national diagnostic standard（GBZ70-2002） of China for pneumoconsis.Thirty healthy people without silica exposure history were chosen as the control population.Serum proteins（peptides） from silica-exposed population and control population was separated by a kind of magnetic beads produced by Invitrogen Company called Dynabeads RPC18, using MALDI-TOF-MS and an analysis software called ClinProTools to screen differences in protein peaks.Then,Matlab analysis software was applied to estabilish an artificial neural network diagnosis model.Finally, the amino acid sequences of the selected protein peaks were identified by MALDI-TOF-TOF-MS.According to the amino acid sequence identified by MALDI-TOF-TOF-MS to synthesize the selected protein. Using different concentrations of protein solutions as stimulus to observe the effects of the target cells in the formation of silicosis called human embryo lung fibroblast（MRC-5） cells.Results1. Differentially expressed protein peaks found by MALDI-TOF-MSUsing neural network algorithm（SNN） to build pairwise comparison between each two groups, we found that the recognition rates between phase 0 and 0+, phase 0 and I , phase 0+ and I were respectively 64.35%,84.38% and 73.49%, similarly the cross-validations were 63.14%,52.82% and 69.07%; while between control group and phase 0, control group and phase 0+, control group and phase I, the recognition rates were 89.23%,98.52% and 98.96% respectively, similarly the cross-validations were 87.66%,94.20% and 85.53%.Clear from the foregoing, the recognition rates and cross-validation capabilities between phase 0 and 0+, phase 0 and I, phase 0+ and I are all poor; while between control group and phase 0, control group and phase 0+, control group and phase I are all better. Thus, we just study differentially expressed protein peaks between control group and phase 0, control group and phase 0+, control group and phase I. A total of 5 peaks （P<0.01）have been found, in which the expressions of 5081Da and 5066Da are up-regulated while the expressions of 3954Da, 2021Da and 1777Da are down-regulated.2. Amino acid sequence identified by MALDI-TOF-TOF-MS2021Da and 1777Da peaks with molecular weight <3KD are selected for MALDI-TOF-TOF-MS. The amino acid sequences of the two peaks identified are both a fragment of complement C3 called complement C3f.3. the correlation between the exprosure dose of dust and the intensitiy of peaks in silica-exposed populationThe correlation coefficient is respectively r5081=0.039（P=0.614）、 r5066=0.104（P=0.180）、r3954=-0.047（P=0.543）、r2021=-0.028（P=0.714）、r1777=-0.016（P=0.853）,and there were no correlation between each group.4.Establishment of artificial neural network diagnosis model of silica-exposed populationPeaks of 2021Da, 2554Da, 5066Da, 8600Da（P<0.01） are chosen to estabilish the diagnosis model. The specificity, sensitivity and accuracy rate of the model to distinguish between silica-exposed population and control group are 100%, 90% and 92.3%. While the recognition rates of phase 0,phase 0+ and phase I are respectively 100%,93% and 96%.5.Expression differences of typeⅠ,Ⅰcollagen and TGF-β₁in the supernatant of MRC-5 stimulated by C3f with different concentrationsWith the increasing concentrations of C3f, the expressions of typeⅠ,Ⅰcollagen and TGF-β₁ show progressive reductions.Compared with control group, any concentration points are significantly different（P<0.05）. 6.Expression differences of TGF-β₁ in the cytoplasm of MRC-5 stimulated by C3f with different concentrationsWith the increasing concentrations of C3f, the expressions of TGF-β₁ show progressive reductions.Compared with control group, any concentration points are significantly different（P<0.05）.Conclusions1.Using MALDI-TOF-MS of liquid-chip time of flight mass spectrometry to search differentially expressed protein peaks and successfully estabilish artificial neural network diagnosis model of silica-exposed population. 2.Using MALDI-TOF-TOF-MS of liquid-chip time of flight mass spectrometry to identify the peaks of 1777Da and 2021Da are both complement C3f. The following functional studies have show that C3f can reduce the formation of typeⅠ,Ⅰcollagen and TGF-β₁of MRC-5.In summary, this study successfully estabilishs artificial neural network diagnosis model of silica-exposed population which can offer a new and effective way for the early diagnosis of silica-exposed population,while the following functional study of C3f provides a clue for further study of the immune mechanisms in the pathogenesis of silicosis.更多还原