孕期神经管缺陷畸形蛋白质谱的初步筛查研究
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摘要
前言
神经管缺陷(neural tube defects, NTDs)是常见的先天性中枢神经系统畸形。其发生机制是在胚胎生长发育的前四周内神经管闭合发生障碍,导致神经系统的各种畸形。包括无脑儿,脊柱裂,脑膜膨出,脊髓脊膜膨出,脑膨出,脑积水,脊髓积水空洞症等。神经管缺陷的发病率为,女性高于男性,农村高于城市,北方高于南方。我国神经管缺陷发生率约为10.63／万。神经管缺陷胎儿约54%在孕27周前自然流产,46%进入围产期。缺陷儿童的出生,不仅造成家庭与社会的沉重负担,而且严重影响人口素质。因此,除对致病因素预防外,产前诊断是目前极为重要而且有效的方法。目前神经管缺陷的产前筛查主要依靠超声影像学和孕母血清和羊水蛋白质标记物的检测。
产前超声检查已成为当前最常用的诊断胎儿形态异常的金标准。但做超声检查,胎龄必须达12周以上,并且对于腰骶部位病变、胎儿体位不理想、胎动活跃,孕妇肥胖等均容易漏诊。孕母血清甲胎蛋白和羊水甲胎蛋白检测是产前诊断的重要内容。孕母血清甲胎蛋白(maternal serum alpha-fetoprotein, MSAFP)和羊水甲胎蛋白(amniotic fluid alpha-fetoprotein, AFAFP)含量增高可以提示胎儿神经管缺陷。但多胎妊娠、胎儿腹壁缺损、先天性肾病、胎死宫内、胎儿血污染羊水等因素均可引起甲胎蛋白假阳性增高。而且羊膜腔穿刺取羊水、早孕绒毛组织检查和植入性产前遗传诊断均为侵入性诊断,可造成孕妇和胎儿的损伤、阴道出血、感染和流产,故其应用受到限制。
蛋白质是细胞代谢和调控途径的主要执行者,蛋白质组学是研究细胞内全部蛋白质的组成和变化的新学科,它对于疾病的早期诊断和发病机制都具有重要意义。研究不同时期细胞蛋白质组成的变化,发现有差异表达的蛋白质即“表达蛋白质组学”是现今应用最为广泛的蛋白质组学研究模式。在质谱分析基础上发展的表面增强激光解吸／离子化飞行时间质谱技术(surface enhanced laser desorption/ ionization time-of-flight mass spectrometry, SELDI-TOF-MS)对某些疾病,特别是肿瘤、遗传性疾病和中枢神经系统疾病的相关蛋白的识别上已经取得了突破性进展。探索神经管缺陷特异性标志蛋白,建立一套简单、快速、灵敏度高和特异性强的早期诊断技术已成为临床医学的迫切需要。本实验中我们采用SELDI技术,选取蛋白质芯片中的弱阳离子芯片改进型CM10芯片,筛选胎儿神经管缺陷的孕母血清、尿液、羊水和神经管缺陷胎鼠羊水蛋白质标志物,为提高神经管缺陷诊断效率奠定基础。本实验中所有临床标本均经过孕妇本人书面同意,并经过中国医科大学附属盛京医院医学伦理委员会批准同意。
材料与方法
一、实验对象
(一)胎儿神经管缺陷的孕母血清标本
经超声确诊为胎儿神经管缺陷的孕妇17例,孕周数相匹配的正常孕妇14例。神经管缺陷包括脊柱裂7例,无脑儿4例,脑积水6例。对照组孕妇为同期接受产前检查的受检者。所有孕妇均于清晨空腹取外周静脉血5ml,立即置于4℃,静置1-2h。再于4℃,4000 rpm,离心10min。吸取上清,按每管100μl分装,置于-80℃保存备用。
(二)胎儿神经管缺陷的孕母尿液标本
经超声确诊为神经管缺陷的孕妇20例,孕周数相匹配的正常孕妇15例。神经管缺陷包括脊柱裂10例,无脑儿5例,脑积水5例。对照组孕妇为同期接受产前检查的受检者。所有孕妇均取清晨空腹尿5ml,立即于4℃,2500rpm,离心min。吸取上清,按每管100μl分装,置于-80℃保存备用。
(三)胎儿神经管缺陷的孕母羊水标本
经超声确诊为神经管缺陷的孕妇11例,孕周数相匹配的正常孕妇9例。神经管缺陷包括脊柱裂5例,无脑儿5例,脑积水1例。对照组孕妇为同期接受产前检查的受检者。所有孕母均于引产前经腹抽取羊水5ml,立即于4℃,2500 rpm,离心5min。吸取上清,按每管100μl分装,置于-80℃保存备用。
(四)神经管缺陷胎鼠羊水标本
26只雌性Wistar大鼠(体重220-260g),分为畸形组(n=11)和对照组(n=15)。在标准条件下饲养,午夜雌：雄=4：1合笼。次日清晨8时阴道涂片,镜检精子,确定其妊娠日期,有精子者计为孕0日(E0)。在孕10日(E10)晨8时,畸形组雌鼠称体重,按120mg／Kg称取全反式维甲酸与矿物油混合均匀(维甲酸浓度为40mg／ml),经胃管一次注入孕鼠胃内。对照组仅将不含维甲酸的矿物油与畸形组同量经胃管一次注入。雌鼠于孕17天(E17),用10%水合氯醛按300mg／Kg进行腹腔注射麻醉。将孕鼠固定于操作台上,酒精消毒腹部,剪开腹部皮肤及肌肉,暴露子宫。在子宫外大体确定是否存在畸形。用2ml无菌注射器抽取胎鼠羊膜腔内羊水,每只胎鼠取出约0.1-0.3ml羊水,每只胎鼠羊水单独分装。选取羊水清亮者立即置于4℃保存。在立体显微镜下进一步确认胎鼠有无畸形和畸形类型。畸形组中胎鼠畸形分四种：①单纯性肛门闭锁畸形；②脊柱裂合并肛门闭锁畸形；③脊柱裂合并肛门闭锁和马蹄内翻足畸形；④给药后无畸形。选取脊柱裂合并肛门闭锁畸形组的胎鼠羊水作为研究对象。对照组胎鼠均为正常胎鼠。所有羊水立即于4℃,4000 rpm,离心10min。吸取上清,按每管100μl分装,置于-80℃保存备用。
二、蛋白质芯片类型
选用SELDI蛋白质芯片中CM10芯片,CM10芯片是弱阳离子亲和芯片WCX2芯片的改进型。具有变异系数小,重复性好,操作方便,结果更稳定等优点。购于美国Ciphergen公司。
三、主要试剂
TFA：三氟乙酸；NaAC:醋酸钠；DTT：二硫苏糖醇；CHAPS:3-[3-(胆酰胺基丙基)二甲氨基]丙磺酸盐；Urea:尿素；ACN：乙腈；SPA：饱和芥子酸。均为Sigma原装进口,购自SIGMA公司北京代理：北京舒伯伟化工仪器有限责任公司。
四、孕母血清(尿,羊水)和胎鼠羊水样品处理
于-80℃中取出孕母血清(尿,羊水)和胎鼠羊水样品,4℃融解。10,000rpm,4℃,离心2min。取10μl血清(尿,羊水)和胎鼠羊水样品用20μl U9缓冲液稀释,混匀,置于4℃变性。加入360μl(尿加250μl,孕母羊水和胎鼠羊水均加170μl)缓冲液,混匀,使血清(尿,孕母羊水和胎鼠羊水)总稀释倍数达到约39倍(尿为28倍,羊水为20倍)。上样和洗脱：在CM10芯片上每孔加入200μl结合缓冲液,震荡5min,甩掉缓冲液。重复上述操作一次。加入处理好的样品100μl,室温震荡60min,甩出样品。再次加入结合缓冲液200μl,室温震荡5min,甩去孔中液体。重复操作一次。加入超纯水200μl,立刻甩出。取出芯片,待自然风干后,加能量吸收分子饱和芥子酸SPA0.5μl二次。待干后,即可上机测定。
五、数据采集与分析
采用PBSIIC型蛋白质芯片阅读机读取数据。设定优化相对分子质量范围1000-30,000Da。每次实验数据收集前,用All-in-one蛋白质芯片校正仪器,使蛋白质分子量误差<0.1%。应用Biomarker Wizard(美国Ciphergen公司)软件分析处理所有峰谱,形成蛋白质指纹图谱。所有的图谱都进行标准化,定义蛋白峰信噪比(S／N)>5,变异系数CV＜10%。采用Mann-Whitney U检验比较配对样本的蛋白峰,计算P值。P<0.05有统计学意义。采用Ciphergen protein chip 3.1.1软件对数据进行统计分析。
实验结果
一、胎儿神经管缺陷的孕母血清标志蛋白质谱分析
在相对分子量1000-30,000Da范围内,共检测到55个血清差异蛋白峰,有统计学意义的差异蛋白峰有12个。病例组中有8种蛋白质高表达,相对分子质量分别为4105,4297,4188,6650,8583,3282,2750,3327；4种蛋白质低表达,相对分子质量分别为5497,28078,9155,9434。
二、血清蛋白质标志物决策分类树诊断模型的建立与结果分析
蛋白质指纹图谱软件(Biomarker Patterns Software, BPS)对经过Biomarker Wizard获得的血清蛋白质谱数据进行分析处理,并采用决策分类树分析方法。建树后,得到了带有3个终结点的决策分类树,获得了2个标志性蛋白质,其分子量分别为4105,7788。计算其各自的权重,变量重要性评分分别为100(4105),44.94(7788)。采用该分类树建立起来的神经管缺陷诊断模型的灵敏度为88.2%,特异度为100%。
三、胎儿神经管缺陷的孕母尿液蛋白质芯片检测结果
在相对分子量1000-30,000Da范围内,共检测到39个尿液差异蛋白峰,有统计学意义的差异蛋白峰有5个。神经管缺陷组尿液特异性蛋白标记物有5个。其中4种蛋白标记物高表达,相对分子质量分别为8320,8209,9099,10567。1种蛋白标记物低表达,相对分子质量为3458。
四、尿液蛋白质标志物决策分类树诊断模型的建立与结果分析
BPS软件对经过Biomarker Wizard获得的尿液蛋白质谱数据进行分析处理,建立决策分类树诊断模型。建树后,得到了带有3个终结点的决策分类树,获得了2个标志性蛋白质,其分子量分别为9096,8244。采用该分类树建立起来的神经管缺陷诊断模型,进行留一法交叉验证后,确定其灵敏度为80.0%,特异度为93.3%。
五、胎儿神经管缺陷孕母羊水蛋白质谱分析
在相对分子量1000-30,000Da范围内,共检测到35个羊水差异蛋白峰,有统计学意义的差异蛋白峰有7个。神经管缺陷组羊水中有6种蛋白质高表达,相对分子质量分别为14700,7995,15891,16027,13776,11040。1种蛋白质低表达,相对分子质量为23417。
六、神经管缺陷胎鼠羊水蛋白质谱分析
在相对分子量1000-30,000Da范围内,共检测到55个羊水差异蛋白峰,有统计学意义的差异蛋白峰有9个。脊柱裂合并肛门闭锁组胎鼠羊水中有5种蛋白质高表达,相对分子质量分别为11658,27387,7898,11603,13829。4种蛋白低表达,相对分子质量分别为5124,14702,5403,13626。
七、神经管缺陷胎儿和神经管缺陷胎鼠羊水蛋白质比较
神经管缺陷胎儿和神经管缺陷胎鼠羊水中共同蛋白质为：4138(4145),7947(7941),8588(8588),9385(9390),14702(14700)。其中14700(P=0.006)具有非常显著性差异,很可能是神经管缺陷胎儿和神经管缺陷胎鼠羊水共同蛋白质标志物。
结论
1、应用表面增强激光解吸／离子化飞行时间质谱技术筛查出胎儿神经管缺陷的孕母血清、尿液和羊水的差异蛋白峰,这些差异蛋白峰可能是胎儿神经管缺陷孕母血清、尿液和羊水的特异性蛋白质标志物。
2、应用胎儿神经管缺陷的孕母血清和尿液蛋白质标记物建立决策分类树诊断模型,对于神经管缺陷的诊断灵敏度分别为88.2%、80.0%,特异度分别为100%、93.3%。证明表面增强激光解吸／离子化飞行时间质谱技术对于诊断神经管缺陷是一项有效、快捷、灵敏度高、特异性强的临床诊断工具。
3、神经管缺陷胎儿和神经管缺陷胎鼠羊水共同蛋白质为：4138(4145),7947(7941),8588(8588),9385(9390),14702(14700)。其中14700(P=0.006)具有非常显著性差异,很可能是神经管缺陷胎儿和神经管缺陷胎鼠羊水共同蛋白质标志物。
Introduction
Neural tube defects (NTDs) are quite common congenital central nervous system abnormalities. Embryologically, failure in neural tube closure determines a group of diseases called neural tube defects, including anencephaly, spina bifida, meningocele, myelomeningocele, encephalocele, hydrencephaly, hydrosyringomyelia. Neural tube defects have been described in all popμlations in which they have been sought. Half of these defects are spina bifida and half are anencephaly with or without spina bifida. Historically, the birth prevalence of NTDs has ranged from about 0.5 to 6 in 1,000 births. Both environmental and genetic causes may be the reason of neural tube defects. Prevalence of neural tube defects is about 10.63 in 10,000 births, female is superior to male, countryside is superior to city. Abortion will occur in 54%of neural tube defects before twenty seven pregnancy weeks, and 46%of neural tube defects will entry in perinatal period. Newborns with neural tube defects will be a serious burden to their families and decrease the population quality.
At present, prenatal diagnosis may be the most important screening method. Maternal serum alpha-fetoprotein (MSAFP) and amniotic fluid alpha fetoprotein (AFAFP) screening and ultrasonography have been used for detecting neural tube defects prenatally. The improved resolution of ultrasonography has allowed detailed imaging of nervous system anatomy and enhanced understanding of both development and pathology. Prenatal screening in the general population is based on two complementary methods, maternal serum AFP screening and ultrasound screening. It is necessary for ultrasonography that gestation age must excess to 12 weeks in pregnancy, and many factors will result in the missed diagnosis of ultrasonography. Prenatal diagnosis in pregnancies identified as being at a high risk of open neural tube defects requires fetal scanning by an expert sonographer. MSAFP and AFAFP levels will be abnormally high in the open neural tube defects and can be used as screening tests. However, both specificities are not good and such screenings are inadvisable. Amniocentesis for acetylcholinesterase electrophoresis is an invasive method and should be limited.
The surface enhanced laser desorption/ionization flight-of-time mass spectrometry (SELDI-TOF-MS) technology, developed from the technology of chromatography and mass spectrometry (MS), includes a protein capture chip. The specific protein can be captured on the chip surface. SELDI-TOF-MS offers the advantages of rapid and simple examination as well as high specificity and sensitivity. It analyses small volumes of clinical samples without destroying the proteins to be detected and is capable of examining proteins and peptides, which are not available for conventional methods. New proteins specific to some diseases and characterization of these proteins can be discovered and captured by comparative analysis of the mass spectra of the samples from patients and normal controls. Thus, it is suitable for examination of small volumes of samples such as serum, urine, amniotic fluid with complicated components, and an ideal method to find protein biomarkers. At present, there are many exciting SELDI-TOF-MS applications, which have been described by numerous laboratories, especially in studying cancers of various organs, including prostate, ovary, breast, lung, colon, and others. To our knowledge, there has been no study reported using SELDI-TOF-MS technology to investigate neural tube defects. In this study, the serum, urine, amniotic fluid proteins of the patients and rat with neural tube defects and those of normal controls were analysed. SELDI-TOF-MS (Ciphergen Biosystems, USA) was used to detect specific protein biomarkers in serum, urine, amniotic fluid and to obtain diagnostic fingerprints which, coupled with the dicision tree analysis patterns for detection of serum and urine proteins, would give an early diagnosis of neural tube defects.
Material and methods
1. Collection and preparation of samples
(1) serum samples
Of the 31 serum samples obtained,17 were from patients with neural tube defects and 14 from healthy volunteers undergoing pregnancy routineμltrasonography examination in the Department of ultrasound, Shengjing Hospital, China Medical University. The diagnosis of the neural tube defects was confirmed routine ultrasonography examination. All fasting blood were obtained early in the morning. Untreated whole blood were collected and allowed to clot 1-2hrs at room temperature. Serum was purified from blood by centrifugation for 10 minutes (4000rpm) at 4℃, aliquoted as 100 microliters and stored at-80℃. Serum samples were not subjected to more than two freeze-thaw cycles before the assay.
(2) urine samples
Of the 35 urine samples obtained,20 were from patients with neural tube defects and 15 from healthy volunteers undergoing routine ultrasonography examination in the Department of ultrasound, Shengjing Hospital, China Medical University. The diagnosis of the neural tube defects was confirmed routine ultrasonography examination. All fasting urine were obtained early in the morning. Urine were collected and centrifugated for 5 minutes (2500 rpm) at 4℃immediately after collection, aliquoted as 100 microliters, and stored at-80℃until analysis. Urine samples were not subjected to more than two freeze-thaw cycles before the assay.
(3) amniotic fluid samples of fetal neural tube defects
Of the 20 amniotic fluid samples obtained,11 were from patients with neural tube defects and 9 from healthy volunteers undergoing routine ultrasonography examination in the Department of ultrasound, Shengjing Hospital, China Medical University. The diagnosis of the neural tube defects was confirmed routine ultrasonography examination. AF was retrieved by transabdominal amniocentesis. Centrifugation were performed immediately after amniocentesis as part of the clinical workup. Specimen was centrifuged at 2500rpm and 4℃for 5 min, aliquoted as 100 microliters, and stored at -80℃until analysis.
The Ethics Boards of China Medical University approved this research study. Written informed consent was obtained from all participants prior to the procedure. Subjects were enrolled prospectively based on the availability of one of the investigators for consent procedures.
(4) amniotic fluid samples of fetal rat neural tube defects
Timed-mated (GD 0 assigned as the day of mating) female Wistar rats were acquired from medicine animal center of China Medical University. Rats were healthy and mature and ranged between 220-250g at the initiation of dosing. The rats were housed individually in cages. Certified rodent diet and drinking water were provided ad lib. Animals were randomly assigned to experiment groups and control groups. Environmental conditions were set to maintain room temperature and humidity for rats. Room lighting was on a 12-hr light/dark cycle. The facility is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International. Pregnant Wistar rats were administered with a suspension of all-trans retinoic acid (120 mg/kg) and liquid paraffin (40 mg/ml) on gestational days 10 and control group were studied. Amniotic fluid of fetal rat on gestational days 17 were aspirated by a needle. The deformities of fetal rats were identified by microscopy. Tha rats with spina bifida and anal atresia were chosen as experiment objects. The amniotic fluid must not be muddy, and amniotic fluid was immediately centrifuged at 4000rpm and 4℃for 10 minitus, aliquoted as 100 microliters, and stored at-80℃until analysis.
2. Samples preparation
The serum samples (urine, amniotic fluid) from the patients and rats with neural tube defects were collected prior to the start of treatment. All samples were thawed at room temperature and then centrifugated for 2 minutes (10,000 rpm) at 4℃. Ten microlitres of supernatant were first put into 20μl of protein denaturant (9 mol/L urea, 2%CHAPS,1%DTT,50 mmoL/L Tris-HCL, pH 9.0) and shaken at 4℃for 30 minutes on a shaker for complete protein denaturing. Then,30 microlitres of denatured sample was further diluted with 50 mmol/L sodium ethanoate (acetate, pH 4.0)to 390μl (urine to 280μl, amniotic fluid to 200μl)
3. Reagents and instruments
Sodium ethanoate (acetate), carbamide, acetonitrile, trifluoroethanoic acid and SPA(sinapinic acid)were purchased from Sigma(USA). Protein chip biosystem(PBSⅡC) and CM 10 chip were purchased from Ciphergen Biosystems (USA)
4. samples preparation
A protein chip was installed into a bioprocessor (Ciphergen, USA). Two hundred microlitres of binding buffer (50 mmol/L sodium ethanoate, pH 4.0) were added into each spot of an eight spot chip, and shaken for 5 minutes on a shaker. The shaking was repeated in the same way after the binding buffer was removed. One hundred microlitres of sample were added and shaken for 60 minutes. After the serum sample (urine sample, amniotic fluid sample) was thrown off, the chip was washed two times with binding buffer for 5 minutes each time, rinsed once with ultrapure water and airdried. The proteins bound CM 10 chip was then treated with 1μl of saturated sinapinic acid solution(Ciphergen,USA). The chip was airdried for future examination.
5. collection and preparation fo data
A mass spectrometer was calibrated with chips that had been bound with all-in-one standard proteins to set up parameters. The parameters used were:the optimal detection mass/charge size (m/z) range was between 1000 and 30,000Da; the laser intensity was set at 225 and the detector sensitivity was set at 9. An average value of 130 spots was presented for each sample. All samples were detected with the same parameters. All the raw data were normalized with the ProteinChip Software version 3.1.1. The peaks m/z of the samples with more than 1000 Da were normalized with biomark wizard of ProteinChip Software version 3.1.1 for noise filtering. The first threshold for noise filtering was set at 5. Generation of the tree analysis pattern was performed by Biomarker Patterns Software (Ciphergen Biosystems, Inc.). The data of spectra were analyzed by bioinformatics tools-Biomarker Wizard and Biomarker Pattern Software.
6. statistical analysis of the data
The data were processed with the ProteinChip Software version 3.1.1 for Mann-Whitney U test. P value< 0.05 was considered statistically significant.
Results
1.maternal serum protein biomarkers
A total of 55 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set. Compared with the spectra of control groups, there were 12 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 8 of which (4105,4297,4188,6650,8583,3282,2750, 3327) and low in the 4 of which(5497,28078,9155,9434). The softwares Biomarker Wizard and Biomarker Pattern Software automatically, under given conditions, selected 2 biomarker proteins (4105,7788) to be used to establish a three layer decision tree differentiate to diagnose neural tube defects and differentiate neural tube defects from control groups with a specificity of 100%and a sensitivity of 88.2%.
2.maternal urine protein biomarkers
A total of 39 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set between 1000 and 30,000Da. Compared with the spectra of control groups, there were 5 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 4 of which (8320,8209,9099,10567) and low in the 1 of which (3458). The softwares Biomarker wizard and Biomarker Pattern Software automatically, under given conditions, selected 2 biomarker (9096,8244) proteins to be used to establish a three layer decision tree with three terminal nodes differentiate to diagnose neural tube defects and differentiate neural tube defects from control groups with a specificity of 93.3% and a sensitivity of 80.0%.
3.maternal amniotic fluid protein biomarkers
A total of 35 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set between 1000 and 30,000Da. Compared with the spectra of control groups, there were 7 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 6 of which (14700,7995,15891,16027,13776, 11040) and low in the 1 of which (23417)
4.rat amniotic fluid protein biomarkers
A total of 55 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set between 1000 and 30,000Da. Compared with the spectra of control groups, there were 9 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 5 of which (11658,27387,7898,11603,13829) and low in the 4 of which (5124,14702,5403,13626)
5.comparation between maternal amniotic fluid protein biomarkers and rat amniotic fluid protein biomarkers
Compared between maternal amniotic fluid protein biomarkers and rat amniotic fluid protein biomarkers, five mass peaks, including 4138 (4145),7947 (7941), 8588 (8588),9385 (9390),14702 (14700),especially m/z 14700 (P=0.006) may be the same protein/peptide of them.
Conclusion
1. These discrepancy mass peaks of serum, urine and amniotic fluid identified by SELD-TOF-MS (surface enhanced laser desorption/ionization time-of-flight mass spectrometry) may be the specific serum, urine and amniotic fluid protein biomarkers of neural tube defects.
2. New serum and urine biomarkers of neural tube defects have been identified, and this SELDI mass spectrometry coupled with decision tree classification algorithm will provide a highly accurate and innovative approach for the early diagnosis of neural tube defects.
神经管缺陷(neural tube defects, NTDs)是常见的先天性中枢神经系统畸形。其发生机制是在胚胎生长发育的前四周内神经管闭合发生障碍,导致神经系统的各种畸形。包括无脑儿,脊柱裂,脑膜膨出,脊髓脊膜膨出,脑膨出,脑积水,脊髓积水空洞症等。神经管缺陷的发病率为,女性高于男性,农村高于城市,北方高于南方。我国神经管缺陷发生率约为10.63／万。神经管缺陷胎儿约54%在孕27周前自然流产,46%进入围产期。缺陷儿童的出生,不仅造成家庭与社会的沉重负担,而且严重影响人口素质。因此,除对致病因素预防外,产前诊断是目前极为重要而且有效的方法。目前神经管缺陷的产前筛查主要依靠超声影像学和孕母血清和羊水蛋白质标记物的检测。
产前超声检查已成为当前最常用的诊断胎儿形态异常的金标准。但做超声检查,胎龄必须达12周以上,并且对于腰骶部位病变、胎儿体位不理想、胎动活跃,孕妇肥胖等均容易漏诊。孕母血清甲胎蛋白和羊水甲胎蛋白检测是产前诊断的重要内容。孕母血清甲胎蛋白(maternal serum alpha-fetoprotein, MSAFP)和羊水甲胎蛋白(amniotic fluid alpha-fetoprotein, AFAFP)含量增高可以提示胎儿神经管缺陷。但多胎妊娠、胎儿腹壁缺损、先天性肾病、胎死宫内、胎儿血污染羊水等因素均可引起甲胎蛋白假阳性增高。而且羊膜腔穿刺取羊水、早孕绒毛组织检查和植入性产前遗传诊断均为侵入性诊断,可造成孕妇和胎儿的损伤、阴道出血、感染和流产,故其应用受到限制。
蛋白质是细胞代谢和调控途径的主要执行者,蛋白质组学是研究细胞内全部蛋白质的组成和变化的新学科,它对于疾病的早期诊断和发病机制都具有重要意义。研究不同时期细胞蛋白质组成的变化,发现有差异表达的蛋白质即“表达蛋白质组学”是现今应用最为广泛的蛋白质组学研究模式。在质谱分析基础上发展的表面增强激光解吸／离子化飞行时间质谱技术(surface enhanced laser desorption/ ionization time-of-flight mass spectrometry, SELDI-TOF-MS)对某些疾病,特别是肿瘤、遗传性疾病和中枢神经系统疾病的相关蛋白的识别上已经取得了突破性进展。探索神经管缺陷特异性标志蛋白,建立一套简单、快速、灵敏度高和特异性强的早期诊断技术已成为临床医学的迫切需要。本实验中我们采用SELDI技术,选取蛋白质芯片中的弱阳离子芯片改进型CM10芯片,筛选胎儿神经管缺陷的孕母血清、尿液、羊水和神经管缺陷胎鼠羊水蛋白质标志物,为提高神经管缺陷诊断效率奠定基础。本实验中所有临床标本均经过孕妇本人书面同意,并经过中国医科大学附属盛京医院医学伦理委员会批准同意。
材料与方法
一、实验对象
(一)胎儿神经管缺陷的孕母血清标本
经超声确诊为胎儿神经管缺陷的孕妇17例,孕周数相匹配的正常孕妇14例。神经管缺陷包括脊柱裂7例,无脑儿4例,脑积水6例。对照组孕妇为同期接受产前检查的受检者。所有孕妇均于清晨空腹取外周静脉血5ml,立即置于4℃,静置1-2h。再于4℃,4000 rpm,离心10min。吸取上清,按每管100μl分装,置于-80℃保存备用。
(二)胎儿神经管缺陷的孕母尿液标本
经超声确诊为神经管缺陷的孕妇20例,孕周数相匹配的正常孕妇15例。神经管缺陷包括脊柱裂10例,无脑儿5例,脑积水5例。对照组孕妇为同期接受产前检查的受检者。所有孕妇均取清晨空腹尿5ml,立即于4℃,2500rpm,离心min。吸取上清,按每管100μl分装,置于-80℃保存备用。
(三)胎儿神经管缺陷的孕母羊水标本
经超声确诊为神经管缺陷的孕妇11例,孕周数相匹配的正常孕妇9例。神经管缺陷包括脊柱裂5例,无脑儿5例,脑积水1例。对照组孕妇为同期接受产前检查的受检者。所有孕母均于引产前经腹抽取羊水5ml,立即于4℃,2500 rpm,离心5min。吸取上清,按每管100μl分装,置于-80℃保存备用。
(四)神经管缺陷胎鼠羊水标本
26只雌性Wistar大鼠(体重220-260g),分为畸形组(n=11)和对照组(n=15)。在标准条件下饲养,午夜雌：雄=4：1合笼。次日清晨8时阴道涂片,镜检精子,确定其妊娠日期,有精子者计为孕0日(E0)。在孕10日(E10)晨8时,畸形组雌鼠称体重,按120mg／Kg称取全反式维甲酸与矿物油混合均匀(维甲酸浓度为40mg／ml),经胃管一次注入孕鼠胃内。对照组仅将不含维甲酸的矿物油与畸形组同量经胃管一次注入。雌鼠于孕17天(E17),用10%水合氯醛按300mg／Kg进行腹腔注射麻醉。将孕鼠固定于操作台上,酒精消毒腹部,剪开腹部皮肤及肌肉,暴露子宫。在子宫外大体确定是否存在畸形。用2ml无菌注射器抽取胎鼠羊膜腔内羊水,每只胎鼠取出约0.1-0.3ml羊水,每只胎鼠羊水单独分装。选取羊水清亮者立即置于4℃保存。在立体显微镜下进一步确认胎鼠有无畸形和畸形类型。畸形组中胎鼠畸形分四种：①单纯性肛门闭锁畸形；②脊柱裂合并肛门闭锁畸形；③脊柱裂合并肛门闭锁和马蹄内翻足畸形；④给药后无畸形。选取脊柱裂合并肛门闭锁畸形组的胎鼠羊水作为研究对象。对照组胎鼠均为正常胎鼠。所有羊水立即于4℃,4000 rpm,离心10min。吸取上清,按每管100μl分装,置于-80℃保存备用。
二、蛋白质芯片类型
选用SELDI蛋白质芯片中CM10芯片,CM10芯片是弱阳离子亲和芯片WCX2芯片的改进型。具有变异系数小,重复性好,操作方便,结果更稳定等优点。购于美国Ciphergen公司。
三、主要试剂
TFA：三氟乙酸；NaAC:醋酸钠；DTT：二硫苏糖醇；CHAPS:3-[3-(胆酰胺基丙基)二甲氨基]丙磺酸盐；Urea:尿素；ACN：乙腈；SPA：饱和芥子酸。均为Sigma原装进口,购自SIGMA公司北京代理：北京舒伯伟化工仪器有限责任公司。
四、孕母血清(尿,羊水)和胎鼠羊水样品处理
于-80℃中取出孕母血清(尿,羊水)和胎鼠羊水样品,4℃融解。10,000rpm,4℃,离心2min。取10μl血清(尿,羊水)和胎鼠羊水样品用20μl U9缓冲液稀释,混匀,置于4℃变性。加入360μl(尿加250μl,孕母羊水和胎鼠羊水均加170μl)缓冲液,混匀,使血清(尿,孕母羊水和胎鼠羊水)总稀释倍数达到约39倍(尿为28倍,羊水为20倍)。上样和洗脱：在CM10芯片上每孔加入200μl结合缓冲液,震荡5min,甩掉缓冲液。重复上述操作一次。加入处理好的样品100μl,室温震荡60min,甩出样品。再次加入结合缓冲液200μl,室温震荡5min,甩去孔中液体。重复操作一次。加入超纯水200μl,立刻甩出。取出芯片,待自然风干后,加能量吸收分子饱和芥子酸SPA0.5μl二次。待干后,即可上机测定。
五、数据采集与分析
采用PBSIIC型蛋白质芯片阅读机读取数据。设定优化相对分子质量范围1000-30,000Da。每次实验数据收集前,用All-in-one蛋白质芯片校正仪器,使蛋白质分子量误差<0.1%。应用Biomarker Wizard(美国Ciphergen公司)软件分析处理所有峰谱,形成蛋白质指纹图谱。所有的图谱都进行标准化,定义蛋白峰信噪比(S／N)>5,变异系数CV＜10%。采用Mann-Whitney U检验比较配对样本的蛋白峰,计算P值。P<0.05有统计学意义。采用Ciphergen protein chip 3.1.1软件对数据进行统计分析。
实验结果
一、胎儿神经管缺陷的孕母血清标志蛋白质谱分析
在相对分子量1000-30,000Da范围内,共检测到55个血清差异蛋白峰,有统计学意义的差异蛋白峰有12个。病例组中有8种蛋白质高表达,相对分子质量分别为4105,4297,4188,6650,8583,3282,2750,3327；4种蛋白质低表达,相对分子质量分别为5497,28078,9155,9434。
二、血清蛋白质标志物决策分类树诊断模型的建立与结果分析
蛋白质指纹图谱软件(Biomarker Patterns Software, BPS)对经过Biomarker Wizard获得的血清蛋白质谱数据进行分析处理,并采用决策分类树分析方法。建树后,得到了带有3个终结点的决策分类树,获得了2个标志性蛋白质,其分子量分别为4105,7788。计算其各自的权重,变量重要性评分分别为100(4105),44.94(7788)。采用该分类树建立起来的神经管缺陷诊断模型的灵敏度为88.2%,特异度为100%。
三、胎儿神经管缺陷的孕母尿液蛋白质芯片检测结果
在相对分子量1000-30,000Da范围内,共检测到39个尿液差异蛋白峰,有统计学意义的差异蛋白峰有5个。神经管缺陷组尿液特异性蛋白标记物有5个。其中4种蛋白标记物高表达,相对分子质量分别为8320,8209,9099,10567。1种蛋白标记物低表达,相对分子质量为3458。
四、尿液蛋白质标志物决策分类树诊断模型的建立与结果分析
BPS软件对经过Biomarker Wizard获得的尿液蛋白质谱数据进行分析处理,建立决策分类树诊断模型。建树后,得到了带有3个终结点的决策分类树,获得了2个标志性蛋白质,其分子量分别为9096,8244。采用该分类树建立起来的神经管缺陷诊断模型,进行留一法交叉验证后,确定其灵敏度为80.0%,特异度为93.3%。
五、胎儿神经管缺陷孕母羊水蛋白质谱分析
在相对分子量1000-30,000Da范围内,共检测到35个羊水差异蛋白峰,有统计学意义的差异蛋白峰有7个。神经管缺陷组羊水中有6种蛋白质高表达,相对分子质量分别为14700,7995,15891,16027,13776,11040。1种蛋白质低表达,相对分子质量为23417。
六、神经管缺陷胎鼠羊水蛋白质谱分析
在相对分子量1000-30,000Da范围内,共检测到55个羊水差异蛋白峰,有统计学意义的差异蛋白峰有9个。脊柱裂合并肛门闭锁组胎鼠羊水中有5种蛋白质高表达,相对分子质量分别为11658,27387,7898,11603,13829。4种蛋白低表达,相对分子质量分别为5124,14702,5403,13626。
七、神经管缺陷胎儿和神经管缺陷胎鼠羊水蛋白质比较
神经管缺陷胎儿和神经管缺陷胎鼠羊水中共同蛋白质为：4138(4145),7947(7941),8588(8588),9385(9390),14702(14700)。其中14700(P=0.006)具有非常显著性差异,很可能是神经管缺陷胎儿和神经管缺陷胎鼠羊水共同蛋白质标志物。
结论
1、应用表面增强激光解吸／离子化飞行时间质谱技术筛查出胎儿神经管缺陷的孕母血清、尿液和羊水的差异蛋白峰,这些差异蛋白峰可能是胎儿神经管缺陷孕母血清、尿液和羊水的特异性蛋白质标志物。
2、应用胎儿神经管缺陷的孕母血清和尿液蛋白质标记物建立决策分类树诊断模型,对于神经管缺陷的诊断灵敏度分别为88.2%、80.0%,特异度分别为100%、93.3%。证明表面增强激光解吸／离子化飞行时间质谱技术对于诊断神经管缺陷是一项有效、快捷、灵敏度高、特异性强的临床诊断工具。
3、神经管缺陷胎儿和神经管缺陷胎鼠羊水共同蛋白质为：4138(4145),7947(7941),8588(8588),9385(9390),14702(14700)。其中14700(P=0.006)具有非常显著性差异,很可能是神经管缺陷胎儿和神经管缺陷胎鼠羊水共同蛋白质标志物。
Introduction
Neural tube defects (NTDs) are quite common congenital central nervous system abnormalities. Embryologically, failure in neural tube closure determines a group of diseases called neural tube defects, including anencephaly, spina bifida, meningocele, myelomeningocele, encephalocele, hydrencephaly, hydrosyringomyelia. Neural tube defects have been described in all popμlations in which they have been sought. Half of these defects are spina bifida and half are anencephaly with or without spina bifida. Historically, the birth prevalence of NTDs has ranged from about 0.5 to 6 in 1,000 births. Both environmental and genetic causes may be the reason of neural tube defects. Prevalence of neural tube defects is about 10.63 in 10,000 births, female is superior to male, countryside is superior to city. Abortion will occur in 54%of neural tube defects before twenty seven pregnancy weeks, and 46%of neural tube defects will entry in perinatal period. Newborns with neural tube defects will be a serious burden to their families and decrease the population quality.
At present, prenatal diagnosis may be the most important screening method. Maternal serum alpha-fetoprotein (MSAFP) and amniotic fluid alpha fetoprotein (AFAFP) screening and ultrasonography have been used for detecting neural tube defects prenatally. The improved resolution of ultrasonography has allowed detailed imaging of nervous system anatomy and enhanced understanding of both development and pathology. Prenatal screening in the general population is based on two complementary methods, maternal serum AFP screening and ultrasound screening. It is necessary for ultrasonography that gestation age must excess to 12 weeks in pregnancy, and many factors will result in the missed diagnosis of ultrasonography. Prenatal diagnosis in pregnancies identified as being at a high risk of open neural tube defects requires fetal scanning by an expert sonographer. MSAFP and AFAFP levels will be abnormally high in the open neural tube defects and can be used as screening tests. However, both specificities are not good and such screenings are inadvisable. Amniocentesis for acetylcholinesterase electrophoresis is an invasive method and should be limited.
The surface enhanced laser desorption/ionization flight-of-time mass spectrometry (SELDI-TOF-MS) technology, developed from the technology of chromatography and mass spectrometry (MS), includes a protein capture chip. The specific protein can be captured on the chip surface. SELDI-TOF-MS offers the advantages of rapid and simple examination as well as high specificity and sensitivity. It analyses small volumes of clinical samples without destroying the proteins to be detected and is capable of examining proteins and peptides, which are not available for conventional methods. New proteins specific to some diseases and characterization of these proteins can be discovered and captured by comparative analysis of the mass spectra of the samples from patients and normal controls. Thus, it is suitable for examination of small volumes of samples such as serum, urine, amniotic fluid with complicated components, and an ideal method to find protein biomarkers. At present, there are many exciting SELDI-TOF-MS applications, which have been described by numerous laboratories, especially in studying cancers of various organs, including prostate, ovary, breast, lung, colon, and others. To our knowledge, there has been no study reported using SELDI-TOF-MS technology to investigate neural tube defects. In this study, the serum, urine, amniotic fluid proteins of the patients and rat with neural tube defects and those of normal controls were analysed. SELDI-TOF-MS (Ciphergen Biosystems, USA) was used to detect specific protein biomarkers in serum, urine, amniotic fluid and to obtain diagnostic fingerprints which, coupled with the dicision tree analysis patterns for detection of serum and urine proteins, would give an early diagnosis of neural tube defects.
Material and methods
1. Collection and preparation of samples
(1) serum samples
Of the 31 serum samples obtained,17 were from patients with neural tube defects and 14 from healthy volunteers undergoing pregnancy routineμltrasonography examination in the Department of ultrasound, Shengjing Hospital, China Medical University. The diagnosis of the neural tube defects was confirmed routine ultrasonography examination. All fasting blood were obtained early in the morning. Untreated whole blood were collected and allowed to clot 1-2hrs at room temperature. Serum was purified from blood by centrifugation for 10 minutes (4000rpm) at 4℃, aliquoted as 100 microliters and stored at-80℃. Serum samples were not subjected to more than two freeze-thaw cycles before the assay.
(2) urine samples
Of the 35 urine samples obtained,20 were from patients with neural tube defects and 15 from healthy volunteers undergoing routine ultrasonography examination in the Department of ultrasound, Shengjing Hospital, China Medical University. The diagnosis of the neural tube defects was confirmed routine ultrasonography examination. All fasting urine were obtained early in the morning. Urine were collected and centrifugated for 5 minutes (2500 rpm) at 4℃immediately after collection, aliquoted as 100 microliters, and stored at-80℃until analysis. Urine samples were not subjected to more than two freeze-thaw cycles before the assay.
(3) amniotic fluid samples of fetal neural tube defects
Of the 20 amniotic fluid samples obtained,11 were from patients with neural tube defects and 9 from healthy volunteers undergoing routine ultrasonography examination in the Department of ultrasound, Shengjing Hospital, China Medical University. The diagnosis of the neural tube defects was confirmed routine ultrasonography examination. AF was retrieved by transabdominal amniocentesis. Centrifugation were performed immediately after amniocentesis as part of the clinical workup. Specimen was centrifuged at 2500rpm and 4℃for 5 min, aliquoted as 100 microliters, and stored at -80℃until analysis.
The Ethics Boards of China Medical University approved this research study. Written informed consent was obtained from all participants prior to the procedure. Subjects were enrolled prospectively based on the availability of one of the investigators for consent procedures.
(4) amniotic fluid samples of fetal rat neural tube defects
Timed-mated (GD 0 assigned as the day of mating) female Wistar rats were acquired from medicine animal center of China Medical University. Rats were healthy and mature and ranged between 220-250g at the initiation of dosing. The rats were housed individually in cages. Certified rodent diet and drinking water were provided ad lib. Animals were randomly assigned to experiment groups and control groups. Environmental conditions were set to maintain room temperature and humidity for rats. Room lighting was on a 12-hr light/dark cycle. The facility is accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International. Pregnant Wistar rats were administered with a suspension of all-trans retinoic acid (120 mg/kg) and liquid paraffin (40 mg/ml) on gestational days 10 and control group were studied. Amniotic fluid of fetal rat on gestational days 17 were aspirated by a needle. The deformities of fetal rats were identified by microscopy. Tha rats with spina bifida and anal atresia were chosen as experiment objects. The amniotic fluid must not be muddy, and amniotic fluid was immediately centrifuged at 4000rpm and 4℃for 10 minitus, aliquoted as 100 microliters, and stored at-80℃until analysis.
2. Samples preparation
The serum samples (urine, amniotic fluid) from the patients and rats with neural tube defects were collected prior to the start of treatment. All samples were thawed at room temperature and then centrifugated for 2 minutes (10,000 rpm) at 4℃. Ten microlitres of supernatant were first put into 20μl of protein denaturant (9 mol/L urea, 2%CHAPS,1%DTT,50 mmoL/L Tris-HCL, pH 9.0) and shaken at 4℃for 30 minutes on a shaker for complete protein denaturing. Then,30 microlitres of denatured sample was further diluted with 50 mmol/L sodium ethanoate (acetate, pH 4.0)to 390μl (urine to 280μl, amniotic fluid to 200μl)
3. Reagents and instruments
Sodium ethanoate (acetate), carbamide, acetonitrile, trifluoroethanoic acid and SPA(sinapinic acid)were purchased from Sigma(USA). Protein chip biosystem(PBSⅡC) and CM 10 chip were purchased from Ciphergen Biosystems (USA)
4. samples preparation
A protein chip was installed into a bioprocessor (Ciphergen, USA). Two hundred microlitres of binding buffer (50 mmol/L sodium ethanoate, pH 4.0) were added into each spot of an eight spot chip, and shaken for 5 minutes on a shaker. The shaking was repeated in the same way after the binding buffer was removed. One hundred microlitres of sample were added and shaken for 60 minutes. After the serum sample (urine sample, amniotic fluid sample) was thrown off, the chip was washed two times with binding buffer for 5 minutes each time, rinsed once with ultrapure water and airdried. The proteins bound CM 10 chip was then treated with 1μl of saturated sinapinic acid solution(Ciphergen,USA). The chip was airdried for future examination.
5. collection and preparation fo data
A mass spectrometer was calibrated with chips that had been bound with all-in-one standard proteins to set up parameters. The parameters used were:the optimal detection mass/charge size (m/z) range was between 1000 and 30,000Da; the laser intensity was set at 225 and the detector sensitivity was set at 9. An average value of 130 spots was presented for each sample. All samples were detected with the same parameters. All the raw data were normalized with the ProteinChip Software version 3.1.1. The peaks m/z of the samples with more than 1000 Da were normalized with biomark wizard of ProteinChip Software version 3.1.1 for noise filtering. The first threshold for noise filtering was set at 5. Generation of the tree analysis pattern was performed by Biomarker Patterns Software (Ciphergen Biosystems, Inc.). The data of spectra were analyzed by bioinformatics tools-Biomarker Wizard and Biomarker Pattern Software.
6. statistical analysis of the data
The data were processed with the ProteinChip Software version 3.1.1 for Mann-Whitney U test. P value< 0.05 was considered statistically significant.
Results
1.maternal serum protein biomarkers
A total of 55 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set. Compared with the spectra of control groups, there were 12 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 8 of which (4105,4297,4188,6650,8583,3282,2750, 3327) and low in the 4 of which(5497,28078,9155,9434). The softwares Biomarker Wizard and Biomarker Pattern Software automatically, under given conditions, selected 2 biomarker proteins (4105,7788) to be used to establish a three layer decision tree differentiate to diagnose neural tube defects and differentiate neural tube defects from control groups with a specificity of 100%and a sensitivity of 88.2%.
2.maternal urine protein biomarkers
A total of 39 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set between 1000 and 30,000Da. Compared with the spectra of control groups, there were 5 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 4 of which (8320,8209,9099,10567) and low in the 1 of which (3458). The softwares Biomarker wizard and Biomarker Pattern Software automatically, under given conditions, selected 2 biomarker (9096,8244) proteins to be used to establish a three layer decision tree with three terminal nodes differentiate to diagnose neural tube defects and differentiate neural tube defects from control groups with a specificity of 93.3% and a sensitivity of 80.0%.
3.maternal amniotic fluid protein biomarkers
A total of 35 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set between 1000 and 30,000Da. Compared with the spectra of control groups, there were 7 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 6 of which (14700,7995,15891,16027,13776, 11040) and low in the 1 of which (23417)
4.rat amniotic fluid protein biomarkers
A total of 55 qualified mass peaks (signal-to-noise ratio> 5) were detected in the training set between 1000 and 30,000Da. Compared with the spectra of control groups, there were 9 potential markers detected in the spectra of the neural tube defects patients, the protein expression was high in 5 of which (11658,27387,7898,11603,13829) and low in the 4 of which (5124,14702,5403,13626)
5.comparation between maternal amniotic fluid protein biomarkers and rat amniotic fluid protein biomarkers
Compared between maternal amniotic fluid protein biomarkers and rat amniotic fluid protein biomarkers, five mass peaks, including 4138 (4145),7947 (7941), 8588 (8588),9385 (9390),14702 (14700),especially m/z 14700 (P=0.006) may be the same protein/peptide of them.
Conclusion
1. These discrepancy mass peaks of serum, urine and amniotic fluid identified by SELD-TOF-MS (surface enhanced laser desorption/ionization time-of-flight mass spectrometry) may be the specific serum, urine and amniotic fluid protein biomarkers of neural tube defects.
2. New serum and urine biomarkers of neural tube defects have been identified, and this SELDI mass spectrometry coupled with decision tree classification algorithm will provide a highly accurate and innovative approach for the early diagnosis of neural tube defects.
引文
1 Xiao KZ, Zhang ZY, Su YM, et al. Central nervous system congenital malformations, especially neural tube defects in 29 provinces, metropolitan cities and autonomous regions of China. Int J Epidemiol.1990; 19:978-982.
2 叶荣伟,李松,郑俊池,等.中国30个县(市)1993-2000年神经管畸形在出生人群中的患病率及变动趋势分析.北京大学学报(医学版).2002；34(3)：204-209.
3 Rosano A, Smithells D, Cacciani L, et al. Time trends in neural tube defects prevalence in relation to preventive strategies:an international study. J Epidemiol Community Health.1999; 53(10):630.
4 Cuckle HS. Prenatal screening and diagnosis of neural tube defects in England and Wales in 1985. Prenat Diagn.1989; 9(6):393.
5 Azam AZ, Vial Y, Fawer CL, et al. Prenatal diagnosis of congenital cytomegalovirus infection. Obstetrics Gynecology.2001; 97 (3):443-448.
6 American college of obstetricians and gynecologists, committee on obstetric practice. Guidelines for diagnostic imaging during pregnancy. ACOG Comm Opin.1995; 158:1.
7 U. K. Collaborative Study:Maternal serum-alpha-fetoprotein measurement in antenatal screening for anencephaly and spina bifida in early pregnancy. Report of U. K. collaborative study on alpha-fetoprotein in relation to neural-tube defects.Lancet.1977; 1:1323.
8 鲍培忠,吴亚农,顾青,等.孕妇血清标记物用于严重胎儿缺陷的产前筛查.中华妇产科杂志.1997；32(11)：649-651.
9 Onda T, Tanaka T, Yoshida K,et al. Triple marker screening for trisomy 21,trisomy 18 and open neural tube defects in singleton pregnancies of native Japanese pregnant women. J Obstet Gynaecol Res.2000; 26 (6):441-447.
10 Muller F. Prenatal biochemical screening for neural tube defects. Childs Nerv Syst.2003; 19(7-8):433-435.
11 Clinical management guidelines for obstetricians-gynecologists. Neural tube defects. ACOG Practice Bulletin No.44. (Replaces Committee Opinion Number 252, March 2001). Obstet Gynecol.2003; 102:203-213.
12 Clinical management guidelines for obstetricians-gynecologists. Ultrasonography in pregnancy. ACOG Practice Bulletin No.58. American College of Obstetricians and Gynecologists. Obstet Gynecol.2004; 104:1449-1458.
13 Palomaki GE, Williams JR., Haddow JE. Prenatal screening for open neural-tube defects in Maine. N Engl J Med.1999; 340:1049-1050.
14 Lennon CA, Gray DL. Sensitivity and specificity of ultrasound for the detection of neural tube and ventral wall defects in a high-risk population. Obstet Gynecol.1999; 94:562-566.
15 Platt LD, Feuchtbaum L, Filly R,et al. The California Maternal Serum alpha-Fetoprotein Screening Program:the role of ultrasonography in the detection of spina bifida. Am J Obstet Gynecol.1992;166:1328-1329.
16 Summers AM, Farrell SA, Huang T, et al. Maternal serum screening in Ontario using the triple marker test. J Med Screen.2003;10:107-111.
17 Burton BK. Elevated maternal serum alpha-fetoprotein (MSAFP):interpretation and follow-up. Clin Obstet Gynecol.1988;31:293-305.
18 Burton BK, Sowers SG, Nelson LH. Maternal serum alphafetoprotein screening in North Carolina:experience with more than twelve thousand pregnancies. Am J Obstet Gynecol.1983; 146:439-444.
19 Velie EM, Shaw GM. Impact of prenatal diagnosis and elective termination on prevalence and risk estimates of neural tube defects in California,1989-1991. Am J Epidemiol. 1996;144:473-479.
20 Nicolaides KH, Campbell S, Gabbe SG, et al. Ultrasound screening for spina bifida:cranial and cerebellar signs. Lancet.1986;2:72-74.
21 Norem CT, Schoen EJ, Walton DL,et al. Routine ultrasonography compared with maternal serum alpha-fetoprotein for neural tube defect screening. Obstet Gynecol. 2005;106(4):747-752.
22 Cunningham GC, Tompkinison DG. Cost and effectiveness of the California triple marker prenatal screening program. Genet Med.1999;1:199-206.
23 Wald NJ, Cuckle H, Brock JH,et al. Maternal serum-alpha-fetoprotein measurement in
antenatal screening for anencephaly and spina bifida in early pregnancy. Report of U.K. collaborative study on alpha-fetoprotein in relation to neural-tube defects. Lancet.1977;1:1323-1332.
24 Cohen FL. Neural tube defects:epidemiology, detection, and prevention. J Obstet Gynecol Neonatal Nurs.1987;16:105-115.
25 Widlund KF, Gottvall T. Routine assessment of amniotic fluid alpha-Fetoprotein in early second-trimester amniocentesis is no longer justified. Acta Obstet Gynecol Scand. 2007;86(2):167-171.
26 Dashe JS, Twickler DM, Santos-Ramos R. et al. Alpha-fetoprotein detection of neural tube defects and the impact of standard ultrasound. Am J Obstet Gynecol. 2006;195(6):1623-1628.
27 Merchant M, Weinberger SR. Recent advancements in surface-enhanced laser desorption/ ionization-time of flight-mass spectrometry. Electrophoresis.2000; 21:1164-1177.
28 Petricoin EF, Ardenkani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet.2002;359:572-577.
29 Li J, Zhang Z, Rosenzweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem.2002; 48(8):1396-1304.
30 Grazyna Kwapiszewska, Markus Meyer, Ralf Bogumil, et al. Identification of proteins in laser-microdissected small cell numbers by SELDI-TOF and Tandem MS. BMC Biotechnol.2004;3(3):1472-1482.
31 孙念古.产前诊断相关问题及讨论.第三届全国产前诊断会议.2001；10.
32 Onda T, Tanaka T, Yoshida K, et al. Triple marker screening for trisomy 21,trisomy 18 and open neural tube defects in singleton pregnancies of native Japanese pregnant women. J Obstet Gynaecol Res.2000; 26 (6):441-447.
33 郑明明,胡娅莉.神经管缺陷及其病因学研究.国外医学妇幼保健分册.2003；5：282-284.
34 尤胜,罗淄资.神经管缺陷的病因、预防与产前控制.医学与哲学(临床决策论坛版).2007；28(3)：13-15.
35 Fields S. Proteomics in genomeland. Science.2001; 291:1221-1224.
36 Pandey A, Mann M. Proteomics to study genes and genomes.Nature.2000; 405:837-846.
37 Spahr,C.S., Davis,M.T., McGinley,M.D.,et al. Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry. I. Profiling an unfractionated tryptic digest. Proteomics.2001; 1:93-107.
38 Pang,J.X., Ginanni,N.,Dongre,A.R.,et al. Biomarker discovery in urine by proteomics. J. Proteome Res.2002; 1:161-169.
39 Thongboonkerd,V., McLeish,K.R., Arthur, J. M.,et al. Proteomic analysis of normal human urinary proteins isolated by acetone precipitation or ultracentrifugation. Kidney Int.2002; 62:1461-1469.
40 Pieper,R., Gatlin,C.L., McGrath,A.M.,et al. Characterization of the human urinary proteome: a method for high-resolution display of urinary proteins on two-dimensional electrophoresis gels with a yield of nearly 1400 distinct protein spots. Proteomics.2004; 4:1159-1174.
41 Pisitkun,T., Shen,R.F., Knepper,M.A. Identification and proteomic profiling of exosomes in human urine. Proc. Natl. Acad. Sci.U. S. A..2004; 101:13368-13373.
42 Oh,J., Pyo,J.H., Jo,E.H.,et al. Establishment of a near-standard two-dimensional human urine proteomic map. Proteomics.2004; 4:3485-3497.
43 Smith,G., Barratt,D., Rowlinson,R.,et al. Development of a high-throughput method for preparing human urine for two-dimensional electrophoresis. Proteomics.2005; 5:2315-2318.
44 Sun,W., Li,F., Wu,S., et al. Human urine proteome analysis by three separation approaches. Proteomics.2005; 5:4994-5001.
45 Castagna,A., Cecconi,D., Sennels,L.,et al. Exploring the hidden human urinary proteome via ligand library beads. J. Proteome Res.2005; 4:1917-1930.
46 Jurgens,M., Appel,A., Heine,G.,et al. Towards characterization of the human urinary peptidome. Comb. Chem. High Throughput Screen.2005; 8:757-765.
47 Wang,L., Li,F., Sun,W., et al. Concanavalin A-captured glycoproteins in healthy human urine. Mol. Cell. Proteomics.2006; 5:560-562.
48 Pisitkun T, Johnstone R, Knepper MA. Discovery of urinary biomarkers. Mol Cell Proteomics. 2006; 5(10):1760-1771.
49 O'riordan E, Orlova TN, Podust VN, et al. Characterization of Urinary Peptide Biomarkers of Acute Rejection in Renal Allografts. Am J Transplant.2007; 27.
50 Jahnukainen T, Malehorn D, Sun M,et al. Proteomic analysis of urine in kidney transplant patients with BK virus nephropathy. J Am Soc Nephrol.2006; 17(11):3248-3256.
51 Clarke W. Proteomic research in renal transplantation. Ther Drug Monit.2006; 28(1):19-22.
52 Clarke W, Silverman BC, Zhang Z, et al. Characterization of renal allograft rejection by urinary proteomic analysis. Ann Surg.2003; 237(5):660-664.discussion 664-665.
53 Munro NP, Cairns DA, Clarke P,et al. Urinary biomarker profiling in transitional cell carcinoma. Int J Cancer.2006,119(11):2642-2650.
54 Ord JJ, Streeter E, Jones A,et al. Phase I trial of intravesical Suramin in recurrent superficial transitional cell bladder carcinoma. Br J Cancer.2005; 92(12):2140-2147.
55 Liu W, Guan M, Wu D, et al. Using tree analysis pattern and SELDI-TOF-MS to discriminate transitional cell carcinoma of the bladder cancer from noncancer patients. Eur Urol.2005; 47(4):456-462.
56 Zhang YF, Wu DL, Guan M,et al. Tree analysis of mass spectral urine profiles discriminates transitional cell carcinoma of the bladder from noncancer patient. Clin Biochem.2004; 37(9):772-779.
57 Khurana M, Traum AZ, Aivado M, et al. Urine proteomic profiling of pediatric nephrotic syndrome. Pediatr Nephrol.2006; 21(9):1257-1265.
58 Woroniecki RP, Orlova TN, Mendelev N,et al. Urinary proteome of steroid-sensitive and steroid-resistant idiopathic nephrotic syndrome of childhood. Am J Nephrol.2006; 26(3):258-267.
59 Otu HH, Can H, Spentzos D, et al. Prediction of diabetic nephropathy using urine proteomic profiling 10 years prior to development of nephropathy. Diabetes Care.2007; 30(3):638-643.
60 Mosley K, Tam FW, Edwards RJ, et al. Urinary proteomic profiles distinguish between active and inactive lupus nephritis. Rheumatology (Oxford).2006; 45(12):1497-1504.
61 Nguyen MT, Ross GF, Dent CL, et al. Early prediction of acute renal injury using urinary proteomics. Am J Nephrol.2005;25(4):318-326.
62 Wu DL, Wang WJ, Guan M, et al. Screening urine markers of renal cell carcinoma using SELDI-TOF-MS. Zhonghua Yi Xue Za Zhi.2004; 84(13):1092-1095.
63 Cadieux PA, Beiko DT, Watterson JD,et al. Surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS):a new proteomic urinary test for patients with urolithiasis. J Clin Lab Anal.2004; 18(3):170-175.
64 Kooper AJ, de Bruijn D, van Ravenwaaij-Arts CM, et al. Fetal anomaly scan potentially will replace routine AFAFP assays for the detection of neural tube defects. Prenat Diagn.2007; 27(1):29-33.
65 Tsangaris GT, Karamessinis P, Kolialexi A,et al. Proteomic analysis of amniotic fluid in pregnancies with Down syndrome. Proteomics.2006; 6(15):4410-4419.
66 Vuadens F, Benay C, Crettaz D,et al. Identification of biologic markers of the premature rupture of fetal membranes:proteomic approach. Proteomics.2003; 3(8):1521-1525.
67 Thadikkaran L, Crettaz D, Siegenthaler MA,et al. The role of proteomics in the assessment of premature rupture of fetal membranes. Clin Chim Acta.2005; 360(1-2):27-36.
68 Buhimschi IA, Zhao G, Pettker CM, et al. The receptor for advanced glycation end products (RAGE) system in women with intraamniotic infection and inflammation. Am J Obstet Gynecol.2007; 196(2):181.e1-181.el3.
69 Buhimschi CS, Bhandari V, Hamar BD, et al. Proteomic Profiling of the Amniotic Fluid to Detect Inflammation, Infection, and Neonatal Sepsis. PLoS Med.2007; 4(1):e18,0084-0094.
70 Ruetschi U, Rosen A, Karlsson G, et al. Proteomic analysis using protein chips to detect biomarkers in cervical and amniotic fluid in women with intra-amniotic inflammation. J Proteome Res.2005; 4(6):2236-2242.
71 Klein LL, Freitag BC, Gibbs RS, et al. Detection of intra-amniotic infection in a rabbit model by proteomics-based amniotic fluid analysis. Am J Obstet Gynecol.2005; 193(4):1302-1306.
72 Buhimschi IA, Buhimschi CS, Weiner CP,et al. Proteomic but not enzyme-linked immunosorbent assay technology detects amniotic fluid monomeric calgranulins from their complexed calprotectin form. Clin Diagn Lab Immunol.2005; 12(7):837-844.
73 Buhimschi IA, Christner R, Buhimschi CS. Proteomic biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation. BJOG.2005; 112(2):173-181.
74 Muller F. Prenatal biochemical screening for neural tube defects. Childs Nerv Syst.2003; 19(7-8):433-435.
1 Wu W, Hu W, Kavanagh JJ. Proteomics in cancer research. Int Gyncol Cancer.2002;12(5):409-423.
2 Merchant M, Weinberger SR. Recent advancements in surface enhanced laser desorption ionization time of flight mass spectrometry. Electrophoresis.2000;21 (6):1164-1177.
3 Grazyna Kwapiszewska, Markus Meyer, Ralf Bogumil, et al. Identification of proteins in laser-microdissected small cell numbers by SELDI-TOF and Tandem MS. BMC Biotechnol.2004;3(3):1472-1482.
4 Fink L, Kohlhoff S, Stein MM, et al. cDNA array hybridization after laser-assisted microdissection from nonneoplastic tissue. Am J Pat hol.2002;160(1):81-90.
5 Steve RB, Mahfuz BK, Michael DP, et al. SELDI-TOF-MS analysis of transcriptional activation protein binding to response elements regulating carcinogenesis enzymes. Int J Mol Sci.2002;3 (3):1027-1038.
6 Petricoin EF, Ardenkani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet.2002;359:572-577.
7 Li J, Zhang Z, Rosenzweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem.2002;48(8):1396-1304.
8 王家祥,陈新让,张蛟,等.肾母细胞瘤血清蛋白质标记物检测与分期模型构建研究.中华小儿外科杂志.2007;28(2)：90-94.
9 王家祥,张蛟,刘秋亮,等.基于正常向量机对肾母细胞瘤患者血清蛋白质标记物的检测分析.中华医学杂志.2006;86(42)：2982-2985.
10 de Bont JM, den Boer ML, Reddingius RE, et al. Identification of apolipoprotein A-II in cerebrospinal fluid of pediatric brain tumor patients by protein expression profiling. Clin Chem.2006;52(8):1501-1509.
11 Li Y, Dang TA, Shen J, et al. Identification of a plasma proteomic signature to distinguish pediatric osteosarcoma from benign osteochondroma. Proteomics.2006;6(11):3426-3435.
12 He QY, Zhu R, Ren Y,et al. Serological protein profiling of neuroblastoma by ProteinChip SELDI-TOF technology. J Cell Biochem.2005;95(1):165-172.
13 Lauten M, Schrauder A, Kardinal C, et al. Unsupervised proteome analysis of human leukaemia cells identifies the Valosin-containing protein as a putative marker for glucocorticoid resistance. Leukemia.2006;20(5):820-826.
14 张军,王惠芳,张建中,等.蛋白质芯片筛选儿童急性淋巴细胞白血病血清标志蛋白质的临床研究.北京医学.2007;29(5)：290-292.
15 Izbicka E, Campos D, Marty J, et al. Molecular determinants of differential sensitivity to docetaxel and paclitaxel in human pediatric cancer models. Anticancer Res.2006;26(3A):1983-1988.
16 Khurana M, Traum AZ, Aivado M, et al. Urine proteomic profiling of pediatric nephrotic syndrome. Pediatr Nephrol.2006;21(9):1257-1265.
17 Woroniecki RP, Orlova TN, Mendelev N,et al. Urinary proteome of steroid-sensitive and steroid-resistant idiopathic nephrotic syndrome of childhood. Am J Nephrol.2006;26(3):258-267.
18 Suzuki M, Ross GF, Wiers K, et al. Identification of a urinary proteomic signature for lupus nephritis in children. Pediatr Nephrol.2007;22(12):2047-2057.
19 王家祥,秦攀,刘秋亮,等.先天性巨结肠血清蛋白质标记物检测.中华小儿外科杂志.2007;28(1)：14-17.
20 McMorran BJ, Patat SA, Carlin JB, et al. Novel neutrophil-derived proteins in bronchoalveolar lavage fluid indicate an exaggerated inflammatory response in pediatric cystic fibrosis patients. Clin Chem.2007;53(10):1782-1791.
21 Shah ZA, Jortani SA, Tauman R, et al. Serum proteomic patterns associated with sleep-disordered breathing in children. Pediatr Res.2006;59(3):466-470.
22 Miyamae T, Malehorn DE, Lemster B, et al. Serum protein profile in systemic-onset juvenile idiopathic arthritis differentiates response versus nonresponse to therapy. Arthritis Res Ther.2005;7(4):R746-55.
23 Dammann CE, Meyer M, Dammann O,et al. Protein detection in dried blood by surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS). Biol Neonate.2006;89(2):126-132.
24 Stears RL, Martirsky T, Schena M. Trends in microarrary analysis. Nat Med.2003;9 (1): 140-145.
25 童荔,汪理,周绍棠,等.采用SELDI技术检测肾移植患者尿液蛋白质指纹图谱诊断慢性移植肾肾病.中华器官移植杂志.2007;28(4)：242-244.
2 叶荣伟,李松,郑俊池,等.中国30个县(市)1993-2000年神经管畸形在出生人群中的患病率及变动趋势分析.北京大学学报(医学版).2002；34(3)：204-209.
3 Rosano A, Smithells D, Cacciani L, et al. Time trends in neural tube defects prevalence in relation to preventive strategies:an international study. J Epidemiol Community Health.1999; 53(10):630.
4 Cuckle HS. Prenatal screening and diagnosis of neural tube defects in England and Wales in 1985. Prenat Diagn.1989; 9(6):393.
5 Azam AZ, Vial Y, Fawer CL, et al. Prenatal diagnosis of congenital cytomegalovirus infection. Obstetrics Gynecology.2001; 97 (3):443-448.
6 American college of obstetricians and gynecologists, committee on obstetric practice. Guidelines for diagnostic imaging during pregnancy. ACOG Comm Opin.1995; 158:1.
7 U. K. Collaborative Study:Maternal serum-alpha-fetoprotein measurement in antenatal screening for anencephaly and spina bifida in early pregnancy. Report of U. K. collaborative study on alpha-fetoprotein in relation to neural-tube defects.Lancet.1977; 1:1323.
8 鲍培忠,吴亚农,顾青,等.孕妇血清标记物用于严重胎儿缺陷的产前筛查.中华妇产科杂志.1997；32(11)：649-651.
9 Onda T, Tanaka T, Yoshida K,et al. Triple marker screening for trisomy 21,trisomy 18 and open neural tube defects in singleton pregnancies of native Japanese pregnant women. J Obstet Gynaecol Res.2000; 26 (6):441-447.
10 Muller F. Prenatal biochemical screening for neural tube defects. Childs Nerv Syst.2003; 19(7-8):433-435.
11 Clinical management guidelines for obstetricians-gynecologists. Neural tube defects. ACOG Practice Bulletin No.44. (Replaces Committee Opinion Number 252, March 2001). Obstet Gynecol.2003; 102:203-213.
12 Clinical management guidelines for obstetricians-gynecologists. Ultrasonography in pregnancy. ACOG Practice Bulletin No.58. American College of Obstetricians and Gynecologists. Obstet Gynecol.2004; 104:1449-1458.
13 Palomaki GE, Williams JR., Haddow JE. Prenatal screening for open neural-tube defects in Maine. N Engl J Med.1999; 340:1049-1050.
14 Lennon CA, Gray DL. Sensitivity and specificity of ultrasound for the detection of neural tube and ventral wall defects in a high-risk population. Obstet Gynecol.1999; 94:562-566.
15 Platt LD, Feuchtbaum L, Filly R,et al. The California Maternal Serum alpha-Fetoprotein Screening Program:the role of ultrasonography in the detection of spina bifida. Am J Obstet Gynecol.1992;166:1328-1329.
16 Summers AM, Farrell SA, Huang T, et al. Maternal serum screening in Ontario using the triple marker test. J Med Screen.2003;10:107-111.
17 Burton BK. Elevated maternal serum alpha-fetoprotein (MSAFP):interpretation and follow-up. Clin Obstet Gynecol.1988;31:293-305.
18 Burton BK, Sowers SG, Nelson LH. Maternal serum alphafetoprotein screening in North Carolina:experience with more than twelve thousand pregnancies. Am J Obstet Gynecol.1983; 146:439-444.
19 Velie EM, Shaw GM. Impact of prenatal diagnosis and elective termination on prevalence and risk estimates of neural tube defects in California,1989-1991. Am J Epidemiol. 1996;144:473-479.
20 Nicolaides KH, Campbell S, Gabbe SG, et al. Ultrasound screening for spina bifida:cranial and cerebellar signs. Lancet.1986;2:72-74.
21 Norem CT, Schoen EJ, Walton DL,et al. Routine ultrasonography compared with maternal serum alpha-fetoprotein for neural tube defect screening. Obstet Gynecol. 2005;106(4):747-752.
22 Cunningham GC, Tompkinison DG. Cost and effectiveness of the California triple marker prenatal screening program. Genet Med.1999;1:199-206.
23 Wald NJ, Cuckle H, Brock JH,et al. Maternal serum-alpha-fetoprotein measurement in
antenatal screening for anencephaly and spina bifida in early pregnancy. Report of U.K. collaborative study on alpha-fetoprotein in relation to neural-tube defects. Lancet.1977;1:1323-1332.
24 Cohen FL. Neural tube defects:epidemiology, detection, and prevention. J Obstet Gynecol Neonatal Nurs.1987;16:105-115.
25 Widlund KF, Gottvall T. Routine assessment of amniotic fluid alpha-Fetoprotein in early second-trimester amniocentesis is no longer justified. Acta Obstet Gynecol Scand. 2007;86(2):167-171.
26 Dashe JS, Twickler DM, Santos-Ramos R. et al. Alpha-fetoprotein detection of neural tube defects and the impact of standard ultrasound. Am J Obstet Gynecol. 2006;195(6):1623-1628.
27 Merchant M, Weinberger SR. Recent advancements in surface-enhanced laser desorption/ ionization-time of flight-mass spectrometry. Electrophoresis.2000; 21:1164-1177.
28 Petricoin EF, Ardenkani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet.2002;359:572-577.
29 Li J, Zhang Z, Rosenzweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem.2002; 48(8):1396-1304.
30 Grazyna Kwapiszewska, Markus Meyer, Ralf Bogumil, et al. Identification of proteins in laser-microdissected small cell numbers by SELDI-TOF and Tandem MS. BMC Biotechnol.2004;3(3):1472-1482.
31 孙念古.产前诊断相关问题及讨论.第三届全国产前诊断会议.2001；10.
32 Onda T, Tanaka T, Yoshida K, et al. Triple marker screening for trisomy 21,trisomy 18 and open neural tube defects in singleton pregnancies of native Japanese pregnant women. J Obstet Gynaecol Res.2000; 26 (6):441-447.
33 郑明明,胡娅莉.神经管缺陷及其病因学研究.国外医学妇幼保健分册.2003；5：282-284.
34 尤胜,罗淄资.神经管缺陷的病因、预防与产前控制.医学与哲学(临床决策论坛版).2007；28(3)：13-15.
35 Fields S. Proteomics in genomeland. Science.2001; 291:1221-1224.
36 Pandey A, Mann M. Proteomics to study genes and genomes.Nature.2000; 405:837-846.
37 Spahr,C.S., Davis,M.T., McGinley,M.D.,et al. Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry. I. Profiling an unfractionated tryptic digest. Proteomics.2001; 1:93-107.
38 Pang,J.X., Ginanni,N.,Dongre,A.R.,et al. Biomarker discovery in urine by proteomics. J. Proteome Res.2002; 1:161-169.
39 Thongboonkerd,V., McLeish,K.R., Arthur, J. M.,et al. Proteomic analysis of normal human urinary proteins isolated by acetone precipitation or ultracentrifugation. Kidney Int.2002; 62:1461-1469.
40 Pieper,R., Gatlin,C.L., McGrath,A.M.,et al. Characterization of the human urinary proteome: a method for high-resolution display of urinary proteins on two-dimensional electrophoresis gels with a yield of nearly 1400 distinct protein spots. Proteomics.2004; 4:1159-1174.
41 Pisitkun,T., Shen,R.F., Knepper,M.A. Identification and proteomic profiling of exosomes in human urine. Proc. Natl. Acad. Sci.U. S. A..2004; 101:13368-13373.
42 Oh,J., Pyo,J.H., Jo,E.H.,et al. Establishment of a near-standard two-dimensional human urine proteomic map. Proteomics.2004; 4:3485-3497.
43 Smith,G., Barratt,D., Rowlinson,R.,et al. Development of a high-throughput method for preparing human urine for two-dimensional electrophoresis. Proteomics.2005; 5:2315-2318.
44 Sun,W., Li,F., Wu,S., et al. Human urine proteome analysis by three separation approaches. Proteomics.2005; 5:4994-5001.
45 Castagna,A., Cecconi,D., Sennels,L.,et al. Exploring the hidden human urinary proteome via ligand library beads. J. Proteome Res.2005; 4:1917-1930.
46 Jurgens,M., Appel,A., Heine,G.,et al. Towards characterization of the human urinary peptidome. Comb. Chem. High Throughput Screen.2005; 8:757-765.
47 Wang,L., Li,F., Sun,W., et al. Concanavalin A-captured glycoproteins in healthy human urine. Mol. Cell. Proteomics.2006; 5:560-562.
48 Pisitkun T, Johnstone R, Knepper MA. Discovery of urinary biomarkers. Mol Cell Proteomics. 2006; 5(10):1760-1771.
49 O'riordan E, Orlova TN, Podust VN, et al. Characterization of Urinary Peptide Biomarkers of Acute Rejection in Renal Allografts. Am J Transplant.2007; 27.
50 Jahnukainen T, Malehorn D, Sun M,et al. Proteomic analysis of urine in kidney transplant patients with BK virus nephropathy. J Am Soc Nephrol.2006; 17(11):3248-3256.
51 Clarke W. Proteomic research in renal transplantation. Ther Drug Monit.2006; 28(1):19-22.
52 Clarke W, Silverman BC, Zhang Z, et al. Characterization of renal allograft rejection by urinary proteomic analysis. Ann Surg.2003; 237(5):660-664.discussion 664-665.
53 Munro NP, Cairns DA, Clarke P,et al. Urinary biomarker profiling in transitional cell carcinoma. Int J Cancer.2006,119(11):2642-2650.
54 Ord JJ, Streeter E, Jones A,et al. Phase I trial of intravesical Suramin in recurrent superficial transitional cell bladder carcinoma. Br J Cancer.2005; 92(12):2140-2147.
55 Liu W, Guan M, Wu D, et al. Using tree analysis pattern and SELDI-TOF-MS to discriminate transitional cell carcinoma of the bladder cancer from noncancer patients. Eur Urol.2005; 47(4):456-462.
56 Zhang YF, Wu DL, Guan M,et al. Tree analysis of mass spectral urine profiles discriminates transitional cell carcinoma of the bladder from noncancer patient. Clin Biochem.2004; 37(9):772-779.
57 Khurana M, Traum AZ, Aivado M, et al. Urine proteomic profiling of pediatric nephrotic syndrome. Pediatr Nephrol.2006; 21(9):1257-1265.
58 Woroniecki RP, Orlova TN, Mendelev N,et al. Urinary proteome of steroid-sensitive and steroid-resistant idiopathic nephrotic syndrome of childhood. Am J Nephrol.2006; 26(3):258-267.
59 Otu HH, Can H, Spentzos D, et al. Prediction of diabetic nephropathy using urine proteomic profiling 10 years prior to development of nephropathy. Diabetes Care.2007; 30(3):638-643.
60 Mosley K, Tam FW, Edwards RJ, et al. Urinary proteomic profiles distinguish between active and inactive lupus nephritis. Rheumatology (Oxford).2006; 45(12):1497-1504.
61 Nguyen MT, Ross GF, Dent CL, et al. Early prediction of acute renal injury using urinary proteomics. Am J Nephrol.2005;25(4):318-326.
62 Wu DL, Wang WJ, Guan M, et al. Screening urine markers of renal cell carcinoma using SELDI-TOF-MS. Zhonghua Yi Xue Za Zhi.2004; 84(13):1092-1095.
63 Cadieux PA, Beiko DT, Watterson JD,et al. Surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS):a new proteomic urinary test for patients with urolithiasis. J Clin Lab Anal.2004; 18(3):170-175.
64 Kooper AJ, de Bruijn D, van Ravenwaaij-Arts CM, et al. Fetal anomaly scan potentially will replace routine AFAFP assays for the detection of neural tube defects. Prenat Diagn.2007; 27(1):29-33.
65 Tsangaris GT, Karamessinis P, Kolialexi A,et al. Proteomic analysis of amniotic fluid in pregnancies with Down syndrome. Proteomics.2006; 6(15):4410-4419.
66 Vuadens F, Benay C, Crettaz D,et al. Identification of biologic markers of the premature rupture of fetal membranes:proteomic approach. Proteomics.2003; 3(8):1521-1525.
67 Thadikkaran L, Crettaz D, Siegenthaler MA,et al. The role of proteomics in the assessment of premature rupture of fetal membranes. Clin Chim Acta.2005; 360(1-2):27-36.
68 Buhimschi IA, Zhao G, Pettker CM, et al. The receptor for advanced glycation end products (RAGE) system in women with intraamniotic infection and inflammation. Am J Obstet Gynecol.2007; 196(2):181.e1-181.el3.
69 Buhimschi CS, Bhandari V, Hamar BD, et al. Proteomic Profiling of the Amniotic Fluid to Detect Inflammation, Infection, and Neonatal Sepsis. PLoS Med.2007; 4(1):e18,0084-0094.
70 Ruetschi U, Rosen A, Karlsson G, et al. Proteomic analysis using protein chips to detect biomarkers in cervical and amniotic fluid in women with intra-amniotic inflammation. J Proteome Res.2005; 4(6):2236-2242.
71 Klein LL, Freitag BC, Gibbs RS, et al. Detection of intra-amniotic infection in a rabbit model by proteomics-based amniotic fluid analysis. Am J Obstet Gynecol.2005; 193(4):1302-1306.
72 Buhimschi IA, Buhimschi CS, Weiner CP,et al. Proteomic but not enzyme-linked immunosorbent assay technology detects amniotic fluid monomeric calgranulins from their complexed calprotectin form. Clin Diagn Lab Immunol.2005; 12(7):837-844.
73 Buhimschi IA, Christner R, Buhimschi CS. Proteomic biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation. BJOG.2005; 112(2):173-181.
74 Muller F. Prenatal biochemical screening for neural tube defects. Childs Nerv Syst.2003; 19(7-8):433-435.
1 Wu W, Hu W, Kavanagh JJ. Proteomics in cancer research. Int Gyncol Cancer.2002;12(5):409-423.
2 Merchant M, Weinberger SR. Recent advancements in surface enhanced laser desorption ionization time of flight mass spectrometry. Electrophoresis.2000;21 (6):1164-1177.
3 Grazyna Kwapiszewska, Markus Meyer, Ralf Bogumil, et al. Identification of proteins in laser-microdissected small cell numbers by SELDI-TOF and Tandem MS. BMC Biotechnol.2004;3(3):1472-1482.
4 Fink L, Kohlhoff S, Stein MM, et al. cDNA array hybridization after laser-assisted microdissection from nonneoplastic tissue. Am J Pat hol.2002;160(1):81-90.
5 Steve RB, Mahfuz BK, Michael DP, et al. SELDI-TOF-MS analysis of transcriptional activation protein binding to response elements regulating carcinogenesis enzymes. Int J Mol Sci.2002;3 (3):1027-1038.
6 Petricoin EF, Ardenkani AM, Hitt BA, et al. Use of proteomic patterns in serum to identify ovarian cancer. Lancet.2002;359:572-577.
7 Li J, Zhang Z, Rosenzweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem.2002;48(8):1396-1304.
8 王家祥,陈新让,张蛟,等.肾母细胞瘤血清蛋白质标记物检测与分期模型构建研究.中华小儿外科杂志.2007;28(2)：90-94.
9 王家祥,张蛟,刘秋亮,等.基于正常向量机对肾母细胞瘤患者血清蛋白质标记物的检测分析.中华医学杂志.2006;86(42)：2982-2985.
10 de Bont JM, den Boer ML, Reddingius RE, et al. Identification of apolipoprotein A-II in cerebrospinal fluid of pediatric brain tumor patients by protein expression profiling. Clin Chem.2006;52(8):1501-1509.
11 Li Y, Dang TA, Shen J, et al. Identification of a plasma proteomic signature to distinguish pediatric osteosarcoma from benign osteochondroma. Proteomics.2006;6(11):3426-3435.
12 He QY, Zhu R, Ren Y,et al. Serological protein profiling of neuroblastoma by ProteinChip SELDI-TOF technology. J Cell Biochem.2005;95(1):165-172.
13 Lauten M, Schrauder A, Kardinal C, et al. Unsupervised proteome analysis of human leukaemia cells identifies the Valosin-containing protein as a putative marker for glucocorticoid resistance. Leukemia.2006;20(5):820-826.
14 张军,王惠芳,张建中,等.蛋白质芯片筛选儿童急性淋巴细胞白血病血清标志蛋白质的临床研究.北京医学.2007;29(5)：290-292.
15 Izbicka E, Campos D, Marty J, et al. Molecular determinants of differential sensitivity to docetaxel and paclitaxel in human pediatric cancer models. Anticancer Res.2006;26(3A):1983-1988.
16 Khurana M, Traum AZ, Aivado M, et al. Urine proteomic profiling of pediatric nephrotic syndrome. Pediatr Nephrol.2006;21(9):1257-1265.
17 Woroniecki RP, Orlova TN, Mendelev N,et al. Urinary proteome of steroid-sensitive and steroid-resistant idiopathic nephrotic syndrome of childhood. Am J Nephrol.2006;26(3):258-267.
18 Suzuki M, Ross GF, Wiers K, et al. Identification of a urinary proteomic signature for lupus nephritis in children. Pediatr Nephrol.2007;22(12):2047-2057.
19 王家祥,秦攀,刘秋亮,等.先天性巨结肠血清蛋白质标记物检测.中华小儿外科杂志.2007;28(1)：14-17.
20 McMorran BJ, Patat SA, Carlin JB, et al. Novel neutrophil-derived proteins in bronchoalveolar lavage fluid indicate an exaggerated inflammatory response in pediatric cystic fibrosis patients. Clin Chem.2007;53(10):1782-1791.
21 Shah ZA, Jortani SA, Tauman R, et al. Serum proteomic patterns associated with sleep-disordered breathing in children. Pediatr Res.2006;59(3):466-470.
22 Miyamae T, Malehorn DE, Lemster B, et al. Serum protein profile in systemic-onset juvenile idiopathic arthritis differentiates response versus nonresponse to therapy. Arthritis Res Ther.2005;7(4):R746-55.
23 Dammann CE, Meyer M, Dammann O,et al. Protein detection in dried blood by surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS). Biol Neonate.2006;89(2):126-132.
24 Stears RL, Martirsky T, Schena M. Trends in microarrary analysis. Nat Med.2003;9 (1): 140-145.
25 童荔,汪理,周绍棠,等.采用SELDI技术检测肾移植患者尿液蛋白质指纹图谱诊断慢性移植肾肾病.中华器官移植杂志.2007;28(4)：242-244.
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