2型糖尿病肾病尿液蛋白组学研究及早期诊断标志物的筛选
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摘要
糖尿病肾病(Diabetic Nephropathy,DN)是2型糖尿病患者(Type 2diabetes mellitus,T2DM)最常见、最严重的慢性并发症,发病率逐年升高,已成为危害人类健康的重大疾病。在欧美国家DN也是终未期肾病(End-stage renaldisease,ESRD)的最常见病因,约占全部ESRD病例的44%。早期诊断DN并延缓其发展越来越受到人们的重视,但DN起病隐袭,目前临床上早期诊断DN存在较大困难。肾穿刺活检术创伤大,并发症多,而且费用较高,患者难以接受,不能作为T2DM患者检查的常规项目,而尿液富含肾脏病变信息,取材简单、无创伤,可重复取样,所以在DN早期诊断方面,对尿液的分析一直备受关注。目前临床上普遍采用尿微量白蛋白(Microalbuminuria,MALB)作为DN早期诊断指标,但已有许多研究发现MALB诊断DN的准确性和特异性不高,它受多种因素的影响,比如泌尿系统的炎症、出血,都会有血浆白蛋白的渗出或漏出,使尿白蛋白排出量增加,且在MALB出现时,DN已发展到第Ⅲ期,因而只依靠监测MALB并不能及时准确地对DN做出诊断,会带来较高的误诊和漏诊。随着蛋白质组学技术的发展,将其与体液技术相结合的尿液蛋白质组学技术为DN早期诊断标志物的筛选提供了技术支持,利用尿液蛋白质组学技术可能发现一些新的DN早期诊断标志物。本研究通过普通双向凝胶电泳(Two dimensionalgel electrophoresis,2-DE)和荧光差异双向凝胶电泳(Two dimensionalfluorescence difference gel electrophoresis,2D-DIGE)技术对T2DM合并微量蛋白尿、大量蛋白尿、正常蛋白尿的患者,以及健康志愿者的尿液标本进行比较蛋白组学分析,筛选DN患者尿液中的差异表达蛋白,对差异蛋白进行质谱鉴定和生物信息学分析,并挑选出两种感兴趣的差异蛋白进行深入研究,评价其与2型糖尿病肾病的关系以及早期诊断糖尿病肾病的价值,本课题研究内容共分为以下五部分。
第一部分2型糖尿病肾病患者尿液2-DE图谱的建立及差异蛋白的筛选
目的建立T2DM合并正常蛋白尿组(无肾病期)、微量蛋白尿组(DN早期)、大量蛋白尿组(DN临床期)以及正常对照组的尿液双向凝胶电泳(2-DE)图谱及相关技术,并分析比较四组尿液2-DE图谱的差异,筛选出在2型糖尿病肾病患者差异表达的蛋白点。
方法收集8例T2DM合并大量蛋白尿患者(UAER＞300mg/24h,DN2组),8例T2DM合并微量蛋白尿患者(30＜UAER＜300mg/24h,DN1组),8例T2DM合并正常蛋白尿患者(UAER＜30mg/24h,DM组),以及8例年龄、性别相匹配的健康志愿者(control组)的晨起清洁中段尿。所有尿液样本经透析除盐后采用冷丙酮沉淀法获取尿蛋白,以固相IPG pH梯度等电聚焦为第一向,SDS均一胶的垂直电泳为第二向,银染后用PDQuest软件配比分析,筛选差异表达蛋白点。
结果成功获得不同时期2型糖尿病。肾病患者的尿液蛋白2-DE图谱。PDQuest软件对四组图像进行统计分析,发现DN2组凝胶的平均蛋白质点数为217±42,DN1组凝胶的平均蛋白质点数为178±36,DM组凝胶的平均蛋白质点数为135±31,control组凝胶的平均蛋白质点数为98±27((?)±s),经四组图像的定量、对比分析,在DN组寻找到16个差异蛋白点(ratio＞2.0,p＜0.01),其中9个在DN组出现上调,7个出现下调。
结论对不同时期2型糖尿病肾病患者的尿液进行2-DE分析是可行的,可以获得清晰的DN患者尿液2-DE图谱,并筛选到多个差异蛋白点。
第二部分2型糖尿病肾病患者尿液2D-DIGE图谱的建立及差异蛋白的筛选
目的为了弥补2-DE技术重复性较差的缺陷,提高本研究的准确度、可信度。本实验同时采用了荧光差异双向凝胶电泳(2D-DIGE)技术对2型糖尿病合并正常蛋白尿组、微量蛋白尿组、大量蛋白尿组以及健康对照组的尿液样本进行分析,构建不同时期DN患者尿液的2D-DIGE图谱,并通过软件比较分析,筛选出在2型DN患者尿液中差异表达的蛋白点。
方法收集T2DM合并正常蛋白尿(DM)、微量蛋白尿(DN1)、大量蛋白尿(DN2)以及健康对照组(Control)的尿液标本各8例(同第一部分),将各组尿样等量混合成四份样本。经透析除盐后采用冷丙酮沉淀法获取尿液总蛋白,对制备好的四份尿蛋白样本用荧光材料Cy3或Cy5分别进行标记,同时设立内标用Cy2标记。然后以固相IPG pH梯度等电聚焦为第一向,SDS均一胶的垂直电泳为第二向进行双向凝胶电泳,荧光扫描仪扫描凝胶,利用DeCyder软件对图像进行配比分析,筛选差异表达蛋白点。
结果成功获得不同时期2型糖尿病肾病患者的尿液2D-DIGE图谱。分别用不同波长激光对Cy2(488 nm)、Cy3(532nm)、Cy5(633nm)进行扫描,得到不同颜色的扫描图,经DeCyder软件对荧光图像进行分析,每张胶图得到大于400个蛋白质点。与内标配比分析后,共得到21个差异表达蛋白点(ratio＞2.0,p＜0.01),其中13个在DN组上调,8个下调。
结论对不同时期2型DN患者的混合尿液样本进行2D-DIGE的蛋白组学分析是准确可行的,与传统2-DE技术相比,不仅省时、省力,而且可以筛选到更多的差异蛋白点。
第三部分差异蛋白的质谱鉴定及生物信息学分析
目的对2-DE技术寻找到的的16个差异蛋白点,以及2D-DIGE技术寻找到的21个差异蛋白点行质谱鉴定,并对鉴定出的蛋白进行生物信息学初步分析。
方法首先将37个差异蛋白点自凝胶中切下后行胰酶酶解,在反射模式下进行基质辅助激光吸电离飞行时间质谱(MALDI-TOF-MS)分析,获得肽质量指纹图(PMF)。通过MASCOT软件进行肽段的鉴定,并将鉴定出的蛋白质输入Swiss-Prot或者TrEMBL数据库可以得到相关蛋白的基本生物信息学数据。
结果2-DE技术寻找到的16个差异蛋白点经质谱鉴定和数据分析,得到8种蛋白质,其中在DN组上调的蛋白质6个,分别是:上皮细胞钙粘蛋白(Epithelial-cadherin,E-cadherin),血清白蛋白(Serum albumin),锌-a2糖蛋白(Zinc-alpha-2-glycoprotein),a1-酸性糖蛋白(Orosomucoid),视黄醇结合蛋白(retinol-binding protein),激肽原(Kininogen)。在DN组下调的蛋白质2个,分别是:尿调节素(Uromodulin),转甲状腺素蛋白(Transthyretin)。2D-DIGE技术寻找到的21个差异蛋白点经质谱鉴定和数据分析,得到10个蛋白质,其中在DN组上调的蛋白质7个,分别是上皮细胞钙粘蛋白(Epithelial-cadherin,E-cadherin),血清白蛋白(Serum albumin),锌-a2糖蛋白(Zinc-alpha-2-glycoprotein),a1-酸性糖蛋白(Orosomucoid),视黄醇结合蛋白(Retinol-binding protein),前列腺素-H2D-异构酶(Prostaglandin-H2D-isomerase),免疫球蛋白κ链C区(Ig kappa chain Cregion);在DN组下调的蛋白质3个,分别是:AMBP蛋白(AMBP protein),尿调节素(Uromodulin),触珠蛋白(Haptoglobin)。在所有被鉴定出的蛋白中,有6种蛋白通过2-DE/MS和2D-DIGE/MS两种蛋白组学方法均被鉴定出来,分别是:上皮细胞钙粘蛋白,血清白蛋白,锌-a2糖蛋白,a1-酸性糖蛋白,视黄醇结合蛋白,尿调节素。
结论通过MALDI-TOF-MS质谱鉴定和生物信息学分析,可以准确的鉴定出在DN患者尿液中差异表达的蛋白质。这些差异蛋白的识别为DN早期诊断的研究提供了候选标志物,有助于DN早期诊断和发病机制的深入探索。
第四部分差异蛋白E-cadherin与2型糖尿病肾病的相关性研究
目的验证差异蛋白“上皮细胞钙粘蛋白(E-cadherin)”在T2DM合并微量蛋白尿、大量蛋白尿,正常蛋白尿患者,以及健康对照者尿液中的表达及浓度变化,分析其诊断DN的价值。检测E-cadherin在DN患者和正常人肾脏组织中的表达,了解其在DN发病机制中的作用。
方法用Western blot方法对24例T2DM合并微量蛋白尿(DN1)、大量蛋白尿(DN2),正常蛋白尿(DM),以及健康对照者(control)的尿液标本(各6例)进行分析,验证E-cadherin在尿液中的表达;另外收集160例T2DM合并微量蛋白尿、大量蛋白尿、正常蛋白尿,以及健康对照者的尿液标本(各40例),用ELISA方法检测尿液中E-cadherin的含量,分析E-cadherin在不同时期2型糖尿病肾病患者尿液中的变化情况,并初步计算尿E-cadherin诊断DN的准确性和特异性;收集5例诊断为DN的T2DM患者的肾活检标本,同时收集4例正常人的肾脏组织标本(肾移植供体肾的活检标本)作为对照。用免疫组化的方法检测E-cadherin在DN患者肾组织中的表达变化。
结果Western blot结果显示,在正常对照组的尿液中未检测到E-cadherin的表达,在DM、DN1、DN2组的尿液标本中均检测到了可溶性80KD片段的E-cadherin的表达(sE-cadherin),同时发现sE-cadherin在DN2组尿液标本中大量表达,在DN1组尿液标本中中量表达,在DM组尿液标本仅有微量表达。ELISA数据也显示了sE-cadherin在尿液中的水平随着DN的进展而逐渐升高。与DM或control组相比,尿sE-cadherin/Cr的水平在DN1、DN2组均显著升高(2751.5±164,5839.6±428 vs.721.9±93 or 652.7±87ug/g;p＜0.001),而且DN2组显著高于DN1组(5839.6±428 vs.2751.5±164ug/g;p＜0.01)。与control组相比,尿sE-cadherin/Cr在DM组的变化无统计学意义(721.9±93vs.652.7±87ug/g;p＞0.05)。经计算,尿sE-cadherin/Cr诊断DN的敏感性和特异性分别是:78.8%(95%CI,74-83%)和80%(95%CI,65-91%)。同时,Pearson相关分析和逐步回归分析也显示:尿sE-cadherin/Cr与尿白蛋白排泄率,以及血清肌酐呈显著正相关(r=0.861,r=0.713;p＜0.01),血清肌酐是尿sE-cadherin/Cr的独立影响因子(R~2=0.831,F=56.72;p＜0.01)。另外,我们的免疫组化的结果显示E-cadherin主要表达于肾小管上皮细胞的细胞膜和细胞浆,它在DN肾脏中的表达较正常肾脏显著降低。
结论尿sE-cadherin具有潜在的早期诊断DN的价值,它在2型DN患者尿液中的浓度显著升高,而且随着肾病的进展逐渐增加。另外,E-cadherin在DN患者肾脏中的表达显著减少,它可能参与DN的发生与发展。
第五部分差异蛋白orosomucoid与2型糖尿病肾病的相关性研究
目的分析差异蛋白“a1-酸性糖蛋白(orosomucoid)”在T2DM合并微量蛋白尿、大量蛋白尿、正常蛋白尿患者,以及健康人尿液中的浓度变化,评价尿orosomucoid的排泄率(UOER)与DN的关系,以及诊断DN的价值。
方法定时收集160例T2DM合并微量蛋白尿(DN1)、大量蛋白尿(DN2)、正常蛋白尿患者(DM),以及健康对照者的尿液标本(各40例,同第四部分)。用免疫比浊法检测所有尿液样本中orosomucoid的含量,计算其在尿液中的排泄率UOER,评价UOER在不同时期2型DN患者尿液中的变化。用Pearson相关分析和多元Logistic回归分析来评价UOER与DN的相关性,并计算UOER诊断DN的敏感性和特异性。
结果免疫比浊法的检测结果显示,与control组相比,UOER在DM、DN1、DN2组是增加的,而且逐渐升高(0.91±0.37,1.87±0.72,2.95±0.84 vs.0.42±0.19 ug/min;P＜0.05)。Pearson相关分析显示UOER和UAER、血清肌酐、C-反应蛋白密切相关(r=0.781,0.695,0.401,respectively;P＜0.05)。而且,多元Logistic回归分析显示升高的UOER是DN的独立危险因素(OR=2.88,P＜0.01)。另外,通过初步计算,UOER诊断DN的敏感性和特异性分别是:75.8%(95%CI,71-82%)和69%(95%CI,58-83%)。
结论UOER具有潜在的早期诊断DN的价值,它在DN发病早期就出现升高,并随着肾病的进展逐步升高。另外,升高的UOER也是DN的独立危险因素。
Diabetic nephropathy (DN) as a common and severe chronic complication of type 2 diabetes mellitus has rapidly become an important public health problem. In the western world, DN is now the single most common cause of ESRD, account for approximately 44% of all ESRD cases. Therefore, early detection of the risk of DN before advanced renal damage has occurred is an obviously important goal, this goal is made difficult by the fact that much of the important diabetic renal structural injury can occur in absolute clinical silence. Although analysis of kidney tissue may provide clues to determine which patients may progress to DN, current clinical practice does not allow for routine kidney biopsies because the procedure is invasive.
Urine can provides much information of kidney disease, and has been defined as a fluid biopsy of the kidney, so the research on urine has received much concern. At present, microalbuminuria is considered as the best noninvasive available marker for DN risk, but recent studies have proved it has inadequate specificity and sensitivity. Because many factors affect its accuracy, for example, when the inflammation and bleeding of urinary system happened, plasma albumin will leak out to the urine and lead to the increasing of microalbuminuria. Besides, when microalbuminuria occurs, DN has developed to the stage of III. Thus, only monitor microalbuminuria can't realize early diagnosis of DN, looking for a new diagnostic method is needed.
Recently, with the development of proteomics technology, the urinary proteomes has been demonstrated to identify novel proteins, or protein patterns, that may serve as biomarkers for DN. In the present study, we used urinary proteomic approach of two-dimensional gel electrophoresis (2-DE) and two dimensional fluorescence difference gel electrophoresis (2D-DIGE) to identify differentially expressed proteins in urine samples, which were from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and healthy control group. Then, the differentially expressed proteins were identified by MALDI-TOF mass spectra and analyzed by bioinformatics. At last, we performed further studies on partly identified proteins to evaluate their early diagnostic value of DN. The research contents were divided into five parts as below.
Part I : Analysis of 2-DE for the differentially expressed proteins in type 2 diabetic nephropathy
Objective To establish the two-dimensional gel electrophoresis (2-DE) profiles and explore the differentially expressed proteins among type 2 diabetes patients with normoalbuminuria (DM), microalbuminuria (early DN), macroalbuminuria (overt DN) and healthy controls.
Methods Urine samples were collected from type 2 diabetes patients with normoalbuminuria (UAER<30mg/24h, DM group), microalbuminuria (30300mg/24h, DN2 group) and control group (n=8 in each group). The urinary protein of all urine samples was isolated by cold acetone precipitation after dialysis. The rehydrated IPG strips containing protein samples were isoelectric focusing (IEF), after IEF, the equilibrated strips are transferred to the vertical SDS gel. After silver stained, the gel images were analyzed using the software PDQuest, then the differentially expressed protein spots were found.
Results Using the proper method stated above, satisfactory 2-DE maps of urinary protein was obtained and the preliminary analysis results were reported. After analysis by the PDQuest software, 217±42, 178±36, 135±31 and 98±27 (mean±SD) protein spots were visualized on each gel of DN2, DN1, DM and control group, respectively. By quantitative and statistical analysis among the proteomic maps from four groups, a total of 16 protein spots were markedly differentially expressed in DN group (abundance ratio>2, p<0.01). Among these 16 protein spots, 9 were up-regulated and 7 were down-regulated in DN group.
Conclusion Urinary proteomics method of 2-DE is feasible to be applied in the study of type 2 diabetes patients with nephropathy and without nephropathy. A few differentially expressed protein spots in type 2 diabetes patients with nephropathy can be found by 2-DE method.
Part II: Analysis of 2D-DIGE for the differentially expressed proteins in type 2 diabetic nephropathy
Objective To overcome the disadvantage of poor repeatability by ordinary 2-DE, we used another proteomic method, the two-dimensional fluorescence difference gel electrophoresis (2D-DIGE), to explore the differentially expressed proteins among type 2 diabetes patients with normoalbuminuria(DM), microalbuminuria (early DN), macroalbuminuria (overt DN) and healthy controls.
Methods Urine samples were collected from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and healthy control group (n=8 in each group, same with part I). The urine samples were mixed equally in each group, and then the urinary protein was isolated by cold acetone precipitation after dialysis. The prepared urine protein samples from four groups were labeled with Cy3 or Cy5 fluorescent dyes, and the internal standard (a pool of equal amounts from all samples) was labeled with Cy2. Then, isoelectric focusing (IEF) was performed in an Ettan IPGphor II apparatus with 24cm immobilized pH gradient (IPG) strips. After IEF, SDS-PAGE was run using an Ettan DALT twelve system. After scanning using Typhoon scanner, the gel images were analyzed statistically by DeCyder software to explore the differentially expressed protein spots in DN group.
Results We obtained the satisfactory 2-D DIGE maps of urinary protein from DN2, DN1, DM and healthy control groups. The different color scanning images can be seen after scanned for Cy2, Cy3 and Cy5 using different wavelength of laser 488 nm, 532nm and 633nm. After the analysis by the DeCyder software, more than 400 protein spots were visualized on each gel scanning image. By quantitative comparison with internal standard, a total of 21 protein spots were markedly differentially expressed in DN1 and DN2 groups (abundance ratio>2, p<0.01). Among these 21 protein spots, 13 were up-regulated and 8 were down-regulated in DN group.
Conclusion Urinary quantitative proteomics method of 2D-DIGE is feasible to be applied in the study of type 2 diabetes nephropathy. 2D-DIGE is more accurate and convenient than ordinary 2-DE method, and more differential protein spots can be obtained using 2D-DIGE method.
Part III: Mass spectrometry identification and basic bioinformatics analysis of the differentially expressed proteins
Objective To identify the differential expressed proteins based on mass spectrometer and bioinformatics analysis from 16 differential expressed protein spots selected by 2-DE technique and 21 protein spots selected by 2D-DIGE technique.
Methods A total of 37 differential expressed protein spots were cut out and subjected to enzymatic digestion with trypsin. Subsequent protein identification was carried out using matrix-assisted laser desorption/ionization-time of flight tandem mass spectrometry (MALDI-TOF-MS) on a reflective setting. The mass spectrometry data was then searched in comparison with the human subset of the Swiss-Prot/TrEMBL protein database using GPS explorer software with a MASCOT search engine.
Results After mass spectrometry identification and bioinformatics analysis, 8 proteins were identified from 16 differential expressed protein spots selected by 2-DE technique. Among them, 6 proteins were significantly up-regulated in DN groups, which were epithelial-cadherin, serum albumin, zinc-alpha-2 glycoprotein, orosomucoid, retinol-binding protein and kininogen. Another 2 proteins were significantly down-regulated in DN groups, which were uromodulin and transthyretin. Besides, 10 proteins were identified from 21 differential expressed protein spots selected by 2D-DIGE technique, including 7 proteins significantly up-regulated and 3 proteins down-regulated in DN group. The up-regulated protein were epithelial-cadherin, serum albumin, zinc-alpha-2-glycoprotein, orosomucoid, retinol-binding protein,prostaglandin-H2D-isomerase and Ig kappa chain C region. The down-regulated protein were AMBP protein, uromodulin and haptoglobin. It is noteworthy that there were 6 proteins identified by both 2-DE and 2D-DIGE technique, which were epithelial-cadherin, serum albumin, zinc-alpha-2 glycoprotein, orosomucoid, retinol-binding protein and uromodulin.
Conclusion The protein biomarkers associated with type 2 diabetic nephropathy could be identified by MALDI-TOF mass spectrometry and bioinformatics analysis. The research on differential proteins identification is helpful to the early diagnosis and pathogenic mechanism study of DN.
Part IV: The study on the relationship between E-cadherin and type 2 diabetic nephropathy
Objective To analyze the concentration changes of urinary E-cadherin in type 2 diabetic patients with nephropathy and without nephropathy, and evaluate its diagnostic value for diabetic nephropathy; To detect the expression of E-cadherin in renal tissue of type 2 diabetic nephropathy patients, and analyze its role in pathogenesis of diabetic nephropathy.
Methods Western blot method was performed to verify the expression of E-cadherin in urine samples, which were from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroal- buminuria (DN2 group) and control group (n=6 in each group). Meanwhile, the concentration of urinary E-cadherin was measured by ELISA detection in urine samples from DM, DN1, DN2 and control group (n=40 in each group). From this data, the sensitivity and specificity of urinary sE-cadherin for diagnosis of DN were calculated by formula. Besides, we performed immunohistochemical staining to analyze the expression of E-cadherin in human renal biopsies from type 2 diabetic nephropathy patients (n=5) and normal renal tissue (n=4).
Results The results of western blot demonstrated E-cadherin did not be detected in control group, but the soluble 80kDa fragment of E-cadherin (sE-cadherin) was detected in DM, DN1 and DN2 groups. Meanwhile, we found sE-cadherin was weakly expressed in DM group, but significantly expressed in DN1 and DN2 groups, especially in DN2 group. The ELISA data also demonstrated urinary sE-cadherin/Cr was markedly increased in DN1 and DN2 groups versus DM or control group (2751.5±164 and 5839.6±428 vs. 721.9±93 or 652.7±87 ug/g; p<0.001), and markedly elevated in DN2 group versus DN1 group (5839.6±428 vs. 2751.5±164 ug/g; p<0.01). But no significant difference of urinary sE-cadherin/Cr was found between DM group and control group (721.9±93 vs. 652.7±87 ug/g; p>0.05). The sensitivity and specificity of urinary sE-cadherin for diagnosis of DN were calculated as 78.8% (95%CI, 74-83%) and 80% (95%CI, 65-91%). Pearson correlation and stepwise regression analysis indicated urinary sE-cadherin/Cr was high positive correlation with UAER and serum creatinine (r=0.861, r=0.713; p<0.01), and serum creatinine was the only independent influential factor of urinary sE-cadherin/Cr (R~2=0.831, F=56.72; p<0.01). Besides, immunohistochemical stain showed E-cadherin was mainly expressed in membrane and cytoplasm of renal tubular epithelial cells, and its expression was markedly decreased in DN kidneys versus normal kidneys.
Conclusion Urinary sE-cadherin has a potential clinical diagnostic value for DN, which is elevated in DN patients, and gradually increased with the development of nephropathy. Besides, E-cadherin may participate in the pathogenesis of DN, whose expression was markedly decreased in kidneys of DN.
Part V: The study on the relationship between urinary orosomucoid and type 2 diabetic nephropathy
Objective To detect the concentration changes of urinary orosomucoid in type 2 diabetes patients with normoalbuminuria, microalbuminuria, macroalbuminuria and healthy control group; To analyze the relationship between urinary orosomucoid and type 2 diabetic nephropathy, and evaluate its diagnostic value for diabetic nephropathy.
Methods The urinary level of urinary orosomucoid was detected by immunoturbidimetry assay in urine samples, which were from 160 type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and healthy control group (n=40 in each group, the same with part IV). Then, we calculated the urinary orosomucoid excretion rate (UOER), to analyze the changes of UOER in different stages of DN. Besides, Pearson correlation analysis and multivariate logistic regression analysis were performed to evaluate the influencing factor of UOER. Meanwhile, the sensitivity and specificity of UOER for diagnosis of DN were calculated.
Results The data of immunoturbidimetry assay showed UOER was gradually increased in normo-, micro- and macroalbuminuria group versus control group (0.91±0.37, 1.87±0.72, 2.95±0.84 vs. 0.42±0.19 ug/min, P<0.05). The result indicated UOER increased in early stage of DN and gradually increased with the development of DN. Besides, Pearson correlation analysis indicated UOER was positively correlated with UAER, serum creatinine and CRP (r=0.781, 0.695, 0.401, respectively; P<0.05). And multivariate logistic regression analysis showed increased UOER was an independent risk factor for DN (OR=2.88, P<0.01). After the calculation by formula, the sensitivity and specificity of UOER for diagnosis of DN were 75.8% (95%CI, 71-82%) and 69% (95%CI, 58-83%).
Conclusion UOER is increased in early stage of type 2 diabetic nephropathy, and gradually increased with the development of nephropathy. Besides, increased UOER is an independent risk factor of DN, and it also has potential diagnostic value for DN.
第一部分2型糖尿病肾病患者尿液2-DE图谱的建立及差异蛋白的筛选
目的建立T2DM合并正常蛋白尿组(无肾病期)、微量蛋白尿组(DN早期)、大量蛋白尿组(DN临床期)以及正常对照组的尿液双向凝胶电泳(2-DE)图谱及相关技术,并分析比较四组尿液2-DE图谱的差异,筛选出在2型糖尿病肾病患者差异表达的蛋白点。
方法收集8例T2DM合并大量蛋白尿患者(UAER＞300mg/24h,DN2组),8例T2DM合并微量蛋白尿患者(30＜UAER＜300mg/24h,DN1组),8例T2DM合并正常蛋白尿患者(UAER＜30mg/24h,DM组),以及8例年龄、性别相匹配的健康志愿者(control组)的晨起清洁中段尿。所有尿液样本经透析除盐后采用冷丙酮沉淀法获取尿蛋白,以固相IPG pH梯度等电聚焦为第一向,SDS均一胶的垂直电泳为第二向,银染后用PDQuest软件配比分析,筛选差异表达蛋白点。
结果成功获得不同时期2型糖尿病。肾病患者的尿液蛋白2-DE图谱。PDQuest软件对四组图像进行统计分析,发现DN2组凝胶的平均蛋白质点数为217±42,DN1组凝胶的平均蛋白质点数为178±36,DM组凝胶的平均蛋白质点数为135±31,control组凝胶的平均蛋白质点数为98±27((?)±s),经四组图像的定量、对比分析,在DN组寻找到16个差异蛋白点(ratio＞2.0,p＜0.01),其中9个在DN组出现上调,7个出现下调。
结论对不同时期2型糖尿病肾病患者的尿液进行2-DE分析是可行的,可以获得清晰的DN患者尿液2-DE图谱,并筛选到多个差异蛋白点。
第二部分2型糖尿病肾病患者尿液2D-DIGE图谱的建立及差异蛋白的筛选
目的为了弥补2-DE技术重复性较差的缺陷,提高本研究的准确度、可信度。本实验同时采用了荧光差异双向凝胶电泳(2D-DIGE)技术对2型糖尿病合并正常蛋白尿组、微量蛋白尿组、大量蛋白尿组以及健康对照组的尿液样本进行分析,构建不同时期DN患者尿液的2D-DIGE图谱,并通过软件比较分析,筛选出在2型DN患者尿液中差异表达的蛋白点。
方法收集T2DM合并正常蛋白尿(DM)、微量蛋白尿(DN1)、大量蛋白尿(DN2)以及健康对照组(Control)的尿液标本各8例(同第一部分),将各组尿样等量混合成四份样本。经透析除盐后采用冷丙酮沉淀法获取尿液总蛋白,对制备好的四份尿蛋白样本用荧光材料Cy3或Cy5分别进行标记,同时设立内标用Cy2标记。然后以固相IPG pH梯度等电聚焦为第一向,SDS均一胶的垂直电泳为第二向进行双向凝胶电泳,荧光扫描仪扫描凝胶,利用DeCyder软件对图像进行配比分析,筛选差异表达蛋白点。
结果成功获得不同时期2型糖尿病肾病患者的尿液2D-DIGE图谱。分别用不同波长激光对Cy2(488 nm)、Cy3(532nm)、Cy5(633nm)进行扫描,得到不同颜色的扫描图,经DeCyder软件对荧光图像进行分析,每张胶图得到大于400个蛋白质点。与内标配比分析后,共得到21个差异表达蛋白点(ratio＞2.0,p＜0.01),其中13个在DN组上调,8个下调。
结论对不同时期2型DN患者的混合尿液样本进行2D-DIGE的蛋白组学分析是准确可行的,与传统2-DE技术相比,不仅省时、省力,而且可以筛选到更多的差异蛋白点。
第三部分差异蛋白的质谱鉴定及生物信息学分析
目的对2-DE技术寻找到的的16个差异蛋白点,以及2D-DIGE技术寻找到的21个差异蛋白点行质谱鉴定,并对鉴定出的蛋白进行生物信息学初步分析。
方法首先将37个差异蛋白点自凝胶中切下后行胰酶酶解,在反射模式下进行基质辅助激光吸电离飞行时间质谱(MALDI-TOF-MS)分析,获得肽质量指纹图(PMF)。通过MASCOT软件进行肽段的鉴定,并将鉴定出的蛋白质输入Swiss-Prot或者TrEMBL数据库可以得到相关蛋白的基本生物信息学数据。
结果2-DE技术寻找到的16个差异蛋白点经质谱鉴定和数据分析,得到8种蛋白质,其中在DN组上调的蛋白质6个,分别是:上皮细胞钙粘蛋白(Epithelial-cadherin,E-cadherin),血清白蛋白(Serum albumin),锌-a2糖蛋白(Zinc-alpha-2-glycoprotein),a1-酸性糖蛋白(Orosomucoid),视黄醇结合蛋白(retinol-binding protein),激肽原(Kininogen)。在DN组下调的蛋白质2个,分别是:尿调节素(Uromodulin),转甲状腺素蛋白(Transthyretin)。2D-DIGE技术寻找到的21个差异蛋白点经质谱鉴定和数据分析,得到10个蛋白质,其中在DN组上调的蛋白质7个,分别是上皮细胞钙粘蛋白(Epithelial-cadherin,E-cadherin),血清白蛋白(Serum albumin),锌-a2糖蛋白(Zinc-alpha-2-glycoprotein),a1-酸性糖蛋白(Orosomucoid),视黄醇结合蛋白(Retinol-binding protein),前列腺素-H2D-异构酶(Prostaglandin-H2D-isomerase),免疫球蛋白κ链C区(Ig kappa chain Cregion);在DN组下调的蛋白质3个,分别是:AMBP蛋白(AMBP protein),尿调节素(Uromodulin),触珠蛋白(Haptoglobin)。在所有被鉴定出的蛋白中,有6种蛋白通过2-DE/MS和2D-DIGE/MS两种蛋白组学方法均被鉴定出来,分别是:上皮细胞钙粘蛋白,血清白蛋白,锌-a2糖蛋白,a1-酸性糖蛋白,视黄醇结合蛋白,尿调节素。
结论通过MALDI-TOF-MS质谱鉴定和生物信息学分析,可以准确的鉴定出在DN患者尿液中差异表达的蛋白质。这些差异蛋白的识别为DN早期诊断的研究提供了候选标志物,有助于DN早期诊断和发病机制的深入探索。
第四部分差异蛋白E-cadherin与2型糖尿病肾病的相关性研究
目的验证差异蛋白“上皮细胞钙粘蛋白(E-cadherin)”在T2DM合并微量蛋白尿、大量蛋白尿,正常蛋白尿患者,以及健康对照者尿液中的表达及浓度变化,分析其诊断DN的价值。检测E-cadherin在DN患者和正常人肾脏组织中的表达,了解其在DN发病机制中的作用。
方法用Western blot方法对24例T2DM合并微量蛋白尿(DN1)、大量蛋白尿(DN2),正常蛋白尿(DM),以及健康对照者(control)的尿液标本(各6例)进行分析,验证E-cadherin在尿液中的表达;另外收集160例T2DM合并微量蛋白尿、大量蛋白尿、正常蛋白尿,以及健康对照者的尿液标本(各40例),用ELISA方法检测尿液中E-cadherin的含量,分析E-cadherin在不同时期2型糖尿病肾病患者尿液中的变化情况,并初步计算尿E-cadherin诊断DN的准确性和特异性;收集5例诊断为DN的T2DM患者的肾活检标本,同时收集4例正常人的肾脏组织标本(肾移植供体肾的活检标本)作为对照。用免疫组化的方法检测E-cadherin在DN患者肾组织中的表达变化。
结果Western blot结果显示,在正常对照组的尿液中未检测到E-cadherin的表达,在DM、DN1、DN2组的尿液标本中均检测到了可溶性80KD片段的E-cadherin的表达(sE-cadherin),同时发现sE-cadherin在DN2组尿液标本中大量表达,在DN1组尿液标本中中量表达,在DM组尿液标本仅有微量表达。ELISA数据也显示了sE-cadherin在尿液中的水平随着DN的进展而逐渐升高。与DM或control组相比,尿sE-cadherin/Cr的水平在DN1、DN2组均显著升高(2751.5±164,5839.6±428 vs.721.9±93 or 652.7±87ug/g;p＜0.001),而且DN2组显著高于DN1组(5839.6±428 vs.2751.5±164ug/g;p＜0.01)。与control组相比,尿sE-cadherin/Cr在DM组的变化无统计学意义(721.9±93vs.652.7±87ug/g;p＞0.05)。经计算,尿sE-cadherin/Cr诊断DN的敏感性和特异性分别是:78.8%(95%CI,74-83%)和80%(95%CI,65-91%)。同时,Pearson相关分析和逐步回归分析也显示:尿sE-cadherin/Cr与尿白蛋白排泄率,以及血清肌酐呈显著正相关(r=0.861,r=0.713;p＜0.01),血清肌酐是尿sE-cadherin/Cr的独立影响因子(R~2=0.831,F=56.72;p＜0.01)。另外,我们的免疫组化的结果显示E-cadherin主要表达于肾小管上皮细胞的细胞膜和细胞浆,它在DN肾脏中的表达较正常肾脏显著降低。
结论尿sE-cadherin具有潜在的早期诊断DN的价值,它在2型DN患者尿液中的浓度显著升高,而且随着肾病的进展逐渐增加。另外,E-cadherin在DN患者肾脏中的表达显著减少,它可能参与DN的发生与发展。
第五部分差异蛋白orosomucoid与2型糖尿病肾病的相关性研究
目的分析差异蛋白“a1-酸性糖蛋白(orosomucoid)”在T2DM合并微量蛋白尿、大量蛋白尿、正常蛋白尿患者,以及健康人尿液中的浓度变化,评价尿orosomucoid的排泄率(UOER)与DN的关系,以及诊断DN的价值。
方法定时收集160例T2DM合并微量蛋白尿(DN1)、大量蛋白尿(DN2)、正常蛋白尿患者(DM),以及健康对照者的尿液标本(各40例,同第四部分)。用免疫比浊法检测所有尿液样本中orosomucoid的含量,计算其在尿液中的排泄率UOER,评价UOER在不同时期2型DN患者尿液中的变化。用Pearson相关分析和多元Logistic回归分析来评价UOER与DN的相关性,并计算UOER诊断DN的敏感性和特异性。
结果免疫比浊法的检测结果显示,与control组相比,UOER在DM、DN1、DN2组是增加的,而且逐渐升高(0.91±0.37,1.87±0.72,2.95±0.84 vs.0.42±0.19 ug/min;P＜0.05)。Pearson相关分析显示UOER和UAER、血清肌酐、C-反应蛋白密切相关(r=0.781,0.695,0.401,respectively;P＜0.05)。而且,多元Logistic回归分析显示升高的UOER是DN的独立危险因素(OR=2.88,P＜0.01)。另外,通过初步计算,UOER诊断DN的敏感性和特异性分别是:75.8%(95%CI,71-82%)和69%(95%CI,58-83%)。
结论UOER具有潜在的早期诊断DN的价值,它在DN发病早期就出现升高,并随着肾病的进展逐步升高。另外,升高的UOER也是DN的独立危险因素。
Diabetic nephropathy (DN) as a common and severe chronic complication of type 2 diabetes mellitus has rapidly become an important public health problem. In the western world, DN is now the single most common cause of ESRD, account for approximately 44% of all ESRD cases. Therefore, early detection of the risk of DN before advanced renal damage has occurred is an obviously important goal, this goal is made difficult by the fact that much of the important diabetic renal structural injury can occur in absolute clinical silence. Although analysis of kidney tissue may provide clues to determine which patients may progress to DN, current clinical practice does not allow for routine kidney biopsies because the procedure is invasive.
Urine can provides much information of kidney disease, and has been defined as a fluid biopsy of the kidney, so the research on urine has received much concern. At present, microalbuminuria is considered as the best noninvasive available marker for DN risk, but recent studies have proved it has inadequate specificity and sensitivity. Because many factors affect its accuracy, for example, when the inflammation and bleeding of urinary system happened, plasma albumin will leak out to the urine and lead to the increasing of microalbuminuria. Besides, when microalbuminuria occurs, DN has developed to the stage of III. Thus, only monitor microalbuminuria can't realize early diagnosis of DN, looking for a new diagnostic method is needed.
Recently, with the development of proteomics technology, the urinary proteomes has been demonstrated to identify novel proteins, or protein patterns, that may serve as biomarkers for DN. In the present study, we used urinary proteomic approach of two-dimensional gel electrophoresis (2-DE) and two dimensional fluorescence difference gel electrophoresis (2D-DIGE) to identify differentially expressed proteins in urine samples, which were from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and healthy control group. Then, the differentially expressed proteins were identified by MALDI-TOF mass spectra and analyzed by bioinformatics. At last, we performed further studies on partly identified proteins to evaluate their early diagnostic value of DN. The research contents were divided into five parts as below.
Part I : Analysis of 2-DE for the differentially expressed proteins in type 2 diabetic nephropathy
Objective To establish the two-dimensional gel electrophoresis (2-DE) profiles and explore the differentially expressed proteins among type 2 diabetes patients with normoalbuminuria (DM), microalbuminuria (early DN), macroalbuminuria (overt DN) and healthy controls.
Methods Urine samples were collected from type 2 diabetes patients with normoalbuminuria (UAER<30mg/24h, DM group), microalbuminuria (30
Results Using the proper method stated above, satisfactory 2-DE maps of urinary protein was obtained and the preliminary analysis results were reported. After analysis by the PDQuest software, 217±42, 178±36, 135±31 and 98±27 (mean±SD) protein spots were visualized on each gel of DN2, DN1, DM and control group, respectively. By quantitative and statistical analysis among the proteomic maps from four groups, a total of 16 protein spots were markedly differentially expressed in DN group (abundance ratio>2, p<0.01). Among these 16 protein spots, 9 were up-regulated and 7 were down-regulated in DN group.
Conclusion Urinary proteomics method of 2-DE is feasible to be applied in the study of type 2 diabetes patients with nephropathy and without nephropathy. A few differentially expressed protein spots in type 2 diabetes patients with nephropathy can be found by 2-DE method.
Part II: Analysis of 2D-DIGE for the differentially expressed proteins in type 2 diabetic nephropathy
Objective To overcome the disadvantage of poor repeatability by ordinary 2-DE, we used another proteomic method, the two-dimensional fluorescence difference gel electrophoresis (2D-DIGE), to explore the differentially expressed proteins among type 2 diabetes patients with normoalbuminuria(DM), microalbuminuria (early DN), macroalbuminuria (overt DN) and healthy controls.
Methods Urine samples were collected from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and healthy control group (n=8 in each group, same with part I). The urine samples were mixed equally in each group, and then the urinary protein was isolated by cold acetone precipitation after dialysis. The prepared urine protein samples from four groups were labeled with Cy3 or Cy5 fluorescent dyes, and the internal standard (a pool of equal amounts from all samples) was labeled with Cy2. Then, isoelectric focusing (IEF) was performed in an Ettan IPGphor II apparatus with 24cm immobilized pH gradient (IPG) strips. After IEF, SDS-PAGE was run using an Ettan DALT twelve system. After scanning using Typhoon scanner, the gel images were analyzed statistically by DeCyder software to explore the differentially expressed protein spots in DN group.
Results We obtained the satisfactory 2-D DIGE maps of urinary protein from DN2, DN1, DM and healthy control groups. The different color scanning images can be seen after scanned for Cy2, Cy3 and Cy5 using different wavelength of laser 488 nm, 532nm and 633nm. After the analysis by the DeCyder software, more than 400 protein spots were visualized on each gel scanning image. By quantitative comparison with internal standard, a total of 21 protein spots were markedly differentially expressed in DN1 and DN2 groups (abundance ratio>2, p<0.01). Among these 21 protein spots, 13 were up-regulated and 8 were down-regulated in DN group.
Conclusion Urinary quantitative proteomics method of 2D-DIGE is feasible to be applied in the study of type 2 diabetes nephropathy. 2D-DIGE is more accurate and convenient than ordinary 2-DE method, and more differential protein spots can be obtained using 2D-DIGE method.
Part III: Mass spectrometry identification and basic bioinformatics analysis of the differentially expressed proteins
Objective To identify the differential expressed proteins based on mass spectrometer and bioinformatics analysis from 16 differential expressed protein spots selected by 2-DE technique and 21 protein spots selected by 2D-DIGE technique.
Methods A total of 37 differential expressed protein spots were cut out and subjected to enzymatic digestion with trypsin. Subsequent protein identification was carried out using matrix-assisted laser desorption/ionization-time of flight tandem mass spectrometry (MALDI-TOF-MS) on a reflective setting. The mass spectrometry data was then searched in comparison with the human subset of the Swiss-Prot/TrEMBL protein database using GPS explorer software with a MASCOT search engine.
Results After mass spectrometry identification and bioinformatics analysis, 8 proteins were identified from 16 differential expressed protein spots selected by 2-DE technique. Among them, 6 proteins were significantly up-regulated in DN groups, which were epithelial-cadherin, serum albumin, zinc-alpha-2 glycoprotein, orosomucoid, retinol-binding protein and kininogen. Another 2 proteins were significantly down-regulated in DN groups, which were uromodulin and transthyretin. Besides, 10 proteins were identified from 21 differential expressed protein spots selected by 2D-DIGE technique, including 7 proteins significantly up-regulated and 3 proteins down-regulated in DN group. The up-regulated protein were epithelial-cadherin, serum albumin, zinc-alpha-2-glycoprotein, orosomucoid, retinol-binding protein,prostaglandin-H2D-isomerase and Ig kappa chain C region. The down-regulated protein were AMBP protein, uromodulin and haptoglobin. It is noteworthy that there were 6 proteins identified by both 2-DE and 2D-DIGE technique, which were epithelial-cadherin, serum albumin, zinc-alpha-2 glycoprotein, orosomucoid, retinol-binding protein and uromodulin.
Conclusion The protein biomarkers associated with type 2 diabetic nephropathy could be identified by MALDI-TOF mass spectrometry and bioinformatics analysis. The research on differential proteins identification is helpful to the early diagnosis and pathogenic mechanism study of DN.
Part IV: The study on the relationship between E-cadherin and type 2 diabetic nephropathy
Objective To analyze the concentration changes of urinary E-cadherin in type 2 diabetic patients with nephropathy and without nephropathy, and evaluate its diagnostic value for diabetic nephropathy; To detect the expression of E-cadherin in renal tissue of type 2 diabetic nephropathy patients, and analyze its role in pathogenesis of diabetic nephropathy.
Methods Western blot method was performed to verify the expression of E-cadherin in urine samples, which were from type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroal- buminuria (DN2 group) and control group (n=6 in each group). Meanwhile, the concentration of urinary E-cadherin was measured by ELISA detection in urine samples from DM, DN1, DN2 and control group (n=40 in each group). From this data, the sensitivity and specificity of urinary sE-cadherin for diagnosis of DN were calculated by formula. Besides, we performed immunohistochemical staining to analyze the expression of E-cadherin in human renal biopsies from type 2 diabetic nephropathy patients (n=5) and normal renal tissue (n=4).
Results The results of western blot demonstrated E-cadherin did not be detected in control group, but the soluble 80kDa fragment of E-cadherin (sE-cadherin) was detected in DM, DN1 and DN2 groups. Meanwhile, we found sE-cadherin was weakly expressed in DM group, but significantly expressed in DN1 and DN2 groups, especially in DN2 group. The ELISA data also demonstrated urinary sE-cadherin/Cr was markedly increased in DN1 and DN2 groups versus DM or control group (2751.5±164 and 5839.6±428 vs. 721.9±93 or 652.7±87 ug/g; p<0.001), and markedly elevated in DN2 group versus DN1 group (5839.6±428 vs. 2751.5±164 ug/g; p<0.01). But no significant difference of urinary sE-cadherin/Cr was found between DM group and control group (721.9±93 vs. 652.7±87 ug/g; p>0.05). The sensitivity and specificity of urinary sE-cadherin for diagnosis of DN were calculated as 78.8% (95%CI, 74-83%) and 80% (95%CI, 65-91%). Pearson correlation and stepwise regression analysis indicated urinary sE-cadherin/Cr was high positive correlation with UAER and serum creatinine (r=0.861, r=0.713; p<0.01), and serum creatinine was the only independent influential factor of urinary sE-cadherin/Cr (R~2=0.831, F=56.72; p<0.01). Besides, immunohistochemical stain showed E-cadherin was mainly expressed in membrane and cytoplasm of renal tubular epithelial cells, and its expression was markedly decreased in DN kidneys versus normal kidneys.
Conclusion Urinary sE-cadherin has a potential clinical diagnostic value for DN, which is elevated in DN patients, and gradually increased with the development of nephropathy. Besides, E-cadherin may participate in the pathogenesis of DN, whose expression was markedly decreased in kidneys of DN.
Part V: The study on the relationship between urinary orosomucoid and type 2 diabetic nephropathy
Objective To detect the concentration changes of urinary orosomucoid in type 2 diabetes patients with normoalbuminuria, microalbuminuria, macroalbuminuria and healthy control group; To analyze the relationship between urinary orosomucoid and type 2 diabetic nephropathy, and evaluate its diagnostic value for diabetic nephropathy.
Methods The urinary level of urinary orosomucoid was detected by immunoturbidimetry assay in urine samples, which were from 160 type 2 diabetes patients with normoalbuminuria (DM group), microalbuminuria (DN1 group), macroalbuminuria (DN2 group) and healthy control group (n=40 in each group, the same with part IV). Then, we calculated the urinary orosomucoid excretion rate (UOER), to analyze the changes of UOER in different stages of DN. Besides, Pearson correlation analysis and multivariate logistic regression analysis were performed to evaluate the influencing factor of UOER. Meanwhile, the sensitivity and specificity of UOER for diagnosis of DN were calculated.
Results The data of immunoturbidimetry assay showed UOER was gradually increased in normo-, micro- and macroalbuminuria group versus control group (0.91±0.37, 1.87±0.72, 2.95±0.84 vs. 0.42±0.19 ug/min, P<0.05). The result indicated UOER increased in early stage of DN and gradually increased with the development of DN. Besides, Pearson correlation analysis indicated UOER was positively correlated with UAER, serum creatinine and CRP (r=0.781, 0.695, 0.401, respectively; P<0.05). And multivariate logistic regression analysis showed increased UOER was an independent risk factor for DN (OR=2.88, P<0.01). After the calculation by formula, the sensitivity and specificity of UOER for diagnosis of DN were 75.8% (95%CI, 71-82%) and 69% (95%CI, 58-83%).
Conclusion UOER is increased in early stage of type 2 diabetic nephropathy, and gradually increased with the development of nephropathy. Besides, increased UOER is an independent risk factor of DN, and it also has potential diagnostic value for DN.
引文
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