一、系统性血管炎血清蛋白质组学的研究 二、原发性干燥综合征的临床研究
|
摘要
课题一系统性血管炎血清蛋白质组学研究
背景
系统性血管炎由于临床表现复杂,病情偏重,且缺乏特异性生物学标志物,早期诊治困难,致残率、病死率高,预后差。因此,寻找系统性血管炎新的、特异性的生物学标志物已成为临床研究的热点。近年来,蛋白质指纹图谱技术即SELDI-TOF-MS技术已广泛用于对多种疾病,尤其是那些传统肿瘤标志物阴性的恶性肿瘤的早期诊断及生物标志物的筛查,并取得了成功,且后续对差异蛋白的鉴定成果业已见诸于报道。但其在系统性血管炎领域中的应用尚属空白。此外,本室前期研究显示抗膜突蛋白抗体与血管损伤、血管炎相关,推测其或许是系统性血管炎较特异的抗体。本研究首次在国内外采用蛋白质指纹图谱技术对白塞病、大动脉炎及ANCA相关性系统性血管炎(AASV)进行血清蛋白质组学研究,以期发现疾病特异性生物标志物及其组合模型,有助于对疾病的诊断、活动性监测及疗效评判。并对血清差异目的蛋白质分离富集的方法进行了初步探索,以期为后续差异蛋白质的鉴定提供技术支持。首次在国外内用免疫印迹法检测系统性血管炎患者血清抗膜突蛋白抗体的表达情况,探讨其临床意义。
目的
利用SELDI-TOF-MS技术检测系统性血管炎患者血清蛋白质指纹图谱,筛选出差异表达蛋白,构建系统性血管炎血清蛋白质指纹图谱分类树模型,寻找疾病活动性监测指标,分析差异蛋白与系统性血管炎临床表现、免疫学指标等临床资料的关系;如果能发现对系统性血管炎相对特异的差异蛋白质,则应用离子交换磁性微珠、SDS-PAGE,辅以SELDI-TOF-MS,对其进行分离和富集,利用MALDI-TOF-MS鉴定蛋白质。以重组膜突蛋白为抗原,采用免疫印迹法检测系统性血管炎患者血清抗膜突蛋白抗体的表达情况,探讨其临床意义。
方法
1.详细记录实验组及对照者的临床资料,并通过住院病历、门诊随诊记录对实验组进行随访。实验组为138例系统性血管炎患者,其中白塞病59例、大动脉炎42例及AASV 37例(包括韦格纳肉芽肿27例、显微镜下多血管炎9例及变应性肉芽肿性血管炎1例)。疾病对照组为30例狼疮性肾炎患者、15例冠心病患者。健康对照组为年龄、性别各相匹配的正常人,共115例。
2.采用SELDI-TOF-MS技术检测所有入组者的血清蛋白质指纹图谱,应用生物信息技术,通过差异比对,筛查出差异表达蛋白质,构建系统性血管炎的疾病分类树模型、疾病活动性判定联合模式,寻找疾病特异性的血清标志物。
3.分析差异表达蛋白与系统性血管炎病变分布、免疫学指标等临床资料的关系。
4.采用离子交换磁性微珠、SDS-PAGE,辅以SELDI-TOF-MS分离富集差异表达的目的蛋白,并用MALDI-TOF-MS鉴定目的蛋白。
5.利用重组膜突蛋白为抗原,采用免疫印迹法检测系统性血管炎患者血清中抗膜突蛋白抗体的阳性率,探讨其临床意义。
结果
1.由M/Z 7625.7、M/Z 3937.5和M/Z 12555.8所组成的白塞病诊断分类树模型、M/Z 7618.6组成的大动脉炎诊断分类树模型和M/Z 8337.8组成的AASV诊断分类树模型的敏感性依次是78.9%、91.7%、91.7%,特异性依次是80.0%、80.0%、100.0%;
2.M/Z 7813.2峰强度≥1.20时,对白塞病活动性判断的敏感性为74.0%,特异性为77.8%;联合应用M/Z 8690.9、M/Z 16508.8和M/Z 4346.8三者对大动脉炎疾病活动性判断的敏感性为76.9%,特异性为100.0%;联合应用M/Z 11449.2、M/Z3276.6和M/Z 11671.9三者对AASV疾病活动性判断的敏感性为96.7%,特异性为100.0%;
3.M/Z 13751.6峰强度≥0.64时,对白塞病内脏损害诊断的敏感性为84.2%,特异性为81.0%;
4.M/Z 11689.7峰强度≥3.04时,对白塞病治疗无效者判断的敏感性为80.0%,特异性为87.5%;
5.对蛋白沈脱液的蛋白质指纹图谱测定中可见,WCX磁性微珠捕获了血清目的蛋白M/Z 28.9kDa及M/Z 16.7kDa。SDS-PAGE电泳凝胶上可见相应两处条带。对28.9kDa处条带质谱鉴定结果为混合物。对16.7kDa处条带质谱鉴定结果为免疫球蛋白Kappa 1轻链;
6.系统性血管炎患者血清抗膜突蛋白抗体的阳性率为32.6%,高于冠心病(6.7%)及正常人(5.0%),而与SLE患者(20%)相同;
7.白塞病患者血清抗膜突蛋白抗体的阳性率为42.4%%,大动脉炎者为33.3%,AASV患者为16.2%;
8.白塞病不同临床表现和实验室指标与血清抗膜突蛋白抗体无关;大动脉炎头臂动脉型患者抗膜突蛋白抗体的阳性率高于广泛型患者;
9.抗膜突蛋白抗体阳性对系统性血管炎诊断的敏感性为32.6%,特异性为89.1%。
结论
1.蛋白质指纹图谱技术是一项极具潜力的适合于差异蛋白质组学研究的技术,可以用于对疾病生物标志物的筛查;
2.由M/Z 7625.7、M/Z 3937.5和M/Z 12555.8所组成的白塞病分类树模型、M/Z7618.6组成的大动脉炎分类树模型和M/Z 8337.8组成的AASV分类树模型,对疾病的诊断有一定意义;
3.M/Z 7813.2峰强度有助对白塞病疾病活动性的评判:M/Z 8690.9、M/Z 16508.8和M/Z 4346.8三者联合应用及M/Z 11449.2、M/Z 3276.6和M/Z 11671.9三者联合应用分别是评判大动脉炎、AASV疾病活动性的良好指标,均优于血沉、C反应蛋白等指标;
4.M/Z 13751.6峰强度是白塞病内脏受累的良好标志物;
5.M/Z 11689.7峰强度对评价白塞病患者对治疗的反应有一定的价值;
6.所筛选出的系统性血管炎患者大量差异蛋白质可作为今后探索的目的蛋白;
7.磁性微珠技术、蛋白质指纹图谱技术和Tricine-SDS-PAGE三者相结合来分离纯化蛋白质,具有良好的研究前景,是今后研究血清差异蛋白的有力武器。
8.系统性血管炎患者血清中存在抗膜突蛋白抗体,其阳性率高于冠心病及正常人,而与SLE患者相同;不同系统性血管炎抗膜突蛋白抗体的阳性率不同,白塞病和大动脉炎患者明显高于AASV患者;白塞病不同临床表现和实验室指标与血清抗膜突蛋白抗体无关;大动脉炎头臂动脉型患者抗膜突蛋白抗体的阳性率高于广泛型患者;
9.抗膜突蛋白抗体阳性对系统性血管炎的诊断具有一定意义。
Background
Since nonspecific clinical manifestations, particularly the lack of specific biomarker, systemic vasculitis is a challenge for rheumatologists to diagnose early and has a poor prognosis with a higher morbidity and mortality. Currently, screening of specific and facilitative biomarkers has become a hot field in clinical studies on systemic vasculitis. During the last years, protein fingerprinting technology (also named as SELDI-TOF-MS) has been applied widely in medical field for the detection of diseases, especially for cancers without traditional tumor makers. An increasing number of cancer-related biomarkers for diagnosis, progression and prognosis have been identified successfully using SELDI-TOF-MS. When about systemic vasculitis, only one study on Wegener's granulomatosis has been reported. On the other hand, in a previous study, we found the positive relation between anti-moesin antibody and the damage of vascular and vasculitis. So for the first time, we carry out studies on Behcet's disease(BD), Takayasu arteritis(TA) and ANCA-associated systemic vasculitis (AASV) using SELDI-TOF-MS and detect the positive rate of anti-moesin antibody in patients with systemic vasculitis and evaluate its clinical significance.
Objective
1. To detect serum proteomic fingerprinting of patients with systemic vasculitis, and screen differentially expressed proteins, and establish classification tree models or serum biomarker pattern for diagnosis and monitoring on disease activity.
2. To screen differential proteins and analyze their relationships with the clinical and immunological patterns of systemic vasculitis.
3. To identify the aim proteins by the proteomics technique.
4. To detect the positive rate of anti-moesin antibody in patients with systemic vasculitis, and analyze their clinical significance.
Method
1. Record the clinical dates of all subjects and follow up the experimental group with the clinical record in hospitalization and/or out-patient clinic. The experimental group is composed of 138 patients with systemic vasculitis, including 59 patients with BD, 42 with TA, 37 with AASV. 30 patients with lupus nephritis, 15 patients with coronary heart disease, 115 healthy persons were collected as controls. Serum samples of all subjects were collected when they entered the study.
2. Detect all serum samples using SELDI-TOF-MS and obtain serum proteomic fingerprinting, and screen differentially expressed proteins using Ciphergen Biomarker Wizard, and establish classification tree models or serum biomarker pattern for diagnosis and monitoring on disease activity.using using Ciphergen Biomarker Wizard.
3. Using Ciphergen Biomarker Wizard, screen differentially expressed proteins and analyze their relationships with the clinical and immunological patterns of systemic vasculitis.
4. To identify the aim proteins by weak cation exchange interaction magnetic bead(WCX), SDS-PAGE, SELDI-TOF-MS and MALDI-TOF-MS.
5. With recombinant moesin as antigen, sera were screened for the presence of anti-moesin antibody in all subjects by Western blotting and discuss its clinical significance.
Results
1. The diagnosis classification tree model for BD is composed of m/z 7625.7, m/z 3937.5 and m/z 12555.8 ions, while for TA and AASV are composed of m/z 7618.6 and m/z 8337.8 respectively, the sensitivities as follows respectively: 78.9%、91.7%、91.7%, and the specificities are as follows respectively 80.0%、80.0%、100.0%.
2. The peak intensity of m/z 7813.2 gave 74.0% sensitivity and 77.8% specificity for active BD versus remission one at the cut-off point 1.20. The combination of m/z 8690.9、m/z 16508.8 and m/z 4346.8 has a sensitivity of 76.9% for active TA and a specificity of 100.0%, while the combination of m/z 11449.2、m/z 3276.6 and m/z 11671.9 has a sensitivity of 96.7% for active AASV and a specificity of 100.0%.
3. The peak intensity of m/z 13751.6 has 84.2% sensitivity and 100.0% specificity for BD patients with systemic involvement at the cut-off point 0.64.
4. The peak intensity of m/z 11689.7 has 80.0% sensitivity and 87.5% specificity for BD patients failed to respond to therapy at the cut-off point 3.04.
5. With SELDI-TOF-MS, the aim proteins m/z 28.9 and m/z 16.7 was purified and enriched by WCX magnetic bead, SDS-PAGE, and identified with MALDI-TOF-MS as mixture for the band 28.9kDa and immunoglobulin kappa 1 light chain for the band 16.7kDa respectively.
6. Taking recombinant moesin as antigen, sera were screened for the presence of anti-moesin antibody in all subjects by Western blotting. The positive rates are follows: 32.6% (45/138) in systemic vasculitis, including 42.4% (25/59) in BD, 33.3% (14/42) in TA and 16.2% (6/37). 20.0% (4/20) in lupus nephritis, 6.7% (1/15) in coronary heart disease and 5.0% (1/20) in healthy persons.
7. No relationship has been found between anti-moesin antibody and the clinical features of BD. While higher rate has been found in TA patients with the type of brachiocephalic artery involvememt versus those with the type of general involvememt.
8. As a diagnosis method of systemic vasculitis, the sensitivity and specificity are 32.6% and 89.1% respectively.
Conclusion
1. Protein fingerprinting technology is a potential tool for discovery of novel biomarker in systemic vasculitis.
2. The diagnosis classification tree models, including m/z 7625.7, m/z 3937.5 and m/z 12555.8 for BD, m/z 7618.6 for TA and m/z 8337.8 for AASV, have a certain value for diagnosis.
3. Serum biomarker patterns, such as single ion m/z 7813.2 in BD, combination of m/z 8690.9、m/z 16508.8 and m/z 4346.8 in TA , and combination of m/z 11449.2、m/z 3276.6 and m/z 11671.9 in AASV, have significantly predictive value for active disease and better than ERS and CRP.
4. Ion m/z13751.6 has a strong predictive value for systemic involvement in BD patients.
5. Ion m/z11689.7 is a moderate predictive of patients with BD response to therapy.
6. All of these differentially expressed proteins could be aimed as objects in the future studies.
7. Combination of WCX magnetic bead, Tricine-SDS-PAGE and SELDI-TOF-MS, would be a powerful arm to studies on serum differential proteome.
8. The positive rate of anti-moesin antibody is higher in patients with systemic vasculitis than in those with coronary heart disease and healthy persons, and equal as patients in lupus nephritis. Among systemic vasculitis, patients with BD and TA have higher positive rate than those with AASV. Anti-moesin antibody has no relationship with the clinical features of BD.
9. Anti-moesin antibody has moderate value for the diagnosis of systemic vasculitis.
背景
系统性血管炎由于临床表现复杂,病情偏重,且缺乏特异性生物学标志物,早期诊治困难,致残率、病死率高,预后差。因此,寻找系统性血管炎新的、特异性的生物学标志物已成为临床研究的热点。近年来,蛋白质指纹图谱技术即SELDI-TOF-MS技术已广泛用于对多种疾病,尤其是那些传统肿瘤标志物阴性的恶性肿瘤的早期诊断及生物标志物的筛查,并取得了成功,且后续对差异蛋白的鉴定成果业已见诸于报道。但其在系统性血管炎领域中的应用尚属空白。此外,本室前期研究显示抗膜突蛋白抗体与血管损伤、血管炎相关,推测其或许是系统性血管炎较特异的抗体。本研究首次在国内外采用蛋白质指纹图谱技术对白塞病、大动脉炎及ANCA相关性系统性血管炎(AASV)进行血清蛋白质组学研究,以期发现疾病特异性生物标志物及其组合模型,有助于对疾病的诊断、活动性监测及疗效评判。并对血清差异目的蛋白质分离富集的方法进行了初步探索,以期为后续差异蛋白质的鉴定提供技术支持。首次在国外内用免疫印迹法检测系统性血管炎患者血清抗膜突蛋白抗体的表达情况,探讨其临床意义。
目的
利用SELDI-TOF-MS技术检测系统性血管炎患者血清蛋白质指纹图谱,筛选出差异表达蛋白,构建系统性血管炎血清蛋白质指纹图谱分类树模型,寻找疾病活动性监测指标,分析差异蛋白与系统性血管炎临床表现、免疫学指标等临床资料的关系;如果能发现对系统性血管炎相对特异的差异蛋白质,则应用离子交换磁性微珠、SDS-PAGE,辅以SELDI-TOF-MS,对其进行分离和富集,利用MALDI-TOF-MS鉴定蛋白质。以重组膜突蛋白为抗原,采用免疫印迹法检测系统性血管炎患者血清抗膜突蛋白抗体的表达情况,探讨其临床意义。
方法
1.详细记录实验组及对照者的临床资料,并通过住院病历、门诊随诊记录对实验组进行随访。实验组为138例系统性血管炎患者,其中白塞病59例、大动脉炎42例及AASV 37例(包括韦格纳肉芽肿27例、显微镜下多血管炎9例及变应性肉芽肿性血管炎1例)。疾病对照组为30例狼疮性肾炎患者、15例冠心病患者。健康对照组为年龄、性别各相匹配的正常人,共115例。
2.采用SELDI-TOF-MS技术检测所有入组者的血清蛋白质指纹图谱,应用生物信息技术,通过差异比对,筛查出差异表达蛋白质,构建系统性血管炎的疾病分类树模型、疾病活动性判定联合模式,寻找疾病特异性的血清标志物。
3.分析差异表达蛋白与系统性血管炎病变分布、免疫学指标等临床资料的关系。
4.采用离子交换磁性微珠、SDS-PAGE,辅以SELDI-TOF-MS分离富集差异表达的目的蛋白,并用MALDI-TOF-MS鉴定目的蛋白。
5.利用重组膜突蛋白为抗原,采用免疫印迹法检测系统性血管炎患者血清中抗膜突蛋白抗体的阳性率,探讨其临床意义。
结果
1.由M/Z 7625.7、M/Z 3937.5和M/Z 12555.8所组成的白塞病诊断分类树模型、M/Z 7618.6组成的大动脉炎诊断分类树模型和M/Z 8337.8组成的AASV诊断分类树模型的敏感性依次是78.9%、91.7%、91.7%,特异性依次是80.0%、80.0%、100.0%;
2.M/Z 7813.2峰强度≥1.20时,对白塞病活动性判断的敏感性为74.0%,特异性为77.8%;联合应用M/Z 8690.9、M/Z 16508.8和M/Z 4346.8三者对大动脉炎疾病活动性判断的敏感性为76.9%,特异性为100.0%;联合应用M/Z 11449.2、M/Z3276.6和M/Z 11671.9三者对AASV疾病活动性判断的敏感性为96.7%,特异性为100.0%;
3.M/Z 13751.6峰强度≥0.64时,对白塞病内脏损害诊断的敏感性为84.2%,特异性为81.0%;
4.M/Z 11689.7峰强度≥3.04时,对白塞病治疗无效者判断的敏感性为80.0%,特异性为87.5%;
5.对蛋白沈脱液的蛋白质指纹图谱测定中可见,WCX磁性微珠捕获了血清目的蛋白M/Z 28.9kDa及M/Z 16.7kDa。SDS-PAGE电泳凝胶上可见相应两处条带。对28.9kDa处条带质谱鉴定结果为混合物。对16.7kDa处条带质谱鉴定结果为免疫球蛋白Kappa 1轻链;
6.系统性血管炎患者血清抗膜突蛋白抗体的阳性率为32.6%,高于冠心病(6.7%)及正常人(5.0%),而与SLE患者(20%)相同;
7.白塞病患者血清抗膜突蛋白抗体的阳性率为42.4%%,大动脉炎者为33.3%,AASV患者为16.2%;
8.白塞病不同临床表现和实验室指标与血清抗膜突蛋白抗体无关;大动脉炎头臂动脉型患者抗膜突蛋白抗体的阳性率高于广泛型患者;
9.抗膜突蛋白抗体阳性对系统性血管炎诊断的敏感性为32.6%,特异性为89.1%。
结论
1.蛋白质指纹图谱技术是一项极具潜力的适合于差异蛋白质组学研究的技术,可以用于对疾病生物标志物的筛查;
2.由M/Z 7625.7、M/Z 3937.5和M/Z 12555.8所组成的白塞病分类树模型、M/Z7618.6组成的大动脉炎分类树模型和M/Z 8337.8组成的AASV分类树模型,对疾病的诊断有一定意义;
3.M/Z 7813.2峰强度有助对白塞病疾病活动性的评判:M/Z 8690.9、M/Z 16508.8和M/Z 4346.8三者联合应用及M/Z 11449.2、M/Z 3276.6和M/Z 11671.9三者联合应用分别是评判大动脉炎、AASV疾病活动性的良好指标,均优于血沉、C反应蛋白等指标;
4.M/Z 13751.6峰强度是白塞病内脏受累的良好标志物;
5.M/Z 11689.7峰强度对评价白塞病患者对治疗的反应有一定的价值;
6.所筛选出的系统性血管炎患者大量差异蛋白质可作为今后探索的目的蛋白;
7.磁性微珠技术、蛋白质指纹图谱技术和Tricine-SDS-PAGE三者相结合来分离纯化蛋白质,具有良好的研究前景,是今后研究血清差异蛋白的有力武器。
8.系统性血管炎患者血清中存在抗膜突蛋白抗体,其阳性率高于冠心病及正常人,而与SLE患者相同;不同系统性血管炎抗膜突蛋白抗体的阳性率不同,白塞病和大动脉炎患者明显高于AASV患者;白塞病不同临床表现和实验室指标与血清抗膜突蛋白抗体无关;大动脉炎头臂动脉型患者抗膜突蛋白抗体的阳性率高于广泛型患者;
9.抗膜突蛋白抗体阳性对系统性血管炎的诊断具有一定意义。
Background
Since nonspecific clinical manifestations, particularly the lack of specific biomarker, systemic vasculitis is a challenge for rheumatologists to diagnose early and has a poor prognosis with a higher morbidity and mortality. Currently, screening of specific and facilitative biomarkers has become a hot field in clinical studies on systemic vasculitis. During the last years, protein fingerprinting technology (also named as SELDI-TOF-MS) has been applied widely in medical field for the detection of diseases, especially for cancers without traditional tumor makers. An increasing number of cancer-related biomarkers for diagnosis, progression and prognosis have been identified successfully using SELDI-TOF-MS. When about systemic vasculitis, only one study on Wegener's granulomatosis has been reported. On the other hand, in a previous study, we found the positive relation between anti-moesin antibody and the damage of vascular and vasculitis. So for the first time, we carry out studies on Behcet's disease(BD), Takayasu arteritis(TA) and ANCA-associated systemic vasculitis (AASV) using SELDI-TOF-MS and detect the positive rate of anti-moesin antibody in patients with systemic vasculitis and evaluate its clinical significance.
Objective
1. To detect serum proteomic fingerprinting of patients with systemic vasculitis, and screen differentially expressed proteins, and establish classification tree models or serum biomarker pattern for diagnosis and monitoring on disease activity.
2. To screen differential proteins and analyze their relationships with the clinical and immunological patterns of systemic vasculitis.
3. To identify the aim proteins by the proteomics technique.
4. To detect the positive rate of anti-moesin antibody in patients with systemic vasculitis, and analyze their clinical significance.
Method
1. Record the clinical dates of all subjects and follow up the experimental group with the clinical record in hospitalization and/or out-patient clinic. The experimental group is composed of 138 patients with systemic vasculitis, including 59 patients with BD, 42 with TA, 37 with AASV. 30 patients with lupus nephritis, 15 patients with coronary heart disease, 115 healthy persons were collected as controls. Serum samples of all subjects were collected when they entered the study.
2. Detect all serum samples using SELDI-TOF-MS and obtain serum proteomic fingerprinting, and screen differentially expressed proteins using Ciphergen Biomarker Wizard, and establish classification tree models or serum biomarker pattern for diagnosis and monitoring on disease activity.using using Ciphergen Biomarker Wizard.
3. Using Ciphergen Biomarker Wizard, screen differentially expressed proteins and analyze their relationships with the clinical and immunological patterns of systemic vasculitis.
4. To identify the aim proteins by weak cation exchange interaction magnetic bead(WCX), SDS-PAGE, SELDI-TOF-MS and MALDI-TOF-MS.
5. With recombinant moesin as antigen, sera were screened for the presence of anti-moesin antibody in all subjects by Western blotting and discuss its clinical significance.
Results
1. The diagnosis classification tree model for BD is composed of m/z 7625.7, m/z 3937.5 and m/z 12555.8 ions, while for TA and AASV are composed of m/z 7618.6 and m/z 8337.8 respectively, the sensitivities as follows respectively: 78.9%、91.7%、91.7%, and the specificities are as follows respectively 80.0%、80.0%、100.0%.
2. The peak intensity of m/z 7813.2 gave 74.0% sensitivity and 77.8% specificity for active BD versus remission one at the cut-off point 1.20. The combination of m/z 8690.9、m/z 16508.8 and m/z 4346.8 has a sensitivity of 76.9% for active TA and a specificity of 100.0%, while the combination of m/z 11449.2、m/z 3276.6 and m/z 11671.9 has a sensitivity of 96.7% for active AASV and a specificity of 100.0%.
3. The peak intensity of m/z 13751.6 has 84.2% sensitivity and 100.0% specificity for BD patients with systemic involvement at the cut-off point 0.64.
4. The peak intensity of m/z 11689.7 has 80.0% sensitivity and 87.5% specificity for BD patients failed to respond to therapy at the cut-off point 3.04.
5. With SELDI-TOF-MS, the aim proteins m/z 28.9 and m/z 16.7 was purified and enriched by WCX magnetic bead, SDS-PAGE, and identified with MALDI-TOF-MS as mixture for the band 28.9kDa and immunoglobulin kappa 1 light chain for the band 16.7kDa respectively.
6. Taking recombinant moesin as antigen, sera were screened for the presence of anti-moesin antibody in all subjects by Western blotting. The positive rates are follows: 32.6% (45/138) in systemic vasculitis, including 42.4% (25/59) in BD, 33.3% (14/42) in TA and 16.2% (6/37). 20.0% (4/20) in lupus nephritis, 6.7% (1/15) in coronary heart disease and 5.0% (1/20) in healthy persons.
7. No relationship has been found between anti-moesin antibody and the clinical features of BD. While higher rate has been found in TA patients with the type of brachiocephalic artery involvememt versus those with the type of general involvememt.
8. As a diagnosis method of systemic vasculitis, the sensitivity and specificity are 32.6% and 89.1% respectively.
Conclusion
1. Protein fingerprinting technology is a potential tool for discovery of novel biomarker in systemic vasculitis.
2. The diagnosis classification tree models, including m/z 7625.7, m/z 3937.5 and m/z 12555.8 for BD, m/z 7618.6 for TA and m/z 8337.8 for AASV, have a certain value for diagnosis.
3. Serum biomarker patterns, such as single ion m/z 7813.2 in BD, combination of m/z 8690.9、m/z 16508.8 and m/z 4346.8 in TA , and combination of m/z 11449.2、m/z 3276.6 and m/z 11671.9 in AASV, have significantly predictive value for active disease and better than ERS and CRP.
4. Ion m/z13751.6 has a strong predictive value for systemic involvement in BD patients.
5. Ion m/z11689.7 is a moderate predictive of patients with BD response to therapy.
6. All of these differentially expressed proteins could be aimed as objects in the future studies.
7. Combination of WCX magnetic bead, Tricine-SDS-PAGE and SELDI-TOF-MS, would be a powerful arm to studies on serum differential proteome.
8. The positive rate of anti-moesin antibody is higher in patients with systemic vasculitis than in those with coronary heart disease and healthy persons, and equal as patients in lupus nephritis. Among systemic vasculitis, patients with BD and TA have higher positive rate than those with AASV. Anti-moesin antibody has no relationship with the clinical features of BD.
9. Anti-moesin antibody has moderate value for the diagnosis of systemic vasculitis.
引文
1. Reinhold-Keller E, Herlyn K, Wagner-Bastmeyer R, et al. Stable incidence of primary systemic vasculitides over five years: results from the German vasculitis register. Arthritis Rheum. 2005; 53(1): 93-99.
2. Yi D, Shi GY. The synopsis of the 8th International meeting on BD. Natl Med J China, 1999, 38: 135-136.
3. Walton E W. Giant cell granuloma of the respiratory tract (Wegener's granulomatosis). Br Med J 1958; ii: 265 - 270.
4. Wasinger VC , Cordewell SJ , Cerpa-Poljak A,et al. Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis, 1995, 16:1090-1094.
5. Kahn P. From genome to proteome: Looking at a cell's proteins. Science, 1995, 270:369-370.
6. Petricoin EF, Belluco C, Araujo RP, et al.The blood peptidome: a higher dimension of information content for cancer biomarker discovery. Nat Rev Cancer. 2006;6(12):961-967.
7. Tirumalai RS, Chan KC, Prieto DA, et al. Characterization of the low molecular weight human serum proteome. Mol Cell Proteomics 2003;2:1096 - 1103.
8. Liotta LA, Ferrari M, Petricoin EF. Clinical proteomics: written in blood. Nature 2003;425:905.
9. Merchant M, Weinberger SR. Recent advancements in surface-enhanced laser desorption / ionization time-of-flight mass spectrometry. Electrophoresis, 2000:21(6): 1164-1177.
10. Ward DG, Cheng Y , N'Kontchot G, et al. Changes in the serum proteome associated with the development of hepatocellular carcinoma in hepatitis C-related cirrhosis. Br J Cancer, 2006,94: 287 -292.
11. Li J, Zhang Z, Rosenweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem, 2002,48:1296-1304.
12. Petricoin EF, Ardekani AM, Hitt BA,et al. Use of proteomic patterns in serum to identify ovarian cancer .Lancet, 2002, 359: 572-577.
13. Meehan KL, Holand JW, Dawkins HJ. Proteomic analysis of normal and malignant prostate tissue to identify novel proteins lost in cancer. Prostate, 2002,50:54-63.
14. Tomosugi N, Kitagawa K, Takahashi N, et al. Diagnostic potential of tear proteomic patterns in Sjogren's syndrome. J Proteome Res. 2005; 4(3): 820-825.
15. Ryu OH, Atkinson JC, Hoehn GT, et al. Identification of parotid salivary biomarkers in Sjogren's syndrome by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and two-dimensional difference gel electrophoresis.Rheumatology(Oxford).2006;45(9):1077-1086.
16.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):R746-755.
17.de Seny D,Fillet M,Meuwis MA,et al.Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.Arthritis Rheum.2005;52(12):3801-3812.
18.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.
19.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.
20.Stone JH,Rajapakse VN,Hoffrnan GS,et al.A serum proteomic approach to gauging the state of remission in Wegener's Granulomatosis.Arthritis Rheum.2005;52(3):902-910.
21.Praprotnik S,Blank M,Meroni PL,et al.Classification of anti-endothelial cell antibodies into antidoies against microvascular and macrovascular endothelial cell.Arthritis Rheum.2001;44:1484-1494.
22.郑文洁,唐福林,赵岩,等.系统性血管炎中抗内皮细胞抗体的检测及其靶抗原研究.
23.Lankes WT,Furthmayr H.Moesin:a member of the protein 4.1-talin-ezrin family of proteins Proc Natl Acad Sci USA.1991,88(19):8297-8301.
24.Polesello C,Payre F.Small is beautiful:what flies tell us about ERM protein function in development.Trends Cell Biol,2004,14:294-302.
25.Li Y,Harada T,Juang YT,et al.Phosphorylated ERM is responsible for increased T cell polarization,adhesion and migration in patients with systemic lupus erythematosus.J Immunol,2007,17:1938-1947.
26.International Study Group.Criteria for diagnosis of Behcet's disease.International Study Group for Behcet's Disease.Lancet.1990;335(8697):1078-1080.
27.Arend WP,Michel BA,Bloch DA et al.The American College of Rheumatology criteria for the classification of Takayasu arteritis.Arthritis Rheum,1990;33:1129-1134.
28.Leavitt RY,Fauci AS,Bloch DA,et al.The American College of Rheumatology criteria for the classification of Wegener's Granulomatosis.Arthritis Rheum 1990;33:1101-1107.
29.Masi AT,Hunder GG,Lie JT,et al.The American College of Rheumatology 1990 criteria for the classification of Churg-Strauss syndrome (Allergic granulomatosis and angiitis). Arthritis Rheum 1990; 33: 1094-1100.
30. Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 1997;40:1725.
31. Luqmani R A, Bacon P A, Moots R J, et al. Birmingham vasculitis activity score (BVAS) in systemic necrotizing vasculitis.Q J Med, 1994; 87: 671-678.
32. Kerr GS, Hallahan CW, Giordano J, et al. Takayasu's arteritis. Ann Intern Med,1994, 120: 919-929.
33. Petricoin EF, Ornstein DK, Paweletz CP, et al. Serum proteomic patterns for detection of prostate cancer. J. Natl Cancer Inst. 2002; 94(20), 1576 - 1578.
34. Brouwers, F. M. et al. Low molecular weight proteomic information distinguishes metastatic from benign pheochromocytoma. Endocr. Relat. Cancer. 12, 263 - 272(2005).
35. Sundsten T, Zethelius B, Berne C,et al. Plasma proteome changes in subjects with Type 2 diabetes mellitus with a low or high early insulin response. Clin Sci (Lond).2008;114(7):499-507.
36. Basso D., Valerio A., Seraglia R., et al. Putative pancreatic cancer-associated diabetogenic factor: 2030 MW peptide. Pancreas 2002; 24, 8 -14.
37. Lopez MF, Mikulskis A, Kuzdzal S, et al. High-resolution serum proteomic profiling of Alzheimer disease samples reveals disease-specific, carrier-protein-bound mass signatures. Clin Chem 2005;51:1946-1954.
38. Rubin R.B, Merchant M. A rapid protein profiling system that speeds study of cancer and other diseases. Am Clin Lab. 2000; 19, 28 -29.
39. Issaq HJ, Conrads TP, Prieto DA, et al. SELDI-TOF MS for diagnostic proteomics.Anal Chem. 2003; 75(7):148A-155A.
40. Zhu H, Snyder M. Protein chip technology.Curr Opin Chem Biol. 2003; 7(1): 55-63.
41. Poon TCW,Sung JJY,Chow SM,et al. Diagnosis of gastric cancer by serum proteomic fingerprinting. Gastroenterology, 2006; 130: 1858-1864.
42. Han KQ, Huang G, Gao CF,et al, Identification of lung cancer patients by serum protein profiling using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Am J Clin Oncol. 2008; 31(2): 133-139.
43. Zhu LR, Zhang WY, Yu L, et al. Proteiomic patterns for endometrial cancer using SELDI-TOF-MS. J Zhejiang Univ Sci B. 2008; 9(4):286-90.
44. Rao JK, Weinberger M, Oddone EZ, et al. The role of antineutrophil cytoplasmic antibody (c-ANCA) testing in the diagnosis of Wegener granulomatosis. A literature review and meta-analysis. Ann Intern Med 1995; 123:925-932.
45.张卓莉,彭劲民,侯小萌,等.1996 例白塞病患者的临床荟萃分析.北京医学,2007; 29(1): 10-12.
46.Hoffman GS,Ahmed AE.Surrogate markers of disease activity in patients with Takayasu's arteritis:a preliminary report from the Intemational Network for the Study of Systemic Vasculitis.Int J Cardiol,1998,66(Suppl 1):191-195.
47.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.
48.Tolson J,Bogumil R,Brunst E,Beck H,Elsner R,Humeny A,et al.Serum protein profiling by SELDI mass spectrometry:detection of multiple variants of serum amyloid αin renal cancer patients.Lab Invest 2004;84:845-856.
49.Le L,Chi K,Tyldesley S,Flibotte S,Diamond DL,Kuzyk MA,et al.Identification of serum amyloid A as a biomarker to distinguish prostate cancer patients with bone lesions.Ciin Chem 2005;51:695-707.
50.Cho WC,Yip TT,Yip C,Yip V,Thulasiraman V,Ngan RK,et al.Identification of serum amyloid A as a potentially useful biomarker to monitor relapse of nasopharyngeal cancer by serum proteomic profiling.Clin Cancer Res 2004;10:43-1052.
51.戴嵩玮,王小敏,刘丽云,等.一个在肺癌血清中高表达的标志分子SAA的发现及鉴定.中国科学:C辑.2007,37(2):129-134.
52.Kokubun M,Imafuku Y,Okada M,et al.Serum amyloid A(SAA) concentration varies among rheumatoid arthritis patients estimated by SAA/CRP ratio.Clin Chimica Acta,2005,360:97-102.
53.Malle E,De Beer F C.Human serum amyloid A(SAA) protein:a prominent acute-phase reactant for clinical practice.Eur J Clin Invest,1996,26(6):427-435.
54.Yip T,Chan J,Cho W,et al.Protein chip array profiling analysis in patients with severe acute respirator syndrome identified serum amyloid A protein as a biomarker potentially useful in monitoring the extent of pneumonia.Clin Chem,2005,51:47-55.
55.张国安,许雪姣,张素艳,等.蛋白质组的分离与分析及其应用进展.分析化学,2003,31(5):611-618.
56.Simpson RJ,Dorow DS1.Cancer proteomics:from signaling networks to tumor markers.Trends Biotechnol,2001,19(10):40-48.
57.Klein E,Klein JB,Thongboonkerd V.Two dimensional gel electrophoresis:a fundamental tool for expression proteomics studies.Contrib Nephrol,2004,(141):25-39.
58.曹佐武.有效分离1kDa小肽的Tricine-SDS-PAGE方法.中国生物工程杂志,2004,24(1):74-76.
59.Laget MP,Defossen PA,Albagli O,et al.Two functionally distinct domains responsible for transactivation by the Ets family member ERM.Oncogene.1996;12(6):1325-1336.
60.Polesello C,Payre F.Small is beautiful:what flies tell us about ERM protein function in development. Trends Cell Biol, 2004, 14: 294-302.
61. Masahide T, toshiro N, Yukihito S, et al. Altered expression of the ERM proteins in lung adenocaroinoma. Laboratory Investigation, 2000, 80(11): 1643 -1651.
62. Brandwein-Gensler M, Schect N, Brougel D, et al. Ezrin and moesin cytoplasmic mislocation as potential predictive biomarkers: a tissue microarray validation study. Arch Otolaryngol Head Neck Surg, 2006, 132: 903-904.
63. Hiroiehi K, Junji S, JunyaM. Shift in celular localization of moesin in normal oral epithelium,oral epithelial dysplasia, vernlcous carcinoma and oral squamous cell carcinoma. J Oral Pathol Med , 2003, 32: 344-349.
64. Martin K, Tilmann L, Matthias W , et al. Ezrin promotes ovarian caroinomacel invasion and its retained expression predicts poor prognosis in ovarian carcinoma. Internatioan. Journal of Gynecological Pathology, 2006. 25: 121-130.
65. Satoshi N, Chert ST, Fuad G, et al. Diagnostic markers that distinguish colon and ovarian adenocarcinomas: identification by genomic, proteomic and tisue array profiling. Cancer Research, 2003, 63: 5243-5250.
66. Krishnan S, Nambiar MP, Warke VG, et al. Alterations in lipid raft composition and dynamics contribute to abnormal T cell responses in systemic lupus erythematosus. J Immunol.2004;172(12):7821-7831.
67. Wagatsuma M, Kimura M, Suzuki R, et al. Ezrin, radixin and moesin are possible auto-immune antigens in rheumatoid arthritis. Mol Immunol, 1996, 33:1171-1176.
68. Koss M, Pfeiffer GR, Wang Y, et al. Ezrin/radixin/moesin proteins are phosphorylated by TNF-alpha and modulate permeability increases in human pulmonary microvascular endothelial cells. J Immunol. 2006; 176(2): 1218-1227.
69. Jensen PV, Larsson LI. Actin microdomains on endothelial cells: association with CD44, ERM proteins, and signaling molecules during quiescence and wound healing. Histochem Cell Biol.2004, 121:361-369.
70. Takamatsu H, Feng X, Chuhjo T et al. Specific antibodies to moesin, a membrane-cytoskeleton linker protein,are frequently detected in patients with acquired aplastic anemia. Blood. 2007; 109:2514-2520.
1.Wasinger VC,Cordewell SJ,Cerpa-Poljak A,et al.Progress with gene-product mapping of the Mollicutes:Mycoplasma genitalium.Electrophoresis,1995,16:1090-1094.
2.Kahn P.From genome to proteome:Looking at a cell's proteins.Science,1995,270:369-370.
3.Peng J,Gygi SP.Proteomics:the move to mixtures.J Mass Spectrom,2001,36:1083.
4.Blackstock WP,Weir MP.Proteomics:quantitative and physical mapping of cellular proteins.Trends Biotechnol.1999 Mar;17(3):121-127.
5.O'Farrell PH.High resolution two-dimensional electrophoresis of proteins.J Biol Chem.1975May 25;250(10):4007-4021.
6.Simpson RJ,Dorow DS.Cancer proteomics:from signaling networks to tumor markers.Trends Biotechnol.2001;19(10):40-48.
7.Klein E,Klein JB,Thongboonkerd V.Two dimensional gel electrophoresis:a fundamental tool for expression proteomics studies.Contrib Nephrol,2004,141:25-39.
8.Fenn JB,Mann M,Meng CK,et al.Electrospray ionization for mass spectrometry of large biomolecules.Science,1989,246:64-71.
9.Tanaka K,Waki H,et al.Protein and polymer analysis up to m/z 100,000 by laser ionization time-of-flight mass spectrometry.Rapid Commun Mass Spectrom,1988,2:151-153.
10.Aebersold R,Mann M.Mass spectrometry-based proteomics.Nature.2003 Mar 13;422(6928):198-207.
11.Andersen JS,Mann M.Functional genomics by mass spectrometry.FEBS Lett.2000 Aug 25;480(1):25-31.
12.Merchant M,Weinberger SR.Recent advancements in surface- enhanced laser desorption/ionization time-of-flight mass spectrometry.Electrophoresis,2000,21(6):1164-1177.
13.Weinberger SR,Morris TS,Pawlak M.Recent trends in protein biochip technology.Pharmacogenomics,2000;1(4):395-416.
14.Tang N,Tornatorc P,Weinberger SR.Current developments in SELDI afinity technology.Mass Speetrom Rev,2004,23(1):34-44.
15.Wright GL,Cazarcs LH,Leung SM,et al.SELDI mass spectrometry:a novel protein biochip technology for detection of biomarker in complex protein mixtures.Prostate Cancer and Prostatic Disease,1999,2(5):264-276.
16.Vlahou A,Schellhammer PF,Mendrincs S,et al.Development of a novel proteomie approach for the detection of transitional cell carcinoma of the bladder in urine.Am J Pathol。2001,158(4):1491-1502.
17. Issaq HJ, Conrads TP, Prieto DA, et al. SELDI-TOF MS for diagnostic proteomics. Anal Chem.2003; 75(7): 148A-155A.
18. Zhu H, Snyder M. Protein chip technology. Curr Opin Chem Biol. 2003; 7(1): 55-63.
19. Ward DG, Cheng Y , N'Kontchot G, et al. Changes in the serum proteome associated with the development of hepatocellular carcinoma in hepatitis C-related cirrhosis. Br J Cancer, 2006,94:287 -292.
20. Li J, Zhang Z, Rosenweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem, 2002, 48:1296-1304.
21. Petricoin EF, Ardekani AM, Hitt BA,et al. Use of proteomic patterns in serum to identify ovarian cancer .Lancet, 2002, 359: 572-577.
22. Meehan KL, Holand JW, Dawkins HJ. Proteomic analysis of normal and malignant prostate tissue to identify novel proteins lost in cancer. Prostate, 2002,50:54-63.
23. Stone JH, Rajapakse VN, Hoffman GS, et al. A serum proteomic approach to gauging the state of remission in Wegener's Granulomatosis. Arthritis Rheum. 2005; 52(3): 902-910.
24. Ryu OH, Atkinson JC, Hoehn GT, et.al. Identification of parotid salivary biomarkers in Sjogren's syndrome by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and two- dimensional difference gel electrophoresis.Rheumatology (Oxford). 2006; 45(9): 1077-1086.
25. Tomosugi N, Kitagawa K, Takahashi N, et al. Diagnostic potential of tear proteomic patterns in Sjogren's syndrome. J Proteome Res. 2005 May-Jun;4(3):820-825.
26. 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-R755.
27. Naishiro Y, Suzuki C, Kimura M, et al. Plasma analysis of rheumatoid arthritis by SELDI Nihon Rinsho Meneki Gakkai Kaishi. 2007; 30(3): 145-150. [Article in Japanese]
28. de Seny D, Fillet M, Meuwis MA, et al. Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ ionization time-of-flight mass spectrometry ProteinChip approach. Arthritis Rheum. 2005 Dec;52(12):3801-3812.
29. 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.
30. 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.
31. Stears RL, Martinsky T, Schena M. Trends in microarray analysis. Nat Med. 2003; 9(1): 140-145.
32. Petricoin EF, Zoon KC, Kohn EC, et al. Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov. 2002; 1(9): 683-695.
1 张乃峥,曾庆馀,张凤山,等.中国风湿性疾病流行情况的调查研究.中华风湿病学杂志,1997,1:31-35.
2 Vitali C,Bombardieri S,Jonsson R,et al.Classication criteria for Sjrgren's syndrome:a revised version of the European criteria proposed by the American-European Consensus Group.Ann Rheum Dis,2002,61:554-558.
3 赵岩,董怡,郭晓萍,等原发性干燥综合征的临床分析.北京医学,1997,19:100-104.
4 Garcia-Carrasco M,Ramos-Casals M,Rosas J,et al.Primary Sj(o|¨)gren syndrome:clinical and immunologic disease patterns in a cohort of 400 patients.Medicine (Baltimore),2002,81:270-280.
5 Skopouli FN,Dafni U,Ioannidis JP,et al.Clinical evolution,and morbidity and mortality of primary Sj(o|¨)gren's Syndrome.Semin Arthritis Rheum,2000,29:296-304.
6 Davidson BKS,Kelly CA,Griffiths.Primary Sj(o|¨)gren's Syndrome in the North East of England:a long-term follow-up study.Rheumatology,1999,38:245-253.
7 唐福林,汪国生,孙丽蓉,等原发性干燥综合征合并甲状腺功能异常的临床分析.中华风湿病学杂志,1998,2:71-74.
8 Quismorio FP Jr.Pulmonary involvement in primary Sjogren's syndrome.Curr Opin Pulm Med,1996,2:424-428.
9 Gardiner P,Ward C,Allison A,et al.Pleuropulmonary abnormalities in primary Sj(o|¨)gren's syndrome.J Rheumatol,1993,20:831-837.
10 张烜,董怡,张奉春.结缔组织病肺间质病变的临床特点分析.中华风湿病学杂志,1999.3:247-248.
11 Cha SI,Fessler MB,Cool CD,et al.Lymphoid interstitial pneumonia:clinical features,associations and prognosis.Eur Respir J,2006,28:364-369.
12 Ito I,Nagai S,Kitaichi M,et al.Pulmonary manifestations of primary Sjogren's syndrome:a clinical,radiologic,and pathologic study.Am J Respir Crit Care Med,2005,171:632-638.
13 张烜,张奉春,董怡.结缔组织病中肺动脉高压临床特点分析.中华风湿病学杂志,1999.3:5-7.
14 曾小峰,吴敏,李明佳,等原发性干燥综合征死亡原因及相关因素分析.中华风湿病学杂志,1999,3:222-223.
1 张乃峥,施胜全,要庆平,等.原发性干燥综合征的流行病学调查.中华内科杂志.1993,32:522-524.
2 田新平,吴敏,曾小峰.原发性干燥综合征临床表现分类新模式及169例回顾分析.中华风湿病学杂志,1999,3:80-83.
3 赵岩,董怡,郭晓萍,等.原发性干燥综合征的临床分析.北京医学,1997,19:100-104.
4 李敬扬,周炜,张卓莉,等.101例原发性干燥综合征临床首发症状及误诊分析.中国医刊.2004,39:19-21.
5 董怡,张乃峥.干燥综合征的肾脏损害.中华内科杂志,1988,27:162-164.
6 任红,陈楠,陈晓农,等.干燥综合征合并肾脏损害147例临床病理及随访情况.中华风湿病学杂志,2005,9:351-353.
7 杨军,李学旺,黄庆元,等.原发性干燥综合征26例合并肾脏损害临床及病理分析.中华内科杂志,1997,36:28-31.
8 郭俊唐,郭清华,陆菊明.肾小管酸中毒88例临床分析.临床内科杂志,2005,22:40-41.
9 李小霞,许文兵,朱元珏,等.108例原发性干燥综合征的肺部表现.中华内科杂志.1996,35:764-765.
10 徐治波,毛伯勤,王小霞,等.原发性干燥综合征的肺部改变.中华风湿病学杂志,2000,4:42-43.
11 程杰军,许建荣,吴华伟,等.干燥综合征肺部病变的HRCT表现.中国医学计算机成像杂志,2004,10:239-242.
12 朱春兰,赵阴环,田素礼,等.原发性干燥综合征胃粘膜病例特点分析.中华风湿病学杂志,2004,8:88-91.
13 张卓莉,董怡.原发性干燥综合征肝脏损害的临床及免疫学特点(附30例临床分析).中华风湿病学杂志,1998,2:92-96.
14 伍沪生,宋慧,黄彦弘,等.原发性干燥综合征的肝脏损害.中华风湿病学杂志,2001,5:29-31.
15 徐欣萍,董怡,陈元方.干燥综合征消化系临床表现80例分析.中华消化杂志.1996,16:29-31.
16 张烜,朱强.原发性干燥综合征的肝胰损害一例.中华风湿病学杂志,2001,5:233.
17 费亚新,董怡,彭斌,等.原发性干燥综合征的神经系统和肌肉合并症.临床神经科学.1995,3:38-41.
18 王学锋,赵玉宾.原发性干燥综合征的神经系统损害.中国神经精神疾病杂志,1994,20:213-215.
19 唐福林,汪国生,孙丽蓉,等.原发性干燥综合征合并甲状腺功能异常的临床分析.中华风湿病学杂志,1998,2:71-74.
20 黄菁梅,张学武,贾园,等.原发性干燥综合征合并甲状腺功能异常的临床及血清学分析.中华风湿病学杂志,2002,6:456-458.
21 谢雯.原发性干燥综合征血液系统损害临床特点.现代实用医学.2002,14:409-410.
22 张幼莉,江海燕,庞学丰,等.原发性干燥综合征103例血液学变化.临床内科杂志.2001,18:55-56.
23 竺红,宫怡.原发性干燥综合征心脏病变的超声表现.中国误诊学杂志,2006,6:466-467.
24 张烜,张奉春,董怡.结缔组织病中肺动脉高压临床表现特点分析.中华风湿病学杂志.1999,3:5-7.
25 孙丽蓉,唐福林,曾小峰,等.原发性干燥综合征合并恶性肿瘤(附8例病例分析).中国医师杂志,1999,1:44-45.
26 Dong Y,Zhao Y,Zeng X,et al.Primary Sjogren's syndrome and its lymphoid malignancy:a report of four cases.Chin Med J(Engl),1998,111:218-219.
27 李倩.涎腺粘膜相关淋巴组织淋巴瘤.国外医学口腔医学分册,2002,29:332-334.
2. Yi D, Shi GY. The synopsis of the 8th International meeting on BD. Natl Med J China, 1999, 38: 135-136.
3. Walton E W. Giant cell granuloma of the respiratory tract (Wegener's granulomatosis). Br Med J 1958; ii: 265 - 270.
4. Wasinger VC , Cordewell SJ , Cerpa-Poljak A,et al. Progress with gene-product mapping of the Mollicutes: Mycoplasma genitalium. Electrophoresis, 1995, 16:1090-1094.
5. Kahn P. From genome to proteome: Looking at a cell's proteins. Science, 1995, 270:369-370.
6. Petricoin EF, Belluco C, Araujo RP, et al.The blood peptidome: a higher dimension of information content for cancer biomarker discovery. Nat Rev Cancer. 2006;6(12):961-967.
7. Tirumalai RS, Chan KC, Prieto DA, et al. Characterization of the low molecular weight human serum proteome. Mol Cell Proteomics 2003;2:1096 - 1103.
8. Liotta LA, Ferrari M, Petricoin EF. Clinical proteomics: written in blood. Nature 2003;425:905.
9. Merchant M, Weinberger SR. Recent advancements in surface-enhanced laser desorption / ionization time-of-flight mass spectrometry. Electrophoresis, 2000:21(6): 1164-1177.
10. Ward DG, Cheng Y , N'Kontchot G, et al. Changes in the serum proteome associated with the development of hepatocellular carcinoma in hepatitis C-related cirrhosis. Br J Cancer, 2006,94: 287 -292.
11. Li J, Zhang Z, Rosenweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem, 2002,48:1296-1304.
12. Petricoin EF, Ardekani AM, Hitt BA,et al. Use of proteomic patterns in serum to identify ovarian cancer .Lancet, 2002, 359: 572-577.
13. Meehan KL, Holand JW, Dawkins HJ. Proteomic analysis of normal and malignant prostate tissue to identify novel proteins lost in cancer. Prostate, 2002,50:54-63.
14. Tomosugi N, Kitagawa K, Takahashi N, et al. Diagnostic potential of tear proteomic patterns in Sjogren's syndrome. J Proteome Res. 2005; 4(3): 820-825.
15. Ryu OH, Atkinson JC, Hoehn GT, et al. Identification of parotid salivary biomarkers in Sjogren's syndrome by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and two-dimensional difference gel electrophoresis.Rheumatology(Oxford).2006;45(9):1077-1086.
16.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):R746-755.
17.de Seny D,Fillet M,Meuwis MA,et al.Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.Arthritis Rheum.2005;52(12):3801-3812.
18.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.
19.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.
20.Stone JH,Rajapakse VN,Hoffrnan GS,et al.A serum proteomic approach to gauging the state of remission in Wegener's Granulomatosis.Arthritis Rheum.2005;52(3):902-910.
21.Praprotnik S,Blank M,Meroni PL,et al.Classification of anti-endothelial cell antibodies into antidoies against microvascular and macrovascular endothelial cell.Arthritis Rheum.2001;44:1484-1494.
22.郑文洁,唐福林,赵岩,等.系统性血管炎中抗内皮细胞抗体的检测及其靶抗原研究.
23.Lankes WT,Furthmayr H.Moesin:a member of the protein 4.1-talin-ezrin family of proteins Proc Natl Acad Sci USA.1991,88(19):8297-8301.
24.Polesello C,Payre F.Small is beautiful:what flies tell us about ERM protein function in development.Trends Cell Biol,2004,14:294-302.
25.Li Y,Harada T,Juang YT,et al.Phosphorylated ERM is responsible for increased T cell polarization,adhesion and migration in patients with systemic lupus erythematosus.J Immunol,2007,17:1938-1947.
26.International Study Group.Criteria for diagnosis of Behcet's disease.International Study Group for Behcet's Disease.Lancet.1990;335(8697):1078-1080.
27.Arend WP,Michel BA,Bloch DA et al.The American College of Rheumatology criteria for the classification of Takayasu arteritis.Arthritis Rheum,1990;33:1129-1134.
28.Leavitt RY,Fauci AS,Bloch DA,et al.The American College of Rheumatology criteria for the classification of Wegener's Granulomatosis.Arthritis Rheum 1990;33:1101-1107.
29.Masi AT,Hunder GG,Lie JT,et al.The American College of Rheumatology 1990 criteria for the classification of Churg-Strauss syndrome (Allergic granulomatosis and angiitis). Arthritis Rheum 1990; 33: 1094-1100.
30. Hochberg MC. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 1997;40:1725.
31. Luqmani R A, Bacon P A, Moots R J, et al. Birmingham vasculitis activity score (BVAS) in systemic necrotizing vasculitis.Q J Med, 1994; 87: 671-678.
32. Kerr GS, Hallahan CW, Giordano J, et al. Takayasu's arteritis. Ann Intern Med,1994, 120: 919-929.
33. Petricoin EF, Ornstein DK, Paweletz CP, et al. Serum proteomic patterns for detection of prostate cancer. J. Natl Cancer Inst. 2002; 94(20), 1576 - 1578.
34. Brouwers, F. M. et al. Low molecular weight proteomic information distinguishes metastatic from benign pheochromocytoma. Endocr. Relat. Cancer. 12, 263 - 272(2005).
35. Sundsten T, Zethelius B, Berne C,et al. Plasma proteome changes in subjects with Type 2 diabetes mellitus with a low or high early insulin response. Clin Sci (Lond).2008;114(7):499-507.
36. Basso D., Valerio A., Seraglia R., et al. Putative pancreatic cancer-associated diabetogenic factor: 2030 MW peptide. Pancreas 2002; 24, 8 -14.
37. Lopez MF, Mikulskis A, Kuzdzal S, et al. High-resolution serum proteomic profiling of Alzheimer disease samples reveals disease-specific, carrier-protein-bound mass signatures. Clin Chem 2005;51:1946-1954.
38. Rubin R.B, Merchant M. A rapid protein profiling system that speeds study of cancer and other diseases. Am Clin Lab. 2000; 19, 28 -29.
39. Issaq HJ, Conrads TP, Prieto DA, et al. SELDI-TOF MS for diagnostic proteomics.Anal Chem. 2003; 75(7):148A-155A.
40. Zhu H, Snyder M. Protein chip technology.Curr Opin Chem Biol. 2003; 7(1): 55-63.
41. Poon TCW,Sung JJY,Chow SM,et al. Diagnosis of gastric cancer by serum proteomic fingerprinting. Gastroenterology, 2006; 130: 1858-1864.
42. Han KQ, Huang G, Gao CF,et al, Identification of lung cancer patients by serum protein profiling using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Am J Clin Oncol. 2008; 31(2): 133-139.
43. Zhu LR, Zhang WY, Yu L, et al. Proteiomic patterns for endometrial cancer using SELDI-TOF-MS. J Zhejiang Univ Sci B. 2008; 9(4):286-90.
44. Rao JK, Weinberger M, Oddone EZ, et al. The role of antineutrophil cytoplasmic antibody (c-ANCA) testing in the diagnosis of Wegener granulomatosis. A literature review and meta-analysis. Ann Intern Med 1995; 123:925-932.
45.张卓莉,彭劲民,侯小萌,等.1996 例白塞病患者的临床荟萃分析.北京医学,2007; 29(1): 10-12.
46.Hoffman GS,Ahmed AE.Surrogate markers of disease activity in patients with Takayasu's arteritis:a preliminary report from the Intemational Network for the Study of Systemic Vasculitis.Int J Cardiol,1998,66(Suppl 1):191-195.
47.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.
48.Tolson J,Bogumil R,Brunst E,Beck H,Elsner R,Humeny A,et al.Serum protein profiling by SELDI mass spectrometry:detection of multiple variants of serum amyloid αin renal cancer patients.Lab Invest 2004;84:845-856.
49.Le L,Chi K,Tyldesley S,Flibotte S,Diamond DL,Kuzyk MA,et al.Identification of serum amyloid A as a biomarker to distinguish prostate cancer patients with bone lesions.Ciin Chem 2005;51:695-707.
50.Cho WC,Yip TT,Yip C,Yip V,Thulasiraman V,Ngan RK,et al.Identification of serum amyloid A as a potentially useful biomarker to monitor relapse of nasopharyngeal cancer by serum proteomic profiling.Clin Cancer Res 2004;10:43-1052.
51.戴嵩玮,王小敏,刘丽云,等.一个在肺癌血清中高表达的标志分子SAA的发现及鉴定.中国科学:C辑.2007,37(2):129-134.
52.Kokubun M,Imafuku Y,Okada M,et al.Serum amyloid A(SAA) concentration varies among rheumatoid arthritis patients estimated by SAA/CRP ratio.Clin Chimica Acta,2005,360:97-102.
53.Malle E,De Beer F C.Human serum amyloid A(SAA) protein:a prominent acute-phase reactant for clinical practice.Eur J Clin Invest,1996,26(6):427-435.
54.Yip T,Chan J,Cho W,et al.Protein chip array profiling analysis in patients with severe acute respirator syndrome identified serum amyloid A protein as a biomarker potentially useful in monitoring the extent of pneumonia.Clin Chem,2005,51:47-55.
55.张国安,许雪姣,张素艳,等.蛋白质组的分离与分析及其应用进展.分析化学,2003,31(5):611-618.
56.Simpson RJ,Dorow DS1.Cancer proteomics:from signaling networks to tumor markers.Trends Biotechnol,2001,19(10):40-48.
57.Klein E,Klein JB,Thongboonkerd V.Two dimensional gel electrophoresis:a fundamental tool for expression proteomics studies.Contrib Nephrol,2004,(141):25-39.
58.曹佐武.有效分离1kDa小肽的Tricine-SDS-PAGE方法.中国生物工程杂志,2004,24(1):74-76.
59.Laget MP,Defossen PA,Albagli O,et al.Two functionally distinct domains responsible for transactivation by the Ets family member ERM.Oncogene.1996;12(6):1325-1336.
60.Polesello C,Payre F.Small is beautiful:what flies tell us about ERM protein function in development. Trends Cell Biol, 2004, 14: 294-302.
61. Masahide T, toshiro N, Yukihito S, et al. Altered expression of the ERM proteins in lung adenocaroinoma. Laboratory Investigation, 2000, 80(11): 1643 -1651.
62. Brandwein-Gensler M, Schect N, Brougel D, et al. Ezrin and moesin cytoplasmic mislocation as potential predictive biomarkers: a tissue microarray validation study. Arch Otolaryngol Head Neck Surg, 2006, 132: 903-904.
63. Hiroiehi K, Junji S, JunyaM. Shift in celular localization of moesin in normal oral epithelium,oral epithelial dysplasia, vernlcous carcinoma and oral squamous cell carcinoma. J Oral Pathol Med , 2003, 32: 344-349.
64. Martin K, Tilmann L, Matthias W , et al. Ezrin promotes ovarian caroinomacel invasion and its retained expression predicts poor prognosis in ovarian carcinoma. Internatioan. Journal of Gynecological Pathology, 2006. 25: 121-130.
65. Satoshi N, Chert ST, Fuad G, et al. Diagnostic markers that distinguish colon and ovarian adenocarcinomas: identification by genomic, proteomic and tisue array profiling. Cancer Research, 2003, 63: 5243-5250.
66. Krishnan S, Nambiar MP, Warke VG, et al. Alterations in lipid raft composition and dynamics contribute to abnormal T cell responses in systemic lupus erythematosus. J Immunol.2004;172(12):7821-7831.
67. Wagatsuma M, Kimura M, Suzuki R, et al. Ezrin, radixin and moesin are possible auto-immune antigens in rheumatoid arthritis. Mol Immunol, 1996, 33:1171-1176.
68. Koss M, Pfeiffer GR, Wang Y, et al. Ezrin/radixin/moesin proteins are phosphorylated by TNF-alpha and modulate permeability increases in human pulmonary microvascular endothelial cells. J Immunol. 2006; 176(2): 1218-1227.
69. Jensen PV, Larsson LI. Actin microdomains on endothelial cells: association with CD44, ERM proteins, and signaling molecules during quiescence and wound healing. Histochem Cell Biol.2004, 121:361-369.
70. Takamatsu H, Feng X, Chuhjo T et al. Specific antibodies to moesin, a membrane-cytoskeleton linker protein,are frequently detected in patients with acquired aplastic anemia. Blood. 2007; 109:2514-2520.
1.Wasinger VC,Cordewell SJ,Cerpa-Poljak A,et al.Progress with gene-product mapping of the Mollicutes:Mycoplasma genitalium.Electrophoresis,1995,16:1090-1094.
2.Kahn P.From genome to proteome:Looking at a cell's proteins.Science,1995,270:369-370.
3.Peng J,Gygi SP.Proteomics:the move to mixtures.J Mass Spectrom,2001,36:1083.
4.Blackstock WP,Weir MP.Proteomics:quantitative and physical mapping of cellular proteins.Trends Biotechnol.1999 Mar;17(3):121-127.
5.O'Farrell PH.High resolution two-dimensional electrophoresis of proteins.J Biol Chem.1975May 25;250(10):4007-4021.
6.Simpson RJ,Dorow DS.Cancer proteomics:from signaling networks to tumor markers.Trends Biotechnol.2001;19(10):40-48.
7.Klein E,Klein JB,Thongboonkerd V.Two dimensional gel electrophoresis:a fundamental tool for expression proteomics studies.Contrib Nephrol,2004,141:25-39.
8.Fenn JB,Mann M,Meng CK,et al.Electrospray ionization for mass spectrometry of large biomolecules.Science,1989,246:64-71.
9.Tanaka K,Waki H,et al.Protein and polymer analysis up to m/z 100,000 by laser ionization time-of-flight mass spectrometry.Rapid Commun Mass Spectrom,1988,2:151-153.
10.Aebersold R,Mann M.Mass spectrometry-based proteomics.Nature.2003 Mar 13;422(6928):198-207.
11.Andersen JS,Mann M.Functional genomics by mass spectrometry.FEBS Lett.2000 Aug 25;480(1):25-31.
12.Merchant M,Weinberger SR.Recent advancements in surface- enhanced laser desorption/ionization time-of-flight mass spectrometry.Electrophoresis,2000,21(6):1164-1177.
13.Weinberger SR,Morris TS,Pawlak M.Recent trends in protein biochip technology.Pharmacogenomics,2000;1(4):395-416.
14.Tang N,Tornatorc P,Weinberger SR.Current developments in SELDI afinity technology.Mass Speetrom Rev,2004,23(1):34-44.
15.Wright GL,Cazarcs LH,Leung SM,et al.SELDI mass spectrometry:a novel protein biochip technology for detection of biomarker in complex protein mixtures.Prostate Cancer and Prostatic Disease,1999,2(5):264-276.
16.Vlahou A,Schellhammer PF,Mendrincs S,et al.Development of a novel proteomie approach for the detection of transitional cell carcinoma of the bladder in urine.Am J Pathol。2001,158(4):1491-1502.
17. Issaq HJ, Conrads TP, Prieto DA, et al. SELDI-TOF MS for diagnostic proteomics. Anal Chem.2003; 75(7): 148A-155A.
18. Zhu H, Snyder M. Protein chip technology. Curr Opin Chem Biol. 2003; 7(1): 55-63.
19. Ward DG, Cheng Y , N'Kontchot G, et al. Changes in the serum proteome associated with the development of hepatocellular carcinoma in hepatitis C-related cirrhosis. Br J Cancer, 2006,94:287 -292.
20. Li J, Zhang Z, Rosenweig J, et al. Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer. Clin Chem, 2002, 48:1296-1304.
21. Petricoin EF, Ardekani AM, Hitt BA,et al. Use of proteomic patterns in serum to identify ovarian cancer .Lancet, 2002, 359: 572-577.
22. Meehan KL, Holand JW, Dawkins HJ. Proteomic analysis of normal and malignant prostate tissue to identify novel proteins lost in cancer. Prostate, 2002,50:54-63.
23. Stone JH, Rajapakse VN, Hoffman GS, et al. A serum proteomic approach to gauging the state of remission in Wegener's Granulomatosis. Arthritis Rheum. 2005; 52(3): 902-910.
24. Ryu OH, Atkinson JC, Hoehn GT, et.al. Identification of parotid salivary biomarkers in Sjogren's syndrome by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry and two- dimensional difference gel electrophoresis.Rheumatology (Oxford). 2006; 45(9): 1077-1086.
25. Tomosugi N, Kitagawa K, Takahashi N, et al. Diagnostic potential of tear proteomic patterns in Sjogren's syndrome. J Proteome Res. 2005 May-Jun;4(3):820-825.
26. 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-R755.
27. Naishiro Y, Suzuki C, Kimura M, et al. Plasma analysis of rheumatoid arthritis by SELDI Nihon Rinsho Meneki Gakkai Kaishi. 2007; 30(3): 145-150. [Article in Japanese]
28. de Seny D, Fillet M, Meuwis MA, et al. Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ ionization time-of-flight mass spectrometry ProteinChip approach. Arthritis Rheum. 2005 Dec;52(12):3801-3812.
29. 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.
30. 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.
31. Stears RL, Martinsky T, Schena M. Trends in microarray analysis. Nat Med. 2003; 9(1): 140-145.
32. Petricoin EF, Zoon KC, Kohn EC, et al. Clinical proteomics: translating benchside promise into bedside reality. Nat Rev Drug Discov. 2002; 1(9): 683-695.
1 张乃峥,曾庆馀,张凤山,等.中国风湿性疾病流行情况的调查研究.中华风湿病学杂志,1997,1:31-35.
2 Vitali C,Bombardieri S,Jonsson R,et al.Classication criteria for Sjrgren's syndrome:a revised version of the European criteria proposed by the American-European Consensus Group.Ann Rheum Dis,2002,61:554-558.
3 赵岩,董怡,郭晓萍,等原发性干燥综合征的临床分析.北京医学,1997,19:100-104.
4 Garcia-Carrasco M,Ramos-Casals M,Rosas J,et al.Primary Sj(o|¨)gren syndrome:clinical and immunologic disease patterns in a cohort of 400 patients.Medicine (Baltimore),2002,81:270-280.
5 Skopouli FN,Dafni U,Ioannidis JP,et al.Clinical evolution,and morbidity and mortality of primary Sj(o|¨)gren's Syndrome.Semin Arthritis Rheum,2000,29:296-304.
6 Davidson BKS,Kelly CA,Griffiths.Primary Sj(o|¨)gren's Syndrome in the North East of England:a long-term follow-up study.Rheumatology,1999,38:245-253.
7 唐福林,汪国生,孙丽蓉,等原发性干燥综合征合并甲状腺功能异常的临床分析.中华风湿病学杂志,1998,2:71-74.
8 Quismorio FP Jr.Pulmonary involvement in primary Sjogren's syndrome.Curr Opin Pulm Med,1996,2:424-428.
9 Gardiner P,Ward C,Allison A,et al.Pleuropulmonary abnormalities in primary Sj(o|¨)gren's syndrome.J Rheumatol,1993,20:831-837.
10 张烜,董怡,张奉春.结缔组织病肺间质病变的临床特点分析.中华风湿病学杂志,1999.3:247-248.
11 Cha SI,Fessler MB,Cool CD,et al.Lymphoid interstitial pneumonia:clinical features,associations and prognosis.Eur Respir J,2006,28:364-369.
12 Ito I,Nagai S,Kitaichi M,et al.Pulmonary manifestations of primary Sjogren's syndrome:a clinical,radiologic,and pathologic study.Am J Respir Crit Care Med,2005,171:632-638.
13 张烜,张奉春,董怡.结缔组织病中肺动脉高压临床特点分析.中华风湿病学杂志,1999.3:5-7.
14 曾小峰,吴敏,李明佳,等原发性干燥综合征死亡原因及相关因素分析.中华风湿病学杂志,1999,3:222-223.
1 张乃峥,施胜全,要庆平,等.原发性干燥综合征的流行病学调查.中华内科杂志.1993,32:522-524.
2 田新平,吴敏,曾小峰.原发性干燥综合征临床表现分类新模式及169例回顾分析.中华风湿病学杂志,1999,3:80-83.
3 赵岩,董怡,郭晓萍,等.原发性干燥综合征的临床分析.北京医学,1997,19:100-104.
4 李敬扬,周炜,张卓莉,等.101例原发性干燥综合征临床首发症状及误诊分析.中国医刊.2004,39:19-21.
5 董怡,张乃峥.干燥综合征的肾脏损害.中华内科杂志,1988,27:162-164.
6 任红,陈楠,陈晓农,等.干燥综合征合并肾脏损害147例临床病理及随访情况.中华风湿病学杂志,2005,9:351-353.
7 杨军,李学旺,黄庆元,等.原发性干燥综合征26例合并肾脏损害临床及病理分析.中华内科杂志,1997,36:28-31.
8 郭俊唐,郭清华,陆菊明.肾小管酸中毒88例临床分析.临床内科杂志,2005,22:40-41.
9 李小霞,许文兵,朱元珏,等.108例原发性干燥综合征的肺部表现.中华内科杂志.1996,35:764-765.
10 徐治波,毛伯勤,王小霞,等.原发性干燥综合征的肺部改变.中华风湿病学杂志,2000,4:42-43.
11 程杰军,许建荣,吴华伟,等.干燥综合征肺部病变的HRCT表现.中国医学计算机成像杂志,2004,10:239-242.
12 朱春兰,赵阴环,田素礼,等.原发性干燥综合征胃粘膜病例特点分析.中华风湿病学杂志,2004,8:88-91.
13 张卓莉,董怡.原发性干燥综合征肝脏损害的临床及免疫学特点(附30例临床分析).中华风湿病学杂志,1998,2:92-96.
14 伍沪生,宋慧,黄彦弘,等.原发性干燥综合征的肝脏损害.中华风湿病学杂志,2001,5:29-31.
15 徐欣萍,董怡,陈元方.干燥综合征消化系临床表现80例分析.中华消化杂志.1996,16:29-31.
16 张烜,朱强.原发性干燥综合征的肝胰损害一例.中华风湿病学杂志,2001,5:233.
17 费亚新,董怡,彭斌,等.原发性干燥综合征的神经系统和肌肉合并症.临床神经科学.1995,3:38-41.
18 王学锋,赵玉宾.原发性干燥综合征的神经系统损害.中国神经精神疾病杂志,1994,20:213-215.
19 唐福林,汪国生,孙丽蓉,等.原发性干燥综合征合并甲状腺功能异常的临床分析.中华风湿病学杂志,1998,2:71-74.
20 黄菁梅,张学武,贾园,等.原发性干燥综合征合并甲状腺功能异常的临床及血清学分析.中华风湿病学杂志,2002,6:456-458.
21 谢雯.原发性干燥综合征血液系统损害临床特点.现代实用医学.2002,14:409-410.
22 张幼莉,江海燕,庞学丰,等.原发性干燥综合征103例血液学变化.临床内科杂志.2001,18:55-56.
23 竺红,宫怡.原发性干燥综合征心脏病变的超声表现.中国误诊学杂志,2006,6:466-467.
24 张烜,张奉春,董怡.结缔组织病中肺动脉高压临床表现特点分析.中华风湿病学杂志.1999,3:5-7.
25 孙丽蓉,唐福林,曾小峰,等.原发性干燥综合征合并恶性肿瘤(附8例病例分析).中国医师杂志,1999,1:44-45.
26 Dong Y,Zhao Y,Zeng X,et al.Primary Sjogren's syndrome and its lymphoid malignancy:a report of four cases.Chin Med J(Engl),1998,111:218-219.
27 李倩.涎腺粘膜相关淋巴组织淋巴瘤.国外医学口腔医学分册,2002,29:332-334.