妊娠期高血压疾病患者血清差异蛋白的表达及意义
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摘要
目的:
妊娠期高血压疾病(hypertensive disorder complicating pregnancy)是严重危害母婴健康的产科疾病,是导致产妇及新生儿死亡的主要原因之一。虽经过多年的研究,该病的发病机制至今仍未完全阐明。由于妊娠期高血压疾病病因不明,无法早期诊断,及时阻断子痫、HELLP综合征等严重并发症的发生,所以早期筛查高危孕妇,适时监控高危人群,对减少该病的发生、降低孕产妇及围产儿死亡率显得尤为重要。但至今为止尚无特异性的血清标志物可作为早期筛查的指标。随着蛋白质组学的出现为我们研究妊娠期高血压疾病的发病机制和疾病的筛查提供了一个全新的方法和思路。
本实验采用表面加强激光解析电离飞行时间质谱(Surface-Enhanced LaserDesorption/IonizationTime of Flight-Mass Spectrometry,SELDI-TOF-MS)技术绘制妊娠期高血压疾病患者和正常孕妇血清蛋白质谱图,通过比较分析,筛选妊娠期高血压疾病的血清蛋白质特异性标志物,以期获得妊娠期高血压疾病筛查的血清学指标,同时期望获得疾病特异性相关蛋白,为我们深入研究该病的发病机制提供了新的方向。
方法:
SELDI-TOF-MS技术检测足月妊娠期高血压疾病患者21例及正常孕妇血清10例,获得弱阳离子交换(weak cation exchange,WCX2)芯片的蛋白质指纹图谱。用BioMarker Wizard软件分析妊娠期高血压疾病和正常人血清的差异蛋白质。运用Biomark Pattern Systerm软件建立妊娠期高血压疾病及重度子痫前期的诊断模型。以此模型双盲法检测子痫前期患者及正常妊娠孕妇,评价诊断模型的精确度和特异度。根据差异蛋白的分子量在UniProt蛋白数据库中搜索,以鉴定差异蛋白。并以ELISA实验进一步证实。
结果:
1.轻度子痫前期患者与正常晚期妊娠孕妇的血清蛋白质谱图在质荷比(mass/charge ,M/Z)为1000～20000的范围内有明显差异。轻度子痫前期患者血清中,M/Z为3936的蛋白质相对含量(2.52±1.89)明显低于正常孕妇(8.42±4.75)(P<0.05),而M/Z为3263、7979、13773的蛋白质相对含量(4.67±0.79、24.16±15.27、3.87±1.5)均高于正常孕妇(0.85±0.45、3.23±1.21、0.46±0.16)(P<0.05)。
2.重度子痫前期患者与轻度子痫前期患者的血清蛋白质谱图在质荷比为1000～20000的范围内有明显差异。重度子痫前期患者血清中,M/Z为7982、15943的蛋白质相对含量(3.18±1.35、2.12±1.58)明显低于轻度子痫前期患者(21.18±13.41、18.12±10.46) (P<0.05),而M/Z为3263、13773的蛋白质相对含量(16.34±4.5、9.49±0.75)均高于轻度子痫前期患者(4.67±0.79、3.87±1.5)(P<0.05)。
3.利用Biomarker Pattern软件对31例血清标本(21例妊娠期高血压疾病患者和10例正常妊娠妇女)进行盲法测定,结果发现M/Z为3263、13773蛋白质能够对正常人和妊娠期高血压疾病患者进行鉴别。灵敏性为90.48%,特异性为80%。
4.利用Biomarker Pattern软件对15例血清标本(8例轻度子痫前期患者患者和7例重度子痫前期患者)进行盲法测定,结果发现M/Z为3263、7982、13773、15943蛋白质能够对正常人和妊娠期高血压疾病患者进行鉴别。灵敏性为100%,特异性为87.5%。
5.对差异蛋白质进行蛋白质数据库搜索鉴定,分别得到了与分子量最为接近的6种蛋白质。
6.利用ELISA进一步证实M/Z为3263和13773的蛋白分别为VIP和MCP-1。
结论:
1.应用SELDI-TOF-MS技术对妊娠期高血压疾病患者血清进行检测发现6种差异蛋白,提示这6种差异蛋白质可能参与了妊娠期高血压疾病的发生、发展及代偿过程。
2.利用差异蛋白建立的诊断模型具有高度的灵敏性和特异性。
3.采用搜库法初步鉴定出6种差异蛋白,分别为血管活性肠肽、胰岛淀粉样多肽、泛醇-细胞色素C还原酶复合物7.8Kda蛋白、铁氧化还原样蛋74个氨基酸、低诱导趋化因子A2前体、心房利钠因子前体。
4.采用ELISA检测发现妊娠期高血压疾病患者血清中的MCP-1含量随着疾病程度的加重而递增,提示其与疾病的发生、发展有关。
5.采用ELISA检测发现妊娠期高血压疾病患者血清中的VIP含量随着疾病程度的加重而递增,提示其与疾病的发生、发展有关。
6.应用SELDI-TOF-MS筛选妊娠期高血压疾病特异性生物标志物的方法快速、有效,操作自动化。
Objective:
Hypertensive disorder complicating pregnancy is a kind of diseasethat severily harm the health of pregnant women and infants.It is the main cause ofpregnant women and infants’death. Althought there are many hypothesizes ,peoplecan not satisfactly interprete the pathogenesy of this diease. Because there is no satisfact therapy for this diease,it is very impormtent that to screen high risk gravida and monitori high-risk group as early as possible.But up to now there are still not specific biomarker in serum can as early scanning indicatrix. Proteomics give us a new method and strategy to study the pathogenesy and the method of early scanning hypertensive disorder complicating pregnancy.
Our study apply proteome echnique to scan the serum special biomarker of hypertensive disorder complicating pregnancy. We hope we can get the serum special biomarker of hypertensive disorder complicating pregnancy and some specificness associated proteins of this disease and give us some enlightenment of pathogenesy.
Method:
21 patients that are hypertensive disorder complicating pregnancy and 10 normal pregnancies were tested by Weak cationic exchang (WCX2) protein chip and surface enhanced laser desorption ionization-time of flight-mass-spectrometry of Ciphergen Inc. The differentially expressed proteins were analyzed by BioMarker Wizard, set up diagnostic cast of the hypertensive disorder complicating pregnancy and severe preeclampsia by Biomark Pattern Software and obtained its positive predictive value and accuracy and specificity. Using this diagnostic cast we gave a double-blind trial to the remanent serum samples from patients with and control group to get its accuracy and specificity. At last we researched the differently expressed protein on the UniPort protein database according to their molecular weight and it was further verified by ELISA
Result:
1. In the rang of M/Z from 1000 to 20000 there are distinction between two groups’serum mass spectrums. In the serum of mild preeclampsia group,the relative amount of protein which M/Z is 3936 ( 2.52±1.89 ) is obviously lower than normal group (8.42±4.75) (P< 0.05 ), the relative amount of proteins which M/Z are 3263、7979 and 13773 (4.67±0.79, 24.16±15.27, 3.87±1.5) is obviously higher than normal group( 0.85±0.45, 3.23±1.21, 0.46±0.16 ) ( P< 0.05 )。
2. In the rang of M/Z from 1000 to 20000 there are distinction between two groups’serum mass spectrums. In the serum of severe preeclampsia group,the relative amount of protein which M/Z is 7982 and 15943 (3.18±1.35, 2.12±1.58 ) is obviously lower than mild preeclampsia group (21.18±13.41, 18.12±10.46) (P< 0.05 ), the relative amount of proteins which M/Z are 3263 and 13773 (16.34±4.5, 9.49±0.75) is obviously higher than mild preeclampsia group (4.67±0.79, 3.87±1.5 ) ( P< 0.05 )。
3. We have developed two protein profiles (3263, 13773) that can separate patients with hypertensive disorder complicating pregnancy from normal pregnancies. It gives the much-improved sensitivity of 90.48% and the specificity of 80%.
4. We have developed four protein profiles (3263, 7982, 13773, 15943) that can separate patients with severe preeclampsia from patients with mild preeclampsia. It gives the much-improved sensitivity of 100% and the specificity of 87.5%.
5. Through searching databases, we have got six probably significant protein related with six different protein among three groups.
6. Further confirmed by ELISA, M / Z for 3263 and 13773, respectively protein VIP and MCP-1.
Conclusion:
1. Application of SELDI-TOF-MS technology to test serum from patients with hypertensive disorder complicating pregnancy and found six kinds of the differently expressed proteins, these proteins may participate the occurrence and development of hypertensive disorder complicating pregnancy.
2. The diagnose model making use of the differently expressed proteins has a high degree of sensitivity and specificity.
3. Search the database to identification of the six kinds of the differently expressed proteins, are Vasoactive intestinal peptide, Islet amyloid polypeptide, Ubiquinol-cytochrome c reductase complex 7.8 kDa protein, Ferredoxin-like, Small-inducible cytokine A2 precursor, Atrial natriuretic factor precursor.
4. By ELISA found content of MCP-1 in serum from patients with hypertensive disorder complicating pregnancy to increase progressively along with disease aggravation, and prompts MCP-1 related to incidence and development of diseases.
5. By ELISA found content of VIP in serum from patients with hypertensive disorder complicating pregnancy to increase progressively along with disease aggravation, and prompts VIP related to incidence and development of diseases.
6. Using SELDI-TOF-MS, the method of sieving the marker from becomes quick and valid.
妊娠期高血压疾病(hypertensive disorder complicating pregnancy)是严重危害母婴健康的产科疾病,是导致产妇及新生儿死亡的主要原因之一。虽经过多年的研究,该病的发病机制至今仍未完全阐明。由于妊娠期高血压疾病病因不明,无法早期诊断,及时阻断子痫、HELLP综合征等严重并发症的发生,所以早期筛查高危孕妇,适时监控高危人群,对减少该病的发生、降低孕产妇及围产儿死亡率显得尤为重要。但至今为止尚无特异性的血清标志物可作为早期筛查的指标。随着蛋白质组学的出现为我们研究妊娠期高血压疾病的发病机制和疾病的筛查提供了一个全新的方法和思路。
本实验采用表面加强激光解析电离飞行时间质谱(Surface-Enhanced LaserDesorption/IonizationTime of Flight-Mass Spectrometry,SELDI-TOF-MS)技术绘制妊娠期高血压疾病患者和正常孕妇血清蛋白质谱图,通过比较分析,筛选妊娠期高血压疾病的血清蛋白质特异性标志物,以期获得妊娠期高血压疾病筛查的血清学指标,同时期望获得疾病特异性相关蛋白,为我们深入研究该病的发病机制提供了新的方向。
方法:
SELDI-TOF-MS技术检测足月妊娠期高血压疾病患者21例及正常孕妇血清10例,获得弱阳离子交换(weak cation exchange,WCX2)芯片的蛋白质指纹图谱。用BioMarker Wizard软件分析妊娠期高血压疾病和正常人血清的差异蛋白质。运用Biomark Pattern Systerm软件建立妊娠期高血压疾病及重度子痫前期的诊断模型。以此模型双盲法检测子痫前期患者及正常妊娠孕妇,评价诊断模型的精确度和特异度。根据差异蛋白的分子量在UniProt蛋白数据库中搜索,以鉴定差异蛋白。并以ELISA实验进一步证实。
结果:
1.轻度子痫前期患者与正常晚期妊娠孕妇的血清蛋白质谱图在质荷比(mass/charge ,M/Z)为1000～20000的范围内有明显差异。轻度子痫前期患者血清中,M/Z为3936的蛋白质相对含量(2.52±1.89)明显低于正常孕妇(8.42±4.75)(P<0.05),而M/Z为3263、7979、13773的蛋白质相对含量(4.67±0.79、24.16±15.27、3.87±1.5)均高于正常孕妇(0.85±0.45、3.23±1.21、0.46±0.16)(P<0.05)。
2.重度子痫前期患者与轻度子痫前期患者的血清蛋白质谱图在质荷比为1000～20000的范围内有明显差异。重度子痫前期患者血清中,M/Z为7982、15943的蛋白质相对含量(3.18±1.35、2.12±1.58)明显低于轻度子痫前期患者(21.18±13.41、18.12±10.46) (P<0.05),而M/Z为3263、13773的蛋白质相对含量(16.34±4.5、9.49±0.75)均高于轻度子痫前期患者(4.67±0.79、3.87±1.5)(P<0.05)。
3.利用Biomarker Pattern软件对31例血清标本(21例妊娠期高血压疾病患者和10例正常妊娠妇女)进行盲法测定,结果发现M/Z为3263、13773蛋白质能够对正常人和妊娠期高血压疾病患者进行鉴别。灵敏性为90.48%,特异性为80%。
4.利用Biomarker Pattern软件对15例血清标本(8例轻度子痫前期患者患者和7例重度子痫前期患者)进行盲法测定,结果发现M/Z为3263、7982、13773、15943蛋白质能够对正常人和妊娠期高血压疾病患者进行鉴别。灵敏性为100%,特异性为87.5%。
5.对差异蛋白质进行蛋白质数据库搜索鉴定,分别得到了与分子量最为接近的6种蛋白质。
6.利用ELISA进一步证实M/Z为3263和13773的蛋白分别为VIP和MCP-1。
结论:
1.应用SELDI-TOF-MS技术对妊娠期高血压疾病患者血清进行检测发现6种差异蛋白,提示这6种差异蛋白质可能参与了妊娠期高血压疾病的发生、发展及代偿过程。
2.利用差异蛋白建立的诊断模型具有高度的灵敏性和特异性。
3.采用搜库法初步鉴定出6种差异蛋白,分别为血管活性肠肽、胰岛淀粉样多肽、泛醇-细胞色素C还原酶复合物7.8Kda蛋白、铁氧化还原样蛋74个氨基酸、低诱导趋化因子A2前体、心房利钠因子前体。
4.采用ELISA检测发现妊娠期高血压疾病患者血清中的MCP-1含量随着疾病程度的加重而递增,提示其与疾病的发生、发展有关。
5.采用ELISA检测发现妊娠期高血压疾病患者血清中的VIP含量随着疾病程度的加重而递增,提示其与疾病的发生、发展有关。
6.应用SELDI-TOF-MS筛选妊娠期高血压疾病特异性生物标志物的方法快速、有效,操作自动化。
Objective:
Hypertensive disorder complicating pregnancy is a kind of diseasethat severily harm the health of pregnant women and infants.It is the main cause ofpregnant women and infants’death. Althought there are many hypothesizes ,peoplecan not satisfactly interprete the pathogenesy of this diease. Because there is no satisfact therapy for this diease,it is very impormtent that to screen high risk gravida and monitori high-risk group as early as possible.But up to now there are still not specific biomarker in serum can as early scanning indicatrix. Proteomics give us a new method and strategy to study the pathogenesy and the method of early scanning hypertensive disorder complicating pregnancy.
Our study apply proteome echnique to scan the serum special biomarker of hypertensive disorder complicating pregnancy. We hope we can get the serum special biomarker of hypertensive disorder complicating pregnancy and some specificness associated proteins of this disease and give us some enlightenment of pathogenesy.
Method:
21 patients that are hypertensive disorder complicating pregnancy and 10 normal pregnancies were tested by Weak cationic exchang (WCX2) protein chip and surface enhanced laser desorption ionization-time of flight-mass-spectrometry of Ciphergen Inc. The differentially expressed proteins were analyzed by BioMarker Wizard, set up diagnostic cast of the hypertensive disorder complicating pregnancy and severe preeclampsia by Biomark Pattern Software and obtained its positive predictive value and accuracy and specificity. Using this diagnostic cast we gave a double-blind trial to the remanent serum samples from patients with and control group to get its accuracy and specificity. At last we researched the differently expressed protein on the UniPort protein database according to their molecular weight and it was further verified by ELISA
Result:
1. In the rang of M/Z from 1000 to 20000 there are distinction between two groups’serum mass spectrums. In the serum of mild preeclampsia group,the relative amount of protein which M/Z is 3936 ( 2.52±1.89 ) is obviously lower than normal group (8.42±4.75) (P< 0.05 ), the relative amount of proteins which M/Z are 3263、7979 and 13773 (4.67±0.79, 24.16±15.27, 3.87±1.5) is obviously higher than normal group( 0.85±0.45, 3.23±1.21, 0.46±0.16 ) ( P< 0.05 )。
2. In the rang of M/Z from 1000 to 20000 there are distinction between two groups’serum mass spectrums. In the serum of severe preeclampsia group,the relative amount of protein which M/Z is 7982 and 15943 (3.18±1.35, 2.12±1.58 ) is obviously lower than mild preeclampsia group (21.18±13.41, 18.12±10.46) (P< 0.05 ), the relative amount of proteins which M/Z are 3263 and 13773 (16.34±4.5, 9.49±0.75) is obviously higher than mild preeclampsia group (4.67±0.79, 3.87±1.5 ) ( P< 0.05 )。
3. We have developed two protein profiles (3263, 13773) that can separate patients with hypertensive disorder complicating pregnancy from normal pregnancies. It gives the much-improved sensitivity of 90.48% and the specificity of 80%.
4. We have developed four protein profiles (3263, 7982, 13773, 15943) that can separate patients with severe preeclampsia from patients with mild preeclampsia. It gives the much-improved sensitivity of 100% and the specificity of 87.5%.
5. Through searching databases, we have got six probably significant protein related with six different protein among three groups.
6. Further confirmed by ELISA, M / Z for 3263 and 13773, respectively protein VIP and MCP-1.
Conclusion:
1. Application of SELDI-TOF-MS technology to test serum from patients with hypertensive disorder complicating pregnancy and found six kinds of the differently expressed proteins, these proteins may participate the occurrence and development of hypertensive disorder complicating pregnancy.
2. The diagnose model making use of the differently expressed proteins has a high degree of sensitivity and specificity.
3. Search the database to identification of the six kinds of the differently expressed proteins, are Vasoactive intestinal peptide, Islet amyloid polypeptide, Ubiquinol-cytochrome c reductase complex 7.8 kDa protein, Ferredoxin-like, Small-inducible cytokine A2 precursor, Atrial natriuretic factor precursor.
4. By ELISA found content of MCP-1 in serum from patients with hypertensive disorder complicating pregnancy to increase progressively along with disease aggravation, and prompts MCP-1 related to incidence and development of diseases.
5. By ELISA found content of VIP in serum from patients with hypertensive disorder complicating pregnancy to increase progressively along with disease aggravation, and prompts VIP related to incidence and development of diseases.
6. Using SELDI-TOF-MS, the method of sieving the marker from becomes quick and valid.
引文
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25. Yanik FF, Amanvermez R, Yanik A, Celik C, Kokcu A. Pre-eclampsia associated with increased lipid peroxidation and decreased serum vitamin E levels[J]. Int JGynaecol Obstet, 1999;64:27–33.
26. Kunsch C, Medford RM. Oxidative stress as a regulator of gene expression in the vasculature[J]. Circ Res,1999;85: 753–66.
27. Myatt L, Miodovnik M. Prediction of preeclampsia[J]. Semin Perinatol, 1999,23: 45–57.
28. Zeek PM, Assali NS. Vascular changes associated with eclamptogenic toxemia of pregnancy[J]. Am J Clin Pathol, 1950; 20:1099 –1109.
29. Staff AC, Ranheim T, Khoury J, Henriksen T. Increased contents of phospholipids, cholesterol, and lipid peroxides in decidua basalis in women with preeclampsia[J]. Am J Obstet Gynecol, 1999; 180:587–592.
30. Collins T, Read MA, Neish AS, Whitley MZ, Thanos D, Maniatis T. Transcriptional regulation of endothelial cell adhesion molecules: NF-kappa B and cytokine-inducible enhancers[J]. FASEB J, 1995; 9:899 –909.
31. Maziere C, Auclair M, Djavaheri-Mergny M, Packer L, Maziere JC. Oxidized low density lipoprotein induces activation of the transcription factor NF kappa B in fibroblasts, endothelial and smooth muscle cells[J]. Biochem Mol Biol Int, 1996,39:1201–7.
32. Collins T, Cybulsky MI. NF-kappaB: Pivotal mediator or innocent bystander in atherogenesis[J]? J Clin Invest, 2001; 107:255–64.
33. Gerszten RE, Garcia-Zepeda EA, Lim YC, Yoshida M, Ding HA, Gimbrone MA Jr, et al. MCP-1 and IL-8 trigger firm adhesion of monocytes to vascular endothelium under flow conditions[J]. Nature, 1999; 398:718 –23.
34. Watanabe T, Fan J. Atherosclerosis and inflammation mononuclear cell recruitment and adhesion molecules with reference to the implication of ICAM-1/LFA-1 pathway in atherogenesis[J]. Int J Cardiol, 1998; 66:S45–S53.
35. Hanscn V, Maigaard S, Allen J. Effects of vasoactive intestinal polypeptide and substancc P on human intramyometrial arteries and stem villous arterics in term pregnancy[J]. lacenta, 1988, 9; 501-506.
36. Ercal N, Dorisio MS, Vinik A, et al. Vasoactive intestinal peptide receptors in human platelet memhrane. Characterization of binding and functional activity[J]. Ann NY Acad Sci, 1988, 527;663-666.
37. Davison JM. Pre-eclampsia as a multi-system disease[J]. Adv Exp Med Biol, 1989, 252; 119-131.
38. Fung, E T, Thulasiraman V, Weinberger S. et al. Protein biochips for differential profiling[J]. Curr Opin Biotechnol, 2001, 12(1):65-69.
39. Wu W, Tang X, Hu W, et al. Identification and validation of metastasis-associated proteins in head and neck cancer cell lines by two-dimensional electrophoresis and mass spectrometry[J]. Clin Exp Metastasis, 2002, 19 (4): 319-326.
40. Seiberta V, Wiesnerb A, Buschmanna T, et al. Surface-enhanced laser desorption ionization time-of –flight mass spectrometry (SELDI-TOF-MS) and ProteinChips technology in proteomics research[J]. Pathology Research and Practice, 2004, 200(2): 83-94.
41. Henderson NA, Steele RJ. SELDI-TOF proteomic analysis and cancer detection[J]. Surgeon, 2005 ; 3(6): 383-90, 422.
42. Vitzthum F, Behrens F, Anderson NL, et al. Proteomics: from basic research to diagnostic application. A review of requirements & needs[J]. J Proteome Res, 2005, 4(4): 1086-97.
1. Tinnakorn C. A proteomic approach for the identification of biological markers of preeclampsia[J]. Am J Obster and Gynecol,2003,11(1):S95.
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3. Watanabe H, Hamada H, Yanada N, et al. Proteome analysis reveals elevated serum levels of clustein in patients with preeclampsia[J]. Proteomics,2004,4(2): 537 - 543 .
4. Koy C, Heitner J C, Woisch R, et al. Cryodetector mass spectrometry profiling of plasma sample for HELLP diagnosis: an exploratory study[J]. Proteomics,2005, 5(12): 3079-3087.
5. Norwitz E R, Tsen L C, Park J S, et al. Discriminatory proteomic biomarker analysis identifies free hemoglobin in the cerebrospinal fluid of women with severe preeclampsia[J]. Am J Obstet Gynecol,2005,193(3):957-964.
6. Buhimschi I A, Guomao Z, Funai, et al. Proteomics analysis of urine in preeclampsia: A novel diagnosis for an old disease[J]. Am J Obstet Gynecol, 2006, 193(6):S15.
7. Hardy D B, Yang K. The expression of 11 beta-hydroxysteroid dehydrogenase type
2 is induced during trophoblast differentiation:effect of hypoxia [J]. J Clin Endocrinol Metab,2002,87(8):A3696-A3701.
8. Gratton R J, Gandley R E, Genbacev O, et al. Conditioned medium from hypoxic cytotrophoblasts alters arterial function [J]. Am J Obstet Gynecol,2001, 184(5): 984- 990.
9. Hoang V M, Foulk R, Clauser K, et al. Functional proteomics:examining the effects of hypoxia on the cytotrophoblast protein repertoire[J]. Endocrinology, 2003, 144(4): 1147-1154.
10. Vuadens F, Benay C, Crettaz D, et al. Identification of biologic markers of the premature rupture of fetal membranes:proteomic approach[J]. Proteomics, 2003,3(8): 1521-1525.
11. Thadikkaran L, Novy D, Siegenthaler M A, et al. The role of proteomics in the assessment of premature rupture of fetal membranes[J]. Clin Chim Acta,2005, 60 (1-2):27-36.
12. Michel P E, Crettaz D, Morier P, et al. Porteome analysis of human and amniotic fluid by Off-Gel isoelectric focusing followed by nano-LC-MS/MS[J]. Electrophoresis,2006,27:5-6.
13. Anderson N, Polanski M, Pieper R, et al. The human plasma proteome: A nonredundant list developed by combination of four separate sources[J]. Mol Cell Proteomics,2004,3:311-326.
14. Gravett M G, Novy M S, Rosenfeld R G, et al. Dianosis of intra-amniotic infection by proteomic profiling and identification of biomarker[J]. JAMA, 2004, 292:4.
15. Buhimschi I A, Christner R, Buhimschi C S. Proteomic biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation[J]. BJOG, 2005, 112(2):173-181.
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24. Walsh SW. Maternal-placental interactions of oxidative stress and antioxidants in preeclampsia[J]. Sernin Reprod Endocrinol, 1998;16: 93–104.
25. Yanik FF, Amanvermez R, Yanik A, Celik C, Kokcu A. Pre-eclampsia associated with increased lipid peroxidation and decreased serum vitamin E levels[J]. Int JGynaecol Obstet, 1999;64:27–33.
26. Kunsch C, Medford RM. Oxidative stress as a regulator of gene expression in the vasculature[J]. Circ Res,1999;85: 753–66.
27. Myatt L, Miodovnik M. Prediction of preeclampsia[J]. Semin Perinatol, 1999,23: 45–57.
28. Zeek PM, Assali NS. Vascular changes associated with eclamptogenic toxemia of pregnancy[J]. Am J Clin Pathol, 1950; 20:1099 –1109.
29. Staff AC, Ranheim T, Khoury J, Henriksen T. Increased contents of phospholipids, cholesterol, and lipid peroxides in decidua basalis in women with preeclampsia[J]. Am J Obstet Gynecol, 1999; 180:587–592.
30. Collins T, Read MA, Neish AS, Whitley MZ, Thanos D, Maniatis T. Transcriptional regulation of endothelial cell adhesion molecules: NF-kappa B and cytokine-inducible enhancers[J]. FASEB J, 1995; 9:899 –909.
31. Maziere C, Auclair M, Djavaheri-Mergny M, Packer L, Maziere JC. Oxidized low density lipoprotein induces activation of the transcription factor NF kappa B in fibroblasts, endothelial and smooth muscle cells[J]. Biochem Mol Biol Int, 1996,39:1201–7.
32. Collins T, Cybulsky MI. NF-kappaB: Pivotal mediator or innocent bystander in atherogenesis[J]? J Clin Invest, 2001; 107:255–64.
33. Gerszten RE, Garcia-Zepeda EA, Lim YC, Yoshida M, Ding HA, Gimbrone MA Jr, et al. MCP-1 and IL-8 trigger firm adhesion of monocytes to vascular endothelium under flow conditions[J]. Nature, 1999; 398:718 –23.
34. Watanabe T, Fan J. Atherosclerosis and inflammation mononuclear cell recruitment and adhesion molecules with reference to the implication of ICAM-1/LFA-1 pathway in atherogenesis[J]. Int J Cardiol, 1998; 66:S45–S53.
35. Hanscn V, Maigaard S, Allen J. Effects of vasoactive intestinal polypeptide and substancc P on human intramyometrial arteries and stem villous arterics in term pregnancy[J]. lacenta, 1988, 9; 501-506.
36. Ercal N, Dorisio MS, Vinik A, et al. Vasoactive intestinal peptide receptors in human platelet memhrane. Characterization of binding and functional activity[J]. Ann NY Acad Sci, 1988, 527;663-666.
37. Davison JM. Pre-eclampsia as a multi-system disease[J]. Adv Exp Med Biol, 1989, 252; 119-131.
38. Fung, E T, Thulasiraman V, Weinberger S. et al. Protein biochips for differential profiling[J]. Curr Opin Biotechnol, 2001, 12(1):65-69.
39. Wu W, Tang X, Hu W, et al. Identification and validation of metastasis-associated proteins in head and neck cancer cell lines by two-dimensional electrophoresis and mass spectrometry[J]. Clin Exp Metastasis, 2002, 19 (4): 319-326.
40. Seiberta V, Wiesnerb A, Buschmanna T, et al. Surface-enhanced laser desorption ionization time-of –flight mass spectrometry (SELDI-TOF-MS) and ProteinChips technology in proteomics research[J]. Pathology Research and Practice, 2004, 200(2): 83-94.
41. Henderson NA, Steele RJ. SELDI-TOF proteomic analysis and cancer detection[J]. Surgeon, 2005 ; 3(6): 383-90, 422.
42. Vitzthum F, Behrens F, Anderson NL, et al. Proteomics: from basic research to diagnostic application. A review of requirements & needs[J]. J Proteome Res, 2005, 4(4): 1086-97.
1. Tinnakorn C. A proteomic approach for the identification of biological markers of preeclampsia[J]. Am J Obster and Gynecol,2003,11(1):S95.
2. Mert O B, Ray B S, Joshua A, et al. Serum proteomics distinguish preeclamptic women from normal women[J].Obstct &Gynecol,2003,4:S82.
3. Watanabe H, Hamada H, Yanada N, et al. Proteome analysis reveals elevated serum levels of clustein in patients with preeclampsia[J]. Proteomics,2004,4(2): 537 - 543 .
4. Koy C, Heitner J C, Woisch R, et al. Cryodetector mass spectrometry profiling of plasma sample for HELLP diagnosis: an exploratory study[J]. Proteomics,2005, 5(12): 3079-3087.
5. Norwitz E R, Tsen L C, Park J S, et al. Discriminatory proteomic biomarker analysis identifies free hemoglobin in the cerebrospinal fluid of women with severe preeclampsia[J]. Am J Obstet Gynecol,2005,193(3):957-964.
6. Buhimschi I A, Guomao Z, Funai, et al. Proteomics analysis of urine in preeclampsia: A novel diagnosis for an old disease[J]. Am J Obstet Gynecol, 2006, 193(6):S15.
7. Hardy D B, Yang K. The expression of 11 beta-hydroxysteroid dehydrogenase type
2 is induced during trophoblast differentiation:effect of hypoxia [J]. J Clin Endocrinol Metab,2002,87(8):A3696-A3701.
8. Gratton R J, Gandley R E, Genbacev O, et al. Conditioned medium from hypoxic cytotrophoblasts alters arterial function [J]. Am J Obstet Gynecol,2001, 184(5): 984- 990.
9. Hoang V M, Foulk R, Clauser K, et al. Functional proteomics:examining the effects of hypoxia on the cytotrophoblast protein repertoire[J]. Endocrinology, 2003, 144(4): 1147-1154.
10. Vuadens F, Benay C, Crettaz D, et al. Identification of biologic markers of the premature rupture of fetal membranes:proteomic approach[J]. Proteomics, 2003,3(8): 1521-1525.
11. Thadikkaran L, Novy D, Siegenthaler M A, et al. The role of proteomics in the assessment of premature rupture of fetal membranes[J]. Clin Chim Acta,2005, 60 (1-2):27-36.
12. Michel P E, Crettaz D, Morier P, et al. Porteome analysis of human and amniotic fluid by Off-Gel isoelectric focusing followed by nano-LC-MS/MS[J]. Electrophoresis,2006,27:5-6.
13. Anderson N, Polanski M, Pieper R, et al. The human plasma proteome: A nonredundant list developed by combination of four separate sources[J]. Mol Cell Proteomics,2004,3:311-326.
14. Gravett M G, Novy M S, Rosenfeld R G, et al. Dianosis of intra-amniotic infection by proteomic profiling and identification of biomarker[J]. JAMA, 2004, 292:4.
15. Buhimschi I A, Christner R, Buhimschi C S. Proteomic biomarker analysis of amniotic fluid for identification of intra-amniotic inflammation[J]. BJOG, 2005, 112(2):173-181.