Abstract

Preeclampsia (PE) is the leading cause of death of the fetus and the mother. The exact pathomechanism has not so far been clarified. PE coexists with many other diseases, but it is often difficult to explain the association between them and find a clear reason for their occurrence. There are many predictive factors, but none are highly specific in preeclampsia. The diagnosis of preeclampsia seems to be very complex, which is another argument for the exploration of knowledge on this subject. Although many of the discoveries have hitherto been made in the field of proteomics, still no single specific biomarker of preeclampsia has been discovered. Research at the genome level is important because it can help us understand the genetic predisposition of patients affected by this disease. Nevertheless, researchers have recently become more interested in the pathophysiology of PE, and they are trying to answer the question: what is the real, direct cause of preeclampsia? Thus, the discovery of a protein that is a good predictor of preeclampsia development would significantly accelerate the medical care of pregnant women, and consequently reduce the risk of occurrence of HELLP syndrome and fetal death. Apart from the predictive and diagnostic function, such a discovery would help us to better understand the pathogenesis of preeclampsia and to find in the future a medical drug to suppress this disease. In order to make a breakthrough in this field, scientists need to use the most modern methods of proteomics, which allow for the analysis of small amounts of biological material in the shortest possible time, thereby giving a lot of information about existing proteins in the sample. Such optimization allows two methods, most commonly used by researchers: tandem mass spectrometry and protein microarray technique.

References

• 1. Anderson U.D., Olsson M.G., Kristensen K.H., Akerstrom B., HanssonS.R.: Review: Biochemical markers to predict preeclampsia. Placenta,2012; 33: S42-S47
  Google Scholar
• 2. Barbulovic-Nad I., Lucente M., Sun Y., Zhang M., Wheeler A.R.,Bussmann M.: Bio-microarray fabrication techniques – a review. Crit.Rev. Biotechnol., 2006; 26: 237-259
  Google Scholar
• 3. Brower V.: Proteomics: biology in the post-genomic era. Companiesall over the world rush to lead the way in the new post-genomicsrace. EMBO Rep., 2001; 2: 558-560
  Google Scholar
• 4. Buhimschi I.A., Zhao G., Funai E.F., Harris N., Sasson I.E., BernsteinI.M., Saade G.R., Buhimschi C.S.: Proteomic profiling of urineidentifies specific fragments of serpina-1 and albumin as biomarkersof preeclampsia. Am. J. Obstet. Gynecol., 2008; 199: 551.e1-551.e16
  Google Scholar
• 5. Carty D.M., Delles C., Dominiczak A.F.: Novel biomarkers for predictingpreeclampsia. Trends Cardiovasc. Med., 2008; 18: 186-194
  Google Scholar
• 6. Carty D.M., Siwy J., Brennand J.E., Zurbig P., Mullen W., Franke J.,McCulloch J.W., Roberts C.T., North R.A., Chappell L.C., Mischak H.,Poston L., Dominiczak A.F., Delles C.: Urinary proteomics for predictionof preeclampsia. Hypertension, 2011; 57: 561-569
  Google Scholar
• 7. Conde-Agudelo A., Villar J., Lindheimer M.: World Health Organizationsystematic review of screening tests for preeclampsia. Obstet.Gynecol., 2004; 104: 1367-1391
  Google Scholar
• 8. Davila R.D., Julian C.G., Browne V.A., Toledo-Jaldin L., Wilson M.J.,Rodriguez A., Vargas E., Moore L.G.: Role of cytokines in altitudeassociatedpreeclampsia. Pregnancy Hypertens., 2012; 2: 65-70
  Google Scholar
• 9. Davison J.M., Homuth V., Jeyabalan A., Conrad K.P., KarumanchiS.A., Quaggin S., Dechend R., Luft F.C.: New aspects in the pathophysiologyof preeclampsia. J. Am. Soc. Nephrol., 2004; 15: 2440-2448
  Google Scholar
• 10. Gerszten R.E., Wang T.J.: The search for new cardiovascular biomarkers.Nature, 2008; 451: 949-952
  Google Scholar
• 11. Griffin J.L., Shockcor J.P.: Metabolic profiles of cancer cells. Nat.Rev. Cancer, 2004; 4: 551-561
  Google Scholar
• 12. Gulmann C., Sheehan K.M., Kay E.W., Liotta L.A., PetricoinE.F.3rd: Array-based proteomics: mapping of protein circuitries fordiagnostics, prognostics, and therapy guidance in cancer. J. Pathol.,2006; 208: 595-606
  Google Scholar
• 13. Hartmann M., Roeraade J., Stoll D., Templin M.F., Joos T.O.: Proteinmicroarrays for diagnostic assays. Anal. Bioanal. Chem., 2009;393: 1407-1416
  Google Scholar
• 14. Hortin G.L.: The MALDI-TOF mass spectrometric view of theplasma proteome and peptidome. Clin. Chem., 2006; 52: 1223-1237
  Google Scholar
• 15. Hou L., Zhu Y., Ma X., Li J., Zhang W.: Serum protein microarrayanalysis of patients with preeclampsia. Mol. Med. Rep., 2012; 6: 83-87
  Google Scholar
• 16. Jonsson Y., Ruber M., Matthiesen L., Berg G., Nieminen K., SharmaS., Ernerudh J., Ekerfelt C.: Cytokine mapping of sera from womenwith preeclampsia and normal pregnancies. J. Reprod. Immunol.,2006; 70: 83-91
  Google Scholar
• 17. Karas M., Bahr U., Dulcks T.: Nano-electrospray ionization massspectrometry: addressing analytical problems beyond routine. FreseniusJ. Anal. Chem., 2000; 366: 669-676
  Google Scholar
• 18. Kaufmann P., Black S., Huppertz B.: Endovascular trophoblastinvasion: implications for the pathogenesis of intrauterine growthretardation and preeclampsia. Biol. Reprod., 2003; 69: 1-7
  Google Scholar
• 19. Kim Y.J.: Pathogenesis and promising non-invasive markers forpreeclampsia. Obstet. Gynecol. Sci., 2013; 56: 2-7
  Google Scholar
• 20. Kingsmore S.F.: Multiplexed protein measurement: technologiesand applications of protein and antibody arrays. Nat. Rev. DrugDiscov., 2006; 5: 310-320
  Google Scholar
• 21. Kronborg C.S., Gjedsted J., Vittinghus E., Hansen T.K., AllenJ., Knudsen U.B.: Longitudinal measurement of cytokines in preeclampticand normotensive pregnancies. Acta Obstet. Gynecol.Scand., 2011; 90: 791-796
  Google Scholar
• 22. Lam C., Lim K.H., Karumanchi S.A.: Circulating angiogenic factorsin the pathogenesis and prediction of preeclampsia. Hypertension,2005; 46: 1077-1085
  Google Scholar
• 23. Laudanski P., Lemancewicz A., Kuc P., Charkiewicz K., RamotowskaB., Kretowska M., Jasinska E., Raba G., Karwasik-KajszczarekK., Kraczkowski J., Laudanski T.: Chemokines profiling of patientswith preterm birth. Mediators Inflamm., 2014; 2014: 185758
  Google Scholar
• 24. Laudanski P., Lemancewicz A., Pierzynski P., Akerlund M., LaudanskiT.: Decreased serum level of macrophage inflammatorychemokine-3β/CCL19 in preterm labor and delivery. Eur. J. Obstet.Gynecol. Reprod. Biol., 2006; 124: 23-26
  Google Scholar
• 25. Laudanski P., Zbucka-Kretowska M., Charkiewicz K., WolczynskiS., Wojcik D., Charkiewicz R.: Maternal plasma and amniotic fluidchemokines screening in fetal Down syndrome. Mediators Inflamm.,2014; 2014: 835837
  Google Scholar
• 26. Lee E.S., Oh M.J., Jung J.W., Lim J.E., Seol H.J., Lee K.J., Kim H.J.:The levels of circulating vascular endothelial growth factor andsoluble Flt-1 in pregnancies complicated by preeclampsia. J. KoreanMed. Sci., 2007; 22: 94-98
  Google Scholar
• 27. Liu C., Zhang N., Yu H., Chen Y., Liang Y., Deng H., Zhang Z.: Proteomicanalysis of human serum for finding pathogenic factors andpotential biomarkers in preeclampsia. Placenta, 2011; 32: 168-174
  Google Scholar
• 28. MacLellan W.R., Wang Y., Lusis A.J.: Systems-based approachesto cardiovascular disease. Nat. Rev. Cardiol., 2012; 9: 172-184
  Google Scholar
• 29. Max Planck Institute for plant breeding research. MALDI-TOFTOFMS/MS. https://www.mpipz.mpg.de/44542/MALDI-TOF-TOF_MS_MS (15.03.2014)
  Google Scholar
• 30. Oh K.J., Park J.S., Norwitz E.R., Kim S.M., Kim B.J., Park C.W., JunJ.K., Syn H.C.: Proteomic biomarkers in second trimester amnioticfluid that identify women who are destined to develop preeclampsia.Reprod. Sci., 2012; 19: 694-703
  Google Scholar
• 31. Pawlak M., Schick E., Bopp M.A., Schneider M.J., Oroszlan P.,Ehrat M.: Zeptosens› protein microarrays: a  novel high performancemicroarray platform for low abundance protein analysis.Proteomics, 2002; 2: 383-393
  Google Scholar
• 32. Pinheiro M.B., Martins-Filho O.A., Mota A.P., Alpoim P.N., GodoiL.C., Silveira A.C., Teixeira-Carvalho A., Gomes K.B., Dusse L.M.: Severepreeclampsia goes along with a cytokine network disturbancetowards a systemic inflammatory state. Cytokine, 2013; 62: 165-173
  Google Scholar
• 33. Potter J.M., Nestel P.J.: The hyperlipidemia of pregnancy innormal and complicated pregnancies. Am. J. Obstet. Gynecol., 1979;133: 165-170
  Google Scholar
• 34. Sattar N., Greer I.A.: Pregnancy complications and maternalcardiovascular risk: opportunities for intervention and screening?Br. Med. J., 2002; 325: 157-160
  Google Scholar
• 35. Sauer S., Lange B.M., Gobom J., Nyarsik L., Seitz H., Lehrach H.:Miniaturization in functional genomics and proteomics. Nat. Rev.Genet., 2005; 6: 465-476
  Google Scholar
• 36. Sun L.Z., Yang N.N., De W., Xiao Y.S.: Proteomic analysis of proteinsdifferentially expressed in preeclamptic trophoblasts. Gynecol.Obstet. Invest., 2007; 64: 17-23
  Google Scholar
• 37. Szarka A., Rigo J.Jr., Lazar L., Beko G., Molvarec A.: Circulatingcytokines, chemokines and adhesion molecules in normal pregnancyand preeclampsia determined by multiplex suspension array. BMCImmunol., 2010; 11: 59
  Google Scholar
• 38. VanMeter A.J., Rodriguez A.S., Bowman E.D., Jen J., Harris C.C.,Deng J., Calvert V.S., Silvestri A., Fredolini C., Chandhoke V., PetricoinE.F.3rd, Liotta L.A., Espina V.: Laser capture microdissection andprotein microarray analysis of human non-small cell lung cancer:differential epidermal growth factor receptor (EGFR) phosphorylationevents associated with mutated EGFR compared with wild type.Mol. Cell. Proteomics, 2008; 7: 1902-1924
  Google Scholar
• 39. Watanabe H., Hamada H., Yamada N., Sohda S., Yamakawa-KobayashiK., Yoshikawa H., Arinami T.: Proteome analysis revealselevated serum levels of clusterin in patients with preeclampsia.Proteomics, 2004; 4: 537-543
  Google Scholar
• 40. Weibel K.E., Mor J.R., Fiechter A.: Rapid sampling of yeast cellsand automated assays of adenylate, citrate, pyruvate and glucose-6-phosphate pools. Anal. Biochem., 1974; 58: 208-216
  Google Scholar
• 41. Yarmush M.L., Jayaraman A.: Advances in proteomic technologies.Annu. Rev. Biomed. Eng., 2002; 4: 349-373
  Google Scholar
• 42. Yin P., Zhao X., Li Q., Wang J., Li J., Xu G.: Metabonomics studyof intestinal fistulas based on ultraperformance liquid chromatographycoupled with Q-TOF mass spectrometry (UPLC/Q-TOF MS). J.Proteome Res., 2006; 5: 2135-2143
  Google Scholar
• 43. Young B.C., Levine R.J., Karumanchi S.A.: Pathogenesis of preeclampsia.Annu. Rev. Pathol., 2010; 5: 173-192
  Google Scholar
• 44. Yu X., Schneiderhan-Marra N., Hsu H.Y., Bachmann J., Joos T.O.:Protein microarrays: effective tools for the study of inflammatorydiseases. Methods Mol. Biol., 2009; 577: 199-214
  Google Scholar
• 45. Yu X., Schneiderhan-Marra N., Joos T.O.: Protein microarraysfor personalized medicine. Clin. Chem., 2010; 56: 376-387
  Google Scholar
• 46. Zenobi R.: Single-cell metabolomics: analytical and biologicalperspectives. Science, 2013; 342: 1243259
  Google Scholar
• 47. Zhu H., Snyder M.: Protein chip technology. Curr. Opin. Chem.Biol., 2003; 7: 55-63
  Google Scholar

Full text