A label-free selected reaction monitoring workflow identifies a subset of pregnancy specific glycoproteins as potential predictive markers of early-onset pre-eclampsia

Molecular and Cellular Proteomics

Volumn 12, Issue 11, 2013, Pages 3148-3159

  Blankley, Richard T ^a,b   Fisher, Christal ^a,b   Westwood, Melissa ^a   North, Robyn ^c   Baker, Philip N ^a   Walker, Michael J ^a   Williamson, Andrew ^a   Whetton, Anthony D ^a   Lin, Wanchang ^b   McCowan, Lesley ^d   Roberts, Claire T ^e   Cooper, Garth J S ^b   Unwin, Richard D ^b   Myers, Jenny E ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b MANCHESTER UNIVERSITY NHS FOUNDATION TRUST   (United Kingdom)

^c KING'S COLLEGE LONDON   (United Kingdom)

^d UNIVERSITY OF AUCKLAND   (New Zealand)

^e UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER; CHEMOKINE; CXCL7 CHEMOKINE; CYSTEINE; PREGNANCY SPECIFIC BETA1 GLYCOPROTEIN; PREGNANCY SPECIFIC BETA1 GLYCOPROTEIN 9; UNCLASSIFIED DRUG;

ADULT; AGED; ANALYTIC METHOD; ARTICLE; CONTROLLED STUDY; DILUTION CURVE; ENZYME LINKED IMMUNOSORBENT ASSAY; FEMALE; GESTATIONAL AGE; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; HUMAN; MAJOR CLINICAL STUDY; MASS SPECTROMETRY; NULLIPARA; PREDICTIVE VALUE; PREECLAMPSIA; PREGNANT WOMAN; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN BLOOD LEVEL; PROTEIN CLEAVAGE; SELECTED REACTION MONITORING WORKFLOW; WORKFLOW;

ADOLESCENT; ADULT; AMINO ACID SEQUENCE; AUTOMATION; BETA-THROMBOGLOBULIN; BIOLOGICAL MARKERS; CHROMATOGRAPHY, HIGH PRESSURE LIQUID; COHORT STUDIES; EARLY DIAGNOSIS; ENZYME-LINKED IMMUNOSORBENT ASSAY; FEMALE; GLYCOPROTEINS; HUMANS; MOLECULAR SEQUENCE DATA; PRE-ECLAMPSIA; PREGNANCY; PREGNANCY PROTEINS; PREGNANCY TRIMESTER, SECOND; PROSPECTIVE STUDIES; PROTEOMICS; TANDEM MASS SPECTROMETRY; WORKFLOW; YOUNG ADULT;

EID: 84887038366     PISSN: 15359476     EISSN: 15359484     Source Type: Journal    
DOI: 10.1074/mcp.M112.026872     Document Type: Article

References (26)

1. Carr, S. A., and Anderson, L. (2008) Protein quantitation through targeted mass spectrometry: The way out of biomarker purgatory? Clin. Chem. 54, 1749-1752.
2. Makawita, S., and Diamandis, E. P. (2010) The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry- based approaches: current strategies for candidate verification. Clin. Chem. 56, 212-222.
3. Stahl-Zeng, J., Lange, V., Ossola, R., Eckhardt, K., Krek, W., Aebersold, R., and Domon, B. (2007) High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites. Mol. Cell. Proteomics 6, 1809-1817. (Pubitemid 350031682)
4. Kuzyk, M. A., Smith, D., Yang, J., Cross, T.J., Jackson, A.M., Hardie, D. B., Anderson, N. L., and Borchers, C. H. (2009) Multiple reaction monitoringbased, multiplexed, absolute quantitation of 45 proteins in human plasma. Mol. Cell. Proteomics 8, 1860-1877.
5. Keshishian, H., Addona, T., Burgess, M., Kuhn, E., and Carr, S. A. (2007) Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution. Mol. Cell. Proteomics 6, 2212-2229.
6. Anderson, L., and Hunter, C. L. (2006) Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins. Mol. Cell. Proteomics 5, 573-588.
7. Zhi, W., Wang, M., and She, J. X. (2011) Selected reaction monitoring (SRM) mass spectrometry without isotope labeling can be used for rapid protein quantification. Rapid Commun. Mass Spectrom. 25, 1583-1588.
8. Tang, H. Y., Beer, L. A., Barnhart, K. T., and Speicher, D. W. (2011) Rapid verification of candidate serological biomarkers using gel-based, labelfree multiple reaction monitoring. J. Proteome Res. 10, 4005-4017.
9. Wilkinson, H. (2011) Saving mothers' lives. Reviewing maternal deaths to make motherhood safer: 2006-2008. Br. J. Obs. GYN. 118:1402-1403; discussion 1403-1404.
10. Centre for Maternal and Child Enquiries (CMACE). (2011). Perinatal Mortality 2009: United Kingdom. (CMACE, London).
11. Roberts, J.M., Taylor, R.N., Musci, T.J., Rodgers, G.M., Hubel, C.A., and McLaughlin, M.K. (1989) Preeclampsia: An endothelial cell disorder. Am. J. Obstet. Gynecol. 161, 1200-1204. (Pubitemid 20007682)
12. Myatt, L., Clifton, R. G., Roberts, J. M., Spong, C. Y., Hauth, J. C., Varner, M. W., Thorp, J. M. Jr., Mercer, B. M., Peaceman, A. M., Ramin, S. M., Carpenter, M. W., Iams, J. D., Sciscione, A., Harper, M., Tolosa, J. E., Saade, G., Sorokin, Y., and Anderson, G. D. (2012) First-trimester prediction of preeclampsia in nulliparous women at low risk. Obstet. Gynecol. 119, 1234-1242.
13. Myers, J. E., Kenny, L., McCowan, L., Chan, E., Dekker, G., Poston, L., Simpson, N., and North, R. (2013). Angiogenic factors combined with clinical risk factors to predict preterm pre-eclampsia in nulliparous women: A predictive test accuracy study. Br. J. Obstet. Gyn., DOI: 10.1111/1471-0528.12195.
14. Myers, J. E., Tuytten, R., Thomas, G., Laroy, W., Kas, K., Vanpoucke, G., Roberts, C. T., Kenny, L. C., Simpson, N. A., Baker, P. N., and North, R. A. (2013) Integrated proteomics pipeline yields novel biomarkers for predicting preeclampsia. Hypertension 61, 1281-1288.
15. North, R. A., McCowan, L. M., Dekker, G. A., Poston, L., Chan, E. H., Stewart, A. W., Black, M. A., Taylor, R. S., Walker, J. J., Baker, P. N., and Kenny, L. C. (2011) Clinical risk prediction for pre-eclampsia in nulliparous women: development of model in international prospective cohort. BMJ 342, d1875.
16. Shilov, I. V., Seymour, S. L., Patel, A. A., Loboda, A., Tang, W. H., Keating, S. P., Hunter, C. L., Nuwaysir, L. M., and Schaeffer, D. A. (2007) The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra. Mol. Cell. Proteomics 6, 1638-1655. (Pubitemid 47506173)
17. MacLean, B., Tomazela, D. M., Shulman, N., Chambers, M., Finney, G.L., Frewen, B., Kern, R., Tabb, D. L., Liebler, D. C., and MacCoss, M. J. (2010) Skyline: An open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966-968.
18. Sarkar, D. (2008). Lattice: Multivariate Data Visualization with R (New York, U.S.A., Springer).
19. Mischak, H., Allmaier, G., Apweiler, R., Attwood, T., Baumann, M., Benigni, A., Bennett, SE., Bischoff, R., Bongcam-Rudloff, E., Capasso, G., Coon, J. J., D'Haese, P., Dominiczak, A. F., Dakna, M., Dihazi, H., Ehrich, J. H., Fernandez-Llama, P., Fliser, D., Frokiaer, J., Garin, J., Girolami, M., Hancock, W. S., Haubitz, M., Hochstrasser, D., Holman, R. R., Ioannidis, J. P., Jankowski, J., Julian, B. A., Klein, J. B., Kolch, W., Luider, T., Massy, Z., Mattes, W. B., Molina, F., Monsarrat, B., Novak, J., Peter, K., Rossing, P., Sánchez-Carbayo, M., Schanstra, J. P., Semmes, O. J., Spasovski, G., Theodorescu, D., Thongboonkerd, V., Vanholder, R., Veenstra, T. D., Weissinger, E., Yamamoto, T., Vlahou, A. (2010). Recommendations for biomarker identification and qualification in clinical proteomics. Sci. Transl. Med. 2, 46ps42.
20. Kroksveen, A. C., Aasebo, E., Vethe, H., Van Pesch, V., Franciotta, D., Teunissen, C. E., Ulvik, R. J., Vedeler, C., Myhr, K. M., Barsnes, H., and Berven, F. S. (2013) Discovery and initial verification of differentially abundant proteins between multiple sclerosis patients and controls using iTRAQ and SID-SRM. J. Proteomics 78, 312-325.
21. Picotti, P., Rinner, O., Stallmach, R., Dautel, F., Farrah, T., Domon, B., Wenschuh, H., and Aebersold, R. (2010) High-throughput generation of selected reaction-monitoring assays for proteins and proteomes. Nat. Methods 7, 43-46.
22. Brun, V., Dupuis, A., Adrait, A., Marcellin, M., Thomas, D., Court, M., Vandenesch, F., and Garin, J. (2007) Isotope-labeled protein standards: Toward absolute quantitative proteomics. Mol. Cell. Proteomics 6, 2139-2149.
23. Zhao, Y., Jia, W., Sun, W., Jin, W., Guo, L., Wei, J., Ying, W., Zhang, Y., Xie, Y., Jiang, Y., He, F., and Qian, X. (2010) Combination of improved (18)O incorporation and multiple reaction monitoring: A universal strategy for absolute quantitative verification of serum candidate biomarkers of liver cancer. J. Proteome Res. 9, 3319-3327.
24. Camolotto, S., Racca, A., Rena, V., Nores, R., Patrito, L. C., Genti-Raimondi, S., and Panzetta-Dutari, G. M. (2010) Expression and transcriptional regulation of individual pregnancy-specific glycoprotein genes in differentiating trophoblast cells. Placenta 31, 312-319.
25. Addona, T. A., Abbatiello, S. E., Schilling, B., Skates, S. J., Mani, D. R., Bunk, D. M., Spiegelman, C. H., Zimmerman, L. J., Ham, A. J., Keshishian, H., Hall, S. C., Allen, S., Blackman, R. K., Borchers, C. H., Buck, C., Cardasis, H. L., Cusack, M. P., Dodder, N. G., Gibson, B. W., Held, J. M., Hiltke, T., Jackson, A., Johansen, E. B., Kinsinger, C. R., Li, J., Mesri, M., Neubert, T. A., Niles, R. K., Pulsipher, T. C., Ransohoff, D., Rodriguez, H., Rudnick, P. A., Smith, D., Tabb, D. L., Tegeler, T. J., Variyath, A. M., Vega-Montoto, L. J., Wahlander, A., Waldemarson, S., Wang, M., Whiteaker, J. R., Zhao, L., Anderson, N. L., Fisher, S. J., Liebler, D. C., Paulovich, A. G., Regnier, F. E., Tempst, P., and Carr, S. A. (2009) Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma. Nat. Biotechnol. 27, 633-641.
26. Percy, A. J., Chambers, A. G., Yang, J., Domanski, D., and Borchers, C. H. (2012) Comparison of standard- And nano-flow liquid chromatography platforms for MRM-based quantitation of putative plasma biomarker proteins. Anal. Bioanal. Chem. 404, 1089-1101.