Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/79344
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dc.contributor.authorMyers, J.en
dc.contributor.authorTuytten, R.en
dc.contributor.authorThomas, G.en
dc.contributor.authorLaroy, W.en
dc.contributor.authorKas, K.en
dc.contributor.authorVanpoucke, G.en
dc.contributor.authorRoberts, C.en
dc.contributor.authorKenny, L.en
dc.contributor.authorSimpson, N.en
dc.contributor.authorBaker, P.en
dc.contributor.authorNorth, R.en
dc.date.issued2013en
dc.identifier.citationHypertension, 2013; 61(6):1281-1329en
dc.identifier.issn0194-911Xen
dc.identifier.issn1524-4563en
dc.identifier.urihttp://hdl.handle.net/2440/79344-
dc.description.abstractPreeclampsia, a hypertensive pregnancy complication, is largely unpredictable in healthy nulliparous pregnant women. Accurate preeclampsia prediction in this population would transform antenatal care. To identify novel protein markers relevant to the prediction of preeclampsia, a 3-step mass spectrometric work flow was applied. On selection of candidate biomarkers, mostly from an unbiased discovery experiment (19 women), targeted quantitation was used to verify and validate candidate biomarkers in 2 independent cohorts from the SCOPE (SCreening fOr Pregnancy Endpoints) study. Candidate proteins were measured in plasma specimens collected at 19 to 21 weeks’ gestation from 100 women who later developed preeclampsia and 200 women without preeclampsia recruited from Australia and New Zealand. Protein levels (n=25), age, and blood pressure were then analyzed using logistic regression to identify multimarker models (maximum 6 markers) that met predefined criteria: sensitivity ≥50% at 20% positive predictive value. These 44 algorithms were then tested in an independent European cohort (n=300) yielding 8 validated models. These 8 models detected 50% to 56% of preeclampsia cases in the training and validation sets; the detection rate for preterm preeclampsia cases was 80%. Validated models combine insulin-like growth factor acid labile subunit and soluble endoglin, supplemented with maximally 4 markers of placental growth factor, serine peptidase inhibitor Kunitz type 1, melanoma cell adhesion molecule, selenoprotein P, and blood pressure. Predictive performances were maintained when exchanging mass spectrometry measurements with ELISA measurements for insulin-like growth factor acid labile subunit. In conclusion, we demonstrated that biomarker combinations centered on insulin-like growth factor acid labile subunit have the potential to predict preeclampsia in healthy nulliparous women.en
dc.description.statementofresponsibilityJenny E. Myers, Robin Tuytten, Grégoire Thomas, Wouter Laroy, Koen Kas, Griet Vanpoucke, Claire T. Roberts, Louise C. Kenny, Nigel A.B. Simpson, Philip N. Baker and Robyn A. Northen
dc.language.isoenen
dc.publisherLippincott Williams & Wilkinsen
dc.rights© 2013 American Heart Association, Inc.en
dc.subjectMass spectrometry; preeclampsia; screening; selective reaction monitoring; sensitivity; specificityen
dc.titleIntegrated proteomics pipeline yields novel biomarkers for predicting preeclampsiaen
dc.typeJournal articleen
dc.identifier.rmid0020130272en
dc.identifier.doi10.1161/HYPERTENSIONAHA.113.01168en
dc.identifier.pubid18985-
pubs.library.collectionObstetrics and Gynaecology publicationsen
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidRoberts, C. [0000-0002-9250-2192]en
Appears in Collections:Obstetrics and Gynaecology publications

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