title: Integrated proteomics pipeline yields novel biomarkers for predicting preeclampsia.
abstract: Preeclampsia, 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.
authors.affiliation: Maternal & Fetal Health Research Centre, Centre, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK. Jenny.myers@manchester.ac.uk
authors.forename: Jenny E
authors.initials: JE
authors.lastname: Myers
authors.forename: Robin
authors.initials: R
authors.lastname: Tuytten
authors.forename: Grégoire
authors.initials: G
authors.lastname: Thomas
authors.forename: Wouter
authors.initials: W
authors.lastname: Laroy
authors.forename: Koen
authors.initials: K
authors.lastname: Kas
authors.forename: Griet
authors.initials: G
authors.lastname: Vanpoucke
authors.forename: Claire T
authors.initials: CT
authors.lastname: Roberts
authors.forename: Louise C
authors.initials: LC
authors.lastname: Kenny
authors.forename: Nigel A B
authors.initials: NA
authors.lastname: Simpson
authors.forename: Philip N
authors.initials: PN
authors.lastname: Baker
authors.forename: Robyn A
authors.initials: RA
authors.lastname: North
mesh_terms: D000328:Adult; D001315:Australia / Q000453:epidemiology; D015415:Biomarkers / Q000097:blood*; D001794:Blood Pressure / Q000502:physiology; D005260:Female; D005500:Follow-Up Studies; D005865:Gestational Age; D006133:Growth Substances; D006801:Humans; D015994:Incidence; D007231:Infant, Newborn; D008297:Male; D013058:Mass Spectrometry; D000072483:Placenta Growth Factor; D011225:Pre-Eclampsia / Q000097:blood* / Q000175:diagnosis / Q000453:epidemiology; D011237:Predictive Value of Tests; D011247:Pregnancy; D011256:Pregnancy Outcome; D011257:Pregnancy Proteins / Q000097:blood*; D011379:Prognosis; D011446:Prospective Studies; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012307:Risk Factors; D018608:Ultrasonography, Doppler; D055988:Uterine Artery / Q000000981:diagnostic imaging / Q000503:physiopathology
chemical_list: D015415:Biomarkers; D006133:Growth Substances; C000608036:PGF protein, human; D011257:Pregnancy Proteins; D000072483:Placenta Growth Factor
keywords: mass spectrometry; preeclampsia; screening; selective reaction monitoring; sensitivity; specificity