Background: To explore the use of maternal urine proteome for the identification of preeclampsia biomarkers. Methods: Maternal urine samples from women with and without preeclampsia were used for protein discovery followed by a validation study. The targeted proteins of interest were then measured in urine samples collected at 20–24 and 30–34 weeks among nine women who developed preeclampsia, one woman with fetal growth restriction, and 20 women with uncomplicated pregnancies from a longitudinal study. Protein identification and quantification was obtained using liquid chromatography–tandem mass spectrometry (LC–MS/MS). Results: Among the 1108 urine proteins quantified in the discovery study, 21 were upregulated in preeclampsia and selected for validation. Nineteen (90%) proteins were confirmed as upregulated in preeclampsia cases. Among them, two proteins, ceruloplasmin and serpin A7, were upregulated at 20–24 weeks and 30–34 weeks of gestation (p < 0.05) in cases of preeclampsia, and could have served to identify 60% of women who subsequently developed preeclampsia and/or fetal growth restriction at 20–24 weeks of gestation, and 78% at 30–34 weeks, for a false-positive rate of 10%. Conclusions: Proteomic profiling of maternal urine can differentiate women with and without preeclampsia. Several proteins including ceruloplasmin and serpin A7 are upregulated in maternal urine before the diagnosis of preeclampsia and potentially fetal growth restriction.
Objectives
Placental growth factor (PlGF) is used for first-trimester preeclampsia screening and could be combined with other biochemical markers for Down syndrome screening. We aim to estimate the predictive value of the combination of pregnancy-associated plasma protein (PAPP-A), free β-human chorionic gonadotropin (free β-hCG), placental growth factor (PlGF) and α-fetoprotein (AFP) with and without nuchal translucency.
Methods
Singleton pregnancies recruited at 11–14 weeks and followed until delivery. The four maternal markers were measured using Kryptor (ThermoFisher-BRAHMS) and adjusted for gestational age and maternal characteristics. The risk of Down syndrome was calculated using the Fetal Medicine Foundation algorithm and multivariate linear regression analyses in all cases and in 2,200 controls. Receiver-operator characteristic (ROC) curves were used to calculate the detection and false-positive rates.
Results
Twenty-six (0.2%) cases of Down syndrome were diagnosed among 13,386 participants. The combination of the four biomarkers could have detected 88% (95% CI: 72–97%) of the cases at a false-positive rate of 13% (95% CI: 12–15%). The addition of nuchal translucency would have increased the detection rate to 96% (95% CI: 82–99%) at a false-positive rate of 4% (95% CI: 4–5%) using a 1:300 cut-off and to 100% (95% CI: 89–100%) at a false-positive rate of 6% (95% CI: 5–8%) using a 1:500 cut-off.
Conclusions
First-trimester screening using biochemical markers allows the identification of approximately 88% of Down syndrome cases for a false-positive rate of 13%. The addition of nuchal translucency raises the detection rate above 95% with a false-positive rate below 5%.
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