Objective To test the hypothesis that a combination of PP13, PAPP-A and first-trimester uterine artery Doppler would improve the prediction of preeclampsia. Methods This is a prospective cohort study of pregnant women followed from the first-trimester to delivery. PP13 and PAPPA were determined by immunoassay of maternal serum at 11 – 14 weeks’, when uterine artery Doppler measurements were assessed. Cases identified with any form of preeclampsiawere compared with a control group without preeclampsia. The sensitivity of each marker or their combinations in predicting preeclampsia for different fixed false positive rates was calculated from the ROC curves. Results Forty two women were diagnosed with preeclampsia and 410 women with pregnancies not complicated by preeclampsia were used as controls. For a fixed false positive rate (FPR) of 20%, PP13, PAPP-A and mean uterine artery pulsatility index identified 49%, 58% and 62% respectively, of women who developed any form of preeclampsia. PP13 was best in predicting early onset preeclampsia with a sensitivity of 79% at a 20% FPR.Combinations of the three first trimester assessments did not improve the prediction of preeclampsia in later pregnancy. Conclusion First-trimester PP13, PAPP-A and uterine artery PI are reasonable, individual predictors of women at risk to develop preeclampsia. Combinations of these assessments do not further improve the prediction of preeclampsia

Objective We tested the hypothesis that first-trimester metabolic biomarkers offered a unique profile in women with preeclampsia (PE) in the second half of pregnancy, compared to controls. Method We conducted a nested-case control study within a prospective cohort of pregnant women followed from the first-trimester to delivery. Cases were those who developed PEat any gestational age and these were compared with a control group without adverse pregnancy outcome, matched for gestational age within three days. We analyzed maternal blood obtained at 11–14 weeks’ gestation for 40 acylcarnitine species (C2-C18 saturated, unsaturated, and hydroxylated) and 32 amino acids by LC tandem mass spectrometry. Logistic regression modeling estimated the association of each metabolite with development ofPE. Results We compared 41 cases with preeclampsia with 41 controls, and found four metabolites (Hydroxyhexanoylcarnitine, alanine, phenylalanine, and glutamate) that were significantly higher in the cases withPE. The area under the curve (AUC) using these metabolites individually to predict PE varied from 0.77–0.80; and when combined, the AUC improved to 0.82(95% CI 0.80–0.85) for all cases of PEand 0.85 (95% CI 0.76–0.91) for early onsetPE. Conclusion Our findings suggest a potential role for first-trimester metabolomics in screening for PE.

Objective To estimate the utility of first-trimester 3D placental volume and vascular flow indices in the prediction of adverse pregnancy outcomes. Methods A prospective cohort study including women with singleton pregnancies seen between 11 – 14 weeks’ as part of a screening program for aneuploidy. Placental volume and vascularization indices were obtained using 3D power Doppler imaging and the VOCAL technique. Placental volume (PV), Vascularization Index (VI), Flow Index (FI) and Vascularization Flow Index (VFI) were calculated. The adverse pregnancy outcomes investigated include preeclampsia (PE), gestational hypertension (GH) and small for gestational age (SGA). The predictive ability of each variable was evaluated using receiver-operating characteristic (ROC) curves. Results Of 388 women included, PE was seen in 30 (7.7%), GH in 37 (9.0%) and SGA in 31 (8.0%). Placental volume was not significantly different between the pregnancies with adverse outcomes and those without. The mean values of the VI and VFI were significantly lower in the pregnancies that developed PE but not in GH or SGA. The area under the ROC curve for the prediction of PE was 0.71, 0.69 and 0.70 for VI, FI and VFI, respectively. Conclusion The study confirms lower 3D power Doppler vascular flow indices in pregnancies that develop PE. The discriminatory ability of using these indices alone for predicting PE appears modest.

Objective To determine if a simplified model for predicting pre-eclampsia can be developed by combining first trimester serum analytes, PAPP-A and free β-hCG, and maternal characteristics. Methods A retrospective cohort study of patients seen for first-trimester aneuploidy screening from 2003–2009. The 5th, 10th, 90th and 95th percentiles for the analyte-MoMs for our population were determined and evaluated for association with pre-eclampsia. Univariate and backward stepwise logistic regression analyses were performed and the area under the ROC curves (AUC) used to determine the best models for predicting pre-eclampsia. Results Among 4,020 women meeting the inclusion criteria, outcome data was available for 3,716 (93%). There were 293 cases of pre-eclampsia. The final model identified a history of pre-gestational diabetes (aOR 2.6, 95% CI 1.7–3.9), chronic hypertension (aOR 2.6, 95% CI 1.7–3.9), maternal BMI >25 (aOR 2.5, 95% CI 1.9–3.4), African American race (aOR 1.8, 95% CI 1.3–2.6), and PAPP-A MoM <10th percentile (aOR 1.6, 95% CI 1.1–2.4) to be significant predictors of pre-eclampsia. (AUC= 0.70, 95% CI 0.65–0.72) Conclusion Low first-trimester PAPP-A levels are associated with the development of pre-eclampsia; however, the model was only modestly efficient in its predictive ability.

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