Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction

Kaspar Ratnik; Kristiina Rull; Oliver Aasmets; Triin Kikas; Ele Hanson; Kalle Kisand; Krista Fischer; Maris Laan

doi:10.3389/fcvm.2022.932480

Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction

Front Cardiovasc Med. 2022 Jul 27:9:932480. doi: 10.3389/fcvm.2022.932480. eCollection 2022.

Authors

Kaspar Ratnik^{1

2}, Kristiina Rull^{1

3

4}, Oliver Aasmets⁵, Triin Kikas¹, Ele Hanson^{3

4}, Kalle Kisand⁶, Krista Fischer^{5

7}, Maris Laan¹

Affiliations

¹ Department of Biomedicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia.
² SYNLAB Eesti OÜ, Tallinn, Estonia.
³ Women's Clinic, Tartu University Hospital, Tartu, Estonia.
⁴ Department of Obstetrics and Gynaecology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.
⁵ Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
⁶ Department of Internal Medicine, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.
⁷ Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia.

Abstract

Preeclampsia (PE) is a common pregnancy-linked disease, causing preterm births, complicated deliveries, and health consequences for mothers and offspring. We have previously developed 6PLEX, a multiplex assay that measures PE-related maternal serum biomarkers ADAM12, sENG, leptin, PlGF, sFlt-1, and PTX3 in a single test tube. This study investigated the potential of 6PLEX to develop novel PE prediction models for early pregnancy. We analyzed 132 serum samples drawn at 70-275 gestational days (g days) from 53 pregnant women (PE, n = 22; controls, n = 31). PE prediction models were developed using a machine learning strategy based on the stepwise selection of the most significant models and incorporating parameters with optimal resampling. Alternative models included also placental FLT1 rs4769613 T/C genotypes, a high-confidence risk factor for PE. The best performing PE prediction model using samples collected at 70-98 g days comprised of PTX3, sFlt-1, and ADAM12, the subject's parity and gestational age at sampling (AUC 0.94 [95%CI 0.84-0.99]). All cases, that developed PE several months later (onset 257.4 ± 15.2 g days), were correctly identified. The model's specificity was 80% [95%CI 65-100] and the overall accuracy was 88% [95%CI 73-95]. Incorporating additionally the placental FLT1 rs4769613 T/C genotype data increased the prediction accuracy to 93.5% [AUC = 0.97 (95%CI 0.89-1.00)]. However, 6PLEX measurements of samples collected at 100-182 g days were insufficiently informative to develop reliable PE prediction models for mid-pregnancy (accuracy <75%). In summary, the developed model opens new horizons for first-trimester PE screening, combining the easily standardizable 6PLEX assay with routinely collected antenatal care data and resulting in high sensitivity and specificity.

Keywords: 6PLEX; PTX3; Preeclampsia; biomarkers; early pregnancy; multiplex immunoassay; risk prediction; statistical modeling.