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Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363612/ https://www.ncbi.nlm.nih.gov/pubmed/35966513 http://dx.doi.org/10.3389/fcvm.2022.932480 |
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author | Ratnik, Kaspar Rull, Kristiina Aasmets, Oliver Kikas, Triin Hanson, Ele Kisand, Kalle Fischer, Krista Laan, Maris |
author_facet | Ratnik, Kaspar Rull, Kristiina Aasmets, Oliver Kikas, Triin Hanson, Ele Kisand, Kalle Fischer, Krista Laan, Maris |
author_sort | Ratnik, Kaspar |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9363612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93636122022-08-11 Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction Ratnik, Kaspar Rull, Kristiina Aasmets, Oliver Kikas, Triin Hanson, Ele Kisand, Kalle Fischer, Krista Laan, Maris Front Cardiovasc Med Cardiovascular Medicine 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. Frontiers Media S.A. 2022-07-27 /pmc/articles/PMC9363612/ /pubmed/35966513 http://dx.doi.org/10.3389/fcvm.2022.932480 Text en Copyright © 2022 Ratnik, Rull, Aasmets, Kikas, Hanson, Kisand, Fischer and Laan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Ratnik, Kaspar Rull, Kristiina Aasmets, Oliver Kikas, Triin Hanson, Ele Kisand, Kalle Fischer, Krista Laan, Maris Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction |
title | Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction |
title_full | Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction |
title_fullStr | Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction |
title_full_unstemmed | Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction |
title_short | Novel Early Pregnancy Multimarker Screening Test for Preeclampsia Risk Prediction |
title_sort | novel early pregnancy multimarker screening test for preeclampsia risk prediction |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9363612/ https://www.ncbi.nlm.nih.gov/pubmed/35966513 http://dx.doi.org/10.3389/fcvm.2022.932480 |
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