Preeclampsia risk prediction from prenatal cell-free DNA screening

Preeclampsia is characterized by placental dysfunction and results in significant morbidity, but reliable early prediction remains challenging. We investigated whether clinically obtained prenatal cell-free DNA (cfDNA) screening (PDNAS) using whole-genome sequencing (WGS) data can be leveraged to predict preeclampsia risk early in pregnancy (≤16 weeks). Using 1,854 routinely collected clinical PDNAS samples (median, 12.1 weeks) with low-coverage (0.5×) WGS data, we developed a framework to quantify maternal and fetal tissue signatures using nucleosome accessibility, revealing early placental and endothelial dysfunction. These signatures informed a prediction model for preeclampsia risk, which achieved a validation performance of 0.85 area under the receiver operating characteristic curve (AUC) (81% sensitivity at 80% specificity) for preterm phenotypes several months prior to disease onset in a separate cohort of 831 consecutively collected samples, and subsequently confirmed in an external cohort of 141 samples (AUC 0.84, 79% sensitivity). We demonstrate that assessment of cfDNA nucleosome accessibility from early-pregnancy cfDNA sequence data enables the detection of early placental and endothelial-tissue aberrations and may aid in the determination of preeclampsia risk.

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Publication Details

Journal
Nature Medicine
Published
2025-02-12
DOI
https://doi.org/10.1038/s41591-025-03509-w
Citations
17
Primary Topic
Prenatal Screening and Diagnostics
Type
article
Field-Weighted Citation Impact
59.40

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article

Preeclampsia risk prediction from prenatal cell-free DNA screening

L. Chen, Sarah Rosen, Brice G. Colbert, Patricia C. Galipeau et al.
17 citations
Nature Medicine
Prenatal Screening and Diagnostics
59.40
article

Preeclampsia risk prediction from prenatal cell-free DNA screening

L. Chen, Sarah Rosen, Brice G. Colbert, Patricia C. Galipeau, Jonathan Reichel, Michael Yang, Christina M. Lockwood, Gavin Ha, Robert D. Patton, Shreeram Akilesh, Colin C. Pritchard, Anna-Lisa Doebley, Raj Shree, Mohamed Adil, Thomas Persse, Teodora Kolarova, Erin Kawelo, Cara L. Tobey
article en
17 citations

Abstract

Preeclampsia is characterized by placental dysfunction and results in significant morbidity, but reliable early prediction remains challenging. We investigated whether clinically obtained prenatal cell-free DNA (cfDNA) screening (PDNAS) using whole-genome sequencing (WGS) data can be leveraged to predict preeclampsia risk early in pregnancy (≤16 weeks). Using 1,854 routinely collected clinical PDNAS samples (median, 12.1 weeks) with low-coverage (0.5×) WGS data, we developed a framework to quantify maternal and fetal tissue signatures using nucleosome accessibility, revealing early placental and endothelial dysfunction. These signatures informed a prediction model for preeclampsia risk, which achieved a validation performance of 0.85 area under the receiver operating characteristic curve (AUC) (81% sensitivity at 80% specificity) for preterm phenotypes several months prior to disease onset in a separate cohort of 831 consecutively collected samples, and subsequently confirmed in an external cohort of 141 samples (AUC 0.84, 79% sensitivity). We demonstrate that assessment of cfDNA nucleosome accessibility from early-pregnancy cfDNA sequence data enables the detection of early placental and endothelial-tissue aberrations and may aid in the determination of preeclampsia risk.

Nature MedicineVol. 31(4)
University of Washington (US), Fred Hutch Cancer Center (US), Brotman Baty Institute (US)
University of Washington, Magee-Womens Research Institute, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Institute of General Medical Sciences, Office of Research Infrastructure Programs, National Institutes of Health, National Center for Medical Rehabilitation Research
Good health and well-being
Openalex Percentile: Top 0%
Prenatal Screening and Diagnostics
59.40
DOIOpen Access PDFOpenAlex
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