- Preprint Article
- 10.64898/2026.03.12.26348234
First-Trimester Multi-modal cfDNA Analysis for Prediction of Preterm and Term Preeclampsia
- Mar 13, 2026
- medRxiv
- Rebecca Ertl + 9 more +9
Background: Preeclampsia, which is a leading cause of maternal and perinatal mortality and morbidity, represents a biologically heterogeneous syndrome. First-trimester screening with the Fetal Medicine Foundation competing-risks model enables prevention of preterm preeclampsia through aspirin prophylaxis but depends on Doppler velocimetry and biochemical measurements that limit scalability and offer limited discrimination for term disease. A unified, molecular first trimester test capable of stratifying risk across the full clinical spectrum of preeclampsia has not been established. Objective: To determine whether multi-modal, tissue-resolved analysis of first trimester circulating cell-free DNA (cfDNA), obtained during routine non-invasive prenatal testing (NIPT), enables early prediction of both preterm and term preeclampsia. Study Design: This nested case-control study included 125 singleton pregnancies sampled at 11-14 weeks' gestation after quality control (48 controls, 30 preterm preeclampsia, 47 term preeclampsia). For 80 pregnancies, matched placental villi and maternal buffy coat samples were available to derive tissue reference profiles. Plasma cfDNA underwent multi-modal sequencing using Oxford Nanopore Technologies, enabling tissue-resolved analysis of fragmentomic and epigenetic signatures. Separate ensemble machine-learning classifiers were developed for preterm (<37 weeks) and term (>=37 weeks) preeclampsia using stratified 10-fold cross-validation. Model discrimination was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity at predefined specificity thresholds, and comparison with the FMF first-trimester risk score. A population-level simulation of 100,000 pregnancies, applying incidence point estimates of 2.5% for preterm and 7.5% for term PE, was used to derive predictive values and likelihood ratios. Results: The multi-modal cfDNA classifier achieved an AUROC (95% CI) of 0.85 (0.77-0.91) for preterm preeclampsia and 0.84 (0.76-0.91) for term preeclampsia. The FMF score yielded an AUROC of 0.80 (0.70-0.89) for preterm and 0.53 (0.43-0.63) for term PE. At 80% specificity, cfDNA sensitivity was 70.5% for preterm and 72.1% for term preeclampsia, demonstrating improved discrimination for term disease compared with FMF screening. In simulated population-level analysis, positive likelihood ratios were 4.25 (preterm) and 3.83 (term), with negative likelihood ratios of 0.21 and 0.34, respectively, supporting meaningful post-test risk stratification and strong rule-out performance. Conclusion: First-trimester multi-modal, tissue-resolved cfDNA analysis enables early risk stratification across the full clinical spectrum of preeclampsia from a single routine blood sample. Compared with FMF screening, this approach can potentially improve discrimination for term preeclampsia while providing incremental improvement for preterm disease. The potential for integration into existing NIPT workflows offers a scalable pathway toward unified precision prevention, supporting timely aspirin prophylaxis for preterm preeclampsia and risk-adapted surveillance strategies for term disease.
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