medRxivGenetic & Genomic MedicinePreprint
Detection of early-onset severe preeclampsia by cell-free DNA fragmentome
Haiqiang ZhangiD, Longwei QiaoiD, Xintao HuiD, Chunhua ZhangiD, Yu LiniD, Jingyu Zhao, Xiaojuan WuiD, Xiao‐Yan SongiD, Hui Tang, Ying Wen XueiD, Yang SuniD, Rijing Ou, Xinxin WangiD, Yan Zhang, Xin JiniD, Ting WangiD
Abstract
Early-onset severe preeclampsia (EO-PE) is a distinct and highly consequential form of preeclampsia (PE), presenting significant challenges for early detection. Here, we investigated the fragmentation pattern of plasma cell-free DNA (cfDNA) in EO-PE patients. We uncovered that the nucleotide composition at the 5 end (i.e. ends motif) of plasma cfDNA showed a unique pathological preference in EO-PE pregnancies and gestational-psychology preference in healthy pregnancies. By integrating 91 EO-PE specific motifs into a machine-learning model, we achieved accurate prediction of EO-PE development in early pregnancies. Remarkably, our model demonstrated robust performance in an independent cohort of 74 early pregnancies and 1,241 non-invasive prenatal testing (NIPT) samples with ultra-low sequencing depth. Additionally, we revealed that these PE-specific motif signatures lacked tissue specificity, originating extracellularly, and were associated with the abnormal concentration of DNA fragmentation factor subunit beta (DFFB) in EO-PE patients plasma. These findings establish the plasma DNA fragmentome as a non-invasive and cost-effective biomarker that can be simultaneously captured during NIPT for early EO-PE detection and provide valuable insights into cfDNA production mechanisms in preeclampsia patients.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: differential expression
- research focus: variant calling
- approach: machine learning (classical)
- Citations
- 1
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