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Updated: Aug 17, 2026
Preparation of Frozen Non-Human Primate Fetal Islets for Combined Single Nuclei RNA-Sequencing and ATAC-Sequencing, and Bulk Metabolomics
Published on: November 8, 2024
Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction
Yan Cao1,2, Wenjing Hao3, Yan Wang1,2
1Department of Laboratory Medicine, Beijing Obstetrics and Gynecology Hospital, Beijing Maternal and Child Health Care Hospital, Capital Medical University, Beijing, China.
Background:
Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms.
Methods:
Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n = 11), persistent FGR (n = 9), and healthy controls (n = 13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n = 69).
Results:
Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p < 0.001).
Conclusions:
This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular signatures reflecting the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.
