Multi-Omics Insights into Maternal-Fetal Immune Tolerance in Recurrent Pregnancy Loss

Overview

Recurrent pregnancy loss (RPL) involves complex dysregulation of maternal-fetal immune tolerance and altered immune cell interactions at the decidua. Multi-omics approaches reveal mechanistic heterogeneity, immune-metabolic signatures, and microbiome influences, highlighting potential biomarkers and pathways for improved risk stratification and individualized management.

Background

RPL affects 1% to 5% of reproductive-age women and is defined variably by professional societies, typically as two or more pregnancy losses. Its etiology is multifactorial, including chromosomal abnormalities, immune dysregulation, endocrine and anatomical factors, with many cases remaining unexplained. Traditional single-omics methods inadequately capture the complex molecular networks involved, necessitating integrated multi-omics and systems biology approaches. These approaches aim to elucidate immune-metabolic-microbiome interactions at the maternal-fetal interface to improve mechanistic understanding and clinical stratification.

Data Highlights

Multi-omics profiling modalities applied to RPL include genomics, epigenomics, single-cell and spatial transcriptomics, proteomics, metabolomics, microbiome analyses, and immunomics. Key findings include chromosomal abnormalities linked to embryonic failure, aberrant DNA methylation and imprinting, altered decidual immune cell composition (uNK cells, macrophages, Treg, Th17), immune-metabolic signatures impairing trophoblast function, and gut-reproductive axis influences on systemic immunity. Computational integration methods such as WGCNA, MOFA, and deep learning facilitate subtype classification and risk prediction, though current studies are limited by small cohorts and cross-platform heterogeneity.

Key Findings

• Genomic studies associate chromosomal abnormalities and pathogenic variants with early embryonic developmental failure in RPL.
• Epigenomic profiling reveals aberrant methylation patterns and imprinting disturbances affecting immune regulation.
• Single-cell and spatial transcriptomics identify disrupted cellular composition and communication among decidual stromal cells, uterine NK cells, macrophages, regulatory T cells, Th17 cells, and trophoblasts.
• Proteomic and metabolomic analyses uncover immune-metabolic signatures linked to impaired trophoblast function and vascular remodeling.
• Emerging microbiome research suggests a gut–reproductive axis modulating systemic immune homeostasis relevant to RPL.
• Integration of multi-omics data with computational frameworks improves RPL subtype classification and identification of actionable pathways but is limited by cohort size and reproducibility challenges.

Clinical Implications

Multi-omics approaches provide a more comprehensive understanding of immune dysregulation in RPL, supporting the development of immune-informed risk assessment tools. These insights may enable more precise patient stratification and pave the way for individualized therapeutic strategies targeting specific immune and metabolic pathways. However, standardized multi-omics pipelines and multicenter validation are needed before routine clinical application.

Conclusion

Integrating multi-omics data advances the mechanistic understanding of maternal-fetal immune tolerance disruptions in RPL and holds promise for improving diagnosis and personalized management. Future research should focus on standardized methodologies and immune-centric frameworks to translate these findings into clinical practice.

References

1. European Society of Human Reproduction and Embryology (ESHRE) 2021 -- Definitions of Recurrent Pregnancy Loss
2. American Society for Reproductive Medicine (ASRM) 2020 -- Recurrent Pregnancy Loss Guidelines
3. Royal College of Obstetricians and Gynaecologists (RCOG) 2017 -- Early Pregnancy Loss Management
4. Chinese Expert Consensus 2022 -- Recurrent Pregnancy Loss Diagnosis and Treatment