ArticleBMC pregnancy and childbirth2025
TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning.
Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Comparative Analysis of Extracellular Vesicle-Like Particles From Different ProcessingFood science & nutrition · 2026Article
- Multi-omics insights into immune tolerance at the maternal-fetal interface in recurrent pregnancy loss: mechanisms, integration challenges, and translational perspectives.Frontiers in immunology · 2026Review
- SHAP-interpretable machine learning integrating exposures and multi-omics reveals immune alterations and biomarkers in COPD-lung cancer comorbidity.Frontiers in immunology · 2026Article
- Integrative Multi-Omics Analysis Unveils Biomarkers Linking the Gut Microbiota, Blood Metabolites, and Recurrent Pregnancy Loss.International journal of women's health · 2026Article
- Decoding inflammatory regulation in ovarian cancer at single-cell resolution.Frontiers in immunology · 2025Review
- From gut dysbiosis to decidual hostility: the immuno-metabolic crosstalk driving recurrent pregnancy loss.Frontiers in immunology · 2025Review
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Authors and funding
16 authors.
Funding
Abstract
backgroundRecurrent pregnancy loss (RPL), characterized by multiple miscarriages, remains a condition with unclear etiology, posing significant challenges for affected women and couples. This study aims to explore the underlying mechanisms of RPL, focusing on the role of decidual Natural Killer (dNK) cells and the TNF receptor-associated factor 3 (TRAF3) gene as a potential diagnostic marker and therapeutic target.
methodsWe used single-cell transcriptomic analysis and machine learning techniques to analyze decidual tissues from RPL patients and normal pregnancy(NP). Weighted Gene Co-expression Network Analysis (WGCNA) was employed to identify key gene clusters. Validation studies included RT-PCR, immunohistochemistry, and molecular docking analyses.
resultsWe observed an increased proportion of specific dNK cell subtypes (dNK2 and dNK3) in the RPL group compared to NP, implicating their role in RPL pathology. dNK cells in RPL primarily interacted with monocytes via the Macrophage Migration Inhibitory Factor (MIF) signaling pathway. Our diagnostic model, incorporating TRAF3 and nine other genes, demonstrated high diagnostic efficiency. TRAF3 expression was significantly lower in the decidua of RPL patients, and Diethylstilbestrol and Metformin were identified as potential modulators of TRAF3.
conclusionsThis study highlights TRAF3 as a promising diagnostic marker and therapeutic target for RPL. The diagnostic model we developed has potential for early detection and personalized treatment strategies for RPL.
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