TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning
Abstract Background Recurrent 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 K...
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BMC
2025-05-01
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| Series: | BMC Pregnancy and Childbirth |
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| Online Access: | https://doi.org/10.1186/s12884-025-07742-6 |
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| author | Yi-bo He Jun-yu Li Shi-liang Chen Rui Ye Yi-ran Fei Shi-yuan Tong Yu-xuan Song Cong Wang Li Zhang Ju Fang Yue Shang Zhe-zhong Zhang Jin Chen Ai-zhong Yang Jie Liu Yong-lin Liu |
| author_facet | Yi-bo He Jun-yu Li Shi-liang Chen Rui Ye Yi-ran Fei Shi-yuan Tong Yu-xuan Song Cong Wang Li Zhang Ju Fang Yue Shang Zhe-zhong Zhang Jin Chen Ai-zhong Yang Jie Liu Yong-lin Liu |
| author_sort | Yi-bo He |
| collection | DOAJ |
| description | Abstract Background Recurrent 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. Methods We 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. Results We 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. Conclusions This 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. |
| format | Article |
| id | doaj-art-b74f04d91ab74075a9e1c2bf85ec9db9 |
| institution | DOAJ |
| issn | 1471-2393 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Pregnancy and Childbirth |
| spelling | doaj-art-b74f04d91ab74075a9e1c2bf85ec9db92025-08-20T03:22:03ZengBMCBMC Pregnancy and Childbirth1471-23932025-05-0125111910.1186/s12884-025-07742-6TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learningYi-bo He0Jun-yu Li1Shi-liang Chen2Rui Ye3Yi-ran Fei4Shi-yuan Tong5Yu-xuan Song6Cong Wang7Li Zhang8Ju Fang9Yue Shang10Zhe-zhong Zhang11Jin Chen12Ai-zhong Yang13Jie Liu14Yong-lin Liu15Department of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Chinese Medicine)Department of Pharmacy, Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Chinese Medicine)School of Medical Technology and Information Engineering, Zhejiang Chinese Medical UniversityThe First Clinical Medical College, Zhejiang Chinese Medicine UniversityState Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan UniversityDepartment of Urology, Peking University People’s HospitalDepartment of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Chinese Medicine)Obstetrics and Gynecology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine)Reproductive Center, Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong UniversityReproductive Center, Hainan Branch, Shanghai Children’s Medical Center, School of Medicine, Shanghai Jiao Tong UniversityDepartment of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, (Zhejiang Provincial Hospital of Chinese Medicine)School of Medical Technology and Information Engineering, Zhejiang Chinese Medical UniversityReproductive Center, The Second Affiliated Hospital of Zhejiang Chinese Medical UniversityReproductive Center, The Second Affiliated Hospital of Zhejiang Chinese Medical UniversityReproductive Center, The Second Affiliated Hospital of Zhejiang Chinese Medical UniversityAbstract Background Recurrent 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. Methods We 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. Results We 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. Conclusions This 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.https://doi.org/10.1186/s12884-025-07742-6Recurrent Pregnancy Loss (RPL)Decidual Natural Killer Cells (dNK)Macrophage Migration Inhibitory Factor (MIF) pathwaySingle-cell transcriptomicsHigh-Dimensional Weighted Gene Co-expression Network Analysis (HdWGCNA)Machine learning |
| spellingShingle | Yi-bo He Jun-yu Li Shi-liang Chen Rui Ye Yi-ran Fei Shi-yuan Tong Yu-xuan Song Cong Wang Li Zhang Ju Fang Yue Shang Zhe-zhong Zhang Jin Chen Ai-zhong Yang Jie Liu Yong-lin Liu TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning BMC Pregnancy and Childbirth Recurrent Pregnancy Loss (RPL) Decidual Natural Killer Cells (dNK) Macrophage Migration Inhibitory Factor (MIF) pathway Single-cell transcriptomics High-Dimensional Weighted Gene Co-expression Network Analysis (HdWGCNA) Machine learning |
| title | TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning |
| title_full | TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning |
| title_fullStr | TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning |
| title_full_unstemmed | TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning |
| title_short | TRAF3 as a potential diagnostic biomarker for recurrent pregnancy loss: insights from single-cell transcriptomics and machine learning |
| title_sort | traf3 as a potential diagnostic biomarker for recurrent pregnancy loss insights from single cell transcriptomics and machine learning |
| topic | Recurrent Pregnancy Loss (RPL) Decidual Natural Killer Cells (dNK) Macrophage Migration Inhibitory Factor (MIF) pathway Single-cell transcriptomics High-Dimensional Weighted Gene Co-expression Network Analysis (HdWGCNA) Machine learning |
| url | https://doi.org/10.1186/s12884-025-07742-6 |
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