科技科学

Identification and validation of cellular senescence biomarkers in recurrent pregnancy loss using machine learning and single-cell RNA sequencing

Nature作者：Yulu Zeng2026年8月12日正文已收录本站
  • Article
  • Open access
  • Published:
  • Jiayi Gan1 na1,
  • Li Wei1,
  • Jinlian Cheng1,
  • Yiyun Wei1,
  • Changqiang Wei1,
  • Xiangyun Zhu1,
  • Wenyao Jing1 &
  • …
  • Lihong Pang  ORCID: orcid.org/0009-0001-8299-77851,2,3,4 

Scientific Reports (2026) Cite this article

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Abstract

Recurrent pregnancy loss (RPL) is a major reproductive health problem in women of childbearing age, and its molecular mechanisms remain incompletely understood. This study aimed to identify key cellular senescence–related biomarkers for RPL and to evaluate their diagnostic value. Multiple RPL-related transcriptomic datasets were retrieved from the Gene Expression Omnibus (GEO) database, integrated, and corrected for batch effects. Differential expression analysis was performed, and the results were intersected with senescence-associated genes from the CellAge database to obtain senescence-related differentially expressed genes (DEARGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, protein–protein interaction (PPI) network construction, and gene set enrichment analysis (GSEA) were conducted to explore potential functional pathways. Multiple machine-learning algorithms were then applied to screen for hub genes, yielding five key senescence-related genes: CYB5R3, LEO1, PAK2, RHOA, and GADD45G. A nomogram model was developed based on these genes, and its diagnostic performance was assessed using calibration curves, decision curve analysis, and receiver operating characteristic (ROC) analysis. Single-cell RNA-sequencing analysis indicated that GADD45G was highly expressed in decidual stromal cells, and virtual knockout analysis suggested that it may be involved in extracellular matrix remodeling, adhesion, and related signaling pathways. In addition, drug enrichment analysis predicted potential candidate small-molecule compounds. Finally, quantitative real-time PCR (qRT-PCR) validation in clinical decidual tissue samples showed that CYB5R3, PAK2, RHOA, and GADD45G were significantly upregulated in RPL, whereas LEO1 was significantly downregulated. Collectively, this study identified key senescence-related genes associated with RPL and established a diagnostic model with potential clinical utility, providing new insights for mechanistic research and precision diagnosis and treatment of RPL.

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Acknowledgements

We gratefully acknowledge the support from the National Natural Science Foundation of China.

Funding

This research was supported by grants from the National Natural Science Foundation of China ( Nos. 82260306 and 81960281), the construction of clinical intervention protocols Guangxi key R & D program (Guike AB20159031 ; AB24010080), and the Clinical Research Climbing Program Innovation Team of the First Affiliated Hospital of Guangxi Medical University (YYZS2022006).

Author information

Author notes

  1. Yulu Zeng and Jiayi Gan contributed equally to this work.

Authors and Affiliations

  1. Department of Prenatal Diagnosis and Genetic Diagnosis, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China

    Yulu Zeng, Jiayi Gan, Li Wei, Jinlian Cheng, Yiyun Wei, Changqiang Wei, Xiangyun Zhu, Wenyao Jing & Lihong Pang

  2. National Health Commission Key Laboratory of Thalassemia Medicine, Nanning, Guangxi, China

    Lihong Pang

  3. Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Gaungxi Medical University, Ministry of Education, Nanning, Guangxi, China

    Lihong Pang

  4. Guangxi Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Nanning, Guangxi, China

    Lihong Pang

Authors

  1. Yulu Zeng
  2. Jiayi Gan
  3. Li Wei
  4. Jinlian Cheng
  5. Yiyun Wei
  6. Changqiang Wei
  7. Xiangyun Zhu
  8. Wenyao Jing
  9. Lihong Pang

Corresponding author

Correspondence to Lihong Pang.

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Competing interests

The authors declare no competing interests.

Informed consent

Informed consent was obtained from all participants involved in the study.

Institutional review board

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Medical Ethics Committee of First Affiliated Hospital of Guangxi Medical University (Protocol Code:2026-E0178).

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Cite this article

Zeng, Y., Gan, J., Wei, L. et al. Identification and validation of cellular senescence biomarkers in recurrent pregnancy loss using machine learning and single-cell RNA sequencing. Sci Rep (2026). https://doi.org/10.1038/s41598-026-65744-6

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  • DOI: https://doi.org/10.1038/s41598-026-65744-6

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