Transcriptome analysis of ovaries in mice with premature ovarian failure after treatment with Zishen Yutai pills

Zifan Song, Kuangyu Song, Jing Zhang, Lin Li, Yuanqiao He, Jia Hu

Article ID: 3677
Vol 39, Issue 3, 2025
DOI: https://doi.org/10.54517/jbrha3677
Received: 12 May 2025; Accepted: 31 July 2025; Available online: 23 October 2025; Issue release: 30 September 2025


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Abstract

Premature ovarian failure (POF) is a critical cause of female infertility, influencing not only reproduction but also life quality. Among the many treatments of POF, hormone replacement therapy is the most commonly adopted. However, it increases the risk of gynecologic tumour formation as well as the severity of cardiovascular and cerebrovascular disorders. Zishenyutai Pill (ZSYTP) is a traditional Chinese patent medication that has been widely used to treat infertility in China, while its underlying mechanism and therapeutic targets on POF remains unknown. To investigate this, we used 4-vinylcyclohexene diepoxide to build POF mouse model, and treated with ZSYTP. Ovaries were collected for histopathological observation, apoptosis assessment and RNA-seq analysis. Results showed that ZSYTP treatment not only decreased atretic follicles, but also increased primary and secondary follicles. In comparison to Model group, ZSYTP group had a significantly lower apoptotic index. Analysis based on differentially expressed genes (DEGs) between Normal and Model group revealed that the immunological response, cell-cell adhesion, and phagosome pathways were most closely associated with the development of POF, while the employment of ZSYTP could ameliorate them. RT-qPCR demonstrated that ZSYTP treatment downregulated the expression of H2-Ab1, H2-Eb1, and H2-Aa, which play multiple and vital roles in immune response. In conclusion, ZSYTP can alleviate ovarian damage of POF mice possibly by downregulating immune response, cell-cell adhesion, and phagocytic pathways.


Keywords

Zishen Yutai Pills; Chinese medicine; premature ovarian failure; RNA-seq; transcriptomics


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