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Peer-reviewedCC BY 4.0PLOS One

Androgenetic alopecia drugs and male infertility: Evidence from pharmacovigilance and testicular transcriptomics

  • Zhuozhi Gong1
  • Jing He2
  • Qiujian Feng3
  • Wenyu Chen4
  • Yonglong Xu
  • Qingying Wang
  • Shengjing Liu
4 affiliations
  1. 1Department of Andrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China
  2. 2School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
  3. 3Beijing University of Chinese Medicine, Beijing, China
  4. 4Department of Dermatology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China
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Abstract

Objective: To identify disproportionality signals linking androgenetic alopecia (AGA) drugs (finasteride, dutasteride, and minoxidil) with male infertility-related adverse events and to explore infertility-related biological features using testicular transcriptomic datasets. Methods: A dual-database replication design was employed using FAERS (2004–2025) and EudraVigilance (2002–2025). Disproportionality analysis with multiple signal detection metrics assessed drug–infertility associations. Multi-level bioinformatic analyses—including toxicity prediction, drug-associated target screening, testicular transcriptomic analysis, single-cell RNA sequencing, intercellular communication analysis, gene set enrichment analysis (GSEA), and immune infiltration analysis—were integrated to explore biological features potentially relevant to male infertility. Results: Disproportionality analyses detected signals for all three drugs, with finasteride demonstrating the most prominent reporting signal, followed by dutasteride and minoxidil. Multi-level bioinformatic analysis identified HIF1A as an overlap-derived candidate under the specified datasets and screening criteria, and HIF1A expression was higher in testicular tissue from patients with male infertility. Single-cell analysis showed higher HIF1A expression in late spermatocytes, Leydig cells, and myoid cells from infertility samples, together with group-dependent inferred communication patterns for selected VEGF-, PDGF-, IGF-, and FGF-related signaling axes. GSEA associated higher HIF1A expression with immune-response-, wound-healing-, and cell-adhesion-related processes, whereas lower HIF1A expression was associated with spermatid-development- and cilium/flagellum-dependent motility-related processes. ssGSEA-based analysis showed positive correlations between HIF1A expression and several immune-cell signature scores. Conclusion: This study systematically evaluated associations between AGA drugs and male infertility using real-world pharmacovigilance data and integrated bioinformatic analyses. The HIF1A-related transcriptomic findings provide a hypothesis-generating biological context for male infertility but do not establish a shared or drug-specific mechanism linking the three medications to infertility. The pharmacovigilance findings indicate reporting signals rather than incidence or causality.

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Cite

BibTeXRIS
BibTeX
@article{gong2026androgenetic,
  title = {{Androgenetic alopecia drugs and male infertility: Evidence from pharmacovigilance and testicular transcriptomics}},
  author = {Zhuozhi Gong and Jing He and Qiujian Feng and Wenyu Chen and Yonglong Xu and Qingying Wang and Shengjing Liu},
  journal = {PLOS One},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pone.0357154},
  url = {https://doi.org/10.1371/journal.pone.0357154},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Androgenetic alopecia drugs and male infertility: Evidence from pharmacovigilance and testicular transcriptomics
AU  - Zhuozhi Gong
AU  - Jing He
AU  - Qiujian Feng
AU  - Wenyu Chen
AU  - Yonglong Xu
AU  - Qingying Wang
AU  - Shengjing Liu
PY  - 2026
DA  - 2026/09/24
JO  - PLOS One
DO  - 10.1371/journal.pone.0357154
UR  - https://doi.org/10.1371/journal.pone.0357154
AB  - Objective: To identify disproportionality signals linking androgenetic alopecia (AGA) drugs (finasteride, dutasteride, and minoxidil) with male infertility-related adverse events and to explore infertility-related biological features using testicular transcriptomic datasets. Methods: A dual-database replication design was employed using FAERS (2004–2025) and EudraVigilance (2002–2025). Disproportionality analysis with multiple signal detection metrics assessed drug–infertility associations. Multi-level bioinformatic analyses—including toxicity prediction, drug-associated target screening, testicular transcriptomic analysis, single-cell RNA sequencing, intercellular communication analysis, gene set enrichment analysis (GSEA), and immune infiltration analysis—were integrated to explore biological features potentially relevant to male infertility. Results: Disproportionality analyses detected signals for all three drugs, with finasteride demonstrating the most prominent reporting signal, followed by dutasteride and minoxidil. Multi-level bioinformatic analysis identified HIF1A as an overlap-derived candidate under the specified datasets and screening criteria, and HIF1A expression was higher in testicular tissue from patients with male infertility. Single-cell analysis showed higher HIF1A expression in late spermatocytes, Leydig cells, and myoid cells from infertility samples, together with group-dependent inferred communication patterns for selected VEGF-, PDGF-, IGF-, and FGF-related signaling axes. GSEA associated higher HIF1A expression with immune-response-, wound-healing-, and cell-adhesion-related processes, whereas lower HIF1A expression was associated with spermatid-development- and cilium/flagellum-dependent motility-related processes. ssGSEA-based analysis showed positive correlations between HIF1A expression and several immune-cell signature scores. Conclusion: This study systematically evaluated associations between AGA drugs and male infertility using real-world pharmacovigilance data and integrated bioinformatic analyses. The HIF1A-related transcriptomic findings provide a hypothesis-generating biological context for male infertility but do not establish a shared or drug-specific mechanism linking the three medications to infertility. The pharmacovigilance findings indicate reporting signals rather than incidence or causality.
SN  - 1932-6203
ER  -