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<p>Reproductive aging impacts women’s health through fertility decline, disease susceptibility, and systemic aging. This study explores the retinal age gap—the difference between predicted retinal age and chronological age—as a novel biomarker for reproductive aging. By developing a Swin-Transformer-based dual-channel transfer learning model with data from 1294 healthy women, we examined associations between the retinal age gap and Anti-Müllerian Hormone (AMH), a key marker of ovarian reserve. Findings revealed a negative association between the retinal age gap and AMH levels, particularly among women aged 40–50. Lower AMH levels correlated with earlier reproductive aging milestones, emphasizing the predictive value of retinal aging. Genetic data from genome-wide association studies further supported these associations and enhanced AMH prediction through multimodal modeling. These findings highlight the retinal age gap as a promising, non-invasive biomarker for reproductive aging and its potential role in disease prediction and personalized health interventions in women.</p>

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Artificial intelligence-derived retinal age gap as a marker for reproductive aging in women

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月16日

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  • Hanpei Miao,
  • Sian Liu,
  • Zehua Wang,
  • Yu Ke,
  • Linling Cheng,
  • Wenyao Yu,
  • Dihui Yu,
  • Kang Zhang,
  • Yuanxu Gao,
  • Zhuo Sun

摘要

Reproductive aging impacts women’s health through fertility decline, disease susceptibility, and systemic aging. This study explores the retinal age gap—the difference between predicted retinal age and chronological age—as a novel biomarker for reproductive aging. By developing a Swin-Transformer-based dual-channel transfer learning model with data from 1294 healthy women, we examined associations between the retinal age gap and Anti-Müllerian Hormone (AMH), a key marker of ovarian reserve. Findings revealed a negative association between the retinal age gap and AMH levels, particularly among women aged 40–50. Lower AMH levels correlated with earlier reproductive aging milestones, emphasizing the predictive value of retinal aging. Genetic data from genome-wide association studies further supported these associations and enhanced AMH prediction through multimodal modeling. These findings highlight the retinal age gap as a promising, non-invasive biomarker for reproductive aging and its potential role in disease prediction and personalized health interventions in women.