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<p>The prevalence of obesity is steadily rising and poses a significant challenge to women’s health. Preeclampsia (PE), a leading cause of maternal and fetal mortality, is significantly linked to a high body mass index (BMI). However, the shared genetic architecture underlying these conditions remains poorly understood. In this study, we used summary-level data from large-scale genome-wide association studies of BMI (<i>N</i> = 434,794) and PE (<i>N</i>cases = 8185; <i>N</i>controls = 234,147) to assess the shared genetic architecture between them. Our findings revealed a significant genetic correlation between BMI and PE, with an estimated sample overlap of approximately 0.8%. We identified roughly 1100 shared genetic variants, with the most notable region of local genetic correlation located in 16q12.2. Enrichment analyses highlighted endothelial dysfunction as a key biological mechanism linking BMI and PE. Additionally, RABEP2 was identified as a novel shared risk gene. Mendelian randomization analysis demonstrated a bidirectional causal relationship between BMI and PE, with blood pressure identified as a key mediator. We identified the shared genetic foundation between BMI and PE, providing valuable insights into the comorbidity of these conditions and offering a new framework for future research into comorbidity.</p>

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Elucidating shared genetic association between female body mass index and preeclampsia

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月27日

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  • Fengmei Yang,
  • Zhijian Zha,
  • Fang Gao,
  • Man Wang,
  • Enfu Du,
  • Ziyang Wang,
  • Lei Zhou,
  • Bo Gao,
  • Si Li,
  • Danfeng Zhang

摘要

The prevalence of obesity is steadily rising and poses a significant challenge to women’s health. Preeclampsia (PE), a leading cause of maternal and fetal mortality, is significantly linked to a high body mass index (BMI). However, the shared genetic architecture underlying these conditions remains poorly understood. In this study, we used summary-level data from large-scale genome-wide association studies of BMI (N = 434,794) and PE (Ncases = 8185; Ncontrols = 234,147) to assess the shared genetic architecture between them. Our findings revealed a significant genetic correlation between BMI and PE, with an estimated sample overlap of approximately 0.8%. We identified roughly 1100 shared genetic variants, with the most notable region of local genetic correlation located in 16q12.2. Enrichment analyses highlighted endothelial dysfunction as a key biological mechanism linking BMI and PE. Additionally, RABEP2 was identified as a novel shared risk gene. Mendelian randomization analysis demonstrated a bidirectional causal relationship between BMI and PE, with blood pressure identified as a key mediator. We identified the shared genetic foundation between BMI and PE, providing valuable insights into the comorbidity of these conditions and offering a new framework for future research into comorbidity.