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一种自我适应的多基因风险评分模型改善了汉族中国队列中静脉血栓栓塞的风险预测
Zhaoman Wan1, Zhu Zhang2, Mingming Su3
1State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou, 215123 Jiangsu China.
Phenomics (Cham, Switzerland)
|September 26, 2025
概括
一个新的自我适应的多基因风险评分 (PRS) 模型有效地识别了在中国人群中患有静脉血栓栓塞 (VTE) 的高风险个体. 该模型利用44个单核酸多态 (SNP),改善了用于精确预防策略的VTE风险分层.
科学领域:
- 遗传学 遗传学 是一个
- 基因组学就是基因组学.
- 流行病学 流行病学
背景情况:
- 对静脉血栓栓塞 (VTE) 的全基因组关联研究 (GWAS) 主要使用欧洲数据,限制了在其他人群中应用现有的多基因风险评分 (PRS).
- 影响中国人群VTE风险的遗传因素仍未得到充分研究,阻碍了有针对性的预防工作.
研究的目的:
- 开发和验证一个改进的PRS模型,用于中国人群中VTE风险分层.
- 确定关键的单核酸多态 (SNP) 以准确预测VTE风险.
主要方法:
- 在中国队列中对VTE相关的SNP进行了全面分析.
- 使用各种算法和风险评估标准,开发一个自适应的PRS模型.
- 在独立的中国人口队列上对PRS模型进行独立测试.
主要成果:
- 自适应的PRS模型,特别是基于44个SNP的模型,表现出强的性能 (AUC0.709),优于传统的PRS模型 (AUC0.620-0.718).
- 开发的PRS模型被证明是VTE风险的独立预测因素,超出了年龄和吸烟等临床因素.
- 从44个SNP衍生出的PRS模型有效地歧视VTE高风险亚群.
结论:
- 基于44个SNP的自适应PRS模型对中国人群中VTE风险分层有效.
- 这种模型有望在VTE查和精确预防计划中具有临床实用性.
- 进一步开发可以将该模型整合到实际的VTE查计划中,以改善公共卫生结果.
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