使用公开可用的数据构建多祖先多基因子宫纤维瘤风险评分,突显了对包容性遗传研究的需求
Jessica L G Winters1, Jacqueline A Piekos1, Jacklyn N Hellwege1
1Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37203, USA.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 13, 2024
概括
一个新的多祖先多基因风险评分 (PRS) 能够有效地预测不同人群的子宫纤维瘤风险. 这种基因工具有助于早期诊断,并突出了精准医学多样性的重要性.
科学领域:
- 遗传学和基因组学 遗传学和基因组学
- 生殖健康 生殖健康
- 精准医学是一门精准的医学.
背景情况:
- 子宫肌瘤 (纤维瘤) 是常见的妇科瘤,引起显著的症状,影响生活质量和生育能力.
- 早期识别患有纤维瘤的高风险个体可以改善诊断时间表,并可能减少对侵袭性生育损害治疗的需求.
- 多基因风险评分 (PRS) 是量化对疾病遗传倾向的新兴工具.
研究的目的:
- 开发和验证子宫纤维瘤的多祖先多基因风险评分 (META PRS).
- 评估META PRS在不同人群中的预测性能.
- 为了比较多祖先PRS与单祖先PRS在纤维瘤预测方面的疗效.
主要方法:
- 使用PRS-CSx软件和来自FinnGen和日本生物银行的GWAS总结统计数据,为纤维瘤构建了一个多祖先的PRS.
- 在跨祖先队列中验证了META PRS,包括eMerge网络和两个BioVU队列 (ICD代码和成像确认).
- 开发了欧洲 (EUR) 和东亚 (EAS) 祖先的单一祖先PRS,用于比较分析.
主要成果:
- META PRS在eMERGE队列中显示出与纤维瘤状况的显著关联 (OR=1.11每SD,p=5.21x10-5).
- 在BioVU队列中的验证显示,META PRS中每SD增加纤维瘤的几率增加 (ICD队列:OR=1.23,p=9.68x10-9;成像队列:OR=1.26,p=2.40x10-11).
- 在eMERGE队列中发现了纤维瘤和EAS PRS之间名义上显著的关联,但不是EUR PRS,这强调了多祖先模型的好处.
结论:
- 一个多祖先的PRS显示出强大的预测能力的子宫纤维瘤在不同的人口.
- META PRS的表现优于单一祖先的PRS,强调在遗传风险预测中需要多样化的数据.
- 这项研究支持通过包容性遗传研究开发公平的精准医学策略.
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