通过结合罕见,低频率和特定人群的变异来改善2型糖尿病多基因风险评分
Katie Taylor1, Alicia Huerta-Chagoya1,2,3, Xiaoyu Wang4,5
1Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, 2142, USA.
medRxiv : the preprint server for health sciences
|December 8, 2025
概括
在多基因风险评分 (PRSs) 中纳入罕见和特定人群的变异可显著改善2型糖尿病 (T2D) 的预测,特别是在罕见变异携带者身上. 像CTSLEB这样的新方法在不同人群中显示出更高的准确性.
科学领域:
- 遗传学 遗传学 是一个
- 基因组流行病学 基因组流行病学
- 精准医学是一门精准的医学.
背景情况:
- 多基因风险评分 (PRS) 对于预测2型糖尿病 (T2D) 风险至关重要.
- 当前的PRS通常不包括低频,罕见和特定人群的变异,限制了它们的预测能力.
- 全基因组关联研究 (GWAS) 的元分析和扩展的参考面板是提高PRS准确性的关键.
研究的目的:
- 通过使用大规模的GWAS元分析和扩展的链接不平衡 (LD) 参考面板,调查是否结合罕见变体可以改善T2D风险预测.
- 构建和评估包括罕见变体的新型T2D PRS (CTSLEB,PRS-CS TAGIT,PRS-CS HM3).
- 将这些新型PRS的性能与基准多祖先PRS进行比较.
主要方法:
- 构建了一个大型GWAS元分析 (230,675例T2D病例,991,401例对照) 以包括罕见变异 (MAF 1x10^-5 - 0.01).
- 开发了三个T2D PRS:CTSLEB (罕见变异的自定义LD面板),PRS-CS (TAGIT) (扩展参考面板) 和PRS-CS (HM3) (标准LD面板).
- 评估了我们所有人研究计划中的PRS性能,并与D-PRISM基准PRS进行了比较.
主要成果:
- 与PRS-CS (TAGIT) 和CTSLEB相比,扩大PRS-CS (TAGIT) 和CTSLEB的变种覆盖率提高了T2D风险预测,而不是PRS-CS (HM3).
- 对于罕见变异载体 (AUC=0.832) 与PRS-CS (TAGIT) 和PRS-CS (HM3) 相比,CTSLEB的预测准确度更高.
- 基准D-PRISM PRS的整体表现最好,除了在非洲祖先种群中,CTSLEB显示了类似的整体表现和更好的罕见变异载体预测.
结论:
- 将罕见的和特定种群的变体纳入PRS构造可以提高T2D遗传风险预测.
- 像CTSLEB这样的新型PRS方法提供了更高的准确性,特别是对于携带罕见变异的人来说.
- 这些发现凸显了多样化遗传数据和先进方法对跨人群公平风险预测的重要性.
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