贝叶斯式方法评估疾病遗传风险的人口差异,适用于前列腺癌
Iain R Timmins1,2,3, , Frank Dudbridge1
1Department of Population Health Sciences, University of Leicester, Leicester, United Kingdom.
PLoS genetics
|April 17, 2024
概括
人群之间的遗传风险差异受GWAS培训样本大小和遗传距离的影响. 目前的样本大小往往缺乏检测中度遗传风险变异的能力,但可以识别出实质性的差异.
科学领域:
- 人口遗传学 人口遗传学
- 统计基因组学 统计基因组学
- 疾病风险评估 疾病风险评估
背景情况:
- 人口在疾病风险上的差异是公认的,但它们的遗传基础仍然不清楚.
- 使用多基因分数对人口进行基因风险比较的现有方法经常忽视来自有限基因组广泛协会研究 (GWAS) 训练数据的统计噪声.
研究的目的:
- 开发和验证贝叶斯的方法来评估跨人群的遗传风险差异.
- 量化GWAS培训样本大小,多基因性和遗传距离对这些估计不确定性的影响.
- 引入一个强大的统计测试来评估遗传风险差异.
主要方法:
- 利用贝叶斯的多基因分数方法来模拟遗传风险估计中的不确定性.
- 衍生出Wald测试来评估遗传风险差异,使用链接不平衡 (LD) 修剪以获得独立性.
- 在无限小的遗传架构下开发了用于不确定性评估的闭式表达式.
主要成果:
- 遗传风险差异的不确定性在很大程度上取决于GWAS培训样本大小,多基因性和FST (遗传距离).
- 传统的方法 (例如t测试) 由于未被解决的采样错误,导致1型错误率膨胀.
- 目前的GWAS样本大小往往不足以检测中等遗传风险差异,但可以检测出实质性差异 (相对风险>1.5).
结论:
- 一个新的贝叶斯框架为评估人口特异性遗传风险提供了校准的1型错误率.
- 该研究强调了对更大的GWAS培训数据集的关键需求,以准确地比较不同人群中的遗传风险.
- 对前列腺癌的应用显示,与欧洲和东亚祖先群体相比,非洲祖先男性的遗传风险更高.
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