Variable prediction accuracy of polygenic scores within an ancestry group
Variable prediction accuracy of polygenic scores within an ancestry group
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DOI：
10.7554/elife.48376
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发表时间：
2020-01-30
期刊：
影响因子：
7.7
通讯作者：
Przeworski, Molly
中科院分区：
文献类型：
--
作者：
Mostafavi, Hakhamanesh;Harpak, Arbel;Przeworski, Molly
人类遗传学和社会学等不同领域越来越多地使用基于全基因组关联研究 (GWAS) 的多基因评分来进行表型预测。然而，最近的研究表明，多基因评分在不同遗传祖先群体之间的可移植性有限，限制了它们可以可靠使用的环境，并可能在未来的临床应用中造成严重的不平等。使用英国生物银行数据，我们证明，即使在单一祖先群体内（即，当连锁不平衡或因果等位基因频率的差异可以忽略不计时），多基因评分的预测准确性也可能取决于进行 GWAS 和预测的个体的社会经济地位、年龄或性别等特征，以及 GWAS 设计。我们的研究结果强调了解释多基因评分的复杂性以及其广泛使用的障碍被低估。
Fields as diverse as human genetics and sociology are increasingly using polygenic scores based on genome-wide association studies (GWAS) for phenotypic prediction. However, recent work has shown that polygenic scores have limited portability across groups of different genetic ancestries, restricting the contexts in which they can be used reliably and potentially creating serious inequities in future clinical applications. Using the UK Biobank data, we demonstrate that even within a single ancestry group (i.e., when there are negligible differences in linkage disequilibrium or in causal alleles frequencies), the prediction accuracy of polygenic scores can depend on characteristics such as the socio-economic status, age or sex of the individuals in which the GWAS and the prediction were conducted, as well as on the GWAS design. Our findings highlight both the complexities of interpreting polygenic scores and underappreciated obstacles to their broad use.