Almazov National Medical Research Centre, Saint-Petersburg, Russia.
ITMO University, Saint-Petersburg, Russia.
PLoS One. 2022 Jun 28;17(6):e0269434. doi: 10.1371/journal.pone.0269434. eCollection 2022.
Numerous studies demonstrated the lack of transferability of polygenic score (PGS) models across populations and the problem arising from unequal presentation of ancestries across genetic studies. However, even within European ancestry there are ethnic groups that are rarely presented in genetic studies. For instance, Russians, being one of the largest, diverse, and yet understudied group in Europe. In this study, we evaluated the reliability of genotype imputation for the Russian cohort by testing several commonly used imputation reference panels (e.g. HRC, 1000G, HGDP). HRC, in comparison with two other panels, showed the most accurate results based on both imputation accuracy and allele frequency concordance between masked and imputed genotypes. We built polygenic score models based on GWAS results from the UK biobank, measured the explained phenotypic variance in the Russian cohort attributed to polygenic scores for 11 phenotypes, collected in the clinic for each participant, and finally explored the role of allele frequency discordance between the UK biobank and the study cohort in the resulting PGS performance.
许多研究表明,多基因评分(PGS)模型在人群之间的可转移性不足,并且在遗传研究中存在着不同的祖先表现所带来的问题。然而,即使在欧洲血统内部,也有一些在遗传研究中很少出现的族群。例如,俄罗斯人是欧洲最大、最多样化但研究最少的族群之一。在这项研究中,我们通过测试几种常用的基因型推断参考面板(例如 HRC、1000G、HGDP)来评估俄罗斯队列基因型推断的可靠性。与另外两个面板相比,HRC 在基于推断准确性和掩蔽与推断基因型之间的等位基因频率一致性的基础上,显示出最准确的结果。我们基于英国生物库的 GWAS 结果构建了多基因评分模型,测量了俄罗斯队列中归因于 11 种表型的多基因评分的表型方差解释,这些表型是为每个参与者在诊所收集的,最后探索了英国生物库和研究队列之间的等位基因频率差异在导致 PGS 性能的作用。