Schultz Laura M, Merikangas Alison K, Ruparel Kosha, Jacquemont Sébastien, Glahn David C, Gur Raquel E, Barzilay Ran, Almasy Laura
Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Lifespan Brain Institute, Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA 19104, USA.
HGG Adv. 2022 Jan 21;3(2):100091. doi: 10.1016/j.xhgg.2022.100091. eCollection 2022 Apr 14.
Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.
多基因评分(PGS)通常通过它们所解释的表型变异比例在群体水平上评估其预测准确性。为了在精准医学应用中发挥作用,当表型不一定已知时,它们还需要在个体水平上进行评估。我们使用针对创伤后应激障碍(PTSD)、2型糖尿病(T2D)和身高的不同发现全基因组关联研究(GWAS)结果,调查了来自费城神经发育队列和青少年大脑认知发展研究的欧洲裔美国人(EUR)和非裔美国人(AFR)血统个体中PGS的稳定性。我们发现,针对同一性状的成对EUR血统GWAS的遗传相关性>0.92。然而,从同血统和不同血统GWAS对计算出的PGS的相关性范围为<0.01至0.74。身高的PGS稳定性高于PTSD或T2D。英国生物银行的一系列身高GWAS表明,PGS之间的相关性强烈依赖于发现GWAS之间的样本重叠程度。关注PGS分布的上限,不同的发现GWAS在较高百分位数中并不能始终识别出相同的个体,最好的情况是从一个身高GWAS到另一个身高GWAS,PGS第80百分位数以上的个体中有60%重叠。随着考虑更高的百分位数、遗传性较低的性状和不同血统的GWAS,重叠程度急剧下降。从不同发现GWAS计算出的PGS在个体水平上只有适度的相关性,这突出了在将PGS整合到精准医学应用中时需要谨慎行事。