Abstract

Cross-trait polygenic risk score (PRS) method has gained popularity for assessing genetic correlation of complex traits using summary statistics from biobank-scale genome-wide association studies (GWAS). However, empirical evidence has shown a common bias phenomenon that highly significant cross-trait PRS can only account for a very small amount of genetic variance (R² can be $<1\%$) in independent testing GWAS. The aim of this paper is to investigate and address the bias phenomenon of cross-trait PRS in numerous GWAS applications. We show that the estimated genetic correlation can be asymptotically biased toward zero. A consistent cross-trait PRS estimator is then proposed to correct such asymptotic bias. In addition, we investigate whether or not SNP screening by GWAS p-values can lead to improved estimation and show the effect of overlapping samples among GWAS. We analyze GWAS summary statistics of reaction time and brain structural magnetic resonance imaging-based features measured in the Pediatric Imaging, Neurocognition, and Genetics study. We find that the raw cross-trait PRS estimators heavily underestimate the genetic similarity between cognitive function and human brain structures (mean $R^2=1.32\%$), whereas the bias-corrected estimators uncover the moderate degree of genetic overlap between these closely related heritable traits (mean $R^2=22.42\%$). Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

 抽象的

跨性状多基因风险评分（PRS）方法在使用生物库规模全基因组关联研究（GWAS）的汇总统计来评估复杂性状的遗传相关性方面已广受欢迎。然而，经验证据表明一个常见的偏差现象，即高度显着的跨性状 PRS 只能解释非常少量的遗传方差（ R ²可以是 $<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9"><</span>\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">1</span>}\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">\%</span>}$ ）在独立测试 GWAS 中。本文的目的是调查并解决众多 GWAS 应用中跨性状 PRS 的偏差现象。我们表明，估计的遗传相关性可以渐近地偏向于零。然后提出一致的跨特征 PRS 估计器来纠正这种渐近偏差。此外，我们还研究了通过 GWAS p值筛选 SNP 是否可以改进估计并显示 GWAS 之间重叠样本的影响。我们分析了儿科影像、神经认知和遗传学研究中测量的反应时间和基于脑结构磁共振成像的特征的 GWAS 摘要统计数据。我们发现原始的跨特质 PRS 估计量严重低估了认知功能和人类大脑结构之间的遗传相似性（平均 ${\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">右</span>}}^{\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">2</span>}}<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">=</span>\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">1.</span>32}\%$ ），而偏差校正估计量揭示了这些密切相关的遗传性状之间的中等程度的遗传重叠（平均 ${\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">右</span>}}^{\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">2</span>}}<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">=</span>\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">22.42</span>}\mathrm{<span\; data-immersive-translate-walked="44a901d6-2e54-4740-bbc3-2a74367764c9">\%</span>}$ ）。本文的补充材料（包括可用于复制该作品的材料的标准化描述）可作为在线补充材料获得。