Linkage-Disequilibrium Score Regression (LDSC) is a popular framework for analyzing GWAS summary statistics that allows for estimating SNP heritability, confounding, and functional enrichment of genetic variants with different annotations. Recent work has highlighted the influence of implicit and explicit assumptions of the model on the biological interpretation of the results. In this work, we explored a formulation of LDSC that replaces the r² measure of LD with a recently-proposed unbiased estimator of the D² statistic. In addition to modest statistical difference across estimators, this derivation highlighted implicit and unrealistic assumptions about the relationship between allele frequency, effect size, and annotation status. We carry out a systematic comparison of alternative LDSC formulations by applying them to summary statistics from 47 GWAS traits. Our results show that commonly used models likely underestimate functional enrichment. These results highlight the importance of calibrating the LDSC model to achieve a more robust understanding of polygenic traits.

中文翻译：

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关于复杂性状频率相关架构的假设偏向功能丰富性的措施

连锁不平衡得分回归（LDSC）是用于分析GWAS摘要统计数据的流行框架，该框架可用于估计具有不同注释的遗传变异的SNP遗传力，混淆和功能丰富。最近的工作强调了该模型的隐式和显式假设对结果的生物学解释的影响。在这项工作中，我们探索了LDSC的公式，用最近提出的D ^2的无偏估计量来代替LD的r ²度量。统计。除了估计值之间的统计差异不大外，该推导还强调了有关等位基因频率，效应大小和注释状态之间关系的隐式和不现实假设。我们通过将其应用于47种GWAS特性的汇总统计数据，对其他LDSC配方进行了系统的比较。我们的结果表明，常用模型可能会低估功能丰富性。这些结果凸显了校准LDSC模型以更全面地了解多基因性状的重要性。