PDF(Pubmed)
Abstract：
LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.
摘要：
LD评分回归（LDSC）是一种仅从全基因组关联研究（GWAS）汇总统计来估计狭义遗传力的方法，使它成为一种快速和流行的方法。在这项工作中,我们提出了相互作用-LD评分(i-LDSC)回归:解释遗传变异之间相互作用的原始LDSC框架的扩展.通过研究模拟中的各种生成模型，并通过重新分析来自英国生物银行的349,468个人和日本生物银行中多达159,095个人的25种经过充分研究的定量表型，我们表明,纳入顺式相互作用评分(即局灶性变异体和近端变异体之间的相互作用)可以恢复LDSC未捕获的遗传变异.对于在英国生物银行和日本生物银行分析的25个性状中的每一个，i-LDSC检测由遗传相互作用贡献的额外变异。i-LDSC软件及其在这些生物库中的应用代表了解决非加性遗传效应来源对复杂性状变异的进一步遗传贡献的一步。
