Improved Heritability Estimation from Genome-wide SNPs
Improved Heritability Estimation from Genome-wide SNPs
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DOI：
10.1016/j.ajhg.2012.10.010
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发表时间：
2012-12-07
影响因子：
9.8
通讯作者：
Balding, David J.
中科院分区：
文献类型：
--
作者：
Speed, Doug;Hemani, Gibran;Balding, David J.
从无关个体的全基因组SNP基因分型来估计狭义遗传力h（2）最近引起了人们的兴趣，并提供了一些优于传统的基于谱系的方法的优点。使用这种方法，据估计，超过一半的人类身高的遗传力可以归因于全基因组基因分型阵列上的近似300，000个SNP。相比之下，只有5%-10%可以通过SNP达到全基因组意义来解释。我们通过模拟研究了支持基于SNP的h（2）估计中使用的混合模型分析的几个关键假设的有效性。虽然我们发现该方法对违反四个关键假设具有合理的鲁棒性，但它对SNP之间的不均匀连锁不平衡（LD）高度敏感：在高LD区域，因果变异对h（2）的贡献被高估，而在低LD区域被低估。偏差的总体方向可以是向上或向下，这取决于性状的遗传结构，但在现实情况下可能很大。我们提出了一个修改的亲属矩阵，其中SNPs加权根据当地LD。我们表明，这种校正大大降低了偏差，提高了精度的h（2）估计。我们展示了我们的方法对威康信托病例控制联盟研究的前七种疾病的影响。我们的LD调整向下修正了免疫相关疾病的h（2）估计值，正如预期的那样，因为主要组织相容性区域的LD较高，但对于某些非免疫性疾病，它会增加。为了计算修正后的亲属关系矩阵，我们开发了LDAK软件，用于计算LD调整后的亲属关系。
Estimation of narrow-sense heritability, h(2), from genome-wide SNPs genotyped in unrelated individuals has recently attracted interest and offers several advantages over traditional pedigree-based methods. With the use of this approach, it has been estimated that over half the heritability of human height can be attributed to the similar to 300,000 SNPs on a genome-wide genotyping array. In comparison, only 5%-10% can be explained by SNPs reaching genome-wide significance. We investigated via simulation the validity of several key assumptions underpinning the mixed-model analysis used in SNP-based h(2) estimation. Although we found that the method is reasonably robust to violations of four key assumptions, it can be highly sensitive to uneven linkage disequilibrium (LD) between SNPs: contributions to h(2) are overestimated from causal variants in regions of high LD and are underestimated in regions of low LD. The overall direction of the bias can be up or down depending on the genetic architecture of the trait, but it can be substantial in realistic scenarios. We propose a modified kinship matrix in which SNPs are weighted according to local LD. We show that this correction greatly reduces the bias and increases the precision of h(2) estimates. We demonstrate the impact of our method on the first seven diseases studied by the Wellcome Trust Case Control Consortium. Our LD adjustment revises downward the h(2) estimate for immune-related diseases, as expected because of high LD in the major-histocompatibility region, but increases it for some nonimmune diseases. To calculate our revised kinship matrix, we developed LDAK, software for computing LD-adjusted kinships.