Estimating the causal tissues for complex traits and diseases
Estimating the causal tissues for complex traits and diseases
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DOI：
10.1038/ng.3981
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发表时间：
2017-12-01
期刊：
影响因子：
30.8
通讯作者：
Dermitzakis, Emmanouil T.
中科院分区：
文献类型：
--
作者：
Ongen, Halit;Brown, Andrew A.;Dermitzakis, Emmanouil T.
如何解释通过全基因组关联研究（GWAS）确定的易感标记物的生物学原因仍然是一个悬而未决的问题。一个直接和强大的方法来评估GWAS背后的遗传因果关系是通过分析表达数量性状基因座（eQTL）。在这里，我们描述了一种新的方法来估计各种GWAS性状的遗传因果关系背后的组织，使用基因型-组织表达（GTEx）协会的44个组织中的顺式eQTL。我们已经调整了调控性状一致性（RTC）评分来衡量eQTL在多个组织中活跃的概率，并计算GWAS相关变体和eQTL标记相同功能效应的概率。通过将GWAS-eQTL的概率由eQTL的组织共享估计值归一化，我们生成了GWAS性状的相对组织因果关系图谱。我们的方法不仅涉及可能介导个体GWAS信号的基因，而且还突出了可能表现出个体性状遗传因果关系的组织。
How to interpret the biological causes underlying the predisposing markers identified through genome-wide association studies (GWAS) remains an open question. One direct and powerful way to assess the genetic causality behind GWAS is through analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.