Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.
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DOI：
10.1038/s41467-018-03621-1
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发表时间：
2018-05-08
影响因子：
16.6
通讯作者：
Im HK
中科院分区：
文献类型：
--
作者：
Barbeira AN;Dickinson SP;Bonazzola R;Zheng J;Wheeler HE;Torres JM;Torstenson ES;Shah KP;Garcia T;Edwards TL;Stahl EA;Huckins LM;GTEx Consortium;Nicolae DL;Cox NJ;Im HK
需要可扩展的综合方法来理解遗传变异与表型之间的联系机制。在这里，我们推导了一个数学表达式来计算PrediXcan（一种基因定位方法）使用汇总数据（S-PrediXcan）的结果，并展示了它的准确性和对错误指定参考集的一般鲁棒性。我们将这一框架应用于44个GTEx组织和来自GWAS和荟萃分析研究的100多种表型，创建了一个不断增长的公共关联目录，旨在捕捉基因表达变异对人类表型的影响。在一个独立的队列中显示了复制。大多数关联是组织特异性的，这表明该性状的病因具有环境特异性。在意想不到的组织中定位的重要关联强调了对多种背景进行不可知论扫描的必要性，以提高我们检测因果调节机制的能力。单基因疾病基因在相关性状的显著关联中富集，表明这些基因的较小改变可能导致一系列较温和的表型。表型变异和疾病受遗传变异和基因表达等因素的影响。在这里，Barbeira等人开发了S-PrediXcan，利用汇总数据计算PrediXcan结果，并研究了基因表达变异对44个GTEx组织和bbb100个表型的人类表型的影响。
Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations are tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes. Phenotypic variation and diseases are influenced by factors such as genetic variants and gene expression. Here, Barbeira et al. develop S-PrediXcan to compute PrediXcan results using summary data, and investigate the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes.
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作者：
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通讯作者：
Fuchsberger, Christian