Population-Matched Transcriptome Prediction Increases TWAS Discovery and Replication Rate.

Population-Matched Transcriptome Prediction Increases TWAS Discovery and Replication Rate.
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DOI:
10.1016/j.isci.2020.101850
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发表时间:
2020-12-18
期刊:
影响因子:
5.8
通讯作者:
Wheeler HE
Wheeler HE
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Geoffroy E;Gregga I;Wheeler HE

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大多数全基因组关联研究(GWAS)和全转录组关联研究(TWAS)关注欧洲人群;然而,由于遗传结构的差异,这些结果并不总是准确地应用于非欧洲人群。利用基因组学和流行病学研究中的人口结构中的 GWAS 摘要统计数据,该研究包括约 50,000 名西班牙裔/拉丁裔、非裔美国人、亚洲人、夏威夷原住民和美洲原住民,我们执行 TWAS 来确定基因性状关联。我们使用源自动脉粥样硬化人群多种族研究的三种转录组预测模型来比较结果:非裔美国人和西班牙裔/拉丁裔 (AFHI) 模型、欧洲 (EUR) 模型以及非裔美国人、西班牙裔/拉丁裔和欧洲 (ALL) 模型。我们鉴定了 240 个独特的重要性状相关基因。我们发现,与 EUR 或 ALL 模型相比,应用 AFHI 模型时,在更大的群体中复制的共定位基因更重要。因此,具有人群匹配转录组模型的 TWAS 具有更强的发现和复制能力,表明需要在不同人群中进行更多转录组研究。 TWAS 机械地扩展了不同人群中的 GWAS 研究结果 人群匹配的转录组模型检测到更多可复制的关联 共定位显示 GWAS 变异可能通过基因表达调控发挥作用 需要在不同人群中进行更多 GWAS 和转录组建模遗传学;基因组学;人类遗传学
Most genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) focus on European populations; however, these results cannot always be accurately applied to non-European populations due to genetic architecture differences. Using GWAS summary statistics in the Population Architecture using Genomics and Epidemiology study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we perform TWAS to determine gene-trait associations. We compared results using three transcriptome prediction models derived from Multi-Ethnic Study of Atherosclerosis populations: the African American and Hispanic/Latino (AFHI) model, the European (EUR) model, and the African American, Hispanic/Latino, and European (ALL) model. We identified 240 unique significant trait-associated genes. We found more significant, colocalized genes that replicate in larger cohorts when applying the AFHI model than the EUR or ALL model. Thus, TWAS with population-matched transcriptome models have more power for discovery and replication, demonstrating the need for more transcriptome studies in diverse populations. TWAS mechanistically extends GWAS findings in diverse populations Population-matched transcriptome models detect more replicable associations Colocalization shows GWAS variants likely act through gene expression regulation More GWAS and transcriptome modeling in diverse populations are needed Population; Genetics; Genomics; Human Genetics
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