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对来自两个队列的 70,000 多个外显子组中的数千种表型进行全基因组罕见变异分析。

Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts.

机构信息

Helix, 101S Ellsworth Ave Suite 350, San Mateo, CA, 94401, USA.

Desert Research Institute, 2215 Raggio Pkwy, Reno, NV, 89512, USA.

出版信息

Nat Commun. 2020 Jan 28;11(1):542. doi: 10.1038/s41467-020-14288-y.

Abstract

Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp (https://ukb.research.helix.com). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data.

摘要

了解罕见变异的影响对于理解人类健康至关重要。我们针对来自英国生物库的 49960 名外显子组测序个体的 4264 种表型和 Helix 进行外显子组+测序的 21866 名健康内华达州计划(HNP)队列成员的 1934 种表型(与英国生物库重叠 1821 种),分析了罕见(MAF<0.1%)变异。在使用针对罕见变异的定制方法来减少检验统计量膨胀后,我们在对两个队列的荟萃分析中确定了 64 个基于基因的统计学上显著关联,而在仅一个队列中可用的表型中有 37 个。单核苷酸多态性对我们的结果有重要贡献,而且绝大多数关联都不可能通过基因分型芯片来识别。我们的结果可在一个网络应用程序(https://ukb.research.helix.com)中进行交互式浏览。这项全面分析说明了结合 NGS 数据的大型、深度表型未选择人群队列的生物学价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea26/6987107/e858bf12ecfc/41467_2020_14288_Fig1_HTML.jpg

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