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

被引：96

作者：

Cirulli, Elizabeth T. ^{[1
]}

White, Simon ^{[1
]}

Read, Robert W. ^{[2
,3
]}

Elhanan, Gai ^{[2
,3
]}

Metcalf, William J. ^{[2
,3
]}

Tanudjaja, Francisco ^{[1
]}

Fath, Donna M. ^{[1
]}

Sandoval, Efren ^{[1
]}

Isaksson, Magnus ^{[1
]}

Schlauch, Karen A. ^{[2
,3
]}

Grzymski, Joseph J. ^{[2
,3
]}

Lu, James T. ^{[1
]}

Washington, Nicole L. ^{[1
]}

机构：

[1] Helix, 101S Ellsworth Ave Suite 350, San Mateo, CA 94401 USA

[2] Desert Res Inst, 2215 Raggio Pkwy, Reno, NV 89512 USA

[3] Renown Inst Hlth Innovat, Reno, NV 89512 USA

来源：

NATURE COMMUNICATIONS | 2020年 / 11卷 / 01期

基金：

英国医学研究理事会;

关键词：

IDENTIFIES COMMON; ASSOCIATION; MUTATIONS; RISK; ARCHITECTURE; METAANALYSIS; DISCOVERY; DISEASES; TOOL;

D O I：

10.1038/s41467-020-14288-y

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：10

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