Exome sequencing of Finnish isolates enhances rare-variant association power
File(s)
Author(s)
Type
Journal Article
Abstract
Exome-sequencing studies have generally been underpowered to identify deleterious alleles with a large effect on complex traits as such alleles are mostly rare. Because the population of northern and eastern Finland has expanded considerably and in isolation following a series of bottlenecks, individuals of these populations have numerous deleterious alleles at a relatively high frequency. Here, using exome sequencing of nearly 20,000 individuals from these regions, we investigate the role of rare coding variants in clinically relevant quantitative cardiometabolic traits. Exome-wide association studies for 64 quantitative traits identified 26 newly associated deleterious alleles. Of these 26 alleles, 19 are either unique to or more than 20 times more frequent in Finnish individuals than in other Europeans and show geographical clustering comparable to Mendelian disease mutations that are characteristic of the Finnish population. We estimate that sequencing studies of populations without this unique history would require hundreds of thousands to millions of participants to achieve comparable association power.
Date Issued
2019-08-15
Date Acceptance
2019-07-02
Citation
Nature, 2019, 572 (7769), pp.323-328
ISSN
0028-0836
Publisher
Nature Research
Start Page
323
End Page
328
Journal / Book Title
Nature
Volume
572
Issue
7769
Copyright Statement
© The Author(s), under exclusive licence to Springer Nature Limited 2019.
Sponsor
UNIVERSITY OF OULU
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000481414100034&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
Nil
Subjects
Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
GENOME-WIDE ASSOCIATION
LOW-FREQUENCY
MISSING HERITABILITY
CARDIOVASCULAR RISK
BLOOD-PRESSURE
DISEASE
TRAITS
CHOLESTEROL
POPULATION
PREDICTION
Publication Status
Published
Date Publish Online
2019-07-31