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Interpretation of association signals and identification of causal variants from genome-wide association studies.

Abstract：

:GWAS have been successful in identifying disease susceptibility loci, but it remains a challenge to pinpoint the causal variants in subsequent fine-mapping studies. A conventional fine-mapping effort starts by sequencing dozens of randomly selected samples at susceptibility loci to discover candidate variants, which are then placed on custom arrays or used in imputation algorithms to find the causal variants. We propose that one or several rare or low-frequency causal variants can hitchhike the same common tag SNP, so causal variants may not be easily unveiled by conventional efforts. Here, we first demonstrate that the true effect size and proportion of variance explained by a collection of rare causal variants can be underestimated by a common tag SNP, thereby accounting for some of the "missing heritability" in GWAS. We then describe a case-selection approach based on phasing long-range haplotypes and sequencing cases predicted to harbor causal variants. We compare this approach with conventional strategies on a simulated data set, and we demonstrate its advantages when multiple causal variants are present. We also evaluate this approach in a GWAS on hearing loss, where the most common causal variant has a minor allele frequency (MAF) of 1.3% in the general population and 8.2% in 329 cases. With our case-selection approach, it is present in 88% of the 32 selected cases (MAF = 66%), so sequencing a subset of these cases can readily reveal the causal allele. Our results suggest that thinking beyond common variants is essential in interpreting GWAS signals and identifying causal variants.

journal_name

Am J Hum Genet

journal_title

American journal of human genetics

authors

Wang K,Dickson SP,Stolle CA,Krantz ID,Goldstein DB,Hakonarson H

doi

10.1016/j.ajhg.2010.04.003

subject

Has Abstract

pub_date

2010-05-14 00:00:00

pages

730-42

issue

5

eissn

0002-9297

issn

1537-6605

pii

S0002-9297(10)00204-1

journal_volume

86

pub_type

杂志文章

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