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Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers
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Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers
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Journal Article
Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers
2019
Overview
Genome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
/ Adult
/ Aged
/ Female
/ Genome-wide association studies
/ Genome-Wide Association Study
/ Genomes
/ High-Throughput Nucleotide Sequencing
/ Humanities and Social Sciences
/ Humans
/ Male
/ Polymorphism, Single Nucleotide
/ Power
/ Science
/ Single-nucleotide polymorphism
