The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.

The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.

Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL...

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Main Authors: Elisabeth M van Leeuwen, Françoise A S Smouter, Tony Kam-Thong, Nazanin Karbalai, Albert V Smith, Tamara B Harris, Lenore J Launer, Colleen M Sitlani, Guo Li, Jennifer A Brody, Joshua C Bis, Charles C White, Alok Jaiswal, Ben A Oostra, Albert Hofman, Fernando Rivadeneira, Andre G Uitterlinden, Eric Boerwinkle, Christie M Ballantyne, Vilmundur Gudnason, Bruce M Psaty, L Adrienne Cupples, Marjo-Riitta Järvelin, Samuli Ripatti, Aaron Isaacs, Bertram Müller-Myhsok, Lennart C Karssen, Cornelia M van Duijn
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0109290
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Summary:Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.
ISSN:1932-6203

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