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Abstract:
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 SNPxSNP
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
(N-total = 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 SNPxSNP 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.
