The Challenges of Genome-Wide Interaction Studies: Lessons to Learn from the Analysis of HDL Blood Levels

Elisa Leeuwen, FAS Smouter, T Kam-Thong, N Karbalai, AV Smith, TB Harris, LJ (Lenore) Launer, CM Sitlani, G Li, JA Brody, JC Bis, CC White, A Jaiswal, Ben Oostra, Bert Hofman, Fernando Rivadeneira, André Uitterlinden, E Boerwinkle, CM Ballantyne, V GudnasonBM Psaty, LA Cupples, MR Jarvelin, S Ripatti, Aaron Isaacs, B Muller-Myhsok, Lennart Karssen, Cornelia Duijn

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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.
Original languageUndefined/Unknown
JournalPLoS One (print)
Volume9
Issue number10
DOIs
Publication statusPublished - 2014

Research programs

  • EMC MM-01-39-09-A
  • EMC NIHES-01-64-02

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