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

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 and Cornelia M van Duijn

PLOS ONE, 2014, vol. 9, issue 10, 1-13

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 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

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0109290

DOI: 10.1371/journal.pone.0109290

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