TY - JOUR
T1 - The challenges of genome-wide interaction studies
T2 - lessons to learn from the analysis of HDL blood levels
AU - van Leeuwen, Elisabeth M
AU - Smouter, Françoise A S
AU - Kam-Thong, Tony
AU - Karbalai, Nazanin
AU - Smith, Albert V
AU - Harris, Tamara B
AU - Launer, Lenore J
AU - Sitlani, Colleen M
AU - Li, Guo
AU - Brody, Jennifer A
AU - Bis, Joshua C
AU - White, Charles C
AU - Jaiswal, Alok
AU - Oostra, Ben A
AU - Hofman, Albert
AU - Rivadeneira, Fernando
AU - Uitterlinden, Andre G
AU - Boerwinkle, Eric
AU - Ballantyne, Christie M
AU - Gudnason, Vilmundur
AU - Psaty, Bruce M
AU - Cupples, L Adrienne
AU - Järvelin, Marjo-Riitta
AU - Ripatti, Samuli
AU - Isaacs, Aaron
AU - Müller-Myhsok, Bertram
AU - Karssen, Lennart C
AU - van Duijn, Cornelia M
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Cholesterol, HDL/blood
KW - Female
KW - Genome-Wide Association Study
KW - Humans
KW - Male
KW - Middle Aged
KW - Polymorphism, Single Nucleotide
U2 - 10.1371/journal.pone.0109290
DO - 10.1371/journal.pone.0109290
M3 - Article
C2 - 25329471
SN - 1932-6203
VL - 9
SP - e109290
JO - PLOS ONE
JF - PLOS ONE
IS - 10
ER -