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

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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.

Autor: Elisabeth M. van Leeuwen, Françoise A. S. Smouter, Tony Kam-Thong, Nazanin Karbalai, Albert V. Smith, Tamara B. Harris, Lenore J



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