Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individualsReport as inadecuate




Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals - Download this document for free, or read online. Document in PDF available to download.

BioData Mining

, 10:25

First Online: 24 July 2017Received: 02 January 2017Accepted: 12 July 2017

Abstract

BackgroundThe genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits: low-density lipoprotein cholesterol LDL-C, high-density lipoprotein cholesterol HDL-C, total cholesterol TC, and triglycerides TG.

ResultsOur analysis consisted of a discovery phase using a merged dataset of five different cohorts n = 12,853 to n = 16,849 depending on lipid phenotype and a replication phase with ten independent cohorts totaling up to 36,938 additional samples. Filters are often applied before interaction testing to correct for the burden of testing all pairwise interactions. We used two different filters: 1. A filter that tested only single nucleotide polymorphisms SNPs with a main effect of p < 0.001 in a previous association study. 2. A filter that only tested interactions identified by Biofilter 2.0. Pairwise models that reached an interaction significance level of p < 0.001 in the discovery dataset were tested for replication. We identified thirteen SNP-SNP models that were significant in more than one replication cohort after accounting for multiple testing.

ConclusionsThese results may reveal novel insights into the genetic etiology of lipid levels. Furthermore, we developed a pipeline to perform a computationally efficient interaction analysis with multi-cohort replication.

KeywordsGenetics Lipids Interactions Computational genetics Genetic epidemiology Electronic supplementary materialThe online version of this article doi:10.1186-s13040-017-0145-5 contains supplementary material, which is available to authorized users.

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Author: Emily R. Holzinger - Shefali S. Verma - Carrie B. Moore - Molly Hall - Rishika De - Diane Gilbert-Diamond - Matthew B. 

Source: https://link.springer.com/







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