TY  - JOUR
SN  - 1756-0381
Y1  - 2017///
TI  - Discovery and replication of SNP-SNP interactions for quantitative lipid traits in over 60,000 individuals
SP  - 1
A1  - Holzinger, Emily R.
A1  - Verma, Shefali S.
A1  - Moore, Carrie B.
A1  - Hall, Molly
A1  - De, Rishika
A1  - Gilbert-Diamond, Diane
A1  - Lanktree, Matthew B.
A1  - Pankratz, Nathan
A1  - Amuzu, Antoinette
A1  - Burt, Amber
A1  - Dale, Caroline
A1  - Dudek, Scott
A1  - Furlong, Clement E.
A1  - Gaunt, Tom R.
A1  - Kim, Daniel S.
A1  - Riess, Helene
A1  - Sivapalaratnam, Suthesh
A1  - Tragante, Vinicius
A1  - van Iperen, Erik P. A.
A1  - Brautbar, Ariel
A1  - Carrell, David S.
A1  - Crosslin, David R.
A1  - Jarvik, Gail P.
A1  - Kuivaniemi, Helena
A1  - Kullo, Iftikhar J.
A1  - Larson, Eric B.
A1  - Rasmussen-Torvik, Laura J.
A1  - Tromp, Gerard
A1  - Baumert, Jens
A1  - Cruickshanks, Karen J.
A1  - Farrall, Martin
A1  - Hingorani, Aroon D.
A1  - Hovingh, G. K.
A1  - Kleber, Marcus E.
A1  - Klein, Barbara E.
A1  - Klein, Ronald
A1  - Koenig, Wolfgang
A1  - Lange, Leslie A.
A1  - M?rz, Winfried
A1  - North, Kari E.
A1  - Onland-Moret, N. Charlotte
A1  - Reiner, Alex P.
A1  - Talmud, Philippa J.
A1  - van der Schouw, Yvonne T.
A1  - Wilson, James G.
A1  - Kivimaki, Mika
A1  - Kumari, Meena
A1  - Moore, Jason H.
A1  - Drenos, Fotios
A1  - Asselbergs, Folkert W.
A1  - Keating, Brendan J.
A1  - Ritchie, Marylyn D.
CY  - London
EP  - 20
UR  - https://archiv.ub.uni-heidelberg.de/volltextserver/23283/
N2  - Background: The 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).   Results: Our 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.   Conclusions: These 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.
JF  - BioData Mining
AV  - public
IS  - 25
PB  - BioMed Central
ID  - heidok23283
VL  - 10
ER  -