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

Authors :
Emily R. Holzinger
Shefali S. Verma
Carrie B. Moore
Molly Hall
Rishika De
Diane Gilbert-Diamond
Matthew B. Lanktree
Nathan Pankratz
Antoinette Amuzu
Amber Burt
Caroline Dale
Scott Dudek
Clement E. Furlong
Tom R. Gaunt
Daniel Seung Kim
Helene Riess
Suthesh Sivapalaratnam
Vinicius Tragante
Erik P.A. van Iperen
Ariel Brautbar
David S. Carrell
David R. Crosslin
Gail P. Jarvik
Helena Kuivaniemi
Iftikhar J. Kullo
Eric B. Larson
Laura J. Rasmussen-Torvik
Gerard Tromp
Jens Baumert
Karen J. Cruickshanks
Martin Farrall
Aroon D. Hingorani
G. K. Hovingh
Marcus E. Kleber
Barbara E. Klein
Ronald Klein
Wolfgang Koenig
Leslie A. Lange
Winfried Mӓrz
Kari E. North
N. Charlotte Onland-Moret
Alex P. Reiner
Philippa J. Talmud
Yvonne T. van der Schouw
James G. Wilson
Mika Kivimaki
Meena Kumari
Jason H. Moore
Fotios Drenos
Folkert W. Asselbergs
Brendan J. Keating
Marylyn D. Ritchie
Source :
BioData Mining, Vol 10, Iss 1, Pp 1-20 (2017)
Publication Year :
2017
Publisher :
BMC, 2017.

Abstract

Abstract 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

Details

Language :
English
ISSN :
17560381
Volume :
10
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BioData Mining
Publication Type :
Academic Journal
Accession number :
edsdoj.425535da8ac4698843693a6461d84e0
Document Type :
article
Full Text :
https://doi.org/10.1186/s13040-017-0145-5