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Steffens M, Becker T, Sander T, et al. Feasible and successful: genome-wide interaction analysis involving all 1.9 x 10(11) pair-wise interaction tests. Hum Hered. 2010;69(4):268-84doi: 10.1159/000295896.
Steffens, M., Becker, T., Sander, T., Fimmers, R., Herold, C., Holler, D. A., Leu, C., Herms, S., Cichon, S., Bohn, B., Gerstner, T., Griebel, M., Nöthen, M. M., Wienker, T. F., & Baur, M. P. (2010). Feasible and successful: genome-wide interaction analysis involving all 1.9 x 10(11) pair-wise interaction tests. Human heredity, 69(4), 268-84. https://doi.org/10.1159/000295896
Steffens, Michael, et al. "Feasible and successful: genome-wide interaction analysis involving all 1.9 x 10(11) pair-wise interaction tests." Human heredity vol. 69,4 (2010): 268-84. doi: https://doi.org/10.1159/000295896
Steffens M, Becker T, Sander T, Fimmers R, Herold C, Holler DA, Leu C, Herms S, Cichon S, Bohn B, Gerstner T, Griebel M, Nöthen MM, Wienker TF, Baur MP. Feasible and successful: genome-wide interaction analysis involving all 1.9 x 10(11) pair-wise interaction tests. Hum Hered. 2010;69(4):268-84. doi: 10.1159/000295896. Epub 2010 Mar 31. PMID: 20357478.
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Hum Hered. 2010;69(4):268-84. doi: 10.1159/000295896. Epub 2010 Mar 31.

Feasible and successful: genome-wide interaction analysis involving all 1.9 x 10(11) pair-wise interaction tests.

Human heredity

Michael Steffens, Tim Becker, Thomas Sander, Rolf Fimmers, Christine Herold, Daniela A Holler, Costin Leu, Stefan Herms, Sven Cichon, Bastian Bohn, Thomas Gerstner, Michael Griebel, Markus M Nöthen, Thomas F Wienker, Max P Baur

Affiliations

  1. Institute for Medical Biometry, Informatics and Epidemiology, University of Bonn, Bonn, Germany.

PMID: 20357478 DOI: 10.1159/000295896

Abstract

The Genome-Wide Association Study (GWAS) is the study design of choice for detecting common genetic risk factors for multifactorial diseases. The performance of full Genome-Wide Interaction Analyses (GWIA) has always been considered computationally challenging. Two-stage strategies to reduce the amount of numerical analysis require the detection of single marker effects or prior pathophysiological hypotheses before the analysis of interaction. This prevents the detection of pure epistatic effects. Our case-control study in idiopathic generalized epilepsy demonstrates that a full GWIA is feasible through use of data compression, specific data representation, interleaved data organization, and parallelization of the analysis on a multi-processor system. Following extensive quality control of the genotypes, our final list of top interaction hits contains only pairs of interacting SNPs with negligible marginal effects. The TOP HIT interaction was between a SNP-pair intragenic to gene DNER (chr 2) and gene CTNNA3 (chr 10). Both of these genes are functionally involved in neuronal migration, synaptogenesis, and the formation of neuronal circuits. Our results therefore indicate a possible interaction between these two genes in epileptogenesis. Results from GWAS are beginning to reveal a 'missing heritability' in complex traits and diseases. Systematic, hypothesis-free analysis of epistatic interaction (GWIA) may help to close this increasingly recognized gap in heritability.

Copyright 2010 S. Karger AG, Basel.

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