Genome-wide interaction analysis reveals replicated epistatic effects on brain structure

Hibar, D. P., Stein, J. L., Jahanshad, N., Kohannim, O., Hua, X., Toga, A. W., McMahon, K. L., de Zubicaray, Greig I., Martin, N. G., Wright, M. J., Weiner, M. W., & Thompson, P. M. (2015) Genome-wide interaction analysis reveals replicated epistatic effects on brain structure. Neurobiology of Aging, 36(S1), S151-S158.

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The discovery of several genes that affect the risk for Alzheimer's disease ignited a worldwide search for single-nucleotide polymorphisms (SNPs), common genetic variants that affect the brain. Genome-wide search of all possible SNP-SNP interactions is challenging and rarely attempted because of the complexity of conducting approximately 1011 pairwise statistical tests. However, recent advances in machine learning, for example, iterative sure independence screening, make it possible to analyze data sets with vastly more predictors than observations. Using an implementation of the sure independence screening algorithm (called EPISIS), we performed a genome-wide interaction analysis testing all possible SNP-SNP interactions affecting regional brain volumes measured on magnetic resonance imaging and mapped using tensor-based morphometry. We identified a significant SNP-SNP interaction between rs1345203 and rs1213205 that explains 1.9% of the variance in temporal lobe volume. We mapped the whole brain, voxelwise effects of the interaction in the Alzheimer's Disease Neuroimaging Initiative data set and separately in an independent replication data set of healthy twins (Queensland Twin Imaging). Each additional loading in the interaction effect was associated with approximately 5% greater brain regional brain volume (a protective effect) in both Alzheimer's Disease Neuroimaging Initiative and Queensland Twin Imaging samples.

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7 citations in Scopus
4 citations in Web of Science®
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ID Code: 85767
Item Type: Journal Article
Refereed: Yes
Keywords: Epistasis, Genome-wide, GWAS, GWIA, Interaction, Sure independence screening, Tensor-based morphometry
DOI: 10.1016/j.neurobiolaging.2014.02.033
ISSN: 1558-1497
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copright 2015 Elsevier Inc.
Deposited On: 07 Sep 2015 07:56
Last Modified: 25 Jun 2017 05:01

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