Paper Info
Title
A kernel machine method for detecting effects of interaction between multidimensional variable sets: An imaging genetics application.
Abstract
Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of the interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks.
Year
DOI
Venue
2015
10.1016/j.neuroimage.2015.01.029
NeuroImage
Keywords
Field
DocType
Interaction,Kernel machines,Alzheimer's disease,Cardiovascular disease,Imaging genetics
Disease,Epistasis,Imaging genetics,Genome-wide association study,Cognitive psychology,Psychology,Biomarker (medicine),Genetic association,Single-nucleotide polymorphism,Neuroimaging,Computational biology,Bioinformatics
Journal
Volume
ISSN
Citations 
109
1053-8119
4
PageRank 
References 
Authors
0.46
8
6
Name
Order
Citations
PageRank
Tian Ge1261.52
Thomas E. Nichols214118.85
Debashis Ghosh349649.16
Elizabeth C Mormino4113.31
Jordan W Smoller551.82
Sabuncu Mert R.6134478.78