Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease

TY - JOUR

T1 - Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease

AU - Vounou, Maria

AU - Janousova, Eva

AU - Wolz, Robin

AU - Stein, Jason L

AU - Thompson, Paul M

AU - Rueckert, Daniel

AU - Montana, Giovanni

AU - Alzheimer's Disease Neuroimaging Initiative

PY - 2012/3

Y1 - 2012/3

N2 - Scanning the entire genome in search of variants related to imaging phenotypes holds great promise in elucidating the genetic etiology of neurodegenerative disorders. Here we discuss the application of a penalized multivariate model, sparse reduced-rank regression (sRRR), for the genome-wide detection of markers associated with voxel-wise longitudinal changes in the brain caused by Alzheimer's disease (AD). Using a sample from the Alzheimer's Disease Neuroimaging Initiative database, we performed three separate studies that each compared two groups of individuals to identify genes associated with disease development and progression. For each comparison we took a two-step approach: initially, using penalized linear discriminant analysis, we identified voxels that provide an imaging signature of the disease with high classification accuracy; then we used this multivariate biomarker as a phenotype in a genome-wide association study, carried out using sRRR. The genetic markers were ranked in order of importance of association to the phenotypes using a data re-sampling approach. Our findings confirmed the key role of the APOE and TOMM40 genes but also highlighted some novel potential associations with AD.

AB - Scanning the entire genome in search of variants related to imaging phenotypes holds great promise in elucidating the genetic etiology of neurodegenerative disorders. Here we discuss the application of a penalized multivariate model, sparse reduced-rank regression (sRRR), for the genome-wide detection of markers associated with voxel-wise longitudinal changes in the brain caused by Alzheimer's disease (AD). Using a sample from the Alzheimer's Disease Neuroimaging Initiative database, we performed three separate studies that each compared two groups of individuals to identify genes associated with disease development and progression. For each comparison we took a two-step approach: initially, using penalized linear discriminant analysis, we identified voxels that provide an imaging signature of the disease with high classification accuracy; then we used this multivariate biomarker as a phenotype in a genome-wide association study, carried out using sRRR. The genetic markers were ranked in order of importance of association to the phenotypes using a data re-sampling approach. Our findings confirmed the key role of the APOE and TOMM40 genes but also highlighted some novel potential associations with AD.

KW - Algorithms

KW - Alzheimer Disease

KW - Female

KW - Genome-Wide Association Study

KW - Humans

KW - Image Processing, Computer-Assisted

KW - Male

KW - Neuroimaging

KW - Phenotype

U2 - 10.1016/j.neuroimage.2011.12.029

DO - 10.1016/j.neuroimage.2011.12.029

M3 - Article

C2 - 22209813

SN - 1053-8119

VL - 60

SP - 700

EP - 716

JO - NeuroImage

JF - NeuroImage

IS - 1

M1 - N/A

ER -