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

J 2012

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

VOUNOU, Maria, Eva JANOUŠOVÁ, Robin WOLZ, Jason L STEIN, Paul M THOMPSON et. al.

Základní údaje

Originální název

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

Autoři

VOUNOU, Maria, Eva JANOUŠOVÁ, Robin WOLZ, Jason L STEIN, Paul M THOMPSON, Daniel RUECKERT a Giovanni MONTANA

Vydání

Neuroimage, Spojené státy americké, Elsevier, 2012, 1053-8119

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30000 3. Medical and Health Sciences

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 6.252

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.1016/j.neuroimage.2011.12.029

UT WoS

000301218700072

Klíčová slova anglicky

imaging genetics, genome-wide association, sparse reduce rank regression, sRRR, penalized multivariate model, Alzheimer's disease, mild cognitive impairment, variable selection

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 23. 4. 2014 15:22, Soňa Böhmová

Anotace

V originále

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 resampling approach. Our findings confirmed the key role of the APOE and TOMM40 genes but also highlighted some novel potential associations with AD.

Citovat

VOUNOU, Maria, Eva JANOUŠOVÁ, Robin WOLZ, Jason L STEIN, Paul M THOMPSON, Daniel RUECKERT a Giovanni MONTANA. Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease. Neuroimage. Spojené státy americké: Elsevier, 2012, roč. 60, č. 1, s. 700-716. ISSN 1053-8119. Dostupné z: https://dx.doi.org/10.1016/j.neuroimage.2011.12.029.

@article{991082,
   author = {Vounou, Maria and Janoušová, Eva and Wolz, Robin and Stein, Jason L and Thompson, Paul M and Rueckert, Daniel and Montana, Giovanni},
   article_location = {Spojené státy americké},
   article_number = {1},
   doi = {http://dx.doi.org/10.1016/j.neuroimage.2011.12.029},
   keywords = {imaging genetics, genome-wide association, sparse reduce rank regression, sRRR, penalized multivariate model, Alzheimer's disease, mild cognitive impairment, variable selection},
   language = {eng},
   issn = {1053-8119},
   journal = {Neuroimage},
   title = {Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease},
   url = {http://www.sciencedirect.com/science/article/pii/S1053811911014315},
   volume = {60},
   year = {2012}
}

TY  - JOUR
ID  - 991082
AU  - Vounou, Maria - Janoušová, Eva - Wolz, Robin - Stein, Jason L - Thompson, Paul M - Rueckert, Daniel - Montana, Giovanni
PY  - 2012
TI  - Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease
JF  - Neuroimage
VL  - 60
IS  - 1
SP  - 700-716
EP  - 700-716
PB  - Elsevier
SN  - 10538119
KW  - imaging genetics, genome-wide association, sparse reduce rank regression, sRRR, penalized multivariate model, Alzheimer's disease, mild cognitive impairment, variable selection
UR  - http://www.sciencedirect.com/science/article/pii/S1053811911014315
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 resampling approach. Our findings confirmed the key role of the APOE and TOMM40 genes but also highlighted some novel potential associations with AD.
ER  -

VOUNOU, Maria, Eva JANOUŠOVÁ, Robin WOLZ, Jason L STEIN, Paul M THOMPSON, Daniel RUECKERT a Giovanni MONTANA. Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease. \textit{Neuroimage}. Spojené státy americké: Elsevier, 2012, roč.~60, č.~1, s.~700-716. ISSN~1053-8119. Dostupné z: https://dx.doi.org/10.1016/j.neuroimage.2011.12.029.

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