Identification of gene pathways implicated in Alzheimer's
disease using longitudinal imaging phenotypes with sparse
regression

J 2012

Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression

SILVER, Matt, Eva JANOUŠOVÁ, Xue HUA, Paul M. THOMPSON, Giovanni MONTANA et. al.

Základní údaje

Originální název

Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression

Autoři

SILVER, Matt (826 Velká Británie a Severní Irsko, garant), Eva JANOUŠOVÁ (203 Česká republika, domácí), Xue HUA (840 Spojené státy), Paul M. THOMPSON (840 Spojené státy) a Giovanni MONTANA (840 Spojené státy)

Vydání

Neuroimage, Elsevier, 2012, 1053-8119

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

Genetika a molekulární biologie

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 6.252

Kód RIV

RIV/00216224:14110/12:00063448

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.1016/j.neuroimage.2012.08.002

UT WoS

000310379100066

Klíčová slova anglicky

Alzheimer's disease; Imaging genetics; Atrophy; Gene pathways; Sparse regression

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 31. 1. 2014 12:45, RNDr. Eva Koriťáková, Ph.D.

Anotace

V originále

We present a new method for the detection of gene pathways associated with a multivariate quantitative trait, and use it to identify causal pathways associated with an imaging endophenotype characteristic of longitudinal structural change in the brains of patients with Alzheimer's disease (AD). Our method, known as pathways sparse reduced-rank regression (PsRRR), uses group lasso penalised regression to jointly model the effects of genome-wide single nucleotide polymorphisms (SNPs), grouped into functional pathways using prior knowledge of gene-gene interactions. Pathways are ranked in order of importance using a resampling strategy that exploits finite sample variability. Our application study uses whole genome scans and MR images from 99 probable AD patients and 164 healthy elderly controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. 66,182 SNPs are mapped to 185 gene pathways from the KEGG pathway database. Voxel-wise imaging signatures characteristic of AD are obtained by analysing 3D patterns of structural change at 6,12 and 24 months relative to baseline. High-ranking, AD endophenotype-associated pathways in our study include those describing insulin signalling, vascular smooth muscle contraction and focal adhesion. All of these have been previously implicated in AD biology. In a secondary analysis, we investigate SNPs and genes that may be driving pathway selection. High ranking genes include a number previously linked in gene expression studies to beta-amyloid plaque formation in the AD brain (PIK3R3,PIK3CC, PRKCA and PRKCB), and to AD related changes in hippocampal gene expression (ADCY2, ACTN1, ACACA, and GNAI1). Other high ranking previously validated AD endophenotype-related genes include CR1, TOMM40 and APOE.

Přiložené soubory

silver_NeuroImage.pdf

Požádat o autorskou verzi souboru

Citovat

SILVER, Matt, Eva JANOUŠOVÁ, Xue HUA, Paul M. THOMPSON a Giovanni MONTANA. Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression. Neuroimage. Elsevier, 2012, roč. 63, č. 3, s. 1681-1694. ISSN 1053-8119. Dostupné z: https://dx.doi.org/10.1016/j.neuroimage.2012.08.002.

@article{1084918,
   author = {Silver, Matt and Janoušová, Eva and Hua, Xue and Thompson, Paul M. and Montana, Giovanni},
   article_number = {3},
   doi = {http://dx.doi.org/10.1016/j.neuroimage.2012.08.002},
   keywords = {Alzheimer's disease; Imaging genetics; Atrophy; Gene pathways; Sparse regression},
   language = {eng},
   issn = {1053-8119},
   journal = {Neuroimage},
   title = {Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression},
   volume = {63},
   year = {2012}
}

TY  - JOUR
ID  - 1084918
AU  - Silver, Matt - Janoušová, Eva - Hua, Xue - Thompson, Paul M. - Montana, Giovanni
PY  - 2012
TI  - Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression
JF  - Neuroimage
VL  - 63
IS  - 3
SP  - 1681-1694
EP  - 1681-1694
PB  - Elsevier
SN  - 10538119
KW  - Alzheimer's disease
KW  - Imaging genetics
KW  - Atrophy
KW  - Gene pathways
KW  - Sparse regression
N2  - We present a new method for the detection of gene pathways associated with a multivariate quantitative trait, and use it to identify causal pathways associated with an imaging endophenotype characteristic of longitudinal structural change in the brains of patients with Alzheimer's disease (AD). Our method, known as pathways sparse reduced-rank regression (PsRRR), uses group lasso penalised regression to jointly model the effects of genome-wide single nucleotide polymorphisms (SNPs), grouped into functional pathways using prior knowledge of gene-gene interactions. Pathways are ranked in order of importance using a resampling strategy that exploits finite sample variability. Our application study uses whole genome scans and MR images from 99 probable AD patients and 164 healthy elderly controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. 66,182 SNPs are mapped to 185 gene pathways from the KEGG pathway database. Voxel-wise imaging signatures characteristic of AD are obtained by analysing 3D patterns of structural change at 6,12 and 24 months relative to baseline. High-ranking, AD endophenotype-associated pathways in our study include those describing insulin signalling, vascular smooth muscle contraction and focal adhesion. All of these have been previously implicated in AD biology. In a secondary analysis, we investigate SNPs and genes that may be driving pathway selection. High ranking genes include a number previously linked in gene expression studies to beta-amyloid plaque formation in the AD brain (PIK3R3,PIK3CC, PRKCA and PRKCB), and to AD related changes in hippocampal gene expression (ADCY2, ACTN1, ACACA, and GNAI1). Other high ranking previously validated AD endophenotype-related genes include CR1, TOMM40 and APOE.
ER  -

SILVER, Matt, Eva JANOUŠOVÁ, Xue HUA, Paul M. THOMPSON a Giovanni MONTANA. Identification of gene pathways implicated in Alzheimer's disease using longitudinal imaging phenotypes with sparse regression. \textit{Neuroimage}. Elsevier, 2012, roč.~63, č.~3, s.~1681-1694. ISSN~1053-8119. Dostupné z: https://dx.doi.org/10.1016/j.neuroimage.2012.08.002.

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