TY - JOUR
T1 - Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS)
AU - Shi, Hui
AU - Belbin, Olivia
AU - Medway, Christopher
AU - Brown, Kristelle
AU - Kalsheker, Noor
AU - Carrasquillo, Minerva
AU - Proitsi, Petroula
AU - Powell, John
AU - Lovestone, Simon
AU - Goate, Alison
AU - Younkin, Steven
AU - Passmore, Peter
AU - Morgan, Kevin
AU - Genetic and Environmental Risk for Alzheimer's Disease (GERAD1) Consortium
AU - Kehoe, Patrick
N1 - Copyright © 2012 Elsevier Inc. All rights reserved.
PY - 2012/8
Y1 - 2012/8
N2 - Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. We have selected the 10 most promising late-onset Alzheimer's disease (LOAD) susceptibility genes identified through several recent large genome-wide association studies (GWAS). These 10 LOAD genes (APOE, CLU, PICALM, CR1, BIN1, ABCA7, MS4A6A, CD33, CD2AP, and EPHA1) have been tested for association with human aging in our dataset (1385 samples with documented age at death [AAD], age range: 58-108 years; mean age at death: 80.2) using the most significant single nucleotide polymorphisms (SNPs) found in the previous studies. Apart from the APOE locus (rs2075650) which showed compelling evidence of association with risk on human life span (p = 5.27 × 10(-4)), none of the other LOAD gene loci demonstrated significant evidence of association. In addition to examining the known LOAD genes, we carried out analyses using age at death as a quantitative trait. No genome-wide significant SNPs were discovered. Increasing sample size and statistical power will be imperative to detect genuine aging-associated variants in the future. In this report, we also discuss issues relating to the analysis of genome-wide association studies data from different centers and the bioinformatic approach required to distinguish spurious genome-wide significant signals from real SNP associations.
AB - Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. We have selected the 10 most promising late-onset Alzheimer's disease (LOAD) susceptibility genes identified through several recent large genome-wide association studies (GWAS). These 10 LOAD genes (APOE, CLU, PICALM, CR1, BIN1, ABCA7, MS4A6A, CD33, CD2AP, and EPHA1) have been tested for association with human aging in our dataset (1385 samples with documented age at death [AAD], age range: 58-108 years; mean age at death: 80.2) using the most significant single nucleotide polymorphisms (SNPs) found in the previous studies. Apart from the APOE locus (rs2075650) which showed compelling evidence of association with risk on human life span (p = 5.27 × 10(-4)), none of the other LOAD gene loci demonstrated significant evidence of association. In addition to examining the known LOAD genes, we carried out analyses using age at death as a quantitative trait. No genome-wide significant SNPs were discovered. Increasing sample size and statistical power will be imperative to detect genuine aging-associated variants in the future. In this report, we also discuss issues relating to the analysis of genome-wide association studies data from different centers and the bioinformatic approach required to distinguish spurious genome-wide significant signals from real SNP associations.
KW - Age Distribution
KW - Aging
KW - Alzheimer Disease
KW - Chromosome Mapping
KW - Genetic Markers
KW - Genetic Predisposition to Disease
KW - Genetic Variation
KW - Genome-Wide Association Study
KW - Humans
KW - Polymorphism, Single Nucleotide
KW - Prevalence
U2 - 10.1016/j.neurobiolaging.2012.02.014
DO - 10.1016/j.neurobiolaging.2012.02.014
M3 - Article (Academic Journal)
C2 - 22445811
SN - 0197-4580
VL - 33
SP - 1849.e5-18
JO - Neurobiology of Aging
JF - Neurobiology of Aging
IS - 8
ER -