title: Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS).
abstract: 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.
authors.affiliation: Human Genetics, School of Molecular Medical Science, University of Nottingham, Nottingham, UK.
authors.forename: Hui
authors.initials: H
authors.lastname: Shi
authors.forename: Olivia
authors.initials: O
authors.lastname: Belbin
authors.forename: Christopher
authors.initials: C
authors.lastname: Medway
authors.forename: Kristelle
authors.initials: K
authors.lastname: Brown
authors.forename: Noor
authors.initials: N
authors.lastname: Kalsheker
authors.forename: Minerva
authors.initials: M
authors.lastname: Carrasquillo
authors.forename: Petroula
authors.initials: P
authors.lastname: Proitsi
authors.forename: John
authors.initials: J
authors.lastname: Powell
authors.forename: Simon
authors.initials: S
authors.lastname: Lovestone
authors.forename: Alison
authors.initials: A
authors.lastname: Goate
authors.forename: Steven
authors.initials: S
authors.lastname: Younkin
authors.forename: Peter
authors.initials: P
authors.lastname: Passmore
authors.forename: Kevin
authors.initials: K
authors.lastname: Morgan
mesh_terms: D017677:Age Distribution; D000375:Aging / Q000235:genetics*; D000544:Alzheimer Disease / Q000453:epidemiology* / Q000235:genetics*; D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D005819:Genetic Markers / Q000235:genetics*; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D014644:Genetic Variation / Q000235:genetics; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D015995:Prevalence
chemical_list: D005819:Genetic Markers