• Hui Shi, Olivia Belbin, Christopher Medway, Kristelle Brown, Noor Kalsheker, Minerva Carrasquillo, Petroula Proitsi, John Powell, Simon Lovestone, Alison Goate, Steven Younkin, Peter Passmore, Genetic and Environmental Risk for Alzheimer's Disease Consortium, Kevin Morgan, and Alzheimer's Research UK Consortium.
• Human Genetics, School of Molecular Medical Science, University of Nottingham, Nottingham, UK.
• Neurobiol. Aging. 2012 Aug 1;33(8):1849.e5-18.

AbstractGenetics 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.Copyright © 2012 Elsevier Inc. All rights reserved.

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