O2‐06–01: A powerful, genome‐wide association scan for susceptibility genes for late‐onset Alzheimer's disease
Year: 2008
Type: article
Study design: Observational Study
Abstract: The generation of dense SNP marker maps and the decoding of the LD architecture of the human genome, together with developments in SNP genotyping platforms have allowed researchers to capture the entire genome's common variation in a single experiment, testing the majority of genes and inter-genic regions. Such genome-wide association (GWA) studies provide a hypothesis-free design that permits the identification of novel genetic risk factors, pathways and gene interactions. We are conducting the largest GWA study in Alzheimer's Disease (AD), a genetically complex disease in which multiple genes are thought to confer modest risk for disease development. By using large, well-characterised case-control samples, collectively totalling over 16,000 individuals, we have sufficient power to identify genes of modest effect and reduce spurious false positive findings. We have adopted a tiered genotyping strategy. In Stage 1 DNA from a multi-centre collaboration from the UK, of 3984 AD cases and over 6000 controls (1,229 age matched and 4–5000 additional unscreened population controls genotyped as part of the UK based 1958 Birth Cohort study) are being genotyped using the Illumina HumanHap550 platform at the Sanger centre (Cambridge, UK). The most significant SNPs from Stage 1 will be genotyped in 2,131 cases and 2,845 controls from the USA and 1,057 UK age-matched, screened controls not included in the first stage. We will also conduct meta-analyses using data from our study and those available from other GWA studies in AD, merging information from over 20,000 individuals. We will present results based on over 10,000 UK samples from Stage 1 of this study, focusing on our most promising associations and discuss future research directions. We are undertaking the most powerful genetic association study in AD to date. Our study has sufficient power to detect genes of small effect, novel pathways and interactions and the data generated will be of considerable importance for future AD research.
Source: Alzheimer s & Dementia
Authors: Julie Williams, Richard Abraham, Angharad Morgan, Rebecca Sims, Paul Hollingworth, Michael O'Donovan, Michael Owen, Peter Holmans, Ivan Nikolov, Valentina Moskvina, Simon Lovestone, David Rubinsztein, Carol Brayne, Mike Gill, Brian Lawlor, Kevin Morgan, Peter Passmore, Patrick Kehoe, Clive Holmes, David Smith, David Mann, John Hardy, Martin Rossor, Nick Fox, Simon Mead
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2144600979