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Understanding the genetics of Alzheimer’s disease (AD) is one of the best ways of improving our knowledge of the underlying pathophysiological processes. Indeed, genetic factors account for up to 80% of the attributable risk in common AD forms. It is likely that most of the pathophysiological pathways in AD are driven by or include genetic determinants. The advent of genomic approaches (such as genome-wide association studies, GWASs) has led to the characterization of 26 genetic determinants. However, less than 50% of the AD genetic attributable risk has been characterised; substantial additional efforts are thus still required to define the genetic landscape in AD. It will be particularly important to maximize study population sizes; studies of other multifactorial diseases have shown that the number of identified variants increases with the sample size.

Our objective is thus to significantly increase the generation of GWAS-based population data via the creation of a European Alzheimer’s Disease DNA BioBank (EADB). We shall be able to collate 31,911 AD cases (of which 24,049 have yet to be genotyped) and 40,802 controls (of which 15,638 have yet to be genotyped) from 11 countries. GWASs and complementary statistical studies (based on genotype and imputation data) will be performed, in order to capture the missing heritability and identify potential disease pathways. This initiative will increase the number of AD samples available for genetic studies in Europe by more than 4-fold and worldwide by almost 2-fold. In parallel, the EADB will collect DNA samples from Europe’s largest longitudinal cohort of MCI cases, with a view to identifying genetic markers that modulate the rate of disease progression and cognitive decline. At present, we have compiled approximately 9,109 MCI cases (of which 6,952 have yet to be genotyped) and have data on AD conversion, neuropsychological parameters, cerebrospinal fluid biomarkers and neuroimaging for most of these samples. We shall investigate the influence of genetic risk factors for AD in a genome-wide- or hypothesis-based manner. From a translational perspective, the identification of genetic factors in pathways that modulate the AD risk and increase the rate of disease progression/cognitive decline in MCI will be pivotal for the development and testing of therapeutic approaches.

 

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