JPND:A European DNA bank for deciphering the missing heritability of Alzheimer's disease

Understanding the genetics of Alzheimer's disease is one of the best ways of improving our knowledge of the biology underpinning the disease. Genes are thought to account for around 80% of disease risk. Advances in the field of biomedical genetics have allowed the identification of 26 genes that act to increase a person's risk of developing disease. However, it is believed that there are at least the same number of genes that also contribute to disease risk are yet to be discovered.
To identify new disease related genes substantial additional efforts are required. It is particularly important to maximise sample numbers; studies of other complex genetic diseases have shown that the number of disease genes a study can identify increases with the sample size of the study.
Our primary objective is therefore to increase the number of Alzheimer's disease samples with genetic data to identify new risk genes for disease. We will achieve this via the creation of a European Alzheimer's Disease DNA BioBank (EADB). We have identified a European cohort of 31,911 AD cases (of which 24,049 have no genetic data) and 40,802 controls (of which 15,638 have no genetic data) from 11 countries. We will undertake genotyping of these 39,687 samples with no genetic data and analyse the new data along with existing genetic data via standard methods. This study plan will allow us to identify new Alzheimer's disease risk genes and the biological pathways in which these genes function. This initiative will increase the number of Alzheimer's disease samples available for genetic studies in Europe by more than 4-fold and worldwide by almost 2-fold.
In parallel, the EADB will collect samples from Europe's largest cohort of mild cognitive impairment cases, with a view to identifying genes that change the rate of disease progression and cognitive decline. We have available to us 9,109 mild cognitive impairment cases (of which 6,952 have no genetic data). The cohort includes data on conversion to Alzheimer's disease, cognitive and non-cognitive parameters, cerebrospinal fluid proteins and brain imaging.
The identification of genes that are functional in pathways that act to modify Alzheimer's disease risk and increase the rate of disease progression, or increase cognitive decline in mild cognitive impairment, is essential to allow the development and testing of novel treatments.

Our objective is to significantly increase the generation of Genome Wide Association Study-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.

As a global and growing problem associated with an increasing aged population, studies to improve, focus and streamline research on Alzheimer's disease will have a universal impact.
In addition to the vast academic impact of this study, we anticipate a significant impact on the delivery of clinical trials for AD therapies, and any commercial private sector companies involved in these trials will benefit. Participants can be selected for trials based on their genetic profile, increasing the likelihood of success using a smaller study cohort. In addition, the biomarkers used to measure trial outcome will be more accurately defined leading to clearer interpretation of results. This will impact on study design and the financial investment required finding drugs effective in targeting AD.
The identification of as yet unaccounted for AD genetic risk factors will help guide the research undertaken by, or funded by, commercial companies, government agencies and charities. A better, more comprehensive, genetic profile of AD will improve research focus and deliver better value for money from AD research. This should lead to more impactful research studies for minimal investment.
In the long term, the accurate and early prediction of AD risk has impact for the entire general public through the implementation of early detection and development of personalised medicine. Those at high risk of AD can be identified, together with the specific pathophysiological pathways involved, before providing a personalised medicine to specifically target the manifestation of disease in the individual.