ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Pippa Thomson |
| Institution: | University of Edinburgh |
| Department: | Institute of Genetics and Molecular Medicine |
| Country: | |
| Proposed Analysis: | Late onset Alzheimer’s disease (LOAD) is a highly heritable disorder with estimates from twin and family-based studies suggesting a heritability of 0.75-0.80. {Gatz, 2006 #1;Lee, 2012 #28} Genome-wide association studies (GWAS) have demonstrated a significant polygenic contribution to LOAD where disease risk is determined by the summation of many alleles of small individual magnitude. {Lee, 2012 #28} Modelling genome-wide polygenic risk scores may be a powerful way of identifying premorbid pathological processes contributing to the disorder whose genetic architecture is related to that of LOAD. We will test the ability of a polygenic risk score to classify individuals “at risk” or affected by LOAD. We will use the publically available summary data from the GERAD1 genome-wide association study to derive a genome-wide polygenic risk score from the individual Illumina 610-Quad BeadChip genotype data available from ADNI. Scores will be derived following et al. (2009; "Common polygenic variation contributes to risk of schizophrenia and bipolar disorder." Nature 460(7256): 748-752.). We will analyse the ability of these scores to discriminate between cases and controls and investigate the distributions of these scores in the two groups. If possible we will also investigate the ability of the genome-wide polygenic risk score to predict which individuals with mild cognitive impairment MCI at baseline converted to AD, using univariate or multivariate models included other non-genetic phenotypic data. We intend to also test these models in a much larger sample from the Generation Scotland: Scottish Family Health Study containing a cohort of individuals at familial risk of developing Alzheimer's disease. |
| Additional Investigators |