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's Name:||Aristotle Voineskos|
|Institution:||Centre for Addiction and Mental Health, University of Toronto|
|Proposed Analysis:||We would like to request access to the ADNI database in order to provide additional evidence for a number of hypotheses that our lab has been developing on the effects of Alzheimer's disease genetic risk factors and regional brain morphology.. We have the tools and computational ability to analyze MR images acquired from both 1.5T and 3T strength scanners with sophisticated processing pipelines, to measure brain morphology, including cortical thickness, an informative predictor of initial neurostructural deficits found at the earliest stages of Alzheimer's diease, such as thinning of the etorhinal cortex. Growing knowledge of multiple related pathophysiologies of Alzheimer's disease, particularly neurotrophin secretion, activity, and APP processing, has led us to pursue a number of hypotheses that access to ADNI data would allow us to investigate in a much greater, more scientifically valuable capacity. Some of our initial findings in the field have been driven by the search for early risk factors and predictors of disease; we have found age-dependent effects of the BDNF val66met polymorphism on cortical thickness and cognition in a cross-sectional study of 69 healthy controls (Voineskos et al., 2011, Arch. Gen. Psych.). Access to the ADNI data would allow us to replicate this finding longitudinally. As a next step, we plan to use our knowledge of the neurogenetic pathways of Alzheimer's risk genes to more accurately predict disease susceptibility and outcome at multiple levels. It has been found that pro-BDNF excretion is largely dependent upon this val66met polymorphism and it's interaction with the vesicular sorting protein SORL1. We have preliminary data demonstrating effects of genetic variation in the SORL1 gene on brain structure and circuitry– results that will be presented at the upcoming Imaging-Genetics Conference in Irvine California. If the differential release of BDNF is being driven in part by the interaction of variants in its own pro-domain as well as in the SORL1 gene, we might expect to find greater levels of AB1-42 in the CSF and greater thinning of the temporal cortex in individuals possessing both risk genotypes than any other combination. We have also recently found effects of the well-known APOE e4 risk allele on subcortical structures, however are underpowered to further investigate the combinatory effects of variation at these genes in our sample alone. APOE is a ligand of SORL1 and may play a role in the localization of BACE1 to vesicles containing APP – providing further impetus to examine downstream effects of its variation on multiple phenotypes. We propose to use the ADNI dataset to explore the interaction of APOE, BDNF and SORL1 in addition to the effects of other Alzheimer risk genes on neuroimaging and cognitive phenotypes including, but not limited to cortical thickness, subcortical structure volume, and peripheral measures such as CSF AB1-42 levels. Additionally, the large ADNI dataset would present an excellent opportunity to corroborate and extend our findings by going beyond our intermediate phenotype approach in healthy controls and looking into mild cognitive impairment and Alzheimer's patients using both cross-sectional and longitudinal approaches.|
|Investigator's Name:||Daniel Felsky|
|Proposed Analysis:||Mr. Felsky is a graduate student training in my laboratory and will work on the proposed project under my supervision|