There are many active research projects accessing and applying shared ADNI data. Use the search above to find specific research focuses on the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Toshikazu Ikuta |
| Institution: | University of Mississippi |
| Department: | Communication Sciences and Disorders |
| Country: | |
| Proposed Analysis: | While Alzheimer’s disease has been understood as a gray matter disease, recent studies suggest the ineligible role of the white matter. Here we seek to understand genetic impact to age dependent changes in white matter and cognitive declines. Some genetic polymorphisms that increase the risk of Alzheimer’s disease have been shown to have influence on age-associated white matter changes, such as APOE. However, the consequences of genetically influenced white matter change to cognitive decline still remains unclear. The longitudinal Diffusion Tensor Imaging (DTI) data will be analyzed with Tract Based Spatial Statistics (TBSS) and Probabilistic Tractography to isolate the responsible white matter region and to identify the pathways that mediate genetically influenced cognitive decline. Alzheimer’s disease is a progressive disorder, which is shown to be partly genetic, but not fully. More importantly, aging is the most critical risk factor. We aim to assess the genetic influence on aging of white matter integrity, which mediates cognitive decline of the disorder. We first aim to isolate the white matter change that is influenced by AD related genes using TBSS, which is a voxel based approach. This will allow us to look for candidate regions that are genetically influenced without having a priori hypothesis within the white matter tracts. After finding regions of interest from TBSS, we will perform probabilistic tractography from the given regions. This will allow us to find the gray matter region that is mediated by the white matter pathway, which is genetically influenced in an age dependent fashion. Finally, we will test the association between the white matter integrity within the pathway and cognitive declines. The current design will allow us to understand which cognitive decline is genetically affected by changes to which white matter tract. We will employ combinatory use of TBSS and Probabilistic tractography by which we will start without a priori hypothesis of the white matter regions, but will end with a very specific white matter tract. By examining which brain changes cause which age dependent cognitive decline, the study can provide a future target of genetically customized treatment. The use of the finding will not be limited to a futuristic cure such as reconstructive procedure with iPS technique, but can help in choosing cognitive and behavioral therapies. As the finding will help predicting the cognitive domains that will most likely be affected in the future, opportunities can be delivered earlier as appropriate preventive therapies for each individual. We consider that we will and shall be able to start preventive actions before we observe well pronounced cognitive decline. Earlier use of appropriate therapies, cognitive or behavioral, or pharmacological or biological will prevent, or at least slow, the reduction of the QOL in the individual and their caregivers. |
| Additional Investigators |
