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: | Seunggeun Lee |
| Institution: | Seoul National University |
| Department: | Data Science |
| Country: | |
| Proposed Analysis: | We will develop integrative analysis approaches of genetics and brain imaging phenotypes and apply them to ADNI to identify brain features predictive to Alzheimer’s disease. We will first carry out imaging genetics association analysis to identify genetic variants associated with phenotypic changes of brain-regions due to Alzheimer's disease (AD). Single variant and gene-based tests will be used with adjusting for covariates such as genetic PCs for population stratification adjustment. ROI will be used as phenotypes. Second, we will apply deep-learning-based dimension-reduction methods to identify imaging features that are associated with Alzheimer’s diseases. We will use raw MRI data as input. The method will use multiview embedding for image phenotypes, genetic markers associated with AD and AD phenotypes. We will evaluate the prediction performance of the identified features to predict AD risk. |
| Additional Investigators |
