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: | Didac Vidal-Pineiro |
| Institution: | University of Oslo |
| Department: | Department of Psychology |
| Country: | |
| Proposed Analysis: | The aim of the study is. We aim to test the relationship between cortical thinning from 4-90 years and gene expression profiles that are associated with specific cell types. These are derived from the Allen brain atlas. The ADNI data will be used to create a replication sample of longitudinal data to compare the findings obtained with an inhouse sample. |
| Additional Investigators | |
| Investigator's Name: | Anders Martin Fjell |
| Proposed Analysis: | We want to use ADNI data as part of a manuscript on Sleep, Aging, and Amyloid-Beta as follows. ADNI data will be used to test the relationship between Amyloid-beta (quantified either by PET or CSF) and sleep disturbances (assessed with NPI). We will use all observations that include both NPI and Amyloid-beta quantification. We will model the relationship with mixed-model logistic regressions (age, sex, diagnostic and subject ID will be also required). This analysis will be a secondary analysis of an overarching paper on sleep, brain changes and Amyloid-beta deposition that will use inhouse datasets as the main sample. |
| Investigator's Name: | Esten Leonardsen |
| Proposed Analysis: | We will use deep learning techniques (Simple Fully Convolutional Network (SFCN-reg) model) to predict brain age. We will carry a phenome-wide association study (PheWAS) to reveal associations with the predictions of the model, including older appearing brains in individuals. Regarding ADNI, we apply the trained model in a transfer learning context, the intermediate representations learned by the SFCN-reg, to see whether they outperform brain age delta as a predictor for Alzheimer's disease (amongst several neurodevelopmental and neurodegenerative diseases). ADNI will be one amongst approximately 30 different datasets used in the study. |
