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: | Jason Zhang |
| Institution: | UCL |
| Department: | Neurology |
| Country: | |
| Proposed Analysis: | Genome-wide association analyses and exome sequencing have revolutionized our understanding of Alzheimer’s disease pathogenesis involves identifying microglial and lipid metabolism genes. However, the rate of decline in cases with the disease is also highly variable, and this variability is poorly understood. It is hypothesised that a core set of genetic variants drive the rate of progression of Disease and that their effect may be brain region specific. GWAS of the rate of decline/Survival analysis will elucidate variants which will affect the rate of decline in AD. We hope to employ machine learning techniques such as survival random forests to identify the effects of various genes on the rate of decline. Cross-validated models will also be employed to ensure replicability. Any significant finding will be validated in smaller cohorts we can access or 20% of the total sample number. The ADNI datasets will be an essential resource for our study. |
| Additional Investigators |
