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: | CANDACE CHAN |
| Institution: | UNIVERSITY OF CALIFORNIA, SAN FRANCISCO |
| Department: | Institute for Human Genetics |
| Country: | |
| Proposed Analysis: | Diagnosis of Alzheimer’s disease (AD) is currently reliant on clinical signs and symptoms, often at later stages of disease progression. Early detection and objective diagnosis of AD could be used to identify progression of disease, drug effectiveness, and improve clinical outcomes. We seek to develop novel computational methods to identify biomarker signatures of AD present in DNA sequences. I will use derived biomarker sequences from the genome and train a machine learning model that will classify patients with and without AD. We will leverage insights gained from ADNI genetic data to predict disease AD diagnosis; integration of WGS data from ADNI will enable us to derive patterns of mutations found in AD patients and improve our predictive model. This study will discover viable biomarkers for detection of AD and allow us to contribute to the development of a sequence-based diagnostic platform to confirm disease diagnosis. |
| Additional Investigators |
