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: | Jie Zhang |
| Institution: | Shansier Medical, Inc. Hangzhou, China |
| Department: | Data science |
| Country: | |
| Proposed Analysis: | In the present analysis, we aimed to examine the associations of age, APOE4, sex with plasma and CSF amyloid-beta levels. Further, we also aimed to examine whether this association is modified by different clinical stages (Normal cognition, SMC, MCI and AD). |
| Additional Investigators | |
| Investigator's Name: | Wenjun Zhou |
| Proposed Analysis: | In the present analysis, we aimed to examine the associations of age, APOE4, sex with plasma and CSF amyloid-beta levels. Further, we also aimed to examine whether this association is modified by different clinical stages (Normal cognition, SMC, MCI and AD). |
| Investigator's Name: | Xiwu Wang |
| Proposed Analysis: | Given the complex and progressive nature of mild cognitive impairment (MCI), the ability to delineate and understand the heterogeneous cognitive trajectories is crucial for developing personalized medicine and informing trial design. The primary goal of this study was to examine whether different cognitive trajectories can be identified within subjects with MCI and, if present, to characterize each trajectory in relation to changes in all major Alzheimer’s disease (AD) biomarkers over time.In the current study, by applying a data-driven, longitudinal clustering analysis approach, we investigated whether distinct cognitive trajectories could be derived within the Alzheimer’s Disease Neuroimaging Initiative (ADNI) MCI cohort and, if present, assessed the associations of trajectory membership with longitudinal changes in all major AD biomarkers. |
| Investigator's Name: | Teng Ye |
| Proposed Analysis: | Given the complex and progressive nature of mild cognitive impairment (MCI), the ability to delineate and understand the heterogeneous cognitive trajectories is crucial for developing personalized medicine and informing trial design. The primary goal of this study was to examine whether different cognitive trajectories can be identified within subjects with MCI and, if present, to characterize each trajectory in relation to changes in all major Alzheimer’s disease (AD) biomarkers over time.In the current study, by applying a data-driven, longitudinal clustering analysis approach, we investigated whether distinct cognitive trajectories could be derived within the Alzheimer’s Disease Neuroimaging Initiative (ADNI) MCI cohort and, if present, assessed the associations of trajectory membership with longitudinal changes in all major AD biomarkers. |
