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: | Michelle Nuno |
| Institution: | University of Southern California |
| Department: | Population and Public Health Sciences |
| Country: | |
| Proposed Analysis: | We propose looking at biomarker eligibility criteria when biomarker outcomes are used as the primary analysis. We plan to investigate how different eligibility criteria affect power to detect a treatment effect. |
| Additional Investigators | |
| Investigator's Name: | Mikaela Nishida |
| Proposed Analysis: | The proposed project has several aims. In the first aim, we will explore the association between time-to- progression of Alzheimer’s disease (AD) as defined by the visit-specific clinical diagnosis and study partner type. We will also investigate whether a study partner change during the study is associated with a change in the risk of progression over time. As part of the second aim, we are interested in quantifying the association between time-to-progression of AD and the biomarkers amyloid beta and tau, measured both in CSF and via PET imaging. The third will focus on the development of novel statistical methodologies for efficient biomarker discover. In this aim we will focus on extension of the nested case-control design to assess biomarker utility in underrepresented populations. Specifically we will use ADNI data to compare results from traditional full cohort analyses to those of the nested case-control design when oversampling controls from under-represented populations. |
| Investigator's Name: | Daniel Gillen |
| Proposed Analysis: | The proposed project has several aims. In the first aim, we will explore the association between time-to- progression of Alzheimer’s disease (AD) as defined by the visit-specific clinical diagnosis and study partner type. We will also investigate whether a study partner change during the study is associated with a change in the risk of progression over time. As part of the second aim, we are interested in quantifying the association between time-to-progression of AD and the biomarkers amyloid beta and tau, measured both in CSF and via PET imaging. The third will focus on the development of novel statistical methodologies for efficient biomarker discover. In this aim we will focus on extension of the nested case-control design to assess biomarker utility in underrepresented populations. Specifically we will use ADNI data to compare results from traditional full cohort analyses to those of the nested case-control design when oversampling controls from under-represented populations. |
| Investigator's Name: | Fangqing Liu |
| Proposed Analysis: | We will use the Brain Health Registry Data to investigate how the characteristics of study partner type differ and how these may be associated with differences in time to dropout between study partner dyads, |
