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: | Nikki Stricker |
| Institution: | Mayo Clinic |
| Department: | Psychiatry and Psychology |
| Country: | |
| Proposed Analysis: | We will examine the diagnostic accuracy of several cognitive measures for differentiating non-demented participants in ADNI who are A+N+ vs. A-N- using A-N- neuropsychological norms that we will soon develop within the Mayo Clinic Study of Aging (MCSA) and two conventional normative data approaches: (a) normative data derived from the MCSA using all CU subjects regardless of biomarker status (updated conventional norms) and (b) applying existing normative scores from the Mayo’s Older Americans Normative Studies (MOANS). Hypothesis: A-N- neuropsychological norms will have higher sensitivity to MCI (CU A-N- vs MCI A+N+) and to subtle cognitive decline among CU participants (CU A-N- vs CU A+N+) relative to conventional norms. We will use clinical, neuropsychological, structural MRI, and amyloid PET data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1, ADNI-GO, ADNI2, and ADNI3). Inclusion criteria will be participants classified as CU or MCI at baseline who have structural MRI and florbetapir (18F-AV45) PET scans available. Sensitivity, specificity and total area under the curve for cognitive measures will be compared across the different normative approaches. Derived optimal cut-offs for each normative approach will be reported, and conventional cut-offs will also be explored. Analyses will be repeated separately for males and females. |
| Additional Investigators | |
| Investigator's Name: | Teresa Christianson |
| Proposed Analysis: | We will examine the diagnostic accuracy of several cognitive measures for differentiating non-demented participants in ADNI who are A+N+ vs. A-N- using A-N- neuropsychological norms that we will soon develop within the Mayo Clinic Study of Aging (MCSA) and two conventional normative data approaches: (a) normative data derived from the MCSA using all CU subjects regardless of biomarker status (updated conventional norms) and (b) applying existing normative scores from the Mayo’s Older Americans Normative Studies (MOANS). Hypothesis: A-N- neuropsychological norms will have higher sensitivity to MCI (CU A-N- vs MCI A+N+) and to subtle cognitive decline among CU participants (CU A-N- vs CU A+N+) relative to conventional norms. We will use clinical, neuropsychological, structural MRI, and amyloid PET data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1, ADNI-GO, ADNI2, and ADNI3). Inclusion criteria will be participants classified as CU or MCI at baseline who have structural MRI and florbetapir (18F-AV45) PET scans available. Sensitivity, specificity and total area under the curve for cognitive measures will be compared across the different normative approaches. Derived optimal cut-offs for each normative approach will be reported, and conventional cut-offs will also be explored. Analyses will be repeated separately for males and females. |
| Investigator's Name: | Michael Basso |
| Proposed Analysis: | Proposed analysis: We will examine the diagnostic accuracy of several cognitive measures for differentiating non-demented participants in ADNI who are A+N+ vs. A-N- using A-N- neuropsychological norms that we will soon develop within the Mayo Clinic Study of Aging (MCSA) and two conventional normative data approaches: (a) normative data derived from the MCSA using all CU subjects regardless of biomarker status (updated conventional norms), in two different forms to compare normative methods and (b) applying and comparing several existing normative scores from the Mayo’s Older Americans Normative Studies (MOANS) and other sources. Hypothesis: A-N- neuropsychological norms will have higher sensitivity to MCI (CU A-N- vs MCI A+N+) and to subtle cognitive decline among CU participants (CU A-N- vs CU A+N+) relative to conventional norms. We will use clinical, neuropsychological, structural MRI, and amyloid PET data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1, ADNI-GO, ADNI2, and ADNI3). Inclusion criteria will be participants classified as CU or MCI at baseline who have structural MRI and florbetapir (18F-AV45) PET scans available. Sensitivity, specificity and total area under the curve for cognitive measures will be compared across the different normative approaches. Derived optimal cut-offs for each normative approach will be reported, and conventional cut-offs will also be explored. Analyses will be repeated separately for males and females. |
