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: | Christian Agudelo |
| Institution: | University of Miami Miller School of Medicine |
| Department: | Neurology |
| Country: | |
| Proposed Analysis: | TITLE: Grey matter microstructure integrity, a biomarker of neurocognitive aging SPECIFIC AIMS: DTI-based measures of grey matter diffusivity are considered biomarkers of microstructure integrity. Loss of grey matter microstructure integrity may be an early step in the progression from normal cognition (CN) to mild cognitive impairment (MCI) to Alzheimer’s Dementia (AD). We hypothesize that beta-amyloid deposition is associated with the loss of grey matter microstructure integrity, and that loss of microstructure integrity precedes grey matter atrophy. We also hypothesize that loss of grey matter microstructure integrity will be associated with neurocognitive impairment. These associations will be evident among those with normal cognition in pre-clinical stages of AD. The following three specific aims are designed to test this hypothesis, which is illustrated in this simplified model of Alzheimer’s disease pathology progression. [beta-amyloid deposition] --> [loss of grey matter microstructure integrity] --> [grey matter atrophy] 1. Cerebral amyloid-deposition and processes associated with amyloid-deposition may be responsible for loss of microstructure integrity in persons with normal cognition and MCI. Specific Aim 1a: We hypothesize that higher total cerebral amyloid deposition (PET with Florbetapir or PIB) will be cross-sectionally associated with higher diffusivities (DTI) of grey matter regions. Specific Aim 1b: We hypothesize that higher rates of total cerebral amyloid deposition will be associated with higher rates of increase of diffusivities in grey matter regions. In specific aims 1a and 1b, we expect that increases in grey matter diffusivity will occur most notably in mesial temporal lobe structures such as the hippocampus. We also expect that these hypothesized relationships will be most evident in CN and MCI participants, as the burden of amyloid deposition tends to plateau later in disease. 2. The loss of regional grey matter microstructure integrity is a step in the progression from non-pathological grey matter to atrophied grey matter in AD. Specific Aim 2a: We hypothesize that higher regional grey matter diffusivities will predict longitudinal regional grey matter atrophy in participants initially with normal cognition or early MCI. 3. The loss of grey matter microstructure integrity may be a structural substrate of early neurocognitive decline. Specific Aim 3a: We hypothesize that higher regional grey matter diffusivities will be associated with lower neurocognitive function. Specific Aim 3b: We hypothesize that higher rates of increase of grey matter diffusivities will be associated with lower neurocognitive function. Diffusivities in mesial temporal lobe structures will have the greatest association with lower neurocognitive function. We expect this relationship to occur even in those considered to be cognitively normal. DATA REQUESTED: 1. DEMOGRAPHICS, MEDICATIONS, and DIAGNOSTIC SUMMARIES. Demographics, medications, and diagnostic summaries will be needed to characterize the analytic subsample and as covariates to statistical models. 2. COGNITIVE ASSESSMENTS Cognitive assessments will be needed for specific aim 3. 3. DTI DATA DTI will be needed for specific aims 1, 2, and 3. If diffusivities for segmented grey matter regions are available, a table with this data would be most desired. Alternatively, the corrected maps of mean diffusivity, radial diffusivity, axial diffusivity, and fractional anisotropy will be needed. 4. MP-RAGE SEGMENTATION DATA MP-RAGE data will be needed if DTI measures of grey matter regions of interest are not detailed in a table. We would need to use an available mask of segmented grey matter regions. Masks available as per the ADNI website include the: - MAPER segmentation by Heckermann et al. - Hippocampal Mask by the Schuff Grup. Alternatively, we could use a whole-brain mask that has already been skull-stripped, and subsequently perform our own segmentation. Skull-stripped whole-brain masks available as per the ADNI website include: - BEaST normalized MPRAGE - BEaST manual brain mask 5. GREY MATTER VOLUMETRIC DATA Grey matter volumetric data are needed to answer specific aim 2. As per the ADNI website, there is more than one avenue to obtain volumetric MRI data, each of which could be valuable to our analysis. First, hippocampal T2 data (Yushkevich and Das) provide volumetric measurements of the hippocampus and its subfields. Second, regional volumetric data could be derived from MP-RAGE data. Third, regional volumetric data may already be organized by grey matter regions in tables available for download. 6. PIB AND FLORBETAPIR PET Amyloid PET imaging data will be needed to answer specific aim 1. Ideally, a table with whole brain SUVr values would be the most efficient way to obtain this data. Alternatively, whole brain and regional SUVr values could be obtained from the PIB and Florbetapir PET imaging data. |
| Additional Investigators |
