ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
| Principal Investigator | |
| Principal Investigator's Name: | Paul Mattis |
| Institution: | Feinstein Institute of Medical Research |
| Department: | Functional Brain Imaging Lab |
| Country: | |
| Proposed Analysis: | There are no widely available tests to clearly exclude the presence of Alzheimer’s disease (AD) when considering the clinical diagnosis of Parkinson’s disease (PD) Dementia (PDD). This poses a significant problem within both patient care and for clinical trials. In separate studies, using spatial covariance mapping of 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) imaging data, we have identified separate patterns of brain metabolism associated with cognitive functioning in patients with PD and AD. However, these patterns have yet to be examined outside of their own study population. Our overarching hypothesis is that our PD Cognition Pattern (PDCP) can be utilized to quantify the cognitive dysfunction associated with PD and serve as an objective biomarker within subjects suspected of having and diagnosed with PD. We propose that PDCP activity is uniquely associated with Parkinson’s disease and distinguishable from cognitive dysfunction in AD and from the neuroimaging biomarker AD Related Pattern (ADRP). B. Specific Aims We plan to test this hypothesis by pursuing the following specific aims: Aim 1: Examine the sensitivity and specificity of our two metabolic covariance networks in the differentiation of AD and PD. Simply, we hypothesize that patients with PD will not exhibit high levels of ADRP activity, and that patients with AD will not exhibit high levels of PDCP. Aim 2: Evaluate the relationship between these unique metabolic networks and neuropsychological functioning. Specifically, we hypothesize that PDCP will correlate with neuropsychological data in PD but not AD patients, and ADRP will correlate with neuropsychological data in AD but not AD patients. |
| Additional Investigators | |
| Investigator's Name: | David Eidelberg |
| Proposed Analysis: | A. Hypothesis There are no widely available tests to clearly exclude the presence of Alzheimer’s disease (AD) when considering the clinical diagnosis of Parkinson’s disease (PD) Dementia (PDD). This poses a significant problem within both patient care and for clinical trials. In separate studies, using spatial covariance mapping of 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) imaging data, we have identified separate patterns of brain metabolism associated with cognitive functioning in patients with PD and AD. However, these patterns have yet to be examined outside of their own study population. Our overarching hypothesis is that our PD Cognition Pattern (PDCP) can be utilized to quantify the cognitive dysfunction associated with PD and serve as an objective biomarker within subjects suspected of having and diagnosed with PD. We propose that PDCP activity is uniquely associated with Parkinson’s disease and distinguishable from cognitive dysfunction in AD and from the neuroimaging biomarker AD Related Pattern (ADRP). B. Specific Aims We plan to test this hypothesis by pursuing the following specific aims: Aim 1: Examine the sensitivity and specificity of our two metabolic covariance networks in the differentiation of AD and PD. Simply, we hypothesize that patients with PD will not exhibit high levels of ADRP activity, and that patients with AD will not exhibit high levels of PDCP. Aim 2: Evaluate the relationship between these unique metabolic networks and neuropsychological functioning. Specifically, we hypothesize that PDCP will correlate with neuropsychological data in PD but not AD patients, and ADRP will correlate with neuropsychological data in AD but not AD patients. |
| Investigator's Name: | Christian Habeck |
| Proposed Analysis: | A. Hypothesis There are no widely available tests to clearly exclude the presence of Alzheimer’s disease (AD) when considering the clinical diagnosis of Parkinson’s disease (PD) Dementia (PDD). This poses a significant problem within both patient care and for clinical trials. In separate studies, using spatial covariance mapping of 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) imaging data, we have identified separate patterns of brain metabolism associated with cognitive functioning in patients with PD and AD. However, these patterns have yet to be examined outside of their own study population. Our overarching hypothesis is that our PD Cognition Pattern (PDCP) can be utilized to quantify the cognitive dysfunction associated with PD and serve as an objective biomarker within subjects suspected of having and diagnosed with PD. We propose that PDCP activity is uniquely associated with Parkinson’s disease and distinguishable from cognitive dysfunction in AD and from the neuroimaging biomarker AD Related Pattern (ADRP). B. Specific Aims We plan to test this hypothesis by pursuing the following specific aims: Aim 1: Examine the sensitivity and specificity of our two metabolic covariance networks in the differentiation of AD and PD. Simply, we hypothesize that patients with PD will not exhibit high levels of ADRP activity, and that patients with AD will not exhibit high levels of PDCP. Aim 2: Evaluate the relationship between these unique metabolic networks and neuropsychological functioning. Specifically, we hypothesize that PDCP will correlate with neuropsychological data in PD but not AD patients, and ADRP will correlate with neuropsychological data in AD but not AD patients. |
| Investigator's Name: | Jeremy Koppel |
| Proposed Analysis: | A. Hypothesis There are no widely available tests to clearly exclude the presence of Alzheimer’s disease (AD) when considering the clinical diagnosis of Parkinson’s disease (PD) Dementia (PDD). This poses a significant problem within both patient care and for clinical trials. In separate studies, using spatial covariance mapping of 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) imaging data, we have identified separate patterns of brain metabolism associated with cognitive functioning in patients with PD and AD. However, these patterns have yet to be examined outside of their own study population. Our overarching hypothesis is that our PD Cognition Pattern (PDCP) can be utilized to quantify the cognitive dysfunction associated with PD and serve as an objective biomarker within subjects suspected of having and diagnosed with PD. We propose that PDCP activity is uniquely associated with Parkinson’s disease and distinguishable from cognitive dysfunction in AD and from the neuroimaging biomarker AD Related Pattern (ADRP). B. Specific Aims We plan to test this hypothesis by pursuing the following specific aims: Aim 1: Examine the sensitivity and specificity of our two metabolic covariance networks in the differentiation of AD and PD. Simply, we hypothesize that patients with PD will not exhibit high levels of ADRP activity, and that patients with AD will not exhibit high levels of PDCP. Aim 2: Evaluate the relationship between these unique metabolic networks and neuropsychological functioning. Specifically, we hypothesize that PDCP will correlate with neuropsychological data in PD but not AD patients, and ADRP will correlate with neuropsychological data in AD but not AD patients. |