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: | Marwan Sabbagh |
| Institution: | Barrow Neurological Institute |
| Department: | Neurology |
| Country: | |
| Proposed Analysis: | This project concerns the progression of confirmed Alzheimer's Disease (AD) in patient populations with Type 2 Diabetes Mellitus (T2DM). This project aims to measure this using AD biomarkers and MRI scans of white matter provided by the ADNI (Alzheimer’s Disease Neuroimaging Initiative) database. The hypothesis of this study is that cognitive decline occurs more rapidly with the comorbidity of T2DM. Although the risk of patients having AD with a T2DM diagnosis has been measured many times, data on the progression of confirmed AD with type 2 diabetic patients has been studied considerably less (with inconsistent results). Most studies explore the cognitive effects of AD (through various cognitive exams), but this paper aims to look additionally at biomarkers and brain MRIs. After querying the ADNI database, this paper will look at biomarkers associated with Alzheimer’s disease in all of the groups to determine if there are any differences between the control and experimental group. ADNI provides both CSF and blood biomarkers within its database, so this project will be looking at both of these values in addition to their MRI scans. These MRI scans will be used to evaluate whether there is a difference in brain white matter amongst the control and experimental groups. The statistical analysis performed for this study will employ chi-square analysis for categorical variables and independent sample t-tests for continuous variables. The p values garnered from these statistical tests will then be used for between-group comparisons to differentiate the values between subjects in the Alzheimer’s Disease with Type 2 Diabetes Mellitus and Alzheimer’s Disease only groups. A potential problem that we may need to mitigate is that sample populations may decrease as the number of visits increase through different data points. If this is the case, we will employ Leven’s test as it will enable us to correct for the differences in the sample populations and ensure a valid p value. We are requesting AD dementia subjects confirmed by amyloid PET and stratified into AD+T2DN and AD-T2DM. We request at least two epochs to determine trajectory. Included in the request is access to MRI and biomarker and PET data |
| Additional Investigators | |
| Investigator's Name: | Yumna Siddique |
| Proposed Analysis: | This project concerns the progression of confirmed Alzheimers Disease (AD) in patient populations with Type 2 Diabetes Mellitus (T2DM). This project aims to measure this using AD biomarkers and MRI scans of white matter provided by the ADNI (Alzheimer’s Disease Neuroimaging Initiative) database. The hypothesis of this study is that cognitive degeneration occurs more rapidly with the comorbidity of T2DM. Although the risk of patients having AD with a T2DM diagnosis has been measured many times, data on the progression of confirmed AD with type 2 diabetic patients has been studied considerably less (with inconsistent results). Most studies explore the cognitive effects of AD (through various cognitive exams), but this paper aims to look additionally at biomarkers and brain MRIs. After querying the ADNI database, this paper will look at biomarkers associated with Alzheimer’s disease in all of the groups to determine if there are any differences between the control and experimental group. ADNI provides both CSF and blood biomarkers within its database, so this project will be looking at both of these values in addition to their MRI scans. These MRI scans will be used to evaluate whether there is a difference in brain white matter amongst the control and experimental groups. . The statical analysis performed for this study will employ chi-square analysis for categorical variables and independent sample t-tests for continuous variables. The p values garnered from these statistical tests will then be used for between-group comparisons to differentiate the values between subjects in the Alzheimer’s Disease with Type 2 Diabetes Mellitus and Alzheimer’s Disease only groups. A potential problem that we may need to mitigate is that sample populations may decrease as the number of visits increase through different data points. If this is the case, we will employ Leven’s test as it will enable us to correct for the differences in the sample populations and ensure a valid p value. |
