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: | Ehsan Pishva |
| Institution: | Maastricht University |
| Department: | Psychiatry and Neuropsychology |
| Country: | |
| Proposed Analysis: | The genome-wide DNA methylation, expression, genotyping data, in addition to neuropsychiatric, cognitive, CSF measures from the participants will be used to address three main objectives as follows: (1) To identify genomic biomarkers to predict the rates of cognitive decline (using genetic variations, baseline methylation). (2) To identify genomic blood signatures for trajectory of cognitive function (using genetic variations, baseline methylation, and gene expression data) (3) To identify AD+Psychosis genomic blood signatures to develop biomarkers to predict greater rates of cognitive decline in AD patients. (Given the known impact of psychosis in the rates of progression to AD-dementia). Advanced single level as well as integrative multiomics data analyses will be conducted in order to address the listed objectives. |
| Additional Investigators | |
| Investigator's Name: | Joshua Harvey |
| Proposed Analysis: | Computing polygenic risk scores of AD , Educational attainment and Major depressive disorders as predictors of classes of cognitive decline created by latent class analysis and MMSE scores. |
| Investigator's Name: | Rick Reijnders |
| Proposed Analysis: | The genome-wide DNA methylation, expression, genotyping data, in addition to neuropsychiatric, cognitive, CSF measures from the participants will be used to address three main objectives as follows: (1) To identify genomic biomarkers to predict the rates of cognitive decline (using genetic variations, baseline methylation). (2) To identify genomic blood signatures for trajectory of cognitive function (using genetic variations, baseline methylation, and gene expression data) (3) To identify AD+Psychosis genomic blood signatures to develop biomarkers to predict greater rates of cognitive decline in AD patients. (Given the known impact of psychosis in the rates of progression to AD-dementia). Advanced single level as well as integrative multiomics data analyses will be conducted in order to address the listed objectives. Multi-trait Polygenic risk scores will be computed using ADNI genotyping data and will be tested in a multivariate prediction models of trajectory of cognitive decline. Trajectory of cognitive decline has been determined using latent class modeling and individual slopes of MMSE changes. |
| Investigator's Name: | Valentin Laroch |
| Proposed Analysis: | Computing multi-trait polygenic risk scores as predictors of classes of cognitive decline created by latent class analysis and MMSE scores. |
