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: | Yuliya Nikolova |
| Institution: | Centre for Addiction and Mental Health |
| Department: | Campbell Family Mental Health Research Institute |
| Country: | |
| Proposed Analysis: | Age-related polygenic risk score (AGE-PRS) will be calculated for each ADNI participant as the sum of functional variants shifting age-dependent gene expression towards a more old-age-like state using PLINK 1.9. Specific weights and risk allele information will be obtained from our previous work, which identified 1065 age-related genes and SNPs predicting their transcriptional profile. General linear models including sex and age, will be fitted to investigate whether PRS-AGE predicts AD and MCI diagnoses (Aim 1); as well as executive functioning, and depressive symptoms, assessed across diagnostic groups via the Montreal Cognitive Assessment (MoCA) and Geriatric Depression Scale (GDS), respectively (Aim 2). Structural changes in the cortex (Aim 3) will be assessed through thickness of cortical regions and volume of subcortical nuclei, measured with FreeSurfer (v6.0). Models will be fitted to investigate whether PRS-AGE predict structural changes in the whole sample and in each diagnosis group. Results could lead to the innovative development of early markers of biological brain aging, indexing risk for age-related brain disorders, and paving the way for preventive interventions. Exploratory analyses: Additional PRS associated with elevated risk of depression or AD based on results from prior genome-wide association studies (GWAS) or with depression-like changes in postmortem gene expression in brain tissue will also be conducted as described above. |
| Additional Investigators | |
| Investigator's Name: | Fernanda Caroline Dos Santos |
| Proposed Analysis: | Dr. Dos Santos will be responsible for all the genetic and statistical analyses in the project described below: Age-related polygenic risk score (AGE-PRS) will be calculated for each ADNI participant as the sum of functional variants shifting age-dependent gene expression towards a more old-age-like state using PLINK 1.9. Specific weights and risk allele information will be obtained from our previous work, which identified 1065 age-related genes and SNPs predicting their transcriptional profile. General linear models including sex and age, will be fitted to investigate whether PRS-AGE predicts AD and MCI diagnoses (Aim 1); as well as executive functioning, and depressive symptoms, assessed across diagnostic groups via the Montreal Cognitive Assessment (MoCA) and Geriatric Depression Scale (GDS), respectively (Aim 2). Structural changes in the cortex (Aim 3) will be assessed through thickness of cortical regions and volume of subcortical nuclei, measured with FreeSurfer (v6.0). Models will be fitted to investigate whether PRS-AGE predict structural changes in the whole sample and in each diagnosis group. Results could lead to the innovative development of early markers of biological brain aging, indexing risk for age-related brain disorders, and paving the way for preventive interventions. Exploratory analyses: Additional PRS associated with elevated risk of depression or AD based on results from prior genome-wide association studies (GWAS) or with depression-like changes in postmortem gene expression in brain tissue will also be conducted as described above. |
| Investigator's Name: | Amy Miles |
| Proposed Analysis: | Dr. Miles will be responsible for neuroimaging data processing and analysis in the project described below: Age-related polygenic risk score (AGE-PRS) will be calculated for each ADNI participant as the sum of functional variants shifting age-dependent gene expression towards a more old-age-like state using PLINK 1.9. Specific weights and risk allele information will be obtained from our previous work, which identified 1065 age-related genes and SNPs predicting their transcriptional profile. General linear models including sex and age, will be fitted to investigate whether PRS-AGE predicts AD and MCI diagnoses (Aim 1); as well as executive functioning, and depressive symptoms, assessed across diagnostic groups via the Montreal Cognitive Assessment (MoCA) and Geriatric Depression Scale (GDS), respectively (Aim 2). Structural changes in the cortex (Aim 3) will be assessed through thickness of cortical regions and volume of subcortical nuclei, measured with FreeSurfer (v6.0). Models will be fitted to investigate whether PRS-AGE predict structural changes in the whole sample and in each diagnosis group. Results could lead to the innovative development of early markers of biological brain aging, indexing risk for age-related brain disorders, and paving the way for preventive interventions. Exploratory analyses: Additional PRS associated with elevated risk of depression or AD based on results from prior genome-wide association studies (GWAS) or with depression-like changes in postmortem gene expression in brain tissue will also be conducted as described above. |
| Investigator's Name: | Kevan Clifford |
| Proposed Analysis: | Kevan Clifford will conduct exploratory analyses comparing structural covariance network patterns between participants with low and high PRS-AGE. |
