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: | Gyungah Jun |
| Institution: | Boston University |
| Department: | Medicine |
| Country: | |
| Proposed Analysis: | With the increasing number of elder persons ages 80 years and above, the segment of the population with memory impairment is expected to increase dramatically over the next several decades. Neuropsychological (NP) tests are commonly used to assess cognitive and memory function in clinical settings and for population screening. Previous studies have linked area-specific activation in brain with domain-specific memory processing, but little is known about the genetic basis of domain-specific cognitive function and age-related cognitive decline. Recent genetic studies have investigated cognitive function cross-sectionally and longitudinally using a global cognitive score among individuals with Alzheimer’s disease (AD) and in community-based samples containing a large proportion of persons who are cognitively impaired. This approach is based on an assumption that a specific domain is governed by general cognitive processes and mainly impaired during progression to AD. However, the genetic basis of memory performance in the general population and cohorts prospectively followed into old age has not been rigorously studied. Our primary goal is to uncover genetic risk factors for domain-specific cognitive impairment and decline along with those for area-specific brain damage during normal aging process using MRI scans, and compare them with domain-general genetic risk factors. Specific Aim 1: Conduct genome-wide association (GWA) analyses using worst domain-specific cognitive performance tests and area-specific MRI measures separately in normal, MCI, AD, and the entire data. - Adjustment: age at worst score, sex, population substructure (PCs) - Phenotype: worst score (Y) - Y~SNP+AgeAtWorstScore+Sex+PCs Specific Aim 2: Conduct genome-wide association (GWA) analyses using domain-specific cognitive decline and global cognitive decline phenotypes and rate of changes on area-specific MRI measures among individuals progressed from normal to MCI, normal to AD, and MCI to AD during the follow up period. - Adjustment: age at baseline, score at baseline -Phenotype: rate of change (baseline to last exam; Y) - Y~SNP+AgeAtBaseline+ScoreAtBaseline+Sex+PCs Specific Aim 3: Conduct genome-wide association (GWA) analyses simultaneously considering cognitive and MRI traits for each model in Aims 1 and 2. - Adjustment: described above in Aims 1 and 2 - Phenotype: cognitive score/rate (Y1) and MRI score/rate (Y2) - Y1,Y2~SNP+Covariates (Aims 1 and 2) All analyses will be conducted in linear regression models. |
| Additional Investigators | |
| Investigator's Name: | Jaeyoon Chung |
| Proposed Analysis: | Genome-wide association studies using cognitive tests and MRI scans in ADNI sample. |
| Investigator's Name: | John Farrell |
| Proposed Analysis: | He will conduct quality control of sequencing data and develop HLA genotype prediction algorithm using sequencing data. |
| Investigator's Name: | Rebecca Panitch |
| Proposed Analysis: | Rebecca will conduct polygenic risk score analysis using genome-wide association study data in ADNI. |
| Investigator's Name: | Donghe Li |
| Proposed Analysis: | We will conduct integrated analysis of baseline and longitudinal data analysis using ADNI data. |
| Investigator's Name: | Junming Hu |
| Proposed Analysis: | He will conduct network analysis using blood transcriptome data in ADNI and evaluate preservation with networks from brain transcriptome data. |
| Investigator's Name: | Nathan Sahelijo |
| Proposed Analysis: | He will conduct association analyses linking omics profiles with clinical and biomarker phenotypes in ADNI. |
| Investigator's Name: | Dhawal Priyadarshi |
| Proposed Analysis: | He will conduct data cleaning and preparing data for analyses. |
| Investigator's Name: | Yueh-Ting Wang |
| Proposed Analysis: | She will conduct genome wide association studies using biomarker phenotypes in ADNI. |
