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: | Tao He |
| Institution: | San Francisco State University |
| Department: | Mathematics |
| Country: | |
| Proposed Analysis: | Genome-wide association studies (GWAS) haven been powerful tool to unveil the genetic architecture of many complex diseases. However, the power of traditional GWAS analyses by assessing the effect of SNPs one at a time, is limited due to weak marginal signals and the lack of considering potential interactions among the genetic variants. We have developed novel set-based association testing methods where association between the binary trait and a group of genetic variants is jointly tested. On one hand, the subtle effects in multiple variants can be combined so that the joint signal of the set could be potentially boosted and be detected. On the other hand, the set-based strategy improves the power by capturing the complicated interactions among variants if any. We would like to apply the method to dbgap Alzheimer’s GWAS data (Alzheimer's Disease Genetics Consortium (ADGC) Genome Wide Association Study-NIA Alzheimer's Disease Centers Cohort) to identify the biological pathways (a set of genes or SNPs) that are associated with Alzheimer’s disease and study how genes/SNPs in the pathway work together to affect the risk of getting the disease. The requested GWAS data set provide timely support for our project to evaluate our methodology. We hope novel pathways can be identified with our new methods. |
| Additional Investigators |
