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: | Manikandan Narayanan |
| Institution: | IIT Madras |
| Department: | Computer Science and Engineering |
| Country: | |
| Proposed Analysis: | We would like to use the ADNI data for causal discovery applications using methods based on MR (Mendelian Randomization), Fast Causal Inference, etc. to arrive at causal gene-gene/gene-SNP network models for AD. Furthermore, we would like to use the GWAS and genotype data from ADNI to compute ethnicity and pathway specific genetic risk scores. |
| Additional Investigators | |
| Investigator's Name: | Ritwiz Kamal |
| Proposed Analysis: | We would like to use the ADNI data for causal discovery applications using methods based on MR (Mendelian Randomization), Fast Causal Inference, etc. to arrive at causal gene-gene/gene-SNP network models for AD. Furthermore, we would like to use the GWAS and genotype data from ADNI to compute ethnicity and pathway specific polygenic risk scores (PRS). I will also explore extensions of the causal discovery or PRS methods. |
| Investigator's Name: | Sanga Mitra |
| Proposed Analysis: | We would like to use the ADNI data for causal discovery applications using methods based on MR (Mendelian Randomization), Fast Causal Inference, etc. to arrive at causal gene-gene/gene-SNP network models for AD. Furthermore, we would like to use the GWAS and genotype data from ADNI to compute ethnicity and pathway specific polygenic risk scores (PRS). I will also explore biological interpretations of the aforementioned analyses involving pathways and causal gene networks. |
