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: | Sai Kaushik Shankar Ramesh Kumar |
| Institution: | University of Minnesota |
| Department: | Department of Laboratory Medicine and Pathology |
| Country: | |
| Proposed Analysis: | We will use GWAS to study the genetic variants that are associated with plasma concentration of SM [OH] C22:1. GWAS analysis will be conducted to identify SNP variants associated with SM(OH) C22:1. The plasma concentration for biomarker (SM(OH) C22:1) will be log-transformed due to their right-skewed distribution. To improve the power of identifying SNP variants, we intend to combine data from the ROSMAP study (sample size = 603) and ADNI 3 study. Standard GWAS QC will be performed on all 3 datasets and the datasets will be combined to perform a mega GWAS analysis to identify variants. Quality controls include the following: 1) The minimum call rate for SNP and individuals should be 98%. 2) Autosomal SNP’s that are not in Hardy -Weinberg equilibrium (p<1*10-6) will be excluded. 3) X-chromosome SNP’s will be analyzed to eliminate sex inconsistencies if any. 4) Only SNP with MAF>0.05 will be included for analysis. |
| Additional Investigators | |
| Investigator's Name: | Danni Li |
| Proposed Analysis: | We will use GWAS to study the genetic variants that are associated with plasma concentration of SM [OH] C22:1. GWAS analysis will be conducted to identify SNP variants associated with SM(OH) C22:1. The plasma concentration for biomarker (SM(OH) C22:1) will be log-transformed due to their right-skewed distribution. To improve the power of identifying SNP variants, we intend to combine data from the ROSMAP study (sample size = 603) and ADNI 3 study. Standard GWAS QC will be performed on all 3 datasets and the datasets will be combined to perform a mega GWAS analysis to identify variants. Quality controls include the following: 1) The minimum call rate for SNP and individuals should be 98%. 2) Autosomal SNP’s that are not in Hardy -Weinberg equilibrium (p<1*10-6) will be excluded. 3) X-chromosome SNP’s will be analyzed to eliminate sex inconsistencies if any. 4) Only SNP with MAF>0.05 will be included for analysis. |
