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: | Molly Hall |
| Institution: | Pennsylvania State University |
| Department: | Veterinary and Biomedical Sciences |
| Country: | |
| Proposed Analysis: | There is an increasing need to develop sophisticated tools for multi-omics data integration to uncover the etiology of Alzheimer’s Disease; however, research between the genome and metabolome has not kept pace with other omic data. Particularly, there is a growing need to develop computational methods that integrate the genome and metabolome in ways that preserve the biological interactions between them to reveal the genome-metabolome risk combinations that lead to disease. We are developing a novel and widely applicable tool: Software for Integrated Genome-Metabolome Analysis (SIGMA). Using SIGMA, we propose to integrate genomic and metabolomic data to predict Alzheimer's disease progression and to uncover new genomic-metabolomic mechanisms and risks associated with Alzheimer's disease. |
| Additional Investigators | |
| Investigator's Name: | Tomas Gonzalez Zarzar |
| Proposed Analysis: | There is an increasing need to develop sophisticated tools for multi-omics data integration to uncover the etiology of Alzheimer’s Disease; however, research between the genome and metabolome has not kept pace with other omic data. Particularly, there is a growing need to develop computational methods that integrate the genome and metabolome in ways that preserve the biological interactions between them to reveal the genome-metabolome risk combinations that lead to disease. We are developing a novel and widely applicable tool: Software for Integrated Genome-Metabolome Analysis (SIGMA). Using SIGMA, we propose to integrate genomic and metabolomic data to predict Alzheimer's disease progression and to uncover new genomic-metabolomic mechanisms and risks associated with Alzheimer's disease. |
| Investigator's Name: | Kristin Passero |
| Proposed Analysis: | There is an increasing need to develop sophisticated tools for multi-omics data integration to uncover the etiology of Alzheimer’s Disease; however, research between the genome and metabolome has not kept pace with other omic data. Particularly, there is a growing need to develop computational methods that integrate the genome and metabolome in ways that preserve the biological interactions between them to reveal the genome-metabolome risk combinations that lead to disease. We are developing a novel and widely applicable tool: Software for Integrated Genome-Metabolome Analysis (SIGMA). Using SIGMA, we propose to integrate genomic and metabolomic data to predict Alzheimer's disease progression and to uncover new genomic-metabolomic mechanisms and risks associated with Alzheimer's disease. |
