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: | Li-San Wang |
| Institution: | University of Pennsylvania |
| Department: | Pathology and Laboratory Medicine |
| Country: | |
| Proposed Analysis: | The proposed analysis is part of the Alzheimer's Disease Genetic Consortium, headed by Dr. Gerard Schellenberg, University of Pennsylvania. We ask for access for the ADNI phenotype and genetic data; we will perform genome-wide association analysis (including SNP, haplotype, and CNV genotypes) and compare significant loci with SNPs/genes known to be associated with Alzheimer's disease (and other neurodegenerative diseases), as well as findings from analysis of additional samples that will be genotyped by the consortium. |
| Additional Investigators | |
| Investigator's Name: | Vivianna Van Deerlin |
| Proposed Analysis: | Alzheimer’s (AD), Parkinson’s disease (PD), frontotemporal degeneration (FTD), and amyotrophic lateral sclerosis (ALS) result from the progressive loss of normal structure and function of neurons and synapses in the central nervous system. Once considered distinct and unrelated neurodegenerative diseases (ND), it is recognized that there is a significant amount of overlap in clinical and molecular features phenotypes of these disorders. To determine genetic characteristics which may contribute to the heterogeneity or shared clinicopathological phenotypes of ND, we will evaluate the genetic variations in our well characterized ND cohorts. The goals of our study are to 1) screen pathogenic mutations in genes that are associated with ND, and 2) identify genetic variants that increase risks in cohorts with NDs and their unaffected relatives. We will perform targeted next generation sequencing using a custom panel which contains a group of genes associated with FTD, ALS, PD, and AD and study the genetic spectrum of the cases, including in the 5’ and 3” UTR. We will utilize and analyze whole exome sequencing data from subjects who are cognitively normal and available in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and compare them with our genetic data of ND cases. We plan to access the data files in both variant calling format (VCF) and binary format of the sequence alignment data (BAM) to evaluate and compare quality measures. |
| Investigator's Name: | Wan-Ping Lee |
| Proposed Analysis: | We propose to conduct genetic variant association analysis on Alzheimer's Disease (AD) by using genomes that were collected and sequenced by the Alzheimer's Disease Sequencing Project (ADSP). We will use phenotype and genetic data in ADSP. The data has been de-identified and accessible via the National Institute on Aging Genetics of Alzheimer's Disease (NIAGADS) Data Storage Site with approvals of data access applications. As to the research plan, we will start with copy number variation (CNV) and structural variation (SV) detection and characterization of CNV sequence features (e.g., microhomology, non-template insertions, and segmental duplications) to understand potential mechanisms of CNV formation. Next, we will study the association of AD status with CNVs using standard association methods and adjusting for population structure (PS) and ages of onset. Since the data was collected multi-ethnic, we will perform ethnic-specific and ethnic-combined association analyses. We will use principle-component-based methods to adjust for PS but also explore the efficacy of other PS adjustment methods. Finally, we will conduct biological annotation on identified risk variants. We would appreciate your informed review and approval of the project. If you have any questions or concerns, do not hesitate to contact me at (412) 880-8674. I will serve as the contact person for this project. We look forward to your comments and approval. |
