ADNI data is made available to researchers around the world. As such, there are many active research projects accessing and applying the shared ADNI data. To further encourage Alzheimer’s disease research collaboration, and to help prevent duplicate efforts, the list below shows the specific research focus of the active ADNI investigations. This information is requested annually as a requirement for data access.
|Principal Investigator's Name:||Mette Peters|
|Proposed Analysis:||Many of the millions of SNPs in the public domain identified in GWA studies have no a priori link to biological processes and most reside in non-coding regions, making it difficult to link the polymorphism to a protein or RNA impacting a biological process. To identify genes and DNA variants causal for diseases in human populations, Sage Bionetworks has analyzed data from thousands of human tissues collected from healthy individuals as well as those with complex diseases such as cardiovascular disease, diabetes, obesity or Alzheimer’s disease. Mapping the genetic architecture of gene expression in the human population allow us to identify SNPs associated to a biological function. Sage Bionetworks has already analyzed over 1000 human livers, more than 2000 adipose samples, and more than 800 brain samples from three different regions of the brain and identified ~100k eSNPs for ~20k genes. We have shown how these eSNPs can be used to enrich for signal in GWAS data and more specifically applied to perform pathway analysis (1-2). We plan to use our collection of eSNPs and networks linked to disease from both human and mouse to help mine the ADNI data. In particular we would like to use the set of SNPs we have identified linked to the expression of transcripts in normal brain regions, and patients with neurodegenerative disease, as a tool to understand AD pathology through the integration of genomic and medical imaging data  H. Zhong, J. Beaulaurier, P.Y. Lum, C. Molony, X. Yang, D.J. Macneil, D.T. Weingarth, B. Zhang, D. Greenawalt, R. Dobrin, K. Hao, S. Woo, C. Fabre-Suver, S. Qian, M.R. Tota, M.P. Keller, C.M. Kendziorski, B.S. Yandell, V. Castro, A.D. Attie, L.M. Kaplan, and E.E. Schadt, “Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes.,” PLoS Genetics, vol. 6, Jan. 2010, p. e1000932.  H. Zhong, X. Yang, L.M. Kaplan, C. Molony, and E.E. Schadt, “Integrating pathway analysis and genetics of gene expression for genome-wide association studies.,” American Journal of Human Genetics, vol. 86, Apr. 2010, pp. 581-91.|