Using cardiovascular disease as a model system, the AGENDA Project (Approach to GENomic Discovery in Atherosclerosis) aims to:
- Identify those genes most likely to make contributions to disease variation.
- Identify the variations within this group of genes
- Conduct association studies to link gene variants with disease phenotype. In particular, we use multiple methods to identify candidate genes most likely to make contributions to disease variation within populations of patients.
The project integrates several components that use unique clinical resources available at Duke:
Gene Discovery Using Microarrays (Components 1 and 5)
A large series of aorta samples from heart transplant donors is being collected as a source of vascular tissue for gene expression analysis. A wide range of phenotypes, from early stages of atherosclerosis to advanced forms of the disease, provides a unique opportunity to match gene expression profiles with the development of disease.
Component 1 performs the microarray analysis. Component 5 develops and applies novel methods of statistical analysis.
Gene Discovery Using Genome-Wide Scanning (Components 2 and 6)
Investigators are studying the genetics of early onset cardiovascular disease, offering the opportunity to identify loci that are linked with the development of disease. This approach provides a mechanism for the identification of additional candidate genes without any bias whatsoever, including whether the gene actually functions within cardiovascular tissue or not.
Component 2 conducts the genome-wide scanning. Component 6 handles the bioinformatics efforts.
Discovery of Single Nucleotide Polymorphisms (SNPs) (Component 3)
The combined efforts of component 1 and component 2, taking different approaches to the identification of candidate genes, will then be the source of substrate to discover SNPs within this group of genes.
Much of this work will take advantage of existing information regarding SNPs as well as other major studies directed at cardiovascular disease. But effort will also be required to identify as exhaustively as possible those sequence variants that can then be the subject for assays in clinical populations.
Large-Scale Genotyping (Component 4)
SNPs identified in component 3 will go into an expansive genotyping program, to bring these candidate genes to a point of validation within the Duke Cardiovascular Database. The database was initiated some 30 years ago at Duke to follow the clinical course of every cardiovascular disease patient. As such, we now have access to over 40,000 patients who are followed on a regular basis, creating an unmatched clinical dataset that is unique in quantity as well as quality of patient clinical data.
Leveraging statistical power to find associations in this large, complex data set poses a major challenge. Component 5, which will develop the methodologies for understanding the complex gene expression dataset, will also develop the statistical approaches for analyzing the complex genotyping studies.
Integrating With Education Programs
Component 6 will also integrate with existing and developing education programs in bioinformatics and genome technology at Duke, bringing in talented investigators from multiple disciplines in each area critical for the program.
Faculty and Staff
William E. Kraus, MD
Administrative Component
Component 1
Neil Freedman, MD
Geoffrey S. Ginsburg, MD, PhD
Joseph R. Nevins, PhD
Component 2
Jeffrey Vance, MD
William E. Kraus, MD
Component 3
Simon Gregory, PhD
Component 4
Jeffrey Vance, MD
Simon Gregory, PhD
Liyong Wang, PhD
Component 5
Mike West, PhD
Component 6
Elizabeth R. Hauser, PhD
Svati H. Shah, MD
Jessica Connelly, PhD
Component 7 (Administrative)
Contact
Campus mail: DUMC Box 3327, Durham, NC, 27710
Phone: 919-660-6613
Fax: 919-668-6301