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DESCRIPTION (provided by applicant):
Despite great success of GWA studies in identification of common genetic variants associated with complex diseases, we are still faced with great challenges to not only confirm the association finding of significant SNPs, but to ultimately identify the path from genomic information to the complex phenotypes. The current GWA studies have primarily focused on testing association of a single SNP at a time. Since common disease are often caused by multiple genes and environments that are organized into a myriad of complex networks, to only test for association of single SNP offers limited understanding of complex diseases and is insufficient to dissect complex genetic structure of diseases. The current GWA studies have also paid less attention to global "systems-level" approach that provides a functional context within which DNA variation occurs. The function of many SNPs may not be well characterized, but function of genes and particularly pathways, on the contrary, are much better investigated. SNPs and genes carry out their functions through intricate pathways of reactions and interaction. Attempting to understand and interpret a number of significant SNPs without any unifying biological theme can be demanding. Pending conceptual and statistical challenges of the GWA studies are (1) how to take a comprehensive view of the complex genetic structure of common disease to gain insight into the biological processes and disease mechanism and (2) how to integrate genetics and other functional data to connect genomic variation to final clinical outcomes. Overall objective of this application is to use existing genome-wide genotyping data of RA in WTCCC studies (cases: 1860 and controls: 2938, 459,653 SNPs) and in NARAC studies (cases: 866 and controls: 1194, 545,080 SNPs), ankylosing spondylitis (AS) (cases: 1,000 in U. S., 1,000 in U.K., 1,500 controls in U. S., 3,000 controls in U. K. 375,000 SNPs), and psoriasis in GAIN(cases: 1421 and controls: 1425, 451,725 SNPs) as well as expression data of psoriasis ( 34 controls, 37 involved and uninvolved skins from cases, 54,675 probes) to develop novel analytic strategies for gene and pathway-based genome-wide association analysis in which genes and pathways are taken as basic units of association analysis in addition to SNPs, and integrations of genetic, gene expressions and other functional data to decipher path from genomic information to the clinical endpoints of complex diseases, to meet above conceptual and statistical challenges.
PUBLIC HEALTH RELEVANCE:
The work proposed in this application uses existing genome-wide genotype data of RA, AS and psoriasis and gene expression data of psoriasis that were obtained from NIH, WTCCC by data access agreement, and our funded project P01 AR052915-01A1: Genetics and Ankylosing Spondylitis (AS) Pathogenesis to perform gene and pathway-based GWA studies of RA, AS and psoriasis. This application will also use structural equations to integrate analysis of genotype and expression data and build network models for deciphering path from genomic information to diseases of RA, AS and psoriasis. We believe that the proposed study is timely and we expect that the methodological developments and insights we gain will influence genetic studies of RA, AS, psoriasis and other complex diseases and continue beyond this project.
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Narrative
The work proposed in this application uses existing genome-wide genotype data of RA, AS and
psoriasis and gene expression data of psoriasis that were obtained from NIH, WTCCC by data
access agreement, and our funded project P01 AR052915-01A1: Genetics and Ankylosing
Spondylitis (AS) Pathogenesis to perform gene and pathway-based GWA studies of RA, AS and
psoriasis. This application will also use structural equations to integrate analysis of genotype
and expression data and build network models for deciphering path from genomic information to
diseases of RA, AS and psoriasis. We believe that the proposed study is timely and we expect
that the methodological developments and insights we gain will influence genetic studies of RA,
AS, psoriasis and other complex diseases and continue beyond this project.
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