Genomic Landscapes in Large Scale Integrated JRA Studies

Children'S Hospital Med Ctr (Cincinnati), Cincinnati OH

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Abstract

DESCRIPTION (provided by applicant): Juvenile Rheumatoid Arthritis (JRA) is a heterogeneous group o f chronic pediatric arthropathies that a reinfluenced by a complex genetic trait and environmental factors. A better understanding of the complexity of both genetic and environmental contributions to the disease risk would greatly facilitate correct diagnosis and treatment, especially in severe cases of joint erosion which at present cannot be predicted in the early stages of the JRA onset. The principal hypothesis for this project is that large-scale integrated analysis of gene expression; polymorphism and other genomic data in conjunction with clinical data will yield new, powerful insights into biological pathways and processes that underlie JRA. Our general aim is to develop novel computational methods for large-scale data mining and classification as well as build carefully validated databases of JRA gene expression and relevant polymorphisms in order to facilitate multidimensional mining with the ability to Ieverage the use of a priori knowledge of relevant gene-gene interactions and pathways. In particular, Specific Aim 1 consists of building an integrated database of clinical, gene expression and polymorphism profiles for a large population of JRA patients. Specific Aim 2 develops and implements tailored large-scale classification algorithms that are suitable for the analysis of the diverse genomic and clinical data we propose to collect in an integrated fashion. Special emphasis is given to dimension reduction and the development of statistical significance measures, two key computational challenges arising from the type of data involved. Finally, Specific Aim 3 builds on the previous two aims and proposes to use the computational tools developed in Aim 2 and the database built up in aim 1 to classify JRA subtype and clinical outcomes. Furthermore, we address the hypothesis that a joint analysis of IL-4 and IL-6 expression levels and polymorphisms can be used for more accurate discrimination of polyarticular and systemic JRA versus pauciarticular JRA.