The broad objectives are to learn more about bioinformatics and establish collaborations about osteoarthritis (OA) genetics, and to learn and apply practical approaches to assess whether genetic sequence variants may act as disease genes. The sabbatical fits the NIAMS mission because it will train a clinical scientist to investigate causes of arthritis. The sabbatical fits within the area of genomics as defined by study of genes and their functions. I will refresh my knowledge in genetic epidemiology through short courses in statistical genetics and epidemiology, gain bioinformatics familiarity through Oxford short courses, and learn from Oxford human genetics and molecular medicine seminars and discussions. The sabbatical project will provide practical experience through testing the hypothesis that OA clinical variants differ in gene expression stemming from distinctive genetic predispositions. OA subjects undergoing clinically indicated arthroplasty procedures will be classified as to clinical variant. Surgical specimens and peripheral blood will be obtained and used to purify RNA. Normal cartilage samples will be procured from ethnically and demographically similar sources, largely cadaveric. Imbalance in allele expression will be measured for specific OA-associated genes and analyzed for distinctive differences consistent with separate pathogenetic mechanisms. The manner of comparison-mRNAs differing between OA variants and from normals-will pull out the subsets relevant to osteoarthritis clinical variation. The project's outcomes will include a practical grasp of applications to teach, valuable reagents, results to publish, and new ideas for collaborative projects; the sabbatical experience will generate new conceptual and technical approaches for genetic studies that I can use and teach to junior investigators. Osteoarthritis is the most common, costly, and disabling form of arthritis. No current medicine blocks or modifies osteoarthritis progression-this is partly because no meaningful tools exist to resolve its heterogeneity. With methods to separate osteoarthritis into more homogeneous subgroups, such as with gene activity patterns, we can design more powerful and fruitful future studies to find disease genes, to predict osteoarthritis risk, outcomes, or response to therapy, and to investigate potentially disease-modifying interventions like cytokine blockers, cartilage repair agonists, or other measures. ? ? ?
