Gene Expression Profiles in Osteoarthritis Clinical Variants

描述（由申请人提供）：广泛的目标是了解更多关于生物信息学和建立有关骨关节炎（OA）遗传学的合作，并学习和应用实用方法来评估遗传序列变异是否可能作为疾病基因。休假符合NIAMS的使命，因为它将培养一名临床科学家来调查关节炎的原因。休假符合基因组学领域的定义，即研究基因及其功能。我将通过统计遗传学和流行病学的短期课程来刷新我在遗传流行病学方面的知识，通过牛津短期课程来熟悉生物信息学，并从牛津人类遗传学和分子医学研讨会和讨论中学习。休假项目将提供实际经验，通过测试的假设，OA临床变异不同的基因表达源于独特的遗传倾向。接受有临床指征的关节置换术的OA受试者将被分类为临床变异。将获得手术标本和外周血并用于纯化RNA。正常软骨样本将从种族和人口统计学相似的来源获得，主要是尸体。将测量特定OA相关基因的等位基因表达不平衡，并分析与单独发病机制一致的显著差异。比较的方式--OA变异和正常之间mRNA的差异--将提取出与骨关节炎临床变异相关的子集。该项目的成果将包括实际掌握的应用程序，以教，有价值的试剂，结果公布，和新的想法合作项目;休假的经验将产生新的概念和技术方法的遗传研究，我可以使用和教初级研究人员。骨关节炎是最常见、最昂贵、最致残的关节炎。目前还没有药物能够阻止或改变骨关节炎的进展，这部分是因为没有有意义的工具来解决其异质性。通过将骨关节炎分为更同质的亚组的方法，例如基因活性模式，我们可以设计更强大和富有成效的未来研究来寻找疾病基因，预测骨关节炎风险，结果或对治疗的反应，并研究潜在的疾病修饰干预措施，如细胞因子阻滞剂，软骨修复激动剂或其他措施。

DESCRIPTION (provided by applicant): 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.