Large-Scale Characterization of Autoantibody Responses in Rheumatoid Arthritis

类风湿关节炎自身抗体反应的大规模表征

• 批准号: 8910250
• 负责人: William H Robinson
• 金额: $ 33.45万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8910250
• 关键词: Address; Affect; Affinity; Antibodies; Antibody Affinity; Antibody Formation; Antibody Repertoire; Antibody Response; Antigen Targeting; Antigen-Antibody Complex; Antigens; Autoantibodies; Autoantigens; Autoimmune Diseases; Autoimmune Process; Autoimmune Responses; Automobile Driving; B-Lymphocytes; Back; Binding; Bioinformatics; Blood; Blood Cells; Cells; Citrulline; Complementary DNA; Computer Simulation; Data Set; Development; Disease; Enzyme-Linked Immunosorbent Assay; Epitopes; Evolution; Exhibits; Family; Fibrinogen; Generations; Genes; Health; Immune response; Immunoblotting; Immunoglobulin A; Immunoglobulin G; Immunoglobulin Light Chain Genes; Immunoglobulin Somatic Hypermutation; In Vitro; Individual; Large-Scale Sequencing; Lead; Light; Mass Spectrum Analysis; Memory B-Lymphocyte; Methods; Mutate; Mutation; Mutation Analysis; Pathogenesis; Pathogenicity; Patients; Plasma Cells; Plasmablast; Population; Production; Property; Recombinant Antibody; Recombinants; Research; Rheumatoid Arthritis; Rheumatoid Factor; Sequence Analysis; Sorting - Cell Movement; Staging; Sushi Domain; Synovial Membrane; Synovitis; T cell response; TLR4 gene; TNF gene; Technology; Testing; Tissues; Trees; citrullinated protein; expression cloning; high throughput analysis; insight; macrophage; member; mouse model; next generation sequencing; novel; novel diagnostics; novel therapeutic intervention; novel therapeutics; pre-clinical; research study; response; success

DESCRIPTION (provided by applicant): Rheumatoid arthritis (RA) is an autoimmune synovitis that affects 0.5% of the world population, yet the key autoantigen targets remain unknown. Production of autoantibodies, such as the anti-citrullinated protein antibodies (ACPAs), is a hallmark of RA. However, which antigens the critical ACPAs and other RA- associated autoantibodies target remains largely unknown. Also unknown is how these ACPAs develop, how similar the ACPA repertoires are between different individuals with RA, and whether and how they contribute to the pathogenesis of RA. So far, the research field has lacked the means to comprehensively characterize the autoantibodies associated with a given disease and to then rationally winnow them to those that are important-that is, those that either drive the disease or serve as identifiers of the key antigens that trigger the pathogenic T-cell response. We have now developed "antibody repertoire capture" technology, a high- throughput method that allows us to do just that. Harnessing the power of next-generation sequencing, we have developed a novel method for barcoding all the cDNAs generated from individual antibody-expressing cells, thereby enabling high-throughput analysis of the paired heavy- and light-chain immunoglobulin genes expressed by single B cells, plasmablasts, or plasma cells. We hypothesize that we can elucidate the pathogenic autoantibody responses associated with RA by defining the antibody repertoire of plasmablasts and antigen-sorted memory B cells in the blood, and of plasmablasts and plasma cells in the synovium, of individuals with RA. We will then bioinformatically analyze the antibody sequences we obtain to generate evolutionary trees of the antibody repertoires and thereby identify and clone the affinity-matured antibodies that are likely the key autoantibodies. We will identify the antigens targeted by these recombinant, affinity-matured autoantibodies, investigate how their specific sequences develop, dissect their binding and immunostimulatory properties, and assess their pathogenicity. Success of this proposal would shed light on the development of the autoantibody response and identify the key autoantigens targeted in RA, findings that could lead to the development of new diagnostics and therapies for RA.

描述（由申请人提供）：类风湿性关节炎 (RA) 是一种自身免疫性滑膜炎，影响世界人口的 0.5%，但关键的自身抗原靶标仍然未知。自身抗体的产生，例如抗瓜氨酸蛋白抗体 (ACPA)，是 RA 的一个标志。然而，关键 ACPA 和其他 RA 相关自身抗体针对哪些抗原仍然很大程度上未知。同样未知的是这些 ACPA 是如何发展的、不同 RA 个体之间的 ACPA 谱系有多相似、以及它们是否以及如何促进 RA 的发病机制。到目前为止，该研究领域还缺乏全面表征与特定疾病相关的自身抗体的方法，然后合理筛选出那些重要的抗体，即那些驱动疾病或充当关键抗原标识符的抗体。触发致病性 T 细胞反应。我们现在开发了“抗体库捕获”技术，这是一种高通量方法，使我们能够做到这一点。利用下一代测序的力量，我们开发了一种新方法，用于对单个抗体表达细胞产生的所有 cDNA 进行条形码编码，从而能够对单个 B 细胞表达的配对重链和轻链免疫球蛋白基因进行高通量分析、浆母细胞或浆细胞。我们假设我们可以通过定义 RA 个体血液中浆母细胞和抗原分选的记忆 B 细胞以及滑膜中浆母细胞和浆细胞的抗体库来阐明与 RA 相关的致病性自身抗体反应。然后，我们将对获得的抗体序列进行生物信息分析，以生成抗体库的进化树，从而识别和克隆可能是关键自身抗体的亲和力成熟的抗体。我们将鉴定这些重组、亲和力成熟的自身抗体所靶向的抗原，研究它们的特定序列如何发展，剖析它们的结合和免疫刺激特性，并评估它们的致病性。该提案的成功将揭示自身抗体反应的发展，并确定 RA 中针对的关键自身抗原，这些发现可能会导致 RA 新诊断和疗法的开发。