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: 8579836
• 负责人: William H Robinson
• 金额: $ 33.44万
• 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 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8579836
• 关键词: Address; Affect; Affinity; Antibodies; Antibody Affinity; Antibody Formation; Antibody Repertoire; 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; 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; Proteins; 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; expression cloning; high throughput analysis; insight; macrophage; member; mouse model; next generation sequencing; novel; novel diagnostics; novel therapeutic intervention; novel therapeutics; pre-clinical; public health relevance; 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）：类风湿关节炎（RA）是一种自身免疫性滑膜炎，影响了世界人口0.5％，但主要的自身抗原靶标仍然未知。自身抗体的产生，例如抗硝化蛋白抗体（ACPA），是RA的标志。然而，抗原关键的ACPA和其他相关的自身抗体靶标仍然在很大程度上未知。同样未知的是这些ACPA的发展方式，不同RA的个体之间的ACPA曲目如何相似，以及它们是否以及如何贡献RA的发病机理。到目前为止，研究领域还缺乏全面表征与给定疾病相关的自身抗体的手段，然后合理地将它们归因于重要的抗体，即那些驱动疾病或用作触发病原体T细胞反应的关键抗原的识别剂的自身抗体。现在，我们已经开发了“抗体库捕获”技术，这是一种高吞吐量方法，可以使我们做到这一点。利用下一代测序的力量，我们开发了一种新的方法，用于对单个表达抗体的细胞产生的所有cDNA进行对例，从而对成对的重链和轻链免疫球蛋白基因（由单个B细胞，等离子碱或plasbablasts或plasma Cells表达）进行了高通量分析。我们假设我们可以通过定义血液中血浆和抗原分类的记忆B细胞以及Synovium中的血浆和血浆细胞的抗体曲目来阐明与RA相关的致病自身抗体反应。然后，我们将生化分析我们获得的抗体序列，以生成抗体库的进化树，从而识别并克隆可能是关键自身抗体的亲和成熟抗体。我们将确定这些重组，亲和力成熟自身抗体靶向的抗原，研究其特定序列如何发展，剖析其结合和免疫刺激特性并评估其致病性。该提案的成功将阐明自身抗体反应的发展，并确定RA中针对的主要自动抗原，这可能导致RA的新诊断和疗法的发展。