Modeling B Cell Vaccine Responses in Transplant Recipients

描述（由申请人提供）：美国有超过25万名肾移植受者。基本上所有这些都需要持续的免疫抑制来防止T细胞（Tc）和B细胞（Bc）介导的移植物排斥。这类药物会改变Bc分化为PC和记忆Bc，阻碍Bc和抗体对病毒病原体和疫苗的反应，包括严重流感感染的风险。了解Bc分化和使用定量方法鉴定正常和免疫抑制患者对流感疫苗接种的反应之间的差异可以显著改善临床疫苗组合物和方法。这是一个重大的公共卫生问题，因为免疫抑制移植受者被建议每年接种流感疫苗，即使应答率可能只有50%。此外，流感感染对这一人群具有显著的发病率和死亡率。鉴于目前的实验和临床研究方法只允许外周血免疫反应的采样，我们提出的方法（1）用于分析外周血中疫苗特异性Bc的新型统计方法，结合（2）体外和体内分支随机过程建模，提供了一种从此类数据中提取更多相关信息的新型和定量严格的方法。 本项目旨在鉴定与疫苗应答相关的外周血Bc亚群，健康志愿者和免疫抑制肾移植受者。我们的主要假设是，肾移植受者接种疫苗后的循环Bc群体谁响应疫苗和那些谁不响应不同的表型，他们的激活，分裂，分化动力学速率。本项目的总体目标是使用诺埃尔统计方法和Bc分化的分支过程（BP）模型结合广泛的体外和体内数据收集来检验这一假设。具体目标是：（1）开发用于分析用于鉴定Bc群体的高维流式细胞术数据的新的统计方法，（2）使用这些新的统计方法表征流感疫苗接种后小鼠Bc的体内和体外分化，（3）开发体外和体内小鼠Bc分化的分支随机过程模型，（4）应用新的统计学方法和分支过程模型，研究健康和免疫抑制肾移植受者Bc对流感疫苗接种反应的差异。我们评估了统计方法和模型在健康志愿者、免疫抑制疫苗应答者和无应答者中预测流感疫苗接种成功或失败的效果。

DESCRIPTION (provided by applicant): There are over 250,000 kidney transplant recipients in the United States. Essentially all require ongoing immunosuppression to prevent T cell (Tc) and B cell (Bc) mediated graft rejection. Such medications alter Bc differentiation into PC and memory Bc, impeding Bc and antibody responses to viral pathogens and vaccines, including a risk of severe influenza infection. Understanding Bc differentiation and identifying differences between normal and immunosuppressed patient responses to influenza vaccination using quantitative approaches could significantly improve clinical vaccine composition and methods. This is a significant public health is- sue, as immunosuppressed transplant recipients are recommended to have annual influenza vaccination, even though the response rates may only be 50%. Furthermore, influenza infection carries a substantial morbidity and mortality for this population. Given that current experimental and clinical research methods only permit sampling of peripheral blood immune responses, our proposed approach of (1) novel statistical methods for analyzing vaccine-specific Bc in peripheral blood, combined with (2) in vitro and in vivo branching stochastic process modeling, offers a novel and quantitatively rigorous method of extracting more relevant information from such data. This project is designed to identify peripheral blood Bc subsets associated with vaccine responses healthy volunteers and immunosuppressed kidney transplant recipients. Our primary hypothesis is that circulating Bc populations after vaccination in renal transplant recipients who respond to vaccine and those who do not respond differ in respect to their phenotypes, and their activation, division, differentiation kinetic rates. The overall goal of this project is to test this hypothesis using noel statistical methods and branching process (BP) models of Bc differentiation combined with extensive in vitro and in vivo data collection. The specific goals are: (1) To develop novel statistical methods for the analysis of high dimensional flow cytometery data used to identify Bc populations, (2) To characterize the in vivo and in vitro differentiation of murine Bc after influenza vaccination using these novel statistical methods, (3) to develop branching stochastic process models of in vitro and in vivo murine Bc differentiation, and (4) To identify and study differences in Bc responses to influenza vaccination in healthy and immunosuppressed renal transplant recipients using the novel statistical methods and branching process models. We evaluate how well the statistical methods and the model predict the success or failure of influenza vaccination in healthy volunteers, immunosuppressed vaccine responders and non-responders.