Modeling B Cell Vaccine Responses in Transplant Recipients

描述(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)介导的移植排斥反应。这些药物改变了BC向PC和记忆性BC的分化，阻碍了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的分化，并使用定量方法识别正常和免疫抑制患者对流感疫苗接种反应的差异，可以显著改进临床疫苗组成和方法。这是一个重大的公共卫生问题，因为免疫抑制的移植受者被建议每年接种流感疫苗，尽管应答率可能只有50%。此外，流感感染给这一人群带来了相当大的发病率和死亡率。鉴于目前的实验和临床研究方法只允许对外周血液免疫反应进行采样，我们提出的方法(1)分析外周血中疫苗特异性BC的新统计方法，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的、定量严格的方法。该项目旨在确定与疫苗反应相关的外周血BC亚群、健康志愿者和免疫抑制的肾移植受者。我们的基本假设是，肾移植受者接种疫苗后，对疫苗有反应和无反应的循环BC群体的表型、激活、分裂和分化动力学速度不同。本项目的总体目标是使用Noel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验证这一假说。具体目标是：(1)开发用于识别BC群体的高维流动细胞计量学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)建立体外和体内小鼠BC分化的分支随机过程模型；(4)利用新的统计方法和分支过程模型识别和研究健康和免疫抑制的肾移植受者BC对流感疫苗免疫应答的差异。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程度。

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.