Modeling B Cell Vaccine Responses in Transplant Recipients

模拟移植受者的 B 细胞疫苗反应

基本信息

批准号：
8292426
负责人：
Ollivier Hyrien
金额：
$ 44.75万
依托单位：
UNIVERSITY OF ROCHESTER
依托单位国家：
美国
项目类别：
财政年份：
2007
资助国家：
美国
起止时间：
2007-05-15 至 2017-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8292426
关键词：
Accounting Address Algorithms Antibody Formation Appearance B cell differentiation B-Lymphocyte Subsets B-Lymphocytes Biological Blood Cell Cycle Kinetics Cell Size Cells Cessation of life Clinical Clinical Research Data Data Analyses Data Collection Data Set Development Failure Flow Cytometry Frequencies Goals Graft Rejection Grant Hemagglutinin Immune response Immunocompromised Host Immunoglobulins Immunosuppression In Vitro Influenza Influenza vaccination Kidney Transplantation Kinetics Logistic Regressions Mediating Memory B-Lymphocyte Methods Modeling Morbidity - disease rate Mus Nucleotides Ontology Patients Performance Pharmaceutical Preparations Phenotype Plasma Cells Population Process Public Health Research Methodology Risk ST14 gene Sampling Sorting - Cell Movement Spleen Statistical Methods Stochastic Processes T-Lymphocyte Testing Time Transplant Recipients United States Vaccination Vaccines Viral Work computer based statistical methods density design differentiated B cell healthy volunteer human subject immune activation immunosuppressed improved in vitro Model in vivo influenza virus vaccine insight lymph nodes migration mortality novel pathogen peripheral blood prevent research study response success time use tool trafficking trivalent influenza vaccine vaccination strategy

项目摘要

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. PUBLIC HEALTH RELEVANCE: Project Narrative: This project proposes to develop a novel statistical methods and mathematical models of immune responses to influenza vaccination in kidney transplant recipients. If successful, it would greatly advance prediction of vaccine responses and vaccine strategies that improve influenza immunity in kidney transplant recipients

描述（由申请人提供）：美国有超过 250,000 名肾移植接受者。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。此类药物会改变 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。使用定量方法了解 Bc 分化并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着改善临床疫苗成分和方法。这是一个重要的公共卫生问题，因为建议免疫抑制的移植受者每年接种流感疫苗，尽管反应率可能只有 50%。此外，流感感染对该人群具有很高的发病率和死亡率。鉴于当前的实验和临床研究方法仅允许对外周血免疫反应进行采样，我们提出的方法是（1）用于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新颖且定量严格的方法，可以从此类数据中提取更多相关信息。该项目旨在鉴定与健康志愿者和免疫抑制肾移植受者的疫苗反应相关的外周血 Bc 亚群。我们的主要假设是，对疫苗有反应和无反应的肾移植受者接种疫苗后，其循环 Bc 群体在表型及其激活、分裂、分化动力学速率方面存在差异。该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检验这一假设。具体目标是：(1) 开发新的统计方法来分析用于识别 Bc 群体的高维流式细胞术数据，(2) 使用这些新的统计方法来表征流感疫苗接种后小鼠 Bc 的体内和体外分化。方法，(3) 开发体外和体内小鼠 Bc 分化的分支随机过程模型，以及 (4) 使用新的统计方法来识别和研究健康和免疫抑制肾移植受者对流感疫苗接种的 Bc 反应差异方法和分支过程模型。我们评估统计方法和模型对健康志愿者、免疫抑制疫苗应答者和无应答者流感疫苗接种成功或失败的预测效果。公共卫生相关性：项目叙述：该项目提议开发一种新的统计方法和数学模型，用于肾移植受者对流感疫苗接种的免疫反应。如果成功，将极大地推进疫苗反应的预测和提高肾移植受者流感免疫力的疫苗策略