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25万肾移植接受者。本质上，所有这些都需要持续的免疫抑制以防止T细胞（TC）和B细胞（BC）介导的移植物排斥。这种药物改变了BC分化为PC和Memory BC，阻碍了BC和对病毒病原体和疫苗的抗体反应，包括严重流感感染的风险。了解BC分化并确定使用定量方法对患者对流感疫苗的正常和免疫抑制反应之间的差异可以显着改善临床疫苗的组成和方法。这是一个重要的公共卫生，因为建议接受免疫抑制的移植受者进行年流感疫苗接种，即使答复率可能仅为50％。此外，流感感染对该人群带来了大量的发病率和死亡率。鉴于当前的实验和临床研究方法仅允许对周围血液免疫反应进行取样，因此我们提出的方法是（1）（1）新型的统计方法，用于分析外周血中的疫苗特异性BC，并结合（2）体外和体内和体内分支分支过程建模，提供了一种新颖的方法，可提供新颖的方法，以提取更多相关的方法。该项目旨在识别与疫苗反应有关的外围血液BC亚群健康志愿者和免疫抑制的肾脏移植受者。我们的主要假设是，在肾移植受者中疫苗接种后循环的BC种群对疫苗的反应以及对其表型反应不反应的人以及其激活，分裂，分化动力学率有所不同。该项目的总体目标是使用NOEL统计方法和分支过程（BP）模型来检验该假设，并结合了广泛的体外和体内数据收集。 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使用新颖的统计方法和分支过程模型中的健康和免疫抑制肾移植受者中的流感疫苗接种。我们评估了统计方法和模型在健康志愿者，免疫抑制疫苗反应者和非反应者中的流感疫苗接种成功或失败的状况。公共卫生相关性：项目叙述：该项目提议开发一种新颖的统计方法和对肾脏移植受体中流感疫苗接种的免疫反应的新型统计方法和数学模型。如果成功，它将大大提高对疫苗反应和疫苗策略的预测，从而改善肾脏移植受体中流感免疫力