Uncovering latent factors underlying weak and robust responses to influenza vaccine in healthy and obese older adults

揭示健康和肥胖老年人对流感疫苗反应弱和强的潜在因素

• 批准号: 10665055
• 负责人: John F Alcorn
• 金额: $ 77.6万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-13 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10665055
• 关键词: Address; Adult; Affect; Age; Antibodies; Antibody Response; B-Lymphocytes; Blood specimen; Body mass index; Cell Compartmentation; Cells; Cellular Immunity; Chromatin; Computer Analysis; Coupled; Data Set; Development; Dimensions; Discipline; Effectiveness; Elderly; Epigenetic Process; Flow Cytometry; Generations; Genetic; Genetic Transcription; Genomics; Immune; Immune response; Immunity; Immunology; Impairment; Individual; Infection; Inflammation Mediators; Influenza; Influenza prevention; Influenza vaccination; Knowledge; Machine Learning; Measures; Memory; Memory B-Lymphocyte; Molecular; Molecular Profiling; Obesity; Outcome; Participant; Pathway interactions; Pattern; Peripheral Blood Mononuclear Cell; Phenotype; Plasma Cells; Plasmablast; Proteins; Race; Structure of germinal center of lymph node; System; Systems Biology; Testing; Vaccination; Vaccine Design; Vaccines; Variant; Vitamin D; Vulnerable Populations; aged; cohort; cytokine; exceptional responders; experimental analysis; frailty; gene regulatory network; healthy weight; high dimensionality; immunogenicity; influenza virus vaccine; insight; machine learning framework; machine learning method; machine learning prediction; middle age; molecular marker; multiple omics; novel; obese person; programs; response; screening; seasonal influenza; sex; transcriptomics; vaccine formulation; vaccine immunogenicity; vaccine response; vaccinology

Summary/Abstract Although vaccination is the most effective measure for influenza prevention, there is considerable variation in the responses to influenza vaccines that is influenced by factors such as age, sex, and obesity level. Major advances in predicting and analyzing the cellular and molecular basis of vaccine responses are being made possible by the application of high-dimensional experimental and computational approaches that comprise Systems Vaccinology. This framework is yielding predictive molecular signatures for influenza vaccine immunogenicity and protection. However, there remains a considerable knowledge gap in delineation of cellular and molecular pathways that affect the responses to advanced-generation influenza vaccines in older or obese individuals. To gain new insights into the cellular and molecular states that underlie variation of influenza vaccine responses in older, healthy weight or obese individuals we propose to perform deep molecular and genomic profiling of immune cell states after screening for extreme responders. Our approach, focused on extremes of individual vaccine responses, draws upon successful prior use of such a framework in analyzing genetic basis of extreme phenotypic variability. We propose in Aim 1 to elucidate latent factors and B cell genomic states underlying weak or robust immunogenicity of the advanced-generation seasonal influenza vaccine within healthy weight older individuals using deep molecular profiling and interpretable machine learning as well as computational genomics. Aim 2 will delineate latent factors and infer molecular mechanisms by which obesity distinctively affects influenza vaccine immunogenicity based on high-dimensional and multi-scale profiling of the immune responses as in Aim 1. Uncovering new molecular markers and pathways will spur tailored vaccine design that addresses specific impairments in vulnerable individuals. Our team brings together strong expertise in three complementary and essential disciplines that comprise vaccinology, immunology and systems biology.

摘要/摘要 虽然注射疫苗是预防流感最有效的措施， 受年龄，性别， 和肥胖水平。在预测和分析细胞和分子基础的主要进展， 通过应用高维度的实验， 和构成系统疫苗学的计算方法。这一框架正在产生 流感疫苗免疫原性和保护的预测性分子标记。然而，在这方面， 在描述细胞和分子途径方面仍存在相当大的知识缺口， 影响老年人或肥胖者对先进流感疫苗的反应。 获得对流感变异背后的细胞和分子状态的新见解 我们建议在老年人、健康体重或肥胖者中进行深入的疫苗接种， 筛选极端应答者后免疫细胞状态的分子和基因组分析。 我们的方法专注于个体疫苗反应的极端情况， 在分析极端表型变异的遗传基础中使用这样的框架。我们提出 在目的1中，阐明弱或强的潜在因素和B细胞基因组状态 新一代季节性流感疫苗在健康体重范围内的免疫原性 老年人使用深度分子分析和可解释的机器学习， 计算基因组学目标2将描述潜在的因素和推断分子机制， 肥胖明显影响流感疫苗的免疫原性， 以及如目标1中的免疫应答的多尺度分析。发现新的分子标记 和途径将刺激量身定制的疫苗设计，以解决脆弱人群的特定损伤， 个体我们的团队汇集了三个互补和必要的强大专业知识 包括疫苗学、免疫学和系统生物学的学科。