Defining signatures for immune responsiveness by functional systems immunology

描述(由申请人提供)：免疫状态的遗传变异性和个体差异决定了对疫苗接种、感染的反应，并有助于疾病的严重性。人类基因组测序和单倍型图谱的生成现在使人们能够从机制上理解遗传变异如何影响人类免疫反应。然而，多种非遗传因素也相互作用，以维持健康的免疫系统，需要进行复杂的分析，以形成对其对扰动的反应的预测。在这里，我们将使用系统方法和新颖的、高通量和高保真的技术，如多路基因表达、自动化多维流式细胞术和纳米细胞中集成的单细胞分析，以定量评估白细胞功能，最终确定定义个体免疫反应的分子特征。我们将在三个相关研究中解决免疫图谱问题。在研究项目1中，我们将开发流感疫苗反应性的免疫学特征，并确定年龄和功能状态对这些特征的影响。我们将识别能够区分疫苗免疫反应强弱和预测有效反应的基因特征和生物途径。在研究项目2中，我们将调查西尼罗河病毒和丙型肝炎病毒对黄病毒感染的耐药性；通过对分层队列患者反应的分析，我们将建立基因表达、免疫细胞反应和临床结果之间的相关性。在研究项目3中，我们将生成检测连通性并预测免疫系统动态功能反应的数学模型。这一方法将使用多变量统计方法将收集的关于群体和个人的数据联系起来，以整合全队列数据，包括全基因组关联研究和新颖的单细胞分析，以评估与遗传变异相关的免疫反应。我们的功能系统免疫学方法将使我们能够定义病毒感染和疫苗接种后的基线人类免疫特征以及与该基线的偏差，目标是确定未来干预的目标，并建立一套预测疫苗接种反应的生物标记物。

DESCRIPTION (provided by applicant): The genetic variability and Individual variations in immune status dictate responses to vaccinations, infections, and contribute to disease severity. The sequencing of the human genome and generation of the Haplotype Map now enables a mechanistic understanding of how genetic variation influences human immune responses. Yet manifold non-genetic factors also interact to maintain the healthy immune system, and complex analysis will be required to form predictions for its response to perturbations. Here, we will employ systems approaches and novel, high throughput and high-fidelity technologies such as multiplexed gene expression, automated multidimensional flow cytometry, and integrated single-cell assays in nanowells to quantitatively assess leukocyte function to ultimately identify the molecular signatures defining individual immune responses. We will address immune profiles in three related studies. In Research Project 1, we will develop immunologic signatures of influenza vaccine responsiveness and determine the effect of aging and functional status on these signatures. We will identify gene signatures and biological pathways that can distinguish between strong and weak immune responses to vaccination and that predict effective responses. In Research Project 2, we will investigate resistance to flaviviral infections using West Nile virus, and hepatitis C virus; through analysis of responses in patients from stratified cohorts, we will establish correlations between gene expression, immune cell responses and clinical outcome. In Research Project 3, we will generate mathematical models that detect connectivity and predict dynamic functional responses of the immune system. This approach will link data collected on both populations and individuals using multivariate statistical approaches to integrate cohort-wide data including genome wide association studies and novel single-cell analyses to assess immune responsiveness in relationship to genetic variation. Our functional systems immunology approach will allow us to define baseline human immune signatures following viral infection and vaccination along with deviations from this baseline, with the goal of identifying future targets for intervention and establishing sets of biomarkers that predict responses to vaccination.