Immune status as a predictor of neonatal vaccine immunogenicity

项目2 -概要 疫苗每年挽救数百万人的生命，但在生命早期感染的风险仍然很高。改善 生命早期免疫需要更好地理解疫苗诱导的分子途径， 以保护相关物（CoP）的形式保护和免疫原性。系统生物学方法 应用于疫苗学的OMIC（“OMIC”）已经提供了对疫苗介导的保护的重要见解，但 尽管最年幼的儿童非常需要改进免疫接种，但尚未对他们适用。免疫 从出生开始接种B型肝炎疫苗（HBV）非常有效，保护率> 90%。HBV是一种 具有良好表征和可定量CoP（抗Hep B表面抗原抗原）的少数疫苗 （抗-HBs）抗体水平）。重要的是，虽然有一个既定的最低保护阈值（抗-HBs > 10 mIU/ml），达到的绝对滴度与保护直接相关（滴度越高， 保护越持久）。如此高的保护效力，加上可量化的CoP， 新生儿和婴儿人群中显著的应答变异性使HBV成为定义 新生儿免疫成功的机制。因此，我们的重债穷国倡议侧重于 “系统生物学识别新生儿疫苗免疫原性的生物标志物”使用HBV作为模型。到 为此，新生儿将接种无（延迟），HBV，BCG或（HBV + BCG）和外周 免疫前/后采集血液，用于转录组学和蛋白质组学分析，以确定途径 与CoP有关。在我们的项目2（“免疫状态作为新生儿疫苗免疫原性的预测因子”; PI Tobias Kollmann;联合负责人Ryan Brinkman），我们将分析OMIC询问的完全相同的样本 通过详细的免疫表型分析将衍生的OMIC签名翻译成宿主免疫表型的方法 参数这不仅有助于对OMIC消息进行解卷积， 确定预测新生儿免疫后保护性免疫反应的生物标志物所必需的详细视图 乙肝疫苗。在目标1中，我们将通过高端流式细胞术测定血液样品中的细胞组成， 新生儿免疫前和免疫后的样本，并与疫苗结果相关。为此我们 开发了一种新型的自动无监督门控平台，相当于无偏系统 生物学发现方法，但流式细胞术。在目标2中，我们将确定可溶性 免疫调节剂，包括细胞因子、趋化因子和嘌呤代谢酶， 并与疫苗结果相关。在目标3中，我们将开发新的工具， 推进高端免疫表型分析，并将其应用于新生儿疫苗的数据 对HBV的反应。总的来说，我们的努力将提供关键的洞察免疫表型相关的 保护性新生儿免疫接种，从而为今后开发生命早期疫苗提供信息。

PROJECT 2 - SUMMARY Vaccines save millions of lives each year but the risk of infection remains high early in life. Improvement of early life immunization requires a better understanding of vaccine-induced molecular pathways that underlie protection and immunogenicity in the form of Correlates of Protection (CoP). Systems biology approaches (“OMICs”) applied to vaccinology have provided critical insights into vaccine-mediated protection, but have not yet been applied to the youngest, despite their great need for improved immunization. Immunization with Hepatitis B vaccine (HBV) starting at birth is highly effective resulting in protection of > 90%. HBV is one of the few vaccines that has a well characterized and quantifiable CoP (anti-Hep B surface antigen antigen (anti-HBs) antibody levels). Importantly, while there is an established minimal protective threshold (anti-HBs > 10 mIU/ml), the absolute titer reached correlates directly with protection (the higher the titer, the higher and the more durable the protection). Such high protective efficacy, coupled with a quantifiable CoP yet significant response-variability in the neonatal and infant population makes HBV an ideal model to define mechanisms underlying successful neonatal immunization. Accordingly, our HIPC proposal, focuses on ’Systems Biology to Identify Biomarkers of Neonatal Vaccine Immunogenicity’ using HBV as the model. To this end, newborns will be immunized with nothing (delayed), HBV, BCG or (HBV + BCG) and peripheral blood pre-/post-immunization collected for transcriptomic and proteomic analyses to identify pathways associated with CoP. In our Project 2 (“Immune status as a predictor of neonatal vaccine immunogenicity’; PI Tobias Kollmann; Co-Lead Ryan Brinkman) we will analyze the exact same samples interrogated by OMIC approaches via detailed immune phenotyping to translate the derived OMICs signatures to host immune parameters. This will not only help to de-convolute the OMIC message, but generate the fine-granular detailed view necessary to identify biomarkers predicting a protective immune response following neonatal HBV vaccination. In Aim 1 we will determine cell composition in blood samples by high-end flow cytometry in pre- and post immunization samples from newborns and correlate with vaccine outcome. To this end we have developed a novel automated unsupervised gating platform that is the equivalent of unbiased systems biology discovery approaches but for flow cytometry. In Aim 2 we will determine the concentration of soluble immune modulators including cytokines, chemokines, and purine metabolizing enzymes in plasma pre- and post- immunization and correlate with vaccine outcome. In Aim 3 we will develop novel tools to further advance high-end immune phenotyping, and apply them to the data generated here on the newborn vaccine response to HBV. Overall our efforts will provide key insight into immunophenotypes associated with protective neonatal immunization thereby informing future development of early life vaccines.