A systems immunology approach to evaluate malaria vaccine performance in endemic regions of Kenya

高效疟疾疫苗仍然是控制和消除疟疾的最终工具。领跑者 是RTS，S/AS 01，一种包含恶性疟原虫（Pf）环子孢子部分的重组蛋白 蛋白（CSP）。然而，在疟疾流行地区的儿童中观察到的疫苗对临床疟疾的有效性 设置只有36%。为了了解如何改进这种疫苗，对 阻碍疟疾疫苗性能的基线和累积因素，与 与预防疟疾有关的措施。我们最近定义了更强的保护相关性， 基于使用系统血清学方法的功能性抗体活性。迄今为止，这些系统血清学 仅对非流行地区的成年人进行了研究。在这里，我们的目标是测试整体 假设生活在疟疾流行地区的儿童，其免疫细胞不成熟或异常， 不能发展RTS，S引起的功能性抗体和T细胞的广度，以成为 防止疟疾。借鉴世卫组织疟疾疫苗实施方案， 在肯尼亚的传播地区，我们将采用密集的纵向队列研究设计， 在4剂RTS，S疫苗接种计划期间，对Pf感染进行主动和被动随访， 临床疟疾发作，直到他们达到4岁。我们的总体假设将由 以下具体目标：SA 1：全面描述基线和接种前后因素， 与疫苗低反应性有关。利用一个综合系统免疫学和机器 学习方法，我们将确定持续暴露于疟疾，全身炎症， 现有的抗疟疾免疫，以及RTS，S疫苗低剂量的细胞免疫特征的不成熟， 反应性，定义为不能形成功能性抗CSP抗体的核心组。SA 2：至 全面描述儿童接种疫苗后的免疫特征， 预防疟疾。使用系统免疫学方法，我们将确定疫苗的功能- 引发的抗CSP抗体及其与年龄、细胞免疫特征和 疟疾功能性体外研究将评估子孢子的抗体调理作用和抗体依赖性抗体调理作用。 有和没有先天免疫细胞的细胞毒性;评估疫苗的表型和功能- 诱导CSP特异性T细胞;并探索单核细胞表观遗传修饰的潜力（训练的 免疫力）影响疫苗性能。使用计算建模/机器学习方法，我们 将整合深度免疫分析功能，以预测与预防疟疾的相关性。在一起，这 这项研究旨在为下一代疟疾疫苗和疫苗接种计划提供信息，这些疫苗和计划可能包括 免疫调节成分或建议，以便在疟疾预防/治疗中结合联合收割机 疫苗时间表

A highly effective malaria vaccine remains the ultimate tool for malaria control and elimination. The front runner is RTS,S/AS01, a recombinant protein comprising portions of Plasmodium falciparum (Pf) circumsporozoite protein (CSP). However, the observed vaccine efficacy to clinical malaria in children living in malaria endemic settings is only 36%. In order to understand how to improve upon this vaccine, a comprehensive evaluation of baseline and cumulative factors that impede malaria vaccine performance, in direct contrast to factors associated with protection from malaria, is needed. We have recently defined stronger correlates of protection based on functional antibody activity using a systems serology approach. To date, these system serology studies have been conducted only for adults from non-endemic regions. Here, we aim to test the overall hypothesis that children living in malaria endemic areas who have less mature or aberrant immune cells are unable to develop the breadth of functional antibodies and T cells elicited by RTS,S in order to become protected against malaria. Drawing on the WHO Malaria Vaccine Implementation Program in a high- transmission region in Kenya, we will employ an intensive longitudinal cohort study design to follow children during their 4-dose RTS,S vaccination schedule, with active and passive follow-up for Pf infections and episodes of clinical malaria until they reach 4 years of age. Our overall hypothesis will be tested by the following specific aims: SA1: To comprehensively characterize baseline and peri-vaccination factors that correlate with vaccine hyporesponsiveness. Using an integrated systems immunology and machine learning approach, we will determine the effects of ongoing exposures to malaria, systemic inflammation, pre- existing anti-malarial immunity, and immaturity of cellular immune signatures on RTS,S vaccine hypo- responsiveness, defined as the inability to develop a core group of functional anti-CSP antibodies. SA2: To comprehensively characterize the post-vaccination immune signatures in children that correlate with protection from malaria. Using a systems immunology approach, we will determine the function of vaccine- elicited anti-CSP antibodies and their correlation with age, cellular immune signatures, and protection from malaria. Functional in vitro studies will assess antibody opsonization of sporozoites and antibody-dependent cellular cytotoxicity with and without innate immune cells; assess the phenotype and function of vaccine- elicited CSP-specific T cells; and explore the potential for epigenetic modifications of monocytes (trained immunity) to influence vaccine performance. Using a computational modeling/machine learning approach, we will integrate deep immunoprofiling features to predict correlates with protection from malaria. Together, this study aims to inform the next generation of malaria vaccines and vaccination programs that could include immune-modulatory components or recommendations to combine antimalarial prophylaxis/treatment within the vaccine schedule.