A systems biology approach to understand immunity and pathogenesis of malaria in children

疟疾是一个主要的健康问题，世界上大约有一半的人口处于危险之中。大多数疟疾病例和死亡发生在撒哈拉以南非洲，是由“恶性疟原虫”造成的，每年的死亡率高达70万，其中大多数是儿童。尽管经过多年的努力和投资，我们仍然没有一种非常有效的疫苗。其中一个原因是我们对疟疾寄生虫和免疫之间的相互作用了解不完全。对疟原虫的免疫反应是复杂的，疟疾流行地区的保护性免疫只有在暴露若干年后才会产生。我们从对纵向队列的长期研究中了解到，儿童疟疾感染的结果变化很大，有些儿童有两到三次临床发作，而另一些儿童有非常频繁的临床发作或严重的发作，但没有明显的免疫力。疟疾可对免疫反应产生深远的抑制性影响。我们的假设是，这些经常有症状的疟疾感染的儿童陷入了一个因果“循环”（或“恶性循环”），即疟疾发作导致对疟疾的免疫力受损，这反过来又导致疟疾进一步发作。在我们的第一阶段分析中，我们将调查一组对恶性疟原虫疟疾产生免疫力的儿童的免疫反应，我们对这些儿童有详细的疟疾暴露生活史。我们将比较有反复临床疟疾发作史的儿童与临床疟疾发作次数正常（匹配年龄、地点和疟疾暴露）的儿童的免疫反应。我们还将检查住在附近但未接触疟疾的第三组儿童的反应。第一阶段的分析将确立分析方法，确定反应模式，并产生可在第二阶段进行检验的模型和假设（见下文）。我们将结合转录组学、流式细胞术、细胞因子分析和疟疾特异性B细胞/抗体反应，尽可能全面地比较两组宿主反应的特征。单一的免疫反应“瞬间”可能仅代表免疫过程的终点，可能无法反映与疟疾结果差异有因果关系的免疫过程。因此，在第二阶段的检测中，我们将在监测临床疟疾发作之前从整个队列中收集和储存样本。将储存样本，然后在确定与上述第一阶段描述的相似群体时进行测试和分析（即多发发作vs正常发作）。这些样本将由不了解流行病学数据的实验室和分析小组进行分析，并将审查在第一阶段确定的特征与可能发生的疟疾发作之间的关联。我们将在第二年对该队列中的儿童进行进一步的横断面评估，以评估这些标志物随时间的稳定性。我们的研究将确定免疫反应模式，这些模式可以用作儿童对临床疟疾产生免疫能力的预测标记，并将在为合理的疫苗设计提供信息以及监测疫苗疗效和治疗方法方面具有重要价值。我们将建立一套强大的分析和建模工具，可用于进一步的研究，这将结合寄生虫和宿主的遗传变异，并将为动物模型的机制研究提供信息。我们独特的数据集将可供其他研究人员使用，所获得的专业知识将有助于在英国建立系统免疫学专业知识。

Malaria is a major health problem, with approximately half of the world's population at risk. Most malaria cases and deaths occur in sub-Saharan Africa and are caused by the species "Plasmodium falciparum", with an annual mortality rate of up to 700,000, mostly among children.. Despite many years of work and investment, we still do not have a highly effective vaccine. One reason for this is that we have an incomplete understanding of the interaction between malaria parasites and immunity. Immune responses to Plasmodium are complex, and protective immunity in malaria endemic areas develops only after several years of exposure. We know from our long-term studies of longitudinal cohorts that the outcome of malaria infection in children is extremely variable such that some children have two or three clinical episodes while others have very frequent clinical episodes or severe episodes without apparently becoming immune. Malaria can have a profound suppressive impact on immune responses. Our hypothesis is that these children with frequent and symptomatic malaria infections are caught in a causal "loop" (or "vicious cycle") whereby malaria episodes lead to impaired immunity to malaria, which in turn leads to further episodes of malaria. In our first phase of analysis, we will investigate immune responses in a cohort of children developing immunity to P.falciparum malaria, for whom we have detailed life histories of malaria exposure. We will compare those immune responses of children with a history of repeated and clinical malaria episodes with those of children with a normal number of clinical malaria episodes (matching age, location and malaria exposure). We will also examine responses in a third group of children who live nearby, but are not exposed to malaria. This first phase of analysis will establish the analytical methodology, determine patterns of responses, and generate models and hypotheses that can be tested in the second phase (see below). We will combine transcriptomic, flow-cytometric, cytokine analyses, and malaria-specific B cell/antibody responses to compare as comprehensively as possible the features of the host response in the two groups. A single "snap shot" of immune responses may represent only the endpoint of immune processes and may not reflect those that are causally related to differences in malaria outcome. Therefore, in a second phase of testing, we will collect and store samples from the whole cohort prior to surveillance for clinical malaria episodes. Samples will be stored, and then tested and analysed when parallel groups to those describe for the first phase above can be identified (i.e. multiple episodes vs normal episodes). These samples will be analysed by the laboratory and analytical teams blinded to epidemiological data, and the association between the signatures identified in the first phase and malaria episodes in prospect will be examined. We will undertake a further cross-sectional assessment of the children in this cohort in the second year, in order to assess the stability of these markers over time.Our studies will identify immune response patterns that can be used as predictive markers of the child's ability to develop immunity to clinical malaria, and will be of great value in informing rational vaccine design, and monitoring vaccine efficacy and therapeutics. We will establish a set of robust analytical and modeling tools, which can be used in further studies, which will combine genetic variation in parasite and host, and which will inform mechanistic studies in animal models. Our unique dataset will be available for other researchers, and the expertise acquired will help establish a systems immunology expertise in the UK.