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，世界上大约一半的人口面临着疟疾的威胁。大多数疟疾病例和死亡发生在撒哈拉以南非洲，由“恶性疟原虫”引起，每年死亡率高达70万，其中大多数是儿童。尽管多年的工作和投资，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力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几年后才能发展。我们从对纵向队列的长期研究中了解到，儿童感染疟疾的结果差异极大，有些儿童有两三次临床发作，而另一些儿童则有非常频繁的临床发作或严重发作，但没有明显的免疫力。疟疾可以对免疫反应产生深远的抑制作用。我们的假设是，这些频繁和有症状的疟疾感染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的进一步发作。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，我们对他们有详细的疟疾暴露史。我们将比较有反复和临床疟疾发作史的儿童与临床疟疾发作次数正常的儿童的免疫反应（匹配年龄，地点和疟疾暴露）。我们还将研究住在附近但没有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，确定应对模式，并生成可在第二阶段进行检验的模型和假设（见下文）。我们将结合联合收割机转录组学、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中宿主反应的特征。免疫反应的单一“快照”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，在测试的第二阶段，我们将在监测临床疟疾发作之前收集和储存整个队列的样本。将储存样本，然后在可以识别出与上述第一阶段所述平行的组时进行检测和分析（即多次发作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，并将研究第一阶段确定的特征与前景疟疾发病之间的关系。我们将在第二年对这一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应答模式，这些模式可用作儿童对临床疟疾产生免疫力的预测标志物，并将对合理的疫苗设计提供信息，并监测疫苗的有效性和治疗方法具有重要价值。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，这将结合联合收割机在寄生虫和宿主的遗传变异，并将告知在动物模型中的机制研究。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.