Multiscale analysis of immune profiling data from dengue and chikungunya virus infections in humans

项目总结 登革热病毒(DENV)是对公众健康的重大威胁，它通过蚊子传播，感染数百人 每年在世界各地有数百万人，其中大约1亿人成为有症状的人，其中 50万人出现严重并发症，如出血热、休克综合征或死亡。尽管有很多人 解释抗体和血清细胞因子测量的努力，只有一次诊断测试能够 区分易患异型感染的患者，这些感染与重症的风险更高 并发症。对DENV的免疫反应的动态的不确定性一再受挫 努力创造一种疫苗，防止80多年来所有流行的血清型。 也许更紧迫的问题是基孔肯雅病毒(CHIKV)的蓬勃传播，这是另一种 蚊媒病毒具有较高的传播率和感染率，远高于 DENV，大约四分之三的感染者会出现包括慢性 多发性关节炎和疲劳。与DENV共享相同的城市蚊媒，CHIKV在 西半球在两年前首次被报道。像DENV一样，没有批准的 特定的治疗方法或疫苗。到目前为止，人们对分子间的相互作用知之甚少 CHIKV能够进入人体细胞并有效对抗先天免疫系统。 下一代测序和免疫图谱技术，如RNA-seq，Luminex， 蛋白质组学和CyTOF有能力产生丰富的数据，这些数据可以用来帮助阐明全球 推动人类感染病毒的生物分子变化，但前提是信号能从噪音中分离出来 确定有用的签名和关键路径。宿主内感染的发病机制是复杂的。 过程，涉及生物分子网络、细胞类型、组织和宿主个体之间的相互作用。是这样的 复杂性需要多尺度、综合的方法，因为表征一个网络或现象 孤立地不太可能充分解释整个系统发生的变化。 这项研究提出了一项分析，将识别来自免疫图谱的稳健生物标记物 尼加拉瓜儿童DENV和CHIKV感染纵向队列，作为多机构研究的一部分 财团(DHIPC)。此外，我们将把这些数据集成到主机的因果网络模型中- 病原体相互作用，这将揭示与宿主变化相关的通路的关键驱动基因 免疫反应，并促进抗病毒和疫苗的发现。考虑到预期的数据，这项提议 最大限度地提高DENV和CHIKV的建模方法对未来生物发现和 在传染病的整体、数据驱动的建模方面推进最新技术。

PROJECT SUMMARY Dengue virus (DENV) is a significant threat to public health, transmitting via mosquitos and infecting hundreds of millions around the world each year, of which roughly one hundred million become symptomatic and one half-million develop severe complications such as hemorrhagic fever, shock syndrome, or death. Despite many efforts to interpret antibody and serum cytokine measurements, only once has a diagnostic test been able to differentiate patients that are susceptible to heterotypic infections that associate with greater risk for severe complications. The uncertainty of the dynamics of the immune response to DENV has repeatedly thwarted efforts to create a vaccine protecting against all prevalent serotypes for over 80 years. A perhaps even more urgent problem is the blossoming spread of chikungunya virus (CHIKV), another mosquito-borne virus characterized by higher transmissibility and infection rates much higher than those of DENV, with roughly three quarters of infected persons developing symptoms that can include chronic polyarthritis and fatigue. Sharing the same urban mosquito vectors as DENV, the transmission of CHIKV within the Western hemisphere was reported for the first time two years ago. Like DENV, there are no approved specific treatments or vaccines. So far, very little is known about the molecular interactions necessary for CHIKV to enter human cells and effectively counter the innate immune system. Next generation sequencing and immune profiling technologies such as RNA-seq, Luminex, proteomics, and CyTOF have the ability to generate a wealth of data that can be used to help illuminate global biomolecular changes driving viral infections in humans, but only if signal can be separated from noise to identify useful signatures and key pathways. The pathogenesis of an infection within a host is a complex process, involving interactions among networks of biomolecules, cell types, tissues, and host individuals. Such complexity necessitates a multiscale, integrative approach, since characterizing one network or phenomenon in isolation is unlikely to sufficiently explain changes occurring across the entire system. This study proposes analyses that will identify robust biomarkers derived from immune profiling of a longitudinal cohort of pediatric DENV and CHIKV infections in Nicaragua, as part of a multi-institutional consortium (DHIPC). Furthermore, we will integrate these data into causal network models of the host- pathogen interaction, which will reveal key driver genes for pathways that associate with changes in the host immune response and facilitate antiviral and vaccine discovery. Given the anticipated data, this proposal maximizes the impact of the modeling approach for DENV and CHIKV on future biological discovery and advances the state of the art in holistic, data-driven modeling of infectious disease.