Detection and Characterization of Flavivirus and Alphavirus Infections in Acute Suspected Arboviral Cases or Neurological Disease, Central Department, Paraguay
急性疑似虫媒病毒病例或神经系统疾病中黄病毒和甲病毒感染的检测和表征,巴拉圭中央部门
基本信息
- 批准号:9808957
- 负责人:
- 金额:$ 23.51万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-06-12 至 2021-05-31
- 项目状态:已结题
- 来源:
- 关键词:AccountingAcuteAdvanced DevelopmentAlphavirusAlphavirus InfectionsAntibodiesAntibody ResponseArbovirus InfectionsArbovirusesBiological AssayCRISPR/Cas technologyCategoriesChikungunya virusClinicalClinical ManagementDataDengueDengue VirusDetectionDiagnosisDiseaseDisease OutbreaksEncephalitisEpidemicEpidemiologyExposure toFamilyFeverFlavivirusFlavivirus InfectionsGoalsGuillain-Barré SyndromeHeterophile AntibodiesHumanImmunityImmunoglobulin GImmunoglobulin MIncidenceInfectionInterventionLaboratoriesLaboratory DiagnosisMeningitisMeningoencephalitisMethodsMolecularNeurologicNeurologic ProcessOutcomePan GenusParaguayPatient riskPatient-Focused OutcomesPatientsPhylogenetic AnalysisPopulationProtocols documentationResearchRiskRisk stratificationSamplingSerologic testsSerologicalSeroprevalencesSurveillance MethodsSyndromeSystemTechniquesTechnologyTest ResultTestingViralViral EpidemiologyViral GenomeViral Load resultVirusVirus DiseasesWest Nile virusWorkZika Virusarbovirus diseasebasechikungunyaclinical Diagnosiscostgenetic signaturegenome sequencinghuman diseasehuman pathogenimprovednervous system disordernext generation sequencingnovelpathogenpatient populationprognostic assaystransmission processwhole genome
项目摘要
PROJECT ABSTRACT
Flaviviruses and alphaviruses are the two most common genera of arboviral pathogens, accounting for
hundreds of millions of infections annually and repeated epidemics over the past 20 years. In total, these large
genera include over a hundred potential human pathogens. Symptomatic infections with the flaviviruses (e.g.
dengue, Zika, West Nile) and alphaviruses (e.g. chikungunya, Mayaro) present with non-specific
manifestations and predominantly result in two overlapping acute clinical syndromes: a systemic illness with or
without fever and a neurological illness such as meningoencephalitis. However, it is costly and impractical to
test patients for more than a few common pathogens, and research protocols typically focus on one clinical
syndrome. These factors complicate the detection of arboviral infections, surveillance and control efforts, and
the calculation of accurate incidence estimates. Research in this proposal will utilize novel molecular methods
for pan-genus detection and new multiplex serological methods to simultaneously screen for antibodies against
eight arboviruses. The objective of the proposal is to evaluate new molecular and serological methods for the
characterization of the incidence, seroprevalence and diversity of flavivirus and alphavirus infections among
symptomatic patients. Research will be performed in Asunción and the Central Department of Paraguay,
where recent transmission of multiple arboviruses has been documented. Our central hypotheses are that 1)
these new methods will increase the breadth of arbovirus detection among symptomatic patients, 2) evidence
of exposure to multiple arboviruses will be common, and 3) broad, heterotypic antibody responses will protect
against severe disease. This research will first characterize flavivirus and alphavirus infections among patients
with an acute suspected arboviral illness or acute neurological disease (meningitis, encephalitis, Guillain-Barré
syndrome). Pan-flavivirus and pan-alphavirus detection will be performed with a novel molecular assay. Viral
epidemiology, clinical findings, and patient outcomes will be described among patients who meet the study
definitions. The incidence of symptomatic and severe disease will then be determined in relation to arboviral
antibodies at presentation. Multiplex serological testing will be performed to detect IgM and IgG against five
flaviviruses and three alphaviruses. Seroprevalence will be calculated, and the incidence of symptomatic and
severe disease will be evaluated in relation to the presence of pre-infection antibodies to heterotypic viruses.
Finally, whole-genome viral sequences will be obtained directly from clinical samples using a CRISPR/CAS9
depletion system to analyze viral phylogenetics and identify new/rare viral strains. The purpose of this research
is to improve laboratory methods for the most common human arbovirus families and identify patients at risk
for symptomatic or severe arboviral illnesses. This work is expected to have an important positive impact
because improved surveillance methods and patient risk stratification will result in increased arbovirus
detection and targeted interventions for clinical management and outbreak control.
项目摘要
黄病毒和α病毒是弧病毒病原体的两个最常见的属
在过去的20年中,每年数亿个感染和重复发作。总共这些很大
属包括一百多个潜在的人类病原体。黄病毒的有症状感染(例如
登革热,西尼罗河)和α病毒(例如,chikungunya,Mayaro)
表现和主要导致两种重叠的急性临床综合症:一种全身性疾病
没有发烧和神经系统疾病,例如脑膜脑炎。但是,这是昂贵且不切实际的
测试患者的多种常见病原体,研究方案通常集中于一个临床
综合征。这些因素使检测灰臂感染,监视和控制努力以及
准确事件估计的计算。该提案中的研究将利用新颖的分子方法
用于Pan-Genus检测和新的多重血清学方法,以同时筛选抗体
八个arboviruses。该提案的目的是评估新的分子和血清学方法
事件的表征,血清阳性和黄病毒和α病毒感染的多样性
有症状的患者。研究将在Asunción和巴拉圭中央部进行
最近记录了多个弧病毒的传播。我们的中心假设是1)
这些新方法将增加有症状患者中arbovirus检测的广度,2)证据
暴露于多个弧病毒将是常见的,3)宽阔的异型抗体反应将保护
反对严重疾病。这项研究将首先表征患者的黄病毒和α病毒感染
患有急性疑似弧病毒疾病或急性神经系统疾病(脑膜炎,脑炎,Guillain-Barré
综合征)。泛氟病毒和泛阿尔巴病毒检测将使用新型分子测定法进行。病毒性的
在符合研究的患者中,将描述流行病学,临床结果和患者结局
定义。随后将与灰牛病毒有关的有症状和严重疾病的事件
演示时的抗体。将进行多重血清学测试以检测IgM和IgG针对五个
黄病毒和三个α病毒。将计算血清阳性,并有症状和
将评估严重的疾病与异性型病毒的感染前抗体有关。
最后,将使用CRISPR/CAS9直接从临床样品中获得全基因组病毒序列
耗尽系统以分析病毒系统发育学并鉴定新的/稀有的病毒菌株。这项研究的目的
是为了改善最常见的人类Arbovirus家族的实验室方法,并确定有风险的患者
有症状或严重的丘病毒疾病。预计这项工作将产生重要的积极影响
因为改善的监视方法和患者风险分层将导致刺激病毒增加
用于临床管理和爆发控制的检测和针对性干预措施。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Jesse Waggoner其他文献
Jesse Waggoner的其他文献
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{{ truncateString('Jesse Waggoner', 18)}}的其他基金
Once Bitten: Detecting the World's Most Common Vector-Borne Pathogens
一旦被咬:检测世界上最常见的媒介传播病原体
- 批准号:
9347336 - 财政年份:2016
- 资助金额:
$ 23.51万 - 项目类别:
Once Bitten: Detecting the World???s Most Common Vector-Borne Pathogens
一旦被咬:检测世界上最常见的媒介传播病原体
- 批准号:
8677493 - 财政年份:2014
- 资助金额:
$ 23.51万 - 项目类别:
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