Pathway analysis of tuberculosis pathogenesis
结核病发病机制的通路分析
基本信息
- 批准号:7898883
- 负责人:
- 金额:$ 52.67万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-08-01 至 2014-07-31
- 项目状态:已结题
- 来源:
- 关键词:2q215p13AffectAfrica South of the SaharaCandidate Disease GeneCessation of lifeChronicClinicalComplexComputer softwareConsensusContractsDataData AnalysesDevelopmentDiseaseEnvironmentEnvironmental Risk FactorEpidemiological FactorsEpidemiologyEquationFamilyGenesGeneticGenetic Predisposition to DiseaseGenome ScanGoalsHIVHouseholdIFNGR1 geneImmuneImmune responseImmunologic FactorsImmunologicsInterleukin-10JointsKnowledgeLigandsLinkLiteratureMalignant NeoplasmsMapsMeasurementMethodsMicrosatellite RepeatsModelingMycobacterium tuberculosisNatural HistoryNatural ImmunityOutcomePathogenesisPathway AnalysisPathway interactionsPatientsPhenotypePlayPopulation StudyPrevalenceProcessProductionPublic HealthResearchResearch DesignResistanceResistance to infectionRiskRoleStagingStatistical MethodsTNFRSF1A geneTuberculosisUgandaUnited States National Institutes of HealthWorkbasecytokinedisorder riskgenetic analysisgenetic risk factorgenome wide association studyimprovedinterdisciplinary approachlatent infectionmodel developmentnovelpandemic diseaseprospectivepublic health relevanceresponsetherapeutic vaccine
项目摘要
DESCRIPTION (provided by applicant): Tuberculosis (TB), caused by M. tuberculosis (Mtb), is a significant, global public health problem, particularly in sub-Saharan Africa, where the prevalence of TB is increasing dramatically with the rise of the HIV pandemic. Previous studies provide strong evidence that host genetic factors contribute to the risk for TB disease; those studies identified potential candidate genes, but no consensus model for the genetic susceptibility to TB has yet emerged, and no studies have examined genetic influences on the early stages of Mtb infection. The present proposal utilizes patients and data collected through the Tuberculosis Research Unit (TBRU) NIH contract. Since 1995, we have been conducting a household contact study in Uganda where we are able to observe genetic and environmental risk factors for chronic Mtb infection and active TB disease. Our previous work has focused on genetic influences on the immune response and the spectrum of natural history of Mtb infection. We have shown that the TNFR1, IL10, and IFNGR1 genes are associated with TB but not resistance to Mtb infection. We have recently completed a genome scan that identified novel chromosomal regions, 2q21-2q24 and 5p13- 5q22, linked to resistance to Mtb. We have also identified innate immune response variables associated with progression to TB disease, but have not assessed immune factors associated with resistance to Mtb infection. Our preliminary results suggest that genetic and immune factors associated with resistance to Mtb infection versus TB disease development differ. Furthermore, we hypothesize that the complex interrelationships between host genes, innate immune response, and epidemiological factors combine to influence Mtb infection and progression to TB disease. To fully examine this complex network of genes and immune factors, we propose to construct a comprehensive pathway model. To this end, we propose three aims. First, we propose to fine map these novel chromosomal regions and analyze candidate genes in key immune pathways to identify genes associated with resistance to Mtb infection. Second, we propose to analyze a number of cytokines in response to innate immunity ligands to identify aspects of the innate immune response associated with resistance to Mtb infection. Third, we have developed a structural equation modeling framework appropriate for the analysis of family data, and we propose to analyze this data with that model and make software publicly available. We will analyze genetic and immunologic predictors of resistance to Mtb infection within the long-standing household contact study. This will also provide the first examination of resistance to Mtb infection; because of our thorough study design, we are uniquely poised to analyze this novel phenotype. PUBLIC HEALTH RELEVANCE: Tuberculosis (TB) is a disease with great public health importance, with one-third of the world infected by M. tuberculosis (Mtb), and almost 8 million new cases of TB occur annually with 2 million deaths attributed to TB each year. Previous studies have shown a role for both genetic and immunologic factors that predispose to progression from Mtb infection to active TB disease, but these factors have not been analyzed simultaneously and have not identified factors associated with the "healthy" uninfected state. Findings of this project will expand knowledge of the joint genetic, epidemiologic, and immunologic influences on Mtb infection and TB disease, which will facilitate the development of improved vaccines and therapeutics.
描述(由申请人提供):结核病(TB),由M.结核病(Mtb)是一个重大的全球公共卫生问题,特别是在撒哈拉以南非洲,随着艾滋病毒大流行的兴起,结核病的患病率急剧增加。以前的研究提供了强有力的证据表明,宿主遗传因素有助于结核病的风险;这些研究确定了潜在的候选基因,但尚未出现结核病遗传易感性的共识模型,也没有研究检查遗传对结核病感染早期阶段的影响。本提案利用了通过结核病研究单位(TBRU)NIH合同收集的患者和数据。自1995年以来,我们一直在乌干达进行一项家庭接触研究,在那里我们能够观察慢性结核病感染和活动性结核病的遗传和环境风险因素。我们以前的工作集中在遗传对免疫反应的影响和结核病感染的自然史谱。我们已经证明TNFR 1、IL 10和IFNGR 1基因与结核病相关,但与耐结核分枝杆菌感染无关。我们最近完成了一项基因组扫描,发现了与耐结核病有关的新的染色体区域2 q21 - 2 q24和5 p13 - 5 q22。我们还确定了与结核病进展相关的先天免疫应答变量,但尚未评估与耐结核分枝杆菌感染相关的免疫因素。我们的初步结果表明,与耐结核分枝杆菌感染和结核病发展相关的遗传和免疫因素不同。此外,我们假设宿主基因、先天免疫应答和流行病学因素之间复杂的相互关系结合联合收割机来影响结核分枝杆菌感染和结核病的进展。为了全面研究基因和免疫因子的复杂网络,我们建议构建一个全面的途径模型。为此,我们提出三个目标。首先,我们建议对这些新的染色体区域进行精细定位,并分析关键免疫途径中的候选基因,以确定与抗结核杆菌感染相关的基因。其次,我们建议分析一些细胞因子在先天免疫配体的反应,以确定与耐结核分枝杆菌感染的先天免疫反应的方面。第三,我们已经开发了一个结构方程模型框架,适用于家庭数据的分析,我们建议用该模型分析这些数据,并公开提供软件。我们将在长期的家庭接触研究中分析耐结核分枝杆菌感染的遗传学和免疫学预测因素。这也将提供对Mtb感染的抗性的第一次检查;由于我们全面的研究设计,我们独特地准备分析这种新的表型。公共卫生相关性:结核病(TB)是一种具有重大公共卫生意义的疾病,全球有三分之一的人感染结核分枝杆菌。结核病(Mtb)是全球最严重的结核病之一,每年发生近800万新发结核病病例,每年有200万人死于结核病。先前的研究表明,遗传和免疫因素都可能导致从结核分枝杆菌感染进展为活动性结核病,但这些因素尚未同时分析,也没有确定与“健康”未感染状态相关的因素。该项目的发现将扩大对结核分枝杆菌感染和结核病的联合遗传学、流行病学和免疫学影响的认识,这将促进改进疫苗和治疗方法的开发。
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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Catherine Marie Stein其他文献
Catherine Marie Stein的其他文献
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{{ truncateString('Catherine Marie Stein', 18)}}的其他基金
Systems Biology, Bioinformatics, & Data Integration
系统生物学、生物信息学、
- 批准号:
10459538 - 财政年份:2021
- 资助金额:
$ 52.67万 - 项目类别:
Systems Biology, Bioinformatics, & Data Integration
系统生物学、生物信息学、
- 批准号:
10653908 - 财政年份:2021
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$ 52.67万 - 项目类别:
Systems Biology, Bioinformatics, & Data Integration
系统生物学、生物信息学、
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10271171 - 财政年份:2021
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Genetics of TB resistance in HIV positive subjects
HIV 阳性受试者的结核病耐药性遗传学
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