Systems Immunogenetics Core

系统免疫遗传学核心

• 批准号: 8528829
• 负责人: Shannon K. McWeeney
• 金额: $ 43.66万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8528829
• 关键词: Algorithms; Alleles; Architecture; Biological; Biological Markers; Biological Response Modifiers; Candidate Disease Gene; Clinical Data; Communities; Complex; Computational Biology; Computer Simulation; Custom; DNA; Data; Data Analyses; Development; Disease; Disease Outcome; Ensure; Equation; Experimental Designs; Figs - dietary; Gene Expression; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Haplotypes; Health Sciences; Immune; Immune response; Immunity; Immunogenetics; Infection; Inflammation; Influenza; Instruction; Knowledge; Maps; Mediating; Methods; Modeling; Molecular; Natural Immunity; Network-based; Nucleic Acid Regulatory Sequences; Oregon; Other Genetics; Outcome; Pathologic; Phase; Phenotype; Process; Quantitative Trait Loci; Research; Research Personnel; Research Project Grants; Resources; Severe Acute Respiratory Syndrome; Software Tools; Statistical Models; System; Techniques; Therapeutic Intervention; Universities; Validation; Variant; West Nile virus; Work; adaptive immunity; analytical method; base; biodefense; clinical phenotype; data mining; design; genetic analysis; genetic association; genetic resource; interest; molecular phenotype; novel; pathogen; response; therapeutic target; trait; validation studies

PROJECT SUMMARY (See Instructions): DNA variations impact immune host response through the perturbations they cause to transcriptional and biological networks, providing a molecular phenotype* that is an intermediate to the clinical phenotype. By integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data, we are now able to infer transcriptional networks capable of representing causal relationships among genes and traits in the network. This provides the opportunity to identify multiple genetic perturbations that alter the states of molecular networks and that in turn move systems into disease states. Specifically, by dissecting immunogenetic traits, we are able to elucidate key drivers of immune host response beyond what could be achieved by traditional genetic association studies alone. The Systems Immunogenetics core (Core D) will provide critical statistical genetics and computational biology expertise to the U19 investigators across all projects by guiding experimental design with appropriate biostatistical oversight, providing state-of-the-art systems genetics analysis and modeling approaches and ensuring that the vast amounts of data generated are rapidly integrated to identify key genetic regulators of immune phenotype and response to SARS, Influenza and West Nile Viruses.

项目摘要（请参阅说明）： DNA的变异通过对转录和生物网络引起的扰动影响免疫宿主反应，从而提供了分子表型*，这是临床表型的中间。通过整合表达定量性状基因座（EQTL），基因表达和临床数据，我们现在能够推断能够代表网络中基因和性状之间的因果关系的转录网络。这提供了识别多种遗传扰动的机会，这些遗传扰动改变了分子网络状态，然后将系统转移到疾病状态。具体而言，通过解剖免疫发育特征，我们能够阐明免疫宿主反应的关键驱动因素，而不是传统的遗传关联研究所能实现的。 The Systems Immunogenetics core (Core D) will provide critical statistical genetics and computational biology expertise to the U19 investigators across all projects by guiding experimental design with appropriate biostatistical oversight, providing state-of-the-art systems genetics analysis and modeling approaches and ensuring that the vast amounts of data generated are rapidly integrated to identify key genetic regulators of immune phenotype and response to SARS, Influenza and West Nile Viruses.