Mechanisms underlying complex trait human disease
复杂特征人类疾病的潜在机制
基本信息
- 批准号:8431505
- 负责人:
- 金额:$ 27.82万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-20 至 2017-05-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAffectAlgorithmsAlzheimer&aposs DiseaseComplexComputing MethodologiesCoupledCouplingDataDevelopmentDiabetes MellitusDiagnosisDiseaseDrug TargetingEquipment and supply inventoriesExplosionFloodsFrequenciesFutureGenesGenetic VariationGenomeGenomicsGenotypeGoalsHealthHeart DiseasesHeritabilityHumanHuman GeneticsHuman GenomeIndividualInformation NetworksKnowledgeLinkMachine LearningMalignant NeoplasmsMethodsMicroarray AnalysisMinorModelingMolecularOther GeneticsPathway AnalysisPathway interactionsPhenotypePlayPopulationProcessProteinsRNA SplicingRelative (related person)RiskRoleSamplingSomatic MutationStagingTechnologyTherapeuticTranslationsVariantWorkbasedisease phenotypedisorder riskexomeexome sequencinggene functiongenetic variantgenome sequencinggenome wide association studyhuman diseaseimprovedinsightnew technologynovel therapeuticsprotein functionpublic health relevancerisk varianttherapeutic targettooltrait
项目摘要
DESCRIPTION (provided by applicant): There is now an explosion of new genome scale data relating genetic variation within the human population to phenotype, and particularly to common disease. Microarray technology has identified 100s of loci where the presence of particular variants is associated with altered risk of many common diseases; complete sequencing of individual exomes in cancer samples has discovered many somatic mutations in a variety of genes; and sequencing of 1000 human genomes has provided an almost complete inventory of common population variants. Further, these data are only the first in an ever-increasing flood, as even faster and cheaper sequencing technologies come on line. The results hold promise for major advances in treatment and diagnosis of common human diseases. Extracting the expected benefits is not straightforward, and will necessitate acquiring detailed knowledge of the mechanisms linking genetic variation to disease. This project focuses on one aspect of this challenge - using the new genomic data to identify new therapeutic opportunities. We will investigate those principles underlying complex trait disease that are particularly relevant to tha goal. We introduce a three stage mechanistic framework, relating genomic variation to the function of impacted gene products, the impact of these altered functions on pathways, processes and subsystems; and finally the consequences for complex trait disease phenotypes. We will develop computational methods to address key questions concerning three major aspects of the framework (1) How large are the changes in protein function brought about by the genomic variants underlying complex trait disease? What role do different classes of genomic and protein level mechanism, such as expression, non-synonymous changes and splicing, play in these variants? (2) How complete is the set genes with strong influence on the disease phenotypes discovered by current technologies, and how can missing genes be imputed from the genomic and network data? (3) What is the distribution of coupling between the activity of genes involved in disease mechanism and disease phenotypes? The results will deepen understanding of these aspects of complex disease, and provide a basis for identifying potential new drug targets from GWAS and other genomic studies.
描述(由申请人提供):现在有大量新的基因组规模数据将人群内的遗传变异与表型,特别是常见疾病相关联。微阵列技术已识别出数百个位点,其中特定变异的存在与许多常见疾病的风险改变相关;对癌症样本中单个外显子组的完整测序发现了多种基因中的许多体细胞突变;对 1000 个人类基因组的测序提供了几乎完整的常见人群变异清单。此外,随着更快、更便宜的测序技术的上线,这些数据只是不断增加的数据中的第一批数据。这些结果有望在人类常见疾病的治疗和诊断方面取得重大进展。获得预期的益处并不简单,并且需要详细了解遗传变异与疾病之间的联系机制。该项目重点关注这一挑战的一个方面——利用新的基因组数据来识别新的治疗机会。我们将研究与该目标特别相关的复杂性状疾病背后的原理。我们引入了一个三阶段机制框架,将基因组变异与受影响基因产物的功能以及这些改变的功能对途径、过程和子系统的影响联系起来;最后是复杂性状疾病表型的后果。我们将开发计算方法来解决有关框架三个主要方面的关键问题(1)复杂性状疾病背后的基因组变异带来的蛋白质功能变化有多大?不同类别的基因组和蛋白质水平机制(例如表达、非同义变化和剪接)在这些变异中发挥什么作用? (2)现有技术发现的对疾病表型有强烈影响的基因组的完整性如何,以及如何从基因组和网络数据中估算缺失的基因? (3)疾病机制相关基因的活性与疾病表型之间的耦合分布如何?研究结果将加深对复杂疾病这些方面的理解,并为从 GWAS 和其他基因组研究中识别潜在新药靶点提供基础。
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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JOHN MOULT其他文献
JOHN MOULT的其他文献
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{{ truncateString('JOHN MOULT', 18)}}的其他基金
Molecular impact of mutations in monogenic disease and cancer
单基因疾病和癌症突变的分子影响
- 批准号:
9156099 - 财政年份:2016
- 资助金额:
$ 27.82万 - 项目类别:
Molecular impact of mutations in monogenic disease and cancer
单基因疾病和癌症突变的分子影响
- 批准号:
9504498 - 财政年份:2016
- 资助金额:
$ 27.82万 - 项目类别:
Mechanisms underlying complex trait human disease
复杂特征人类疾病的潜在机制
- 批准号:
8854112 - 财政年份:2013
- 资助金额:
$ 27.82万 - 项目类别:
Mechanisms underlying complex trait human disease
复杂特征人类疾病的潜在机制
- 批准号:
8738688 - 财政年份:2013
- 资助金额:
$ 27.82万 - 项目类别:
Analysis of the Functional Impact of Coding Region SNPs
编码区 SNP 的功能影响分析
- 批准号:
6320208 - 财政年份:2001
- 资助金额:
$ 27.82万 - 项目类别:
Analysis of the Functional Impact of Coding Region SNPs
编码区 SNP 的功能影响分析
- 批准号:
6538222 - 财政年份:2001
- 资助金额:
$ 27.82万 - 项目类别:
Analysis of the Functional Impact of Coding Region SNPs
编码区 SNP 的功能影响分析
- 批准号:
6642811 - 财政年份:2001
- 资助金额:
$ 27.82万 - 项目类别:
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