Multi-ethnic risk prediction for complex human diseases integrating multi-source genetic and non-genetic information
整合多源遗传与非遗传信息的人类复杂疾病多民族风险预测
基本信息
- 批准号:10754773
- 负责人:
- 金额:$ 24.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-03-02 至 2026-02-28
- 项目状态:未结题
- 来源:
- 关键词:AccelerationAdvisory CommitteesAlzheimer&aposs DiseaseAreaAwardBayesian MethodBayesian ModelingBiologicalBiological MarkersCOVID-19 mortalityClinicalCollaborationsCommunicationCommunitiesComplementComplexComputing MethodologiesCoronary ArteriosclerosisDataData SetData SourcesDiseaseDisease modelDisparateEducational process of instructingEducational workshopEnsureEnvironmentEpidemiologyEthnic OriginEthnic PopulationEuropeanGene FrequencyGeneticGenetic MarkersGenetic RiskGenomicsGoalsGrantHealthHealthcareHeart DiseasesHeterogeneityIndividualInterdisciplinary StudyInterviewKnowledgeLinkage DisequilibriumLiteratureMalignant NeoplasmsMalignant neoplasm of prostateMeasurementMentorsMethodologyMethodsMinority GroupsModelingModernizationOdds RatioParameter EstimationPathway interactionsPhasePlasma ProteinsPopulationPopulation HeterogeneityPredictive FactorPreventionPrevention ResearchPrivatizationProteinsPublic HealthPublishingResearchResearch PersonnelResearch SupportRiskRisk EstimateRisk FactorsSample SizeServicesSingle Nucleotide PolymorphismSoftware ToolsSourceStrokeStructureTissuesTrainingUnderrepresented MinorityUniversitiesUrineWomanWritingbiobankcareercareer developmentcell typedata fusiondata integrationdisorder riskepidemiology studyethnic disparityethnic diversityflexibilityfunctional genomicsgenetic variantgenome wide association studyhealth inequalitieshigh dimensionalityhuman diseaseimprovedinterdisciplinary collaborationlifestyle factorsmachine learning frameworkmalignant breast neoplasmmenmodel buildingmortalitymortality riskmulti-ethnicmultidisciplinarynon-geneticnovelpolygenic risk scoreprecision medicinepredictive toolsprogramsracial disparityrisk predictionrisk prediction modelskillssociodemographicsstatisticssuccesssymposiumtooltraituser friendly softwareuser-friendly
项目摘要
Project Summary/Abstract
In genome-wide association studies (GWAS), the lack of data sources for non-European populations results in
polygenic risk predictions that could exacerbate health inequity. This racial/ethnic disparity problem exists in
many epidemiologic studies and impacts public health much more broadly. Furthermore, the rapid identification
of novel risk factors for complex diseases brings increasing opportunities to develop comprehensive risk
prediction models to combine information on genetic and other types of risk factors. The scientific goal of this
proposal is to provide enhanced disease risk prediction tools for ethnically diverse populations integrating genetic
and other data sources across disparate studies. The specific aims include: (Aim 1) develop enhanced multi-
ethnic genetic risk prediction models combining ancestry-specific GWAS summary statistics with external
genomic information, and extend the method to jointly analyze multiple related diseases; (Aim 2) develop a
flexible statistical framework that can integrate ancestry-specific, summary-level risk parameter estimates for
genetic markers and a variety of other risk factors to further improve multi-ethnic disease risk prediction; and
(Aim 3) develop and validate the risk prediction models for leading causes of mortality and other complex
traits/diseases, distribute user-friendly software and tools, and investigate their clinical utilization through
applications in precision medicine.
Dr. Jin’s long-term goal is to establish an interdisciplinary research program that combines statistical genetics,
functional genomics and epidemiology, and develop novel statistical and computational methodologies for
integrating multi-source health-related data to improve healthcare and reduce health inequities. This award will
facilitate the necessary training required for Jin’s successful transition to independence, including support from
the mentoring and advisory committee, advanced coursework, and active participation in collaborations,
workshops, and scientific conferences. Jin will gain expertise that complements her current skill set through
working closely with a highly multidisciplinary mentoring team with a combined expertise in statistical genetics,
genomics, epidemiology, and precision medicine. Johns Hopkins University provides young researchers with an
active and engaging intellectual environment, with tremendous opportunities for interdisciplinary collaborations
and career development services such as teaching institute, grant writing workshops and interview skills practice.
The research supported by this grant will generate enhanced, user-friendly disease risk prediction tools for the
underrepresented minority populations, as well as general data integration methodologies that can be widely
implemented by the community to accelerate future research in disease risk prediction and prevention. Upon
completing this award, Jin will gain a critical set of skills in research, mentoring, communication and management
that will ensure her success in establishing an independent research program and pursuing broader career goals.
项目总结/摘要
在全基因组关联研究(GWAS)中,由于缺乏非欧洲人群的数据来源,
多基因风险预测可能加剧健康不平等。这种种族/民族差异问题存在于
许多流行病学研究和影响更广泛的公共卫生。此外,快速识别
复杂疾病的新风险因素的增加带来了越来越多的机会,
预测模型,以结合遗传和其他类型的风险因素的联合收割机信息。这项研究的科学目标是
一项建议是为整合遗传学的种族多样性人群提供增强的疾病风险预测工具,
和其他不同研究的数据源。具体目标包括:(目标1)开发增强的多功能
种族遗传风险预测模型结合祖先特异性GWAS汇总统计与外部
基因组信息,并将该方法扩展到联合分析多种相关疾病;(目的2)开发一种
灵活的统计框架,可以整合特定祖先,摘要级的风险参数估计,
遗传标记和各种其他风险因素,以进一步改善多种族疾病风险预测;
(Aim 3)开发和验证主要死亡原因和其他复杂原因的风险预测模型
特征/疾病,分发用户友好的软件和工具,并通过以下方式调查其临床使用情况
在精准医疗中的应用
博士Jin的长期目标是建立一个跨学科的研究计划,将统计遗传学,
功能基因组学和流行病学,并开发新的统计和计算方法,
整合多源健康相关数据,以改善医疗保健并减少健康不公平现象。这个奖项将
为金成功过渡到独立所需的必要培训提供便利,包括来自
指导和咨询委员会,先进的课程,并积极参与合作,
研讨会和科学会议。Jin将通过以下方式获得补充其现有技能的专业知识
与具有统计遗传学综合专业知识的高度多学科指导团队密切合作,
基因组学、流行病学和精准医学。约翰霍普金斯大学为年轻的研究人员提供了一个
活跃和参与的智力环境,为跨学科合作提供了巨大的机会
以及职业发展服务,如教学机构、助学金写作讲习班和面试技巧练习。
这项资助所支持的研究将产生增强的、用户友好的疾病风险预测工具,
代表性不足的少数民族人口,以及可以广泛使用的一般数据集成方法
由社区实施,以加速未来疾病风险预测和预防的研究。后
完成这个奖项,金将获得一套关键的技能,在研究,指导,沟通和管理
这将确保她成功地建立一个独立的研究计划,并追求更广泛的职业目标。
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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Jin Jin其他文献
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{{ truncateString('Jin Jin', 18)}}的其他基金
Multi-ethnic risk prediction for complex human diseases integrating multi-source genetic and non-genetic information
整合多源遗传与非遗传信息的人类复杂疾病多民族风险预测
- 批准号:
10349828 - 财政年份:2022
- 资助金额:
$ 24.9万 - 项目类别:
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Standard Grant