PAGE-G: Precision Approach combining Genes and Environment in Glaucoma
PAGE-G:青光眼基因与环境相结合的精准方法
基本信息
- 批准号:10797646
- 负责人:
- 金额:$ 31.6万
- 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:2023-09-30 至 2025-08-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAffectAfricanAfrican ancestryAge of OnsetAll of Us Research ProgramAutomobile DrivingBindingBiomedical ResearchBlindnessCharacteristicsChromatinChronic DiseaseClinicalClinical DataComplexDataDatabasesDiseaseDisease ManagementDoctor of PhilosophyEarly DiagnosisEarly treatmentElementsEnhancersEnvironmentEnvironmental Risk FactorEuropeanEvaluation StudiesEventEyeEye diseasesFunctional disorderGene CombinationsGeneticGenetic RiskGenetic VariationGenomicsGlaucomaHealthcareHeritabilityHumanIndividualKnowledgeLiteratureMapsMeasuresMedicalMeta-AnalysisModelingNucleic Acid Regulatory SequencesOptic NerveParticipantPerformancePersonsPhenotypePopulationPopulation HeterogeneityProcessPublishingRegulationRegulatory ElementResearch PersonnelResourcesRiskRisk EstimateRisk FactorsRoleTestingTissuesTrainingUnited KingdomUnited States National Institutes of HealthUntranslated RNAVariantVeteransWorkannotation systembiobankcell typecohortcomorbiditydisorder riskdiverse datafunctional genomicsgene environment interactiongenetic informationgenetic variantgenome sequencinggenome wide association studygenome-widegenomic datahealth care availabilityhealth care service utilizationhigh riskimprovedinnovationinsightpersonalized approachpolygenic risk scoreprecision medicineprogramsprogression riskrisk stratificationrisk variantsocialsocial determinantssocial factorssocial health determinantsstatisticstooltranscription factorwhole genome
项目摘要
PROJECT SUMMARY/ABSTRACT
Glaucoma is the world’s leading cause of irreversible blindness and is projected to affect >110 million people
by 2040. Risk stratification is important in order to identify individuals at high risk of glaucoma, since early
detection and treatment can help decrease the risk of irreversible vision loss. Because glaucoma has a high
level of heritability, polygenic risk scores (PRS) have been developed to examine risk stratification based on
genetic variants. However, because genome-wide association studies have most commonly been performed in
European descent populations, PRS may not generalize well to non-European descent populations. This is a
major issue for glaucoma given that non-European descent populations carry a disproportionate burden of
glaucoma, including earlier age of onset, faster disease progression, and higher risk of vision loss.
The All of Us Research Program offers an opportunity to further improve PRS models for glaucoma and
enhance a precision medicine approach for this complex condition. First, the recent release of whole genome
sequencing data on the All of Us Researcher Workbench provides additional genomic data from a diverse
cohort of participants to add to the growing literature of genomic studies in glaucoma. We plan to develop a
wide array of PRS models that will be trained and tested on data from All of Us (Aim 1). Further, we will
leverage an innovative tool that annotates variants according to their regulatory activity in disease-specific cell
types (in this case, eye tissues) to improve the predictive accuracy of trans-ancestry PRS models (i.e., make
models trained on one population more widely generalizable to other populations) (Aim 2). Finally, because All
of Us includes detailed data regarding environmental factors such as clinical data, healthcare access and
utilization, and social determinants of health, it represents a unique opportunity to better understand gene-
environment interactions in glaucoma and further refine risk stratification by simultaneously analyzing a
multitude of data types (Aim 3).
This study aims to improve PRS for glaucoma by enhancing performance via the strategies outlined above.
Additionally, these aims may potentially uncover new risk variants and generate new insights regarding their
functional importance. These will represent important advancements in precision medicine in glaucoma,
particularly for diverse populations who have been traditionally underrepresented in biomedical research yet
are most severely affected by this blinding eye disease.
项目概要/摘要
青光眼是世界上导致不可逆转失明的主要原因,预计将影响超过 1.1 亿人
到 2040 年。为了识别青光眼高风险人群,风险分层非常重要,因为早期
检测和治疗有助于降低不可逆视力丧失的风险,因为青光眼的风险很高。
多基因风险评分 (PRS) 已开发用于检查基于遗传力水平的风险分层
然而,由于全基因组关联研究最常在
对于欧洲血统人群,PRS 可能无法很好地推广到非欧洲血统人群。
鉴于非欧洲血统人口承受着不成比例的负担,青光眼是青光眼的一个主要问题
青光眼,包括发病年龄较早、疾病进展较快以及视力丧失的风险较高。
All of Us 研究计划提供了进一步改进青光眼和 PRS 模型的机会
首先,最近发布了全基因组。
All of Us 研究人员工作台上的测序数据提供了来自不同领域的额外基因组数据
我们计划开发一个参与者队列,以补充不断增长的青光眼基因组研究文献。
一系列广泛的 PRS 模型将根据我们所有人的数据进行训练和测试(目标 1)。
利用一种创新工具,根据疾病特异性细胞中的调节活性来注释变体
类型(在本例中为眼组织),以提高跨祖先 PRS 模型的预测准确性(即,使
在一个群体上训练的模型可以更广泛地推广到其他群体)(目标 2)。
of Us 包括有关环境因素的详细数据,例如临床数据、医疗保健获取和
利用率和健康的社会决定因素,它代表了更好地了解基因的独特机会
通过同时分析青光眼的环境相互作用,并进一步细化风险分层
多种数据类型(目标 3)。
本研究旨在通过上述策略提高表现来改善青光眼的 PRS。
此外,这些目标可能会发现新的风险变体,并产生关于其风险的新见解。
这些将代表青光眼精准医学的重要进步,
特别是对于传统上在生物医学研究中代表性不足的不同人群
受这种致盲眼病的影响最为严重。
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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Sally Liu Baxter其他文献
Sally Liu Baxter的其他文献
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{{ truncateString('Sally Liu Baxter', 18)}}的其他基金
Bridge2AI: Salutogenesis Data Generation Project
Bridge2AI:Salutogenesis 数据生成项目
- 批准号:
10858583 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Bridge2AI: Salutogenesis Data Generation Project
Bridge2AI:Salutogenesis 数据生成项目
- 批准号:
10471118 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Short-Term Research training In Vision and Eye health (STRIVE)
视觉和眼睛健康短期研究培训 (STRIVE)
- 批准号:
10615857 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical Intervention
多模态人工智能预测青光眼进展和手术干预
- 批准号:
10677890 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Bridge2AI: Salutogenesis Data Generation Project
Bridge2AI:Salutogenesis 数据生成项目
- 批准号:
10885481 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Short-Term Research training In Vision and Eye health (STRIVE)
视觉和眼睛健康短期研究培训 (STRIVE)
- 批准号:
10409942 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical Intervention
多模态人工智能预测青光眼进展和手术干预
- 批准号:
10504041 - 财政年份:2022
- 资助金额:
$ 31.6万 - 项目类别:
Multi-modal Health Information Technology Innovations for Precision Management of Glaucoma
青光眼精准管理的多模式健康信息技术创新
- 批准号:
10018290 - 财政年份:2020
- 资助金额:
$ 31.6万 - 项目类别:
Multi-modal Health Information Technology Innovations for Precision Management of Glaucoma
青光眼精准管理的多模式健康信息技术创新
- 批准号:
10260459 - 财政年份:2020
- 资助金额:
$ 31.6万 - 项目类别:
Multi-modal Health Information Technology Innovations for Precision Management of Glaucoma
青光眼精准管理的多模式健康信息技术创新
- 批准号:
10437231 - 财政年份:2020
- 资助金额:
$ 31.6万 - 项目类别:
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