Methods to maximize the utility of common fund functional genomic data in multi-ethnic genetic studies
在多种族遗传研究中最大限度地利用共同基金功能基因组数据的方法
基本信息
- 批准号:10357165
- 负责人:
- 金额:$ 33.54万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-09-22 至 2023-09-21
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAlcohol consumptionApplied GeneticsCardiovascular DiseasesCatalogsComplexComputer softwareDataData SetDiseaseEpigenetic ProcessEuropeanFundingGene ExpressionGenerationsGenesGeneticGenetic ResearchGenetic studyGenomeGenotypeGenotype-Tissue Expression ProjectHeritabilityHeterogeneityHuman GeneticsIndividualInterventionJointsLeadLicensingLinkMalignant NeoplasmsMeta-AnalysisMethodologyMethodsModelingPhasePhenotypePopulationPopulation HeterogeneityPublic HealthResearchResearch MethodologyResourcesRespiration DisordersRisk FactorsRoleSamplingSeriesSmokingSmoking BehaviorTestingTimeTissuesUntranslated RNAVariantaddictionadvanced analyticsanalytical methodbasecausal variantcost effectivedisorder preventiondrinkingdrinking behaviorfunctional genomicsgenetic architecturegenetic variantgenome wide association studygenomic datahuman diseaseimprovedin silicoinnovationinterestlarge datasetsmethod developmentmodifiable riskmulti-ethnicmultiple datasetsnext generationnicotine usenovelopen sourcepredictive modelingsimulationstatisticstraittranscriptometranscriptomicsuser-friendlyweb portal
项目摘要
ABSTRACT
Smoking and drinking are major modifiable and heritable risk factors for a myriad of human diseases.
Elucidating the genetic basis for smoking and drinking addiction will be critical for public health. In the past few
years, the genetic studies of smoking and drinking addiction have made significant progress. With the help of
large datasets and advanced analytical methods, we have identified >400 associated loci in samples of European
ancestry. As a next step, we will expand our study to include samples of non-European populations, in order to
further empower discovery and elucidate the genetic architecture.
A majority of the identified GWAS loci are non-coding. A critical first step to understand their function is to
identify the target gene. Transcriptome-wide association study (TWAS) was proposed to link regulatory variants
to target genes. In its original form, TWAS integrates eQTL and GWAS data from the matched ancestry. As multi-
ethnic studies become more prevalent, it has been shown that direct integration of European eQTL with non-
European GWAS would lead to loss of power and the results may be difficult to interpret as well. A majority of
Common Funds functional genomic data (e.g., GTEx and 4DN) were primarily from European ancestry. It
remains unclear whether they remain useful in multi-ethnic studies and if so, how to effectively utilize them.
Here we propose a series of methodological innovations to combine GTEx data, epigenetic and 3D genomes data
and other non-European functional genomic data to improve the gene expression prediction accuracy across
tissue types and ancestries. For a given gene expression model, we will also propose methods to perform provably
optimal TWAS in multi-ethnic genetic studies. These proposed methods, if successful, will open doors to use
Common Funds data in the next generation genetic studies of complex traits in diverse populations. Compared
to extremely expensive data generation, these method development projects are cost effective and could be highly
impactful for maximizing the utility of Common Funds datasets.
摘要
吸烟和饮酒是人类多种疾病的主要可改变和可遗传的危险因素。
阐明吸烟和饮酒成瘾的遗传基础对公共卫生至关重要。过去几
近年来,吸烟和饮酒成瘾的遗传学研究取得了重大进展。的帮助下
大数据集和先进的分析方法,我们已经确定了超过400个相关的基因座在欧洲样本中,
祖先作为下一步,我们将扩大我们的研究,包括非欧洲人口的样本,以便
进一步授权发现和阐明遗传结构。
大多数鉴定的GWAS基因座是非编码的。了解它们的功能的关键第一步是
识别目标基因。全转录组关联研究(TWAS)被提议用于关联调节变体
以基因为目标。在其原始形式中,TWAS整合了来自匹配祖先的eQTL和GWAS数据。作为多-
种族研究变得越来越普遍,已经表明欧洲eQTL与非欧洲eQTL的直接整合,
欧洲GWAS将导致功率损失,结果也可能难以解释。大多数
共同基金功能基因组数据(例如,GTEx和4DN)主要来自欧洲血统。它
目前尚不清楚它们是否仍然对多族裔研究有用,如果有用,如何有效利用它们。
在这里,我们提出了一系列的方法创新,结合联合收割机GTEx数据,表观遗传和3D基因组数据
和其他非欧洲的功能基因组数据,以提高基因表达预测的准确性,
组织类型和祖先对于给定的基因表达模型,我们还将提出方法来执行可证明的
多种族遗传研究中的最佳TWAS。这些建议的方法,如果成功,将打开大门使用
共同基金的数据在下一代遗传研究的复杂性状在不同的人群。相比
到极其昂贵的数据生成,这些方法开发项目具有成本效益,
最大化共同基金数据集的效用。
项目成果
期刊论文数量(1)
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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Dajiang Liu其他文献
Dajiang Liu的其他文献
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{{ truncateString('Dajiang Liu', 18)}}的其他基金
Integrative genomic and geospatial analysis of insurance claim, biobank and GWAS summary statistics for complex traits
保险索赔的综合基因组和地理空间分析、生物库和复杂性状的 GWAS 汇总统计
- 批准号:
10688692 - 财政年份:2022
- 资助金额:
$ 33.54万 - 项目类别:
Methods to Identify, Validate & Interpret GWAS Loci in Multi-ethnic Meta-analysis
识别、验证方法
- 批准号:
10291183 - 财政年份:2021
- 资助金额:
$ 33.54万 - 项目类别:
Tools for integrative genomics and disease association study for the X chromosome
X 染色体综合基因组学和疾病关联研究的工具
- 批准号:
10224236 - 财政年份:2018
- 资助金额:
$ 33.54万 - 项目类别:
Methods to Unveil the Genetic Architecture for Nicotine Dependence via NGS data
通过 NGS 数据揭示尼古丁依赖性遗传结构的方法
- 批准号:
8954632 - 财政年份:2015
- 资助金额:
$ 33.54万 - 项目类别:
Methods to Unveil the Genetic Architecture for Nicotine Dependence via NGS data
通过 NGS 数据揭示尼古丁依赖性遗传结构的方法
- 批准号:
9145160 - 财政年份:2015
- 资助金额:
$ 33.54万 - 项目类别:
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