Gene Expression Regulation in Brains of East Asian, African, and European Descent Explains Schizophrenia GWAS in Diverse Populations.
东亚、非洲和欧洲血统大脑中的基因表达调控解释了不同人群中的精神分裂症 GWAS。
基本信息
- 批准号:10382057
- 负责人:
- 金额:$ 78.64万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-03-25 至 2027-01-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAffectAfricanAfrican ancestryAlgorithmsAutopsyBiologicalBiologyBrainBrain MappingChinaChineseCollectionCopy Number PolymorphismDataData SetDiagnosisDiseaseEast AsianEuropeanFoundationsGene ExpressionGene Expression RegulationGene FrequencyGenesGeneticGenetic RiskGenetic TranscriptionGenetic studyGenotypeHeritabilityHumanIndividualLearningLinkage DisequilibriumMapsMediator of activation proteinMendelian randomizationMental disordersMethodsMutationOntologyPathway interactionsPatientsPopulationPopulation AnalysisPopulation HeterogeneityPopulation StudyPrecision therapeuticsProtein IsoformsQuantitative Trait LociRNA SplicingRegulatory ElementReportingResourcesRestSamplingSchizophreniaSex BiasSignal TransductionSingle Nucleotide PolymorphismSpecificitySpliced GenesStructureTestingTissuesUniversitiesUrsidae FamilyVariantbasebrain cellbrain tissuecausal variantcell typedifferential expressiondisorder riskdiverse dataepigenomicsfrontal lobegene functiongenetic architecturegenetic associationgenome wide association studygenomic locushealth disparityhealth disparity populationsimprovedinsightnovelprecision medicinepreservationpsychogeneticsrisk variantschizophrenia risktranscriptometranscriptomics
项目摘要
Abstract
Psychiatric geneticists have discovered hundreds of common single nucleotide polymorphisms (SNPs)
associated with schizophrenia (SCZ) through genome-wide association studies (GWAS). Brain expression
quantitative trait loci (eQTL) can successfully explain some of those genetic associations. Differences in genetic
association between disparate ancestral populations are often reported, however, it is not known whether such
population differences originate from different underlying risk genes or from different allele frequencies and linkage
disequilibrium of the same risk genes. Our central hypothesis is that genetic regulation of gene expression
within brains, as represented by eQTL, can explain the disease GWAS signals. Population structure
influences eQTL as it influences GWAS. The major assumption is that the biological foundation of GWAS and
eQTL is the S-E-D relationship, short for SNP-Gene Expression-Disorder. Functional interpretation of GWAS signals
relies on the discovery of S-E-D relationships. Due to a lack of brain transcriptome data from populations of non-
European descent, interpreting SCZ GWAS results for variants uncommon in other populations presents a
significant challenge. To discover the causes of these population differences, we will develop a transcriptome
dataset of a new brain collection from East Asians (EA, N = 578) combined with samples from the existing
PsychENCODE project (EA, N = 18). We will also use data of individuals of African ancestry (AFR, N = 411) from
the PsychENCODE projects. Along with data from those of European descent (EU), which dominates the
PsychENCODE (N =1,321) projects, we will have brain transcription data of three major populations in the world.
Our specific aims include: 1) to relate SNPs to gene expression (the S-E portion of the S-E-D networks), we will
develop and compare eQTL and coexpression networks of postmortem brains from three populations, EA, AFR and
EU; 2) to connect SNP-expression to SCZ GWAS signals (the S-E-D aspect), we will use brain eQTL data to
explain SCZ GWAS of EA, EU and AFR populations and to identify SCZ risk loci that also serve as regulators of
brain gene expression; 3) to develop a novel cross-population predixcan algorithm that can infer genetically
regulated gene expression, and identify those differentially expressed in patients. The algorithm will be used
to re-analyze existing PGC SCZ data, and use Vanderbilt University data to replicate the findings. This study will
improve the understanding of the genetic contribution of population diversity to SCZ risk. It is critical for developing
more precise diagnoses and treatments for the benefit of diverse populations, for addressing health disparity.
摘要
精神病学遗传学家已经发现了数百种常见的单核苷酸多态性(SNP)
通过全基因组关联研究(GWAS)发现与精神分裂症(SCZ)相关。脑表达
数量性状基因座(eQTL)可以成功地解释其中的一些遗传关联。基因差异
不同的祖先种群之间的关联经常被报道,然而,不知道这种关联是否
群体差异源于不同的潜在风险基因或不同的等位基因频率和连锁
相同风险基因的不平衡。我们的中心假设是基因表达的遗传调节
以eQTL为代表,可以解释疾病的GWAS信号。人口结构
影响eQTL就像影响GWAS一样。主要的假设是,GWAS的生物学基础和
eQTL是S-E-D关系,简称SNP-Gene Expression-Disorder。GWAS信号的功能解释
依赖于对S-E-D关系的发现。由于缺乏来自非哺乳动物群体的大脑转录组数据,
欧洲血统,解释SCZ GWAS结果在其他人群中不常见的变异,
重大挑战。为了发现这些群体差异的原因,我们将开发一个转录组,
来自东亚人(EA,N = 578)的新大脑集合的数据集与来自现有的
PsychENCODE项目(EA,N = 18)。我们还将使用非洲血统个体(AFR,N = 411)的数据,
PsychENCODE项目沿着来自欧洲血统(欧盟)的数据,欧洲血统占主导地位,
PsychENCODE(N = 1,321)项目,我们将拥有世界上三个主要人群的大脑转录数据。
我们的具体目标包括:1)将SNP与基因表达(S-E-D网络的S-E部分)联系起来,我们将
建立和比较eQTL和共表达网络的死后脑从三个群体,EA,AFR和
EU; 2)为了将SNP表达与SCZ GWAS信号(S-E-D方面)联系起来,我们将使用脑eQTL数据来
解释EA,EU和AFR人群的SCZ GWAS,并确定SCZ风险基因座,这些基因座也可作为
脑基因表达; 3)开发一种新的跨种群预扫描算法,可以从基因水平上推断
调节基因表达,并确定那些差异表达的患者。该算法将用于
重新分析现有的PGC SCZ数据,并使用范德比尔特大学的数据来复制这些发现。本研究将
提高对群体多样性对SCZ风险的遗传贡献的理解。这对发展中国家来说至关重要,
更精确的诊断和治疗,造福于不同的人群,解决健康差距。
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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Chunyu Liu其他文献
Chunyu Liu的其他文献
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{{ truncateString('Chunyu Liu', 18)}}的其他基金
Gene Expression Regulation in Brains of East Asian, African, and European Descent Explains Schizophrenia GWAS in Diverse Populations.
东亚、非洲和欧洲血统大脑中的基因表达调控解释了不同人群中的精神分裂症 GWAS。
- 批准号:
10597054 - 财政年份:2022
- 资助金额:
$ 78.64万 - 项目类别:
Trans-omic Analysis of Alcohol Consumption and its Relation to Cardiovascular Disease
酒精消耗及其与心血管疾病关系的跨组学分析
- 批准号:
10436830 - 财政年份:2021
- 资助金额:
$ 78.64万 - 项目类别:
Mitochondrial DNA, Nuclear DNA Methylation, and Cardiometabolic Disease Traits
线粒体 DNA、核 DNA 甲基化和心脏代谢疾病特征
- 批准号:
10646401 - 财政年份:2021
- 资助金额:
$ 78.64万 - 项目类别:
Mitochondrial DNA, Nuclear DNA Methylation, and Cardiometabolic Disease Traits
线粒体 DNA、核 DNA 甲基化和心脏代谢疾病特征
- 批准号:
10475148 - 财政年份:2021
- 资助金额:
$ 78.64万 - 项目类别:
Mitochondrial DNA, Nuclear DNA Methylation, and Cardiometabolic Disease Traits
线粒体 DNA、核 DNA 甲基化和心脏代谢疾病特征
- 批准号:
10297789 - 财政年份:2021
- 资助金额:
$ 78.64万 - 项目类别:
Trans-omic Analysis of Alcohol Consumption and its Relation to Cardiovascular Disease
酒精消耗及其与心血管疾病关系的跨组学分析
- 批准号:
10616528 - 财政年份:2021
- 资助金额:
$ 78.64万 - 项目类别:
Trans-omic Analysis of Alcohol Consumption and its Relation to Cardiovascular Disease
酒精消耗及其与心血管疾病关系的跨组学分析
- 批准号:
10209156 - 财政年份:2021
- 资助金额:
$ 78.64万 - 项目类别:
1/3 High-resolution mapping of cell type-specific DNA (hydroxy)methylation in the human brain during postnatal development and in psychiatric disease.
1/3 出生后发育和精神疾病期间人脑中细胞类型特异性 DNA(羟基)甲基化的高分辨率图谱。
- 批准号:
10576891 - 财政年份:2020
- 资助金额:
$ 78.64万 - 项目类别:
1/3 High-resolution mapping of cell type-specific DNA (hydroxy)methylation in the human brain during postnatal development and in psychiatric disease.
1/3 出生后发育和精神疾病期间人脑中细胞类型特异性 DNA(羟基)甲基化的高分辨率图谱。
- 批准号:
10360523 - 财政年份:2020
- 资助金额:
$ 78.64万 - 项目类别:
Mitochondrial DNA Copy Number and Sequence Variation in Relation to Age, Alzheimer's Disease Related Phenotypes and Age-related Metabolic Traits
线粒体 DNA 拷贝数和序列变异与年龄、阿尔茨海默病相关表型和年龄相关代谢特征的关系
- 批准号:
10212947 - 财政年份:2018
- 资助金额:
$ 78.64万 - 项目类别:
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