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
项目成果
期刊论文数量(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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