Integrating neuroimaging and brain gene expression for functional characterization of psychiatric GWAS
Integrating neuroimaging and brain gene expression for functional characterization of psychiatric GWAS
批准号:
10057769
负责人:
Nikolaos Daskalakis
金额:
$45.1万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-01 至 2023-08-31
关键词:
ArchitectureBiologicalBiological ProcessBiologyBipolar DisorderBrainBrain imagingBrain regionClinicalComplexComputer ModelsDataData SetDatabasesDevelopmentDiagnosticDiseaseElectrophysiology (science)EmotionalEpigenetic ProcessFamilyFutureGene ExpressionGenesGeneticGenetic RiskGenetic VariationGenetic studyGenotypeGoalsHealthHeritabilityHumanHuman GenomeImageIndividualLeadLinkMajor Depressive DisorderMeasuresMediationMental disordersMeta-AnalysisMethodsModalityModelingModificationMolecularMorbidity - disease rateMultimodal ImagingNeurobiologyPathway interactionsPerformancePhenotypePopulation HeterogeneityPost-Traumatic Stress DisordersProcessPsychopathologyResearchResearch PersonnelResolutionRiskSamplingSchizophreniaSignal TransductionSpecificityStatistical ModelsStructureSyndromeTestingTherapeutic InterventionTissuesTranslatingbasebiobankbrain tissueconnectomedisorder riskgenetic associationgenetic predictorsgenetic variantgenome wide association studygenome-widehuman imaginginsightmortalitymultimodalityneuroimagingneuropsychiatrynovelnovel diagnosticsnovel strategiespredictive modelingpsychiatric genomicspsychogeneticssocialstatistical and machine learningstatisticstargeted treatmenttraittranscriptometranscriptomics
中文摘要
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英文摘要
PROJECT SUMMARY/ABSTRACT
Mental disorders are complex, debilitating health conditions, yet the neurobiological causes and
pathophysiological mechanisms underlying these disorders are not well understood. The emergence of large-
scale genome-wide association studies (GWAS) has enabled identification of significant, reliable genetic
associations to mental disorders. However, it has been difficult to translate GWAS loci into specific causal driver
variants/genes to extract mechanistic insights for identifying actionable targets for therapeutic interventions.
Neurobiological intermediate phenotypes (NBIPs) are invaluable in understanding the brain’s structural and
functional correlates of elevated risk of psychopathology, although the underlying processes and molecular
mechanisms for observed NBIPs are elusive. Recent advances in genetic-based imputation now allow one to
infer genetically-regulated portions of intermediate phenotypes from genome-wide genotype data. Our research
team has successfully employed brain-specific transcriptomic imputation approaches across mental disorders to
identify novel genes and pathways of risk.
In this proposal, we seek to increase the biological resolution of the link between neuroimaging genetics and
psychiatric genetics by creating novel polygenic models of multimodal neuroimaging based on brain-specific
gene expression that can be applied to psychiatric GWAS. In Aim 1, we will generate brain transcriptomic
predictive models of multimodal neuroimaging and replicate them in independent datasets. In Aim 2, we will
conduct Imaging Transcriptome-wide Association Studies (ITWAS) to identify neuroimaging associations with
mental disorders at a brain-specific gene-level and distinguish the causal ones. Our integrative analyses will
enhance our understanding of NBIPs and mental disorder risk; thus, they will provide mechanistic insights that
may drive identification of novel diagnostic, trans-diagnostic and treatment approaches.
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