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Integrating neuroimaging and brain gene expression for functional characterization of psychiatric GWAS

Integrating neuroimaging and brain gene expression for functional characterization of psychiatric GWAS
整合神经影像学和脑基因表达以进行精神病学 GWAS 的功能表征
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

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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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