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: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10057769
• 关键词: Architecture; Biological; Biological Process; Biology; Bipolar Disorder; Brain; Brain imaging; Brain region; Clinical; Complex; Computer Models; Data; Data Set; Databases; Development; Diagnostic; Disease; Electrophysiology (science); Emotional; Epigenetic Process; Family; Future; Gene Expression; Genes; Genetic; Genetic Risk; Genetic Variation; Genetic study; Genotype; Goals; Health; Heritability; Human; Human Genome; Image; Individual; Lead; Link; Major Depressive Disorder; Measures; Mediation; Mental disorders; Meta-Analysis; Methods; Modality; Modeling; Modification; Molecular; Morbidity - disease rate; Multimodal Imaging; Neurobiology; Pathway interactions; Performance; Phenotype; Population Heterogeneity; Post-Traumatic Stress Disorders; Process; Psychopathology; Research; Research Personnel; Resolution; Risk; Sampling; Schizophrenia; Signal Transduction; Specificity; Statistical Models; Structure; Syndrome; Testing; Therapeutic Intervention; Tissues; Translating; base; biobank; brain tissue; connectome; disorder risk; genetic association; genetic predictors; genetic variant; genome wide association study; genome-wide; human imaging; insight; mortality; multimodality; neuroimaging; neuropsychiatry; novel; novel diagnostics; novel strategies; predictive modeling; psychiatric genomics; psychogenetics; social; statistical and machine learning; statistics; targeted treatment; trait; transcriptome; transcriptomics

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.

项目摘要/摘要 精神障碍是一种复杂的、令人衰弱的健康状况，但神经生物学原因和 这些疾病的病理生理机制还不是很清楚。大型生物的出现- 大规模全基因组关联研究(GWAS)使得能够识别重要的、可靠的基因 与精神障碍有关。然而，将GWAS基因座转换为特定的因果驱动因素一直是困难的 变异体/基因，以提取机械洞察力，以确定治疗干预的可操作目标。 神经生物学中间表型(NBIP)对于了解大脑的结构和 精神病理风险升高的功能相关性，尽管潜在的过程和分子 观察到的NBIP的机制是难以捉摸的。基于基因的归罪的最新进展现在使人们能够 从全基因组的基因数据中推断中间表型受基因调控的部分。我们的研究 团队已经成功地使用了跨精神障碍的大脑特定转录归因方法来 识别新的风险基因和途径。 在这项建议中，我们寻求提高神经成像遗传学和神经成像遗传学之间联系的生物学分辨率。 精神病学遗传学--创建基于大脑特异性的多模式神经成像新的多基因模型 基因表达，可应用于精神病学广泛性失调症。在目标1中，我们将生成大脑转录 多模式神经成像的预测模型，并在独立的数据集中复制。在目标2中，我们将 进行成像转录组范围的关联研究(ITHAS)以确定神经成像与 精神障碍在大脑特定的基因水平上，并区分因果关系。我们的综合分析将 增强我们对NBIP和精神障碍风险的理解；因此，它们将提供机械的见解， 可推动识别新的诊断、跨诊断和治疗方法。