Identifying genetically driven gene dysregulation in Alzheimer's disease and related dementias using statistical data integration

使用统计数据整合识别阿尔茨海默病和相关痴呆症中遗传驱动的基因失调

• 批准号: 10659349
• 负责人: Georgios Voloudakis
• 金额: $ 67.08万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10659349
• 关键词: Alzheimer' s Disease; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Area; Awareness; Biological; Biological Assay; Biological Process; Brain; Brain Diseases; Brain region; Cell Nucleus; Cell Separation; Chromatin; Code; Complex; Data; Data Set; Dementia; Dementia with Lewy Bodies; Development; Disease; Drug Targeting; Epigenetic Process; Formulation; Frontotemporal Lobar Degenerations; Future; Gene Expression; Genes; Genetic; Genetic Variation; Genome; Genomic approach; Genomics; Genotype; Goals; Heritability; Human; Intervention; Lewy Body Dementia; Linkage Disequilibrium; Mediating; Meta-Analysis; Modeling; Molecular Profiling; Multiomic Data; Outcome; Pathway interactions; Positioning Attribute; Prefrontal Cortex; Proteome; Proteomics; Regulation; Research; Resources; Risk; Role; Schizophrenia; Sorting; Specificity; Therapeutic Intervention; Tissues; Training; Untranslated RNA; Variant; analytical method; biological heterogeneity; brain cell; brain tissue; causal variant; cell type; clinical heterogeneity; data integration; dementia risk; disorder risk; drug development; epigenetic profiling; epigenome; genome wide association study; genome-wide; histone modification; improved; multi-scale modeling; neuropsychiatric disorder; next generation; novel; novel strategies; online resource; psychopharmacologic; risk variant; statistics; trait; transcriptome; transcriptome sequencing; transcriptomic profiling; transcriptomics

PROJECT SUMMARY Alzheimer’s disease (AD) and related dementias (ADRD) are highly heritable, severe, and complex brain disorders. Molecular profiling efforts of the brain have enabled us to understand more about how common variants may be associated with disease risk via regulating gene expression. However, the status quo as it pertains to the use of multiomics data for gene-trait association, is limited to independent transcriptome- and proteome-wide association studies. Here, we propose to: (1) additionally leverage epigenetic datasets and (2) apply a data-driven correlation-aware meta-analytic approach to integrate a wide range of brain cell-type and area specific imputed transcriptomes, proteomes and epigenomes. Our preliminary data suggest that this will greatly increase the power to identify genetically driven gene dysregulation associated with these disorders while controlling for the correlation between different genomic features. First, we will impute brain cell-type (based on FANS/FACS-sorted and single-nucleus data) and brain area (PFC, ACC, EC, STG, IFG) specific transcriptomes, proteomes and epigenomes for AD, frontotemporal lobar degeneration, and dementia with Lewy bodies. Secondly, for each disease, we will perform a data-driven correlation-aware meta-analysis of these imputed genomic features to identify key genes. Lastly, we will develop an open resource that provides for the rapid dissemination and open access to analyses and outcomes. To our knowledge, the proposed approach will result in the largest multiscale modeling of genetically driven gene dysregulation in the brain, will identify novel genes associated with dementias and will enable similar studies in other brain disorders as well.

项目摘要 阿尔茨海默病（AD）和相关痴呆（ADRD）是高度遗传的、严重的和复杂的脑损害 紊乱大脑的分子分析工作使我们能够更多地了解 变异可能通过调节基因表达与疾病风险相关。然而，现状是， 涉及使用多组学数据进行基因-性状关联，仅限于独立的转录组， 蛋白质组关联研究。在这里，我们建议：（1）另外利用表观遗传数据集和（2） 应用数据驱动的相关性感知元分析方法来整合广泛的脑细胞类型， 区域特异性估算转录组、蛋白质组和表观基因组。我们的初步数据显示， 大大增加了识别与这些疾病相关的遗传驱动基因失调的能力， 控制不同基因组特征之间的相关性。 首先，我们将估算脑细胞类型（基于FANS/FACS分类和单核数据）和脑面积 (PFC、ACC、EC、STG、IFG）特异性转录组、蛋白质组和表观基因组， 变性和路易体痴呆其次，对于每种疾病，我们将进行数据驱动的 这些估算的基因组特征的相关性感知荟萃分析，以确定关键基因。最后，我们将开发 一个开放的资源，提供快速传播和开放访问的分析和结果。对我们 知识，所提出的方法将导致最大的多尺度建模的基因驱动的基因 大脑中的失调，将确定与痴呆症相关的新基因，并将使类似的研究， 其他的脑部疾病