Functional genomic resource and integrative model of dopaminergic circuitry associated with psychiatric disease

与精神疾病相关的多巴胺能回路的功能基因组资源和整合模型

基本信息

批准号：
10400466
负责人：
Schahram Akbarian
金额：
$ 1.47万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-01 至 2024-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10400466
关键词：
3-Dimensional Administrative Supplement Adult Architecture Autopsy Award Bayesian Network Bipolar Disorder Brain Chromatin Clinical Trials Communities Complex DNA Data Data Set Depression and Suicide Diagnosis Dimensions Disease Drug Addiction Etiology Functional disorder Genes Genetic Genetic Diseases Genetic Risk Genetic Transcription Genetic Variation Genome Genomics Genotype Grant Greek Human Individual Information Networks Maps Mental disorders Methods Midbrain structure Modeling Molecular Conformation Moods National Institute of Mental Health Neurobiology Neuroglia Parents Pathology Pathway interactions Policies Psychoses Public Health Research Resources Sampling Schizophrenia Source Subgroup Substance abuse problem U-Series Cooperative Agreements United States United States National Institutes of Health Variant Veterans cell type clinical phenotype comorbidity cost data sharing disease phenotype dopaminergic neuron epigenome functional genomics genetic analysis genetic risk factor genome sequencing network models neuropsychiatry phenotypic data prediction algorithm predictive modeling psychiatric genomics reconstruction recurrent depression response three dimensional structure trait transcriptome whole genome

项目摘要

PROJECT SUMMARY: Supplement to Functional genomic resource and integrative model of dopaminergic circuitry associated with psychiatric disease In response to PA-20-272, “Administrative Supplements to Existing NIH Grants and Cooperative Agreements (Parent Admin Supp Clinical Trial Optional),” we propose to validate a small number of additional target genes identified by parent U01 (U01DA048279: Functional genomic resource and integrative model of dopaminergic circuitry associated with psychiatric disease). The parent award aims to construct transcriptome and epigenome (incl. 3D genome/chromosomal conformation) maps for midbrain dopaminergic neurons and for their surrounding nonneuronal cells, and to assess the relationship to known genetic risk factors for complex mental illness, including psychosis with substance abuse co-morbidity. We will apply integrative methods for functional analysis of genetic variation and networks, including but not limited to Bayesian network reconstruction and prediction algorithms of variant causality to identify key drivers of schizophrenia and bipolar disease pathology, and drug addiction co-morbidity. These methods will simultaneously integrate multiple different dimensions of data: DNA variation, RNA expression, chromatin accessibility, 3D structure of the genome, and known pathway and gene network information in the context of clinical phenotype data. The fundamental source of data for the project comes from the current studies on human midbrain functional omics, the CommonMind and PsychENCODE consortia (whole genome sequencing and cortical functional omics data), the Psychiatric Genomics Consortium, and the Million Veterans Project (genetic variation and disease phenotypes). The Million Veterans Project (MVP) has collected genotyping and phenotypic data from ~700,000 individuals, including a subgroup of 50,000 veterans diagnosed with SCZ and BD and a larger group of individuals diagnosed with other neuropsychiatric traits (recurrent depression, suicide and substance abuse). We will make our newly generated transcriptome and epigenome datasets from adult midbrain, as well as the network and predictive models, available to the research community in accordance with NIMH data sharing policies.

项目摘要：功能基因组资源和整合模型的补充与精神疾病相关的多巴胺能回路回应 PA-20-272，“现有 NIH 拨款和合作协议的行政补充（家长管理补充临床试验可选），”我们建议验证少量额外的目标基因由亲本 U01 鉴定（U01DA048279：功能基因组资源和多巴胺能整合模型与精神疾病相关的电路）。家长奖旨在构建转录组和表观基因组。（包括 3D 基因组/染色体构象）中脑多巴胺能神经元及其周围神经元的图谱非神经元细胞，并评估与复杂精神疾病的已知遗传风险因素的关系，包括与药物滥用共存的精神病。我们将应用综合方法进行功能分析。遗传变异和网络，包括但不限于贝叶斯网络重建和预测用于识别精神分裂症和双相情感障碍病理学和药物关键驱动因素的变异因果关系算法这些方法将同时整合多个不同维度的数据：DNA。变异、RNA 表达、染色质可及性、基因组的 3D 结构以及已知的途径和基因临床表型数据背景下的网络信息该项目的基本数据来源。来自当前人类中脑功能组学的研究，CommonMind 和 PsychENCODE 联盟（全基因组测序和皮质功能组学数据）、精神病基因组学联盟、和百万退伍军人项目（遗传变异和疾病表型）百万退伍军人项目（MVP）。已收集约 700,000 人的基因分型和表型数据，其中包括 50,000 人的亚组被诊断患有 SCZ 和 BD 的退伍军人以及更多被诊断患有其他神经精神疾病的人我们将制作新生成的转录组。和来自成人中脑的表观基因组数据集，以及网络和预测模型，可供研究界遵守 NIMH 数据共享政策。