Neuropsychiatric Genome-Scale and RDOC Individualized Domains (N-GRID)

神经精神基因组规模和 RDOC 个体化域 (N-GRID)

基本信息

批准号：
9320861
负责人：
ISAAC S. KOHANE
金额：
$ 329.85万
依托单位：
HARVARD MEDICAL SCHOOL
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-19 至 2019-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9320861
关键词：
Agonist Alcohol or Other Drugs use Anxiety Disorders Biological Biological Markers Categories Cells Cellular Neurobiology Clinical Code Cognition Cognitive Comorbidity Complex Computer Simulation Consent Forms DNA Methylation DSM-IV Dependency Diagnosis Diagnostic Diagnostic tests Dimensions Disease Electronic Health Record Electrophysiology (science)Emerging Technologies Enrollment Epigenetic Process Equipment and supply inventories Fibroblasts Fruit Gene Expression Gene Expression Regulation Genes Genetic Transcription Genetic Variation Genomics Goals Gold Growth Healthcare Systems Histones Human Genome Human Genome Project Individual Informatics Investigation Laboratories Maps Measurement Measures Methodology Modeling Molecular Moods National Human Genome Research Institute National Institute of Mental Health Natural Language Processing Neurons Pathway interactions Patients Pharmaceutical Preparations Pharmacology Phase Phenotype Population Prediction of Response to Therapy Prosencephalon Psychiatry Psychotic Disorders Public Domains RNA RNA Editing RNA Splicing Research Domain Criteria Resolution Resources Risk Running Sampling Scheme Small RNA Standardization Statistical Models Stress Transcript Transcriptional Regulation Translations Untranslated RNA Update Visit Vocabulary base biobank cell type clinical investigation clinical phenotype clinically relevant design disorder risk experimental study functional genomics genome sequencing genome-wide high risk insight interest molecular phenotype neuropsychiatric disorder neuropsychiatric symptom neuropsychiatry neuroregulation novel outcome forecast patient population phenomenological models predicting response prognostic public health relevance relating to nervous system response technology development transcriptome transcriptome sequencing transcriptomics whole genome

项目摘要

DESCRIPTION (provided by applicant): As a result of the accelerated pace of development of technologies for characterizing the human genome, the rate-limiting step for large scale genomic investigation in clinical populations is now phenotyping. This is particularly the case for neuropsychiatric (NP) illness, where phenotypes are complex, biomarkers are lacking, and the primary cell types of interest are difficult to access directly. It has become apparent that both rare and common genetic variation contributes to disease risk and that this risk crosses traditional diagnostic boundaries in psychiatry. Taking advantage of a large, already-established NP biobank could dramatically accelerate progress toward understanding the cross-disorder mechanism of action of disease liability genes. This study proposes novel applications of emerging technologies in informatics and cellular neurobiology to eliminate this phenotyping bottleneck. In doing so, it will accelerate investigation of clinical and cellular phenotypes for understanding single and multilocus/polygenic associations. Aim 1: Adapt and expand one of the largest NP cellular biobanks by parsing electronic health records with gold-standard assessment of cognition and other RDoC phenotypes. Aim 2: Define the genome-wide multidimensional functional genomics (MFG) landscape in NP disease into which the transcriptomic signature (RNA-seq) of each induced neuron (IN) representing a clinically characterized individual is projected. The projection provides the mapping from molecular to phenotypic characterization and a directionality towards healthful/neurotypical states used in Aim 3. Aim 3: Develop a probabilistic model of gene expression dependencies that will predict which small molecular perturbations are likely to shift the IN transcriptomic signature in a healthful direction in the MFG and to then update the model based on measured perturbations in the MFG. Aim 4: Select patient samples to study in greater detail for epigenetic (DNA methylation, histone marks and RNA editing) and transcriptional control particularly with regard to activity dependent changes that have been implicated in many NP diseases. Aim 5: Here we assess just how well the clinical phenotypes are informed by the genome-wide characterizations and assess which is more robust.

描述（由申请人提供）：由于表征人类基因组的技术发展速度加快，临床人群大规模基因组研究的限速步骤现在是表型分析。对于神经精神 (NP) 疾病尤其如此，其表型复杂，缺乏生物标志物，并且难以直接获取感兴趣的原代细胞类型。很明显，罕见和常见的遗传变异都会导致疾病风险，并且这种风险跨越了精神病学的传统诊断界限。利用已经建立的大型 NP 生物库可以极大地加快了解疾病易感基因的跨疾病作用机制的进展。这项研究提出了信息学和细胞神经生物学中新兴技术的新应用，以消除这种表型分析瓶颈。这样做将加速临床和细胞表型的研究，以了解单基因座和多基因座/多基因关联。目标 1：通过对认知和其他 RDoC 表型的金标准评估来解析电子健康记录，调整和扩展最大的 NP 细胞生物库之一。目标 2：定义 NP 疾病的全基因组多维功能基因组学 (MFG) 景观，其中代表临床特征个体的每个诱导神经元 (IN) 的转录组特征 (RNA-seq) 被投影到其中。该投影提供了从分子到表型特征的映射以及目标 3 中使用的健康/神经典型状态的方向性。目标 3：开发基因表达依赖性的概率模型，该模型将预测哪些小分子扰动可能会改变 IN 转录组特征MFG 中的健康方向，然后根据 MFG 中测量的扰动更新模型。目标 4：选择患者样本，更详细地研究表观遗传学（DNA 甲基化、组蛋白标记和 RNA 编辑）和转录控制，特别是与许多 NP 疾病有关的活动依赖性变化。目标 5：在这里，我们评估全基因组特征对临床表型的影响程度，并评估哪个更稳健。