Center for Integrated Approached to Undiagnosed Diseases

未确诊疾病综合治疗中心

基本信息

批准号：
9788516
负责人：
Joseph Loscalzo
金额：
$ 75万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
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：
2014-07-01 至 2022-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9788516
关键词：
Address Adult Bioinformatics Biological Assay Boston Child Clinical Clinical Data Clinical assessments Collaborations Communities Copy Number Polymorphism DNA Sequence DNA Sequence Analysis DNA Sequence Rearrangement Data Data Analyses Data Analytics Data Collection Development Diagnosis Disease Disease Pathway Drug Targeting Environment Environmental Exposure Environmental Risk Factor Etiology Evaluation Event Family member Gene Expression General Hospitals Genes Genetic Genetic Predisposition to Disease Genetic Variation Genomic approach Genomics Genotype Hospitals Image Immunophenotyping Individual Inpatients Interdisciplinary Study Laboratories Lead Massachusetts Methods Molecular Mutation Network-based Occupational Outpatients Pathway interactions Patient Recruitments Patients Pediatric Hospitals Phase Phenotype Physiological Pregnancy Proteomics Protocols documentation Quality Control Site Syndrome Systems Biology Tissues United States National Institutes of Health Untranslated RNA Variant Woman Work analytical method base causal variant clinical phenotype clinical research site crowdsourcing data resource disease diagnosis disease phenotype exome exome sequencing experience genetic analysis genetic variant genome sequencing genomic data improved innovation insight interest meetings member metabolomics multiple omics novel quality assurance systematic review tool transcriptomics translational scientist whole genome

项目摘要

Undiagnosed diseases are likely to be determined by genetic, environmental, and developmental factors. While some undiagnosed diseases will represent novel rare genetic syndromes with monogenic or oligogenic etiologies and others will reflect rare manifestations of known diseases, many are likely to result from a more analytically challenging combination of multiple genetic, environmental, and developmental factors. Whole exome and whole genome sequencing are powerful tools with which to ascertain the genetic contributions to undiagnosed diseases; however, these methods alone are unlikely to elucidate the basis for many, if not most, undiagnosed diseases. The central unifying hypothesis of this proposal is that an integrated, network-based, systems biology approach that incorporates not only genetic variation data, but also gene expression, metabolomic, proteomic, and exposomic data, along with careful deep phenotyping, will prove to be the most effective way to identify the pathways and mechanisms responsible for many undiagnosed diseases. To address the underlying hypothesis, we propose to establish an integrated interdisciplinary research plan for the Harvard Undiagnosed Disease Network Clinical Site (Harvard UDN-CS) that involves three Specific Aims: 1) Ascertainment and clinical characterization--we will perform case ascertainment and phenotypic characterization for selected rare and undiagnosed disease states in adults and children; 2) Genomic assessments--we will use patient and family member-derived DNA sequence, transcriptomic data (when available), and clinical phenotype information to identify potentially causal DNA sequence variants, gene expression variation, and potentially causative pathway derangements; and 3) Network-based systems biology approach to disease diagnosis--we will integrate other -omic data, including metabolomic, proteomic, and exposomic data, along with the candidate genetic variants into the comprehensive interactome, and thereby identify diseases or disease pathways in network proximity to the involved genes that may help identify potential pathobiological modules relevant to the etiology of the undiagnosed disease and potential drug targets that may modify pathophenotype. We will work toward meeting these specific aims and addressing the overall hypothesis in close collaboration with the UDN Coordinating Center (UDN-CC) and other clinical sites in the UDN in order to develop and implement assessment protocols of phenotype, environment, and genotype that will ultimately define the etiology and treatment of undiagnosed diseases.

未确诊的疾病可能是由遗传、环境和发育因素决定的。虽然一些未确诊的疾病将代表具有单基因或寡基因的新型罕见遗传综合征病因学和其他方面将反映已知疾病的罕见表现，许多可能是由更多原因引起的多种遗传、环境和发育因素的组合在分析上具有挑战性。所有的外显子组和全基因组测序是确定遗传贡献的强大工具未确诊的疾病；然而，仅这些方法不太可能阐明许多（如果不是大多数）的基础未确诊的疾病。该提案的中心统一假设是一个集成的、基于网络的、系统生物学方法不仅包含遗传变异数据，还包含基因表达，代谢组学、蛋白质组学和暴露组学数据，以及仔细的深层表型分析，将被证明是最重要的确定导致许多未确诊疾病的途径和机制的有效方法。到为了解决潜在的假设，我们建议建立一个综合的跨学科研究计划哈佛未确诊疾病网络临床站点（哈佛 UDN-CS）涉及三个具体目标： 1) 确定和临床特征——我们将进行病例确定和表型成人和儿童中选定的罕见和未诊断疾病状态的特征； 2) 基因组评估——我们将使用患者和家庭成员衍生的 DNA 序列、转录组数据（如果可用）和临床表型信息，以识别潜在的因果 DNA 序列变异、基因表达变异和潜在的致病途径紊乱；和 3）基于网络的系统生物学方法进行疾病诊断——我们将整合其他组学数据，包括代谢组学、蛋白质组学和暴露组学数据，以及候选遗传变异全面的相互作用组，从而识别网络中的疾病或疾病途径接近所涉及的基因，可能有助于识别与相关的潜在病理生物学模块未确诊疾病的病因学和可能改变病理表型的潜在药物靶点。我们将密切合作，努力实现这些具体目标并解决总体假设与 UDN 协调中心 (UDN-CC) 和 UDN 中的其他临床中心合作，以开发和实施表型、环境和基因型的评估协议，最终定义未确诊疾病的病因和治疗。