Center for Integrated Approached to Undiagnosed Diseases

未确诊疾病综合治疗中心

• 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
• 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

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。 而一些未确诊的疾病将代表新的罕见遗传综合征，单基因或寡基因 病因学和其他将反映已知疾病的罕见表现，许多可能是由于更多的 具有分析挑战性的多个遗传，环境和发育因素的组合。整个 外显子组和全基因组测序是确定遗传贡献的有力工具 未确诊的疾病;然而，这些方法本身不太可能阐明许多，如果不是大多数， 未确诊的疾病这一建议的核心统一假设是，一个综合的，基于网络的， 系统生物学方法不仅包括遗传变异数据，而且包括基因表达， 代谢组学、蛋白质组学和代谢组学数据，沿着仔细的深层次表型分析，将被证明是最重要的 这是一种有效的方法，可以确定导致许多未确诊疾病的途径和机制。到 解决基本假设，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网站（哈佛UDN-CS），涉及三个具体目标： 1)确定和临床表征-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表征; 2)基因组评估-我们将使用患者和家庭成员的DNA序列，转录组学， 数据（如可用）和临床表型信息，以确定潜在的因果DNA序列 变异、基因表达变异和潜在的致病途径紊乱;以及 3)基于网络的疾病诊断系统生物学方法--我们将整合其他组学数据， 包括代谢组学、蛋白质组学和代谢组学数据，沿着候选遗传变异， 综合相互作用组，从而确定网络中的疾病或疾病途径 与相关基因的接近程度，可能有助于识别与肿瘤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。 我们将努力实现这些具体目标，并在密切合作下解决总体假设 与UDN协调中心（UDN-CC）和UDN中的其他临床研究中心合作， 实施表型、环境和基因型的评估方案，最终确定 未确诊疾病的病因和治疗。