Center for Integrated Approaches to Undiagnosed Diseases

未确诊疾病综合治疗中心

• 批准号: 9251865
• 负责人: Joseph Loscalzo
• 金额: $ 228.29万
• 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 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9251865
• 关键词: Address; Adult; Binding; Bioinformatics; Biological Assay; Boston; Child; Clinical; Clinical Data; Clinical assessments; Collaborations; Communities; Complement; Copy Number Polymorphism; DNA; DNA Sequence; DNA Sequence Analysis; Data; Data Analyses; Data Collection; Development; Diagnosis; Diagnostic; Disease; Disease Pathway; 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; Individual; Interdisciplinary Study; Laboratories; Lead; Manuals; Massachusetts; Medical center; Methods; Molecular; Network-based; Occupational; Pathway interactions; Patient Recruitments; Patients; Pediatric Hospitals; Phenotype; Physiological; Procedures; Proteomics; Protocols documentation; Quality Control; Recruitment Activity; Research Infrastructure; Sampling; Site; Standardization; Syndrome; Systems Biology; Tissues; United States National Institutes of Health; Variant; Woman; Work; analytical method; base; clinical phenotype; clinical research site; data resource; disease classification; disease diagnosis; disease phenotype; exome; genetic variant; genome sequencing; improved; insight; interest; meetings; member; metabolomics; multiple omics; novel; operation; programs; public health relevance; quality assurance; response; tool; transcriptomics; translational scientist; whole genome

DESCRIPTION (provided by applicant): 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, therefore, 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 Program Clinical Site (Harvard UDP-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) genetic 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 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. We will work toward meeting these specific aims and addressing the overall hypothesis in close collaboration with the coordinating center 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.

描述（由申请人提供）：未确诊的疾病可能由遗传、环境和发育因素决定。虽然一些未确诊的疾病将代表具有单基因或寡基因病因的新型罕见遗传综合征，而其他疾病将反映已知疾病的罕见表现，但许多疾病可能是由多种遗传，环境和发育因素的更具分析挑战性的组合引起的。全外显子组和全基因组测序是确定未确诊疾病的遗传贡献的有力工具;然而，仅凭这些方法不太可能阐明许多（如果不是大多数）未确诊疾病的基础。因此，这一建议的中心统一假设是，一个集成的，基于网络的，系统生物学的方法，不仅包括遗传变异数据，而且还包括基因表达，代谢组学，蛋白质组学和基因组学数据，沿着仔细的深度表型，将被证明是最有效的方式来确定的途径和机制，负责许多未确诊的疾病。为了解决潜在的假设，我们建议为哈佛未诊断疾病项目临床站点（哈佛UDP-CS）建立一个综合的跨学科研究计划，涉及三个具体目标：1）确定和临床表征-我们将进行 病例确定和表型表征，用于成人和儿童中选定的罕见和未诊断疾病状态; 2）遗传评估-我们将使用患者和家庭成员来源的DNA序列、转录组学数据（当可用时）和临床表型信息，以鉴定潜在的致病DNA序列变异、基因表达变异和潜在的致病途径紊乱;和3）疾病诊断的网络方法-我们将把其他组学数据，包括代谢组学、蛋白质组学和代谢组学数据，连同候选遗传变异沿着整合到综合相互作用组中，从而识别与相关基因网络接近的疾病或疾病途径，这可能有助于识别潜在的病理生物学模块与未确诊疾病的病因有关。我们将与协调中心和UDN的其他临床研究中心密切合作，努力实现这些具体目标，并解决总体假设，以制定和实施表型，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。