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、环境和发育因素在分析上更具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强大工具；然而，仅靠这些方法不太可能阐明许多（即使不是大多数）未诊断疾病的基础。因此，该提案的中心统一假设是，一种集成的、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，将被证明是识别导致许多未确诊疾病的途径和机制的最有效方法。为了解决潜在的假设，我们建议为哈佛未确诊疾病计划临床站点（哈佛 UDP-CS）建立一个综合的跨学科研究计划，该计划涉及三个具体目标：1）确定和临床特征 - 我们将执行 成人和儿童中选定的罕见和未确诊疾病状态的病例确定和表型特征； 2) 遗传评估——我们将使用患者和家庭成员的 DNA 序列、转录组数据（如果可用）和临床表型信息来识别潜在的致病 DNA 序列变异、基因表达变异和潜在的致病途径紊乱； 3）疾病诊断的网络方法——我们将整合其他组学数据，包括代谢组学、蛋白质组学和暴露组学数据，以及候选遗传变异到全面的相互作用组中，从而识别与所涉及基因接近的网络中的疾病或疾病途径，这可能有助于识别与未诊断疾病的病因学相关的潜在病理生物学模块。我们将与 UDN 协调中心和其他临床中心密切合作，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、环境和基因型评估方案，最终确定未确诊疾病的病因和治疗。