Center for Integrated Approached to Undiagnosed Diseases

未确诊疾病综合治疗中心

• 批准号: 10600194
• 负责人: Joseph Loscalzo
• 金额: $ 32.82万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-02 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10600194
• 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 Analytics; Development; Diagnosis; 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; Grant; Hospitals; Image; Immunophenotyping; Individual; Inpatients; Interdisciplinary Study; Laboratories; Lead; Massachusetts; Methods; Molecular; Mutation; Network-based; Occupational; Outpatients; Pathway interactions; Patients; Pediatric Hospitals; Phase; Phenotype; Physiological; Pregnancy; Proteomics; Protocols documentation; 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; gene expression variation; genetic analysis; genetic variant; genome sequencing; genomic data; improved; innovation; insight; interest; meetings; member; metabolomics; multiple omics; novel; proband; systematic review; tool; transcriptomics; translational scientist; whole genome

PROJECT SUMMARY 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. Using 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, has shown to be the most effective way to identify the pathways and mechanisms responsible for many undiagnosed diseases. We will continue our 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, 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. For probands accepted on or before June 30, 2022, this supplement will allow us to continue our 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.

项目摘要 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， 未确诊的疾病使用一种集成的、基于网络的系统生物学方法， 不仅遗传变异数据，而且基因表达、代谢组学、蛋白质组学和生物组学数据，沿着 仔细的深度表型分析，已被证明是最有效的方式来确定的途径和机制 导致许多未确诊的疾病。我们将继续我们的综合跨学科研究计划， 哈佛未诊断疾病网络临床站点（哈佛UDN-CS），涉及三个特定目标： 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来源的DNA序列，转录组学 数据和临床表型信息，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)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， 蛋白质组学和基因组学数据，沿着候选遗传变异进入全面的 相互作用组，从而识别与所涉及的网络邻近的疾病或疾病途径。 基因，可能有助于确定潜在的病理生物学模块相关的病因， 未确诊的疾病 对于在2022年6月30日或之前接受的先证者，本补充将使我们能够继续我们的工作， 满足这些具体目标，并与UDN密切合作，解决总体假设 协调中心（UDN-CC）和UDN中的其他临床研究中心，以便制定和实施 表型、环境和基因型的评估方案，最终将确定病因， 治疗未确诊的疾病。