Center for Integrated Approaches to Undiagnosed Diseases

描述(申请人提供)：未诊断的疾病可能由遗传、环境和发育因素决定。虽然一些未诊断的疾病将代表具有单基因或少基因病因的新的罕见遗传综合征，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造成的。全外显子组和全基因组测序是确定未诊断疾病的遗传因素的有力工具；然而，仅靠这些方法不太可能阐明许多未诊断疾病的基础，如果不是大多数的话。因此，这一建议的中心统一假设是，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、蛋白质组和暴露组数据，以及仔细的深层表型分析，将被证明是识别许多未诊断疾病的途径和机制的最有效方法。为了解决潜在的假设，我们建议为哈佛未诊断疾病计划临床站点(哈佛UDP-CS)建立一个综合的跨学科研究计划，涉及三个具体目标：1)确定和临床特征-我们将执行 我们将利用患者和家庭成员衍生的DNA序列、转录本数据(如果有)和临床表型信息来确定潜在的原因DNA序列变异、基因表达变异和潜在的导致途径错乱；以及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、蛋白质组和暴露组数据，连同候选基因变体整合到全面的交互组中，从而在相关基因附近发现疾病或疾病途径，这些基因可能有助于确定与未诊断的疾病的病因学相关的潜在病理生物学模块。我们将努力实现这些具体目标，并与协调中心和UDN中的其他临床地点密切合作，解决总体假设，以便开发和实施表型、环境和基因的评估方案，最终确定未诊断疾病的病因和治疗。

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.