CNV Atlas of Human Development

描述（申请人提供）：最近发现，拷贝数变异（CNVs），即小基因组片段的丢失或获得，在所有正常个体中很常见，在人类表型变异和疾病中起着重要作用，这对我们理解人类遗传变异产生了深远的影响。然而，我们预测哪些CNV具有生物学或健康意义的能力受到严重限制;从多个正常和患者人群中获得更全面和准确的CNV数据是一项紧迫的研究和公共卫生优先事项。用于高分辨率CNV评估的强大技术现已可用，并已进入临床诊断用途，以评估患有不明原因智力残疾，自闭症或多重出生缺陷的儿童（称为“分子核型”或细胞基因组阵列）。目前的多中心试验也在进行中，以确定这些技术用于产前诊断的有效性。在未来几年内，细胞基因组阵列很可能成为儿科和产前细胞遗传学分析的首选方法。临床细胞遗传学实验室目前正在进行的大量细胞基因组阵列测试提供了一个不寻常的和及时的机会，从患者人群中捕获大型数据集，以帮助我们了解临床人群与正常人群相比CNV的后果。该项目的总体目标是利用临床护理过程中产生的这一大型临床数据集，为人类发育障碍相关的基因发现创建研究资源，并为了解CNV的临床和公共卫生影响建立宝贵的临床资源。该项目将包括四个具体目标：1）从儿科和产前人群的临床阵列测试中收集非常大的标准化数据集。除了传统的完全知情同意模式外，我们还将使用一种新的“选择退出”同意机制，为临床研究中心和临床遗传学检测实验室的大型联盟开发方法，以收集CNV和临床数据并将其提交给中央公共数据库。2)为临床实验室标准化阵列设计和基因型（CNV）数据格式。我们与国际标准细胞基因组阵列（ISCA）联盟合作，正在制定阵列设计、分辨率、格式的标准，以及解释良性与致病性CNV的指南。3)制定标准化的临床（表型）数据。表型工作组将使用当前的国际建议为表型信息开发标准词汇表和数据词典。4)数据收集/储存库、管理和可视化工具开发。一个数据库管理员将监督软件桥梁和适配器的开发，以自动化数据去识别、重新格式化和转移到中央公共储存库（dbGaP、NCBI）。在向研究界和临床医生公开发布之前，将开发自动化和专家数据管理的方法。将与学术团体和商业供应商合作开发便于用户使用的数据可视化和分析工具。 公共卫生相关性：我们基因组中小区域的丢失或获得，拷贝数变异（CNVs），最近被认为是常见和罕见人类疾病的主要原因，具有巨大的潜在公共卫生影响。我们目前对CNVs的了解是有限的：有些是真正良性的，有些被认为是良性的，但可能在未来被证明与常见疾病有关，其他与疾病有关，可以为患者和家庭提供重要信息。为了更好地了解CNVs，我们提出了一种独特的策略，以获得高质量的，标准化的CNVs数据，这些数据与产前和儿科环境中常规临床护理过程中非常大的人群（数十万人）的临床信息相关。

DESCRIPTION (provided by applicant): The recent discovery that copy number variations (CNVs), the loss or gain of small genomic segments, is common in all normal individuals and plays a major role in human phenotypic variation and disease, has had a profound impact on our understanding of human genetic variation. However, our ability to predict which CNVs have biological or health significance is severely limited; the acquisition of more comprehensive and accurate CNV data from multiple normal and patient populations is an urgent research and public health priority. Powerful technologies for high-resolution CNV assessment are now available and have moved into clinical diagnostic use to evaluate children with unexplained intellectual disabilities, autism, or multiple birth defects (termed "molecular karyotypes" or cytogenomic arrays). Current multicenter trials are also underway to determine the efficacy of these technologies for prenatal diagnosis. It is very likely that cytogenomic arrays will become the method of choice for both pediatric and prenatal cytogenetic analysis within the next few years. The large number of cytogenomic array tests now being performed by clinical cytogenetics laboratories presents an unusual and timely opportunity to capture large datasets from patient populations to contribute to our understanding of the consequence of CNVs from clinical populations compared to normal populations. The overall goal of this project is to leverage this large clinical dataset generated in the course of clinical care to create a research resource for gene discovery related to human developmental disorders as well as to build an invaluable clinical resource for learning about the clinical and public health impact of CNVs. This project will encompass four specific aims: 1) Collection of very large standardized datasets from clinical array testing in pediatric and prenatal populations. Using a novel "opt-out" consent mechanism in addition to a traditional full informed consent model, we will develop methods for a large consortium of clinical sites and clinical genetics testing laboratories to collect and submit CNV and clinical data to a central, public data repository. 2) Standardize array design and genotype (CNV) data formats for clinical laboratories. In partnership with the International Standard Cytogenomic Array (ISCA) Consortium, we are developing standards for array design, resolution, format, and guidelines for interpretation of benign versus pathogenic CNVs. 3) Develop standardized clinical (phenotype) data. A Phenotype Workgroup will develop standard vocabularies and data dictionaries for phenotypic information using current international recommendations. 4) Data collection/repository, curation and visualization tool development. A database workgroup will oversee development of software bridges and adaptors to automate data de-identification, reformatting and transfer to a central public repository (dbGaP, NCBI). Methods for automated and expert data curation will be developed prior to public release for the research community as well as clinicians. User-friendly tools for data visualization and analysis will be developed in partnership with academic groups and commercial vendors. PUBLIC HEALTH RELEVANCE: The loss or gain of small regions in our genome, Copy Number Variations (CNVs), have recently been recognized as a major cause of both common and rare human diseases with enormous potential public health impact. Our current understanding of CNVs is limited: some are truly benign, some are thought to be benign but may in the future be shown to be associated with common diseases, and others are associated with disease and can provide important information for patients and families. To better understand CNVs, we propose a unique strategy to obtain high-quality, standardized data on CNVs linked to clinical information from very large populations (hundreds of thousands) during the course of routine clinical care in a prenatal and pediatric setting at minimal cost.