Extending Genome-Phenome Analysis

扩展基因组-表型分析

• 批准号: 8927668
• 负责人: MICHAEL M SEGAL
• 金额: $ 40.66万
• 依托单位: SIMULCONSULT, INC.
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-27 至 2017-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8927668
• 关键词: Accounting; Affect; Award; Clinical; Code; Computer software; Copy Number Polymorphism; Cost Analysis; DNA; DNA analysis; Data; Databases; Diagnosis; Diagnostic; Disease; Extended Family; Family; Fathers; Foundations; Funding; Gene Abnormality; Genes; Genome; Genomics; Goals; Grant; Health; Human; Incidental Findings; Individual; Interview; Manuals; Marketing; Modeling; Molecular Abnormality; Mothers; Nature; Notification; Nuclear Family; Online Mendelian Inheritance In Man; Output; Parents; Patients; Persons; Pharmacogenetics; Phase; Phenotype; Physicians; Predisposition; Probability; Rare Diseases; Reading; Reporting; Siblings; Small Business Innovation Research Grant; Specific qualifier value; Speed; Structure; System; Systematized Nomenclature of Medicine; Terminology; Testing; Time; United States National Library of Medicine; Variant; Work; clinical Diagnosis; clinical care; clinical practice; cost; diagnostic accuracy; efficacy testing; exome; exome sequencing; family structure; gene discovery; genome analysis; genome sequencing; improved; phenome; proband; success; tool

DESCRIPTION (provided by applicant): The declining cost of whole exome sequencing (WES) is nearing the point at which the spread of WES into clinical practice will be limited largely by the cost of interpreting the results and comparing them to the patient's clinical findings. This project builds on our demonstrated capability to reduce this interpretation cost by pairing our diagnostic software, in wide use for clinical diagnosis, with automated genomic sequencing. The clinical diagnostic software compares patients to "phenotypes" of findings in known diseases, so the combination with genome analysis, developed under an SBIR Phase 1 grant, is referred to as automated genome-phenome analysis. This award-winning capability is valued because of its ability to analyze genomes in seconds, and its hypothesis-independent nature. Here we propose to advance the genome-phenome analysis as follows: Aim 1 is to generalize the analysis beyond the trio (affected individual plus parents) in order to support a wider variety of family structures. These include nuclear families with more than one sibling, families that extend beyond the nuclear family and unrelated affected individuals. These capabilities will be useful in both clinical diagnosis and discovery of new connections between genes and diseases. These capabilities will be added in a way that preserves the speed and hypothesis-independent nature of the analysis. Aim 2 is to detect copy number variation (CNV) using exomes and analyze that genomic data in the clinical context. Using WES for CNV analysis will lower the cost of diagnosis by reducing the need to order a microarray before exome analysis, and will facilitate the automated analysis of DNA deletions and duplications in clinical care. Aim 3 is to improve the core analysis by taking into account which genes were well-read but normal, information that is important in excluding other diagnoses. The analysis will also deal with situations of ambiguity over whether an affected individual is homozygous or heterozygous, and do so in a way that only adds possibilities for diagnosis but doesn't reduce possibilities considered by the original analysis. Aim 4 is to improve output by reporting on incidental findings and exporting information in ways that facilitate interactions with referring physicians and reporting of genome variants to public databases. The overall goal is to improve accuracy and reduce the time and cost of analysis, making WES more robust as a clinical tool, as well as a tool for gene discovery. Today, interpretation costs exceed reimbursement rates, and interviews with labs suggest that the major reason for high costs is the manual nature of the clinical correlation, which we automate. As the phenotype becomes known for a greater fraction of genetic abnormalities, the applicability of our automated genome-phenome analysis and the market for it will grow.

描述（由申请人提供）：全外显子组测序（WES）的成本不断下降，其在临床实践中的传播将在很大程度上受到解释结果并将其与患者临床发现进行比较的成本的限制。该项目建立在我们已证明的通过将广泛用于临床诊断的诊断软件与自动基因组测序相结合来降低解释成本的能力的基础上。该临床诊断软件将患者与已知疾病的“表型”进行比较，因此与 SBIR 第一阶段资助下开发的基因组分析相结合，被称为自动化基因组表型分析。这种屡获殊荣的功能因其在几秒钟内分析基因组的能力及其独立于假设的性质而受到重视。在这里，我们建议按如下方式推进基因组-表型组分析：目标 1 是将分析推广到三人组（受影响的个人加父母）之外，以支持更广泛的家庭结构。其中包括有一个以上兄弟姐妹的核心家庭、核心家庭以外的家庭以及无关的受影响个人。这些功能将有助于临床诊断和发现基因与疾病之间的新联系。这些功能将以保持分析速度和假设独立性的方式添加。目标 2 是使用外显子组检测拷贝数变异 (CNV)，并在临床背景下分析该基因组数据。使用 WES 进行 CNV 分析将减少在外显子组分析之前订购微阵列的需要，从而降低诊断成本，并将促进临床护理中 DNA 缺失和重复的自动分析。目标 3 是通过考虑哪些基因已被充分读取但正常，来改进核心分析，这些信息对于排除其他诊断很重要。该分析还将处理受影响个体是纯合子还是杂合子的模糊情况，并且这样做的方式只会增加诊断的可能性，但不会减少原始分析所考虑的可能性。目标 4 是通过报告偶然发现和导出信息来提高产出，以促进与转诊医生的互动以及向公共数据库报告基因组变异。总体目标是提高准确性并减少分析时间和成本，使 WES 作为临床工具以及基因发现工具更加强大。如今，解释成本超过了报销率，对实验室的采访表明，成本高的主要原因是临床相关性的手动性质，我们将其自动化。随着表型因更大比例的遗传异常而闻名，我们的自动化基因组-表型分析的适用性及其市场将会增长。