A phenomics-first resource for interpretation of variants

用于解释变异的表型组学优先资源

• 批准号: 10642958
• 负责人: MELISSA A HAENDEL
• 金额: $ 188.84万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-09 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10642958
• 关键词: Address; Adoption; Algorithms; Basic Science; Biology; Case Study; Characteristics; Clinical; Clinical Data; Communities; Complex; Data; Data Sources; Databases; Development; Diagnosis; Diagnostic; Disease; Disease model; Evaluation; Face; Fast Healthcare Interoperability Resources; Frequencies; Functional disorder; Genes; Genetic Diseases; Genome; Genomics; Genotype; Human; Human Genome; Information Resources; Journals; Knowledge; Link; Mainstreaming; Manuals; Medical Genetics; Methods; Modality; Modeling; Modernization; Ontology; Outcome; Patient Care; Patients; Phenotype; Process; Rare Diseases; Research; Research Personnel; Resources; Software Engineering; Source; Structure; System; Techniques; Technology; Terminology; Variant; Work; clinical care; clinically actionable; community partnership; computational platform; data integration; data modeling; data standards; database schema; disease diagnosis; disease phenotype; empowerment; gene function; genetic variant; genomic variation; heterogenous data; human disease; improved; interoperability; model organism; novel; patient registry; phenomics; phenotypic data; precision medicine; prototype; tool; variant of unknown significance

A Phenomics-First Resource (PFR) for interpretation of variants Genomics is key to precision medicine; however, despite the ease of sequencing, clinical interpretation is still thwarted because relevant data (disease, phenotype, and variant) is complex, heterogeneous, and disaggregated across sources. Moreover, this evidence is sometimes incomplete, conflicting, and erroneous. Consequently, clinicians face long lists of candidate diseases, genes, and countless variants of unknown significance. This situation will not improve without capturing and harmonizing the underlying phenotypic information; computability of this information is the bedrock for the emerging field of ​phenomics​. From basic science to clinical care, communities need structured ways to represent and exchange phenotypes and disease definitions. Addressing these fundamental phenomics needs makes it possible to computationally assess and reveal links between diseases and variants. We have previously shown how the addition of phenotypic information using the Human Phenotype Ontology (HPO) can improve the diagnostic yield for hard-to-diagnose patients, and HPO is therefore now a global standard for “deep phenotyping”. We have demonstrated the applicability of deep phenotyping in the evaluation of rare diseases which have overlapping mechanistic underpinnings with common/complex diseases as well as evolutionarily conserved mechanisms in model organisms. Having coordinated the community and prototyped the underlying computational platforms, we will now align both phenotype ontologies and clinical terminologies, enabling better comparison and inference of phenotypes for improved diagnostic efficacy. We propose to develop a Phenomics-First Resource (PFR). ​Specifically we will: 1. Create a community-driven framework of interoperable phenotype definitions across species​ (uPheno) 2. Harmonize human disease definitions with the ​MONDO​ disease alignment resource 3. Create a community-wide exchange standard for clinical and model-organism phenotypes (​Phenopackets​) 4. Develop an integrated phenomics platform ​to provide the research ​(e.g. BioLink) and clinical (​FHIR​) communities with programmatic access to phenomics ontologies, data, and algorithms The dynamic suite of interlinked technologies will together leverage community-developed knowledge in order to make variant interpretation more reliable, better provenanced, and more clinically actionable.

用于解释变异的表型学第一资源 (PFR) 基因组学是精准医学的关键；然而，尽管测序很容易，但临床解释仍然很困难。 由于相关数据（疾病、表型和变异）复杂、异质且不稳定，因此受到阻碍 此外，这些证据有时是不完整的、相互矛盾的和错误的。 经过测试，面临一长串候选疾病、基因和无数未知变体 如果不捕获和协调潜在的表型，这种情况就不会改善。 信息；这些信息的可计算性是新兴表型组学领域的基石。 从科学到临床护理，社区需要结构化的方式来表示和交换表型， 解决这些基本的表型组学需求使得计算成为可能。 我们之前已经展示了如何添加疾病和变异之间的联系。 使用人类表型本体 (HPO) 的表型信息可以提高诊断率 难以诊断的患者，因此 HPO 现在已成为“深度表型分析”的全球标准。 证明了深度表型分析在评估具有重叠的罕见疾病中的适用性 常见/复杂疾病的机制基础以及进化上保守的机制 协调了社区并制作了底层计算平台的原型， 我们现在将统一表型本体和临床术语，以便更好地进行比较和 我们建议开发表型优先的表型推断。 资源（PFR）​具体来说，我们将： 1. 创建一个社区驱动的跨物种可互操作表型定义框架（uPheno） 2. 将人类疾病定义与​MONDO​疾病对齐资源进行协调 3. 为临床和模型生物表型创建社区范围的交换标准 （​苯酚数据包​） 4. 开发一个综合表型组学平台以提供研究（例如 BioLink）和临床（FHIR） 能够以编程方式访问表型学本体、数据和算法的社区 相互关联的技术的动态套件将共同利用社区开发的知识，以便 使变异解释更可靠、更有依据、更具有临床可操作性。

项目成果

Response to Biesecker et al.

对 Biesecker 等人的回应

• DOI: 10.1016/j.ajhg.2021.07.004
• 发表时间: 2021-09-01
• 期刊: American journal of human genetics
• 影响因子: 9.8
• 作者: A. Hamosh;J. Amberger;Carol A. Bocchini;J. Bodurtha;C. Bult;C. Chute;G. Cutting;Harry C. Dietz;H. Firth;R. Gibbs;W. Grody;M. Haendel;J. Lupski;J. Posey;Peter N. Robinson;L. Schriml;A. F. Scott;Nara Sobreira;D. Valle;Nan Wu;S. Rasmussen
• 通讯作者: S. Rasmussen

The Medical Action Ontology: A Tool for Annotating and Analyzing Treatments and Clinical Management of Human Disease.

医疗行动本体论：注释和分析人类疾病治疗和临床管理的工具。

• 发表时间: 2023-07-13
• 作者: Carmody, Leigh C;Gargano, Michael A;Toro, Sabrina;Vasilevsky, Nicole A;Adam, Margaret P;Blau, Hannah;Chan, Lauren E;Gomez;Horvath, Rita;Kraus, Megan L;Ladewig, Markus S;Lewis;Lochmüller, Hanns;Matentzoglu, Nicolas A
• 通讯作者: Matentzoglu, Nicolas A

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease.

医疗行动本体论：用于注释和分析人类疾病的治疗和临床管理的工具。

• 发表时间: 2023-12-08
• 作者: Carmody, Leigh C;Gargano, Michael A;Toro, Sabrina;Vasilevsky, Nicole A;Adam, Margaret P;Blau, Hannah;Chan, Lauren E;Gomez;Horvath, Rita;Kraus, Megan L;Ladewig, Markus S;Lewis;Lochmüller, Hanns;Matentzoglu, Nicolas A
• 通讯作者: Matentzoglu, Nicolas A

MENDS-on-FHIR: Leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance.

MENDS-on-FHIR：利用 OMOP 通用数据模型和 FHIR 标准进行国家慢性病监测。

• 发表时间: 2023-11-22
• 作者: Essaid, Shahim;Andre, Jeff;Brooks, Ian M;Hohman, Katherine H;Hull, Madelyne;Jackson, Sandra L;Kahn, Michael G;Kraus, Emily M;Mandadi, Neha;Martinez, Amanda K;Mui, Joyce Y;Zambarano, Bob;Soares, Andrey
• 通讯作者: Soares, Andrey