USIDNET: A resource for clinical immunologists

USIDNET：临床免疫学家的资源

• 批准号: 10410606
• 负责人: KATHLEEN E SULLIVAN
• 金额: $ 134.93万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-24 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10410606
• 关键词: Autoimmunity; Caring; Cell Line; ClinVar; Clinical; Collection; Committee Members; Communities; Community Outreach; Complex; Data; Data Aggregation; Data Analytics; Data Collection; Databases; Development; Diagnosis; Diagnostic; Disadvantaged; Education; Evolution; Faculty; Foundations; Funding; Funding Mechanisms; Future; Genes; Genetic; Genetic Databases; Genetic Diseases; Genotype; Goals; Hereditary Disease; Immune; Immunity; Immunologic Deficiency Syndromes; Immunologist; Immunology; Infection; Inflammation; Institutes; Institution; Institutional Review Boards; Knowledge; Laboratories; Literature; Logical Observation Identifiers Names and Codes; Medical Genetics; Medical center; Mentors; Modernization; Monoclonal Antibody R24; Natural History; Newsletter; Oncogenes; Online Mendelian Inheritance In Man; Outcome; Outcome Study; Outcomes Research; Participant; Patient Care; Patient-Focused Outcomes; Patients; Persons; Phenotype; Physicians; Positioning Attribute; Protocols documentation; Publications; Publishing; Quality of life; Rare Diseases; Registries; Research; Research Design; Research Personnel; Resources; Services; Site; Standardization; Structure; Surveys; Systematized Nomenclature of Medicine; Time; United States; Update; Validation; Variant; Vocational Guidance; Work; career; clinical decision-making; clinical phenotype; comorbidity; dashboard; data dissemination; data interoperability; data modeling; data registry; data standards; demographics; discrete data; dissemination strategy; experience; gene discovery; genetic information; genetic variant; human disease; improved; improved outcome; innovation; medical specialties; new technology; next generation; next generation sequencing; optimal treatments; patient health information; patient registry; phenotypic data; programs; rare genetic disorder; skills; success; treatment strategy; web site

ABSTRACT The United States Immunodeficiency Network (USIDNET) has been continuously funded as a resource for Clinical Immunologists since 1992, evolving from single diagnosis registries to a panel of research resources including a robust diverse patient registry with quality of life, laboratory, and clinical features; patient cell lines, and a variety of educational efforts. In 2017, the registry converted the data to SNOMED and LOINC terms, ushering in an era characterized by data standards and interoperability. The registry currently holds complex phenotype data on over 5000 patients with over 3000 discrete data fields. Genetic information is available on over 2000 patients. Under a new funding mechanism, USIDNET is poised to further enhance resources both incorporating and improving the state of genetic diagnostics for Inborn Errors of Immunity. Our central goal is to serve as a nexus of information on genotype and phenotype. The USIDNET registry will continue to serve a critical need by defining phenotypes and propelling improved outcomes research with enhanced longitudinal data. This evolution renders additional technical innovations possible in a manner that will serve community needs identified through discussion and a survey. This Program has six Aims which all derive from the central registry effort. The new registry will be anchored by a semi-automated data extraction from participating sites to maximize data standardization and longitudinal collection. Input of genetic data will be standardized and we will offer next generation sequencing to patients who otherwise cannot have sequencing, to improve the richness of genetic data in USIDNET and to nucleate a “matchmaking” effort. The six Aims are interwoven to support improved data and utilization. In Aim 1, we will improve the registry by developing a protocol for direct data extraction that can be shared across institutions and instituting a Single IRB to facilitate regulatory compliance. Aim 2 develops improved guidance for registry utilization, provides statistical support for end users, and spearheads studies of high impact, defined by the Steering Committee. Aim 3 proposes an innovative use of data to connect investigators who have similar patients through a specific matchmaking approach. In Aim 4, we will utilize USIDNET data to augment efforts to enrich immunology HPO terms and ClinGen entries. In Aim 5, we will galvanize successful dissemination efforts, develop a newsletter with structured features to improve clarity, and enhance material on our website. In Aim 6, we will formalize mentoring efforts to strengthen the research skills of the next generation and provide career mentoring. These resources will provide pivotal information for the Immunology community at a time when the wealth of new monogenic Inborn Errors of Immunity have made clinical decision making far more complex and uncertain. This new R24 builds on previous successes defining phenotypes in Inborn Errors of Immunity, improves data collection, and utilizes the data in new ways to support the community.

摘要 美国免疫缺陷网络（USIDNET）作为一种资源不断得到资助， 自1992年以来，临床免疫学家从单一诊断登记处发展到研究资源小组 包括具有生活质量、实验室和临床特征的稳健的多样化患者登记;患者细胞系， 以及各种各样的教育工作。2017年，注册中心将数据转换为SNOMED和LOINC术语， 开创了一个以数据标准和互操作性为特征的时代。注册处目前持有复杂的 超过5000名患者的表型数据，超过3000个离散数据字段。遗传信息可在 超过2000名患者。在新的筹资机制下，USIDNET准备进一步增加资源， 纳入和改善先天性免疫缺陷的遗传诊断状况。我们的中心目标是 作为基因型和表型信息的纽带。USIDNET注册处将继续为 通过定义表型和推动改进的结果研究， 数据这种演变使得更多的技术创新成为可能， 通过讨论和调查确定的需求。该计划有六个目标，都来自中央 注册工作。新的登记系统将通过从参与研究中心进行半自动数据提取来进行锚定 最大限度地实现数据标准化和纵向收集。基因数据的输入将标准化， 将为无法进行测序的患者提供下一代测序，以改善 丰富的遗传数据在USIDNET和核心的“配对”的努力。这六个目标相互交织， 支持改进的数据和利用率。在目标1中，我们将通过开发一个用于直接注册的协议来改进注册表。 数据提取可在各机构间共享，并建立单一IRB以促进监管 合规目标2为登记利用制定改进的指南，为结束 用户，并带头研究高影响，由指导委员会定义。目标3提出了一个 创新地使用数据，通过特定的配对将拥有相似患者的研究者联系起来 approach.在目标4中，我们将利用USIDNET数据来加强努力，以丰富免疫学HPO术语， ClinGen条目。在目标5中，我们将激励成功的传播工作， 结构化的功能，以提高清晰度，并加强我们网站上的材料。在目标6中，我们将正式 加强下一代的研究技能和提供职业指导的辅导工作。这些 资源将为免疫学界提供关键信息， 单基因先天性免疫缺陷使得临床决策更加复杂和不确定。 这种新的R24建立在先前成功定义先天性免疫缺陷表型的基础上， 收集，并以新的方式利用数据来支持社区。