Calypso: a web software system supporting team-based, longitudinal genomic diagnostic care

Calypso：支持基于团队的纵向基因组诊断护理的网络软件系统

• 批准号: 10559599
• 负责人: Gabor T Marth
• 金额: $ 90.81万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10559599
• 关键词: Address; Adopted; Bioinformatics; Caring; Clinic; Clinical; Collaborations; Communication; Communities; Complex; Computer software; Data; Data Set; Diagnosis; Diagnostic; Discipline; Disease; Ensure; Environment; Evaluation; Funding; Genes; Genetic; Genetic Diseases; Genome; Genomics; Genotype; Goals; Hand; Individual; Infrastructure; Intuition; Joints; Knowledge; Literature; Medical; Medicine; Modernization; Molecular; National Human Genome Research Institute; Neonatal Intensive Care Units; Pathogenicity; Pathologist; Patients; Periodicals; Phenotype; Physicians; Process; Reporting; Research; Resources; Secure; Site; Software Tools; Support System; System; Testing; Time; United States National Institutes of Health; Universities; Update; Utah; Variant; Visual; adjudication; clinical research site; clinically relevant; clinically significant; cloud based; cohort; computational pipelines; computer infrastructure; critically ill newborn; dashboard; data access; data infrastructure; design; diagnostic strategy; genetic counselor; genetic disorder diagnosis; genome sequencing; genomic data; implementation science; improved; insight; longitudinal analysis; member; molecular diagnostics; novel; phenotypic data; programs; rapid diagnosis; response; software development; software systems; support tools; tool; web based software; web-based tool; whole genome

PROJECT SUMMARY/ABSTRACT Some of the most challenging diagnostic cases involve patients who present with complex phenotypes that evolve over time and intersect multiple medical disciplines. The two primary clinical settings for diagnosing such patients are undiagnosed disease clinics and neonatal intensive care unit rapid genome sequencing programs. These clinics have adopted an approach where diagnostic analysis is based on comprehensive genomic sequencing data; and analysis is carried out by a large, collaborative clinical team. This team-based approach leverages the treating physician’s detailed understanding of the patient’s phenotype, the medical geneticist’s deep knowledge of genetic diseases, the bioinformatic analyst’s expertise in adjudicating a variant’s quality and predicted pathogenicity, as well as the diagnostic pathologist’s ability to synthesize all relevant information and reach a conclusion regarding a given variant’s clinical significance. Diagnostic analysis of patients in both of these environments is a long-term process that often continues for months or even years, until new phenotypes in the patient are observed or novel gene-disease associations are reported in the literature that provide the necessary insight for case solution. However, existing software tools typically only cater to the bioinformatician expert or the diagnostic molecular pathologist, but not the treating physician or the genetic counselor; focus on making a genetic diagnosis at a single timepoint, rather than following the patient over time during a lengthy diagnostic process, and are therefore unable to adequately support team-based, longitudinal genomic diagnostic care. Addressing this pressing need, here we propose to develop a comprehensive software system, Calypso, to address this pressing need. Calypso will support team-based diagnostics via intuitive and visual iobio web tools tailored for each team member’s specialized contribution to diagnostic analysis; and facilitate long-term genomic care by keeping patient genomic data up-to-date via a systematic variant re- annotation infrastructure. We will put Calypso into the hands of the clinical teams in our undiagnosed disease clinic and our neonatal intensive care unit, ideal testing grounds for evaluating our tool’s impact on long-term genome diagnostic care in the context of team-based medicine. We will also centrally deploy and evaluate our tool in NHGRI’s Undiagnosed Disease Network to help realize the collaborative diagnostic opportunities presented by a large, clinically focused research consortium.

项目总结/文摘