(OVERALL) We propose here to continue our work to create the world?s best community resource for the curation and dissemination of knowledge on genetic variations relevant to clinical care through the development of the Clinical Genome (ClinGen) Resource. ClinGen?s goals can be summarized by answering questions related to the evidence that variation in a gene causes disease (gene validity), specific variants within a disease gene are associated with disease (variant classification) and whether there is evidence for specific clinical actions if such variants are found (actionability). As part of the three grants submitting U41 applications, our team will have a particular focus on implementation of ClinGen processes for gene and variant curation across non-classic Mendelian disorders including hereditary cancer, somatic variation in cancer, pharmacogenomics and complex inheritance including non-coding variation in common disease. We are also proposing to further enrich the analysis of these variants across populations by the introduction of the ever increasing sequence and genotyping datasets from diverse populations. We will also explore the complex issues around reporting of ancestry in clinical genomics particularly as alleles in different settings may have different disease impact. During the first phase of ClinGen funding the Stanford/Baylor informatics and computational biology teams have built a number of curation interfaces for gene, variant and actionability curation. In this application we plan to expand the suite of online resources that seamlessly aggregates, normalizes and presents disparate sources of evidence to curators. Our goal is to enable consistent curation and improve the clinical application of genomic data in medicine through this informatics infrastructure. We will provide training for the community in the use of these tools by facilitating online learning courses, support of the clinical domain working groups and creation of helpdesks. The clinicalgenome.org online public portal will provide the outcome of these analyses for the community to utilize for clinical interpretation and development of clinical practice guidelines that are based on genetic results.
We will continue to develop and expand the NIH supported Clinical Genome (ClinGen) Resource. The goal of ClinGen is to develop standards and the bioinformatic tools needed for characterization of the clinical impact of genomic variants. We will implement these standards and make the results publically available across the spectrum of genetic disorders.
|Iacocca, Michael A; Chora, Joana R; Carrié, Alain et al. (2018) ClinVar database of global familial hypercholesterolemia-associated DNA variants. Hum Mutat 39:1631-1640|
|Mester, Jessica L; Ghosh, Rajarshi; Pesaran, Tina et al. (2018) Gene-specific criteria for PTEN variant curation: Recommendations from the ClinGen PTEN Expert Panel. Hum Mutat 39:1581-1592|
|Dolman, Lena; Page, Angela; Babb, Lawrence et al. (2018) ClinGen advancing genomic data-sharing standards as a GA4GH driver project. Hum Mutat 39:1686-1689|
|Milko, Laura V; Funke, Birgit H; Hershberger, Ray E et al. (2018) Development of Clinical Domain Working Groups for the Clinical Genome Resource (ClinGen): lessons learned and plans for the future. Genet Med :|
|Madhavan, Subha; Ritter, Deborah; Micheel, Christine et al. (2018) ClinGen Cancer Somatic Working Group - standardizing and democratizing access to cancer molecular diagnostic data to drive translational research. Pac Symp Biocomput 23:247-258|
|Lee, Kristy; Krempely, Kate; Roberts, Maegan E et al. (2018) Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants. Hum Mutat 39:1553-1568|
|Ghosh, Rajarshi; Harrison, Steven M; Rehm, Heidi L et al. (2018) Updated recommendation for the benign stand-alone ACMG/AMP criterion. Hum Mutat 39:1525-1530|
|Ormond, Kelly E; Hallquist, Miranda L G; Buchanan, Adam H et al. (2018) Developing a conceptual, reproducible, rubric-based approach to consent and result disclosure for genetic testing by clinicians with minimal genetics background. Genet Med :|
|Popejoy, Alice B; Ritter, Deborah I; Crooks, Kristy et al. (2018) The clinical imperative for inclusivity: Race, ethnicity, and ancestry (REA) in genomics. Hum Mutat 39:1713-1720|
|Tavtigian, Sean V; Greenblatt, Marc S; Harrison, Steven M et al. (2018) Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework. Genet Med 20:1054-1060|
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