The Clinical Genome (ClinGen) Resource
ClinGen collects phenotypic and clinical information on variants across the genome, develop a consensus approach to identify clinically relevant genetic variants, and disseminate information about the variants to researchers and clinicians. The resource will advance genomics in clinical care and improve our understanding of phenotypic and functional effects of genetic variants and their clinical value.
Medical and research centers are increasingly sequencing exomes or whole genomes of patients. However, identifying sequence variants relevant to disease is difficult. As a result, information on few genomic variants is used in clinical practice. One factor that limits the clinical use of variant information is the lack of an openly accessible knowledge base that captures genetic variants, their phenotypic and functional effects, and other clinical information
ClinGen investigators are developing standard approaches for sharing genomic and phenotypic data provided by clinicians, researchers, and patients through centralized databases, such as ClinVar, and are working to standardize the clinical annotation and interpretation of genomic variants. Working groups are implementing evidence-based expert consensus methods to curate the clinical validity and medical actionability of genes and variants. Experts in the areas of cardiovascular disease, pharmacogenomics, hereditary (germline) cancer, somatic cancer, and inborn errors of metabolism have been brought together to assist in these curation efforts. ClinGen also aims to develop machine-learning algorithms to improve the throughput of variant interpretation and to improve understanding of variation in diverse populations as it relates to interpreting genetic test results. Lastly, ClinGen will disseminate the collective knowledge and resources for unrestricted use in the community and for use in EHR ecosystems.
Goals of ClinGen
- Share genomic and phenotypic data through centralized databases for clinical and research use.
- Standardize clinical annotation and interpretation of variants.
- Improve understanding of variation in diverse populations.
- Develop machine-learning algorithms to improve the throughput of variant interpretation.
- Implement evidence-based expert consensus for curation of clinical validity.
- Assess the 'medical actionability' of genes and variants to support their use in clinical care systems
- Disseminate the collective knowledge/resources and ensure EHR interoperability.
The following groups are receiving grants:
- Heidi L. Rehm, Broad Institute; David H. Ledbetter and Christa L. Martin, Geisinger Health System;
This group is developing standard formats for gathering and depositing data into ClinVar. It will work with clinical laboratories and with specific gene databases to facilitate their submissions to ClinVar and to reduce discrepancies in variant classification. They have also created GenomeConnect, a patient registry, to help people share de-identified genetic and health information with researchers and connect them with other patients.
- Jonathan S. Berg, University of North Carolina Chapel Hill; Marc Williams, Geisinger Health System; Michael S. Watson, American College of Medical Genetics and Genomics; Katrina Goddard, Kaiser Permanente.
This group is defining categories of clinical relevance and medical actionability for genes and variants. They have organized clinical domain working groups with experts in hereditary (germline) cancer, somatic cancer, cardiovascular disease, inborn errors of metabolism, and pediatric neurology to focus on evaluating variants for clinical relevance.
- Carlos D. Bustamante, Stanford University and Sharon E. Plon, Baylor College of Medicine.
This group is working closely with the other grants to develop a robust curation interface to analyze the clinical validity of gene-disease associations and implement the ACMG-AMP guidelines for interpreting sequence variants. Additionally, the team is developing various software products to assist variant curation efforts, such as a Pathogenicity Calculator, which generates assertions automatically based on a set of evidence provided, and an Allele Registry to create and maintain a unique allele ID. Lastly, they are developing the Case Level Evidence Aggregation and Reporting Network (CLEARNET), a scalable resource for aggregating case-level data in the cloud for use in curation
The following individuals are part of the External Scientific Panel:
- Rex Chisholm, Northwestern University - Chair
- Debra Leonard, University of Vermont
- John Carpten, Translational Genomics Research Institute
- Holly Peay, Parent Project Muscular Dystrophy
- Peter Tarczy-Hornoch, University of Washington
- Richard Sharp, Cleveland Clinic
- Georgia L. Weisner, Vanderbilt University Medical Center
Identify those human genes that, when significantly altered,
|Clinical Domain||Jonathan Berg
|Enlist representatives from community-organized efforts to implement standardized protocols for gene or sequence variant specific annotations of genes related to the specific disease domain||Laura Milko
|Consent and Disclosures Recommendations Committee (CADRe)||
Explore the ethical, legal, and social (ELSI) issues relating to reporting the actionability of particular genes/variants
in the clinical care process
|Data Exchange||Larry Babb
|Provide consistent representation of the information housed in ClinGen resources and facilitate ClinGen GA4GH Driver Project||Danielle Azzariti|
|Foster community engagement in all aspects of the ClinGen project through education, outreach, and resource development||CLINGEN_EDUCATION@list.nih.gov|
|Gene Curation||Jonathan Berg
|Develop evidence-based methods for evaluating gene-disease associations to support gene curation activities across
the ClinGen project
|Genomic Variant||Christa Martin
|Develop variant classification and curation standards and facilitate the submission of sequence and structural variants to ClinVar||Danielle Azzariti
|Sequence Variant Interpretation||Leslie Biesecker
|Support the refinement and evolution of the ACMG/AMP Interpreting Sequence Variant Guidelines to develop quantitative approaches to variant interpretation||Danielle Azzariti|
|Steering Committee||Katrina Goddard||Provide oversight and guidance and make executive decisions to ensure ClinGen reaches its goals||CLINGEN_EXEC@list.nih.gov|
ClinGen and ClinVar Partnership
ClinVar and ClinGen, two NIH-based efforts, have formed a critical partnership to improve our knowledge of clinically relevant genomic variation. This partnership includes significant efforts in data sharing, data archiving, and collaborative curation to characterize and disseminate the clinical relevance of genomic variation.
Gelb BD, Cavé H, Dillon MW, Gripp KW, Lee JA, Mason-Suares H, Rauen KA, Williams B, Zenker M, Vincent LM8. RASopathy Expert Panel consensus methods for variant interpretation. Genetics in Medicine. March 2018. [PubMed]
Tavtigian SV, Greenblatt MS, Harrison SM, Nussbaum RL, Prabhu SA, Boucher KM, Biesecker LG. Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework. Genetics in Medicine. January 2018. [PubMed]
Kelly MA, Caleshu C, Morales A, Buchan J, Wolf Z, Harrison SM, Cook S, Dillon MW, Garcia J, Haverfield E, Jongbloed JDH, Macaya D, Manrai A, Orland K, Richard G, Spoonamore K, Thomas M, Thomson K, Vincent LM, Walsh R, Watkins H, Whiffin N, Ingles J, van Tintelen JP, Semsarian C, Ware JS, Hershberger R, Funke B. Adaptation and validation of the ACMG/AMP variant classification framework for MYH7-associated inherited cardiomyopathies: recommendations by ClinGen's Inherited Cardiomyopathy Expert Panel. Genetics in Medicine. March 2018. [PubMed]
- Program Analyst
- Division of Genome Sciences
- Scientific Program Analyst
- Division of Genome Sciences
Last updated: April 22, 2019