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Article| Volume 24, ISSUE 8, P1732-1742, August 2022

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The Gene Curation Coalition: A global effort to harmonize gene–disease evidence resources

      ABSTRACT

      Purpose

      Several groups and resources provide information that pertains to the validity of gene–disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed.

      Methods

      The GenCC drafted harmonized definitions for differing levels of gene–disease validity on the basis of existing resources, and performed a modified Delphi survey with 3 rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene–disease validity assertions from its members.

      Results

      On the basis of 241 survey responses from the genetics community, a consensus term set was chosen for grading gene–disease validity and database submissions. As of December 2021, the database contained 15,241 gene–disease assertions on 4569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene–disease validity ranged from 5.3% to 13.4%.

      Conclusion

      Terminology standardization, sharing of gene–disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

      Keywords

      GenePod

      May 27, 2022

      June 2022: Harmonizing gene–disease evidence resources globally

      As more and more genes are implicated in disease, one of the challenges in implementing genomics in medical practice has been the lack of a single, standardized, and shared genomics database, for both labs and clinicians to access.

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      References

        • Richards S.
        • Aziz N.
        • Bale S.
        • et al.
        Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology.
        Genet Med. 2015; 17: 405-424https://doi.org/10.1038/gim.2015.30
        • Riggs E.R.
        • Andersen E.F.
        • Cherry A.M.
        • et al.
        Technical standards for the interpretation and reporting of constitutional copy-number variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics (ACMG) and the Clinical Genome Resource (ClinGen).
        Genet Med. 2020; 22 (Published correction appears in Genet Med. 2021;23(11):2230.): 245-257
        https://doi.org/10.1038/s41436-019-0686-8
        • Bean L.J.H.
        • Funke B.
        • Carlston C.M.
        • et al.
        Diagnostic gene sequencing panels: from design to report-a technical standard of the American College of Medical Genetics and Genomics (ACMG).
        Genet Med. 2020; 22: 453-461https://doi.org/10.1038/s41436-019-0666-z
        • Wright C.F.
        • Ware J.S.
        • Lucassen A.M.
        • et al.
        Genomic variant sharing: a position statement.
        Wellcome Open Res. 2019; 4: 22https://doi.org/10.12688/wellcomeopenres.15090.2
        • Azzariti D.R.
        • Riggs E.R.
        • Niehaus A.
        • et al.
        Points to consider for sharing variant-level information from clinical genetic testing with ClinVar.
        Cold Spring Harb Mol Case Stud. 2018; 4: a002345https://doi.org/10.1101/mcs.a002345
        • Harrison S.M.
        • Dolinsky J.S.
        • Knight Johnson A.E.
        • et al.
        Clinical laboratories collaborate to resolve differences in variant interpretations submitted to ClinVar.
        Genet Med. 2017; 19: 1096-1104https://doi.org/10.1038/gim.2017.14
        • Harrison S.M.
        • Dolinksy J.S.
        • Chen W.
        • et al.
        Scaling resolution of variant classification differences in ClinVar between 41 clinical laboratories through an outlier approach.
        Hum Mutat. 2018; 39: 1641-1649https://doi.org/10.1002/humu.23643
        • Riggs E.R.
        • Nelson T.
        • Merz A.
        • et al.
        Copy number variant discrepancy resolution using the ClinGen dosage sensitivity map results in updated clinical interpretations in ClinVar.
        Hum Mutat. 2018; 39: 1650-1659https://doi.org/10.1002/humu.23610
        • Mighton C.
        • Smith A.C.
        • Mayers J.
        • et al.
        Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository.
        J Med Genet. 2021; (jmedgenet-2021-107738.)
        https://doi.org/10.1136/jmedgenet-2021-107738
        • Landrum M.J.
        • Lee J.M.
        • Benson M.
        • et al.
        ClinVar: improving access to variant interpretations and supporting evidence.
        Nucleic Acids Res. 2018; 46: D1062-D1067https://doi.org/10.1093/nar/gkx1153
        • Stark Z.
        • Foulger R.E.
        • Williams E.
        • et al.
        Scaling national and international improvement in virtual gene panel curation via a collaborative approach to discordance resolution.
        Am J Hum Genet. 2021; 108: 1551-1557https://doi.org/10.1016/j.ajhg.2021.06.020
        • Strande N.T.
        • Riggs E.R.
        • Buchanan A.H.
        • et al.
        Evaluating the clinical validity of gene-disease associations: an evidence-based framework developed by the clinical genome resource.
        Am J Hum Genet. 2017; 100: 895-906https://doi.org/10.1016/j.ajhg.2017.04.015
        • Caudle K.E.
        • Dunnenberger H.M.
        • Freimuth R.R.
        • et al.
        Standardizing terms for clinical pharmacogenetic test results: consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC).
        Genet Med. 2017; 19: 215-223https://doi.org/10.1038/gim.2016.87
        • Abouelhoda M.
        • Faquih T.
        • El-Kalioby M.
        • Alkuraya F.S.
        Revisiting the morbid genome of Mendelian disorders.
        Genome Biol. 2016; 17: 235https://doi.org/10.1186/s13059-016-1102-1
        • Shamia A.
        • Shaheen R.
        • Sabbagh N.
        • Almoisheer A.
        • Halees A.
        • Alkuraya F.S.
        Revisiting disease genes based on whole-exome sequencing in consanguineous populations.
        Hum Genet. 2015; 134: 1029-1034https://doi.org/10.1007/s00439-015-1580-3
        • Aloraifi F.
        • McCartan D.
        • McDevitt T.
        • Green A.J.
        • Bracken A.
        • Geraghty J.
        Protein-truncating variants in moderate-risk breast cancer susceptibility genes: a meta-analysis of high-risk case-control screening studies.
        Cancer Genet. 2015; 208: 455-463https://doi.org/10.1016/j.cancergen.2015.06.001
        • Taylor A.
        • Brady A.F.
        • Frayling I.M.
        • et al.
        Consensus for genes to be included on cancer panel tests offered by UK genetics services: guidelines of the UK Cancer Genetics Group.
        J Med Genet. 2018; 55: 372-377https://doi.org/10.1136/jmedgenet-2017-105188
        • Rafnar T.
        • Gudbjartsson D.F.
        • Sulem P.
        • et al.
        Mutations in BRIP1 confer high risk of ovarian cancer.
        Nat Genet. 2011; 43: 1104-1107https://doi.org/10.1038/ng.955
        • Firth H.V.
        • Richards S.M.
        • Bevan A.P.
        • et al.
        DECIPHER: database of chromosomal imbalance and phenotype in humans using Ensembl resources.
        Am J Hum Genet. 2009; 84: 524-533https://doi.org/10.1016/j.ajhg.2009.03.010
        • Kent W.J.
        • Sugnet C.W.
        • Furey T.S.
        • et al.
        The human genome browser at UCSC.
        Genome Res. 2002; 12: 996-1006https://doi.org/10.1101/gr.229102
        • Köhler S.
        • Gargano M.
        • Matentzoglu N.
        • et al.
        The human phenotype ontology in 2021.
        Nucleic Acids Res. 2021; 49: D1207-D1217https://doi.org/10.1093/nar/gkaa1043