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Strande NT, Riggs ER, Buchanan AH, 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(6):895-906doi: 10.1016/j.ajhg.2017.04.015.
Strande, N. T., Riggs, E. R., Buchanan, A. H., Ceyhan-Birsoy, O., DiStefano, M., Dwight, S. S., Goldstein, J., Ghosh, R., Seifert, B. A., Sneddon, T. P., Wright, M. W., Milko, L. V., Cherry, J. M., Giovanni, M. A., Murray, M. F., O'Daniel, J. M., Ramos, E. M., Santani, A. B., Scott, A. F., Plon, S. E., Rehm, H. L., Martin, C. L., & Berg, J. S. (2017). Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource. American journal of human genetics, 100(6), 895-906. https://doi.org/10.1016/j.ajhg.2017.04.015
Strande, Natasha T, et al. "Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource." American journal of human genetics vol. 100,6 (2017): 895-906. doi: https://doi.org/10.1016/j.ajhg.2017.04.015
Strande NT, Riggs ER, Buchanan AH, Ceyhan-Birsoy O, DiStefano M, Dwight SS, Goldstein J, Ghosh R, Seifert BA, Sneddon TP, Wright MW, Milko LV, Cherry JM, Giovanni MA, Murray MF, O'Daniel JM, Ramos EM, Santani AB, Scott AF, Plon SE, Rehm HL, Martin CL, Berg JS. Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource. Am J Hum Genet. 2017 Jun 01;100(6):895-906. doi: 10.1016/j.ajhg.2017.04.015. Epub 2017 May 25. PMID: 28552198; PMCID: PMC5473734.
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Am J Hum Genet. 2017 Jun 01;100(6):895-906. doi: 10.1016/j.ajhg.2017.04.015. Epub 2017 May 25.

Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource.

American journal of human genetics

Natasha T Strande, Erin Rooney Riggs, Adam H Buchanan, Ozge Ceyhan-Birsoy, Marina DiStefano, Selina S Dwight, Jenny Goldstein, Rajarshi Ghosh, Bryce A Seifert, Tam P Sneddon, Matt W Wright, Laura V Milko, J Michael Cherry, Monica A Giovanni, Michael F Murray, Julianne M O'Daniel, Erin M Ramos, Avni B Santani, Alan F Scott, Sharon E Plon, Heidi L Rehm, Christa L Martin, Jonathan S Berg

Affiliations

  1. Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
  2. Autism & Developmental Medicine Institute, Geisinger Health System, Danville, PA 17837, USA.
  3. Genomic Medicine Institute, Geisinger Health System, Danville, PA 17822, USA.
  4. Laboratory for Molecular Medicine, Partners Personalized Medicine, Boston, MA 02139, USA; The Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Harvard Medical School, Boston, MA 02115, USA; Department of Pathology, Brigham & Women's Hospital, Boston, MA 02115, USA.
  5. Laboratory for Molecular Medicine, Partners Personalized Medicine, Boston, MA 02139, USA.
  6. Department of Genetics, Stanford University, Stanford, CA 94305, USA.
  7. Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA.
  8. National Human Genome Research Institute, NIH, Bethesda, MD 20892, USA.
  9. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Division of Genomic Diagnostics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
  10. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
  11. Autism & Developmental Medicine Institute, Geisinger Health System, Danville, PA 17837, USA; Genomic Medicine Institute, Geisinger Health System, Danville, PA 17822, USA. Electronic address: [email protected].
  12. Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA. Electronic address: [email protected].

PMID: 28552198 PMCID: PMC5473734 DOI: 10.1016/j.ajhg.2017.04.015

Abstract

With advances in genomic sequencing technology, the number of reported gene-disease relationships has rapidly expanded. However, the evidence supporting these claims varies widely, confounding accurate evaluation of genomic variation in a clinical setting. Despite the critical need to differentiate clinically valid relationships from less well-substantiated relationships, standard guidelines for such evaluation do not currently exist. The NIH-funded Clinical Genome Resource (ClinGen) has developed a framework to define and evaluate the clinical validity of gene-disease pairs across a variety of Mendelian disorders. In this manuscript we describe a proposed framework to evaluate relevant genetic and experimental evidence supporting or contradicting a gene-disease relationship and the subsequent validation of this framework using a set of representative gene-disease pairs. The framework provides a semiquantitative measurement for the strength of evidence of a gene-disease relationship that correlates to a qualitative classification: "Definitive," "Strong," "Moderate," "Limited," "No Reported Evidence," or "Conflicting Evidence." Within the ClinGen structure, classifications derived with this framework are reviewed and confirmed or adjusted based on clinical expertise of appropriate disease experts. Detailed guidance for utilizing this framework and access to the curation interface is available on our website. This evidence-based, systematic method to assess the strength of gene-disease relationships will facilitate more knowledgeable utilization of genomic variants in clinical and research settings.

Copyright © 2017 American Society of Human Genetics. All rights reserved.

Keywords: ClinGen/Clinical Genome Resource; Mendelian disorders; biocuration; clinical validity; evidence framework; gene-disease association; genetic testing

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