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A standardized, evidence-based protocol to assess clinical actionability of genetic disorders associated with genomic variation
Hunter, J. E., Irving, S. A., Biesecker, L. G., Buchanan, A., Jensen, B., Lee, K., Martin, C. L., Milko, L., Muessig, K., Niehaus, A. D., O'Daniel, J., Piper, M. A., Ramos, E. M., Schully, S. D., Scott, A. F., Slavotinek, A., Sobreira, N., Strande, N., Weaver, M., ... Goddard, K. A. B. (2016). A standardized, evidence-based protocol to assess clinical actionability of genetic disorders associated with genomic variation. Genetics in Medicine, 18(12), 1258-1268. https://doi.org/10.1038/gim.2016.40
Purpose: Genome and exome sequencing can identify variants unrelated to the primary goal of sequencing. Detecting pathogenic variants associated with an increased risk of a medical disorder enables clinical interventions to improve future health outcomes in patients and their at-risk relatives. The Clinical Genome Resource, or ClinGen, aims to assess clinical actionability of genes and associated disorders as part of a larger effort to build a central resource of information regarding the clinical relevance of genomic variation for use in precision medicine and research.Methods: We developed a practical, standardized protocol to identify available evidence and generate qualitative summary reports of actionability for disorders and associated genes. We applied a semi-quantitative metric to score actionability.Results: We generated summary reports and actionability scores for the 56 genes and associated disorders recommended by the American College of Medical Genetics and Genomics for return as secondary findings from clinical genome-scale sequencing. We also describe the challenges that arose during the development of the protocol that highlight important issues in characterizing actionability across a range of disorders.Conclusion: The ClinGen framework for actionability assessment will assist research and clinical communities in making clear, efficient, and consistent determinations of actionability based on transparent criteria to guide analysis and reporting of findings from clinical genome-scale sequencing.