Title |
A standardized, evidence-based protocol to assess clinical actionability of genetic disorders associated with genomic variation
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Published in |
Genetics in Medicine, April 2016
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DOI | 10.1038/gim.2016.40 |
Pubmed ID | |
Authors |
Jessica Ezzell Hunter, Stephanie A. Irving, Leslie G. Biesecker, Adam Buchanan, Brian Jensen, Kristy Lee, Christa Lese Martin, Laura Milko, Kristin Muessig, Annie D. Niehaus, Julianne O’Daniel, Margaret A. Piper, Erin M. Ramos, Sheri D. Schully, Alan F. Scott, Anne Slavotinek, Nara Sobreira, Natasha Strande, Meredith Weaver, Elizabeth M. Webber, Marc S. Williams, Jonathan S. Berg, James P. Evans, Katrina A.B. Goddard |
Abstract |
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. 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 semiquantitative metric to score actionability. 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. 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.Genet Med advance online publication 28 April 2016Genetics in Medicine (2016); doi:10.1038/gim.2016.40. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 12 | 28% |
United Kingdom | 3 | 7% |
France | 2 | 5% |
Belgium | 1 | 2% |
Argentina | 1 | 2% |
India | 1 | 2% |
Japan | 1 | 2% |
Spain | 1 | 2% |
Unknown | 21 | 49% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 23 | 53% |
Scientists | 17 | 40% |
Science communicators (journalists, bloggers, editors) | 2 | 5% |
Practitioners (doctors, other healthcare professionals) | 1 | 2% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | <1% |
Canada | 1 | <1% |
Unknown | 105 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 22% |
Other | 16 | 15% |
Student > Ph. D. Student | 12 | 11% |
Student > Master | 10 | 9% |
Student > Bachelor | 8 | 7% |
Other | 19 | 18% |
Unknown | 18 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 35 | 33% |
Medicine and Dentistry | 17 | 16% |
Agricultural and Biological Sciences | 15 | 14% |
Computer Science | 5 | 5% |
Nursing and Health Professions | 2 | 2% |
Other | 12 | 11% |
Unknown | 21 | 20% |