title: Characterizing genetic variants for clinical action.
abstract: Genome-wide association studies, DNA sequencing studies, and other genomic studies are finding an increasing number of genetic variants associated with clinical phenotypes that may be useful in developing diagnostic, preventive, and treatment strategies for individual patients. However, few variants have been integrated into routine clinical practice. The reasons for this are several, but two of the most significant are limited evidence about the clinical implications of the variants and a lack of a comprehensive knowledge base that captures genetic variants, their phenotypic associations, and other pertinent phenotypic information that is openly accessible to clinical groups attempting to interpret sequencing data. As the field of medicine begins to incorporate genome-scale analysis into clinical care, approaches need to be developed for collecting and characterizing data on the clinical implications of variants, developing consensus on their actionability, and making this information available for clinical use. The National Human Genome Research Institute (NHGRI) and the Wellcome Trust thus convened a workshop to consider the processes and resources needed to: (1) identify clinically valid genetic variants; (2) decide whether they are actionable and what the action should be; and (3) provide this information for clinical use. This commentary outlines the key discussion points and recommendations from the workshop.
authors.forename: Erin M
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authors.lastname: Ramos
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authors.forename: Jonathan S
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authors.lastname: O'Donnell
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authors.lastname: Aronson
authors.forename: Leslie G
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authors.lastname: Biesecker
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authors.lastname: Blumberg
authors.forename: Ned
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authors.lastname: Calonge
authors.forename: Helen M
authors.initials: HM
authors.lastname: Colhoun
authors.forename: Robert S
authors.initials: RS
authors.lastname: Epstein
authors.forename: Paul
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authors.lastname: Flicek
authors.forename: Erynn S
authors.initials: ES
authors.lastname: Gordon
authors.forename: Eric D
authors.initials: ED
authors.lastname: Green
authors.forename: Robert C
authors.initials: RC
authors.lastname: Green
authors.forename: Matthew
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authors.lastname: Hurles
authors.forename: Kensaku
authors.initials: K
authors.lastname: Kawamoto
authors.forename: William
authors.initials: W
authors.lastname: Knaus
authors.forename: David H
authors.initials: DH
authors.lastname: Ledbetter
authors.forename: Howard P
authors.initials: HP
authors.lastname: Levy
authors.forename: Elaine
authors.initials: E
authors.lastname: Lyon
authors.forename: Donna
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authors.lastname: Maglott
authors.forename: Howard L
authors.initials: HL
authors.lastname: McLeod
authors.forename: Nazneen
authors.initials: N
authors.lastname: Rahman
authors.forename: Gurvaneet
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authors.lastname: Randhawa
authors.forename: Catherine
authors.initials: C
authors.lastname: Wicklund
authors.forename: Teri A
authors.initials: TA
authors.lastname: Manolio
authors.forename: Rex L
authors.initials: RL
authors.lastname: Chisholm
authors.forename: Marc S
authors.initials: MS
authors.lastname: Williams
mesh_terms: D004493:Education; D014644:Genetic Variation / Q000235:genetics*; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D008490:Medical Informatics / Q000379:methods*; D054560:National Human Genome Research Institute (U.S.); D010641:Phenotype; D057285:Precision Medicine / Q000379:methods* / Q000639:trends; D014481:United States
keywords: DNA sequencing; clinical actionability; database; electronic health records (EHR); genomic medicine; pharmacogenomics