title: Phenotypic information in genomic variant databases enhances clinical care and research: the International Standards for Cytogenomic Arrays Consortium experience.
abstract: Whole-genome analysis, now including whole-genome sequencing, is moving rapidly into the clinical setting, leading to detection of human variation on a broader scale than ever before. Interpreting this information will depend on the availability of thorough and accurate phenotype information, and the ability to curate, store, and access data on genotype-phenotype relationships. This idea has already been demonstrated within the context of chromosomal microarray (CMA) testing. The International Standards for Cytogenomic Arrays (ISCA) Consortium promotes standardization of variant interpretation for this technology through its initiatives, including the formation of a publicly available database housing clinical CMA data. Recognizing that phenotypic data are essential for the interpretation of genomic variants, the ISCA Consortium has developed tools to facilitate the collection of these data and its deposition in a standardized structured format within the ISCA Consortium database. This rich source of phenotypic data can also be used within broader applications such as developing phenotypic profiles of emerging genomic disorders, identification of candidate regions for particular phenotypes, or creation of tools for use in clinical practice. We summarize the ISCA experience as a model for ongoing efforts incorporating phenotype data with genotype data to improve the quality of research and clinical care in human genetics.
authors.affiliation: Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA. erin.riggs@emory.edu
authors.forename: Erin Rooney
authors.initials: ER
authors.lastname: Riggs
authors.forename: Laird
authors.initials: L
authors.lastname: Jackson
authors.forename: David T
authors.initials: DT
authors.lastname: Miller
authors.forename: Steven
authors.initials: S
authors.lastname: Van Vooren
mesh_terms: D020732:Cytogenetic Analysis; D057225:Data Mining; D030541:Databases, Genetic; D056726:Genetic Association Studies; D014644:Genetic Variation; D055106:Genome-Wide Association Study; D006801:Humans; D008490:Medical Informatics; D010641:Phenotype; D057285:Precision Medicine