Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network

Background Systematic study of clinical phenotypes is important for a better understanding of the genetic basis of human diseases and more effective gene-based disease management. A key aspect in facilitating such studies requires standardized representation of the phenotype data using common data elements (CDEs) and controlled biomedical vocabularies. In this study, the authors analyzed how a limited subset of phenotypic data is amenable to common definition and standardized collection, as well as how their adoption in large-scale epidemiological and genome-wide studies can significantly facilitate cross-study analysis. Methods The authors mapped phenotype data dictionaries from five different eMERGE (Electronic Medical Records and Genomics) Network sites studying multiple diseases such as peripheral arterial disease and type 2 diabetes. For mapping, standardized terminological and metadata repository resources, such as the caDSR (Cancer Data Standards Registry and Repository) and...

• Type: Journal
• Year: 2011
• Where: JAMIA
• Authors: Jyotishman Pathak, Janey Wang, Sudha Kashyap, Melissa A. Basford, Rongling Li, Daniel R. Masys, Christopher G. Chute
• Keywords: Algorithms, Clinical Phenotypes, JAMIA 2011, Metadata Repository, Snomed Ct