Linking rare and common disease vocabularies by mapping between the human phenotype ontology and phecodes

Author:

McArthur Evonne1ORCID,Bastarache Lisa2,Capra John A34ORCID

Affiliation:

1. Vanderbilt Genetics Institute, Vanderbilt University , Nashville, Tennessee, USA

2. Department of Biomedical Informatics, Vanderbilt University Medical Center , Nashville, Tennessee, USA

3. Bakar Computational Health Sciences Institute, University of California San Francisco , San Francisco, California, USA

4. Department of Epidemiology and Biostatistics, University of California San Francisco , San Francisco, California, USA

Abstract

AbstractEnabling discovery across the spectrum of rare and common diseases requires the integration of biological knowledge with clinical data; however, differences in terminologies present a major barrier. For example, the Human Phenotype Ontology (HPO) is the primary vocabulary for describing features of rare diseases, while most clinical encounters use International Classification of Diseases (ICD) billing codes. ICD codes are further organized into clinically meaningful phenotypes via phecodes. Despite their prevalence, no robust phenome-wide disease mapping between HPO and phecodes/ICD exists. Here, we synthesize evidence using diverse sources and methods—including text matching, the National Library of Medicine’s Unified Medical Language System (UMLS), Wikipedia, SORTA, and PheMap—to define a mapping between phecodes and HPO terms via 38 950 links. We evaluate the precision and recall for each domain of evidence, both individually and jointly. This flexibility permits users to tailor the HPO–phecode links for diverse applications along the spectrum of monogenic to polygenic diseases.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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4. Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record;Wei;PLoS One,2017

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