Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project - Ong, Edison (Nat Rev Nephrol, 2020)
The Kidney Precision Medicine Project (KPMP) and other national efforts are collecting and integrating large disparate clinical, biotechnology, and imaging datasets to better understand and stratify kidney disease. Enabling these efforts, ontologies are powerful tools for organizing and making sense of different data elements and their relationships. Ontologies are critical for supporting the types of big data analysis necessary to conduct kidney precision medicine, where heterogeneous clinical, imaging, and biopsy data from diverse sources must be combined to define a patient’s phenotype. In this article, we demonstrate how reference ontologies and two KPMP-developed ontologies, the Kidney Tissue Atlas Ontology (KTAO) and the Ontology of Precision Medicine and Investigation (OPMI), will be used to support the creation of the Kidney Tissue Atlas. The KPMP ontologies can improve the concepts available for annotating kidney data, and revise existing definitions of kidney disease in support of precision medicine. We also provide a roadmap for how various ontologies, including KTAO and OPMI, can be used to support kidney disease modeling by the broader nephrology community.