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Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project
Edison Ong1, Lucy L Wang2, Jennifer Schaub3
1Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA.
Abstract:
An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.
Insights
New ontologies will help organize kidney disease data for precision medicine. This advances understanding and treatment by mapping kidney molecular, cellular, and anatomical features.
Area of Science:
- Nephrology
- Bioinformatics
- Genomics
Background:
- Kidney disease requires better stratification based on pathophysiology for targeted therapies.
- Precision medicine initiatives collect diverse patient data for improved understanding.
- Ontologies are essential for organizing and integrating complex biomedical data.
Purpose of the Study:
- To develop ontologies for organizing kidney disease data.
- To support the creation of a comprehensive Kidney Tissue Atlas.
- To enable precise phenotyping for kidney precision medicine.
Main Methods:
- Development of the Kidney Tissue Atlas Ontology.
- Development of the Ontology of Precision Medicine and Investigation.
- Integration of clinical, biological, and imaging data.
Main Results:
- Two new ontologies have been created to support kidney research.
- These ontologies facilitate data annotation and integration.
- The Kidney Tissue Atlas will provide a detailed map of kidney structures.
Conclusions:
- Ontologies are critical for advancing kidney precision medicine.
- Improved data organization will lead to new definitions of kidney disease.
- This work supports the development of more effective kidney disease therapeutics.
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