Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine
He, Y.; Barisoni, L.; Rosenberg, A. Z.; Robinson, P.; Diehl, A. D.; Chen, Y.; Phuong, J. P.; Hansen, J.; Herr, B. W.; Borner, K.; Schaub, J.; Bonevich, N.; Arnous, G.; Boddapati, S.; Zheng, J.; Alakwaa, F.; Sarder, P.; Duncan, W. D.; Liang, C.; Valerius, M. T.; Jain, S.; Iyengar, R.; Himmelfarb, J.; Kretzler, M.; Kidney Precision Medicine Project,
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Many resources are now generating, processing, storing, or providing kidney-related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data organization and integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO) and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD). The Kidney Tissue Atlas Ontology (KTAO) imports and integrates kidney-related terms from existing ontologies (e.g., HPO, CL, and Uberon) and represents 259 kidney-related biomarkers. We also developed a precision medicine metadata ontology (PMMO) to integrate 50 variables from KPMP and CellxGene resources and applied PMMO for integrative analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed in healthy controls or AKI/CKD disease states. This work demonstrates how ontology-based approaches support multi-domain data and knowledge organization and integration to advance precision medicine.
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