M. Todd Valerius

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.

ATP depletion is a hallmark of acute kidney injury. Proliferation is instrumental to kidney repair. We show that ATP levels vary during the cell cycle and that proliferation sensitizes renal epithelial cells to superimposed injuries in vitro. More proliferation and less energy production by the mitochondria are associated with adverse outcomes in injured kidney allografts. This suggests that controlling the timing of kidney repair might be beneficial to mitigate the extent of acute kidney injury.

Organoids serve as a novel tool for disease modeling in three-dimensional multicellular contexts. Static organoids, however, lack the requisite biophysical microenvironment such as fluid flow, limiting their ability to faithfully recapitulate disease pathology. Here, we unite organoids with organ-on-a-chip technology to unravel disease pathology and develop therapies for autosomal recessive polycystic kidney disease. PKHD1 -mutant organoids-on-a-chip are subjected to flow that induces clinically relevant phenotypes of distal nephron dilatation. Transcriptomics discover 229 signal pathways that are not identified by static models. Mechanosensing molecules, RAC1 and FOS, are identified as potential therapeutic targets and validated by patient kidney samples. On the basis of this insight, we tested two U.S. Food and Drug Administration–approved and one investigational new drugs that target RAC1 and FOS in our organoid-on-a-chip model, which suppressed cyst formation. Our observations highlight the vast potential of organoid-on-a-chip models to elucidate complex disease mechanisms for therapeutic testing and discovery.

Directed differentiation of human pluripotent stem cells (hPSCs) into functional ureteric and collecting duct (CD) epithelia is essential to kidney regenerative medicine. Here we describe highly efficient, serum-free differentiation of hPSCs into ureteric bud (UB) organoids and functional CD cells. The hPSCs are first induced into pronephric progenitor cells at 90% efficiency and then aggregated into spheres with a molecular signature similar to the nephric duct. In a three-dimensional matrix, the spheres form UB organoids that exhibit branching morphogenesis similar to the fetal UB and correct distal tip localization of RET expression. Organoid-derived cells incorporate into the UB tips of the progenitor niche in chimeric fetal kidney explant culture. At later stages, the UB organoids differentiate into CD organoids, which contain >95% CD cell types as estimated by single-cell RNA sequencing. The CD epithelia demonstrate renal electrophysiologic functions, with ENaC-mediated vectorial sodium transport by principal cells and V-type ATPase proton pump activity by FOXI1-induced intercalated cells.

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

The Human Reference Atlas (HRA) aims to map all of the cells of the human body to advance biomedical research and clinical practice. This Perspective presents collaborative work by members of 16 international consortia on two essential and interlinked parts of the HRA: (1) three-dimensional representations of anatomy that are linked to (2) tables that name and interlink major anatomical structures, cell types, plus biomarkers (ASCT+B). We discuss four examples that demonstrate the practical utility of the HRA.

1. This paper reviews efforts across 16 international consortia to construct human anatomical structures, cell types, and biomarkers (ASCT+B) tables and three-dimensional reference organs in support of a Human Reference Atlas. We detail the ontological descriptions and spatial three-dimensional anatomical representations together with user interfaces that support the registration and exploration of human tissue data. Four use cases are presented to demonstrate the utility of ASCT+B tables for advancing biomedical research and improving health.

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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.

The endogenous repair process can result in recovery after acute kidney injury (AKI) with adaptive proliferation of tubular epithelial cells, but repair can also lead to fibrosis and progressive kidney disease. There is currently limited knowledge about transcriptional regulators regulating these repair programs. Herein we establish the enhancer and super-enhancer landscape after AKI by ChIP-seq in uninjured and repairing kidneys on day two after ischemia reperfusion injury (IRI). We identify key transcription factors including HNF4A, GR, STAT3 and STAT5, which show specific binding at enhancer and super-enhancer sites, revealing enhancer dynamics and transcriptional changes during kidney repair. Loss of bromodomain-containing protein 4 function before IRI leads to impaired recovery after AKI and increased mortality. Our comprehensive analysis of epigenetic changes after kidney injury in vivo has the potential to identify targets for therapeutic intervention. Importantly, our data also call attention to potential caveats involved in use of BET inhibitors in patients at risk for AKI.