ABSTRACT
The progression of kidney disease varies among individuals, but a general methodology to quantify disease timelines is lacking. Particularly challenging is the task of determining the potential for recovery from acute kidney injury following various insults. Here, we report that quantitation of post-transcriptional adenosine-to-inosine (A-to-I) RNA editing offers a distinct genome-wide signature, enabling the delineation of disease trajectories in the kidney. A well-defined murine model of endotoxemia permitted the identification of the origin and extent of A-to-I editing, along with temporally discrete signatures of double-stranded RNA stress and Adenosine Deaminase isoform switching. We found that A-to-I editing of Antizyme Inhibitor 1 (AZIN1), a positive regulator of polyamine biosynthesis, serves as a particularly useful temporal landmark during endotoxemia. Our data indicate that AZIN1 A-to-I editing, triggered by preceding inflammation, primes the kidney and activates endogenous recovery mechanisms. By comparing genetically modified human cell lines and mice locked in either A-to-I edited or uneditable states, we uncovered that AZIN1 A-to-I editing not only enhances polyamine biosynthesis but also engages glycolysis and nicotinamide biosynthesis to drive the recovery phenotype. Our findings implicate that quantifying AZIN1 A-to-I editing could potentially identify individuals who have transitioned to an endogenous recovery phase. This phase would reflect their past inflammation and indicate their potential for future recovery.
ABSTRACT
Spatial -OMICS technologies facilitate the interrogation of molecular profiles in the context of the underlying histopathology and tissue microenvironment. Paired analysis of histopathology and molecular data can provide pathologists with otherwise unobtainable insights into biological mechanisms. To connect the disparate molecular and histopathologic features into a single workspace, we developed FUSION (Functional Unit State IdentificatiON in WSIs [Whole Slide Images]), a web-based tool that provides users with a broad array of visualization and analytical tools including deep learning-based algorithms for in-depth interrogation of spatial -OMICS datasets and their associated high-resolution histology images. FUSION enables end-to-end analysis of functional tissue units (FTUs), automatically aggregating underlying molecular data to provide a histopathology-based medium for analyzing healthy and altered cell states and driving new discoveries using "pathomic" features. We demonstrate FUSION using 10x Visium spatial transcriptomics (ST) data from both formalin-fixed paraffin embedded (FFPE) and frozen prepared datasets consisting of healthy and diseased tissue. Through several use-cases, we demonstrate how users can identify spatial linkages between quantitative pathomics, qualitative image characteristics, and spatial --omics.
ABSTRACT
Background: Immune checkpoint inhibitors (ICIs) enhance the immune system's ability to target and destroy cancer cells by blocking inhibitory pathways. Despite their efficacy, these treatments can trigger immune-related adverse events (irAEs), such as acute kidney injury (ICI-AKI), complicating patient management. The genetic predispositions to ICI-AKI are not well understood, necessitating comprehensive genomic studies to identify risk factors and improve therapeutic strategies. Objective: To identify genetic predispositions for ICI-AKI using large-scale real-world data. Methods: A systematic literature search led to 14 candidate variants related to irAEs. We performed a candidate variant association study with these 14 variants using the All of Us cohort (AoU, v7, cutoff date: 7/1/2022). A cohort for cancer patients receiving ICI and a general cohort were established to evaluate ICI-AKI risk. Logistic regression, adjusted for sex, was used to evaluate the impact of each candidate genotype, separately for self-reported and ancestry-estimated race. Kaplan-Meier survival analysis assessed the genetic effects on AKI-free survival. Results: The ICI cohort (n=414) showed a one-year AKI incidence rate of 23.2%, significantly higher than the general cohort (6.5%, n=213,282). The rs16957301 variant (chr13:100324308, T>C) in the PCCA gene was a significant risk genotype for ICI-AKI among self-reported Caucasians (Beta=0.93, Bonferroni-corrected P-value=0.047) and ancestry estimated Caucasians (Beta = 0.94, Bonferroni-corrected P-value=0.044). Self-reported Caucasians with the rs16957301 risk genotypes (TC/CC) developed AKI significantly earlier (3.6 months) compared to the reference genotype (TT, 7.0 months, log-rank P=0.04). Consistent results were found in ancestry-estimated Caucasians. This variant did not present significant AKI risks in the general cohort (Beta: -0.008-0.035, FDR: 0.75-0.99). Conclusion: Real-world evidence from the All of Us cohort suggests that, in Caucasians, PCCA variant rs16957301 is a novel AKI risk genotype specific to ICI treatment. Additional studies are warranted to validate rs16957301 as risk marker for AKI in Caucasian patients treated with ICIs and to assess its risk in other ancestral populations.
ABSTRACT
Background: Hypertension (HTN) involves genetic variability in the renin-angiotensin system and influences antihypertensive response. We previously reported that angiotensinogen (AGT) messenger RNA (mRNA) is endogenously bound by miR-122-5p and rs699 A > G decreases reporter mRNA in the microRNA functional-assay PASSPORT-seq. The AGT promoter variant rs5051 C > T is in linkage disequilibrium (LD) with rs699 A > G and increases AGT transcription. The independent effect of these variants is understudied due to their LD therefore we aimed to test the hypothesis that increased AGT by rs5051 C > T counterbalances AGT decreased by rs699 A > G, and when these variants occur independently, it translates to HTN-related phenotypes. Methods: We used in silico, in vitro, in vivo, and retrospective models to test this hypothesis. Results: In silico, rs699 A > G is predicted to increase miR-122-5p binding affinity by 3%. Mir-eCLIP results show rs699 is 40-45 nucleotides from the strongest microRNA-binding site in the AGT mRNA. Unexpectedly, rs699 A > G increases AGT mRNA in an AGT-plasmid-cDNA HepG2 expression model. Genotype-Tissue Expression (GTEx) and UK Biobank analyses demonstrate liver AGT expression and HTN phenotypes are not different when rs699 A > G occurs independently from rs5051 C > T. However, GTEx and the in vitro experiments suggest rs699 A > G confers cell-type-specific effects on AGT mRNA abundance, and suggest paracrine renal renin-angiotensin-system perturbations could mediate the rs699 A > G associations with HTN. Conclusions: We found that rs5051 C > T and rs699 A > G significantly associate with systolic blood pressure in Black participants in the UK Biobank, demonstrating a fourfold larger effect than in White participants. Further studies are warranted to determine if altered antihypertensive response in Black individuals might be due to rs5051 C > T or rs699 A > G. Studies like this will help clinicians move beyond the use of race as a surrogate for genotype.
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OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision management of chronic disease progression. MATERIALS AND METHODS: We first perform requirement analysis with clinicians and data scientists to determine the visual analytics tasks of the TrajVis system as well as its design and functionalities. A graph AI model for chronic kidney disease (CKD) trajectory inference named DisEase PrOgression Trajectory (DEPOT) is used for system development and demonstration. TrajVis is implemented as a full-stack web application with synthetic EMR data derived from the Atrium Health Wake Forest Baptist Translational Data Warehouse and the Indiana Network for Patient Care research database. A case study with a nephrologist and a user experience survey of clinicians and data scientists are conducted to evaluate the TrajVis system. RESULTS: The TrajVis clinical information system is composed of 4 panels: the Patient View for demographic and clinical information, the Trajectory View to visualize the DEPOT-derived CKD trajectories in latent space, the Clinical Indicator View to elucidate longitudinal patterns of clinical features and interpret DEPOT predictions, and the Analysis View to demonstrate personal CKD progression trajectories. System evaluations suggest that TrajVis supports clinicians in summarizing clinical data, identifying individualized risk predictors, and visualizing patient disease progression trajectories, overcoming the barriers of AI implementation in healthcare. DISCUSSION: The TrajVis system provides a novel visualization solution which is complimentary to other risk estimators such as the Kidney Failure Risk Equations. CONCLUSION: TrajVis bridges the gap between the fast-growing AI/ML modeling and the clinical use of such models for personalized and precision management of chronic diseases.
ABSTRACT
The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology. Its application to preclinical models and human samples has provided spatial information about new cell types discovered by single-cell sequencing and new insights into the cell-cell interactions within neighbourhoods, and has improved our understanding of the changes that occur in response to injury. Integration of spatial transcriptomic technologies with other omics methods, such as proteomics and spatial epigenetics, will further facilitate the generation of comprehensive molecular atlases, and provide insights into the dynamic relationships of molecular components in homeostasis and disease. This Review provides an overview of current and emerging spatial transcriptomic methods, their applications and remaining challenges for the field.
ABSTRACT
In this commentary, a novel approach to the reclassification of chronic kidney disease is reviewed. In the revisited study, the investigators identify 4 distinct subtypes of kidney disease derived from an unbiased self-organizing map of transcriptomic data from kidney biopsy samples. These molecular subtypes then are characterized by biologic cell processes, clinical and histopathologic features, urinary proteomics, and disease progression. The strengths and limitations of the self-organizing map approach are assessed; the prognostic, diagnostic, and therapeutic implications are considered briefly.
Subject(s)
Disease Progression , Kidney , Proteomics , Renal Insufficiency, Chronic , Transcriptome , Humans , Prognosis , Renal Insufficiency, Chronic/genetics , Renal Insufficiency, Chronic/diagnosis , Renal Insufficiency, Chronic/pathology , Renal Insufficiency, Chronic/urine , Proteomics/methods , Kidney/pathology , Biopsy , Gene Expression Profiling , Biomarkers/analysis , Biomarkers/urineSubject(s)
Kidney , Humans , Kidney/pathology , Biopsy , Blood Proteins/analysis , Male , Female , Middle Aged , Adult , Aged , Kidney Diseases/pathology , Kidney Diseases/bloodABSTRACT
Chronic kidney disease (CKD) is associated with renal metabolic disturbances, including impaired fatty acid oxidation (FAO). Nicotinamide adenine dinucleotide (NAD + ) is a small molecule that participates in hundreds of metabolism-related reactions. NAD + levels are decreased in CKD, and NAD + supplementation is protective. However, both the mechanism of how NAD + supplementation protects from CKD, as well as the cell types most responsible, are poorly understood. Using a mouse model of Alport syndrome, we show that nicotinamide riboside (NR), an NAD + precursor, stimulates renal peroxisome proliferator-activated receptor α signaling and restores FAO in the proximal tubules, thereby protecting from CKD in both sexes. Bulk RNA-sequencing shows that renal metabolic pathways are impaired in Alport mice and dramatically activated by NR in both sexes. These transcriptional changes are confirmed by orthogonal imaging techniques and biochemical assays. Single nuclei RNA-sequencing and spatial transcriptomics, both the first of their kind from Alport mice, show that NAD + supplementation restores FAO in the proximal tubules with minimal effects on the podocytes. Finally, we also report, for the first time, sex differences at the transcriptional level in this Alport model. Male Alport mice had more severe inflammation and fibrosis than female mice at the transcriptional level. In summary, the data herein identify both the protective mechanism and location of NAD + supplementation in this model of CKD.
ABSTRACT
There is a need to define regions of gene activation or repression that control human kidney cells in states of health, injury, and repair to understand the molecular pathogenesis of kidney disease and design therapeutic strategies. Comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measure dual single nucleus RNA expression and chromatin accessibility, DNA methylation, and H3K27ac, H3K4me1, H3K4me3, and H3K27me3 histone modifications to decipher the chromatin landscape and gene regulation of the kidney in reference and adaptive injury states. We establish a spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we note distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3, KLF6, and KLF10 regulates the transition between health and injury, while in thick ascending limb cells this transition is regulated by NR2F1. Further, combined perturbation of ELF3, KLF6, and KLF10 distinguishes two adaptive proximal tubular cell subtypes, one of which manifested a repair trajectory after knockout. This atlas will serve as a foundation to facilitate targeted cell-specific therapeutics by reprogramming gene regulatory networks.
Subject(s)
Chromatin , Kidney , Humans , Chromatin/genetics , Kidney Tubules, Proximal , Health Status , Cell CountABSTRACT
Chronic kidney disease (CKD) and acute kidney injury (AKI) are heterogeneous syndromes defined clinically by serial measures of kidney function. Each condition possesses strong histopathologic associations, including glomerular obsolescence or acute tubular necrosis, respectively. Despite such characterization, there remains wide variation in patient outcomes and treatment responses. Precision medicine efforts, as exemplified by the Kidney Precision Medicine Project (KPMP), have begun to establish evolving, spatially anchored, cellular and molecular atlases of the cell types, states, and niches of the kidney in health and disease. The KPMP atlas provides molecular context for CKD and AKI disease drivers and will help define subtypes of disease that are not readily apparent from canonical functional or histopathologic characterization but instead are appreciable through advanced clinical phenotyping, pathomic, transcriptomic, proteomic, epigenomic, and metabolomic interrogation of kidney biopsy samples. This perspective outlines the structure of the KPMP, its approach to the integration of these diverse datasets, and its major outputs relevant to future patient care.
Subject(s)
Acute Kidney Injury , Nephrology , Renal Insufficiency, Chronic , Humans , Precision Medicine , Proteomics , Kidney/pathology , Renal Insufficiency, Chronic/epidemiology , Renal Insufficiency, Chronic/therapy , Renal Insufficiency, Chronic/pathology , Acute Kidney Injury/pathologyABSTRACT
Identifying spatially variable genes (SVGs) is critical in linking molecular cell functions with tissue phenotypes. Spatially resolved transcriptomics captures cellular-level gene expression with corresponding spatial coordinates in two or three dimensions and can be used to infer SVGs effectively. However, current computational methods may not achieve reliable results and often cannot handle three-dimensional spatial transcriptomic data. Here we introduce BSP (big-small patch), a non-parametric model by comparing gene expression pattens at two spatial granularities to identify SVGs from two or three-dimensional spatial transcriptomics data in a fast and robust manner. This method has been extensively tested in simulations, demonstrating superior accuracy, robustness, and high efficiency. BSP is further validated by substantiated biological discoveries in cancer, neural science, rheumatoid arthritis, and kidney studies with various types of spatial transcriptomics technologies.
Subject(s)
Arthritis, Rheumatoid , Humans , Gene Expression Profiling , Kidney , Phenotype , Technology , TranscriptomeABSTRACT
The progression of kidney disease varies among individuals, but a general methodology to quantify disease timelines is lacking. Particularly challenging is the task of determining the potential for recovery from acute kidney injury following various insults. Here, we report that quantitation of post-transcriptional adenosine-to-inosine (A-to-I) RNA editing offers a distinct genome-wide signature, enabling the delineation of disease trajectories in the kidney. A well-defined murine model of endotoxemia permitted the identification of the origin and extent of A-to-I editing, along with temporally discrete signatures of double-stranded RNA stress and Adenosine Deaminase isoform switching. We found that A-to-I editing of Antizyme Inhibitor 1 (AZIN1), a positive regulator of polyamine biosynthesis, serves as a particularly useful temporal landmark during endotoxemia. Our data indicate that AZIN1 A-to-I editing, triggered by preceding inflammation, primes the kidney and activates endogenous recovery mechanisms. By comparing genetically modified human cell lines and mice locked in either A-to-I edited or uneditable states, we uncovered that AZIN1 A-to-I editing not only enhances polyamine biosynthesis but also engages glycolysis and nicotinamide biosynthesis to drive the recovery phenotype. Our findings implicate that quantifying AZIN1 A-to-I editing could potentially identify individuals who have transitioned to an endogenous recovery phase. This phase would reflect their past inflammation and indicate their potential for future recovery.
ABSTRACT
Introduction: Primary membranous nephropathy (PMN) is uncommon in children. Therefore, data on the clinical course of affected children are scarce. In recent years, several novel antigens have been implicated in the pathogenesis of PMN. However, the histopathologic characteristics of pediatric patients with PMN remain poorly represented in the literature. Methods: We have retrospectively analyzed the clinical presentation and outcomes data of 21 children with PMN from 3 centers in the United States. In addition, we have identified novel antigens in biopsy specimens from these patients and correlated their presence or absence to clinical outcomes. Finally, we compared the results of the novel antigen staining from our clinical cohort to a validation cohort of 127 biopsy specimens from children with PMN at Arkana Laboratories. Results: The data from the 2 cohorts demonstrated similar overall antigen positivity rates of 62% to 63%, with phospholipase A2 receptor (PLA2R) and exostosin 1 (EXT1) being the most commonly found antigens. Results from the clinical cohort showed that overall, the kidney prognosis for children with PMN was good, with 17 of 21 patients entering a complete or partial remission. Children who were positive for PLA2R or EXT1 were significantly more likely to enter remission than those in the antigen negative group. Conclusion: Approximately 60% of pediatric membranous cases are positive for a novel antigen on kidney biopsy and the clinical prognosis is generally favorable. More studies are needed to understand the clinical implications of each specific novel antigen.
ABSTRACT
Acute kidney injury (AKI) is an important contributor to the development of chronic kidney disease (CKD). There is a need to understand molecular mediators that drive either recovery or progression to CKD. In particular, the role of miRNA and its regulatory role in AKI is poorly understood. We performed miRNA and mRNA sequencing on biobanked human kidney tissues obtained in the routine clinical care of patients with the diagnoses of AKI and minimal change disease (MCD), in addition to nephrectomized (Ref) tissue from individuals without known kidney disease. Transcriptomic analysis of mRNA revealed that Ref tissues exhibited a similar injury signature to AKI, not identified in MCD samples. The transcriptomic signature of human AKI was enriched with genes in pathways involved in cell adhesion and epithelial-to-mesenchymal transition (e.g., CDH6, ITGB6, CDKN1A ). miRNA DE analysis revealed upregulation of miRNA associated with immune cell recruitment and inflammation (e.g., miR-146a, miR-155, miR-142, miR-122). These miRNA (i.e., miR-122, miR-146) are also associated with downregulation of mRNA such as DDR2 and IGFBP6 , respectively. These findings suggest integrated interactions between miRNAs and target mRNAs in AKI-related processes such as inflammation, immune cell activation and epithelial-to-mesenchymal transition. These data contribute several novel findings when describing the epigenetic regulation of AKI by miRNA, and also underscores the importance of utilizing an appropriate reference control tissue to understand canonical pathway alterations in AKI.
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Adverse drug events (ADEs) account for a significant mortality, morbidity, and cost burden. Pharmacogenetic testing has the potential to reduce ADEs and inefficacy. The objective of this INGENIOUS trial (NCT02297126) analysis was to determine whether conducting and reporting pharmacogenetic panel testing impacts ADE frequency. The trial was a pragmatic, randomized controlled clinical trial, adapted as a propensity matched analysis in individuals (N = 2612) receiving a new prescription for one or more of 26 pharmacogenetic-actionable drugs across a community safety-net and academic health system. The intervention was a pharmacogenetic testing panel for 26 drugs with dosage and selection recommendations returned to the health record. The primary outcome was occurrence of ADEs within 1 year, according to modified Common Terminology Criteria for Adverse Events (CTCAE). In the propensity-matched analysis, 16.1% of individuals experienced any ADE within 1-year. Serious ADEs (CTCAE level ≥ 3) occurred in 3.2% of individuals. When combining all 26 drugs, no significant difference was observed between the pharmacogenetic testing and control arms for any ADE (Odds ratio 0.96, 95% CI: 0.78-1.18), serious ADEs (OR: 0.91, 95% CI: 0.58-1.40), or mortality (OR: 0.60, 95% CI: 0.28-1.21). However, sub-group analyses revealed a reduction in serious ADEs and death in individuals who underwent pharmacogenotyping for aripiprazole and serotonin or serotonin-norepinephrine reuptake inhibitors (OR 0.34, 95% CI: 0.12-0.85). In conclusion, no change in overall ADEs was observed after pharmacogenetic testing. However, limitations incurred during INGENIOUS likely affected the results. Future studies may consider preemptive, rather than reactive, pharmacogenetic panel testing.
Subject(s)
Drug-Related Side Effects and Adverse Reactions , Pharmacogenomic Testing , Humans , Aripiprazole , Drug-Related Side Effects and Adverse Reactions/genetics , Norepinephrine , SerotoninABSTRACT
The proximal tubule (PT) is a nephron segment that is responsible for the majority of solute and water reabsorption in the kidney. Each of its sub-segments have specialized functions; however, little is known about the genes and proteins that determine the oxidative phosphorylation capacity of the PT sub-segments. This information is critical to understanding kidney function and will provide a comprehensive landscape of renal cell adaptations to injury, physiologic stressors, and development. This study analyzed three immortalized murine renal cell lines (PT S1, S2, and S3 segments) for protein content and compared them to a murine fibroblast cell line. All three proximal tubule cell lines generate ATP predominantly by oxidative phosphorylation while the fibroblast cell line is glycolytic. The proteomic data demonstrates that the most significant difference in proteomic signatures between the cell lines are proteins known to be localized in the nucleus followed by mitochondrial proteins. Mitochondrial metabolic substrate utilization assays were performed using the proximal tubule cell lines to determine substrate utilization kinetics thereby providing a physiologic context to the proteomic dataset. This data will allow researchers to study differences in nephron-specific cell lines, between epithelial and fibroblast cells, and between actively respiring cells and glycolytic cells. SIGNIFICANCE: Proteomic analysis of proteins expressed in immortalized murine renal proximal tubule cells was compared to a murine fibroblast cell line proteome. The proximal tubule segment specific cell lines: S1, S2 and S3 are all grown under conditions whereby the cells generate ATP by oxidative phosphorylation while the fibroblast cell line utilizes anaerobic glycolysis for ATP generation. The proteomic studies allow for the following queries: 1) comparisons between the proximal tubule segment specific cell lines, 2) comparisons between polarized epithelia and fibroblasts, 3) comparison between cells employing oxidative phosphorylation versus anaerobic glycolysis and 4) comparisons between cells grown on clear versus opaque membrane supports. The data finds major differences in nuclear protein expression and mitochondrial proteins. This proteomic data set will be an important baseline dataset for investigators who need immortalized renal proximal tubule epithelial cells for their research.
Subject(s)
Kidney , Proteomics , Mice , Animals , Kidney Tubules, Proximal/metabolism , Cell Line , Mitochondrial Proteins/metabolism , Adenosine Triphosphate/metabolismABSTRACT
Arteriolar hyalinosis in kidneys is an independent predictor of cardiovascular disease, the main cause of mortality in chronic kidney disease (CKD). The underlying molecular mechanisms of protein accumulation in the subendothelial space are not well understood. Using single cell transcriptomic data and whole slide images from kidney biopsies of patients with CKD and acute kidney injury in the Kidney Precision Medicine Project, the molecular signals associated with arteriolar hyalinosis were evaluated. Co-expression network analysis of the endothelial genes yielded three gene set modules as significantly associated with arteriolar hyalinosis. Pathway analysis of these modules showed enrichment of transforming growth factor beta / bone morphogenetic protein (TGFß / BMP) and vascular endothelial growth factor (VEGF) signaling pathways in the endothelial cell signatures. Ligand-receptor analysis identified multiple integrins and cell adhesion receptors as over-expressed in arteriolar hyalinosis, suggesting a potential role of integrin-mediated TGFß signaling. Further analysis of arteriolar hyalinosis associated endothelial module genes identified focal segmental glomerular sclerosis as an enriched term. On validation in gene expression profiles from the Nephrotic Syndrome Study Network cohort, one of the three modules was significantly associated with the composite endpoint (> 40% reduction in estimated glomerular filtration rate (eGFR) or kidney failure) independent of age, sex, race, and baseline eGFR, suggesting poor prognosis with elevated expression of genes in this module. Thus, integration of structural and single cell molecular features yielded biologically relevant gene sets, signaling pathways and ligand-receptor interactions, underlying arteriolar hyalinosis and putative targets for therapeutic intervention.
ABSTRACT
Kidney stone disease causes significant morbidity and increases health care utilization. In this work, we decipher the cellular and molecular niche of the human renal papilla in patients with calcium oxalate (CaOx) stone disease and healthy subjects. In addition to identifying cell types important in papillary physiology, we characterize collecting duct cell subtypes and an undifferentiated epithelial cell type that was more prevalent in stone patients. Despite the focal nature of mineral deposition in nephrolithiasis, we uncover a global injury signature characterized by immune activation, oxidative stress and extracellular matrix remodeling. We also identify the association of MMP7 and MMP9 expression with stone disease and mineral deposition, respectively. MMP7 and MMP9 are significantly increased in the urine of patients with CaOx stone disease, and their levels correlate with disease activity. Our results define the spatial molecular landscape and specific pathways contributing to stone-mediated injury in the human papilla and identify associated urinary biomarkers.
Subject(s)
Kidney Calculi , Kidney Medulla , Humans , Kidney Medulla/metabolism , Matrix Metalloproteinase 9/metabolism , Matrix Metalloproteinase 7 , Calcium Oxalate/metabolism , Transcriptome , Kidney Calculi/genetics , Kidney Calculi/metabolismABSTRACT
Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.