Rationale and design of the Kidney Precision Medicine Project

Complementing Cell Taxonomies with a Multicellular Analysis of Tissues

The application of single-cell molecular profiling coupled with spatial technologies has enabled charting of cellular heterogeneity in reference tissues and in disease. This new wave of molecular data has highlighted the expected diversity of single-cell dynamics upon shared external queues and spatial organizations. However, little is known about the relationship between single-cell heterogeneity and the emergence and maintenance of robust multicellular processes in developed tissues and its role in (patho)physiology. Here, we present emerging computational modeling strategies that use increasingly available large-scale cross-condition single-cell and spatial datasets to study multicellular organization in tissues and complement cell taxonomies. This perspective should enable us to better understand how cells within tissues collectively process information and adapt synchronized responses in disease contexts and to bridge the gap between structural changes and functions in tissues.

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine

Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data 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 CZ CellxGene data resources and applied PMMO for integrative kidney data analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed under healthy control or AKI/CKD disease statuses. This work demonstrates how ontology-based approaches support multi-domain data and knowledge integration in precision medicine.

tRigon: an R package and Shiny App for integrative (path-)omics data analysis

BACKGROUND

Pathomics facilitates automated, reproducible and precise histopathology analysis and morphological phenotyping. Similar to molecular omics, pathomics datasets are high-dimensional, but also face large outlier variability and inherent data missingness, making quick and comprehensible data analysis challenging. To facilitate pathomics data analysis and interpretation as well as support a broad implementation we developed tRigon (Toolbox foR InteGrative (path-)Omics data aNalysis), a Shiny application for fast, comprehensive and reproducible pathomics analysis.

RESULTS

tRigon is available via the CRAN repository ( https://cran.r-project.org/web/packages/tRigon ) with its source code available on GitLab ( https://git-ce.rwth-aachen.de/labooratory-ai/trigon ). The tRigon package can be installed locally and its application can be executed from the R console via the command 'tRigon::run_tRigon()'. Alternatively, the application is hosted online and can be accessed at https://labooratory.shinyapps.io/tRigon . We show fast computation of small, medium and large datasets in a low- and high-performance hardware setting, indicating broad applicability of tRigon.

CONCLUSIONS

tRigon allows researchers without coding abilities to perform exploratory feature analyses of pathomics and non-pathomics datasets on their own using a variety of hardware.

Precision Medicine in Nephrology: An Integrative Framework of Multidimensional Data in the Kidney Precision Medicine Project

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.

The chromatin landscape of healthy and injured cell types in the human kidney

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.

Patient-Centered Research and Innovation in Nephrology

Patient involvement in research can improve the relevance of research, consequently enhancing the recruitment, retention, and uptake of interventions and policies impacting patient outcomes. Despite this, patients are not often involved in the design and conduct of research. The research agenda and innovations are frequently determined by the interest of health and industry professionals rather than proactively aligning with the priorities of patients. It is now being encouraged and recommended to engage patients in research priority setting to ensure interventions and trials report outcomes valuable to patients, moving away from a history of overlooking the outcomes that reflect the feel and function of patients. Involving patients ensures constant innovative research in nephrology, as this broader depth of evidence fortifies reliability and validity through knowledge gained from lived experience. Findings from such research can enhance clinical practice and strengthen decision-making and policy to support better outcomes. We aim to outline principles and strategies for patient involvement in research, including setting research priorities, identifying and designing interventions, selecting outcomes, and disseminating and translating research. Principles and strategies including engagement, education and training, empowerment, and connection and community provide guidance in patient involvement. There are increasing efforts to involve patients across all stages of research including setting research priorities. Efforts are rising to involve patients across all stages of research including priority setting, identifying and designing interventions, selecting outcomes, and dissemination and translation. Patient involvement throughout the research cycle drives innovative investigations ensuring funding, efforts, and resources are directed toward priorities of patients, contributing to catalyst advancements in care and outcomes.

Diabetic Kidney Disease Prevention Care Model Development

More than one-third of people with diabetes develop diabetic kidney disease (DKD), which substantially increases risks of kidney failure, cardiovascular disease (CVD), hypoglycemia, death, and other adverse health outcomes. A multifaceted approach incorporating self-management education, lifestyle optimization, pharmacological intervention, CVD prevention, and psychosocial support is crucial to mitigate the onset and progression of DKD. The American Diabetes Association convened an expert panel to develop the DKD Prevention Model presented herein. This model addresses prevention and treatment, including screening guidelines, diagnostic tools, and management approaches; comprehensive, holistic interventions; well-defined roles for interdisciplinary health care professionals; community engagement; and future directions for research and policy.

Advances in Imaging Mass Spectrometry for Biomedical and Clinical Research

Imaging mass spectrometry (IMS) allows for the untargeted mapping of biomolecules directly from tissue sections. This technology is increasingly integrated into biomedical and clinical research environments to supplement traditional microscopy and provide molecular context for tissue imaging. IMS has widespread clinical applicability in the fields of oncology, dermatology, microbiology, and others. This review summarizes the two most widely employed IMS technologies, matrix-assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI), and covers technological advancements, including efforts to increase spatial resolution, specificity, and throughput. We also highlight recent biomedical applications of IMS, primarily focusing on disease diagnosis, classification, and subtyping.

Emerging Preventive Strategies in Chronic Kidney Disease: Recent Evidence and Gaps in Knowledge

PURPOSE OF REVIEW

Chronic kidney disease (CKD) is increasingly prevalent worldwide and is associated with increased cardiovascular risk. New therapeutic options to slow CKD progression and reduce cardiovascular morbidity and mortality have recently emerged. This review highlights recent evidence and gaps in knowledge in emerging CKD preventive strategies.

RECENT FINDINGS

EMPA-Kidney trial found that empagliflozin, a sodium-glucose co-transporter 2 inhibitor (SGLT2i) led to 28% lower risk of progression of kidney disease or death from cardiovascular causes, compared to placebo. This reinforced the previous findings from DAPA-CKD and CREDENCE trials and led to inclusion of SGLT2i as the cornerstone of CKD preventive therapy in both diabetic and non-diabetic CKD. Finerenone, a selective nonsteroidal mineralocorticoid receptor antagonist, slowed diabetic kidney disease progression by 23% compared to placebo in a pool analysis of FIDELIO-DKD and FIGARO-DKD trials. Non-pharmacological interventions, including low protein diet, and early CKD detection and risk stratification strategies based on novel biomarkers have also gained momentum. Ongoing efforts to explore the wealth of molecular mechanisms in CKD, added to integrative omics modeling are well posed to lead to novel therapeutic targets in kidney care. While breakthrough pharmacological interventions continue to improve outcomes in CKD, the heterogeneity of kidney diseases warrants additional investigation. Further research into specific kidney disease mechanisms will facilitate the identification of patient populations most likely to benefit from targeted interventions.

Enablers and challenges of spatial omics, a melting pot of technologies

Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly interdisciplinary field that integrates imaging and omics, spatial and molecular analyses, sequencing and mass spectrometry, and image analysis and bioinformatics. The emergence of this field has not only opened a window into spatial biology, but also created multiple novel opportunities, questions, and challenges for method developers. Here, we provide the perspective of technology developers on what makes the spatial omics field unique. After providing a brief overview of the state of the art, we discuss technological enablers and challenges and present our vision about the future applications and impact of this melting pot.

Trends and perspectives for improving quality of chronic kidney disease care: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

Chronic kidney disease (CKD) affects over 850 million people globally, and the need to prevent its development and progression is urgent. During the past decade, new perspectives have arisen related to the quality and precision of care for CKD, owing to the development of new tools and interventions for CKD diagnosis and management. New biomarkers, imaging methods, artificial intelligence techniques, and approaches to organizing and delivering healthcare may help clinicians recognize CKD, determine its etiology, assess the dominant mechanisms at given time points, and identify patients at high risk for progression or related events. As opportunities to apply the concepts of precision medicine for CKD identification and management continue to be developed, an ongoing discussion of the potential implications for care delivery is required. The 2022 KDIGO Controversies Conference on Improving CKD Quality of Care: Trends and Perspectives examined and discussed best practices for improving the precision of CKD diagnosis and prognosis, managing the complications of CKD, enhancing the safety of care, and maximizing patient quality of life. Existing tools and interventions currently available for the diagnosis and treatment of CKD were identified, with discussion of current barriers to their implementation and strategies for improving the quality of care delivered for CKD. Key knowledge gaps and areas for research were also identified.

Design and development of opto-electrochemical biosensing devices for diagnosing chronic kidney disease

Chronic kidney disease (CKD) is emerging as one of the major causes of the increase in mortality rate and is expected to become 5th major cause by 2050. Many studies have shown that it is majorly related to various risk factors, and thus becoming one of the major health issues around the globe. Early detection of renal disease lowers the overall burden of disease by preventing individuals from developing kidney impairment. Therefore, diagnosis and prevention of CKD are becoming the major challenges, and in this situation, biosensors have emerged as one of the best possible solutions. Biosensors are becoming one of the preferred choices for various diseases diagnosis as they provide simpler, cost-effective and precise methods for onsite detection. In this review, we have tried to discuss the globally developed biosensors for the detection of CKD, focusing on their design, pattern, and applicability in real samples. Two major classifications of biosensors based on transduction systems, that is, optical and electrochemical, for kidney disease have been discussed in detail. Also, the major focus is given to clinical biomarkers such as albumin, creatinine, and others related to kidney dysfunction. Furthermore, the globally developed sensors for the detection of CKD are discussed in tabulated form comparing their analytical performance, response time, specificity as well as performance in biological fluids.

Spatial Heterogeneity of Glomerular Phenotypes Affects Kidney Biopsy Findings

Key Points

Background

Detection of rare glomerular phenotypes can affect diagnosis in indication kidney biopsies and in kidney tissue used for research studies. Nephropathologists are aware of potential sampling error when assessing needle biopsy cores, but quantitative data are lacking.

Methods

Kidney tissue from patients undergoing total nephrectomy enrolled in an observational, cross-sectional cohort study was used to characterize glomeruli as typical or atypical, which included globally sclerotic glomeruli (GSGs), segmentally sclerotic glomeruli, ischemic-like, and imploding. A 2D map of the glomerular annotations was generated. Spatial centrality of atypical glomeruli using the L2 metric and differences in pairwise distances between typical or atypical glomeruli were calculated. To determine how the yield of capturing atypical glomerular phenotype was affected by biopsy depth (i.e., not including the renal capsule), simulated kidney biopsies were generated from the 2D map.

Results

The mean number of glomeruli in a nephrectomy specimen was 209 (SD 143), and GSGs were the most common type of atypical glomeruli (median: 13% [interquartile range: 5,31]). Typical glomeruli were more likely to be surrounded by other glomeruli (i.e., centrally located in the kidney cortex) than GSGs, segmentally sclerosed glomeruli, ischemic-like glomeruli, and imploding glomeruli. Atypical glomeruli were 7.3% (95% confidence interval, 4.1 to 10.4) closer together than typical glomeruli and were more likely to be closer together in older patients or those with hypertension. In simulated kidney biopsies, failure to capture the capsule was associated with underdetection of GSGs, ischemic-like glomeruli, and imploding glomeruli.

Conclusions

Spatial analysis of large sections of kidney tissue provided quantitative evidence of spatial heterogeneity of glomerular phenotypes including clustering of atypical glomeruli in individuals with hypertension or older age. Most importantly, deep kidney biopsies that lack subcapsular area underdetect atypical glomerular phenotypes, suggesting that capturing the renal capsule is an important quality control measure for kidney biopsies.

Precision Medicine in Diabetic Kidney Disease: A Narrative Review Framed by Lived Experience

Purpose of review

Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease (CKD) for which many treatments exist that have been shown to prevent CKD progression and kidney failure. However, DKD is a complex and heterogeneous etiology of CKD with a spectrum of phenotypes and disease trajectories. In this narrative review, we discuss precision medicine approaches to DKD, including genomics, metabolomics, proteomics, and their potential role in the management of diabetes mellitus and DKD. A patient and caregivers of patients with lived experience with CKD were involved in this review.

Sources of information

Original research articles were identified from MEDLINE and Google Scholar using the search terms "diabetes," "diabetic kidney disease," "diabetic nephropathy," "chronic kidney disease," "kidney failure," "dialysis," "nephrology," "genomics," "metabolomics," and "proteomics."

Methods

A focused review and critical appraisal of existing literature regarding the precision medicine approaches to the diagnosis, prognosis, and treatment of diabetes and DKD framed by a patient partner's/caregiver's lived experience.

Key findings

Distinguishing diabetic nephropathy from CKD due to other types of DKD and non-DKD is challenging and typically requires a kidney biopsy for a diagnosis. Biomarkers have been identified to assist with the prediction of the onset and progression of DKD, but they have yet to be incorporated and evaluated relative to clinical standard of care CKD and kidney failure risk prediction tools. Genomics has identified multiple causal genetic variants for neonatal diabetes mellitus and monogenic diabetes of the young that can be used for diagnostic purposes and to specify antiglycemic therapy. Genome-wide-associated studies have identified genes implicated in DKD pathophysiology in the setting of type 1 and 2 diabetes but their translational benefits are lagging beyond polygenetic risk scores. Metabolomics and proteomics have been shown to improve diagnostic accuracy in DKD, have been used to identify novel pathways involved in DKD pathogenesis, and can be used to improve the prediction of CKD progression and kidney failure as well as predict response to DKD therapy.

Limitations

There are a limited number of large, high-quality prospective observational studies and no randomized controlled trials that support the use of precision medicine based approaches to improve clinical outcomes in adults with or at risk of diabetes and DKD. It is unclear which patients may benefit from the clinical use of genomics, metabolomics and proteomics along the spectrum of DKD trajectory.

Implications

Additional research is needed to evaluate the role of the use of precision medicine for DKD management, including diagnosis, differentiation of diabetic nephropathy from other etiologies of DKD and CKD, short-term and long-term risk prognostication kidney outcomes, and the prediction of response to and safety of disease-modifying therapies.

Participant Experience with Protocol Research Kidney Biopsies in the Kidney Precision Medicine Project

BACKGROUND

Kidney biopsies are procedures commonly performed in clinical nephrology and are increasingly used in research. In this study we aimed to evaluate the experiences of participants who underwent research kidney biopsies in the Kidney Precision Medicine Project (KPMP).

METHODS

KPMP research participants with acute kidney injury (AKI) or chronic kidney disease (CKD) were enrolled at nine recruitment sites in the United States between September 2019 to January 2023. At 28 days post-biopsy, participants were invited to complete a survey to share their experiences, including: motivation to participate in research; comprehension of informed consent; pain and anxiety during and after the biopsy procedure; overall satisfaction with KPMP participation; and impact of the study on their lives. The survey was developed in collaboration with the KPMP Community Engagement Committee and the Institute of Translational Health Sciences at the University of Washington.

RESULTS

111 participants completed the survey, 23 enrolled for AKI and 88 for CKD. Median age was 61 (IQR 48-67) years, 43% were women, 28% were Black, and 18% were of Hispanic ethnicity. Survey respondents most commonly joined KPMP to help future patients (59%). The consent form was understood by 99% and 97% recognized their important role in the study. Pain during the biopsy was reported by 50%, at a median level of 1 (IQR 0-3) on a 0-10 scale. Anxiety during the biopsy was described by 64% at a median level of 3 (IQR 1-5) on a 0-10 scale. More than half conveyed that KPMP participation impacted their diet, physical activity, and how they think about kidney disease.

CONCLUSIONS

KPMP survey respondents were most commonly motivated to participate in research protocol kidney biopsies by altruism, with excellent understanding of the informed consent process.

Definition, Staging, and Role of Biomarkers in Acute Kidney Injury in the Context of Cardiovascular Interventions

Acute kidney injury (AKI) is a frequently occurring complication of cardiovascular interventions, and associated with adverse outcomes. Therefore, a clear definition of AKI is of paramount importance to enable timely recognition and treatment. Historically, changes in the serum creatinine and urine output have been used to define AKI, and the criteria have evolved over time with better understanding of the impact of AKI on the outcomes. However, the reliance on serum creatinine for these AKI definitions carries numerous limitations including delayed rise, inability to differentiate between hemodynamics versus structural injury and assay variability to name a few.

Kidney fibrosis: Emerging diagnostic and therapeutic strategies

An increasing number of patients worldwide suffers from chronic kidney disease (CKD). CKD is accompanied by kidney fibrosis, which affects all compartments of the kidney, i.e., the glomeruli, tubulointerstitium, and vasculature. Fibrosis is the best predictor of progression of kidney diseases. Currently, there is no specific anti-fibrotic therapy for kidney patients and invasive renal biopsy remains the only option for specific detection and quantification of kidney fibrosis. Here we review emerging diagnostic approaches and potential therapeutic options for fibrosis. We discuss how translational research could help to establish fibrosis-specific endpoints for clinical trials, leading to improved patient stratification and potentially companion diagnostics, and facilitating and optimizing development of novel anti-fibrotic therapies for kidney patients.

Kidney Biopsy Utility: Patient and Clinician Perspectives from the Kidney Precision Medicine Project

Rationale & Objective

Limited data exist on patient perspectives of the implications of kidney biopsies. We explored patients' perspectives alongside those of clinicians to better understand how kidney biopsies affect patients' viewpoints and the clinical utility of biopsies.

Study Design

Prospective Cohort Study.

Setting & Participants

Patient participants and clinicians in the Kidney Precision Medicine Project, a prospective cohort study of patients who undergo a research protocol biopsy, at 9 recruitment sites across the United States. Surveys were completed at enrollment before biopsy and additional timepoints after biopsy (participants: 28 days, 6 months; clinicians: 2 weeks).

Analytical Approach

Kappa statistics assessed prebiopsy etiology concordance between clinicians and participants. Participant perspectives after biopsy were analyzed using a thematic approach. Clinician ratings of clinical management value were compared to prebiopsy ratings with Wilcoxon matched-pairs signed-rank tests and paired t tests.

Results

A total of 167 participants undergoing biopsy (124 participants with chronic kidney disease [CKD], 43 participants with acute kidney injury [AKI]) and 58 clinicians were included in this study. CKD participants and clinicians had low etiology concordance for the 2 leading causes of CKD: diabetes (k = 0.358) and hypertension (k = 0.081). At 28 days postbiopsy, 46 (84%) participants reported that the biopsy affected their understanding of their diagnosis, and 21 (38%) participants reported that the results of the biopsy affected their medications. Participants also shared biopsy impressions in free-text responses, including impacts on lifestyle and concurrent condition management. The biopsy positively shifted clinician perceptions of the procedure's clinical management benefits, while perceptions of prognostic value decreased and diagnostic ratings remained unchanged.

Limitations

Our study did not have demographic data of clinicians and could not provide insight into postbiopsy experiences for participants who did not respond to follow-up surveys.

Conclusions

Participant perspectives of the personal implications of kidney biopsy can be integrated into shared decision-making between clinicians and patients. Enhanced biopsy reports and interactions between nephrologists and pathologists could augment the management and prognostic value of kidney biopsies.

Plain-Language Summary

The utility of kidney biopsy is debated among clinicians, and patients' perspectives are even less explored. To address these gaps, we synthesized perspectives from clinicians and patient participants of the Kidney Precision Medicine Project (KPMP). Both before and after biopsy, clinicians were surveyed on how the procedure affected their clinical management, diagnosis, and prognosis. After biopsy, participants shared how the procedure affected their diagnosis, medication, and lifestyle changes. Clinicians and patients shared an appreciation for the biopsy's impact on medical management but diverged in their takeaways on diagnosis and prognosis. These findings highlight the need for greater collaboration between patients and clinicians, particularly as they navigate shared decision-making when considering kidney biopsy.

A Systems Nephrology Approach to Diabetic Kidney Disease Research and Practice

BACKGROUND

Diagnosis and staging of diabetic kidney disease (DKD) via the serial assessment of routine laboratory indices lacks the granularity required to resolve the heterogeneous disease mechanisms driving progression in the individual patient. A systems nephrology approach may help resolve mechanisms underlying this clinically apparent heterogeneity, paving a way for targeted treatment of DKD.

SUMMARY

Given the limited access to kidney tissue in routine clinical care of patients with DKD, data derived from renal tissue in preclinical model systems, including animal and in vitro models, can play a central role in the development of a targeted systems-based approach to DKD. Multi-centre prospective cohort studies, including the Kidney Precision Medicine Project (KPMP) and the European Nephrectomy Biobank (ENBiBA) project, will improve access to human diabetic kidney tissue for research purposes. Integration of diverse data domains from such initiatives including clinical phenotypic data, renal and retinal imaging biomarkers, histopathological and ultrastructural data, and an array of molecular omics (transcriptomics, proteomics, etc.) alongside multi-dimensional data from preclinical modelling offers exciting opportunities to unravel individual-level mechanisms underlying progressive DKD. The application of machine and deep learning approaches may particularly enhance insights derived from imaging and histopathological/ultrastructural data domains.

KEY MESSAGES

Integration of data from multiple model systems (in vitro, animal models, and patients) and from diverse domains (clinical phenotypic, imaging, histopathological/ultrastructural, and molecular omics) offers potential to create a precision medicine approach to DKD care wherein the right treatments are offered to the right patients at the right time.

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself-OME-Zarr-along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain-the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Early recognition and prevention of acute kidney injury in hospitalised children

Acute kidney injury is common in hospitalised children and is associated with poor patient outcomes. Once acute kidney injury occurs, effective therapies to improve patient outcomes or kidney recovery are scarce. Early identification of children at risk of acute kidney injury or at an early injury stage is essential to prevent progression and mitigate complications. Paediatric acute kidney injury is under-recognised by clinicians, which is a barrier to optimisation of inpatient care and follow-up. Acute kidney injury definitions rely on functional biomarkers (ie, serum creatinine and urine output) that are inadequate, since they do not account for biological variability, analytical issues, or physiological responses to volume depletion. Improved predictive tools and diagnostic biomarkers of kidney injury are needed for earlier detection. Novel strategies, including biomarker-guided care algorithms, machine-learning methods, and electronic alerts tied to clinical decision support tools, could improve paediatric acute kidney injury care. Clinical prediction models should be studied in different paediatric populations and acute kidney injury phenotypes. Research is needed to develop and test prevention strategies for acute kidney injury in hospitalised children, including care bundles and therapeutics.

Return of Results in Genomic Research Using Large-Scale or Whole Genome Sequencing: Toward a New Normal

Genome sequencing is increasingly used in research and integrated into clinical care. In the research domain, large-scale analyses, including whole genome sequencing with variant interpretation and curation, virtually guarantee identification of variants that are pathogenic or likely pathogenic and actionable. Multiple guidelines recommend that findings associated with actionable conditions be offered to research participants in order to demonstrate respect for autonomy, reciprocity, and participant interests in health and privacy. Some recommendations go further and support offering a wider range of findings, including those that are not immediately actionable. In addition, entities covered by the US Health Insurance Portability and Accountability Act (HIPAA) may be required to provide a participant's raw genomic data on request. Despite these widely endorsed guidelines and requirements, the implementation of return of genomic results and data by researchers remains uneven. This article analyzes the ethical and legal foundations for researcher duties to offer adult participants their interpreted results and raw data as the new normal in genomic research.

Defining the molecular correlate of arteriolar hyalinosis in kidney disease progression by integration of single cell transcriptomic analysis and pathology scoring

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 (TGFβ / 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 TGFβ 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.

Advances and prospects for the Human BioMolecular Atlas Program (HuBMAP)

The Human BioMolecular Atlas Program (HuBMAP) aims to create a multi-scale spatial atlas of the healthy human body at single-cell resolution by applying advanced technologies and disseminating resources to the community. As the HuBMAP moves past its first phase, creating ontologies, protocols and pipelines, this Perspective introduces the production phase: the generation of reference spatial maps of functional tissue units across many organs from diverse populations and the creation of mapping tools and infrastructure to advance biomedical research.

The Utility of Spatial Transcriptomics for Solid Organ Transplantation

Spatial transcriptomics (ST) measures and maps transcripts within intact tissue sections, allowing the visualization of gene activity within the spatial organization of complex biological systems. This review outlines advances in genomic sequencing technologies focusing on in situ sequencing-based ST, including applications in transplant and relevant nontransplant settings. We describe the experimental and analytical pipelines that underpin the current generation of spatial technologies. This context is important for understanding the potential role ST may play in expanding our knowledge, including in organ transplantation, and the important caveats/limitations when interpreting the vast data output generated by such methodological platforms.

Genome-wide Association Study for AKI

Key Points

Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI.

Background

Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood.

Methods

We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project.

Results

No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30).

Conclusions

AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.

An atlas of healthy and injured cell states and niches in the human kidney

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.

Advances and Emerging Medical Applications of Direct Mass Spectrometry Technologies for Tissue Analysis

Offering superb speed, chemical specificity, and analytical sensitivity, direct mass spectrometry (MS) technologies are highly amenable for the molecular analysis of complex tissues to aid in disease characterization and help identify new diagnostic, prognostic, and predictive markers. By enabling detection of clinically actionable molecular profiles from tissues and cells, direct MS technologies have the potential to guide treatment decisions and transform sample analysis within clinical workflows. In this review, we highlight recent health-related developments and applications of direct MS technologies that exhibit tangible potential to accelerate clinical research and disease diagnosis, including oncological and neurodegenerative diseases and microbial infections. We focus primarily on applications that employ direct MS technologies for tissue analysis, including MS imaging technologies to map spatial distributions of molecules in situ as well as handheld devices for rapid in vivo and ex vivo tissue analysis.

The chromatin landscape of healthy and injured cell types in the human kidney

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. However, comprehensive integration of gene expression with epigenetic features that define regulatory elements remains a significant challenge. We measured 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 established a comprehensive and spatially-anchored epigenomic atlas to define the kidney's active, silent, and regulatory accessible chromatin regions across the genome. Using this atlas, we noted distinct control of adaptive injury in different epithelial cell types. A proximal tubule cell transcription factor network of ELF3 , KLF6 , and KLF10 regulated the transition between health and injury, while in thick ascending limb cells this transition was regulated by NR2F1 . Further, combined perturbation of ELF3 , KLF6 , and KLF10 distinguished 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.

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself -- OME-Zarr -- along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

Conundrums of choice of 'normal' kidney tissue for single cell studies

PURPOSE OF REVIEW

Defining molecular changes in key kidney cell types across lifespan and in disease states is essential to understand the pathogenetic basis of disease progression and targeted therapies. Various single cell approaches are being applied to define disease associated molecular signatures. Key considerations include the choice of reference tissue or 'normal' for comparison to diseased human specimens and a benchmark reference atlas. We provide an overview of select single cell technologies, key considerations for experimental design, quality control, choices and challenges associated with assay type and source for reference tissue.

RECENT FINDINGS

Several initiatives including Kidney Precision Medicine Project, Human Biomolecular Molecular Atlas Project, Genitourinary Disease Molecular Anatomy Project, ReBuilding a Kidney consortium, Human Cell Atlas and Chan Zuckerburg Initiative are generating single cell atlases of 'normal' or disease kidney. Different sources of kidney tissue are used as reference. Signatures of injury, resident pathology and procurement associated biological and technical artifacts have been identified in human kidney reference tissue.

SUMMARY

Committing to a particular reference or 'normal' tissue has significant implications in interpretation of data from disease samples or in ageing. Voluntarily donated kidney tissue from healthy individuals is generally unfeasible. Having reference datasets for different types of 'normal' tissue can aid in mitigating the confounds of choice of reference tissue and sampling biases.

Overcoming barriers in the design and implementation of clinical trials for acute kidney injury: a report from the 2020 Kidney Disease Clinical Trialists meeting

Acute kidney injury (AKI) is a growing epidemic and is independently associated with increased risk of death, chronic kidney disease (CKD) and cardiovascular events. Randomized-controlled trials (RCTs) in this domain are notoriously challenging and many clinical studies in AKI have yielded inconclusive findings. Underlying this conundrum is the inherent heterogeneity of AKI in its etiology, presentation and course. AKI is best understood as a syndrome and identification of AKI subphenotypes is needed to elucidate the disease's myriad etiologies and to tailor effective prevention and treatment strategies. Conventional RCTs are logistically cumbersome and often feature highly selected patient populations that limit external generalizability and thus alternative trial designs should be considered when appropriate. In this narrative review of recent developments in AKI trials based on the Kidney Disease Clinical Trialists (KDCT) 2020 meeting, we discuss barriers to and strategies for improved design and implementation of clinical trials for AKI patients, including predictive and prognostic enrichment techniques, the use of pragmatic trials and adaptive trials.

Characterization of Glomerular and Tubulointerstitial Proteomes in a Case of Nonsteroidal Anti-Inflammatory Drug-Attributed Acute Kidney Injury: A Clinical Pathologic Molecular Correlation

The major goals of the Kidney Precision Medicine Project (KPMPP) are to establish a molecular atlas of the kidney in health and disease and improve our understanding of the molecular drivers of CKD and AKI. In this clinical-pathologic-molecular correlation, we describe the case of a 38-year-old woman without any history of CKD who underwent a research kidney biopsy in the setting of AKI suspected to be due to nonsteroidal anti-inflammatory use after cesarean section delivery. The participant's histopathology was consistent with mild acute tubular injury, without significant interstitial fibrosis or tubular atrophy. This diagnosis was supported by analysis of the glomerular and tubulointerstitial proteomes. The proteomic interrogation revealed a molecular landscape that demonstrated differences in kidney prostaglandin synthesis that may be in response to nonsteroidal anti-inflammatory drugs and signs of intrarenal inflammation and fibrosis that were not evident by histopathology alone.

Next-Generation Morphometry for pathomics-data mining in histopathology

Pathology diagnostics relies on the assessment of morphology by trained experts, which remains subjective and qualitative. Here we developed a framework for large-scale histomorphometry (FLASH) performing deep learning-based semantic segmentation and subsequent large-scale extraction of interpretable, quantitative, morphometric features in non-tumour kidney histology. We use two internal and three external, multi-centre cohorts to analyse over 1000 kidney biopsies and nephrectomies. By associating morphometric features with clinical parameters, we confirm previous concepts and reveal unexpected relations. We show that the extracted features are independent predictors of long-term clinical outcomes in IgA-nephropathy. We introduce single-structure morphometric analysis by applying techniques from single-cell transcriptomics, identifying distinct glomerular populations and morphometric phenotypes along a trajectory of disease progression. Our study provides a concept for Next-generation Morphometry (NGM), enabling comprehensive quantitative pathology data mining, i.e., pathomics.

Genetics of Kidney Disease: The Unexpected Role of Rare Disorders

Hundreds of different genetic causes of chronic kidney disease are now recognized, and while individually rare, taken together they are significant contributors to both adult and pediatric diseases. Traditional genetics approaches relied heavily on the identification of large families with multiple affected members and have been fundamental to the identification of genetic kidney diseases. With the increased utilization of massively parallel sequencing and improvements to genotype imputation, we can analyze rare variants in large cohorts of unrelated individuals, leading to personalized care for patients and significant research advancements. This review evaluates the contribution of rare disorders to patient care and the study of genetic kidney diseases and highlights key advancements that utilize new techniques to improve our ability to identify new gene-disease associations.

Diabetes Management in Chronic Kidney Disease: A Consensus Report by the American Diabetes Association (ADA) and Kidney Disease: Improving Global Outcomes (KDIGO)

People with diabetes and chronic kidney disease (CKD) are at high risk for kidney failure, atherosclerotic cardiovascular disease, heart failure, and premature mortality. Recent clinical trials support new approaches to treat diabetes and CKD. The 2022 American Diabetes Association (ADA) Standards of Medical Care in Diabetes and the Kidney Disease: Improving Global Outcomes (KDIGO) 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease each provide evidence-based recommendations for management. A joint group of ADA and KDIGO representatives reviewed and developed a series of consensus statements to guide clinical care from the ADA and KDIGO guidelines. The published guidelines are aligned in the areas of CKD screening and diagnosis, glycemia monitoring, lifestyle therapies, treatment goals, and pharmacologic management. Recommendations include comprehensive care in which pharmacotherapy that is proven to improve kidney and cardiovascular outcomes is layered on a foundation of healthy lifestyle. Consensus statements provide specific guidance on use of renin-angiotensin system inhibitors, metformin, sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and a nonsteroidal mineralocorticoid receptor antagonist. These areas of consensus provide clear direction for implementation of care to improve clinical outcomes of people with diabetes and CKD.

Urinary single-cell sequencing captures kidney injury and repair processes in human acute kidney injury

Acute kidney injury (AKI) is a major health issue, the outcome of which depends primarily on damage and reparative processes of tubular epithelial cells. Mechanisms underlying AKI remain incompletely understood, specific therapies are lacking and monitoring the course of AKI in clinical routine is confined to measuring urine output and plasma levels of filtration markers. Here we demonstrate feasibility and potential of a novel approach to assess the cellular and molecular dynamics of AKI by establishing a robust urine-to-single cell RNA sequencing (scRNAseq) pipeline for excreted kidney cells via flow cytometry sorting. We analyzed 42,608 single cell transcriptomes of 40 urine samples from 32 patients with AKI and compared our data with reference material from human AKI post-mortem biopsies and published mouse data. We demonstrate that tubular epithelial cells transcriptomes mirror kidney pathology and reflect distinct injury and repair processes, including oxidative stress, inflammation, and tissue rearrangement. We also describe an AKI-specific abundant urinary excretion of adaptive progenitor-like cells. Thus, single cell transcriptomics of kidney cells excreted in urine provides noninvasive, unprecedented insight into cellular processes underlying AKI, thereby opening novel opportunities for target identification, AKI sub-categorization, and monitoring of natural disease course and interventions.

Present and future directions in diabetic kidney disease

Diabetic kidney disease (DKD) is the leading cause of kidney failure and is associated with substantial risk of cardiovascular disease, morbidity, and mortality. Traditionally, DKD prevention and management have focused on addressing hyperglycemia, hypertension, obesity, and renin-angiotensin system activation as important risk factors for disease. Over the last decade, sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists have been shown to meaningfully reduce risk of diabetes-related kidney and cardiovascular complications. Additional agents demonstrating benefit in DKD such as non-steroidal mineralocorticoid receptor antagonists and endothelin A receptor antagonists are further contributing to the growing arsenal of DKD therapies. With the availability of greater therapeutic options comes the opportunity to individually optimize DKD prevention and management. Novel applications of transcriptomic, proteomic, and metabolomic/lipidomic technologies, as well as use of artificial intelligence and reinforced learning methods through consortia such as the Kidney Precision Medicine Project and focused studies in established cohorts hold tremendous promise for advancing our understanding and treatment of DKD. Specifically, enhanced understanding of the molecular mechanisms underlying DKD pathophysiology may allow for the identification of new mechanism-based DKD subtypes and the development and implementation of targeted therapies. Implementation of personalized care approaches has the potential to revolutionize DKD care.

Diabetes management in chronic kidney disease: a consensus report by the American Diabetes Association (ADA) and Kidney Disease: Improving Global Outcomes (KDIGO)

People with diabetes and chronic kidney disease (CKD) are at high risk for kidney failure, atherosclerotic cardiovascular disease, heart failure, and premature mortality. Recent clinical trials support new approaches to treat diabetes and CKD. The 2022 American Diabetes Association (ADA) Standards of Medical Care in Diabetes and the Kidney Disease: Improving Global Outcomes (KDIGO) 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease each provide evidence-based recommendations for management. A joint group of ADA and KDIGO representatives reviewed and developed a series of consensus statements to guide clinical care from the ADA and KDIGO guidelines. The published guidelines are aligned in the areas of CKD screening and diagnosis, glycemia monitoring, lifestyle therapies, treatment goals, and pharmacologic management. Recommendations include comprehensive care in which pharmacotherapy that is proven to improve kidney and cardiovascular outcomes is layered on a foundation of healthy lifestyle. Consensus statements provide specific guidance on use of renin-angiotensin system inhibitors, metformin, sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide 1 receptor agonists, and a nonsteroidal mineralocorticoid receptor antagonist. These areas of consensus provide clear direction for implementation of care to improve clinical outcomes of people with diabetes and CKD.

Novel Treatment Paradigms: Focal Segmental Glomerulosclerosis

Focal segmental glomerulosclerosis (FSGS) is a histologic pattern of injury defined by the presence of sclerosis in some (segmental) of certain glomeruli (focal). On electron microscopy, it is characterized by a variable degree of podocyte foot process effacement and gaps in the coverage of the glomerular basement membrane. The pattern of injury occurs when podocytes, highly differentiated cells with limited regenerative capacity, are reduced in number. The heterogeneity in underlying causes of podocyte loss results in equally variable clinical phenotypes. Recent work acknowledging advances in defining the genetic and immunologic basis of disease has redefined the classification of FSGS. Unprecedented clinical trial activity and efficacy of repurposed agents presents hope for improved therapeutic options. This minireview summarizes recent advances with a focus on novel treatment paradigms in FSGS.

The Michigan O'Brien Kidney Research Center: transforming translational kidney research through systems biology

Research on kidney diseases is being transformed by the rapid expansion and innovations in omics technologies. The analysis, integration, and interpretation of big data, however, have been an impediment to the growing interest in applying these technologies to understand kidney function and failure. Targeting this urgent need, the University of Michigan O'Brien Kidney Translational Core Center (MKTC) and its Administrative Core established the Applied Systems Biology Core. The Core provides need-based support for the global kidney community centered on enabling incorporation of systems biology approaches by creating web-based, user-friendly analytic and visualization tools, like Nephroseq and Nephrocell, guiding with experimental design, and processing, analysis, and integration of large data sets. The enrichment core supports systems biology education and dissemination through workshops, seminars, and individualized training sessions. Meanwhile, the Pilot and Feasibility Program of the MKTC provides pilot funding to both early-career and established investigators new to the field, to integrate a systems biology approach into their research projects. The relevance and value of the portfolio of training and services offered by MKTC are reflected in the expanding community of young investigators, collaborators, and users accessing resources and engaging in systems biology-based kidney research, thereby motivating MKTC to persevere in its mission to serve the kidney research community by enabling access to state-of-the-art data sets, tools, technologies, expertise, and learning opportunities for transformative basic, translational, and clinical studies that will usher in solutions to improve the lives of people impacted by kidney disease.

Principles of human and mouse nephron development

The mechanisms underlying kidney development in mice and humans is an area of intense study. Insights into kidney organogenesis have the potential to guide our understanding of the origin of congenital anomalies and enable the assembly of genetic diagnostic tools. A number of studies have delineated signalling nodes that regulate positional identities and cell fates of nephron progenitor and precursor cells, whereas cross-species comparisons have markedly enhanced our understanding of conserved and divergent features of mammalian kidney organogenesis. Greater insights into the complex cellular movements that occur as the proximal-distal axis is established have challenged our understanding of nephron patterning and provided important clues to the elaborate developmental context in which human kidney diseases can arise. Studies of kidney development in vivo have also facilitated efforts to recapitulate nephrogenesis in kidney organoids in vitro, by providing a detailed blueprint of signalling events, cell movements and patterning mechanisms that are required for the formation of correctly patterned nephrons and maturation of physiologically functional apparatus that are responsible for maintaining human health.

Gasdermin D-deficient mice are hypersensitive to acute kidney injury

Signaling pathways of regulated necrosis, such as necroptosis and ferroptosis, contribute to acute kidney injury (AKI), but the role of pyroptosis is unclear. Pyroptosis is mediated by the pore-forming protein gasdermin D (GSDMD). Here, we report a specific pattern of GSDMD-protein expression in the peritubular compartment of mice that underwent bilateral ischemia and reperfusion injury (IRI). Along similar lines, the GSDMD-protein expression in whole kidney lysates increased during the first 84 h following cisplatin-induced AKI. Importantly, unlike whole kidney lysates, no GSDMD-protein expression was detectable in isolated kidney tubules. In IRI and cisplatin-induced AKI, GSDMD-deficient mice exhibited hypersensitivity to injury as assessed by tubular damage, elevated markers of serum urea, and serum creatinine. This hypersensitivity was reversed by a combined deficiency of GSDMD and the necroptosis mediator mixed lineage kinase domain-like (MLKL). In conclusion, we demonstrate a non-cell autonomous role for GSDMD in protecting the tubular compartment from necroptosis-mediated damage in IRI.

UMOD Mutations in Chronic Kidney Disease in Taiwan

UMOD is the first identified and the most commonly mutated gene that causes autosomal dominant tubulointerstitial kidney disease (ADTKD). Recent studies have shown that ADTKD-UMOD is a relatively common cause of chronic kidney disease (CKD). However, the status of ADTKD-UMOD in Taiwan remains unknown. In this study, we identified three heterozygous UMOD missense variants, c.121T > C (p.Cys41Arg), c.179G > A (p.Gly60Asp), and c.817G > T (p.Val273Phe), in a total of 221 selected CKD families (1.36%). Two of these missense variants, p.Cys41Arg and p.Gly60Asp, have not been reported previously. In vitro studies showed that both uromodulin variants have defects in cell membrane trafficking and excretion to the culture medium. The structure model predicted altered disulfide bond formation in both variants, but only p.Gly60Asp was predicted to cause protein destabilization. Our findings extend the mutation spectrum and indicate that the ADTKD-UMOD contributed to a small but significant cause of CKD in the Taiwanese population.

Single-cell transcriptomics reveals common epithelial response patterns in human acute kidney injury

Background

Acute kidney injury (AKI) occurs frequently in critically ill patients and is associated with adverse outcomes. Cellular mechanisms underlying AKI and kidney cell responses to injury remain incompletely understood.

Methods

We performed single-nuclei transcriptomics, bulk transcriptomics, molecular imaging studies, and conventional histology on kidney tissues from 8 individuals with severe AKI (stage 2 or 3 according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria). Specimens were obtained within 1–2 h after individuals had succumbed to critical illness associated with respiratory infections, with 4 of 8 individuals diagnosed with COVID-19. Control kidney tissues were obtained post-mortem or after nephrectomy from individuals without AKI.

Results

High-depth single cell-resolved gene expression data of human kidneys affected by AKI revealed enrichment of novel injury-associated cell states within the major cell types of the tubular epithelium, in particular in proximal tubules, thick ascending limbs, and distal convoluted tubules. Four distinct, hierarchically interconnected injured cell states were distinguishable and characterized by transcriptome patterns associated with oxidative stress, hypoxia, interferon response, and epithelial-to-mesenchymal transition, respectively. Transcriptome differences between individuals with AKI were driven primarily by the cell type-specific abundance of these four injury subtypes rather than by private molecular responses. AKI-associated changes in gene expression between individuals with and without COVID-19 were similar.

Conclusions

The study provides an extensive resource of the cell type-specific transcriptomic responses associated with critical illness-associated AKI in humans, highlighting recurrent disease-associated signatures and inter-individual heterogeneity. Personalized molecular disease assessment in human AKI may foster the development of tailored therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01108-9.

A user-friendly tool for cloud-based whole slide image segmentation with examples from renal histopathology

Background

Image-based machine learning tools hold great promise for clinical applications in pathology research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often lack the programming experience required for the setup and use of these tools which often rely on the use of command line interfaces.

Methods

We have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis.

Results

By segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in three murine models.

Conclusions

Histo-Cloud is open source, accessible over the internet, and adaptable for segmentation of any histological structure regardless of stain.