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.

The Kidney Precision Medicine Project and Single-Cell Biology of the Injured Proximal Tubule.

Single-cell RNA sequencing (scRNA-seq) has led to major advances in our understanding of proximal tubule subtypes in health and disease. The proximal tubule serves essential functions in overall homeostasis, but pathologic or physiological perturbations can affect its transcriptomic signature and corresponding tasks. These alterations in proximal tubular cells are often described within a scRNA-seq atlas as cell states, which are pathophysiological subclassifications based on molecular and morphologic changes in a cell's response to that injury compared with its native state. This review describes the major cell states defined in the Kidney Precision Medicine Project's scRNA-seq atlas. The review then identifies the overlap between the Kidney Precision Medicine Project and other seminal works that may use different nomenclature or cluster proximal tubule cells at different resolutions to define cell state subtypes. The goal is for the reader to understand the key transcriptomic markers of important cellular injury and regeneration processes across this highly dynamic and evolving field.

miRNA and mRNA Signatures in Human Acute Kidney Injury Tissue.

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 recovery and progression to CKD. In particular, the regulatory role of miRNAs in AKI is poorly understood. miRNA and mRNA sequencing were performed on biobanked human kidney tissues obtained in the routine care of subjects with a diagnosis of AKI, minimal change disease, or without known kidney disease in nephrectomy tissue. mRNA analysis revealed that nephrectomy tissues exhibited an injury signature similar to that of AKI and not identified in minimal change disease samples. The transcriptomic signature of human AKI was enriched in pathways involved in cell adhesion, epithelial-to-mesenchymal transition, and cell cycle arrest (eg, CDH6, ITGB6, CDKN1A). In AKI, up-regulation of miR-146a, miR-155, miR-142, and miR-122 was associated with pathways involved in immune cell recruitment, inflammation, and epithelial-to-mesenchymal transition. miR-122 and miR-146 were associated with down-regulation of DDR2 and IGFBP6, which are genes involved in the recovery and progression of kidney disease. These data provide integrated miRNA signatures that complement mRNA and other epigenetic data available in kidney atlases.

Prognostic implications of unbiased molecular categorization in kidney disease.

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.

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.

A Precision Mixture Risk Model to Identify Adverse Drug Events in Subpopulations Using a Case-Crossover Design.

Despite the success of pharmacovigilance studies in detecting signals of adverse drug events (ADEs) from real-world data, the risks of ADEs in subpopulations warrant increased scrutiny to prevent them in vulnerable individuals. Recently, the case-crossover design has been implemented to leverage large-scale administrative claims data for ADE detection, while controlling both observed confounding effects and short-term fixed unobserved confounding effects. Additionally, as the case-crossover design only includes cases, subpopulations can be conveniently derived. In this manuscript, we propose a precision mixture risk model (PMRM) to identify ADE signals from subpopulations under the case-crossover design. The proposed model is able to identify signals from all ADE-subpopulation-drug combinations, while controlling for false discovery rate (FDR) and confounding effects. We applied the PMRM to an administrative claims data. We identified ADE signals in subpopulations defined by demographic variables, comorbidities, and detailed diagnosis codes. Interestingly, certain drugs were associated with a higher risk of ADE only in subpopulations, while these drugs had a neutral association with ADE in the general population. Additionally, the PMRM could control FDR at a desired level and had a higher probability to detect true ADE signals than the widely used McNemar's test. In conclusion, the PMRM is able to identify subpopulation-specific ADE signals from a tremendous number of ADE-subpopulation-drug combinations, while controlling for both FDR and confounding effects.

Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis.

The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.

The INGENIOUS trial: Impact of pharmacogenetic testing on adverse events in a pragmatic clinical trial.

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.

Cellular and molecular interrogation of kidney biopsy specimens.

PURPOSE OF REVIEW: Traditional histopathology of the kidney biopsy specimen has been an essential and successful tool for the diagnosis and staging of kidney diseases. However, it is likely that the full potential of the kidney biopsy has not been tapped so far. Indeed, there is now a concerted worldwide effort to interrogate kidney biopsy samples at the cellular and molecular levels with unprecedented rigor and depth. This review examines these novel approaches to study kidney biopsy specimens and highlights their potential to refine our understanding of the pathophysiology of kidney disease and lead to precision-based diagnosis and therapy. RECENT FINDINGS: Several consortia are now active at studying kidney biopsy samples from various patient cohorts with state-of-the art cellular and molecular techniques. These include advanced imaging approaches as well as deep molecular interrogation with tools such as epigenetics, transcriptomics, proteomics and metabolomics. The emphasis throughout is on rigor, reproducibility and quality control. SUMMARY: Although these techniques to study kidney biopsies are complementary, each on its own can yield novel ways to define and classify kidney disease. Therefore, great efforts are needed in order to generate an integrated output that can propel the diagnosis and treatment of kidney disease into the realm of precision medicine.

Spatial transcriptomics and the kidney.

PURPOSE OF REVIEW: The application of spatial transcriptomics technologies to the interrogation of kidney tissue is a burgeoning effort. These technologies share a common purpose in mapping both the expression of individual molecules and entire transcriptomic signatures of kidney cell types and structures. Such information is often superimposed upon a histologic image. The resulting datasets are readily merged with other imaging and transcriptomic techniques to establish a spatially anchored atlas of the kidney. This review provides an overview of the various spatial transcriptomic technologies and recent studies in kidney disease. Potential applications gleaned from the interrogation of other organ systems, but relative to the kidney, are also discussed. RECENT FINDINGS: Spatial transcriptomic technologies have enabled localization of whole transcriptome mRNA expression, correlation of mRNA to histology, measurement of in situ changes in expression across time, and even subcellular localization of transcripts within the kidney. These innovations continue to aid in the development of human cellular atlases of the kidney, the reclassification of disease, and the identification of important therapeutic targets. SUMMARY: Spatial localization of gene expression will complement our current understanding of disease derived from single cell RNA sequencing, histopathology, protein immunofluorescence, and electron microscopy. Although spatial technologies continue to evolve rapidly, their importance in the localization of disease signatures is already apparent. Further efforts are required to integrate whole transcriptome and subcellular expression signatures into the individualized assessment of human kidney disease.

Incidence and Importance of Calcium Deposition in Kidney Biopsy Specimens.

INTRODUCTION: Calcification on native kidney biopsy specimens is often noted by pathologists, but the consequence is unknown. METHODS: We searched the pathology reports in the Biopsy Biobank Cohort of Indiana for native biopsy specimens with calcification. RESULTS: Of the 4,364 specimens, 416 (9.8%) had calcification. We compared clinical and histopathology findings in those with calcification (n = 429) compared to those without calcification (n = 3,936). Patients with calcification were older, had more comorbidities, lower estimated glomerular filtration rates (eGFR), were more likely to have hyaline arteriosclerosis, interstitial fibrosis/tubular atrophy, and a primary pathologic diagnosis of acute tubular injury or acute tubular necrosis when compared to patients without calcification. Patients with calcium oxalate deposition alone, compared to calcium phosphate or mixed calcifications, had fewer comorbidities but were more likely to have a history of gastric bypass surgery or malabsorption and take vitamin D. In patients with two or more years of follow-up, multivariate analyses showed the presence of calcification (HR 0.59, 0.38-0.92, p = 0.02) and higher eGFR (HR 0.76, 0.73-0.79, p < 0.001), was associated with decreased likelihood of progressing to end-stage renal disease. The presence of calcification was also associated with a reduced slope/decline in eGFR compared to known biopsy and clinical risk factors for decline in kidney function. We hypothesized this was due to more recoverable acute kidney injury (AKI) and found more severe acute kidney injury network stage in patients with kidney calcification but also greater improvement over time. DISCUSSION/CONCLUSION: In summary, we demonstrated that calcification on kidney biopsy specimens was associated with a better prognosis than those without calcification due to the association with recoverable AKI.

Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data.

BACKGROUND: Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. METHODS: In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. RESULTS: We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. CONCLUSIONS: We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.

Clinical non-effectiveness of clopidogrel use for peripheral artery disease in patients with CYP2C19 polymorphisms: a systematic review.

PURPOSE: To conduct a systematic review to identify studies that assessed the association between CYP2C19 polymorphisms and clinical outcomes in peripheral artery disease (PAD) patients who took clopidogrel. METHODS: We systematically searched Ovid EMBASE, PubMed, and Web of Science from November 1997 (inception) to September 2020. We included observational studies evaluating how CYP2C19 polymorphism is associated with clopidogrel's effectiveness and safety among patients with PAD. We extracted relevant information details from eligible studies (e.g., study type, patient population, study outcomes). We used the Risk of Bias in Non-randomized Studies-of Interventions (ROBINS-I) Tool to assess the risk of bias for included observational studies. RESULTS: The outcomes of interest were the effectiveness and safety of clopidogrel. The effectiveness outcomes included clinical ineffectiveness (e.g., restenosis). The safety outcomes included bleeding and death related to the use of clopidogrel. We identified four observational studies with a sample size ranging from 50 to 278. Outcomes and comparison groups of the studies varied. Three studies (75%) had an overall low risk of bias. All included studies demonstrated that carrying CYP2C19 loss of function (LOF) alleles was significantly associated with reduced clinical effectiveness and safety of clopidogrel. CONCLUSIONS: Our systematic review showed an association between CYP2C19 LOF alleles and reduced functions of clopidogrel. The use of CYP2C19 testing in PAD patients prescribed clopidogrel may help improve the clinical outcomes. However, based on the limited evidence, there is a need for randomized clinical trials in PAD patients to test both the effectiveness and safety outcomes of clopidogrel.

A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project.

Comprehensive and spatially mapped molecular atlases of organs at a cellular level are a critical resource to gain insights into pathogenic mechanisms and personalized therapies for diseases. The Kidney Precision Medicine Project (KPMP) is an endeavor to generate three-dimensional (3-D) molecular atlases of healthy and diseased kidney biopsies by using multiple state-of-the-art omics and imaging technologies across several institutions. Obtaining rigorous and reproducible results from disparate methods and at different sites to interrogate biomolecules at a single-cell level or in 3-D space is a significant challenge that can be a futile exercise if not well controlled. We describe a "follow the tissue" pipeline for generating a reliable and authentic single-cell/region 3-D molecular atlas of human adult kidney. Our approach emphasizes quality assurance, quality control, validation, and harmonization across different omics and imaging technologies from sample procurement, processing, storage, shipping to data generation, analysis, and sharing. We established benchmarks for quality control, rigor, reproducibility, and feasibility across multiple technologies through a pilot experiment using common source tissue that was processed and analyzed at different institutions and different technologies. A peer review system was established to critically review quality control measures and the reproducibility of data generated by each technology before their being approved to interrogate clinical biopsy specimens. The process established economizes the use of valuable biopsy tissue for multiomics and imaging analysis with stringent quality control to ensure rigor and reproducibility of results and serves as a model for precision medicine projects across laboratories, institutions and consortia.

Large-scale, three-dimensional tissue cytometry of the human kidney: a complete and accessible pipeline.

The advent of personalized medicine has driven the development of novel approaches for obtaining detailed cellular and molecular information from clinical tissue samples. Tissue cytometry is a promising new technique that can be used to enumerate and characterize each cell in a tissue and, unlike flow cytometry and other single-cell techniques, does so in the context of the intact tissue, preserving spatial information that is frequently crucial to understanding a cell's physiology, function, and behavior. However, the wide-scale adoption of tissue cytometry as a research tool has been limited by the fact that published examples utilize specialized techniques that are beyond the capabilities of most laboratories. Here we describe a complete and accessible pipeline, including methods of sample preparation, microscopy, image analysis, and data analysis for large-scale three-dimensional tissue cytometry of human kidney tissues. In this workflow, multiphoton microscopy of unlabeled tissue is first conducted to collect autofluorescence and second-harmonic images. The tissue is then labeled with eight fluorescent probes, and imaged using spectral confocal microscopy. The raw 16-channel images are spectrally deconvolved into 8-channel images, and analyzed using the Volumetric Tissue Exploration and Analysis (VTEA) software developed by our group. We applied this workflow to analyze millimeter-scale tissue samples obtained from human nephrectomies and from renal biopsies from individuals diagnosed with diabetic nephropathy, generating a quantitative census of tens of thousands of cells in each. Such analyses can provide useful insights that can be linked to the biology or pathology of kidney disease. The approach utilizes common laboratory techniques, is compatible with most commercially-available confocal microscope systems and all image and data analysis is conducted using the VTEA image analysis software, which is available as a plug-in for ImageJ.

Targeting fibroblast growth factor 23-responsive pathways uncovers controlling genes in kidney mineral metabolism.

Fibroblast Growth Factor 23 (FGF23) is a bone-derived hormone that reduces kidney phosphate reabsorption and 1,25(OH)2 vitamin D synthesis via its required co-receptor alpha-Klotho. To identify novel genes that could serve as targets to control FGF23-mediated mineral metabolism, gene array and single-cell RNA sequencing were performed in wild type mouse kidneys. Gene array demonstrated that heparin-binding EGF-like growth factor (HBEGF) was significantly up-regulated following one-hour FGF23 treatment of wild type mice. Mice injected with HBEGF had phenotypes consistent with partial FGF23-mimetic activity including robust induction of Egr1, and increased Cyp24a1 mRNAs. Single cell RNA sequencing showed overlapping HBEGF and EGF-receptor expression mostly in the proximal tubule, and alpha-Klotho expression in proximal and distal tubule segments. In alpha-Klotho-null mice devoid of canonical FGF23 signaling, HBEGF injections significantly increased Egr1 and Cyp24a1 with correction of basally elevated Cyp27b1. Additionally, mice placed on a phosphate deficient diet to suppress FGF23 had endogenously increased Cyp27b1 mRNA, which was rescued in mice receiving HBEGF. In HEK293 cells with stable alpha-Klotho expression, FGF23 and HBEGF increased CYP24A1 mRNA expression. HBEGF, but not FGF23 bioactivity was blocked with EGF-receptor inhibition. Thus, our findings support that the paracrine/autocrine factor HBEGF could play novel roles in controlling genes downstream of FGF23 via targeting common signaling pathways.

Rationale and design of the Kidney Precision Medicine Project.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision-medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living-donor kidney biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomic analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for 10 years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network.

PURPOSE: A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS: The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS: Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION: IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.

In Situ Classification of Cell Types in Human Kidney Tissue Using 3D Nuclear Staining.

To understand the physiology and pathology of disease, capturing the heterogeneity of cell types within their tissue environment is fundamental. In such an endeavor, the human kidney presents a formidable challenge because its complex organizational structure is tightly linked to key physiological functions. Advances in imaging-based cell classification may be limited by the need to incorporate specific markers that can link classification to function. Multiplex imaging can mitigate these limitations, but requires cumulative incorporation of markers, which may lead to tissue exhaustion. Furthermore, the application of such strategies in large scale 3-dimensional (3D) imaging is challenging. Here, we propose that 3D nuclear signatures from a DNA stain, DAPI, which could be incorporated in most experimental imaging, can be used for classifying cells in intact human kidney tissue. We developed an unsupervised approach that uses 3D tissue cytometry to generate a large training dataset of nuclei images (NephNuc), where each nucleus is associated with a cell type label. We then devised various supervised machine learning approaches for kidney cell classification and demonstrated that a deep learning approach outperforms classical machine learning or shape-based classifiers. Specifically, a custom 3D convolutional neural network (NephNet3D) trained on nuclei image volumes achieved a balanced accuracy of 80.26%. Importantly, integrating NephNet3D classification with tissue cytometry allowed in situ visualization of cell type classifications in kidney tissue. In conclusion, we present a tissue cytometry and deep learning approach for in situ classification of cell types in human kidney tissue using only a DNA stain. This methodology is generalizable to other tissues and has potential advantages on tissue economy and non-exhaustive classification of different cell types.

Clinical, histopathologic and molecular features of idiopathic and diabetic nodular mesangial sclerosis in humans.

BACKGROUND: Idiopathic nodular mesangial sclerosis, also called idiopathic nodular glomerulosclerosis (ING), is a rare clinical entity with an unclear pathogenesis. The hallmark of this disease is the presence of nodular mesangial sclerosis on histology without clinical evidence of diabetes mellitus or other predisposing diagnoses. To achieve insights into its pathogenesis, we queried the clinical, histopathologic and transcriptomic features of ING and nodular diabetic nephropathy (DN). METHODS: All renal biopsy reports accessioned at Indiana University Health from 2001 to 2016 were reviewed to identify 48 ING cases. Clinical and histopathologic features were compared between individuals with ING and DN (n = 751). Glomeruli of ING (n = 5), DN (n = 18) and reference (REF) nephrectomy (n = 9) samples were isolated by laser microdissection and RNA was sequenced. Immunohistochemistry of proline-rich 36 (PRR36) protein was performed. RESULTS: ING subjects were frequently hypertensive (95.8%) with a smoking history (66.7%). ING subjects were older, had lower proteinuria and had less hyaline arteriolosclerosis than DN subjects. Butanoate metabolism was an enriched pathway in ING samples compared with either REF or DN samples. The top differentially expressed gene, PRR36, had increased expression in glomeruli 248-fold [false discovery rate (FDR) P = 5.93 × 10-6] compared with the REF and increased 109-fold (FDR P = 1.85 × 10-6) compared with DN samples. Immunohistochemistry revealed a reduced proportion of cells with perinuclear reaction in ING samples as compared to DN. CONCLUSIONS: Despite similar clinical and histopathologic characteristics in ING and DN, the uncovered transcriptomic signature suggests that ING has distinct molecular features from nodular DN. Further study is warranted to understand these relationships.