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.

The role of desmoglein-2 in kidney disease.

Desmosomes are multi-protein cell-cell adhesion structures supporting cell stability and mechanical stress resilience of tissues, best described in skin and heart. The kidney is exposed to various mechanical stimuli and stress, yet little is known about kidney desmosomes. In healthy kidneys, we found desmosomal proteins located at the apical-junctional complex in tubular epithelial cells. In four different animal models and patient biopsies with various kidney diseases, desmosomal components were significantly upregulated and partly miss-localized outside of the apical-junctional complexes along the whole lateral tubular epithelial cell membrane. The most upregulated component was desmoglein-2 (Dsg2). Mice with constitutive tubular epithelial cell-specific deletion of Dsg2 developed normally, and other desmosomal components were not altered in these mice. When challenged with different types of tubular epithelial cell injury (unilateral ureteral obstruction, ischemia-reperfusion, and 2,8-dihydroxyadenine crystal nephropathy), we found increased tubular epithelial cell apoptosis, proliferation, tubular atrophy, and inflammation compared to wild-type mice in all models and time points. In vitro, silencing DSG2 via siRNA weakened cell-cell adhesion in HK-2 cells and increased cell death. Thus, our data show a prominent upregulation of desmosomal components in tubular cells across species and diseases and suggest a protective role of Dsg2 against various injurious stimuli.

Semiautomated pipeline for quantitative analysis of heart histopathology.

BACKGROUND: Heart diseases are among the leading causes of death worldwide, many of which lead to pathological cardiomyocyte hypertrophy and capillary rarefaction in both patients and animal models, the quantification of which is both technically challenging and highly time-consuming. Here we developed a semiautomated pipeline for quantification of the size of cardiomyocytes and capillary density in cardiac histology, termed HeartJ, by generating macros in ImageJ, a broadly used, open-source, Java-based software. METHODS: We have used modified Gomori silver staining, which is easy to perform and digitize in high throughput, or Fluorescein-labeled lectin staining. The latter can be easily combined with other stainings, allowing additional quantitative analysis on the same section, e.g., the size of cardiomyocyte nuclei, capillary density, or single-cardiomyocyte protein expression. We validated the pipeline in a mouse model of cardiac hypertrophy induced by transverse aortic constriction, and in autopsy samples of patients with and without aortic stenosis. RESULTS: In both animals and humans, HeartJ-based histology quantification revealed significant hypertrophy of cardiomyocytes reflecting other parameters of hypertrophy and rarefaction of microvasculature and enabling the analysis of protein expression in individual cardiomyocytes. The analysis also revealed that murine and human cardiomyocytes had similar diameters in health and extent of hypertrophy in disease confirming the translatability of our murine cardiac hypertrophy model. HeartJ enables a rapid analysis that would not be feasible by manual methods. The pipeline has little hardware requirements and is freely available. CONCLUSIONS: In summary, our analysis pipeline can facilitate effective and objective quantitative histological analyses in preclinical and clinical heart samples.

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.

Reduction of Endothelial Glycocalyx on Peritubular Capillaries in Chronic Kidney Disease.

In chronic kidney disease (CKD), peritubular capillaries undergo anatomic and functional alterations, such as rarefaction and increased permeability. The endothelial glycocalyx (EG) is a carbohydrate-rich gel-like mesh, which covers the luminal surface of endothelial cells. It is involved in many regulatory functions of the endothelium, including vascular permeability. Herein, we investigated ultrastructural alterations of the EG in different murine CKD models. Fluorescence staining using different lectins with high affinity to components of the renal glycocalyx revealed a reduced binding to the endothelium in CKD in the animal models, and there were similar finding in human kidney specimens. Lanthanum Dysprosium Glycosamino Glycan adhesion staining technique was used to visualize the ultrastructure of the glycocalyx in transmission electron microscopy. This also enabled quantitative analyses, showing a significant reduction of the EG thickness and density. In addition, mRNA expression of proteins involved in glycocalyx biology, synthesis, and turnover (ie, syndecan 1 and glypican 1), which are main components of the glycocalyx, and exostosin 2, involved in the synthesis of the glycocalyx, were significantly up-regulated in endothelial cells isolated from murine CKD models. Visualization of glycocalyx using specific transmission electron microscopy analyses allows qualitative and quantitative analyses and revealed significant pathologic alterations in peritubular capillaries in CKD.

Improving unsupervised stain-to-stain translation using self-supervision and meta-learning.

Background: In digital pathology, many image analysis tasks are challenged by the need for large and time-consuming manual data annotations to cope with various sources of variability in the image domain. Unsupervised domain adaptation based on image-to-image translation is gaining importance in this field by addressing variabilities without the manual overhead. Here, we tackle the variation of different histological stains by unsupervised stain-to-stain translation to enable a stain-independent applicability of a deep learning segmentation model. Methods: We use CycleGANs for stain-to-stain translation in kidney histopathology, and propose two novel approaches to improve translational effectivity. First, we integrate a prior segmentation network into the CycleGAN for a self-supervised, application-oriented optimization of translation through semantic guidance, and second, we incorporate extra channels to the translation output to implicitly separate artificial meta-information otherwise encoded for tackling underdetermined reconstructions. Results: The latter showed partially superior performances to the unmodified CycleGAN, but the former performed best in all stains providing instance-level Dice scores ranging between 78% and 92% for most kidney structures, such as glomeruli, tubules, and veins. However, CycleGANs showed only limited performance in the translation of other structures, e.g. arteries. Our study also found somewhat lower performance for all structures in all stains when compared to segmentation in the original stain. Conclusions: Our study suggests that with current unsupervised technologies, it seems unlikely to produce "generally" applicable simulated stains.

The sodium-glucose co-transporter-2 inhibitor ertugliflozin modifies the signature of cardiac substrate metabolism and reduces cardiac mTOR signalling, endoplasmic reticulum stress and apoptosis.

AIM: To investigate cardiac signalling pathways connecting substrate utilization with left ventricular remodelling in a murine pressure overload model. METHODS: Cardiac hypertrophy was induced by transverse aortic constriction surgery in 20-week-old C57BL/6J mice treated with or without the sodium-glucose co-transporter 2 (SGLT2) inhibitor ertugliflozin (225 mg kg-1 chow diet) for 10 weeks. RESULTS: Ertugliflozin improved left ventricular function and reduced myocardial fibrosis. This occurred simultaneously with a fasting-like response characterized by improved glucose tolerance and increased ketone body concentrations. While cardiac insulin signalling was reduced in response to SGLT2 inhibition, AMP-activated protein kinase (AMPK) signalling was increased with induction of the fatty acid transporter cluster of differentiation 36 and phosphorylation of acetyl-CoA carboxylase (ACC). Further, enzymes responsible for ketone body catabolism (ß-hydroxybutyrate dehydrogenase, succinyl-CoA:3-oxoacid-CoA transferase and acetyl-CoA acetyltransferase 1) were induced by SGLT2 inhibition. Ertugliflozin led to more cardiac abundance of fatty acids, tricarboxylic acid cycle metabolites and ATP. Downstream mechanistic target of rapamycin (mTOR) pathway, relevant for protein synthesis, cardiac hypertrophy and adverse cardiac remodelling, was reduced by SGLT2 inhibition, with alleviation of endoplasmic reticulum (ER) stress and unfolded protein response (UPR) providing a potential mechanism for abundant reduced left ventricular apoptosis and fibrosis. CONCLUSION: SGLT2 inhibition reduced left ventricular fibrosis in a murine model of cardiac hypertrophy. Mechanistically, this was associated with reduced cardiac insulin and increased AMPK signalling as a potential mechanism for less cardiac mTOR activation with alleviation of downstream ER stress, UPR and apoptosis.

Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study.

BACKGROUND: Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable expertise, time, and effort. We aimed to analyse the utility of deep learning to preclassify histology of kidney allograft biopsies into three main broad categories (ie, normal, rejection, and other diseases) as a potential biopsy triage system focusing on transplant rejection. METHODS: We performed a retrospective, multicentre, proof-of-concept study using 5844 digital whole slide images of kidney allograft biopsies from 1948 patients. Kidney allograft biopsy samples were identified by a database search in the Departments of Pathology of the Amsterdam UMC, Amsterdam, Netherlands (1130 patients) and the University Medical Center Utrecht, Utrecht, Netherlands (717 patients). 101 consecutive kidney transplant biopsies were identified in the archive of the Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany. Convolutional neural networks (CNNs) were trained to classify allograft biopsies as normal, rejection, or other diseases. Three times cross-validation (1847 patients) and deployment on an external real-world cohort (101 patients) were used for validation. Area under the receiver operating characteristic curve (AUROC) was used as the main performance metric (the primary endpoint to assess CNN performance). FINDINGS: Serial CNNs, first classifying kidney allograft biopsies as normal (AUROC 0·87 [ten times bootstrapped CI 0·85-0·88]) and disease (0·87 [0·86-0·88]), followed by a second CNN classifying biopsies classified as disease into rejection (0·75 [0·73-0·76]) and other diseases (0·75 [0·72-0·77]), showed similar AUROC in cross-validation and deployment on independent real-world data (first CNN normal AUROC 0·83 [0·80-0·85], disease 0·83 [0·73-0·91]; second CNN rejection 0·61 [0·51-0·70], other diseases 0·61 [0·50-0·74]). A single CNN classifying biopsies as normal, rejection, or other diseases showed similar performance in cross-validation (normal AUROC 0·80 [0·73-0·84], rejection 0·76 [0·66-0·80], other diseases 0·50 [0·36-0·57]) and generalised well for normal and rejection classes in the real-world data. Visualisation techniques highlighted rejection-relevant areas of biopsies in the tubulointerstitium. INTERPRETATION: This study showed that deep learning-based classification of transplant biopsies could support pathological diagnostics of kidney allograft rejection. FUNDING: European Research Council; German Research Foundation; German Federal Ministries of Education and Research, Health, and Economic Affairs and Energy; Dutch Kidney Foundation; Human(e) AI Research Priority Area of the University of Amsterdam; and Max-Eder Programme of German Cancer Aid.

Multisystemic Cellular Tropism of SARS-CoV-2 in Autopsies of COVID-19 Patients.

Multiorgan tropism of SARS-CoV-2 has previously been shown for several major organs. We have comprehensively analyzed 25 different formalin-fixed paraffin-embedded (FFPE) tissues/organs from autopsies of fatal COVID-19 cases (n = 8), using histopathological assessment, detection of SARS-CoV-2 RNA using polymerase chain reaction and RNA in situ hybridization, viral protein using immunohistochemistry, and virus particles using transmission electron microscopy. SARS-CoV-2 RNA was mainly localized in epithelial cells across all organs. Next to lung, trachea, kidney, heart, or liver, viral RNA was also found in tonsils, salivary glands, oropharynx, thyroid, adrenal gland, testicles, prostate, ovaries, small bowel, lymph nodes, skin and skeletal muscle. Viral RNA was predominantly found in cells expressing ACE2, TMPRSS2, or both. The SARS-CoV-2 replicating RNA was also detected in these organs. Immunohistochemistry and electron microscopy were not suitable for reliable and specific SARS-CoV-2 detection in autopsies. These findings were validated using in situ hybridization on external COVID-19 autopsy samples (n = 9). Apart from the lung, correlation of viral detection and histopathological assessment did not reveal any specific alterations that could be attributed to SARS-CoV-2. In summary, SARS-CoV-2 and its replication could be observed across all organ systems, which co-localizes with ACE2 and TMPRSS2 mainly in epithelial but also in mesenchymal and endothelial cells. Apart from the respiratory tract, no specific (histo-)morphologic alterations could be assigned to the SARS-CoV-2 infection.

Non-invasive molecular imaging of kidney diseases.

In nephrology, differential diagnosis or assessment of disease activity largely relies on the analysis of glomerular filtration rate, urinary sediment, proteinuria and tissue obtained through invasive kidney biopsies. However, currently available non-invasive functional parameters, and most serum and urine biomarkers, cannot capture intrarenal molecular disease processes specifically. Moreover, although histopathological analyses of kidney biopsy samples enable the visualization of pathological morphological and molecular alterations, they only provide information about a small part of the kidney and do not allow longitudinal monitoring. These limitations not only hinder understanding of the dynamics of specific disease processes in the kidney, but also limit the targeting of treatments to active phases of disease and the development of novel targeted therapies. Molecular imaging enables non-invasive and quantitative assessment of physiological or pathological processes by combining imaging technologies with specific molecular probes. Here, we discuss current preclinical and clinical molecular imaging approaches in nephrology. Non-invasive visualization of the kidneys through molecular imaging can be used to detect and longitudinally monitor disease activity and can therefore provide companion diagnostics to guide clinical trials, as well as the safe and effective use of drugs.

Pro-cachectic factors link experimental and human chronic kidney disease to skeletal muscle wasting programs.

Skeletal muscle wasting is commonly associated with chronic kidney disease (CKD), resulting in increased morbidity and mortality. However, the link between kidney and muscle function remains poorly understood. Here, we took a complementary interorgan approach to investigate skeletal muscle wasting in CKD. We identified increased production and elevated blood levels of soluble pro-cachectic factors, including activin A, directly linking experimental and human CKD to skeletal muscle wasting programs. Single-cell sequencing data identified the expression of activin A in specific kidney cell populations of fibroblasts and cells of the juxtaglomerular apparatus. We propose that persistent and increased kidney production of pro-cachectic factors, combined with a lack of kidney clearance, facilitates a vicious kidney/muscle signaling cycle, leading to exacerbated blood accumulation and, thereby, skeletal muscle wasting. Systemic pharmacological blockade of activin A using soluble activin receptor type IIB ligand trap as well as muscle-specific adeno-associated virus-mediated downregulation of its receptor ACVR2A/B prevented muscle wasting in different mouse models of experimental CKD, suggesting that activin A is a key factor in CKD-induced cachexia. In summary, we uncovered a crosstalk between kidney and muscle and propose modulation of activin signaling as a potential therapeutic strategy for skeletal muscle wasting in CKD.

SARS-CoV-2 RNA screening in routine pathology specimens.

Virus detection methods are important to cope with the SARS-CoV-2 pandemics. Apart from the lung, SARS-CoV-2 was detected in multiple organs in severe cases. Less is known on organ tropism in patients developing mild or no symptoms, and some of such patients might be missed in symptom-indicated swab testing. Here, we tested and validated several approaches and selected the most reliable RT-PCR protocol for the detection of SARS-CoV-2 RNA in patients' routine diagnostic formalin-fixed and paraffin-embedded (FFPE) specimens available in pathology, to assess (i) organ tropism in samples from COVID-19-positive patients, (ii) unrecognized cases in selected tissues from negative or not-tested patients during a pandemic peak, and (iii) retrospectively, pre-pandemic lung samples. We identified SARS-CoV-2 RNA in seven samples from confirmed COVID-19 patients, in two gastric biopsies, one small bowel and one colon resection, one lung biopsy, one pleural resection and one pleural effusion specimen, while all other specimens were negative. In the pandemic peak cohort, we identified one previously unrecognized COVID-19 case in tonsillectomy samples. All pre-pandemic lung samples were negative. In conclusion, SARS-CoV-2 RNA detection in FFPE pathology specimens can potentially improve surveillance of COVID-19, allow retrospective studies, and advance our understanding of SARS-CoV-2 organ tropism and effects.

Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiased, reproducible, and efficient histopathologic analyses, which will require novel high-throughput tools. A deep learning technique, the convolutional neural network, is increasingly applied in pathology because of its high performance in tasks like histology segmentation. METHODS: We investigated use of a convolutional neural network architecture for accurate segmentation of periodic acid-Schiff-stained kidney tissue from healthy mice and five murine disease models and from other species used in preclinical research. We trained the convolutional neural network to segment six major renal structures: glomerular tuft, glomerulus including Bowman's capsule, tubules, arteries, arterial lumina, and veins. To achieve high accuracy, we performed a large number of expert-based annotations, 72,722 in total. RESULTS: Multiclass segmentation performance was very high in all disease models. The convolutional neural network allowed high-throughput and large-scale, quantitative and comparative analyses of various models. In disease models, computational feature extraction revealed interstitial expansion, tubular dilation and atrophy, and glomerular size variability. Validation showed a high correlation of findings with current standard morphometric analysis. The convolutional neural network also showed high performance in other species used in research-including rats, pigs, bears, and marmosets-as well as in humans, providing a translational bridge between preclinical and clinical studies. CONCLUSIONS: We developed a deep learning algorithm for accurate multiclass segmentation of digital whole-slide images of periodic acid-Schiff-stained kidneys from various species and renal disease models. This enables reproducible quantitative histopathologic analyses in preclinical models that also might be applicable to clinical studies.

Developmental stages of tertiary lymphoid tissue reflect local injury and inflammation in mouse and human kidneys.

Tertiary lymphoid tissues (TLTs) are inducible ectopic lymphoid tissues in chronic inflammatory states and function as sites of priming local immune responses. We previously demonstrated that aged but not young mice exhibited multiple TLTs after acute kidney injury and that TLTs were also detected in human aged and diseased kidneys. However, the forms of progression and the implication for kidney injury remain unclear. To clarify this we analyzed surgically resected kidneys from aged patients with or without chronic kidney disease as well as kidneys resected for pyelonephritis, and classified TLTs into three distinct developmental stages based on the presence of follicular dendritic cells and germinal centers. In injury-induced murine TLT models, the stages advanced with the extent of kidney injury, and decreased with dexamethasone accompanied with improvement of renal function, fibrosis and inflammation. Kidneys from aged patients with chronic kidney disease consistently exhibited more frequent and advanced stages of TLTs than those without chronic kidney disease. Kidneys of patients with pyelonephritis exhibited more frequent TLTs with more advanced stages than aged kidneys. Additionally, TLTs in both cohorts shared similar locations and components, suggesting that TLT formation may not be a disease-specific phenomenon but rather a common pathological process. Thus, our findings provide the insights into biological features of TLT in the kidney and implicate TLT stage as a potential marker reflecting local injury and inflammation.

Empagliflozin improves left ventricular diastolic function of db/db mice.

OBJECTIVES: Investigation of the effect of SGLT2 inhibition by empagliflozin on left ventricular function in a model of diabetic cardiomyopathy. BACKGROUND: SGLT2 inhibition is a new strategy to treat diabetes. In the EMPA-REG Outcome trial empagliflozin treatment reduced cardiovascular and overall mortality in patients with diabetes presumably due to beneficial cardiac effects, leading to reduced heart failure hospitalization. The relevant mechanisms remain currently elusive but might be mediated by a shift in cardiac substrate utilization leading to improved energetic supply to the heart. METHODS: We used db/db mice on high-fat western diet with or without empagliflozin treatment as a model of severe diabetes. Left ventricular function was assessed by pressure catheter with or without dobutamine stress. RESULTS: Treatment with empagliflozin significantly increased glycosuria, improved glucose metabolism, ameliorated left ventricular diastolic function and reduced mortality of mice. This was associated with reduced cardiac glucose concentrations and decreased calcium/calmodulin-dependent protein kinase (CaMKII) activation with subsequent less phosphorylation of the ryanodine receptor (RyR). No change of cardiac ketone bodies or branched-chain amino acid (BCAA) metabolites in serum was detected nor was cardiac expression of relevant catabolic enzymes for these substrates affected. CONCLUSIONS: In a murine model of severe diabetes empagliflozin-dependent SGLT2 inhibition improved diastolic function and reduced mortality. Improvement of diastolic function was likely mediated by reduced spontaneous diastolic sarcoplasmic reticulum (SR) calcium release but independent of changes in cardiac ketone and BCAA metabolism.

Crystal Clots as Therapeutic Target in Cholesterol Crystal Embolism.

RATIONALE: Cholesterol crystal embolism can be a life-threatening complication of advanced atherosclerosis. Pathophysiology and molecular targets for treatment are largely unknown. OBJECTIVE: We aimed to develop a new animal model of cholesterol crystal embolism to dissect the molecular mechanisms of cholesterol crystal (CC)-driven arterial occlusion, tissue infarction, and organ failure. METHODS AND RESULTS: C57BL/6J mice were injected with CC into the left kidney artery. Primary end point was glomerular filtration rate (GFR). CC caused crystal clots occluding intrarenal arteries and a dose-dependent drop in GFR, followed by GFR recovery within 4 weeks, that is, acute kidney disease. In contrast, the extent of kidney infarction was more variable. Blocking necroptosis using mixed lineage kinase domain-like deficient mice or necrostatin-1s treatment protected from kidney infarction but not from GFR loss because arterial obstructions persisted, identifying crystal clots as a primary target to prevent organ failure. CC involved platelets, neutrophils, fibrin, and extracellular DNA. Neutrophil depletion or inhibition of the release of neutrophil extracellular traps had little effects, but platelet P2Y12 receptor antagonism with clopidogrel, fibrinolysis with urokinase, or DNA digestion with recombinant DNase I all prevented arterial occlusions, GFR loss, and kidney infarction. The window-of-opportunity was <3 hours after CC injection. However, combining Nec-1s (necrostatin-1s) prophylaxis given 1 hour before and DNase I 3 hours after CC injection completely prevented kidney failure and infarcts. In vitro, CC did not directly induce plasmatic coagulation but induced neutrophil extracellular trap formation and DNA release mainly from kidney endothelial cells, neutrophils, and few from platelets. CC induced ATP release from aggregating platelets, which increased fibrin formation in a DNase-dependent manner. CONCLUSIONS: CC embolism causes arterial obstructions and organ failure via the formation of crystal clots with fibrin, platelets, and extracellular DNA as critical components. Therefore, our model enables to unravel the pathogenesis of the CC embolism syndrome as a basis for both prophylaxis and targeted therapy.

Dysregulated mesenchymal PDGFR-ß drives kidney fibrosis.

Kidney fibrosis is characterized by expansion and activation of platelet-derived growth factor receptor-ß (PDGFR-ß)-positive mesenchymal cells. To study the consequences of PDGFR-ß activation, we developed a model of primary renal fibrosis using transgenic mice with PDGFR-ß activation specifically in renal mesenchymal cells, driving their pathological proliferation and phenotypic switch toward myofibroblasts. This resulted in progressive mesangioproliferative glomerulonephritis, mesangial sclerosis, and interstitial fibrosis with progressive anemia due to loss of erythropoietin production by fibroblasts. Fibrosis induced secondary tubular epithelial injury at later stages, coinciding with microinflammation, and aggravated the progression of hypertensive and obstructive nephropathy. Inhibition of PDGFR activation reversed fibrosis more effectively in the tubulointerstitium compared to glomeruli. Gene expression signatures in mice with PDGFR-ß activation resembled those found in patients. In conclusion, PDGFR-ß activation alone is sufficient to induce progressive renal fibrosis and failure, mimicking key aspects of chronic kidney disease in humans. Our data provide direct proof that fibrosis per se can drive chronic organ damage and establish a model of primary fibrosis allowing specific studies targeting fibrosis progression and regression.

A collagen-binding protein enables molecular imaging of kidney fibrosis in vivo.

Pathological deposition of collagen is a hallmark of kidney fibrosis. To illustrate this process we employed multimodal optical imaging to visualize and quantify collagen deposition in murine models of kidney fibrosis (ischemia-reperfusion or unilateral ureteral obstruction) using the collagen-binding adhesion protein CNA35. For in vivo imaging, we used hybrid computed tomography-fluorescence molecular tomography and CNA35 labeled with the near-infrared fluorophore Cy7. Upon intravenous injection, CNA35-Cy7 accumulation was significantly higher in fibrotic compared to non-fibrotic kidneys. This difference was not detected for a non-specific scrambled version of CNA35-Cy7. Ex vivo, on kidney sections of mice and patients with renal fibrosis, CNA35-FITC co-localized with fibrotic collagen type I and III, but not with the basement membrane collagen type IV. Following intravenous injection, CNA35-FITC bound to both interstitial and perivascular fibrotic areas. In line with this perivascular accumulation, we observed significant perivascular fibrosis in the mouse models and in biopsy sections from patients with chronic kidney disease using computer-based morphometry quantification. Thus, molecular imaging of collagen using CNA35 enabled specific non-invasive quantification of kidney fibrosis. Collagen imaging revealed significant perivascular fibrosis as a consistent component next to the more commonly assessed interstitial fibrosis. Our results lay the basis for further probe and protocol optimization towards the clinical translation of molecular imaging of kidney fibrosis.

Novel 3D analysis using optical tissue clearing documents the evolution of murine rapidly progressive glomerulonephritis.

Recent developments in optical tissue clearing have been difficult to apply for the morphometric analysis of organs with high cellular content and small functional structures, such as the kidney. Here, we establish combinations of genetic and immuno-labelling for single cell identification, tissue clearing and subsequent de-clarification for histoimmunopathology and transmission electron microscopy. Using advanced light microscopy and computational analyses, we investigated a murine model of crescentic nephritis, an inflammatory kidney disease typified by immune-mediated damage to glomeruli leading to the formation of hypercellular lesions and the rapid loss of kidney function induced by nephrotoxic serum. Results show a graded susceptibility of the glomeruli, significant podocyte loss and capillary injury. These effects are associated with activation of parietal epithelial cells and formation of glomerular lesions that may evolve and obstruct the kidney tubule, thereby explaining the loss of kidney function. Thus, our work provides new high-throughput endpoints for the analysis of complex tissues with single-cell resolution.