Current kidney function parameters overestimate kidney tissue repair in reversible experimental kidney disease

Decoding pathology: the role of computational pathology in research and diagnostics

Traditional histopathology, characterized by manual quantifications and assessments, faces challenges such as low-throughput and inter-observer variability that hinder the introduction of precision medicine in pathology diagnostics and research. The advent of digital pathology allowed the introduction of computational pathology, a discipline that leverages computational methods, especially based on deep learning (DL) techniques, to analyze histopathology specimens. A growing body of research shows impressive performances of DL-based models in pathology for a multitude of tasks, such as mutation prediction, large-scale pathomics analyses, or prognosis prediction. New approaches integrate multimodal data sources and increasingly rely on multi-purpose foundation models. This review provides an introductory overview of advancements in computational pathology and discusses their implications for the future of histopathology in research and diagnostics.

Animal models to study cognitive impairment of chronic kidney disease

Mild cognitive impairment (MCI) is common in people with chronic kidney disease (CKD), and its prevalence increases with progressive loss of kidney function. MCI is characterized by a decline in cognitive performance greater than expected for an individual age and education level but with minimal impairment of instrumental activities of daily living. Deterioration can affect one or several cognitive domains (attention, memory, executive functions, language, and perceptual motor or social cognition). Given the increasing prevalence of kidney disease, more and more people with CKD will also develop MCI causing an enormous disease burden for these individuals, their relatives, and society. However, the underlying pathomechanisms are poorly understood, and current therapies mostly aim at supporting patients in their daily lives. This illustrates the urgent need to elucidate the pathogenesis and potential therapeutic targets and test novel therapies in appropriate preclinical models. Here, we will outline the necessary criteria for experimental modeling of cognitive disorders in CKD. We discuss the use of mice, rats, and zebrafish as model systems and present valuable techniques through which kidney function and cognitive impairment can be assessed in this setting. Our objective is to enable researchers to overcome hurdles and accelerate preclinical research aimed at improving the therapy of people with CKD and MCI.

Deep learning applications for kidney histology analysis

PURPOSE OF REVIEW

Nephropathology is increasingly incorporating computational methods to enhance research and diagnostic accuracy. The widespread adoption of digital pathology, coupled with advancements in deep learning, will likely transform our pathology practices. Here, we discuss basic concepts of deep learning, recent applications in nephropathology, current challenges in implementation and future perspectives.

RECENT FINDINGS

Deep learning models have been developed and tested in various areas of nephropathology, for example, predicting kidney disease progression or diagnosing diseases based on imaging and clinical data. Despite their promising potential, challenges remain that hinder a wider adoption, for example, the lack of prospective evidence and testing in real-world scenarios.

SUMMARY

Deep learning offers great opportunities to improve quantitative and qualitative kidney histology analysis for research and clinical nephropathology diagnostics. Although exciting approaches already exist, the potential of deep learning in nephropathology is only at its beginning and we can expect much more to come.

Discovery of 2,8-dihydroxyadenine in HUA patients with uroliths and biomarkers for its associated nephropathy

Currently, it is acknowledged that gout is caused by uric acid (UA). However, some studies have revealed no correlation between gout and UA levels, and growing evidence suggests that 2,8-dihydroxyadenine (2,8-DHA), whose structural formula is similar to UA but is less soluble, may induce gout. Hence, we hypothesized that uroliths from hyperuricemia (HUA) patients, which is closely associated with gout, may contain 2,8-DHA. In this study, 2,8-DHA in uroliths and serum of HUA patients were determined using HPLC. Moreover, bioinformatics was used to investigate the pathogenic mechanisms of 2,8-DHA nephropathy. Subsequently, a mouse model of 2,8-DHA nephropathy established by the gavage administration of adenine, as well as a model of injured HK-2 cells induced by 2,8-DHA were used to explore the pathogenesis of 2,8-DHA nephropathy. Interestingly, 2,8-DHA could readily deposit in the cortex of the renal tubules, and was found in the majority of these HUA patients. Additionally, the differentially expressed genes between 2,8-DHA nephropathy mice and control mice were found to be involved in inflammatory reactions. Importantly, CCL2 and IL-1β genes had the maximum degree, closeness, and betweenness centrality scores. The expressions of CCL2 and IL-1β genes were significantly increased in the serum of 24 HUA patients with uroliths, indicating that they may be significant factors for 2,8-DHA nephropathy. Further analysis illustrated that oxidative damage and inflammation were the crucial processes of 2,8-DHA renal injury, and CCL2 and IL-1β genes were verified to be essential biomarkers for 2,8-DHA nephropathy. These findings revealed further insights into 2,8-DHA nephropathy, and provided new ideas for its diagnosis and treatment.

Polyploid tubular cells: a shortcut to stress adaptation

Tubular epithelial cells (TCs) compose the majority of kidney parenchyma and play fundamental roles in maintaining homeostasis. Like other tissues, mostly immature TC with progenitor capabilities are able to replace TC lost during injury via clonal expansion and differentiation. In contrast, differentiated TC lack this capacity. However, as the kidney is frequently exposed to toxic injuries, evolution positively selected a response program that endows differentiated TC to maintain residual kidney function during kidney injury. Recently, we and others have described polyploidization of differentiated TC, a mechanism to augment the function of remnant TC after injury by rapid hypertrophy. Polyploidy is a condition characterized by >2 complete sets of chromosomes. Polyploid cells often display an increased functional capacity and are generally more resilient to stress as evidenced by being conserved across many plants and eukaryote species from flies to mammals. Here, we discuss the occurrence of TC polyploidy in different contexts and conditions and how this integrates into existing concepts of kidney cell responses to injury. Collectively, we aim at stimulating the acquisition of novel knowledge in the kidney field as well as accelerating the translation of this basic response mechanism to the clinical sphere.

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.

Impact of renal recovery on in-hospital and post-discharge mortality

OBJECTIVE

To verify the impact of renal recovery on mortality in non-critically ill patients with acute kidney injury.

METHOD

A prospective cohort study was carried out in a public hospital in the Federal District with patients with acute kidney injury admitted to a non-critical care unit. Renal recovery was assessed based on the ratio of serum creatinine to baseline creatinine and the patient was followed up for 6 months. Mortality was assessed during hospitalization and after discharge.

RESULTS

Of the 90 patients with hospital-acquired kidney injury, renal recovery was identified in 34.1% to 75% of cases, depending on the time of assessment, considering a follow-up period of up to 6 months. Recovery of renal function during follow-up had an impact on in-hospital mortality [95% CI 0.15 (0.003 - 0.73; p = 0019).

CONCLUSION

Recovery of renal function has been shown to be a protective factor for mortality in patients admitted to the non-critical care unit. Early identification of kidney damage and monitoring of physiological and laboratory variables proved to be fundamental in identifying the severity of the disease and reducing mortality.

CKD therapy to improve outcomes of immune-mediated glomerular diseases

The management of immunoglobulin A nephropathy, membranous nephropathy, lupus nephritis, anti-neutrophil cytoplasmic antibody-associated vasculitis, C3 glomerulonephritis, autoimmune podocytopathies and other immune-mediated glomerular disorders is focused on two major treatment goals, preventing overall mortality and the loss of kidney function. Since minimizing irreversible kidney damage best serves both goals, the management of immune-mediated kidney disorders must focus on the two central pathomechanisms of kidney function decline, i.e., controlling the underlying immune disease process (e.g. with immunotherapies) and controlling the non-immune mechanisms of chronic kidney disease (CKD) progression. Here we review the pathophysiology of these non-immune mechanisms of CKD progression and discuss non-drug and drug interventions to attenuate CKD progression in immune-mediated kidney disorders. Non-pharmacological interventions include reducing salt intake, normalizing body weight, avoiding superimposed kidney injuries, smoking cessation and regular physical activity. Approved drug interventions include inhibitors of the renin-angiotensin-aldosterone system and sodium-glucose cotransporter-2. Numerous additional drugs to improve CKD care are currently being tested in clinical trials. Here we discuss how and when to use these drugs in the different clinical scenarios of immune-mediated kidney diseases.

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.

The Role of Platelet-Derived Growth Factor in Focal Segmental Glomerulosclerosis

BACKGROUND

FSGS is the final common pathway to nephron loss in most forms of severe or progressive glomerular injury. Although podocyte injury initiates FSGS, parietal epithelial cells (PECs) are the main effectors. Because PDGF takes part in fibrotic processes, we hypothesized that the ligand PDGF-B and its receptor PDGFR- β participate in the origin and progression of FSGS.

METHODS

We challenged Thy1.1 transgenic mice, which express Thy1.1 in the podocytes, with anti-Thy1.1 antibody to study the progression of FSGS. We investigated the role of PDGF in FSGS using challenged Thy1.1 mice, 5/6 nephrectomized mice, Col4 -/- (Alport) mice, patient kidney biopsies, and primary murine PECs, and challenged Thy1.1 mice treated with neutralizing anti-PDGF-B antibody therapy.

RESULTS

The unchallenged Thy1.1 mice developed only mild spontaneous FSGS, whereas challenged mice developed progressive FSGS accompanied by a decline in kidney function. PEC activation, proliferation, and profibrotic phenotypic switch drove the FSGS. During disease, PDGF-B was upregulated in podocytes, whereas PDGFR- β was upregulated in PECs from both mice and patients with FSGS. Short- and long-term treatment with PDGF-B neutralizing antibody improved kidney function and reduced FSGS, PEC proliferation, and profibrotic activation. In vitro , stimulation of primary murine PECs with PDGF-B recapitulated in vivo findings with PEC activation and proliferation, which was inhibited by PDGF-B antibody or imatinib.

CONCLUSION

PDGF-B-PDGFR- β molecular crosstalk between podocytes and PECs drives glomerulosclerosis and the progression of FSGS.

PODCAST

This article contains a podcast at.

Role of endoplasmic reticulum stress and autophagy in the transition from acute kidney injury to chronic kidney disease

Acute kidney injury (AKI) and chronic kidney disease (CKD) are global health concerns with increasing rates in morbidity and mortality. Transition from AKI-to-CKD is common and requires awareness in the management of AKI survivors. AKI-to-CKD transition is a main risk factor for the development of cardiovascular disease and progression to end-stage kidney disease. The mechanisms driving AKI-to-CKD transition are being explored to identify potential molecular and cellular targets for renoprotective drug interventions. Endoplasmic reticulum (ER) stress and autophagy are involved in the process of AKI-to-CKD transition. Excessive ER stress results in the persistent activation of unfolded protein response, which is an underneath cause of kidney cell death. Moreover, ER stress modulates autophagy and vice-versa. Autophagy is a degradation defensive mechanism protecting cells from malfunction. However, the underlying pathological mechanism involved in this interplay in the context of AKI-to-CKD transition is still unclear. In this review, we discuss the crosstalk between ER stress and autophagy in AKI, AKI-to-CKD transition, and CKD progression. In addition, we explore possible therapeutic targets that can regulate ER stress and autophagy to prevent AKI-to-CKD transition to improve the long-term prognosis of AKI survivors.

Polyploid tubular cells and chronic kidney disease

Defective DNA repair drives chronic kidney disease (CKD), but mechanisms are unclear. Airik and colleagues use a genetic model of defective DNA repair mimicking karyomegalic nephritis, a form of CKD characterized by tubular epithelial cells (TEC) with large nuclei and tubulointerstitial nephritis. They show that DNA damage in TEC triggers endoreplication leading to polyploid TEC and CKD. Blocking endoreplication preserved kidney function, suggesting that DNA damage triggers CKD via TEC polyploidization, questioning the concept of G2/M-arrest.