The promise of single-cell RNA sequencing for kidney disease investigation

The integration of scRNA-seq with microarray and in-vivo experiments facilitates a comprehensive elucidation of the molecular mechanisms underlying endothelial cell involvement in myocardial infarction

Myocardial infarction (MI) remains a major global health challenge, with endothelial cell function playing a crucial role in its progression. Advances in single-cell RNA sequencing (scRNA-seq) have enhanced our understanding of MI pathogenesis. This study aims to identify key genes within endothelial cells using scRNA-seq data and validate them through microarray data and in vivo models elucidate their role in the progression of MI. ScRNA-seq and microarray datasets relevant to MI were obtained from the GEO database. The Seurat package was used for data pre-processing and marker gene identification. Endothelial cell subpopulations were characterised using the hdWGCNA package, while intercellular interactions with fibroblasts were assessed using CellChat. Key genes were identified using comprehensive bioinformatics techniques such as scCODE, FindMarkers and protein-protein interaction (PPI) analysis, with validation from microarray data and in vivo experiments (WB, qPCR, immunofluorescence) in the model of MI. The analysis via scRNA-seq revealed 16 distinct cell clusters encompassing 7 unique cell types. Endothelial cells were categorized into 8 subpopulations by hdWGCNA; notably, Endothelial Cells-2 exhibited significant interactions with fibroblasts mediated by PDGF, PROS, and GAS signaling pathways. Integration of hdWGCNA, scCODE and FindMarkers, 10 key genes were identified, which were subsequently refined to DBP, NR1D1, and TEF following PPI analysis. These genes demonstrated marked downregulation the progression of MI, as confirmed by subsequent in vivo experiments. This study highlights the crucial roles of DBP, NR1D1, and TEF in MI development, providing a basis for future research on endothelial cell function in cardiovascular disease.

Inflammatory Cell Interactions in the Rotator Cuff Microenvironment: Insights From Single-Cell Sequencing

Rotator cuff injuries are a common cause of shoulder pain and dysfunction, with chronic inflammation complicating recovery. Recent advances in single-cell RNA sequencing (scRNA-seq) have provided new insights into the immune cell interactions within the rotator cuff microenvironment during injury and healing. This review focuses on the application of scRNA-seq to explore the roles of immune and nonimmune cells, including macrophages, T-cells, fibroblasts, and myofibroblasts, in driving inflammation, tissue repair, and fibrosis. We discuss how immune cell crosstalk and interactions with the extracellular matrix influence the progression of healing or pathology. Single-cell analyses have identified distinct molecular signatures associated with chronic inflammation, which may contribute to persistent tissue damage. Additionally, we highlight the therapeutic potential of targeting inflammation in rotator cuff repair, emphasizing personalized medicine approaches. Overall, the integration of scRNA-seq in studying rotator cuff injuries enhances our understanding of the cellular mechanisms involved and offers new perspectives for developing targeted treatments in regenerative medicine.

A comprehensive bioinformatics analysis identifies mitophagy biomarkers and potential Molecular mechanisms in hypertensive nephropathy

Mitophagy, the selective removal of damaged mitochondria, plays a critical role in kidney diseases, but its involvement in hypertensive nephropathy (HTN) is not well understood. To address this gap, we investigated mitophagy-related genes in HTN, identifying potential biomarkers for diagnosis and treatment. Transcriptome datasets from the Gene Expression Omnibus database were analyzed, resulting in the identification of seven mitophagy related differentially expressed genes (MR-DEGs), namely PINK1, ULK1, SQSTM1, ATG5, ATG12, MFN2, and UBA52. Further, we explored the correlation between MR-DEGs, immune cells, and inflammatory factors. The identified genes demonstrated a strong correlation with Mast cells, T-cells, TGFβ3, IL13, and CSF3. Machine learning techniques were employed to screen important genes, construct diagnostic models, and evaluate their accuracy. Consensus clustering divided the HTN patients into two mitophagy subgroups, with Subgroup 2 showing higher levels of immune cell infiltration and inflammatory factors. The functions of their proteins primarily involve complement, coagulation, lipids, and vascular smooth muscle contraction. Single-cell RNA sequencing revealed that mitophagy was most significant in proximal tubule cells (PTC) in HTN patients. Pseudotime analysis of PTC confirmed the expression changes observed in the transcriptome. Intercellular communication analysis suggested that mitophagy might regulate PTC's participation in intercellular crosstalk. Notably, specific transcription factors such as HNF4A, PPARA, and STAT3 showed strong correlations with mitophagy-related genes in PTC, indicating their potential role in modulating PTC function and influencing the onset and progression of HTN. This study offers a comprehensive analysis of mitophagy in HTN, enhancing our understanding of the pathogenesis, diagnosis, and treatment of HTN.

Single-Cell Analysis of Endothelial Cell Injury in IgA Nephropathy

BACKGROUND

The precise mechanisms responsible for renal injury in IgA nephropathy (IgAN) are not fully understood. Our study employed an extensive scRNA-seq analysis of kidney biopsies obtained from individuals with IgAN, with a specific emphasis on investigating the involvement of renal endothelial cells.

METHODS

We obtained data from the Gene Expression Omnibus database and conducted bioinformatics analysis, which included enrichment analysis of differentially expressed genes, AUCell analysis, and high-dimensional weighted gene co-expression network analysis (hdWGCNA). The results of these analyses were further validated using human renal glomerular endothelial cells (HRGECs).

RESULTS

The ScRNA-seq data uncovered notable variations in gene expression between IgAN and control kidney tissues. The enrichment analysis using AUCell demonstrated a high presence of adhesion molecules and components related to the mitogen-activated protein kinase signaling pathway within the renal endothelial cells. Furthermore, through hdWGCNA analysis, it was discovered that interleukin (IL)-6, Rac1, and cadherin exhibited associations with the renal endothelial cells. Stimulation of HRGECs with IL-6/IL-6 receptor resulted in a significant reduction in VE-cad expression while inhibiting Rac1 led to a substantial decrease in Rac1-GTP levels and an increase in VE-cad expression.

CONCLUSION

This study presents novel findings regarding the contribution of renal endothelial cells to the development of IgAN, as it demonstrates that IL-6 negatively regulates VE-cad expression in HRGECs via Rac1. These results highlight the significant involvement of renal endothelial cells in the pathogenesis of IgAN.

The advance of single cell transcriptome to study kidney immune cells in diabetic kidney disease

Diabetic kidney disease (DKD) is a prevalent microvascular complication of diabetes mellitus and a primary cause of end-stage renal disease (ESRD). Increasing studies suggest that immune cells are involved in regulating renal inflammation, which contributes to the progression of DKD. Compared with conventional methods, single-cell sequencing technology is more developed technique that has advantages in resolving cellular heterogeneity, parallel multi-omics studies, and discovering new cell types. ScRNA-seq helps researchers to analyze specifically gene expressions, signaling pathways, intercellular communication as well as their regulations in various immune cells of kidney biopsy and urine samples. It is still challenging to investigate the function of each cell type in the pathophysiology of kidney due to its complex and heterogeneous structure and function. Here, we discuss the application of single-cell transcriptomics in the field of DKD and highlight several recent studies that explore the important role of immune cells including macrophage, T cells, B cells etc. in DKD through scRNA-seq analyses. Through combing the researches of scRNA-seq on immune cells in DKD, this review provides novel perspectives on the pathogenesis and immune therapeutic strategy for DKD.

Omics Studies in CKD: Diagnostic Opportunities and Therapeutic Potential

Omics technologies have significantly advanced the prediction and therapeutic approaches for chronic kidney disease (CKD) by providing comprehensive molecular insights. This is a review of the current state and future prospects of integrating biomarkers into the clinical practice for CKD, aiming to improve patient outcomes by targeted therapeutic interventions. In fact, the integration of genomic, transcriptomic, proteomic, and metabolomic data has enhanced our understanding of CKD pathogenesis and identified novel biomarkers for an early diagnosis and targeted treatment. Advanced computational methods and artificial intelligence (AI) have further refined multi-omics data analysis, leading to more accurate prediction models for disease progression and therapeutic responses. These developments highlight the potential to improve CKD patient care with a precise and individualized treatment plan .

A Single-Cell Transcriptome Profiling of Triptolide-Induced Nephrotoxicity in Mice

Triptolide (TP), an active component isolated from the traditional Chinese herb Tripterygium wilfordii Hook F (TWHF), shows great promise for treating inflammation-related diseases. However, its potential nephrotoxic effects remain concerning. The mechanism underlying TP-induced nephrotoxicity is inadequately elucidated, particularly at single-cell resolution. Hence, single-cell RNA sequencing (scRNA-seq) of kidney tissues from control and TP-treated mice is performed to generate a thorough description of the renal cell atlas upon TP treatment. Heterogeneous responses of nephron epithelial cells are observed after TP exposure, attributing differential susceptibility of cell subtypes to excessive reactive oxygen species and increased inflammatory responses. Moreover, TP disrupts vascular function by activating endothelial cell immunity and damaging fibroblasts. Severe immune cell damage and the activation of pro-inflammatory Macro_C1 cells are also observed with TP treatment. Additionally, ligand-receptor crosstalk analysis reveals that the SPP1 (osteopontin) signaling pathway targeting Macro_C1 cells is triggered by TP treatment, which may promote the infiltration of Macro_C1 cells to exacerbate renal toxicity. Overall, this study provides comprehensive information on the transcriptomic profiles and cellular composition of TP-associated nephrotoxicity at single-cell resolution, which can strengthen the understanding of the pathogenesis of TP-induced nephrotoxicity and provide valuable clues for the discovery of new therapeutic targets to ameliorate TP-associated nephrotoxicity.

Single-cell lineage tracing approaches to track kidney cell development and maintenance

The kidney is a complex organ consisting of various cell types. Previous studies have aimed to elucidate the cellular relationships among these cell types in developing and mature kidneys using Cre-loxP-based lineage tracing. However, this methodology falls short of fully capturing the heterogeneous nature of the kidney, making it less than ideal for comprehensively tracing cellular progression during kidney development and maintenance. Recent technological advancements in single-cell genomics have revolutionized lineage tracing methods. Single-cell lineage tracing enables the simultaneous tracing of multiple cell types within complex tissues and their transcriptomic profiles, thereby allowing the reconstruction of their lineage tree with cell state information. Although single-cell lineage tracing has been successfully applied to investigate cellular hierarchies in various organs and tissues, its application in kidney research is currently lacking. This review comprehensively consolidates the single-cell lineage tracing methods, divided into 4 categories (clustered regularly interspaced short palindromic repeat [CRISPR]/CRISPR-associated protein 9 [Cas9]-based, transposon-based, Polylox-based, and native barcoding methods), and outlines their technical advantages and disadvantages. Furthermore, we propose potential future research topics in kidney research that could benefit from single-cell lineage tracing and suggest suitable technical strategies to apply to these topics.

Single-cell RNA sequencing in juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is one of the most common chronic inflammatory rheumatic diseases in children, with onset before age 16 and lasting for more than 6 weeks. JIA is a highly heterogeneous condition with various consequences for health and quality of life. For some JIA patients, early detection and intervention remain challenging. As a result, further investigation of the complex and unknown mechanisms underlying JIA is required. Advances in technology now allow us to describe the biological heterogeneity and function of individual cell populations in JIA. Through this review, we hope to provide novel ideas and potential targets for the diagnosis and treatment of JIA by summarizing the current findings of single-cell RNA sequencing studies and understanding how the major cell subsets drive JIA pathogenesis.

Proximal tubule cells in blood and urine as potential biomarkers for kidney disease biopsy

Early diagnosis and treatment are crucial for managing kidney disease, yet there remains a need to further explore pathological mechanisms and develop minimally invasive diagnostic methods. In this study, we employed single-cell RNA sequencing (scRNA-seq) to assess the cellular heterogeneity of kidney diseases. We analyzed gene expression profiles from renal tissue, peripheral blood mononuclear cells (PBMCs), and urine of four patients with nephritis. Our findings identified 12 distinct cell subsets in renal tissues and leukocytes. These subsets encompassed fibroblast cells, mesangial cells, epithelial cells, proximal tubule cells (PTCs), and six immune cell types: CD8+ T cells, macrophages, natural killer cells, dendritic cells, B cells, and neutrophils. Interestingly, PTCs were present in both PBMCs and urine samples but absent in healthy blood samples. Furthermore, several populations of fibroblast cells, mesangial cells, and PTCs exhibited pro-inflammatory or pro-apoptotic behaviors. Our gene expression analysis highlighted the critical role of inflammatory PTCs and fibroblasts in nephritis development and progression. These cells showed high expression of pro-inflammatory genes, which could have chemotactic and activating effect on neutrophils. This was substantiated by the widespread in these cells. Notably, the gene expression profiles of inflammatory PTCs in PBMCs, urine, and kidney tissues had high similarity. This suggests that PTCs in urine and PBMCs hold significant potential as alternative markers to invasive kidney biopsies.

Single-cell transcriptomic profiles in the pathophysiology within the microenvironment of early diabetic kidney disease

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, resulting in a huge socio-economic impact. Kidney is a highly complex organ and the pathogenesis underlying kidney organization involves complex cell-to-cell interaction within the heterogeneous kidney milieu. Advanced single-cell RNA sequencing (scRNA-seq) could reveal the complex architecture and interaction with the microenvironment in early DKD. We used scRNA-seq to investigate early changes in the kidney of db/m mice and db/db mice at the 14th week. Uniform Manifold Approximation and Projection were applied to classify cells into different clusters at a proper resolution. Weighted gene co-expression network analysis was used to identify the key molecules specifically expressed in kidney tubules. Information of cell-cell communication within the kidney was obtained using receptor-ligand pairing resources. In vitro model, human subjects, and co-detection by indexing staining were used to identify the pathophysiologic role of the hub genes in DKD. Among four distinct subsets of the proximal tubule (PT), lower percentages of proliferative PT and PT containing AQP4 expression (PT^AQP4+) in db/db mice induced impaired cell repair activity and dysfunction of renin-angiotensin system modulation in early DKD. We found that ferroptosis was involved in DKD progression, and ceruloplasmin acted as a central regulator of the induction of ferroptosis in PT^AQP4+. In addition, lower percentages of thick ascending limbs and collecting ducts with impaired metabolism function were also critical pathogenic features in the kidney of db/db mice. Secreted phosphoprotein 1 (SPP1) mediated pathogenic cross-talk in the tubular microenvironment, as validated by a correlation between urinary SPP1/Cr level and tubular injury. Finally, mesangial cell-derived semaphorin 3C (SEMA3C) further promoted endothelium-mesenchymal transition in glomerular endothelial cells through NRP1 and NRP2, and urinary SEMA3C/Cr level was positively correlated with glomerular injury. These data identified the hub genes involved in pathophysiologic changes within the microenvironment of early DKD.

Single-cell RNA sequencing for the study of kidney disease

The kidney is an important organ for maintaining normal metabolism and stabilising the internal environment, in which, the heterogeneity of cell types has hindered the progress in understanding the mechanisms underlying kidney disease. In recent years the application of single-cell RNA sequencing (scRNA-seq) in nephrology has developed rapidly. In this review, we summarized the technical platform related to scRNA-seq and the role of this technology in investigating the onset and development of kidney diseases, starting from several common kidney diseases (mainly including lupus nephritis, renal cell carcinoma, diabetic nephropathy and acute kidney injury), and provide a reference for the application of scRNA-seq in the study of kidney disease diagnosis, treatment and prognosis.

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.

Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney disease

Background

There is a growing public concern about diabetic kidney disease (DKD), which poses a severe threat to human health and life. It is important to discover noninvasive and sensitive immune-associated biomarkers that can be used to predict DKD development. ScRNA-seq and transcriptome sequencing were performed here to identify cell types and key genes associated with DKD.

Methods

Here, this study conducted the analysis through five microarray datasets of DKD (GSE131882, GSE1009, GSE30528, GSE96804, and GSE104948) from gene expression omnibus (GEO). We performed single-cell RNA sequencing analysis (GSE131882) by using CellMarker and CellPhoneDB on public datasets to identify the specific cell types and cell-cell interaction networks related to DKD. DEGs were identified from four datasets (GSE1009, GSE30528, GSE96804, and GSE104948). The regulatory relationship between DKD-related characters and genes was evaluated by using WGCNA analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) datasets were applied to define the enrichment of each term. Subsequently, immune cell infiltration between DKD and the control group was identified by using the “pheatmap” package, and the connection Matrix between the core genes and immune cell or function was illuminated through the “corrplot” package. Furthermore, RcisTarget and GSEA were conducted on public datasets for the analysis of the regulation relationship of key genes and it revealed the correlation between 3 key genes and top the 20 genetic factors involved in DKD. Finally, the expression of key genes between patients with 35 DKD and 35 healthy controls were examined by ELISA, and the relationship between the development of DKD rate and hub gene plasma levels was assessed in a cohort of 35 DKD patients. In addition, we carried out immunohistochemistry and western blot to verify the expression of three key genes in the kidney tissue samples we obtained.

Results

There were 8 cell types between DKD and the control group, and the number of connections between macrophages and other cells was higher than that of the other seven cell groups. We identified 356 different expression genes (DEGs) from the RNA-seq, which are enriched in urogenital system development, kidney development, platelet alpha granule, and glycosaminoglycan binding pathways. And WGCNA was conducted to construct 13 gene modules. The highest correlations module is related to the regulation of cell adhesion, positive regulation of locomotion, PI3K-Akt, gamma response, epithelial-mesenchymal transition, and E2F target signaling pathway. Then we overlapped the DEGs, WGCNA, and scRNA-seq, SLIT3, PDE1A and CFH were screened as the closely related genes to DKD. In addition, the findings of immunological infiltration revealed a remarkable positive link between T cells gamma delta, Macrophages M2, resting mast cells, and the three critical genes SLIT3, PDE1A, and CFH. Neutrophils were considerably negatively connected with the three key genes. Comparatively to healthy controls, DKD patients showed high levels of SLIT3, PDE1A, and CFH. Despite this, higher SLIT3, PDE1A, and CFH were associated with an end point rate based on a median follow-up of 2.6 years. And with the gradual deterioration of DKD, the expression of SLIT3, PDE1A, and CFH gradually increased.

Conclusions

The 3 immune-associated genes could be used as diagnostic markers and therapeutic targets of DKD. Additionally, we found new pathogenic mechanisms associated with immune cells in DKD, which might lead to therapeutic targets against these cells.

Single-cell transcriptomics: A new tool for studying diabetic kidney disease

The kidney is a complex organ comprising various functional partitions and special cell types that play important roles in maintaining homeostasis in the body. Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease and is an independent risk factor for cardiovascular diseases. Owing to the complexity and heterogeneity of kidney structure and function, the mechanism of DKD development has not been fully elucidated. Single-cell sequencing, including transcriptomics, epigenetics, metabolomics, and proteomics etc., is a powerful technology that enables the analysis of specific cell types and states, specifically expressed genes or pathways, cell differentiation trajectories, intercellular communication, and regulation or co-expression of genes in various diseases. Compared with other omics, RNA sequencing is a more developed technique with higher utilization of tissues or samples. This article reviewed the application of single-cell transcriptomics in the field of DKD and highlighted the key signaling pathways in specific tissues or cell types involved in the occurrence and development of DKD. The comprehensive understanding of single-cell transcriptomics through single-cell RNA-seq and single-nucleus RNA-seq will provide us new insights into the pathogenesis and treatment strategy of various diseases including DKD.

Applications of Transcriptomics in the Research of Antibody-Mediated Rejection in Kidney Transplantation: Progress and Perspectives

Antibody-mediated rejection (ABMR) is the major cause of chronic allograft dysfunction and loss in kidney transplantation. The immunological mechanisms of ABMR that have been featured in the latest studies indicate a highly complex interplay between various immune and nonimmune cell types. Clinical diagnostic standards have long been criticized for being arbitrary and the lack of accuracy. Transcriptomic approaches, including microarray and RNA sequencing of allograft biopsies, enable the identification of differential gene expression and the continuous improvement of diagnostics. Given that conventional bulk transcriptomic approaches only reflect the average gene expression but not the status at the single-cell level, thereby ignoring the heterogeneity of the transcriptome across individual cells, single-cell RNA sequencing is rising as a powerful tool to provide a high-resolution transcriptome map of immune cells, which allows the elucidation of the pathogenesis and may facilitate the development of novel strategies for clinical treatment of ABMR.

Role of T cells in ischemic acute kidney injury and repair

Ischemic acute kidney injury (AKI) is a common medical problem with significant mortality and morbidity, affecting a large number of patients globally. Ischemic AKI is associated with intrarenal inflammation as well as systemic inflammation; thus, the innate and adaptive immune systems are implicated in the pathogenesis of ischemic AKI. Among various intrarenal immune cells, T cells play major roles in the injury process and in the repair mechanism affecting AKI to chronic kidney disease transition. Importantly, T cells also participate in distant organ crosstalk during AKI, which affects the overall outcomes. Therefore, targeting T cell-mediated pathways and T cell-based therapies have therapeutic promise for ischemic AKI. Here, we review the major populations of kidney T cells and their roles in ischemic AKI.

Single-Nucleus Transcriptional Profiling of Chronic Kidney Disease after Cisplatin Nephrotoxicity

Cisplatin induces both acute and chronic nephrotoxicity during chemotherapy in patients with cancer. Presented here is the first study of single-nucleus RNA sequencing (snRNA-seq) of cisplatin-induced nephrotoxicity. Repeated low-dose cisplatin treatment (RLDC) led to decreases in renal function and kidney weight in mice at 9 weeks. The kidneys of these mice showed tubular degeneration and dilation. snRNA-seq identified 16 cell types and 17 cell clusters in these kidneys. Cluster-by-cluster comparison demonstrated cell type-specific changes in gene expression and identified a unique proximal tubule (PT) injury/repair cluster that co-expressed the injury marker kidney injury molecule-1 (Kim1) and the proliferation marker Ki-67. Compared with control, post-RLDC kidneys had 424 differentially expressed genes in PT cells, including tubular transporters and cytochrome P450 enzymes involved in lipid metabolism. snRNA-seq also revealed transcriptional changes in potential PT injury markers (Krt222, Eda2r, Ltbp2, and Masp1) and repair marker (Bex4). RLDC induced inflammation and proinflammatory cytokines (RelB, TNF-α, Il7, Ccl2, and Cxcl2) and the expression of fibrosis markers (fibronectin, collagen I, connective tissue growth factor, vimentin, and α-smooth muscle actin). Together, these results provide new insights into RLDC-induced transcriptional changes at the single-cell level that may contribute to the development of chronic kidney problems in patients with cancer after cisplatin chemotherapy.

Multidisciplinary approaches for elucidating genetics and molecular pathogenesis of urinary tract malformations

Advances in clinical diagnostics and molecular tools have improved our understanding of the genetically heterogeneous causes underlying congenital anomalies of kidney and urinary tract (CAKUT). However, despite a sharp incline of CAKUT reports in the literature within the past 2 decades, there remains a plateau in the genetic diagnostic yield that is disproportionate to the accelerated ability to generate robust genome-wide data. Explanations for this observation include (i) diverse inheritance patterns with incomplete penetrance and variable expressivity, (ii) rarity of single-gene drivers such that large sample sizes are required to meet the burden of proof, and (iii) multigene interactions that might produce either intra- (e.g., copy number variants) or inter- (e.g., effects in trans) locus effects. These challenges present an opportunity for the community to implement innovative genetic and molecular avenues to explain the missing heritability and to better elucidate the mechanisms that underscore CAKUT. Here, we review recent multidisciplinary approaches at the intersection of genetics, genomics, in vivo modeling, and in vitro systems toward refining a blueprint for overcoming the diagnostic hurdles that are pervasive in urinary tract malformation cohorts. These approaches will not only benefit clinical management by reducing age at molecular diagnosis and prompting early evaluation for comorbid features but will also serve as a springboard for therapeutic development.

Urine Single-Cell RNA Sequencing in Focal Segmental Glomerulosclerosis Reveals Inflammatory Signatures

INTRODUCTION

Individuals with focal segmental glomerular sclerosis (FSGS) typically undergo kidney biopsy only once, which limits the ability to characterize kidney cell gene expression over time.

METHODS

We used single-cell RNA sequencing (scRNA-seq) to explore disease-related molecular signatures in urine cells from subjects with FSGS. We collected 17 urine samples from 12 FSGS subjects and captured these as 23 urine cell samples. The inflammatory signatures from renal epithelial and immune cells were evaluated in bulk gene expression data sets of FSGS and minimal change disease (MCD) (The Nephrotic Syndrome Study Network [NEPTUNE] study) and an immune single-cell data set from lupus nephritis (Accelerating Medicines Partnership).

RESULTS

We identified immune cells, predominantly monocytes, and renal epithelial cells in the urine. Further analysis revealed 2 monocyte subtypes consistent with M1 and M2 monocytes. Shed podocytes in the urine had high expression of marker genes for epithelial-to-mesenchymal transition (EMT). We selected the 16 most highly expressed genes from urine immune cells and 10 most highly expressed EMT genes from urine podocytes as immune signatures and EMT signatures, respectively. Using kidney biopsy transcriptomic data from NEPTUNE, we found that urine cell immune signature and EMT signature genes were more highly expressed in FSGS biopsies compared with MCD biopsies.

CONCLUSION

The identification of monocyte subsets and podocyte expression signatures in the urine samples of subjects with FSGS suggests that urine cell profiling might serve as a diagnostic and prognostic tool in nephrotic syndrome. Furthermore, this approach may aid in the development of novel biomarkers and identifying personalized therapies targeting particular molecular pathways in immune cells and podocytes.

Altered DNA methylation in kidney disease: useful markers and therapeutic targets

Recent studies have demonstrated the association of altered epigenomes with lifestyle-related diseases. Epigenetic regulation promotes biological plasticity in response to environmental changes, and such plasticity may cause a ‘memory effect’, a sustained effect of transient treatment or an insult in the course of lifestyle-related diseases. We investigated the significance of epigenetic changes in several genes required for renal integrity, including the nephrin gene in podocytes, and the sustained anti-proteinuric effect, focusing on the transcription factor Krüppel-like factor 4 (KLF4). We further reported the role of the DNA repair factor lysine-acetyl transferase 5 (KAT5), which acts coordinately with KLF4, in podocyte injury caused by a hyperglycemic state through the acceleration of DNA damage and epigenetic alteration. In contrast, KAT5 in proximal tubular cells prevents acute kidney injury via glomerular filtration regulation by an epigenetic mechanism as well as promotion of DNA repair, indicating the cell type-specific action and roles of DNA repair factors. This review summarizes epigenetic alterations in kidney diseases, especially DNA methylation, and their utility as markers and potential therapeutic targets. Focusing on transcription factors or DNA damage repair factors associated with epigenetic changes may be meaningful due to their cell-specific expression or action. We believe that a better understanding of epigenetic alterations in the kidney will lead to the development of a novel strategy for chronic kidney disease (CKD) treatment.

Precision medicine for the treatment of glomerulonephritis: A bold goal but not yet a transformative achievement

The revolution in our ability to recognize the alterations in fundamental biology brought about by disease has fostered a renewed interest in precision or personalized medicine (“the right treatment, or diagnostic test, for the right patient at the right time”). This nascent field has been led by oncology, immune-hematology and infectious disease, but nephrology is catching up, and quickly. Specific forms of glomerulonephritis thought to represent specific “diseases” have been “downgraded” to “patterns of injury”. New entities have emerged through application of sophisticated molecular technologies; often embraced by the term “multi-omics”. Kidney biopsies are now interpreted by next generation imaging and machine learning. Many opportunities are manifest that will translate these remarkable developments into novel safe and effective treatment regimens for specific pathogenic pathways evoking glomerulonephritis and its progression to kidney failure. A few successes emboldens a positive look to the future. A sustained and highly collaborative engagement with this new paradigm will be required for this field, full of hope and high expectations, to realize its goal of transforming glomerular therapeutics from “one size fits all (or many)” to a true individualized management principle.

Recent advances in lineage tracing for the kidney

Lineage tracing was originally developed by developmental biologists to identify all progeny of a single cell during morphogenesis. More recently this approach has been applied to other fields, including organ homeostasis and recovery from injury. Modern lineage tracing techniques typically rely on reporter gene expression induced by cell-specific DNA recombination. There have been important scientific advances in the last 10 years that have impacted lineage tracing approaches, including intersectional genetics, optical clearing techniques, and the use of sequencing-based genomic lineage tracing. The latter combines CRISPR-Cas9-based genetic scarring with single-cell RNA-sequencing that, in theory, could allow comprehensive reconstruction of a lineage tree for an entire organism. This review summarizes recent advances in lineage tracing technologies and outlines potential applications for kidney research.

Single Cell Transcriptome Helps Better Understanding Crosstalk in Diabetic Kidney Disease

Years of research revealed that crosstalk extensively existed among kidney cells, cell factors and metabolites and played an important role in the development of diabetic kidney disease (DKD). In the last few years, single-cell RNA sequencing (scRNA-seq) technology provided new insight into cellular heterogeneity and genetic susceptibility regarding DKD at cell-specific level. The studies based on scRNA-seq enable a much deeper understanding of cell-specific processes such as interaction between cells. In this paper, we aim to review recent progress in single cell transcriptomic analyses of DKD, particularly highlighting on intra- or extra-glomerular cell crosstalk, cellular targets and potential therapeutic strategies for DKD.

Current Methodological Challenges of Single-Cell and Single-Nucleus RNA-Sequencing in Glomerular Diseases

Single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) allow transcriptomic profiling of thousands of cells from a renal biopsy specimen at a single-cell resolution. Both methods are promising tools to unravel the underlying pathophysiology of glomerular diseases. This review provides an overview of the technical challenges that should be addressed when designing single-cell transcriptomics experiments that focus on glomerulopathies. The isolation of glomerular cells from core needle biopsy specimens for single-cell transcriptomics remains difficult and depends upon five major factors. First, core needle biopsies generate little tissue material, and several samples are required to identify glomerular cells. Second, both fresh and frozen tissue samples may yield glomerular cells, although every experimental pipeline has different (dis)advantages. Third, enrichment for glomerular cells in human tissue before single-cell analysis is challenging because no effective standardized pipelines are available. Fourth, the current warm cell-dissociation protocols may damage glomerular cells and induce transcriptional artifacts, which can be minimized by using cold dissociation techniques at the cost of less efficient cell dissociation. Finally, snRNA-seq methods may be superior to scRNA-seq in isolating glomerular cells; however, the efficacy of snRNA-seq on core needle biopsy specimens remains to be proven. The field of single-cell omics is rapidly evolving, and the integration of these techniques in multiomics assays will undoubtedly create new insights in the complex pathophysiology of glomerular diseases.

Single-Cell Sequencing to Identify Six Heat Shock Protein (HSP) Genes-Mediated Progression Subtypes of Clear Cell Renal Cell Carcinoma

Background

Heat shock proteins (HSPs) are widely involved in tumor occurrence and development and are prognostic markers for multiple tumors. However, the role of HSPs in clear cell renal cell carcinoma (ccRCC) remains unclear.

Methods

We used Cytoscape to identify hub genes in the ccRCC single-cell sequencing data set from the Gene Expression Omnibus (GEO) data repository. We identified subtypes, C1 and C2, of The Cancer Genome Atlas (TCGA) patients based on the expression of hub genes using unsupervised consensus clustering. Principal component analysis (PCA) was used to verify the clustering differences, and Kaplan-Meier (K-M) estimate was used to verify the survival differences between C1 and C2 patients. We used TIMER 2.0 and CIBERSORT to evaluate the immune cell infiltration of HSP genes and C1 and C2 patients. The R package "pRRophetic" was used to evaluate the sensitivity in C1 and C2 patients to the four first-line treatment drugs.

Results

We identified six hub genes (HSP90AA1, HSPH1, HSPA1B, HSPA8, and HSPA1A) encoding HSP, five of which were significantly downregulated in TCGA group, and four had a protective effect on prognosis (p <0.05). Survival analysis showed that C1 patients had a better overall survival (p <0.001). TIMER 2.0 analysis showed that three HSP genes were significantly correlated with the infiltration of CD4+ T cells and CD4+ Th1 cells (|cor|>0.5, p<0.001). CIBERSORT showed significant differences in multiple infiltrating immune cells between C1 and C2 patients. Meanwhile, the expression of PD1 was significantly lower in C1 patients than in C2 patients, and the expression of PDL1 is the another way around. Drug sensitivity analysis showed that C1 patients were more sensitive to sorafenib, pazopanib, and axitinib (p <0.001).

Conclusion

Our research revealed two molecular subtypes of ccRCC based on 6 HSP genes, and revealed significant differences between the two subtypes in terms of clinical prognosis, immune infiltration, and drug sensitivity.

Deconvolution of Focal Segmental Glomerulosclerosis Pathophysiology Using Transcriptomics Techniques

Background

Focal segmental glomerulosclerosis is a histopathological pattern of renal injury and comprises a heterogeneous group of clinical conditions with different pathophysiology, clinical course, prognosis, and treatment. Nevertheless, subtype differentiation in clinical practice often remains challenging, and we currently lack reliable diagnostic, prognostic, and therapeutic biomarkers. The advent of new transcriptomics techniques in kidney research poses great potential in the identification of gene expression biomarkers that can be applied in clinical practice.

Summary

Transcriptomics techniques have been completely revolutionized in the last 2 decades, with the evolution from low-throughput reverse-transcription polymerase chain reaction and in situ hybridization techniques to microarrays and next-generation sequencing techniques, including RNA-sequencing and single-cell transcriptomics. The integration of human gene expression profiles with functional in vitro and in vivo experiments provides a deeper mechanistic insight into the candidate genes, which enable the development of novel-targeted therapies. The correlation of gene expression profiles with clinical outcomes of large patient cohorts allows for the development of clinically applicable biomarkers that can aid in diagnosis and predict prognosis and therapy response. Finally, the integration of transcriptomics with other "omics" modalities creates a holistic view on disease pathophysiology.

Key Messages

New transcriptomics techniques allow high-throughput gene expression profiling of patients with focal segmental glomerulosclerosis (FSGS). The integration with clinical outcomes and fundamental mechanistic studies enables the discovery of new clinically useful biomarkers that will finally improve the clinical outcome of patients with FSGS.

Single-cell biology to decode the immune cellular composition of kidney inflammation

Single-cell biology is transforming the ability of researchers to understand cellular signaling and identity across medical and biological disciplines. Especially for immune-mediated diseases, a single-cell look at immune cell subtypes, signaling, and activity might yield fundamental insights into the disease etiology, mechanisms, and potential therapeutic interventions. In this review, we highlight recent advances in the field of single-cell RNA profiling and their application to understand renal function in health and disease. With a focus on the immune system, in particular on T cells, we propose some key directions of understanding renal inflammation using single-cell approaches. We detail the benefits and shortcomings of the various technological approaches outlined and give advice on potential pitfalls and challenges in experimental setup and computational analysis. Finally, we conclude with a brief outlook into a promising future for single-cell technologies to elucidate kidney function.

A single-cell survey of the human glomerulonephritis

Glomerulonephritis is the one of the major causes of the end-stage kidney disease, whereas the pathological process of glomerulonephritis is still not completely understood. Single-cell RNA sequencing (scRNA-seq) emerges to be a powerful tool to evaluate the full heterogeneity of kidney diseases. To reveal cellular gene expression profiles of glomerulonephritis, we performed scRNA-seq of 2 human kidney transplantation donor samples, 4 human glomerulonephritis samples, 1 human malignant hypertension (MH) sample and 1 human chronic interstitial nephritis (CIN) sample, all tissues were taken from the biopsy. After filtering the cells with < 200 genes and > 10% mitochondria (MT) genes, the resulting 14 932 cells can be divided into 20 cell clusters, consistently with the previous report, in disease samples dramatic immune cells infiltration was found, among which a proximal tubule (PT) subset characterized by wnt-β catenin activation and a natural killer T (NKT) subset high expressing LTB were found. Furthermore, in the cluster of the podocyte, three glomerulonephritis related genes named FXYD5, CD74 and B2M were found. Compared with the mesangial of donor, the gene CLIC1 and RPS26 were up-regulated in mesangial of IgA nephropathy(IgAN), whereas the gene JUNB was up-regulated in podocyte of IgAN in comparison with that of donor. Meanwhile, some membranous nephropathy (MN) high expressed genes such as HLA-DRB5, HLA-DQA2, IFNG, CCL2 and NR4A2, which involve in highest enrichment pathway, display the cellular-specific expression style, whereas monocyte marker of lupus nephritis (LN) named TNFSF13B was also found and interferon alpha/beta signalling pathway was enriched in B and NKT of LN comparing with donor. By scRNA-seq, we first defined the podocyte markers of glomerulonephritis and specific markers in IgA, MN and LN were found at cellular level. Furthermore, the critical role of interferon alpha/beta signalling pathway was enriched in B and NKT of LN was declared.

Epigenetic modifications and the development of kidney graft fibrosis

PURPOSE OF REVIEW

To outline recent discoveries in epigenetic regulatory mechanisms that have potential implications in the development of renal fibrosis following kidney transplantation.

RECENT FINDINGS

The characterization of renal fibrosis following kidney transplantation has shown TGFβ/Smad signaling to play a major role in the progression to chronic allograft dysfunction. The onset of unregulated proinflammatory pathways are only exacerbated by the decline in regulatory mechanisms lost with progressive patient age and comorbidities such as hypertension and diabetes. However, significant developments in the recognition of epigenetic regulatory markers upstream of aberrant TGFβ-signaling has significant clinical potential to provide therapeutic targets for the treatment of renal fibrosis. In addition, discoveries in extracellular vesicles and the characterization of their cargo has laid new framework for the potential to evaluate patient outcomes independent of invasive biopsies.

SUMMARY

The current review summarizes the main findings in epigenetic machinery specific to the development of renal fibrosis and highlights therapeutic options that have significant potential to translate into clinical practice.

The study of single cells in diabetic kidney disease

In the past few years there has been a rapid expansion of interest in the study of single cells, especially through the new techniques that involve single-cell RNA sequencing (scRNA-seq). Recently, these techniques have provided new insights into kidney health and disease, including insights into diabetic kidney disease (DKD). However, despite the interest and the technological advances, the study of individual cells in DKD is not a new concept. Many clinicians and researchers who work within the DKD space may be familiar with experimental techniques that actually involve the study of individual cells, but may be unfamiliar with newer scRNA-seq technology. Here, with the goal of improving accessibility to the single-cell field, we provide a primer on single-cell studies with a focus on DKD. We situate the technology in its historical context and provide a brief explanation of the common aspects of the different technologies available. Then we review some of the most important recent studies of kidney (patho)biology that have taken advantage of scRNA-seq techniques, before emphasizing the new insights into the molecular pathogenesis of DKD gleaned with these techniques. Finally, we highlight common pitfalls and limitations of scRNA-seq methods and we look toward the future to how single-cell experiments may be incorporated into the study of DKD and how to interpret the findings of these experiments.

Experimental and computational technologies to dissect the kidney at the single-cell level

The field of single-cell technologies, in particular single-cell genomics with transcriptomics and epigenomics, and most recently single-cell proteomics, is rapidly growing and holds promise to advance our understanding of organ homoeostasis and disease, and facilitate the identification of novel therapeutic targets and biomarkers. This review offers an introduction to these technologies. In addition, as the size and complexity of the data require sophisticated computational methods for analysis and interpretation, we will also provide an overview of these methods and summarize the single-cell literature specifically pertaining to the kidney.

Single-Cell Transcriptomics Reveal Immune Mechanisms of the Onset and Progression of IgA Nephropathy

IgA nephropathy (IgAN) is the leading cause of kidney failure due to an incomplete understanding of its pathogenesis. We perform single-cell RNA sequencing (RNA-seq) on kidneys and CD14⁺ peripheral blood mononuclear cells (PBMCs) collected from IgAN and normal samples. In IgAN, upregulation of JCHAIN in mesangial cells provides insight into the trigger mechanism for the dimerization and deposition of IgA1 in situ. The pathological mesangium also demonstrates a prominent inflammatory signature and increased cell-cell communication with other renal parenchymal cells and immune cells, suggesting disease progress from the mesangium to the entire kidney. Specific gene expression of kidney-resident macrophages and CD8⁺ T cells further indicates abnormal regulation associated with proliferation and inflammation. A transitional cell type among intercalated cells with fibrosis signatures is identified, suggesting an adverse outcome of interstitial fibrosis. Altogether, we systematically analyze the molecular events in the onset and progression of IgAN, providing a promising landscape for disease treatment.

Near-Single-Cell Proteomics Profiling of the Proximal Tubular and Glomerulus of the Normal Human Kidney

Molecular assessments at the single cell level can accelerate biological research by providing detailed assessments of cellular organization and tissue heterogeneity in both disease and health. The human kidney has complex multi-cellular states with varying functionality, much of which can now be completely harnessed with recent technological advances in tissue proteomics at a near single-cell level. We discuss the foundational steps in the first application of this mass spectrometry (MS) based proteomics method for analysis of sub-sections of the normal human kidney, as part of the Kidney Precision Medicine Project (KPMP). Using ~30-40 laser captured micro-dissected kidney cells, we identified more than 2,500 human proteins, with specificity to the proximal tubular (PT; n = 25 proteins) and glomerular (Glom; n = 67 proteins) regions of the kidney and their unique metabolic functions. This pilot study provides the roadmap for application of our near-single-cell proteomics workflow for analysis of other renal micro-compartments, on a larger scale, to unravel perturbations of renal sub-cellular function in the normal kidney as well as different etiologies of acute and chronic kidney disease.

Klotho, Aging, and the Failing Kidney

Klotho has been recognized as a gene involved in the aging process in mammals for over 30 years, where it regulates phosphate homeostasis and the activity of members of the fibroblast growth factor (FGF) family. The α-Klotho protein is the receptor for Fibroblast Growth Factor-23 (FGF23), regulating phosphate homeostasis and vitamin D metabolism. Phosphate toxicity is a hallmark of mammalian aging and correlates with diminution of Klotho levels with increasing age. As such, modulation of Klotho activity is an attractive target for therapeutic intervention in the diseasome of aging; in particular for chronic kidney disease (CKD), where Klotho has been implicated directly in the pathophysiology. A range of senotherapeutic strategies have been developed to directly or indirectly influence Klotho expression, with varying degrees of success. These include administration of exogenous Klotho, synthetic and natural Klotho agonists and indirect approaches, via modulation of the foodome and the gut microbiota. All these approaches have significant potential to mitigate loss of physiological function and resilience accompanying old age and to improve outcomes within the diseasome of aging.

Application of single-cell RNA sequencing in embryonic development

Embryonic development is a complex process that is regulated by a series of precise cellular behaviours. The limited number of cells in the early stages of embryonic development represents a challenge for studying early gene regulation and maintaining cell sternness. Single-cell sequencing is a new technology for high-throughput sequencing analysis at the single-cell level that not only reflects the heterogeneity between cells but also reveals gene expression characteristics in different cells from limited samples. Currently, the widespread application of single-cell RNA sequencing technology is gradually changing our understanding of disease pathogenesis. This article reviews the application of single-cell RNA sequencing in embryonic development in recent years and provides innovative ideas for research on embryonic development and the treatment of diseases related to embryonic development.

Recent advances of single-cell RNA sequencing technology in mesenchymal stem cell research

Mesenchymal stem cells (MSCs) are multipotent stromal cells with great potential for clinical applications. However, little is known about their cell heterogeneity at a single-cell resolution, which severely impedes the development of MSC therapy. In this review, we focus on advances in the identification of novel surface markers and functional subpopulations of MSCs made by single-cell RNA sequencing and discuss their participation in the pathophysiology of stem cells and related diseases. The challenges and future directions of single-cell RNA sequencing in MSCs are also addressed in this review.

Single Cell Sequencing and Kidney Organoids Generated from Pluripotent Stem Cells

Methods to differentiate human pluripotent stem cells into kidney organoids were first introduced about 5 years ago, and since that time, the field has grown substantially. Protocols are producing increasingly complex three-dimensional structures, have been used to model human kidney disease, and have been adapted for high-throughput screening. Over this same time frame, technologies for massively parallel, single-cell RNA sequencing (scRNA-seq) have matured. Now, both of these powerful approaches are being combined to better understand how kidney organoids can be applied to the understanding of kidney development and disease. There are several reasons why this is a synergistic combination. Kidney organoids are complicated and contain many different cell types of variable maturity. scRNA-seq is an unbiased technology that can comprehensively categorize cell types, making it ideally suited to catalog all cell types present in organoids. These same characteristics also make scRNA-seq a powerful approach for quantitative comparisons between protocols, batches, and pluripotent cell lines as it becomes clear that reproducibility and quality can vary across all three variables. Lineage trajectories can be reconstructed using scRNA-seq data, enabling the rational adjustment of differentiation strategies to promote maturation of desired kidney cell types or inhibit differentiation of undesired off-target cell types. Here, we review the ways that scRNA-seq has been successfully applied in the organoid field and predict future applications for this powerful technique. We also review other developing single-cell technologies and discuss how they may be combined, using "multiomic" approaches, to improve our understanding of kidney organoid differentiation and usefulness in modeling development, disease, and toxicity testing.

Machine learning, the kidney, and genotype-phenotype analysis

With biomedical research transitioning into data-rich science, machine learning provides a powerful toolkit for extracting knowledge from large-scale biological data sets. The increasing availability of comprehensive kidney omics compendia (transcriptomics, proteomics, metabolomics, and genome sequencing), as well as other data modalities such as electronic health records, digital nephropathology repositories, and radiology renal images, makes machine learning approaches increasingly essential for analyzing human kidney data sets. Here, we discuss how machine learning approaches can be applied to the study of kidney disease, with a particular focus on how they can be used for understanding the relationship between genotype and phenotype.

Endothelial-epithelial communication in polycystic kidney disease: Role of vascular endothelial growth factor signalling

Whereas targeting the cyst epithelium and its molecular machinery has been the prevailing clinical strategy for polycystic kidney disease, the endothelium, including blood vasculature and lymphatics, is emerging as an important player in this disorder. In this Review, we provide an overview of the structural and functional alterations to blood vasculature and lymphatic vessels in the polycystic kidney. We also discuss evidence for vascular endothelial growth factor signalling, otherwise critical for endothelial cell development and maintenance, as being a fundamental molecular pathway in polycystic kidney disease and a potential therapeutic target for modulating cyst expansion.

Kidney and organoid single-cell transcriptomics: the end of the beginning

Single-cell RNA sequencing (scRNA-seq) technologies are increasingly being applied to reveal cellular heterogeneity in kidney development and disease. In just the last year, multiple scRNA-seq datasets have been generated from kidney organoids, developing mouse and human kidney, adult kidney, and kidney cancer. The data generated enables a much deeper understanding of biological processes within and between cells. It has also elucidated unforeseen cell lineage relationships, defined the presence of off-target cell types in kidney organoids, and revealed a diverse inflammatory response in a human kidney allograft undergoing rejection. This review summarizes the recent rapid progress in scRNA-seq of the kidney and outlines future directions for single-cell technologies as applied to the kidney.

Systems Biology and Kidney Disease

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

The Current State of the Art in Acute Kidney Injury

Decades of pre-clinical research have revealed biologic pathways that have suggested potential therapies for acute kidney injury (AKI) in experimental models. However, translating these to human AKI has largely yielded disappointing results. Fortunately, recent discoveries in AKI molecular mechanisms are providing new opportunities for early detection and novel interventions. This review identifies technologies that are revealing the exceptionally complex nature of the normal kidney, the remarkable heterogeneity of the AKI syndrome, and the myriad responses of the kidney to AKI. Based on the current state of the art, novel approaches to improve the bench-to-bedside translation of novel discoveries are proposed. These strategies include the use of unbiased approaches to improve our understanding of human AKI, establishment of irrefutable biologic plausibility for proposed biomarkers and therapies, identification of patients at risk for AKI pre-injury using clinical scores and non-invasive biomarkers, initiation of safe, and effective preventive interventions of pre-injury in susceptible patients, identification of patients who may develop AKI post-injury using electronic triggers, clinical scores, and novel biomarkers, employment of sequential biomarkers to initiate appropriate therapies based on knowledge of the underlying pathophysiology, use of new biomarkers as criteria for enrollment in randomized clinical trials, assessing efficacy, and empowering the drug development process, and early initiation of anti-fibrotic therapies. These strategies are immediately actionable and hold tremendous promise for effective bench-to-bedside translation of novel discoveries that will change the current dismal prognosis of human AKI.

Comparison of Kidney Transcriptomic Profiles of Early and Advanced Diabetic Nephropathy Reveals Potential New Mechanisms for Disease Progression

To identify the factors mediating the progression of diabetic nephropathy (DN), we performed RNA sequencing of kidney biopsy samples from patients with early DN, advanced DN, and normal kidney tissue from nephrectomy samples. A set of genes that were upregulated at early but downregulated in late DN were shown to be largely renoprotective, which included genes in the retinoic acid pathway and glucagon-like peptide 1 receptor. Another group of genes that were downregulated at early but highly upregulated in advanced DN consisted mostly of genes associated with kidney disease pathogenesis, such as those related to immune response and fibrosis. Correlation with estimated glomerular filtration rate (eGFR) identified genes in the pathways of iron transport and cell differentiation to be positively associated with eGFR, while those in the immune response and fibrosis pathways were negatively associated. Correlation with various histopathological features also identified the association with the distinct gene ontological pathways. Deconvolution analysis of the RNA sequencing data set indicated a significant increase in monocytes, fibroblasts, and myofibroblasts in advanced DN kidneys. Our study thus provides potential molecular mechanisms for DN progression and association of differential gene expression with the functional and structural changes observed in patients with early and advanced DN.

A Functional Landscape of CKD Entities From Public Transcriptomic Data

Introduction

To develop effective therapies and identify novel early biomarkers for chronic kidney disease, an understanding of the molecular mechanisms orchestrating it is essential. We here set out to understand how differences in chronic kidney disease (CKD) origin are reflected in gene expression. To this end, we integrated publicly available human glomerular microarray gene expression data for 9 kidney disease entities that account for most of CKD worldwide. Our primary goal was to demonstrate the possibilities and potential on data analysis and integration to the nephrology community.

Methods

We integrated data from 5 publicly available studies and compared glomerular gene expression profiles of disease with that of controls from nontumor parts of kidney cancer nephrectomy tissues. A major challenge was the integration of the data from different sources, platforms, and conditions that we mitigated with a bespoke stringent procedure.

Results

We performed a global transcriptome-based delineation of different kidney disease entities, obtaining a transcriptomic diffusion map of their similarities and differences based on the genes that acquire a consistent differential expression between each kidney disease entity and nephrectomy tissue. We derived functional insights by inferring the activity of signaling pathways and transcription factors from the collected gene expression data and identified potential drug candidates based on expression signature matching. We validated representative findings by immunostaining in human kidney biopsies indicating, for example, that the transcription factor FOXM1 is significantly and specifically expressed in parietal epithelial cells in rapidly progressive glomerulonephritis (RPGN) whereas not expressed in control kidney tissue. Furthermore, we found drug candidates by matching the signature on expression of drugs to that of the CKD entities, in particular, the Food and Drug Administration-approved drug nilotinib.

Conclusion

These results provide a foundation to comprehend the specific molecular mechanisms underlying different kidney disease entities that can pave the way to identify biomarkers and potential therapeutic targets. To facilitate further use, we provide our results as a free interactive Web application: https://saezlab.shinyapps.io/ckd_landscape/. However, because of the limitations of the data and the difficulties in its integration, any specific result should be considered with caution. Indeed, we consider this study rather an illustration of the value of functional genomics and integration of existing data.

Understanding the kidney one cell at a time

A revolution in cellular measurement technology is underway. Whereas prior studies have been able to analyze only the averaged outputs from renal tissue, we now can accurately monitor genome-wide gene expression, regulation, function, cellular history, and cellular interactions in thousands of individual cells in a single experiment. These methods are key drivers in changing our previous morphotype-based organ and disease descriptions to unbiased genomic definitions and therefore improving our understanding of kidney development, homeostasis, and disease.

Dietary Effects on Dahl Salt-Sensitive Hypertension, Renal Damage, and the T Lymphocyte Transcriptome

The Dahl salt-sensitive (SS) rat is an established model of SS hypertension and renal damage. In addition to salt, other dietary components were shown to be important determinants of hypertension in SS rats. With previous work eliminating the involvement of genetic differences, grain-fed SS rats from Charles River Laboratories (SS/CRL; 5L2F/5L79) were less susceptible to salt-induced hypertension and renal damage compared with purified diet-fed SS rats bred at the Medical College of Wisconsin (SS/MCW; 0.4% NaCl, AIN-76A). With the known role of immunity in hypertension, the present study characterized the immune cells infiltrating SS/MCW and SS/CRL kidneys via flow cytometry and RNA sequencing in T-cells isolated from the blood and kidneys of rats maintained on their respective parental diet or on 3 weeks of high salt (4.0% NaCl, AIN-76A). SS/CRL rats were protected from salt-induced hypertension (116.5±1.2 versus 141.9±14.4 mm Hg), albuminuria (21.7±3.5 versus 162.9±22.2 mg/d), and renal immune cell infiltration compared with SS/MCW. RNA-seq revealed >50% of all annotated genes in the entire transcriptome to be significantly differentially expressed in T-cells isolated from blood versus kidney, regardless of colony or chow. Pathway analysis of significantly differentially expressed genes between low and high salt conditions demonstrated changes related to inflammation in SS/MCW renal T-cells compared with metabolism-related pathways in SS/CRL renal T-cells. These functional and transcriptomic T-cell differences between SS/MCW and SS/CRL show that dietary components in addition to salt may influence immunity and the infiltration of immune cells into the kidney, ultimately impacting susceptibility to salt-induced hypertension and renal damage.