Diabetic kidney disease (DKD) remains a leading cause of new-onset end-stage renal disease (ESRD), and yet, at present, the treatment is still very limited. A better understanding of the pathogenesis of DKD is therefore necessary to develop more effective therapies. Increasing evidence suggests that glomerular endothelial cell (GEC) injury plays a major role in the development and progression of DKD. Alteration of the glomerular endothelial cell surface layer, including its major component, glycocalyx, is a leading cause of microalbuminuria observed in early DKD. Many studies suggest a presence of cross talk between glomerular cells, such as between GEC and mesangial cells or GEC and podocytes. PDGFB/PDGFRβ is a major mediator for GEC and mesangial cell cross talk, while vascular endothelial growth factor (VEGF), angiopoietins, and endothelin-1 are the major mediators for GEC and podocyte communication. In DKD, GEC injury may lead to podocyte damage, while podocyte loss further exacerbates GEC injury, forming a vicious cycle. Therefore, GEC injury may predispose to albuminuria in diabetes either directly or indirectly by communication with neighboring podocytes and mesangial cells via secreted mediators. Identification of novel mediators of glomerular cell cross talk, such as microRNAs, will lead to a better understanding of the pathogenesis of DKD. Targeting these mediators may be a novel approach to develop more effective therapy for DKD.

Significance Statement: Although transcriptomic profiling of kidney tissues or isolated glomeruli has provided insights into broad changes in the pathogenesis of diabetic kidney disease, the presence of multiple cell types in kidney samples limits what can be discerned about changes in specific types of cells. To better elucidate the mechanisms of early diabetic kidney injury, the authors used single-cell RNA sequencing technology to perform a gene expression analysis of individual kidney glomerular cells of a diabetic mouse model. A comparison of gene expression in normal versus diabetic mouse kidney cells at a single-cell level showed dynamic changes in the pattern of expressed genes. This approach may help identify important factors underlying the pathophysiology of diabetic kidney disease progression and point to potential new therapeutic approaches. Background: Recent single-cell RNA sequencing (scRNA-seq) analyses have offered much insight into cell-specific gene expression profiles in normal kidneys. However, in diseased kidneys, understanding of changes in specific cells, particularly glomerular cells, remains limited. Methods: To elucidate the glomerular cell–specific gene expression changes in diabetic kidney disease, we performed scRNA-seq analysis of isolated glomerular cells from streptozotocin-induced diabetic endothelial nitric oxide synthase (eNOS)–deficient (eNOS^−/−) mice and control eNOS^−/− mice. Results: We identified five distinct cell populations, including glomerular endothelial cells, mesangial cells, podocytes, immune cells, and tubular cells. Using scRNA-seq analysis, we confirmed the expression of glomerular cell–specific markers and also identified several new potential markers of glomerular cells. The number of immune cells was significantly higher in diabetic glomeruli compared with control glomeruli, and further cluster analysis showed that these immune cells were predominantly macrophages. Analysis of differential gene expression in endothelial and mesangial cells of diabetic and control mice showed dynamic changes in the pattern of expressed genes, many of which are known to be involved in diabetic kidney disease. Moreover, gene expression analysis showed variable responses of individual cells to diabetic injury. Conclusions: Our findings demonstrate the ability of scRNA-seq analysis in isolated glomerular cells from diabetic and control mice to reveal dynamic changes in gene expression in diabetic kidneys, with variable responses of individual cells. Such changes, which might not be apparent in bulk transcriptomic analysis of glomerular cells, may help identify important pathophysiologic factors contributing to the progression of diabetic kidney disease.

Background: Diabetic kidney disease (DKD) is the most common cause of the end-stage renal disease (ESRD). Regardless of intensive treatments with hyperglycemic control, blood pressure control, and the use of renin-angiotensin system blockades, the prevalence of DKD remains high. Recent studies suggest that the spectrum of DKD has been changed and many progresses have been made to develop new treatments for DKD. Therefore, it is time to perform a systemic review on the new developments in the field of DKD. Summary: Although the classic clinical presentation of DKD is characterized by a slow progression from microalbuminuria to macroalbuminuria and by a hyperfiltration at the early stage and progressive decline of renal function at the late stage, recent epidemiological studies suggest that DKD patients have a variety of clinical presentations and progression rates to ESRD. Some DKD patients have a decline in renal function without albuminuria but display prominent vascular and interstitial fibrosis on renal histology. DKD patients are more susceptible to acute kidney injury, which might contribute to the interstitial fibrosis. A large portion of type 2 diabetic patients with albuminuria could have overlapping nondiabetic glomerular disease, and therefore, kidney biopsy is required for differential diagnosis for these patients. Only a small portion of DKD patients eventually progress to end-stage renal failure. However, we do not have sensitive and specific biomarkers to identify these high-risk patients. Genetic factors that have a strong association with DKD progression have not been identified yet. A combination of circulating tumor necrosis factor receptor (TNFR)1, TNFR2, and kidney injury molecular 1 provides predictive value for DKD progression. Artificial intelligence could enhance the predictive values for DKD progression by combining the clinical parameters and biological markers. Sodium-glucose co-transporter-2 inhibitors should be added to the new standard care of DKD patients. Several promising new drugs are in clinical trials. Key Messages: Over last years, our understanding of DKD has been much improved and new treatments to halt the progression of DKD are coming. However, better diagnostic tools, predictive markers, and treatment options are still urgently needed to help us to better manage these patients with this detrimental disease.

Nuclear factor (NF)-κB and signal transducer and activator of transcription 3 (STAT3) play a critical role in diabetic nephropathy (DN). Sirtuin-1 (SIRT1) regulates transcriptional activation of target genes through protein deacetylation. Here, we determined the roles of Sirt1 and the effect of NF-κB (p65) and STAT3 acetylation in DN. We found that acetylation of p65 and STAT3 was increased in both mouse and human diabetic kidneys. In human podocytes, advanced glycation end products (AGEs) induced p65 and STAT3 acetylation and overexpression of acetylation-incompetent mutants of p65 and STAT3 abrogated AGE-induced expression of NF-κB and STAT3 target genes. Inhibition of AGE formation in db/db mice by pyridoxamine treatment attenuated proteinuria and podocyte injury, restored SIRT1 expression, and reduced p65 and STAT3 acetylation. Diabetic db/db mice with conditional deletion of SIRT1 in podocytes developed more proteinuria, kidney injury, and acetylation of p65 and STAT3 compared with db/db mice without SIRT1 deletion. Treatment of db/db mice with a bromodomain and extraterminal (BET)-specific bromodomain inhibitor (MS417) which blocks acetylation-mediated association of p65 and STAT3 with BET proteins, attenuated proteinuria, and kidney injury. Our findings strongly support a critical role for p65 and STAT3 acetylation in DN. Targeting protein acetylation could be a potential new therapy for DN.

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.