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It is important to find better treatments for diabetic nephropathy (DN), a debilitating renal complication. Targeting early features of DN, including renal extracellular matrix accumulation (ECM) and glomerular hypertrophy, can prevent disease progression. Here we show that a megacluster of nearly 40 microRNAs and their host long non-coding RNA transcript (lnc-MGC) are coordinately increased in the glomeruli of mouse models of DN, and mesangial cells treated with transforming growth factor-β1 (TGF- β1) or high glucose. Lnc-MGC is regulated by an endoplasmic reticulum (ER) stress-related transcription factor, CHOP. Cluster microRNAs and lnc-MGC are decreased in diabetic Chop −/− mice that showed protection from DN. Target genes of megacluster microRNAs have functions related to protein synthesis and ER stress. A chemically modified oligonucleotide targeting lnc-MGC inhibits cluster microRNAs, glomerular ECM and hypertrophy in diabetic mice. Relevance to human DN is also demonstrated. These results demonstrate the translational implications of targeting lnc-MGC for controlling DN progression. Nephropathy is a common and hard-to-treat consequence of diabetes. Here Kato et al . show that a megacluster of microRNAs regulates early development of diabetic nephropathy in mice, and that inhibition of the cluster's host long non-coding RNA transcript attenuates disease symptoms, suggesting a new therapy for diabetic nephropathy.

The molecular mechanisms of sodium-glucose cotransporter-2 (SGLT2) inhibitors (SGLT2i) remain incompletely understood. Single-cell RNA sequencing and morphometric data were collected from research kidney biopsies donated by young persons with type 2 diabetes (T2D), aged 12 to 21 years, and healthy controls (HCs). Participants with T2D were obese and had higher estimated glomerular filtration rates and mesangial and glomerular volumes than HCs. Ten T2D participants had been prescribed SGLT2i (T2Di[+]) and 6 not (T2Di[-]). Transcriptional profiles showed SGLT2 expression exclusively in the proximal tubular (PT) cluster with highest expression in T2Di(-) patients. However, transcriptional alterations with SGLT2i treatment were seen across nephron segments, particularly in the distal nephron. SGLT2i treatment was associated with suppression of transcripts in the glycolysis, gluconeogenesis, and tricarboxylic acid cycle pathways in PT, but had the opposite effect in thick ascending limb. Transcripts in the energy-sensitive mTORC1-signaling pathway returned toward HC levels in all tubular segments in T2Di(+), consistent with a diabetes mouse model treated with SGLT2i. Decreased levels of phosphorylated S6 protein in proximal and distal tubules in T2Di(+) patients confirmed changes in mTORC1 pathway activity. We propose that SGLT2i treatment benefits the kidneys by mitigating diabetes-induced metabolic perturbations via suppression of mTORC1 signaling in kidney tubules.

Recent evidence suggests that enhanced neutrophil extracellular trap (NET) formation activates plasmacytoid dendritic cells and serves as a source of autoantigens in SLE. We propose that aberrant NET formation is also linked to organ damage and to the premature vascular disease characteristic of human SLE. Here, we demonstrate enhanced NET formation in the New Zealand mixed 2328 (NZM) model of murine lupus. NZM mice also developed autoantibodies to NETs as well as the ortholog of human cathelicidin/LL37 (CRAMP), a molecule externalized in the NETs. NZM mice were treated with Cl-amidine, an inhibitor of peptidylarginine deiminases (PAD), to block NET formation and were evaluated for lupus-like disease activity, endothelial function, and prothrombotic phenotype. Cl-amidine treatment inhibited NZM NET formation in vivo and significantly altered circulating autoantibody profiles and complement levels while reducing glomerular IgG deposition. Further, Cl-amidine increased the differentiation capacity of bone marrow endothelial progenitor cells, improved endothelium-dependent vasorelaxation, and markedly delayed time to arterial thrombosis induced by photochemical injury. Overall, these findings suggest that PAD inhibition can modulate phenotypes crucial for lupus pathogenesis and disease activity and may represent an important strategy for mitigating cardiovascular risk in lupus patients.

ObjectivesAn imbalance between neutrophil extracellular trap (NET) formation and degradation has been described in systemic lupus erythematosus (SLE), potentially contributing to autoantigen externalisation, type I interferon synthesis and endothelial damage. We have demonstrated that peptidylarginine deiminase (PAD) inhibition reduces NET formation and protects against lupus-related vascular damage in the New Zealand Mixed model of lupus. However, another strategy for inhibiting NETs—knockout of NOX2—accelerates lupus in a different murine model, MRL/lpr. Here, we test the effects of PAD inhibition on MRL/lpr mice in order to clarify whether some NET inhibitory pathways may be consistently therapeutic across models of SLE.MethodsNET formation and autoantibodies to NETs were characterised in lupus-prone MRL/lpr mice. MRL/lpr mice were also treated with two different PAD inhibitors, Cl-amidine and the newly described BB-Cl-amidine. NET formation, endothelial function, interferon signature, nephritis and skin disease were examined in treated mice.ResultsNeutrophils from MRL/lpr mice demonstrate accelerated NET formation compared with controls. MRL/lpr mice also form autoantibodies to NETs and have evidence of endothelial dysfunction. PAD inhibition markedly improves endothelial function, while downregulating the expression of type I interferon-regulated genes. PAD inhibition also reduces proteinuria and immune complex deposition in the kidneys, while protecting against skin disease.ConclusionsPAD inhibition reduces NET formation, while protecting against lupus-related damage to the vasculature, kidneys and skin in various lupus models. The strategy by which NETs are inhibited will have to be carefully considered if human studies are to be undertaken.

The proximate genetic cause of both Thin GBM and Alport Syndrome (AS) is abnormal α3, 4 and 5 collagen IV chains resulting in abnormal glomerular basement membrane (GBM) structure/function. We previously reported that podocyte detachment rate measured in urine is increased in AS, suggesting that podocyte depletion could play a role in causing progressive loss of kidney function. To test this hypothesis podometric parameters were measured in 26 kidney biopsies from 21 patients aged 2-17 years with a clinic-pathologic diagnosis including both classic Alport Syndrome with thin and thick GBM segments and lamellated lamina densa [n = 15] and Thin GBM cases [n = 6]. Protocol biopsies from deceased donor kidneys were used as age-matched controls. Podocyte depletion was present in AS biopsies prior to detectable histologic abnormalities. No abnormality was detected by light microscopy at <30% podocyte depletion, minor pathologic changes (mesangial expansion and adhesions to Bowman's capsule) were present at 30-50% podocyte depletion, and FSGS was progressively present above 50% podocyte depletion. eGFR did not change measurably until >70% podocyte depletion. Low level proteinuria was an early event at about 25% podocyte depletion and increased in proportion to podocyte depletion. These quantitative data parallel those from model systems where podocyte depletion is the causative event. This result supports a hypothesis that in AS podocyte adherence to the GBM is defective resulting in accelerated podocyte detachment causing progressive podocyte depletion leading to FSGS-like pathologic changes and eventual End Stage Kidney Disease. Early intervention to reduce podocyte depletion is projected to prolong kidney survival in AS.

Podocytes are key to the glomerular filtration barrier by forming a slit diaphragm between interdigitating foot processes; however, the molecular details and functional importance of protein folding and degradation in the ER remain unknown. Here, we show that the SEL1L-HRD1 protein complex of ER-associated degradation (ERAD) is required for slit diaphragm formation and glomerular filtration function. SEL1L-HRD1 ERAD is highly expressed in podocytes of both mouse and human kidneys. Mice with podocyte-specific Sel1L deficiency develop podocytopathy and severe congenital nephrotic syndrome with an impaired slit diaphragm shortly after weaning and die prematurely, with a median lifespan of approximately 3 months. We show mechanistically that nephrin, a type 1 membrane protein causally linked to congenital nephrotic syndrome, is an endogenous ERAD substrate. ERAD deficiency attenuated the maturation of nascent nephrin, leading to its retention in the ER. We also show that various autosomal-recessive nephrin disease mutants were highly unstable and broken down by SEL1L-HRD1 ERAD, which attenuated the pathogenicity of the mutants toward the WT allele. This study uncovers a critical role of SEL1L-HRD1 ERAD in glomerular filtration barrier function and provides insights into the pathogenesis associated with autosomal-recessive disease mutants.

In renal biopsy reporting, quantitative measurements, such as glomerular number and percentage of globally sclerotic glomeruli, is central to diagnostic accuracy and prognosis. The aim of this study is to determine the number of glomeruli and percent globally sclerotic in renal biopsies by means of registration of serial tissue sections and manual enumeration, compared to the numbers in pathology reports from routine light microscopic assessment. We reviewed 277 biopsies from the Nephrotic Syndrome Study Network (NEPTUNE) digital pathology repository, enumerating 9,379 glomeruli by means of whole slide imaging. Glomerular number and the percentage of globally sclerotic glomeruli are values routinely recorded in the official renal biopsy pathology report from the 25 participating centers. Two general trends in reporting were noted: total number per biopsy or average number per level/section. Both of these approaches were assessed for their accuracy in comparison to the analogous numbers of annotated glomeruli on WSI. The number of glomeruli annotated was consistently higher than those reported (p<0.001); this difference was proportional to the number of glomeruli. In contrast, percent globally sclerotic were similar when calculated on total glomeruli, but greater in FSGS when calculated on average number of glomeruli (p<0.01). The difference in percent globally sclerotic between annotated and those recorded in pathology reports was significant when global sclerosis is greater than 40%. Although glass slides were not available for direct comparison to whole slide image annotation, this study indicates that routine manual light microscopy assessment of number of glomeruli is inaccurate, and the magnitude of this error is proportional to the total number of glomeruli.

HistoLens is an open-source graphical user interface developed using MATLAB AppDesigner for visual and quantitative analysis of histological datasets. HistoLens enables users to interrogate sets of digitally annotated whole slide images to efficiently characterize histological differences between disease and experimental groups. Users can dynamically visualize the distribution of 448 hand-engineered features quantifying color, texture, morphology, and distribution across microanatomic sub-compartments. Additionally, users can map differentially detected image features within the images by highlighting affected regions. We demonstrate the utility of HistoLens to identify hand-engineered features that correlate with pathognomonic renal glomerular characteristics distinguishing diabetic nephropathy and amyloid nephropathy from the histologically unremarkable glomeruli in minimal change disease. Additionally, we examine the use of HistoLens for glomerular feature discovery in the Tg26 mouse model of HIV-associated nephropathy. We identify numerous quantitative glomerular features distinguishing Tg26 transgenic mice from wild-type mice, corresponding to a progressive renal disease phenotype. Thus, we demonstrate an off-the-shelf and ready-to-use toolkit for quantitative renal pathology applications.

Apolipoprotein L1 gene ( ) variants are risk factors for chronic kidney disease (CKD) among Black Americans. Data are sparse on the genetic epidemiology of CKD and the clinical association of variants with CKD in West Africans, a major group in the Black population. We conducted a case-control study involving participants from Ghana and Nigeria who had CKD stages 2 through 5, biopsy-proven glomerular disease, or no kidney disease. We analyzed the association of CKD with variants among participants with high-risk genotypes (two risk alleles) and those with low-risk genotypes (fewer than two risk alleles) by fitting logistic-regression models that controlled for covariates, including clinical site, age, and sex. Among 8355 participants (4712 with CKD stages 2 through 5, 866 with glomerular diseases, and 2777 with no kidney disease), the prevalence of monoallelic variants was 43.0% and that of biallelic variants was 29.7%. Participants with two risk alleles had higher odds of having CKD than those with one risk allele or no risk alleles (adjusted odds ratio, 1.25; 95% confidence interval [CI], 1.11 to 1.40), as well as higher odds of focal segmental glomerulosclerosis (adjusted odds ratio, 1.84; 95% CI, 1.30 to 2.61). Participants with one risk allele had higher odds of having CKD than those with no risk alleles (adjusted odds ratio, 1.18; 95% CI, 1.04 to 1.33), as well as higher odds of focal segmental glomerulosclerosis (adjusted odds ratio, 1.61; 95% CI, 1.04 to 2.48). The inclusion of covariates did not modify the association of monoallelic and biallelic variants with CKD or focal segmental glomerulosclerosis. In this study, monoallelic variants were associated with 18% higher odds of CKD and 61% higher odds of focal segmental glomerulosclerosis; biallelic variants were associated with 25% higher odds of CKD and 84% higher odds of focal segmental glomerulosclerosis. (Funded by the National Human Genome Research Institute and others.).

Pathologists use visual classification to assess patient kidney biopsy samples when diagnosing the underlying cause of kidney disease. However, the assessment is qualitative, or semi-quantitative at best, and reproducibility is challenging. To discover previously unknown features which predict patient outcomes and overcome substantial interobserver variability, we developed an unsupervised bag-of-words model. Our study applied to the C-PROBE cohort of patients with chronic kidney disease (CKD). 107,471 histopathology images were obtained from 161 biopsy cores and identified important morphological features in biopsy tissue that are highly predictive of the presence of CKD both at the time of biopsy and in one year. To evaluate the performance of our model, we estimated the AUC and its 95% confidence interval. We show that this method is reliable and reproducible and can achieve 0.93 AUC at predicting glomerular filtration rate at the time of biopsy as well as predicting a loss of function at one year. Additionally, with this method, we ranked the identified morphological features according to their importance as diagnostic markers for chronic kidney disease. In this study, we have demonstrated the feasibility of using an unsupervised machine learning method without human input in order to predict the level of kidney function in CKD. The results from our study indicate that the visual dictionary, or visual image pattern, obtained from unsupervised machine learning can predict outcomes using machine-derived values that correspond to both known and unknown clinically relevant features.