Kidney360

Background: Lower urine pH has been associated with reduced kidney function and an increased risk of kidney disease; however, its prognostic and pathological significance in biopsy-proven kidney disease remains unclear. A recent study demonstrated that medullary cast formation is independently associated with adverse renal outcomes beyond established predictors such as interstitial fibrosis and tubular atrophy (IFTA), yet its clinical determinants are not fully elucidated. Urine pH reflects the intratubular acid-base microenvironment and may contribute to tubular obstruction through cast formation. In this study, we examined kidney outcomes in patients undergoing native kidney biopsy, and the associations of urine pH with medullary cast formation. Methods: Among 1167 adults who underwent native kidney biopsy between 2011 and 2024, 503 patients with evaluable medullary tissue were included in this retrospective observational cohort study. Urine pH was analyzed in relation to clinical and histological variables and kidney outcomes. The primary outcome was a 40% decline in estimated glomerular filtration rate (eGFR) or initiation of renal replacement therapy. Results: The mean baseline eGFR was 54.3 mL/min/1.73 m2, the mean urine pH was 6.15, and the median urinary protein excretion was 1.1 g/gCr. During a median follow-up of 2.11 years, 113 patients (22.5%) reached the kidney outcome. Kaplan-Meier analysis showed that lower urine pH was associated with a higher risk of kidney outcomes. In Cox proportional hazards models adjusted for proteinuria, baseline eGFR, and IFTA score, urine pH remained independently associated with kidney outcomes (hazard ratio, 0.69; 95% confidence interval, 0.51-0.91). Inclusion of urine pH improved prognostic discrimination beyond established risk factors (Harrell C-index, 0.642 to 0.654). Lower urine pH was also associated with greater medullary cast formation. Conclusion: In patients undergoing native kidney biopsy, lower urine pH was independently associated with adverse kidney outcomes and greater medullary cast formation.

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression remains challenging. This multicenter study developed and validated POCC, a machine learning model for predicting kidney failure risk at 1, 3, and 5 years post-diagnosis in CAKUT patients. Two versions were created using data from 2,249 children. The general model achieved internal AUCs of 0.93-0.99 and external AUCs of 0.90-0.98 and 0.81- 0.90 in two independent validations at pediatric and general hospitals, respectively. The specialized model, integrating congenital-hereditary features, achieved internal AUCs of 0.93-0.99 and external AUCs of 0.91-0.96 in pediatric hospitals. Deployed online, POCC demonstrated 90.7% accuracy in real-world validation, with the specialized model reaching 100% sensitivity and specificity for 5-year predictions. As the first tool for multi-timepoint risk prediction across diverse CAKUT subphenotypes per patient, POCC has strong potential to support personalized management.

BackgroundThe Kidney Precision Medicine Project (KPMP) consortium aims to redefine chronic kidney disease (CKD) by integrating clinical, pathological, and molecular tissue data from kidney biopsies. Here, we demonstrate how biopsy data in CKD can clarify disease etiology and contribute to understandings of disease pathophysiology and clinical prognosis. MethodsThe KPMP is obtaining research kidney biopsies from individuals with CKD (defined as an estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73m2 and/or albuminuria [&ge;]30 mg/g creatinine) and diabetes (enrolled as diabetes and CKD or DKD) or hypertension (enrolled as hypertension and CKD or HCKD). A team of kidney pathologists and nephrologists adjudicated the primary clinico-pathological diagnosis for 258 participants with CKD. We compared pathological features and kidney transcriptional signatures between participants with a primary adjudicated diagnosis of diabetic nephropathy and those with other causes of CKD. We developed a model using clinical and biomarker data that predicted the probability of diabetic nephropathy and tested associations of the signature with CKD progression among Chronic Renal Insufficiency Cohort (CRIC) participants with diabetes (n=229). ResultsAmong 183 participants enrolled as DKD, 102 (56%) had a primary adjudicated clinico-pathologic diagnosis of diabetic nephropathy. Among 75 participants enrolled as HCKD, 42 (56%) had a primary diagnosis of hypertension-associated kidney disease. Those with diabetic nephropathy, compared with other diagnoses, had more severe interstitial fibrosis, tubular atrophy, tubular injury, segmental sclerosis, and severe arteriolar hyalinosis, and single-nucleus and single-cell transcriptional analyses revealed upregulation of immune and inflammatory pathways and downregulation of oxidative phosphorylation. A combination of age, hemoglobin A1c, urine albumin-creatinine ratio, and serum KIM-1 and sTNFR1 predicted a clinico-pathologic diagnosis of diabetic nephropathy in the KPMP (AUC 0.82, 95% CI 0.75-0.89) and was associated with an increased risk of CKD progression among patients with diabetes enrolled in CRIC (HR 1.48 [95% CI 1.27-1.73] per 10% higher predicted probability of diabetic nephropathy). ConclusionIn common presentations of CKD, kidney biopsies may alter a priori impressions, reveal a diversity of diagnosis, structure, and function that is associated with clinical outcomes and can impact therapeutic decisions.

Background: Microvascular dysfunction contributes to chronic kidney disease (CKD), but reproducible clinical measures are limited. Laser Doppler flowmetry (LDF) provides a noninvasive assessment of cutaneous microvascular blood flow and may reflect systemic microvascular health. Its relationship with kidney function and histopathology in CKD remains unclear. Methods: We assessed cutaneous microvascular function in 150 participants with CKD (eGFR <90 mL/min/1.73 m2) using a standardized forearm LDF protocol. Baseline perfusion was recorded at ~30{degrees}C, followed by local heating to 44{degrees}C to induce hyperemia. Percent change in perfusion units (PU) defined microvascular functional reserve. Associations of LDF measures with eGFR and urine protein-to-creatinine ratio (uPCR) were evaluated using multivariable linear regression. K-means clustering identified microvascular phenotypes. In a subset (n=20), associations with glomerulosclerosis (GS) and interstitial fibrosis/tubular atrophy (IFTA) were examined. Results: The mean (SD) age was 64 (14) years, 46% were female. The mean eGFR was 42 (21) mL/min/1.73m2 and median uPCR was 0.21 (interquartile range (IQR) 0.11 to 1.20) mg/mg. Higher baseline PU ({beta} = -12; 95% CI, -24 to -1) and reduced percentage change in PU ({beta} = 7; 95% CI, 2 to 13) were associated with lower eGFR, independent of covariates. Neither measure was associated with uPCR. Clustering identified four phenotypes with graded differences in perfusion and reserve. In biopsy participants, higher baseline PU and lower percent change were associated with greater GS and IFTA severity. Conclusion: CKD is characterized by elevated resting perfusion and impaired microvascular reserve, which are associated with lower eGFR and histopathologic injury.

BackgroundKidney disease refers to a broad range of disorders that impair renal structure and function. Among these, chronic kidney disease (CKD) is the most prevalent worldwide, affecting approximately 10% of the global adult population. While large-scale omics studies have identified numerous molecular associations with kidney function and disease, these insights often remain isolated within individual data layers, hindering a systems-level understanding of the functional interplay between genes, proteins, metabolites and clinical phenotypes. MethodsWe developed the Kidney Disease Atlas (KD Atlas) using an extended QTL-based integration strategy combined with a composite network approach. For this purpose, we leveraged results from omics studies in population-based and kidney disease-specific cohorts from the CKDGen Consortium and other large-scale initiatives and integrated them with data from knowledge databases, inferring a comprehensive network of relationships between metabolites, proteins, genes, and kidney disease-related traits. ResultsWe present the KD Atlas, an online resource (https://metabolomics.helmholtz-munich.de/kdatlas) integrating over 25 large studies providing disease-relevant information on 20,456 protein-coding genes, 1,962 proteins, 1,375 metabolites and 40 kidney disease phenotypes connected by more than 1.2 million relationships. Through an interactive web interface, researchers can dynamically construct context-specific molecular subnetworks and perform integrated analyses without requiring specialized bioinformatics expertise. Application showcases demonstrate the resources utility for providing the molecular context of KD-associated genes or metabolites and for generating novel mechanistic hypotheses. ConclusionThe KD Atlas provides a global, multi-omics network view of kidney pathophysiology through an intuitive interface, empowering researchers to formulate mechanistic hypotheses and prioritize candidate targets for subsequent experimental validation.

Background: Chronic kidney disease (CKD) affects approximately 850 million individuals worldwide and remains a leading cause of morbidity, premature mortality, and escalating healthcare costs. Despite the availability of clinical biomarkers, CKD progression to end stage renal disease (ESRD) is frequently identified late, limiting opportunities for preventive intervention. Conventional predictive models have relied predominantly on static cross sectional laboratory values, failing to capture the temporal dynamics of disease trajectory that longitudinal claims data can provide. Objective: This study proposes a novel hybrid machine learning framework: XGBoost LSTM Attention (XLA), that integrates gradient boosted feature selection with long short-term memory (LSTM) networks and a temporal attention mechanism to improve early prediction of CKD progression from Stage 3 to Stages 4/5 or ESRD using longitudinal claims based features. Methods: We conducted two complementary analyses. Primary analysis: a cross sectional validation using real NHANES 2015 to 2018 data (n=701 CKD Stage 3 adults) predicting significant proteinuria (UACR greater than or equal to 30 mg/g) from clinical features excluding UACR. Supplementary analysis: an NHANES-calibrated longitudinal cohort (n=8,412) with simulated quarterly measurements demonstrated XLA performance under real world longitudinal data conditions. All models were evaluated using 5-fold stratified cross-validation. Results: In the primary NHANES cross sectional analysis, the XLA framework achieved AUC ROC of 0.684 (95% CI: 0.641 to 0.727), with all models performing comparably (AUC 0.684 to 0.710), confirming that cross sectional clinical features alone provide limited signal for proteinuria prediction and underscoring the necessity of UACR measurement. In the longitudinal supplementary analysis, XLA achieved AUC ROC of 0.994 versus 0.939 for the best cross-sectional baseline (+5.5%), demonstrating that temporal trajectory features particularly eGFR slope and RAAS adherence trends: confer substantial incremental predictive value when longitudinal data are available. Conclusion: The XLA framework demonstrates meaningful advantages over traditional approaches when applied to longitudinal claims data. Cross sectional findings highlight the irreplaceable role of direct UACR measurement in CKD risk stratification. Together, these results provide actionable evidence for both the limitations of static prediction and the promise of trajectory based approaches in value based care programs managing large CKD populations. Keywords: chronic kidney disease, CKD progression, machine learning, XGBoost, LSTM, temporal attention, claims data, NHANES, proteinuria, healthcare informatics, value based care.

Background: Single-nephron glomerular filtration rate (GFR) represents a nephron-level functional index that may reveal key pathophysiological mechanisms driving progression in patients with diabetic nephropathy. However, its clinical relevance remains incompletely understood. This cross-sectional study assessed single-nephron estimated GFR (eGFR) across different chronic kidney disease (CKD) stages in patients with advanced diabetic nephropathy. Methods: Nephron number was estimated as the number of nonglobally sclerotic glomeruli per kidney using computed tomography-derived cortical volume combined with biopsy stereology. Single-nephron eGFR was calculated by dividing eGFR by the nephron number of both kidneys. Patients were stratified according to CKD stage at kidney biopsy. Associations between CKD stages and single-nephron eGFR were evaluated using multivariable linear regression models adjusted for age, sex, urinary protein excretion, and eGFR. Results: The study included 105 patients with biopsy-proven diabetic nephropathy and overt proteinuria (median age 59 years, 83% male, HbA1c 6.6%, 57% had nephrotic range proteinuria). The percentage of globally sclerotic glomeruli, mesangial expansion score, and prevalence of nodular lesions increased significantly with advancing CKD stage. Median nephron number declined from 529,178 to 224,458 per kidney, whereas glomerular volume remained constant. Single-nephron eGFR decreased markedly with CKD stage and remained significantly inversely associated with CKD stage after adjustment for clinicopathologic covariates (P for trend <0.001). Conclusion: In overt diabetic nephropathy, single-nephron eGFR decreased with advancing CKD stage, despite relatively preserved glomerular volume. At this stage of disease, structural alterations specific to diabetic nephropathy may impair effective single-nephron filtration capacity.

IntroductionGenomic testing is reshaping nephrology practice, yet the structure, outcomes, and implementation of kidney genetics services remain poorly characterized. MethodsWe conducted a two-part scoping study comprising (i) a literature review (JBI methodology, PRISMA-ScR compliant; OSF registration doi.org/10.17605/OSF.IO/N32VA) of English-language publications (2000-2025) describing kidney genetics services and outcomes, and (ii) an international stakeholder consultation of clinic leads to capture real-world service and implementation experiences. ResultsSixty studies were included, predominantly from North America (n=23), followed by United Kingdom/Ireland (n=5), Europe (n=17), Australia/New Zealand (n=10), and Asia (n=5). Among the 25 studies describing clinic models, four types were identified: multidisciplinary integrated (n=12), nephrologist-led (n=9), mainstreaming (n=2), and traditional genetics referral (n=2). Clinic structure varied by region. Outcome reporting focused on diagnostic yield (92%), with limited data on timeliness (16%), patient-reported outcomes (12%), or implementation outcomes (4%). Test penetration was high across regions and models, while diagnostic yield varied. Nephrologist-led clinics demonstrated comparable performance to multidisciplinary models when adequately supported. International stakeholder consultation data (n=48) revealed diversification of clinic models across regions. In Australia/New Zealand, multidisciplinary clinics predominated, supported by public funding and in-house or hybrid laboratory. United Kingdom/Ireland clinics used public funding and a national laboratory. North American clinics show greater heterogeneity, with higher prevalence of nephrologist-led models, reliance on commercial laboratories, and mixed or private funding. Asian clinics reported nephrologist-led models, with resource constraints, and hybrid testing and funding arrangements. Comprehensive sequencing with virtual panels predominated in Australia/New Zealand, United Kingdom, and Europe; phenotype-driven panels {+/-} reflex testing were more common in North America. ConclusionsKidney genetics care is expanding but remains unevenly implemented. Nephrologist-led and multidisciplinary models can be effective with appropriate support. Patient selection may influence diagnostic yield more than testing modality. Standardized outcome reporting and theory-driven implementation evaluation are essential for delivering equitable, sustainable genomic services. Lay SummaryThis study examined how kidney genetics services are delivered across the globe. We reviewed 60 studies (2000-2025) and consulted 48 clinic leaders globally. Four service models were identified--multidisciplinary integrated, nephrologist-led, mainstreaming, and traditional genetics referral--and mapped variation in care teams, test strategies, test laboratories, and funding. Most studies reported diagnostic yield, but few assessed patient experience or how well services were implemented. European programs showed the highest performance, attributed to clear referral criteria, deep phenotyping, detailed family histories, multidisciplinary review, and strong public funding. Clinics led by nephrologists performed comparably to multidisciplinary teams when adequately supported. Across all settings, patient selection was more important than the specific type of genetic test used in determining diagnostic success. Kidney genetics services are expanding but remain uneven. This study highlights the need for context-specific, theory-informed, and determinants-targeted strategies to support scalable, equitable, and sustainable genomic care worldwide.

Background and objectivesDiagnostic disclosure practices for autosomal dominant polycystic kidney disease (ADPKD) vary and may influence patient experience and linkage to nephrology care. We characterized patient-reported diagnostic pathways, perceived timing, and disclosure experiences in the PK-DIAG survey. Design, setting, participants, and measurementsCross-sectional web-based survey in France (February 2019-August 2024) among adults with self-reported ADPKD, disseminated via patient organizations. Primary outcomes were poor tact (tact score 0-1 on a 0-5 scale) and very negative diagnostic disclosure experience (overall score 0-1 on a 0-5 scale). Multivariable logistic regression used complete-case analyses. ResultsAmong 1,021 respondents, diagnosis was commonly disclosed outside nephrology care; 49% reported disclosure by a radiologist. Poor tact was reported by 25% and was associated with radiologist (vs nephrologist) disclosure (adjusted odds ratio 2.50; 95% confidence interval 1.57-3.98). Very negative experience was reported by 29% and was associated with poor tact (adjusted odds ratio 4.55; 95% confidence interval 2.90-7.12) and information perceived as insufficient/unclear/inaccurate (adjusted odds ratio 2.52; 95% confidence interval 1.53-4.15). Most participants perceived diagnosis as timely (67%), while 18% perceived it as too early and 15% as too late. Distress (36%) or unmet psychological needs (40%) in the immediate post-disclosure period was common. ConclusionsADPKD diagnostic disclosure often occurred outside dedicated nephrology consultations and was frequently associated with poor tact and inadequate information. These findings support structured, guideline-aligned disclosure pathways incorporating timely counseling, psychosocial support, and rapid linkage to nephrology care. Key PointsO_LIIn PK-DIAG, initial disclosure of ADPKD frequently occurred outside nephrology care, most often by radiologists in radiology settings. C_LIO_LIAbout one quarter of respondents reported poor tact and 29% reported a very negative overall diagnostic disclosure experience. C_LIO_LIPoor tact and information perceived as insufficient/unclear/inaccurate were strongly associated with a very negative diagnostic experience. C_LI

Background: Patients with kidney failure undergoing maintenance hemodialysis suffer high rates of major adverse cardiovascular events(MACE) that are not accurately predicted by traditional cardiovascular risk models. There is an urgent need to identify novel, modifiable cardiovascular risk factors for these patients. Methods: We analyzed associations of 6287 circulating proteins with MACE among 1048 participants undergoing hemodialysis in the Chronic Renal Insufficiency Cohort(CRIC) (14-year follow-up) with validation in the Predictors of Arrhythmic and Cardiovascular Risk in End-Stage Renal Disease study(PACE) (7-year follow-up). In both cohorts, proteins were measured shortly after dialysis initiation and one year later. We compared protein-based risk models derived by elastic net regression to the Pooled Cohort Equations(PCE) optimized for these cohorts(Refit PCE), and to an Expanded Refit PCE that included Troponin T and N-terminal pro-B-type natriuretic peptide. Results: In CRIC, 149 proteins were associated with MACE at false discovery rate<0.05. Among 22 proteins significant at Bonferroni p<8x10-6, proteins that validated in PACE included Sushi von Willebrand factor type A EGF and pentraxin domain-containing protein 1(SVEP1), Complement component C7, R-spondin 4, Tenascin, Fibulin-3 and Fibulin-5. Complement pathways were prominent in network analyses. SVEP1 surpassed other markers by statistical significance, with CRIC HR per log2 1.8 (p=2.1x10-12) and HR per annual doubling 1.6 (p=6.8x10-6). For 2-year MACE, AUC(95%CI) for SVEP1 alone was 0.72(0.59, 0.84) in CRIC, and 0.73(0.63, 0.81) in PACE. SVEP1 surpassed the Expanded Refit PCE in CRIC (0.61 (0.48, 0.73)) (p=0.038). In the pooled CRIC + PACE cohort, SVEP1 AUC(95%CI) (0.79(0.70, 0.88)) surpassed Refit PCE (0.61(0.51, 0.72)) (p=0.004). Conclusions: SVEP1, a 390 kDa protein unlikely to be renally cleared, surpassed over 6000 other proteins and by itself outperformed traditional clinical risk models in predicting MACE in two populations of patients undergoing maintenance hemodialysis. Future studies should provide mechanistic insights behind these findings.

BackgroundRenal biopsy provides important prognostic information for patients with chronic kidney disease (CKD), primarily through evaluation of cortical histopathological lesions, including interstitial fibrosis and tubular atrophy (IFTA). However, the prognostic significance of renal medullary lesions remains poorly understood. We investigated whether medullary pathological findings are independently associated with renal outcomes and whether they improve prognostic discrimination beyond conventional cortical assessments. MethodsThis single-center retrospective cohort study screened 1,136 adult patients who underwent native kidney biopsy between 2011 and 2023. After applying predefined inclusion and exclusion criteria, 488 patients with adequate medullary tissue were included in the final analysis. Medullary fibrosis, inflammatory cell infiltration, and cast formation were semi-quantitatively graded and evaluated as predictors of renal outcomes. The primary outcome was a composite of [&ge;]40% decline in estimated glomerular filtration rate (eGFR) or initiation of renal replacement therapy. Associations were assessed using Cox proportional hazards models with sequential adjustment for demographic factors, baseline eGFR, proteinuria, and cortical IFTA. Model discrimination was evaluated using Harrells concordance-index (C-index). ResultsDuring a median follow-up of 2.3 years, 112 patients (23.0%) reached the composite renal outcome. In multivariable analysis adjusted for age, sex, baseline eGFR, and proteinuria, medullary cast formation was significantly associated with adverse renal outcomes (hazard ratio [HR] 1.70, 95% confidence interval [CI] 1.28-2.24). This association remained significant after additional adjustment for IFTA (HR 1.64, 95% CI 1.21-2.21), whereas medullary fibrosis lost significance after IFTA adjustment. Addition of medullary cast formation improved C-index by 0.016, indicating incremental prognostic value beyond conventional predictors. ConclusionMedullary cast formation is independently associated with renal outcomes and improves prognostic discrimination beyond established cortical parameters. Systematic evaluation of medullary lesions during routine kidney biopsy may enhance risk stratification in CKD. Prospective studies are warranted to clarify the causal role of medullary pathology in CKD progression.

BackgroundRising kidney discard rates and uncertainty around accepting higher risk donor kidneys highlight the need for decision support tools that integrate donor and recipient factors and communicate risk in ways that are understandable and usable at the time of offer. Conventional indices (e.g., KDPI/KDRI) provide population level signals but do not deliver individualized, cognitively accessible information aligned with real time clinical workflows. ObjectiveTo describe how key transplant stakeholders (patients, coordinators, and providers) interpret and evaluate a prototype Kidney Risk Calculator app that generates donor-recipient specific survival projections and to identify the content, format and features, and functionality needed for clinically meaningful, patient-centered decision support. DesignQualitative study using focus groups and individual interviews. SettingUniversity of New Mexico Hospital (UNMH) Kidney Transplant Center. ParticipantsFive patients (four transplant candidates and one patient advocate), three transplant coordinators, and five transplant providers (3 attending physicians and 2 advanced practice practitioners). MethodsSemi-structured sessions (45 to 60 minutes) with 13 stakeholders (patients, coordinators, and providers) included a live app demonstration and explored usability, interpretability, contextual information needs, perceived clinical utility, and anticipated barriers/facilitators. Data were collected via one coordinator focus group, one patient focus group, and five provider interviews; sessions were recorded, transcribed, de-identified, and analyzed using inductive reflexive thematic analysis. ResultsStakeholders affirmed the value of personalized projections as an adjunct to clinical judgment, particularly for higher risk offers. Participants prioritized: 1) Content: clear education on hepatitis C virus (HCV) positive donors and Public Health Service (PHS) risk criteria; plain explanations of Calculated Panel Reactive Antibody (CPRA); and framing that makes time on dialysis and tradeoffs salient; 2) Format & Features: plain language narratives, percentages rather than decimals, simple visuals, minimized acronyms, U.S. customary units, and a stepwise (TurboTax-like) input flow preferred by patients; and 3) Functionality: attention to cognitive load and workflow alignment, given phone based time pressure and digital access constraints. Stakeholders emphasized that the value of the tool hinges on clarity, context, and workflow fit, not predictive accuracy alone. LimitationsSingle center, formative prototype study with a modest sample; findings are illustrative and may have limited transferability. Participants reacted to a demonstration rather than using the app during real time offer calls; convenience/email recruitment and Zoom only English sessions may introduce selection bias; team involvement in app development may contribute residual confirmation bias despite mitigation. ConclusionsEarly stakeholder input suggests that a kidney offer decision support tool should integrate individualized predictions with plain language explanations, contextual information that addresses common misconceptions, workflow aligned functionality, and accessible outputs. Tools designed and implemented with these features may support acceptance of medically complex kidneys and may help reduce offer bypass and organ discard. These inferences reflect stakeholder perceptions in a formative qualitative study and warrant prospective evaluation.

Poor outcomes in proteinuric kidney diseases are challenging to successfully manage therapeutically due to the heterogeneity of underlying disease pathogenesis and associated risk for progression. The role of cytoskeleton-associated proteins, including the scaffolding protein Anillin (ANLN), are of specific interest in kidney disease given the importance of actin dynamics in the kidneys specialized epithelial cell types. In this study, we identify the prevalence of genetic variants in ANLN, the gene encoding ANLN, in a cohort of deeply phenotyped individuals with non-diabetic proteinuric kidney disease. Thirty-one individuals (of 864 genotyped) harbor heterozygously expressed variants in ANLN; 7 unrelated individuals shared the same variant (I1109V) in the C-terminal pleckstrin homology (PH) domain, a region necessary for interaction with the plasma membrane. Kidney organoids generated from I1109V induced pluripotent stem cells from 1 of these individuals showed increased epithelial cell mitogen-activated protein kinase 8 network activity and apoptosis, which was enhanced by tumor necrosis factor alpha (TNF-) and phenocopied by actin polymerization inhibition. TNF--treated I1109V organoids also exhibited tubular lumen expansion. Knockdown and re-expression of the analogous ANLN variant in Xenopus laevis embryonic epithelia resulted in defects in cell-cell junction dynamics including wavy cell membranes exhibiting increased transverse movements as well as abnormal junctional F-actin remodeling in response to mechanical stress and leaky barrier function. Taken together, these results indicate that enhanced tubular epithelial cell death, perturbed cell-cell contacts and barrier function defects are associated with a novel ANLN variant discovered in individuals with non-diabetic proteinuric kidney disease. ONE SENTENCE SUMMARYEnhanced tubular epithelial cell death and perturbed cell-cell junction integrity and barrier function are associated with a novel Anillin coding variant discovered in a cohort of individuals with proteinuric kidney disease.

IntroductionPatients with type 2 diabetes mellitus (T2DM) are at increased risk of coronary artery disease and frequently undergo coronary angiography or percutaneous coronary intervention. Although risk factors for post-contrast acute kidney injury (PC-AKI) are well defined, effective preventive strategies remain limited. MethodsThis multicenter observational cohort study included 975 patients aged 18-75 years who underwent coronary angiography and/or percutaneous coronary intervention with iodinated contrast between June 2023 and June 2024. All patients received standardized intravenous hydration. Participants were grouped according to chronic sodium-glucose co-transporter-2 (SGLT2) inhibitor use ([&ge;]3 months). PC-AKI was defined as a [&ge;]25% or [&ge;]0.5 mg/dL increase in serum creatinine within 48-72 hours after contrast exposure. ResultsThe mean age was 59.2 {+/-} 11.7 years, and 70.8% were male; 16.9% were using SGLT2 inhibitors. PC-AKI occurred in 7.3% of patients, and 0.7% required renal replacement therapy. In univariate analysis, advanced age, diabetes, hypertension, heart failure, diuretic use, and elevated urea, creatinine, potassium, and uric acid levels were associated with PC-AKI. Higher eGFR, albumin, sodium levels, and SGLT2 inhibitor use were inversely associated. In multivariate analysis, age [&ge;]65.5 years (OR 4.53), diabetes (OR 2.49), and uric acid >6.75 mg/dL (OR 2.34) remained independent risk factors, while eGFR >81.5 mL/min/1.73 m2 (OR 0.38), sodium >137.5 mmol/L (OR 0.36), and SGLT2 inhibitor use (OR 0.09) were independently protective. ConclusionBeyond established cardioprotective and renoprotective effects, SGLT2 inhibitors may reduce the risk of PC-AKI in patients with T2DM, potentially through decreased renal oxygen consumption and attenuation of contrast-induced hypoxic injury.

BackgroundKidney cell lines are widely used to model kidney physiology and disease; however, their gene expression profiles may differ from primary cells due to immortalization, culture conditions, or experimental treatments. Determining whether a cell line resembles its native cell type is critical for interpreting in vitro findings. We developed a transcriptome-based approach that matches bulk RNA-seq data from kidney cell lines, primary cells, or tissues to reference cell types derived from single-cell RNA-seq (scRNA-seq) datasets. MethodsReference transcriptomic profiles were generated from two human and two murine kidney scRNA-seq datasets by pseudobulk aggregation. Bulk RNA-seq data from microdissected kidney tissue, non-kidney negative controls, and kidney cell lines were matched to these references using three statistical similarity measures (Spearman correlation, Euclidean distance, Poisson distance) and three machine learning classifiers (Random Forest, XGBoost, TabPFN). Each was assessed with global gene expression, curated kidney marker gene lists, and the most variable genes. Matching accuracy was evaluated through a three-step validation strategy: within-dataset matching, cross-reference comparison, and validation against primary kidney tissue and negative controls. ResultsGene expression rank-based Spearman correlation and TabPFN, a foundation model for tabular data, emerged as the most accurate and specific approaches, particularly with curated kidney marker gene lists. Both methods correctly identified microdissected kidney tubule segments and were robust against non-kidney negative controls. Applied to commonly used kidney cell lines, OK cells retained proximal tubule identity, particularly under shear stress, while other proximal tubule lines (HK-2, HKC-8, HKC-11) showed inconsistent matching. Collecting duct-derived mIMCD-3 maintained stable similarity across passages, culture conditions, and genetic modifications. ConclusionWe provide two complementary implementations: CellMatchR, an accessible web-based tool using Spearman correlation for routine use, and comprehensive scripts for TabPFN-based matching (link will be added after peer reviewed publication). Together, these resources enable researchers to make informed decisions about kidney cell culture model selection, interpretation, and stability. Translational StatementKidney cell lines are fundamental tools in nephrology research, yet their transcriptomic similarity to native cell types is rarely validated systematically. We demonstrate that combining bulk RNA-seq data with single-cell reference datasets enables robust assessment of cell line identity using gene expression-rank-based correlation and machine learning approaches. By providing a comprehensive evaluation of matching methods, curated kidney marker gene lists, and reference datasets, our study serves as both a practical resource and a methodological framework for the kidney research community, facilitating informed selection of cell culture models, quality control of experimental conditions, developing new experimental cell culture models, and more reliable translation of in vitro findings to kidney physiology and disease.

Introduction: Podocyte injury is central to the pathogenesis of most glomerulonephritides (GN) and causes segmental glomerulosclerotic lesions that predict progression in IgA Nephropathy (IgAN). Recent advances in high-resolution microscopy and AI-assisted image analysis have enabled detailed quantification of podocyte foot process (FP) morphology. However, whether nanoscale podocyte morphometrics can predict disease progression or treatment response in GN has not been investigated. Aim: To evaluate whether nanoscale podocyte morphometric parameters predict clinical characteristics, disease progression, and treatment response in GN, with a focus on IgAN. Method: Podocyte morphometrics were analyzed in kidney biopsies from patients with GN using high-resolution microscopy and the deep learning-based tool Automatic Morphometric Analysis of Podocytes (AMAP). Four morphometric parameters were quantified: slit diaphragm length (SDL), FP area, FP circularity and FP perimeter. These parameters were correlated with clinical characteristics, conventional electron microscopy (EM) findings and longitudinal follow-up data. Results: The study included 37 patients with GN from Danderyd University Hospital (Stockholm, Sweden), with IgAN representing the largest diagnostic subgroup (n = 19). The median follow-up for the cohort was 3.0 years. SDL correlated significantly with urine albumin-to-creatinine ratio (uACR; p = 0.021), whereas conventional EM measurements did not (p = 0.22). Within the IgAN subgroup, lower SDL was associated with a steeper decline in eGFR, higher FP area with increased long-term proteinuria, and higher FP circularity with improvement in uACR during the first year. The association between lower SDL and eGFR decline remained as a trend in IgAN patients not treated with corticosteroids (p = 0.068) but was absent in the treatment group (p = 0.59). Conclusion: In this proof-of-concept study, nanoscale podocyte morphometrics demonstrated greater sensitivity than conventional EM in quantifying podocyte injury and predicting progression in IgAN. These findings suggest that high-resolution morphometrics may improve risk stratification in IgAN but require validation in larger, independent cohorts before clinical implementation.

BackgroundLife-sustaining hemodialysis (HD) is onerous for patients, especially those with multiple co-morbidities and advanced age. A standard HD prescription is 720 minutes per week. Alternative HD regiments have been proposed in attempt to maintain quality of life (QOL). Studies are needed to investigate the efficacy and safety of less frequent HD prescriptions in this population. This is an institution-wide observational study in New Brunswick, Canada to compare HD prescriptions and the impact on QOL and mortality. ObjectiveThe purpose of this study is to assess the current HD prescribing practices at a provincial healthcare institution in relation to patient QOL. DesignProspective Observational Study. SettingSingle centre hospital and satellite hemodialysis units. PatientsVoluntarily consented patients undergoing in-centre hemodialysis treatment. MeasurementsObservational clinical data was collected for each study participant from their hospital and dialysis electronic medical records. The KDQOL-36TM questionnaire was used to assess patient-reported quality of life at the time of consent. MethodsAdults undergoing in-centre or satellite site HD for at least 3 months were eligible to participate. Consenting patient participants were grouped by HD prescription whether they were prescribed 720 minutes or more per week or less than 720 minutes per week. All participants completed the KDQOL-36 TM questionnaire to estimate QOL and groups were compared using the Mann-Whitney U statistical test. Emergency department visits, hospitalizations, and mortality were analyzed using a negative binomial regression or a logistic regression. ResultsWe enrolled 140 patient participants; 41 were undergoing less than 720 minutes per week of HD and 99 were undergoing 720 minutes or more of HD per week. Patients who were undergoing less than 720 minutes per week of HD were older [Median (IQR): 76 (72- 81) yrs. vs. 64 (55 - 75) yrs.; p < 0.001], had higher median (IQR) QOL scores on the Symptoms/ Problems List scale on the KDQOL-36 TM questionnaire [79.2 (70.8 - 88.5 vs. 70.8 (62.5 - 81.3); p = 0.0022], and were less likely to present to the emergency department (incident rate ratio 0.52, 95% confidence interval [CI] 0.33-0.81). Mortality was similar between groups, even when adjusted for age and comorbidity score (odds ratio 1.62, 95% CI 0.59-4.49). LimitationsPatient participant enrollment was limited by the single centre nature of this study. As this was an observational study, we did not account for how long the patients had been prescribed less than 720 minutes of hemodialysis. We did not include a frailty assessment of the study participants. A higher number of study participants may have identified significant trends in mortality. ConclusionsThe results of this study show that patients undergoing less than 720 minutes of weekly HD had a higher QOL score for the KDQOL-36 TM Symptoms/ Problems List scale, were less frequently in the emergency department and were not more likely to die than patients undergoing 720 minutes or more of weekly HD. Further studies are required to assess the feasibility and safety of a conservative model of HD prescribing to improve QOL of patients with palliative care treatment goals.

IntroductionCatastrophic bleeding can be fatal in patients on hemodialysis using Arteriovenous (AV) fistulas or grafts. Campaigns, such as the UK "Put a Lid On It" and the Australia "Stop the Bleed" have recommended use of bleeding cessation devices, but evidence for their use remains limited. Recent creation of the bleeding cessation device "Kidney-CAP" mandated further study. The objective of this study was to determine how the Kidney-CAP modified decisions related to vascular access, dialysis modality, and kidney transplantation. MethodsCross-sectional surveys were administered at a Canadian academic nephrology program, to health care providers (HCP) managing patients with chronic kidney disease (CKD), to patients on hemodialysis (CKD-HD), and to patients with CKD but not on dialysis (CKD-Clinic). Two tailed, one sample sign test was used to determine if the median response to Likert scale questions differed from "no effect" response, to a p-value of < 0.05. ResultsSurvey respondents included 18 HCP, 23 CKD-HD and 30 CKD-Clinic patients. Having a Kidney-CAP increased CKD-Clinic patients desire to undergo AVF or AVG creation (p=0.020). Having a Kidney-CAP had no impact on CKD-HD patients deside to undergo AVF creation, or to pursue hemodialysis at home, but increased desire to undergo kidney transplantation (p=0.031). Availability of the Kidney-CAP had no impact on HCP recommendations related to AVF creation or kidney transplantation, but increased HCP recommendations for home hemodialysis in ESKD patients (p=0.039 for each). ConclusionThis is the first study to assess the perceived benefit of a bleeding cessation device, with a focus on clinical decision making related to vascular access, kidney transplantation, and dialysis modality. The Kidney-CAP is associated with increased patient uptake of kidney transplantation and creation of AVF. Further study is required to delineate patient decisions within demographic subgroups such as previous kidney transplant, or anticoagulation status.

BackgroundCatheter-related bloodstream infection (CRBSI) is a major cause of morbidity and mortality among patients undergoing hemodialysis (HD), particularly in low- and middle-income settings where non-tunneled hemodialysis catheters (NTHC) are widely used. Local epidemiological data are essential to guide preventive and therapeutic strategies. ObjectivesTo determine the prevalence, microbiological profile, antimicrobial resistance patterns, and clinical outcomes of CRBSI in patients undergoing HD via internal jugular NTHC at a tertiary care center in South India. MethodsThis retrospective observational study included adults initiated on HD using internal jugular NTHC between January 2017 and December 2023. Patients with pre-existing infections or catheters inserted elsewhere were excluded. CRBSI was defined using KDOQI criteria. Demographic, clinical, laboratory, microbiological, and outcome data were analyzed. Logistic regression identified risk factors, and receiver operating characteristic (ROC) analysis evaluated predictors of adverse outcomes. ResultsAmong 396 patients (mean age 56.3 {+/-} 14 years; 70.4% male), 65 (16.4%) developed CRBSI, with an incidence of 4.7 per 1000 catheter days. Emergency HD initiation (OR 14.86, p < 0.001) and access failure (OR 2.71, p = 0.004) significantly increased CRBSI risk, while planned initiation for uremic symptoms was protective. Patients with CRBSI had lower serum albumin and higher leukocyte counts. Gram-negative organisms predominated (53.8%), with Klebsiella pneumoniae being the most common isolate. High resistance was observed to {beta}-lactam/{beta}-lactamase inhibitor combinations and carbapenems. Gram-negative CRBSI was associated with significantly higher odds of hospitalization, ICU admission, inotropic support, and mortality. ROC analysis showed good predictive ability for adverse outcomes (AUC 0.73-0.77). ConclusionsCRBSI remains a significant complication of NTHC-based HD. Predominant Gram-negative infections with high antimicrobial resistance are associated with worse clinical outcomes, underscoring the need for early permanent access creation, strict catheter care, and robust antibiotic stewardship.

Background and objectiveKidney stone disease (KSD) is common and distinct monogenic forms with well-defined treatment pathways exist. However, it is unclear which patients should undergo genetic testing and the significance of monoallelic variants in SLC34A1, SLC34A3, CYP24A1, SLC7A9, and SLC3A1. We aimed to define monogenic KSD inheritance patterns, determine the diagnostic yield of genetic testing in selected and unselected cohorts, and establish the utility of standard serum biochemistry in highlighting those at risk of monogenic KSD. MethodsWe compared genetic and phenotypic data from individuals with and without KSD in the UK Biobank to determine inheritance patterns. We established the "number needed to test" (NNTT) to identify monogenic KSD in the UK Biobank and a specialist adult kidney stone nephrology clinic where patients had genetic testing based on age, recurrence, and family history. We examined the utility of standard serum biochemistry in identifying monogenic KSD in both settings. Key findings and limitationsMonogenic KSD associated with SLC34A3, SLC7A9, and SLC3A1 is inherited in an autosomal dominant manner and monogenic KSD associated with SLC34A1 and CYP24A1 in an autosomal recessive manner. A monogenic diagnosis was made in [~]1% of KSD in the UK Biobank (NNTT[~]90) and 15% of KSD in a specialist nephrology clinic (NNTT[~]7). In both settings, standard serum biochemistry failed to identify individuals at risk of monogenic KSD. Conclusions and clinical implicationsGenetic testing for monogenic KSD has utility in specialist settings where there is clinical suspicion of an inherited disorder even in the absence of biochemical abnormalities.