Kidney International Reports

Chronic kidney disease is a major global health burden, and its early detection is critical for delaying progression to kidney failure using recently developed targeted therapies. However, current diagnostic screening relies heavily on blood markers that are confounded by muscle mass, and on urine tests that frequently miss structural damage occurring without protein leakage. This creates a critical diagnostic blind spot that hinders timely intervention. Here we show a non-invasive liquid biopsy platform that quantifies a specific protein marker, MUC1, on urinary extracellular vesicles to accurately assess renal parenchymal integrity. By bypassing the systemic metabolic noise of traditional blood tests, our assay provides a remarkably stable, person-specific functional signature. Following extensive validation across diverse cohorts, our longitudinal analysis demonstrated that the discrepancy between this novel urine-based readout and standard blood tests unmasks hidden renal vulnerability, successfully predicting rapid functional decline. By comprehensively evaluating both tubular and glomerular integrity from a single spot urine sample, these findings establish a completely non-invasive, highly scalable prescreening tool that resolves the diagnostic blind spot, enabling broader early detection strategies and ushering in a new era of proactive risk management.

Dysfunction of the tubulointerstitial compartment is a key driver of chronic kidney disease (CKD) progression. However, tubular function remains largely unaddressed by routine clinical assessment. Here, we show that the urine ammonium-pH index (uAPI), a composite of urinary ammonium and pH, reflects kidney tubular function and predicts kidney function decline. Using acid/base, dietary, and potassium perturbations, segmental disruption of tubular ammonium handling, mathematical modelling, and data from patients with renal tubular acidosis, we identified defective ammoniagenesis as the main uAPI determinant. The uAPI was suppressed across four kidney disease models and dissociated from GFR. Kidney proteomics and single-nucleus RNA sequencing indicated downregulation of ammoniagenesis in proteinuric and diabetic kidney disease. In type 2 diabetes patients with preserved GFR, a reduced uAPI was associated with faster kidney function decline. In three CKD cohorts, low uAPI predicted CKD progression and significantly improved risk prediction. Together, this positions the uAPI as a scalable, non-invasive measure of kidney tubular function.

Abstract Background Alport Syndrome (AS), caused by pathogenic variants in type IV collagen genes COL4A3/4/5, is a leading monogenic cause of Kidney Failure (KF). Clinical course varies widely, and disease specific predictors of progression relevant to clinical care and trial design remain incompletely defined. Methods In this retrospective cohort study of individuals with AS in the UK National Registry of Rare Kidney Diseases, patients were classified as having AS or heterozygous genotypes and followed to assess proteinuria progression, eGFR slope and kidney survival. Proteinuria and eGFR trajectories were analysed using mixed effects regression models; kidney survival using Kaplan Meier analysis. Results Among 1032 participants (median follow up 11.6 years; 47% female), 475 (46%) had AS genotypes (Male XLAS or autosomal recessive AS). eGFR decline accelerated with advancing CKD stage across all genotypes (p<0.001). Proteinuria increased as eGFR declined and occurred earlier in AS genotypes. After reaching proteinuria thresholds of more than 1.0 and 3.0g/g, kidney survival over the subsequent 5 years did not differ significantly between genotypes (logrank p=0.14, p=0.17, respectively), although modest differences emerged over longer follow-up. Across eGFR thresholds (90, 60, and 45mL/min/1.73m2), higher proteinuria was associated with shorter time to KF; for example, at eGFR 45mL/min/1.73m2, median time to KF was 3.0 years (IQR, 1.6-5.4) for above-median vs 6.5 years (5.1-not estimable) for below-median proteinuria (p<0.0001). Almost all patients who reached KF had developed proteinuria of more than 0.3g/g. Conclusion In this national cohort, eGFR decline accelerated with CKD stage and proteinuria was strongly associated with progression to KF across genotypes. The non linearity of eGFR decline may inform its interpretation in clinical practice and use as a trial endpoint. Once comparable proteinuria levels were reached, differences in outcomes by genotype were attenuated, supporting proteinuria as a key prognostic marker and strengthening rationale for its use as a surrogate endpoint in AS clinical trials

Introduction Acute interstitial nephritis is an important differential diagnosis in patients with deteriorating kidney function. Diagnosis currently requires kidney biopsy, an invasive procedure associated with risks. We hypothesized that urinary T cells may serve as a non-invasive biomarker for acute interstitial nephritis. Methods A total of 320 patients undergoing clinically indicated kidney biopsy were enrolled in a discovery cohort at Charite Berlin (n = 80), an internal validation cohort at Charite (n = 100), and an external validation cohort at The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou (n = 140). Urinary immune cells were assessed by flow cytometry. Renal T cell infiltration was evaluated by immunofluorescence in kidney biopsy specimens from the discovery and internal validation cohorts, including 16 patients with acute interstitial nephritis and 9 patients without acute interstitial nephritis. Additionally, CXCL9 was measured by ELISA in 102 urine samples from these cohorts. Results Across all cohorts, 27 patients (8.4%) were diagnosed with acute interstitial nephritis. In the discovery cohort, multiple urinary T cell subsets were increased in acute interstitial nephritis, with activated CD4+ effector memory T cells expressing CD38 and HLA-DR showing the strongest diagnostic performance. This marker outperformed urinary monocytes, eosinophils, and CXCL9 and was validated in both independent cohorts. Across all cohorts, the area under the receiver operating characteristic curve was 0.84 and increased to 0.91 after exclusion of 8 patients receiving corticosteroids. A cutoff of 211 activated CD4+ effector memory T cells per 100 mL urine yielded a sensitivity of 78% and a specificity of 81%. Urinary activated CD4+ effector memory T cell counts correlated with renal CD4+ and CD4+ CD38+ T cell infiltration in acute interstitial nephritis. Conclusions Urinary activated CD4+ effector memory T cells expressing CD38 and HLA-DR represent a promising non-invasive biomarker for the diagnosis of acute interstitial nephritis.

Monoallelic pathogenic or likely pathogenic variants in COL4A3 and COL4A4 occur in approximately 1 in 106 individuals, yet whether these paralogous genes confer equivalent pathogenicity for the same variant classes has not been tested at population scale. Using whole-genome sequencing data from the UK Biobank (UKB; n = 500,000), with replication in the All of Us Research Program (n = 414,000), we performed per-variant association testing, gene-based collapsing analyses and phenome-wide association studies (PheWAS) across haematuria, proteinuria and chronic kidney disease. We identified 64 COL4A3 and 92 COL4A4 rare variants significantly associated with haematuria or proteinuria, generating a quantitative allelic series for clinical variant interpretation. Glycine substitutions within collagenous domains conferred similar risks in both genes. In contrast, truncating and non-collagenous domain (NC1) missense variants were strongly associated with haematuria and proteinuria in COL4A4 carriers but showed substantially attenuated or absent associations in COL4A3 carriers despite comparable carrier frequencies and predicted pathogenicity scores. These findings were independently replicated in All of Us. Genome-wide association analysis identified the COL4A3/COL4A4 locus as the dominant genetic determinant of haematuria, with the signal attributable to the aggregate effects of rare coding variants and no evidence of independent common variant or trans-acting modifier effects. These findings demonstrate substantial gene-specific differences in tolerance to truncating and NC1 variants between COL4A3 and COL4A4, challenging assumptions of equivalent pathogenicity across paralogous collagen IV genes. Gene identity and not variant class alone, should inform risk stratification, variant interpretation and genetic counselling in individuals carrying collagen IV risk genotypes.

Chronic kidney disease (CKD) is accompanied by systemic inflammation, but whether inflammatory proteins improve risk stratification beyond kidney function and albuminuria remains unclear. We profiled baseline serum samples from 683 children with CKD in the prospective European 4C study using the Olink Target 96 Inflammation panel and related protein levels to kidney outcomes over 8 years. eGFR and albuminuria were the dominant determinants of the inflammation-related serum proteome. Nonetheless, a four-protein inflammation score (iScore; CD40, CD137, PD-L1 and CX3CL1), defined from protein residuals independent of eGFR and albuminuria, stratified kidney survival and predicted CKD progression beyond established clinical risk factors (adjusted hazard ratio per elevated protein, 1.11; 95% CI, 1.01-1.22). The score showed concordant associations in 2,770 UK Biobank participants with reduced eGFR (adjusted hazard ratio, 1.08; 95% CI, 1.02-1.14). Kidney single-cell transcriptomic analysis mapped these axes to immune-parenchymal communication programs in CKD, supporting inflammation-based risk stratification across the life course.

Background: Current understanding of acute kidney injury (AKI) risk factors remains largely descriptive, offering limited precision into how specific biomarker values or physiologic thresholds influence susceptibility. We aimed to synthesize knowledge from machine learning models trained across multiple health systems to identify generalizable, value-specific risk drivers and biomarker interactions contributing to AKI risk. Methods: We analyzed electronic health records (EHRs) from 785,497 adult inpatients between 2010 and 2019 across nine U.S. academic medical centers within PCORnet. Interpretable gradient boosting machine models were independently developed at each health system to quantify predictor-outcome associations. Meta-regression was applied to integrate these site-level results, characterize nonlinear value-risk relationships, and identify bivariate interactions between predictors. Results: Meta-analysis revealed consistent, value-specific risk drivers across health systems. An increase in glucose from 100 mg/dL to 140 mg/dL was associated with a 1.46-fold higher risk of AKI. Chloride and anion gap also demonstrated elevated AKI risk with risk increases overlapping portions of their reference ranges, with anion gap showing a 1.14-fold increase across 4-12 mmol/L and chloride a 1.28-fold increase across 96-100 mEq/L. Electrolytes including potassium, calcium, and sodium showed quadratic associations with AKI risk. Bivariate meta-regression identified interactions between key predictors, highlighting pathways that jointly modulate AKI risk. Conclusion: This cross-system meta-analysis synthesizes machine learning-derived evidence into clinically interpretable knowledge, revealing how specific biomarker ranges and interactions modulate AKI risk. By moving beyond surface-level associations to quantitative, generalizable physiologic thresholds, these findings provide actionable insights to enhance risk stratification and personalized prevention in hospital care.

Importance: Recently, proteinuria has been accepted as a surrogate end point for clinical trials in focal segmental glomerulosclerosis (FSGS) ang IgA nephropathy. However, proteinuria has not been evaluated in Apolipoprotein L1 (APOL1)-mediated kidney disease (AMKD). Methods: Real world data (RWD) analysis of 128 patients of African ancestry with APOL1 high risk genotypes, without diabetes, enrolled in the Million Veteran Program (MVP; n=109) or the biorepository at Vanderbilt University (BioVU; n=19), who had urine albumin-creatinine ratio (UACR) >= 420 mg/g (PCR~0.9 g/g) with a concurrent GFR value. The main predictor was change in the log-UACR at 12 months. The primary outcome was annual GFR slope over 24 months. Secondary outcomes included a kidney composite of a sustained 30% GFR decline, end stage kidney disease (ESKD) or death and ESKD as a single outcome. Linear regression and Cox proportional hazards models were used to assess the effect of changes in UACR and the outcomes. Results: In the pooled analysis the mean age was 56.8 (SD 15.5) y, 116 were male (90.6%) and three patients had diagnosis of FSGS at baseline. Mean baseline eGFR was 46.8 (SD 16.1) mL/min/1.73m2, mean baseline UACR was 1240.8 (1107.7) mg/g, mean eGFR slope was -4.67[-6.00, -3.33] mL/min/1.73m2/year and the geometric mean percentage changes in the UACR at 12 months were -57.5% [-65.0%, -48.4%]. For every 1 unit of log (UACR) increment at 12 months, the annual eGFR slope decreased by -1.80 [-2.56, -1.03] mL/min/1.73m2 in the pooled analysis. For every 1 unit of log (UACR) increment at 12 months, the Cox regression showed a 61% increase in the risk of a kidney composite (p=0.002) and a 98% increase in the risk of ESKD (p<0.001). It was estimated that a 50% reduction of UACR at 12 months was associated with a 28% reduction in the kidney composite endpoint (adjusted hazard ratio [aHR]=0.72; 95% confidence interval [CI]:0.59-0.88; p=0.002), and a 38% reduction in the risk of ESKD (aHR=0.62; 95% CI:0.49-0.80; p<0.001). Conclusions and relevance: Changes in UACR at 12 months significantly modify the rate of decline of GFR over 24 months and clinically meaningful endpoints, supporting the use of UACR changes as surrogate endpoint in AMKD.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by cysts from different nephron segments, yet their origin remains inaccessible to in vivo imaging. Building on ex vivo studies that cyst sodium concentration ([Na+]) may reflect tubular origin, we developed a non-invasive 23Na magnetic resonance imaging (MRI) approach at 7 Tesla to phenotype ADPKD cysts in vivo based on cyst sodium. In nephrectomized ADPKD kidneys, cyst fluid [Na+] closely matched 23Na MRI signal intensities, revealing two distinct cyst phenotypes: serum-like high-[Na+] cysts and low-[Na+] cysts. High-[Na+] cysts expressed the proximal tubular marker sodium-glucose cotransporter-2, whereas low-[Na+] cysts expressed markers of distal tubules and collecting ducts. The vasopressin V2 receptor (V2R), the therapeutic target of tolvaptan, was detected exclusively in low-[Na+] cysts, linking sodium phenotype to therapeutic target expression. In vivo, 23Na MRI enabled classification of 2,299 cysts in 20 ADPKD patients. High-[Na+] cysts were 1.8-fold more frequent overall. Anatomical cyst localization did not predict sodium phenotype, underscoring the need for functional imaging rather than structural inference. Patients exhibited marked interindividual variation in cyst composition, with low-[Na+] cysts comprising 4.6% to 83.9% of all cysts. Given the exclusive expression of V2R in low-[Na+] cysts, this heterogeneity may influence disease progression and therapeutic responsiveness. These findings establish 23Na MRI as a non-invasive method to phenotype ADPKD cysts in vivo and provide a functional imaging approach with potential relevance for stratifying patients and guiding future therapeutic interventions.

Introduction: Autosomal-dominant tubulointerstitial kidney disease (ADTKD) is characterized by chronic kidney disease (CKD) with an average age of end-stage renal disease (ESRD) of approximately 45 years, bland urinary sediment, the absence of proteinuria and autosomal dominant inheritance. While several causative genes have been found, there remain families in whom no molecular diagnosis has been identified (ADTKD-NMD). Methods: We identified BICC1 truncating variants in several families with ADTKD-NMD in the Wake Forest Rare Inherited Kidney Disease Registry and then screened families in our database and other referred families for BICC1 truncating variants. We performed segregation analysis and characterized affected individuals for clinical and histopathologic phenotypes. We analyzed oligomer formation of BICC1 mutants with wild-type BICC1-, ANKS3- and ANKS6 proteins through co-immunoprecipitation and Western blotting, and we tested for posttranscriptional regulation of the BICC1 target mRNA, Dand5, in a Luciferase reporter assay. Results: We found 6 heterozygous truncating mutations in BICC1 segregating with the ADTKD phenotype in 8 independent pedigrees worldwide. Affected individuals developed kidney failure in the 6th to 7th decade of life that was characterized pathologically by tubular atrophy and interstitial fibrosis. The truncated gene products localized to cytoplasmic bodies and demonstrated various degrees of self-association or binding to the known interaction partners, ANKS3 and ANKS6. While the wild-type BICC1 gene product acts as a posttranscriptional repressor of target mRNAs, all truncation variants exhibited increased expression of substrate mRNA. Conclusions: Truncating variants in BICC1 are a novel cause of ADTKD, segregating with the disease phenotype and upregulating BICC1 target gene expression through a dominant-negative- or a gain-of-function mode of action.

Banff acute lesion scores underpin histologic classification of kidney allograft biopsies; however, biomarker studies rely on second-order associations with diagnostic categories that introduce confounding. We quantified the first-order relationships between Banff acute lesion scores and the validated urinary cell three-gene rejection signature. In 354 biopsy-urine pairs, three-gene signature scores computed using a locked regression equation incorporating absolute copy numbers of CD3E mRNA, CXCL10 mRNA, and 18S rRNA in urinary cell RNA-were related to glomerulitis (g), peritubular capillaritis (ptc), interstitial inflammation (i), and tubulitis (t). Signature scores rose monotonically with Banff acute lesion severity, with 1.5 to 1.8-fold higher odds of more severed g, ptc, i, and t (all P<0.0001), and showed good calibration. Associations remained robust for composite microvascular (g+ptc) and tubulointerstitial (i+t) indices and were strongest for severe g and t, supporting this signature as a noninvasive, quantitative readout of acute rejection pathology with immediate diagnostic applicability.

While ultra-rare missense variants in UMOD cause highly penetrant autosomal dominant tubulointerstitial kidney disease, a more frequent UMOD T62P variant conveys intermediate risk with variable penetrance. To determine whether age or polygenic risk contributes to the variable penetrance of T62P, we combined genotype and phenotype data from 882,306 individuals across the UK Biobank (discovery cohort) and the All of Us and MyCode biobanks (validation cohorts). We also analyzed the impact of aging on uromodulin processing and cellular stress in stably transfected kidney tubular cells expressing wild-type or mutant UMOD. We compared the effects of the GPS on risk of CKD between T62P carriers and non-carriers and tested for the GPS-by-T62P interaction. The UMOD T62P variant was reproducibly associated with increased risk of CKD in an age-dependent manner. Compared to wild-type, clones of T62P-expressing cells exhibited a defective uromodulin maturation profile, causing endoplasmic reticulum retention and stress. We also observed significant T62P-by-GPS interaction, with T62P carriers in the top quintile of the GPS having over 5-fold higher risk of CKD compared to population average (OR 5.17, 95%CI: 2.94-9.08, P=1.0E-08). In summary, we demonstrate that the penetrance of kidney disease in T62P carriers is strongly modified by both age and polygenic risk.

The genetic architecture of early-onset chronic kidney disease (CKD) is caused by more than 200 monogenic genes, where their common diagnostic classes include congenital anomalies of the kidney and urinary tract, steroid-resistant nephrotic syndrome, nephronophthisis-related ciliopathies, chronic glomerulonephritis, and urinary stone disease. While advancements in whole-exome and whole-genome sequencing have enabled identification of disease-causing variants, their rates of classification have remained unknown. Likewise, the molecular effects of these pathogenic variants remain unresolved, which is essential for improving personalized treatment approaches. In this study, we collected clinical and biophysical data from 117,373 genetic variants across 129 monogenic genes causing early-onset CKD. This data established the NephVar registry, which aims to be a molecular dictionary for nephrologists to classify variants and resolve their unique molecular effects. Through NephVar, we estimated 1-15% of alleles are reclassified and the time to reclassification per variant is 2-12 years in early-onset CKD. Furthermore, NephVar identified the molecular effects of all variant types, emphasizing missense variants. Our analyses indicate that intrinsically disordered regions of proteins are protective against disease-causing missense alleles across most diagnostic classes, but often occur through a buried loss-of-function (LoF) mechanism. Additionally, we show that the mode of inheritance for these monogenic genes influences clustering patterns of genetic variants, where autosomal dominant (AD) genes are more clustered than those of autosomal recessive (AR) genes. This data accurately predicted the non-LoF effects in INF2, PAX2, GATA3, ACTN4, and LMX1B causing inherited nephrotic syndromes. We demonstrate that variant effect prediction is effective for downgrading variants of unknown significance and classifying AR genes, but challenging for pathogenic alleles in AD genes. Lastly, we propose standards and guidelines for determining non-LoF effects, including gain-of-function and dominant negative, in inherited nephrotic syndrome. Overall, the NephVar renal registry has important implications for defining the molecular architecture and estimating the progress of molecular diagnostics for early-onset CKD.

Background: Initiation of emergency dialysis, often requiring temporary catheter owing to unprepared definitive vascular access, is associated with infectious and vascular complications and suggests advanced chronic kidney disease (CKD) care gaps. Previous studies focused on kidney failure or dialysis timing. This study aimed to predict initiation of emergency dialysis using machine learning and baseline data. Methods: This retrospective cohort study used the Japan Medical Data Center claims data (2014-2022). Adults with an estimated glomerular filtration rate (eGFR) <15 mL/min/1.73 m2 were included. The primary outcome was initiation of emergency dialysis (temporary catheter code without evidence of previous access preparation). Participants were randomly divided into derivation (80%) and validation (20%) cohorts. Logistic regression, support vector machine, XGBoost, LightGBM, and random forest models were evaluated using internal cross-validation, post-hoc calibration of the selected model, and bootstrap confidence intervals. Results: The cohort included 3,062 individuals (derivation; n=2,449, validation; n=613). Emergency dialysis was initiated in 237 participants (7.7%); 185 (7.6%) and 52 (8.5%) in the derivation and validation cohorts, respectively. Validation area under the receiver operating characteristic curve ranged from 0.781-0.799, with the highest value observed for random forest (0.799, 95% confidence interval; 0.740-0.850). Risk stratification showed clear event enrichment in higher predicted risk categories. SHAP analyses identified hemoglobin, proteinuria, baseline eGFR, diabetes history, and diuretic use as key predictors. Decision curve analysis showed greater net benefit than eGFR alone at lower threshold probabilities. Conclusions: Baseline machine learning models showed moderate discrimination for initiation of emergency dialysis and identified clinically plausible predictors. These findings support potential use for risk stratification, although external validation and evaluation within pre-specified care pathways are needed before implementation.

Background. Chronic kidney disease (CKD) affects 10-13% of adults worldwide but remains largely undiagnosed until advanced stages. Hospitalization provides an opportunity for early detection through opportunistic urine albumin-to-creatinine ratio (UACR) measurement. Methods. We conducted a prospective three-arm study of opportunistic CKD screening in general internal medicine wards at Hadassah Mt. Scopus (MS), Hadassah Ein Kerem (EK), and Shaare Zedek Medical Center (SZMC) in Jerusalem (Protocol HMO-23-0300). Adult inpatients without known CKD or recent UACR were enrolled. Pathological UACR was defined as [&ge;]30 mg/g. Confirmed CKD required two pathological measurements [&ge;]90 days apart (KDIGO-compatible). eGFR was computed using the 2021 CKD-EPI race-free equation. Pooled proportions were estimated by fixed-effects logit meta-analysis; odds ratios by DerSimonian-Laird random-effects models. Results. A total of 158 patients were enrolled (MS n=50, EK n=57, SZMC n=51). Pathological first UACR was identified in 43/158 patients (27.2%; 95% CI 21.3-34.1%; I2=0% across centers). Of 24 patients with a second UACR available, 14 (58%) confirmed CKD, yielding a pooled confirmed-CKD rate of 8.9% of all screened patients. In-hospital mortality was significantly higher among patients with pathological UACR (9.3% vs ~2%; Fisher's exact p=0.012). In per-center multivariate logistic regression, three predictors reached pooled significance: BUN (OR 1.10 per mg/dL, 95% CI 1.04-1.17, p=0.002, I2=0%), heart failure (OR 3.21, 95% CI 1.34-7.70, p=0.009, I2=0%), and diabetes mellitus (OR 2.54, 95% CI 1.11-5.82, p=0.028, I2=17%). Cardiac/vascular admissions had the highest pathological UACR rate (~42%); GI/hepatic admissions had 0%. Conclusions. Opportunistic inpatient UACR screening identifies previously unrecognized CKD in approximately 9% of general internal medicine patients, with consistent results across three independent centers. BUN elevation, heart failure, and diabetes are the strongest independent predictors. Pathological UACR carries significant short-term mortality risk, supporting integration of routine screening into inpatient care pathways.

Abstract Objective: To synthesize the available evidence on the association between SARS-CoV-2-related microvascular thrombosis and acute kidney injury (AKI), with emphasis on renal outcomes, mortality, and renal replacement therapy requirements. Methods: This systematic review followed the PRISMA 2020 statement and was prospectively registered in PROSPERO (CRD420251132701). PubMed/MEDLINE, Scopus, and Embase were searched for systematic reviews, including meta-analyses, and umbrella reviews investigating the association between SARS-CoV-2-related microvascular thrombosis and acute kidney injury. Two reviewers independently performed study selection, data extraction, and methodological quality assessment using AMSTAR-2 and ROBIS. Evidence was synthesized through a structured narrative synthesis supported by quantitative data extracted from the included reviews. Results: Six evidence syntheses evaluating kidney involvement, thrombotic events, and microvascular mechanisms in COVID-19 were included. AKI incidence was 9.2% (95%CI 4.6-13.9) among hospitalized patients and 32.6% (95%CI 8.5-56.6) among critically ill patients. In children with multisystem inflammatory syndrome associated with SARS-CoV-2, AKI incidence was 20% (95%CI 14-28). Microvascular or thrombotic events were associated with adverse renal outcomes (OR 2.14; 95%CI 1.32-3.48). AKI was associated with increased mortality (OR 4.68; 95%CI 1.06-20.70) and greater likelihood of renal replacement therapy requirement (OR 2.87; 95%CI 1.45-5.68). The certainty of evidence ranged from moderate to high for the principal outcomes. Conclusion: Current evidence supports an important association between microvascular thrombotic injury and COVID-19-associated AKI. These findings reinforce the relevance of endothelial dysfunction and thromboinflammatory pathways in kidney involvement during COVID-19 and highlight the need for early renal monitoring, risk stratification, and kidney-protective strategies in high-risk patients. Keywords: COVID-19; Acute Kidney Injury; Microvascular Thrombosis; SARS-CoV-2; Renal Replacement Therapy; Systematic Review

Background: Traditional real-world studies comparing SGLT2 and DPP4 inhibitors on renal outcomes rely on propensity score matching, which causes high-dimensional data loss. We used causal machine learning (Causal ML) to unmask heterogeneous treatment effects in diabetic kidney disease (DKD). Methods: Using data from 4,588 patients within the Japanese J-CKD-DB-Ex registry, we implemented a doubly robust (DR) learning framework (Linear DR-learner with XGBoost) to compare SGLT2 and DPP4 inhibitors. Outcomes included the chronic eGFR slope and a composite renal endpoint ([&ge;] 50% eGFR decline or end-stage kidney disease). Heterogeneity was explored via causal SHAP and decision trees. Results: At the population level, SGLT2 inhibitors modestly slowed chronic eGFR decline (average treatment effect [ATE] = 0.14 [95% CI: -0.86, 1.15] mL/min/1.73m^2/year) and reduced composite endpoint risk by 9% (ATE: -0.09 [-0.11, -0.08]) versus DPP4 inhibitors. However, individual-level counterfactual analysis suggested that for the chronic eGFR slope, non-glinide users with stable pre-treatment trajectories who were also taking ACE inhibitors had a greater benefit from SGLT2 inhibitors (ATE: 2.95 [-0.68, 6.58]). Conversely, glinide users with steep pre-treatment decline had a greater benefit from DPP4 inhibitors (ATE: -8.98 [-16.11, -1.85]). For composite renal events, SGLT2 inhibitors had a 28% absolute risk reduction within the algorithmically identified high-risk subgroup (eGFR [&le;] 28.1 mL/min/1.73 m^2 and positive proteinuria; ATE: -0.28 [-0.33, -0.23]). Even non-proteinuric decliners demonstrated a 8% risk reduction with SGLT2 inhibitors (ATE: -0.08 [-0.10, -0.06]). Conclusion: Causal ML advances precision medicine in DKD, shifting from uniform prescribing to individualized, data-driven therapy targeting distinct intrarenal pathways.

Background: Whether benchmark performance reflects robust clinical reasoning rather than surface-level pattern recognition remains uncertain. We evaluated the robustness of state-of-the-art large language models (LLMs) on nephrology board renewal questions using "None of the other answers" (NOTA) substitution. Methods: From 210 Japanese Society of Nephrology board renewal questions (2014-2023), two nephrologists independently reviewed all items. Questions in which NOTA became the sole correct answer after replacement were included, yielding 145 validated questions. GPT-5, GPT-4o, Gemini 2.5 Pro, and Gemini 2.0 Flash were evaluated via application programming interfaces under default settings. The primary endpoint was accuracy, and paired differences were assessed using the exact two-sided McNemar test. Results: Accuracy was significantly lower after NOTA substitution for all models: GPT-4o, 66.21% to 19.31% (drop, 46.90 percentage points [pp]); GPT-5, 87.59% to 73.10% (14.48 pp); Gemini 2.0 Flash, 58.62% to 31.03% (27.59 pp); and Gemini 2.5 Pro, 86.90% to 55.86% (31.03 pp); all P < .001. GPT-5 showed the smallest decline and the highest accuracy in both versions. Conclusions: All evaluated LLMs showed a significant robustness gap after NOTA replacement. Newer models may be more robust, but multiple-choice accuracy remains an incomplete measure of clinical reasoning robustness.

Background IgA vasculitis (IgAV) is the most common systemic vasculitis in children, and its prognosis is largely determined by renal involvement (IgAV nephritis). No routine blood test identifies IgAV or stratifies the risk of nephritis, although aberrant O-glycosylation of the IgA1 hinge region is central to its pathogenesis. We developed a mass-spectrometry assay to profile IgA1 hinge O-glycoforms and define signatures of disease activity and renal involvement. Methods IgA was affinity-purified from 5 uL of plasma from 91 children (27 with acute IgAV, 26 in remission, and 38 age-matched healthy controls; 24 with and 29 without nephritis), trypsin-digested, and hinge-region O-glycopeptides were quantified by LC-MS. Sixty-nine glycoforms were normalized to a total-IgA1 tryptic peptide. Duplicate measurements showed good analytical repeatability, with a median coefficient of variation of 6%. Groups were compared using Mann-Whitney and Kruskal-Wallis tests (Benjamini-Hochberg FDR). Discrimination was assessed by ROC analysis and cross-validated logistic regression panels. Results Acute IgAV showed broad remodeling of the hinge glycoform profile (35 glycoforms differed with excellent discrimination (AUC 0.93-0.95) for the best ones), with an increase in low-sialylated, agalactosylated species and a decrease in complex sialylated species. The profile was normalized in remission (no glycoform differed from the controls). Two distinct renal patterns emerged: disease-associated glycoforms already altered without nephritis and renal-specific glycoforms altered only in nephritis (H2N2S1, H3N3S5, H3N4S4, and H4N4S3). A four-marker panel discriminated nephritis among IgAV children with a cross-validated AUC of 0.86 (IC95 % 0.75-0.94). Conclusions A single mass-spectrometry assay, from a small blood volume, captures an IgAV-associated IgA1 hinge O-glycoform signature that normalizes in remission, together with a distinct renal involvement associated signature. These findings identify candidate IgA1 O-glycoform signatures associated with IgAV activity and documented renal involvement. Prospective longitudinal studies are required to determine whether the renal-associated panel can predict subsequent nephritis.

Background Diagnostic interpretation of kidney allograft biopsies using the Banff classification remains variable, but the determinants of this variability are not fully defined. We performed a global, fully digital multi-reader study to identify the principal drivers of disagreement in Banff-based assessment. Methods Thirty six kidney transplant biopsies were independently scored by 67 renal pathologists on a standardized digital platform. Readers assessed Banff lesions on hematoxylin and eosin, periodic acid Schiff, and Jones' silver stains; final diagnostic categories were assigned using prespecified Banff-based decision rules. Interobserver agreement was quantified with Gwet's agreement coefficient (AC) statistics. Determinants of diagnostic agreement were evaluated) using pairwise mixed-effects logistic regression, and reader similarity was examined by principal component analysis (PCA) with post hoc molecular annotation. Results Agreement for final diagnostic categories was moderate (Gwet's AC1, 0.55; 95% CI, 0.47 - 0.63). Lesion-level agreement varied substantially, with lowest agreement for selected threshold-dependent inflammatory or semi-quantitative lesions, including interstitial inflammation in areas of IFTA, peritubular capillaritis and arteriolar hyalinosis. Diagnostic concordance differed markedly across biopsies, indicating strong case-level heterogeneity. In pairwise models, differences in active inflammatory and vascular lesion scoring were the strongest correlates of diagnostic disagreement; reader experience and geography contributed minimally. Principal component analysis showed reader variation was organized along two dominant axes: a rejection-calling threshold axis linked mainly to tubulointerstitial inflammatory injury, and a T cell-mediated (TCMR/TI) and antibody-mediated/microvascular (AMR/MVI) inflammation-oriented phenotypic classification axis. Conclusion Interobserver variation in Banff-based kidney transplant biopsy assessment is structured rather than random and driven mainly by how readers threshold and integrate key inflammatory lesion compartments rather than experience or geographic location.