Kidney360

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.

Background: Fibrosis, characterised by excessive accumulation of collagen type I (COL1), is a common feature of chronic diseases, including liver diseases (LDs), chronic kidney disease (CKD) and heart failure (HF). COL1 degradation products can be detected in urine by proteomics/ peptidomics analyses and may serve as non-invasive biomarkers of fibrosis. We aimed to identify a common molecular signature of fibrosis across these diseases that may ultimately guide interventions to slow disease progression and prevent organ damage. Methods: Using capillary electrophoresis coupled to mass spectrometry (CE-MS), naturally occurring COL1 degradation products (peptides) in the urine of patients with fibrotic disease, LDs (n=127), CKD (n=263) or HF (n=187), were investigated and compared with the same number of matched controls. Disease-associated COL1 peptides were identified separately for each condition, and peptides showing consistent associations across the three diseases were selected to define a common fibrosis signature. A support vector machine model based on the selected peptides was developed and validated in independent cohorts of patients with LDs (n=110), CKD (n=93), HF (n=32) and controls (n=643). Results: We identified a common fibrotic signature consisting of 50 COL1 degradation products, mainly downregulated in fibrosis. A model based on these peptides achieved a strong performance, with an area under the receiver operating characteristic curve (AUC) of 0.935 (95% confidence interval (CI) 0.917-0.953, p<0.0001) in an external validation cohort comprising pooled disease groups (LDs, CKD, and HF) and controls. Performance was maintained in LDs, CKD and HF, with AUCs of 0.917 (95% CI 0.890-0.944, p<0.0001), 0.951 (95% CI 0.931-0.971, p<0.0001) and 0.950 (95% CI 0.903-0.997, p<0.0001), respectively. The model scores were significantly associated with fibrosis stage in LDs (p=0.0097) and with interstitial fibrosis and tubular atrophy in CKD (p=0.045). Conclusion: A model of urinary COL1 peptides captures a shared collagen degradation signature across organs and diseases, enabling the non-invasive assessment of fibrosis irrespective of its origin. As these peptides exclusively reflect collagen degradation, the findings suggest impaired collagen degradation as a driver in fibrosis. Future clinical studies are warranted to evaluate the utility of this model for early fibrosis detection and earlier implementation of anti-fibrotic interventions.

Background: Genomic reassessment may reveal clinically relevant diagnoses in patients with young-onset kidney failure despite established clinical diagnostic labels. We evaluated this approach after excluding clinically apparent polycystic kidney disease (PKD). Methods: Among 1,139 patients receiving maintenance dialysis at participating Japanese facilities, 355 had initiated dialysis at age [&le;]50 years. After excluding 17 patients with clinically apparent PKD, 108 of 338 eligible patients underwent whole-genome sequencing through voluntary, nonrandom enrollment. Analysis included 465 nuclear candidate genes, mitochondrial DNA, and copy-number/structural variants. Clinically concordant diagnoses were adjudicated using integrated clinical and genetic evidence, with a separate pathogenic/likely pathogenic (P/LP)-supported subset. Results: Diagnoses were identified in 10/108 participants (9.3%; 95% confidence interval, 5.1-16.2), comprising seven renal and three systemic/metabolic diagnoses. Nine diagnoses were P/LP-supported (8.3%; 95% confidence interval, 4.4-15.1). The remaining diagnosis was phenotype-based clinical Dent disease associated with a CLCN5 variant of uncertain significance. Diagnoses occurred across diabetic kidney disease, nephrosclerosis, chronic glomerulonephritis, unknown-cause, and other clinical categories. In a post hoc analysis excluding three participants with low target coverage, the integrated and P/LP-supported proportions were 9/105 (8.6%) and 8/105 (7.6%). Six exploratory findings were excluded from both diagnostic numerators. Gitelman syndrome was included as a clinically manifest renal disorder, although its contribution to kidney failure remained uncertain. Conclusions: Integrated genomic assessment can uncover renal and systemic/metabolic diagnoses across conventional labels in young-onset kidney failure after exclusion of clinically apparent PKD. Nonrandom enrollment and variable sequencing coverage limit generalizability and interpretation of negative results.

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.

Background: Noninvasive biomarkers capable of detecting kidney allograft injury and distinguishing rejection from infection remain an important clinical need. Torque teno virus (TTV) reflects host immune status, but its utility in urine has not been well established. We evaluated urinary TTV, total cell-free DNA (cfDNA), cfDNA fragmentation, and BK polyomavirus (BKV) as potential biomarkers of kidney transplant rejection and BK polyomavirus-associated nephropathy (BKPyVAN). Methods: Urine samples from 334 kidney transplant recipients were analyzed in association with kidney biopsies performed within 30 days of sample collection. TTV and cfDNA were measured by multiplex quantitative PCR (qPCR), with a subset analyzed by digital PCR (dPCR), and BKV was quantified by qPCR. Associations with biopsy results were evaluated using group comparisons and nominal logistic regression. Changes associated with outcomes of consecutive biopsies were assessed by matched pairs analysis. Results: Among 544 unique urine samples, the urinary TTV/cfDNA ratio was significantly lower in rejection than in non-rejection samples (P<0.0001). Logistic regression adjusted for demographic factors confirmed an inverse association between the qPCR-derived TTV/cfDNA metric and rejection (adjusted odds ratio per delta Cq, 0.91; 95% CI, 0.88-0.94; P<0.00001). Significant differences were observed for all types of rejection. Association was confirmed by dPCR: higher TTV was associated with lower rejection odds, whereas higher cfDNA was associated with greater rejection odds. A nominal logistic model incorporating dPCR measurements achieved an AUROC of 0.76 (95% CI, 0.69-0.82). Matched pairs analysis showed a significant decrease in TTV/cfDNA when rejection developed and an increase following recovery from rejection, with no significant changes when biopsy status remained unchanged. BKV levels were strongly associated with BKPyVAN. No correlation between TTV and BKV was observed. Nominal logistic regression integrating TTV, cfDNA, and BKV measurements yielded AUROCs of 0.75, 0.97, and 0.73 for rejection, BKPyVAN, and non-rejection, respectively. Conclusions: A reduced urinary TTV/cfDNA ratio is associated with biopsy-defined kidney transplant rejection, and changes in the ratio correlate with transitions in biopsy results. Combined TTV, cfDNA, and BKV measurements showed differential associations with rejection and BKPyVAN, supporting further evaluation as complementary urinary biomarkers.

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.

Certain glomerulopathies (GN) feature impaired protein homeostasis in the endoplasmic reticulum (ER) of podocytes. Protein misfolding causing ER stress activates the unfolded protein response (UPR), a protective signaling network. Mesencephalic astrocyte-derived neurotrophic factor (MANF) and ERdj3/DNAJB11 are ER chaperones that may be secreted from cells during the UPR. In rats with membranous nephropathy (MN) and focal segmental glomerulosclerosis (FSGS), secretion of MANF or ERdj3 from podocytes into urine identified glomerular ER stress/UPR activation. We address the biomarker potential of MANF and ERdj3 in human MN and FSGS. Glomerular gene expression of MANF and ERdj3 was increased in human MN and FSGS. Urinary MANF and ERdj3 were increased in proteinuric MN and FSGS compared to MN and FSGS in remission (low proteinuria), as well as other GNs, polycystic kidney disease, hypertension and healthy controls. In individuals with proteinuric MN or FSGS, amounts of urinary MANF and ERdj3 correlated weakly with proteinuria; correlation of MANF with ERdj3 was moderate. Males represented ~60% of persons in each group. eGFR in proteinuric MN and FSGS was >40 ml/min/1.73 m2. In MN, there were no significant differences in urinary MANF and ERdj3 between anti-PLA2R positive and negative individuals. In conclusion, proteinuric MN and FSGS show increased glomerular expression of MANF and ERdj3. High urinary levels of these ER chaperones correlate only weakly with proteinuria. In these GNs, urinary ER chaperones are thus non-invasive biomarkers of glomerular/podocyte ER stress. Such biomarkers may eventually be useful in identifying patients for therapies targeting ER protein misfolding.

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.

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.

Background: Histopathological diagnoses in kidney transplant biopsies, as described by the Banff classification, suffer from substantial inter-observer variability and misinterpretation, making them prone to diagnostic errors. Continuous indices based on BanffNET automated lesion scores are proposed to quantify the continuous phenotypic spectrum of kidney transplant biopsies, complementary to pathologist assessment of biopsies. Methods: The BanffNET model was used to obtain continuous lesion scoring for a training cohort of 2544 biopsies, a large validation cohort of 3863 biopsies, and a multi-reader cohort of 36 biopsies scored by 67 pathologists. A penalized regression approach was used to condense 17 automated lesion scores into four indices, representing the most important dimensions of graft injury: a TCMR/TI Index, an AMR/MVI Index, an Activity Index and a Chronicity Index. The BanffNET Indices were evaluated against Banff diagnoses and histological indices in the training cohort and validation cohort. Since pathologist-assigned Banff lesions and diagnoses suffer from inter-observer variability, associations were also assessed with diagnoses in a multi-reader study, with time to kidney graft failure in the training and validation cohort and with biopsy-based molecular signatures in the validation cohort. Results: The BanffNET TCMR/TI Index, AMR/MVI Index and Activity Index showed excellent discrimination of Banff TCMR, Banff MVI and Banff Any Diagnosis respectively, with validation AUCs ranging from 0.80 to 0.92. In addition, the BanffNET Indices explained large amounts of variability in multi-observer reference standards, time to graft failure and molecular biopsy-based diagnostics. In the large majority of cases, variability explained by BanffNET Indices matched or exceeded the variability explained by pathologist-assigned diagnoses and histological indices. Conclusions: BanffNET Indices are reproducible descriptors of whole slide images that could complement and augment kidney transplant biopsy evaluation by pathologists. Associations of BanffNET Indices with multi-observer diagnoses and related outcomes suggest that they capture additional information on tissue injury type and severity on top of pathologist-assigned Banff diagnoses and histological indices.

Introduction: Red blood cell distribution width (RDW) and intra-individual variability (IIV) of biomarkers are different types of variation. Although their high levels are commonly associated with high mortality risks and poor clinical outcomes, the reason for this remains unclear. Methods: We explored the significance of this similarity using time-series data (from 143,475 samples) collected over a 9-year period from 1,216 patients on long-term hemodialysis. The IIV of each of the 22 blood-based biomarkers was assessed using the moving coefficient of variation (mCV). Non-linear longitudinal/temporal changes of the variables and their mutual relationships were analyzed using generalized additive (mixed) models. Results: RDW and all of the IIVs showed similar trends throughout the entire period of dialysis treatment: a rapid decrease after hemodialysis initiation followed by an increase that accelerated prior to death. The slopes of these downward and upward trends during each one-year period were statistically different from zero for RDW and the majority of the IIVs. Given the reported increase in the RDW and IIVs of several biomarkers in the pre-dialysis stages of chronic kidney disease, these shared changes might reflect alterations in homeostatic capacity. The RDW exhibited positive correlations with the mCVs of all 22 biomarkers (all p-values < 0.0009), suggesting that it represents dysregulation of the overall physiological system. Furthermore, the levels of the biomarkers showed a specific (nearly linear or U-shaped) relationship with the RDW, analogous to their reported relationship to all-cause mortality in the hemodialysis population. Conclusion: Increased RDW could serve as a marker of physiological dysregulation, and measurement of the RDW can be an effective tool for assessing the overall health status and identifying optimal ranges for various health indicators.

Background: Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease (CKD). However, most proteomic studies of DKD rely on bulk kidney tissue, which cannot distinguish the contribution or response of individual nephron compartments to injury. Methods: Diabetes was induced in male mice by streptozotocin (STZ) injections. After 16-weeks, the mice and vehicle-treated controls were characterized physiologically, biochemically, and histologically. A deep learning-powered Deep Visual Proteomics (DVP) pipeline, validated against manual annotation, was adapted to isolate proximal tubule (PT) and glomeruli from Megalin stained kidney sections by automated laser microdissection. Bulk kidney, PT, and glomerular proteomes were generated by data independent acquisition mass spectrometry. PT-enriched candidates were prioritized using a composite scoring approach and compared with human tubulointerstitial proteomic data from the Kidney Precision Medicine Project. Results: STZ mice developed sustained hyperglycaemia and albuminuria, alongside elevated markers of tubular injury and interstitial fibrosis. Segmentation models isolated PT and glomeruli with high fidelity (Dice coefficients 0.878 and 0.914; area correlations r=0.993 and r=0.996). Compartment-resolved proteomics determined that PT and glomeruli underwent largely distinct, non-overlapping remodelling: PT exhibited loss of proteostatic, cell cycle, and structural programs with compensatory mitochondrial and lipid metabolic upregulation, whereas glomeruli showed broad loss of oxidative metabolic capacity without any compensatory metabolic program. Fourteen of the top twenty prioritized PT candidates, including LARS2 and ANXA2, changed in the same direction in human CKD tubulointerstitial proteomic data. The STZ PT proteome correlated significantly with this human dataset, while the glomerular comparison did not. Conclusions: Compartment-resolved and deep learning-guided visual proteomics can uncover divergent, biologically coherent PT and glomerular injury programs in DKD that are masked in bulk tissue analysis. A PT injury signature was uncovered that is partially conserved in human CKD, identifying novel candidate mechanisms and biomarkers for future exploration.

ABSTRACT Importance: The prevalence of chronic kidney disease (CKD) is increasing, with aging being a major contributor. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are well established therapies for CKD; however, adults aged 80 years or older have been underrepresented in previous large-scale trials. Consequently, evidence regarding effects of SGLT2i therapy in this cohort remains limited. Objective: To evaluate the association of SGLT2i initiation with mortality, kidney outcomes and cardiovascular outcomes among patients over 80 years of age and CKD. Design, Setting, Participants: This retrospective cohort study used data from TriNetX Research Network, a multicenter electronic health record database. To ensure comparable standard of care and SGLT2i eligibility, the period for the occurrence of the index event was restricted to January 1, 2021, until January 1, 2025. Propensity score matching was performed to balance comorbidities, laboratory parameters, concomitant medications, and frailty-associated factors between groups. Exposures: Initiation of SGLT2i therapy vs. non-use Main Outcomes and Measures: Outcome analysis focused on all-cause mortality, major adverse kidney events (MAKE) and major adverse cardiovascular events (MACE). Cox proportional hazards models were used to estimate hazard ratios with 95% confidence intervals; following propensity score matching, results were considered as adjusted hazard ratios (aHR). Results: After propensity score matching, 5,038 patients were included in each group. During two years of follow-up, SGLT2i initiation was associated with lower all-cause mortality (aHR 0.818; 95% CI 0.746 - 0.896, p<0.0001) and fewer MAKE events (aHR 0.779; 95% CI 0.0.715 - 0.850, p<0.0001). No significant difference in MACE was observed (aHR 1.007; 95%CI 0.938 - 1.082, p=0.84). Results were generally consistent across subgroups. Risk of acute kidney injury was higher in the SGLT2i group, while incident dialysis and end-stage renal disease were significantly reduced. Acute myocardial infarction and acute heart failure were increased in the SGLT2i group. Conclusion and Relevance: Regarding survival and kidney endpoints, even the oldest CKD patients seem to benefit from SGLT2i treatment, which was associated with reduced mortality as well as improved long-term renal outcomes. MACE showed no significant differences, while specific cardiac events were increased, reflecting possible safety concerns requiring further investigation in this specific age group.

Vitamin D sterols, phosphorus binders and calcimimetics are used to treat chronic kidney disease mineral and bone disorder (CKD-MBD) in hemodialysis. With few randomized trials, providers may titrate agents differently reflecting equipoise and opportunities for clinical trials. We studied patients initiating in-center hemodialysis at Dialysis Clinic, Inc facilities from 2006-2015 and who remained on hemodialysis for [&ge;]90 days (n=23,549). Multinomial logit models assessed titration among users of each medication at the start of the month considering static and dynamic CKD-MBD laboratories. Similarly parameterized logistic models assessed treatment initiation. Differences across facilities were quantified as random effects and corresponding median odds ratios. We observed patterns of titration associated with CKD-MBD laboratories including albumin-corrected serum calcium (Ca), serum phosphorus and parathyroid hormone (PTH) and minimal impact of patient characteristics. Best fit models incorporated 3 months of lagged Ca and phosphorus values and linear splines for current Ca, phosphorus and PTH values. Absolute titration probabilities for vitamin D sterols and calcimimetics were influenced by all three CKD-MBD parameters, such that Ca and phosphorus values altered the threshold PTH at which escalation and de-escalation probabilities crossed. Median odds ratios indicated the greatest facility variation for vitamin D sterol titration. Providers titrate CKD-MBD medications based largely on the full CKD-MBD laboratory phenotype, including the recent serum Ca, phosphorus and PTH history. Facility variation suggests equipoise in titration of vitamin D sterols with opportunities for clinical trials.

Background: Chronic kidney disease (CKD) may progress to stage 5 CKD (end-stage renal disease, ESRD), but stage-associated molecular alterations remain incompletely characterized. This study aimed to identify candidate biomarkers associated with CKD and ESRD. Methods: Two discovery datasets comparing CKD or ESRD with healthy controls were analyzed using differential expression analysis and weighted gene co-expression network analysis. Candidate genes were identified by intersecting differentially expressed genes with key co-expression modules, followed by protein-protein interaction network analysis using Degree, Closeness, and Maximal Clique Centrality algorithms. Candidate genes were evaluated in independent GEO validation datasets and further examined by quantitative real-time PCR and western blotting using clinical blood samples. Results: Ten hub genes were identified, among which EPB42, KLF1, and H3F3A were prioritized for further evaluation. EPB42 showed decreased expression in CKD but increased expression in ESRD, indicating an opposite-direction pattern between the two disease states. KLF1 showed no significant difference between healthy controls and CKD but was increased in ESRD, whereas H3F3A was increased in CKD and further increased in ESRD. Functional enrichment analysis highlighted processes related to oxygen transport, mitochondrial function, muscle-associated processes, and inflammation, suggesting possible involvement of hypoxia-associated oxidative injury and ferroptosis-related processes. Conclusions: Integrated transcriptomic and experimental analyses identified EPB42, KLF1, and H3F3A as candidate stage-associated biomarkers in CKD and ESRD. In particular, the opposite-direction expression pattern of EPB42 may provide additional molecular information for distinguishing CKD from ESRD.

Purpose: Autosomal Dominant Polycystic Kidney Disease is the most common monogenic kidney disease and largely due to variants in PKD1. We aimed to assess pathogenicity evidence for PKD1 missense variants in disease databases and evaluate in silico pathogenicity prediction tool performance. Methods: PKD1 missense variants reported as pathogenic, likely pathogenic or likely benign were extracted from ClinVar and PKDB. Variants were re-classified using ACMG/AMP criteria to identify "truth sets" of pathogenic and benign variants. In silico scores were obtained from five tools (SIFT, PolyPhen-2, CADD, REVEL, AlphaMissense) and evaluated using established thresholds. A Receiver Operating Characteristic curve analysis was performed using the PKD1 variant truth sets. Results: 346/389 (89%) reported disease-causing missense variants in PKD1 were downgraded to Variants of Unknown Significance (VUS) using current classification criteria. Based on current thresholds, REVEL achieved the highest sensitivity of 62%, with specificity of 79%. AlphaMissense was the only tool not to misclassify any truth set variants, but many of the variant scores were between the pathogenic and benign thresholds. Conclusion: A large majority of PKD1 missense variants are classified as VUS with current pathogenicity criteria. Commonly used in silico tools, applied with established genome-wide thresholds, do not reliably distinguish pathogenic and benign missense variants in PKD1.

Abstract Background. Enteric hyperoxaluria (EH) causes calcium oxalate kidney stones, oxalate nephropathy, and chronic kidney disease (CKD), and can progress to end-stage kidney disease. It occurs in Crohn's disease (CD), cystic fibrosis (CF), chronic pancreatitis, celiac disease, short bowel syndrome, and after bariatric surgery. Its prevalence in these populations has not been synthesized. Methods. PROSPERO CRD420261364424. PubMed and Embase were searched to 24 August 2026 for studies reporting 24-hour urinary oxalate. Prevalence was pooled using the Freeman-Tukey double arcsine transformation with a DerSimonian-Laird random-effects model; unweighted crude prevalence is also reported. Because heterogeneity was high, the narrative synthesis stratified by testing condition is the primary result. Prespecified subgroups addressed oxalate load before collection, diagnostic threshold, ileal resection, age, and urine collection format. Results. Forty-seven studies were included. In CD (17 studies, 471 patients; 204 with EH), crude prevalence was 43.3% and pooled prevalence 49.3% (95% CI 38.9-59.8; I^2 = 95.3%). With an oxalate load, prevalence was 64.7% (pooled 74.0%, 55.9-88.6) versus 38.6% without (pooled 39.1%, 28.7-50.0). Among CD patients, EH was more frequent with ileal resection (48.8% vs 31.7%; OR 1.62, 0.91-2.89) and with steatorrhea (62.5% vs 29.3%; OR 9.88, 3.81-25.61). In CF (7 studies, 348 patients; 179 with EH), pooled prevalence was 49.8% (40.5-59.1; I^2 = 91.9%). After bariatric surgery (15 studies, 849 patients; 474 with EH), pooled prevalence was 54.7% (45.4-63.9; I^2 = 96.7%). Conclusions. Roughly half of these patients have EH, but the proportion depends heavily on whether an oxalate load precedes urine collection (39% unprovoked vs 65%-74% provoked); because most studies do not state this condition, published prevalence estimates are not directly comparable. Ileal resection and steatorrhea identify those who should be screened.

Background Delayed graft function (DGF) is among the most used metrics in transplant medicine, yet its prevailing definition-dialysis requirement within the first seven postoperative days lacks granularity and fails to capture the dynamic nature of graft recovery. It reflects a treatment decision rather than graft biology, varies by centre practice, and offers no temporal information about the pace or pattern of recovery. This study proposes a trajectory-based framework using serial serum creatinine measurements across three biologically defined time windows to capture the dynamic nature of early renal recovery. Methods We retrospectively analysed 205 adult kidney transplant recipients at Cleveland Clinic Weston Hospital in 2025. Donor groups included living donors, donation after brain death (DBD), donation after circulatory death with normothermic regional perfusion (DCD-NRP), and DCD without NRP. Creatinine slopes were estimated for Days 1-7, 7-30, and 30-90 using ordinary least-squares regression. Logistic regression assessed the predictive performance of each trajectory window for DGF, adjusting for Kidney Donor Profile Index, cold ischemia time, BMI, and donor type. Results DCD non-NRP kidneys showed negligible early creatinine decline (slope +0.02) compared to DBD (-0.71) and DCD-NRP (-0.57) grafts during Days 1-7. During Days 7-30, DCD-NRP kidneys showed accelerated recovery and converged toward DBD-level trajectories, whereas DCD non-NRP grafts remained sluggish. Predictive modelling identified the Day 7-30 trajectory had the strongest discrimination for DGF, with AUC 0.83, pseudo-R2 0.25, and the lowest AIC (181.73), outperforming Days 1-7 (AUC 0.75) and 30-90 (AUC 0.79). DGF rates were 0% in living donors, 25.5% in DBD, 20.7% in DCD-NRP, and 58.9% in DCD non-NRP recipients. Conclusions A trajectory-based creatinine model provides more informative prognostic value than the conventional binary DGF definition The Day 7-30 window periods offers the highest discriminatory power, and normothermic regional perfusion appears to favourably shift DCD kidney recovery trajectories in a manner the binary definition fails to detect.

Background: Chronic kidney disease (CKD) imposes persistent metabolic stress, yet whether metabolic organization can be preserved under sustained renal stress remains unclear. Essential trace elements support redox defense, mitochondrial function, and intermediary metabolism, and their homeostasis is disturbed in CKD; however, single-element supplementation has yielded heterogeneous results. We examined whether a defined multi-element formulation preserves metabolic resilience in CKD. Methods: In a randomized, double-blind, placebo-controlled trial, 80 maintenance dialysis patients received standard care alone (n = 40) or plus a trace element cocktail (TEX, 20 mL/day; n = 40). Longitudinal trajectories were analyzed with linear mixed-effects models; endpoint plasma metabolomics and fecal metagenomics were profiled in subsets. A 5/6 nephrectomy mouse model was used to quantify plasma tryptophan-pathway branches and renal spatial metabolism by MALDI imaging mass spectrometry. Results: TEX was well tolerated, with no treatment-related safety signal, and was associated with modestly more favorable creatinine and eGFR trajectories. Supplementation constrained, rather than erased, CKD-associated metabolic displacement (median |Cohen's d|, 0.25 versus 2.09 for disease effects), selectively realigning circulating metabolism toward the healthy state. The host kynurenine branch responded most strongly, whereas microbial indole metabolism and gut community structure changed little. Renal metabolic remodeling was region-specific, with preservation of selected tubular and antioxidant features. Conclusions: Trace element supplementation preserved metabolic resilience in CKD, limiting metabolic displacement without complete restoration. Preservation of metabolic organization may represent a complementary dimension of therapeutic response in CKD. Trial registration: International Traditional Medicine Clinical Trial Registry, ITMCTR2026000263 (registered 3 February 2026).

Kidney stones are a disorder in which urinary solutes precipitate to form crystalline aggregates in the urinary space. The blood urea nitrogen-to-albumin ratio (BAR), a common inflammatory indicator, has an unclear association with kidney stones. Using NHANES 2007-2020 data, we compared baseline characteristics between kidney stone formers and controls and evaluated the BAR-stone relationship via weighted multivariate logistic regression (WMLR), restricted cubic splines (RCS), stratification analyses, and XGBoost, with validation in an independent external cohort. Twenty baseline features, including BAR and age, differed significantly between groups (P < 0.05). In all WMLR models, BAR was positively and nonlinearly associated with kidney stone risk (OR > 1, P < 0.05). Subgroup analyses revealed stable associations in females (OR = 1.10, P < 0.001), low vitamin A intake (OR = 1.10, P < 0.001), high water intake (OR = 1.11, P < 0.001), age < 50 years (OR = 1.14, P < 0.01), and education less than high school (OR = 1.11, P < 0.01). XGBoost identified BAR and water intake as prominent risk factors (AUC = 0.658). External validation confirmed a positive association (Model 1 OR = 1.029, 95% CI 1.016-1.043; Model 2 OR = 1.030, 95% CI 1.016-1.044; Model 3 OR = 1.029, 95% CI 1.015-1.045; all P < 0.001), and RCS confirmed a nonlinear dose-response relationship (nonlinear P = 0.0006). Subgroups aged [&ge;] 60 years, males, and females showed significant associations (ORs = 1.027-1.034). In XGBoost, BAR was the most important predictor (Gain = 0.265). These findings reveal a significant association between BAR and kidney stones, offering theoretical insights for prevention and risk stratification; BAR may serve as a valuable marker in kidney stone management.