Kidney International Reports

Chronic benign proteinuria (PROCHOB), caused by biallelic pathogenic variants in CUBN, presents in childhood as isolated, asymptomatic tubular proteinuria with preserved long-term kidney function. Because its clinical presentation closely mimics early stage glomerular diseases with moderate proteinuria and without increased urinary {beta}2-microglobulin (uBMG) and 1-microglobulin, numerous patients undergo unnecessary kidney biopsies and receive angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers before genetic testing is considered. Using high-throughput aptamer-based urinary proteomics (SomaScan(R)), we identified urinary myoglobin as a disease-specific biomarker for PROCHOB. We developed and confirmed a diagnostic approach in which the urinary myoglobin-to-creatinine (uMB/Cr) ratio robustly distinguishes PROCHOB from other moderate glomerular proteinuric kidney diseases. Although certain cases of Dent disease causing megalin dysfunction exhibit increased urinary myoglobin levels, PROCHOB and Dent disease can be clearly distinguished based on the uBMG-to creatinine ratio. This biomarker reflects impaired proximal tubular protein reabsorption because of cubilin dysfunction and remains normal in healthy individuals or those with typical glomerular diseases with moderate proteinuria. Our findings establish a noninvasive diagnostic tool for PROCHOB that prompts targeted genetic testing for CUBN variants using the uMB/Cr and urinary uBMG-to-creatinine ratios. This strategy has the potential to transform the clinical diagnostic pathway for isolated proteinuria.

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.

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.

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.

Background and hypothesis Autosomal dominant polycystic kidney disease (ADPKD) affects over 12 million people worldwide including an estimated 30,000-70,000 in the United Kingdom (UK). Tolvaptan is the only disease-modifying therapy approved for rapidly progressing disease. Despite national guidance, prescribing rates were hypothesised to vary by kidney centre. Treatment may not always align with guidelines: some patients eligible for tolvaptan may not be initiated, while other patients initiated on tolvaptan may not meet eligibility criteria. This may have important consequences for healthcare costs and health-related quality of life. Methods The National Registry of Rare Kidney Diseases (RaDaR) collects longitudinal data from UK NHS kidney centres. This retrospective cohort study used routinely collected data (2016-2023) to examine tolvaptan prescribing across kidney centres. Kidney centre-level initiation patterns were described, assessed using mixed-effects logistic regression and visualised with funnel plots. Cost-effectiveness analyses combined observed prescribing practices under likely negotiated commercial discounts to estimate costs and quality-adjusted life year (QALY) consequences of prescribing at the national level. Results Our study included 3,609 people with ADPKD from 72 kidney centres. Patients eligible for tolvaptan who were not initiated accounted for 34.8% (292/839). Across centres, five (6.9%) initiated tolvaptan significantly more than expected among eligible participants, while one centre (1.4%) initiated significantly less. Nationally, this could result in up to {pound}53.7 million in lost savings (assuming a 60% medication price reduction) and result in up to 1,245 lost QALYs. Patients initiated on tolvaptan who were not eligible accounted for 26.1% (103/395). Only one centre had significantly fewer eligible patients than expected among initiated patients. Nationally, this could cost up to {pound}15.9 million (assuming a 60% medication price reduction). Conclusions There is evidence of variation in tolvaptan prescribing in the UK. A substantial proportion of patients eligible for tolvaptan were not initiated at the cohort-level, with evidence of variation between centres suggesting differences in treatment decision-making. A substantial proportion of patients initiated on tolvaptan were not eligible at the cohort-level, but there was limited evidence of variation between centres. Together, these findings raise questions regarding the potential consistency of clinical decision-making, equitable access to a sole disease-modifying therapy in a rare disease, alignment with national guidance, and effective use of healthcare resources.

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.

Autosomal dominant polycystic liver disease (ADPLD) commonly results from a pathogenic variant in one of 6 genes (GANAB, ALG8, LRP5, PRKCSH, SEC61B, SEC63). Pathogenic variants in these genes are also associated with kidney cysts, which rarely cause kidney failure, but the genes are included in cystic kidney panels. This study determined the population frequency of predicted pathogenic variants in the ADPLD genes in the general population. Variants for each gene were downloaded from gnomAD and annotated with ANNOVAR. The population frequencies were calculated from the number of people with "predicted pathogenic" variants in gnomAD v.2.1.1:loss-of-function structural and copy number; null; and rare, computationally-damaging missense changes that affected a conserved residue. Frequencies were also estimated from the number of gnomADv.4.1 variants assessed as Pathogenic or Likely pathogenic in ClinVar. Predicted pathogenic variants affected one in 95 people using our strategy and gnomAD v.2.1.1, and one in 151 with ClinVar assessments of gnomAD v.4.1 variants. LRP5 and ALG8 which are associated with a milder clinical phenotype, were the commonest affected genes with both strategies. Predicted pathogenic variants in ADPLD appear more frequent in admixed American (one in 100), Finnish (one in 107) and African/African American (one in 130) people (p all <0.0001 compared with Europeans (one in 197).Predicted pathogenic variants for ADPLD may be even more common because of additional unidentified causative genes. However not all ADPLD variants result in liver cysts, nor indeed cystic kidneys, because of incomplete penetrance and variable expressivity.

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.

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.

Although several ancillary tests are available in limited laboratories, diagnosis of microphthalmia (MiT)/TFE family translocation renal cell carcinoma (tRCC) could be challenging due to diverse and overlapping tumor morphology and the lack of reliable biomarkers. GPNMB has been recently identified as a diagnostic marker for various renal neoplasms with FLCN/TSC/mTOR-TFE alterations. However, the sensitivity and specificity of GPNMB immunostain are suboptimal and the result interpretation in ambiguous cases could be difficult. To search additional biomarkers that could improve the screening sensitivity and predict genetic aberrations in FLCN/TSC/mTOR-TFE pathway in renal tumors, we performed bioinformatic analysis of publicly available cancer databases and found GPR143, a transmembrane protein regulated by MiT transcription factors, was highly expressed in a subset of renal cell carcinomas (RCCs). In two the Cancer Genome Atlas (TCGA) kidney cancer cohorts, RCCs with high levels of GPR143 expression were enriched for renal neoplasms with FLCN/TSC/mTOR-TFE alterations. Similar to GPNMB labeling, GPR143 immunostain was positive in the majority of tRCC cases and renal tumors with FLCN/TSC/mTOR alterations, suggesting that GPR143 could function as another surrogate marker for FLCN/TSC/mTOR-TFE alterations in certain renal tumors. Interestingly, despite the concordant GPR143 and GPNMB immunoreactivity in most renal neoplasms with FLCN/TSC/mTOR-TFE alterations, diffuse GPR143 immunostain was observed in some cases with negative or focal GPNMB labeling. Taken together, our results indicate GPR143 could serve as a useful adjunct marker to improve the sensitivity for screening renal tumors with FLCN/TSC/mTOR-TFE alterations.

BackgroundDiabetic kidney disease (DKD) is a leading cause of kidney failure in individuals with type 2 diabetes (T2D), yet risk identification in routine clinical practice remains incomplete. A critical and often overlooked barrier is risk observability: how much of a patients underlying risk is actually captured in their clinical record at the time of screening. Existing prediction models evaluate performance using model-specific thresholds, making it difficult to understand how additional data sources alter real-world screening behavior or which individuals benefit when models are expanded. MethodsWe developed a series of five nested machine learning models evaluated at a one-year landmark following T2D diagnosis using data from the All of Us Research Program (N = 39,431; cases = 16,193). Each successive model added a distinct information layer -- intrinsic risk, laboratory snapshots, medication exposure, longitudinal care trajectories, and social determinants of health (SDOH) -- while retaining all prior features. All models were evaluated under a fixed screening policy targeting 90% specificity, so that the false positive rate remained constant as the information available to the model grew. External validation was conducted in the BioMe Biobank (N = 9,818) without retraining. ResultsDiscrimination improved consistently across layers, from AUROC 0.673 (M1) to 0.797 (M5). Under the fixed screening policy, sensitivity nearly doubled from 0.27 to 0.49, with a cumulative recovery of 30.4% of cases missed by the base model. Gains were driven by distinct subgroups at each transition: laboratory features identified biologically high-risk individuals; medication features captured those with high treatment intensity reflecting advanced cardiometabolic burden; longitudinal care trajectory features rescued cases with biological instability observable only through repeated measurements; and SDOH features recovered individuals with limited clinical observability, with rescue probability highest among those with the fewest recorded monitoring domains. Sparse data in the clinical record indicated low observability, not low risk. Social and genetic features each contributed most when downstream physiologic signal was limited, supporting a contextual rather than universal role for each. In BioMe, discrimination was attenuated (M4 AUROC 0.659), but the relative ordering of information layers was fully preserved, and a systematic upward shift in predicted probability distributions underscored the need for recalibration before deployment in a new setting. ConclusionsDKD risk detection in T2D is substantially improved by integrating complementary information layers under a fixed clinical screening policy, with gains arising from distinct domains that identify at-risk individuals in different clinical contexts. The layered landmark framework introduced here reveals how risk observability -- shaped by monitoring intensity, healthcare engagement, and access -- determines what a screening model can detect, and provides a foundation for context-aware EHR-based screening that accounts for data availability at the time of risk assessment. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/26351384v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@1cc7f4borg.highwire.dtl.DTLVardef@b92956org.highwire.dtl.DTLVardef@48ffbcorg.highwire.dtl.DTLVardef@8dc627_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstract.C_FLOATNO Study design and layered DKD screening framework The top row defines the cohort timeline, in which predictors are derived from clinical data collected between T2D diagnosis and the 1-year landmark, and incident DKD is ascertained after the landmark. The second row depicts the nested model architecture, in which five successive models sequentially incorporate intrinsic risk, laboratory snapshot features, medication exposure, longitudinal care trajectories, and social determinants of health, while retaining all features from prior layers. The third row summarizes model development in the All of Us Research Program (N = 39,431) and external validation in the BioMe Biobank (N = 9,818), where the same trained models and risk thresholds were applied without retraining. The bottom row highlights the three evaluation domains: predictive performance, fixed-policy screening, and missed-case recovery context. DKD, diabetic kidney disease; T2D, type 2 diabetes; PRS, polygenic risk scores; AUROC, area under the receiver operating characteristic curve; AUPRC, area under the precision-recall curve; PPV, positive predictive value; SHAP, SHapley Additive exPlanations. C_FIG

BackgroundWithin the kidney, (pro) renin receptor (PRR) is abundantly expressed in the collecting duct (CD) and modulate physiological and pathophysiological processes. We have recently reported that activation of CD PRR mediates obstructive renal fibrosis in a mouse model of unilateral ureteral obstruction (UUO). The current study addresses the underlying mechanisms by examining the profibrotic pathway mediated by soluble PRR (sPRR)-dependent alternative macrophage activation. MethodsWe performed UUO or sham surgery on mice with CD-specific deletion of PRR (CD PRR KO) and floxed controls. After 7 days, we assessed fibrosis-related parameters, inflammatory cytokines, M1/M2 macrophage markers, other gene expression markers of kidney injury, and the concentration of plasma sPRR. We also administered vehicle or site-1 protease (S1P) inhibitor PF-429242 (PF) to C57BL/6 mice with UUO to determine the role of sPRR. Experiments were performed in vitro to examine the mechanism of sPRR-His-mediated macrophage M2 polarization and activation of potential target genes in bone-marrow-derived macrophages (BMDMs). ResultsCompared with the floxed control, CD PRR KO decreased macrophage accumulation, M2 polarization, and Yap/Taz expression while improving renal fibrosis and suppressing plasma sPRR levels following UUO. In BMDMs, sPRR-His treatment promoted macrophage M2 polarization, fibrosis, and Yap/Taz expression, which was dependent on angiotensin type 1 receptor (AT1R). ConclusionCD PRR-derived sPRR acts via ATR to promote macrophage M2 polarization and stimulates the AT1R/Yap/Taz axis, which leads to renal fibrosis during UUO.

Background: Hereditary transthyretin amyloidosis (hATTR) manifests as cardiomyopathy and/or polyneuropathy. The V142I variant predominantly causes cardiac disease in African Americans, though neurological involvement may be underrecognized. We characterized neuropathy documentation and treatment patterns in a predominantly V142I cohort. Methods: Retrospective review of 54 hATTR patients at a major academic medical center. Neuropathy was classified as: objective (abnormal EMG), possible polyneuropathy (documented symptoms suggestive of polyneuropathy), symptoms only (neuropathic symptoms without specialist evaluation), or unclear. Treatment with stabilizers (tafamidis, acoramidis, diflunisal) and gene silencers (patisiran, vutrisiran, eplontersen) was assessed. Results: Of 54 patients (88.9% African American, 85.2% V142I), 51 (94.4%) had confirmed cardiac involvement. Among cardiac patients, 40/42 eligible (95.2%) received stabilizers. Overall, 16 patients (29.6%) received gene silencers, with 13 (24.1%) receiving both a stabilizer and gene silencer concurrently. Possible neuropathy (objective, possible polyneuropathy, or symptoms) was documented in 30 patients (55.6%). Gene silencer use was highest among those with objective neuropathy (8/17, 47.1%) versus symptoms only (1/10, 10.0%). All three patients without confirmed cardiac disease received gene silencers. Conclusions: In this V142I-predominant cohort with 94.4% cardiac involvement, stabilizer use was high (95.2%) among eligible patients. Over half had possible neuropathy based on clinical documentation, though EMG completion was limited (57.4%). Gene silencer use was associated with objective neuropathy documentation and non-cardiac phenotype. These findings support systematic neurological assessment in hATTR, even when cardiac disease predominates.

Background: Extrauterine growth restriction (EUGR) is a common and clinically significant complication among preterm infants, contributing to adverse neurodevelopmental and metabolic outcomes. Early and individualized risk prediction remains challenging. This study aimed to develop and validate an interpretable machine learning model for early prediction of EUGR using routinely available clinical variables, and to implement a user-friendly web-based calculator for clinical use. Methods: We retrospectively analyzed 1,431 preterm infants admitted within 24 hours after birth to our hospital between May 2020 and March 2025. Infants from the Yangpu campus (n=863) formed the training set, and those from the Huangpu campus (n=568) formed the validation set. Early clinical variables available within 48-72 hours were screened using the Boruta algorithm. Logistic regression, XGBoost, random forest, decision tree, and support vector machine models were developed and compared. Model performance was evaluated using area under the curve (AUC), accuracy, sensitivity, specificity, F1 score, and Brier score. SHapley Additive exPlanations (SHAP) were applied to assess global and individual feature contributions, nonlinear effects, and interactions. A web-based calculator was constructed based on the optimal model. Results: Nine variables were identified as important predictors: birth weight, small for gestational age status, gestational age, breastfeeding, multiple gestation, neonatal respiratory distress syndrome, patent ductus arteriosus, maternal hypertension, and maternal group B Streptococcus infection. Among the five models, XGBoost achieved the best performance in the validation set (AUC 0.922, accuracy 0.849, Brier score 0.108). SHAP analysis showed that low birth weight, small for gestational age, maternal group B Streptococcus infection, and patent ductus arteriosus were major risk factors, while breastfeeding was protective. Notable nonlinear and interactive effects were observed, particularly between birth weight and gestational age and between breastfeeding and patent ductus arteriosus. The web-based calculator provides real-time individualized risk estimation and visualized interpretation. Conclusions: An interpretable XGBoost-based model and web calculator were successfully developed and validated for early prediction of EUGR in preterm infants. This tool may support clinicians in identifying high-risk infants and guiding individualized nutritional and clinical management.

Chronic pyelonephritis is characterized by persistent bacterial infection of the kidney and a dysregulated immune response that promotes disease progression. Macrophages are central regulators of antibacterial immunity in the urinary tract. However, the mechanisms underlying their functional reprogramming in chronic infection remain poorly understood. Here, we identify lactate as a key metabolic determinant of macrophage polarization in human pyelonephritis. Proteomic analysis of human kidney tissue revealed extensive metabolic remodelling, including upregulation of enzymes involved in glycolysis. Consistent with this, lactate levels were significantly elevated in urine and plasma of pyelonephritis patients. Concomitantly, we observed a pronounced accumulation of CD163 macrophages in infected kidneys, representing a distinct macrophage subset with immunomodulatory function. Correlation-based network analysis revealed a strong association between CD163 and lactate dehydrogenase A, supporting a functional association between lactate metabolism and macrophage polarization. Mechanistically, exposure of murine bone marrow-derived macrophages to lactate induced intracellular protein lactylation and promoted polarization toward a CD163 phenotype, defining a metabolically imprinted macrophage state distinct from classical activation paradigms. Proteomic profiling demonstrated extensive remodelling of macrophage protein expression in response to lactate with significant alteration of mediators of phagocytosis, Toll-like receptor signalling, and interferon response. Together, these findings identify lactate as a potent metabolic driver of macrophage reprogramming and establish a foundation for investigating lactylation-dependent immune dysfunction in chronic pyelonephritis.

Antimicrobial peptides (AMPs) are key effectors of host defence, however, their functional deployment across renal tissue and urine in pyelonephritis (PN) remains incompletely understood. Here, we integrate kidney and urine proteomics with urinary peptidomics and computational prediction to define AMP organisation and function. Proteomic analysis indicated coordinated induction of multiple AMPs in infected kidneys. These patterns were recapitulated in the urinary proteome, where AMP abundance correlated with leukocyte counts. Multiplex immunofluorescence microscopy localised these AMPs to myeloid cells, identifying them as central effector sources. Importantly, analysis of the urine peptidome revealed multiple encrypted AMPs (EPs), which arise from proteolytic processing of precursor proteins. To systematically assess their relevance for host defence, we applied an ensemble of machine learning-based predictors to prioritise candidates with activity in the urinary environment. This approach identified several potential EPs, among which the S100A12-derived peptide Calcitermin was confirmed in patient urine. Furthermore, it exerts antibacterial activity against uropathogenic E. coli (UPEC) and modulates myeloid cell responses. Together, these findings define a coordinated and compartmentalised AMP defence programme in human PN that extends beyond increased peptide expression, highlighting EPs as functionally relevant effectors with therapeutic potential.

BackgroundHeterozygous c.283+1G>A and c.283G>A variants in the THRB gene, encoding for thyroid hormone receptor (TR){beta}1 and {beta}2, lead to autosomal dominant macular dystrophy (ADMD). We report the detailed clinical characterization of two first-degree relatives with ADMD, heterozygous for THRB c.283+1G>A, and an unrelated ADMD patient with a novel variant, c.283G>C. The genomic and molecular consequences of both variants were studied. MethodsgDNA and mRNA were obtained from leukocytes. Clinical characterization included biochemistry, bone density and body composition, ECG, echocardiography, ultrasound, audiometry and color-vision. In vitro assays investigated TR function and DNA binding. ResultsThe patients manifested no resistance to thyroid hormone beta (RTH{beta}) and had normal FT4 and TSH. Detailed studies in two patients showed no goiter, tachycardia, hypercholesterinemia or hepatic steatosis. Hearing was not impaired. Both had impaired color vision and reduced bone density. RT-PCR from all three patients revealed skipping of exon 4 exclusive to TR{beta}1, producing a deletion of 87 amino acids in the N-terminal domain (TR{beta}1{Delta}NTD). In vitro, DNA-binding affinity of TR{beta}1{Delta}NTD to DR4-TRE with or without RXR was comparable to TR{beta}1WT. Surprisingly, TR{beta}1{Delta}NTD was transcriptionally twice more active than TR{beta}1WT with a similar EC50 for T3, demonstrating gain-of-function of TR{beta}1{Delta}NTD. THRA expression in leukocytes was increased by 3-fold compared to unrelated controls and different from RTH{beta} patients. ConclusionThese THRB splice site variants produce TR{beta}1 exon 4 skipping, resulting in a gain-of-function mutant, TR{beta}1{Delta}NTD. This explains the dominant ADMD phenotype devoid of RTH{beta} and suggests a TR{beta}1 gain-of-function syndrome.

Wolfram syndrome is a rare autosomal recessive disorder caused by pathogenic variants in the WFS1 gene, characterized by early-onset diabetes mellitus, optic atrophy, sensorineural hearing loss, arginine vasopressin deficiency, and progressive neurodegeneration. The condition selectively affects pancreatic {beta} cells and neurons via chronic endoplasmic reticulum (ER) stress, and no proven disease-modifying therapy currently exists. Diabetes mellitus is typically the first manifestation, presenting at a mean age of 6 years as an insulin-dependent phenotype with preserved C-peptide and negative diabetes-related autoantibodies. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are well-established agents in the management of type 2 diabetes, augmenting glucose-dependent insulin secretion, suppressing glucagon, slowing gastric emptying, and promoting satiety. Preclinical evidence further suggests that GLP-1 RAs preserve {beta}-cell mass, attenuate ER stress, and confer neuroprotective effects, properties of particular therapeutic relevance to Wolfram syndrome. We conducted a retrospective cohort study of 84 participants with genetically confirmed Wolfram syndrome and insulin-dependent diabetes mellitus enrolled in the Washington University Wolfram Syndrome International Registry and Clinical Study. Clinical data were extracted from medical records; for participants concurrently enrolled in the Tracking Neurodegeneration in Early Wolfram Syndrome study, longitudinal data were obtained from that source as well. Thirty-five percent of eligible participants had received a GLP-1 RA at some point during follow-up. We characterize the prevalence of GLP-1 RA use, documented rationale for initiation, observed effects on glycemic control and visual outcomes, adverse effects, and reasons for discontinuation. No statistically significant changes in hemoglobin A1c (HbA1c) or body mass index (BMI) were observed. Visual acuity declined significantly at two years, consistent with expected disease progression. Gastrointestinal adverse effects were common and contributed to frequent discontinuation. These observational data provide important clinical context and a foundation for future prospective trials evaluating GLP-1 RAs as a potential disease-modifying strategy in Wolfram syndrome.

Chronic kidney disease of unknown etiology (CKDu) has emerged as an important public health challenge, particularly in agricultural communities across Southern Asia and Central America. Our research aims to explore the role of environmental factors in contributing to CKDu prevalence in these regions. Using an Extreme Gradient Boosting Machine Learning (XGBoost) model, we analyzed an environmental dataset from the CKDu endemic region of Sri Lanka. The XGBoost model achieved 85% accuracy in predicting CKDu prevalence in a total of 100 locales. Significant predictor variables included fluoride concentration in water, electrical conductivity of drinking water (EC), pH, and soil type. Fluoride, a common contaminant in drinking water, was the most influential factor, followed by EC and pH, which influence the solubility and bioavailability of nephrotoxic chemicals in water sources. The study findings highlight the urgent need for targeted water analysis programs and interventions in water quality management, agrochemical usage, and soil treatment in CKDu-endemic regions. These insights also provide a framework for future research to identify causative agents and develop strategies for reducing CKDu prevalence.

Effector CD8+ T cells are key cellular drivers of type 1 diabetes (T1D) pathogenesis, yet questions remain regarding the molecular defects leading to altered cytotoxicity, their signature in peripheral tissues, and their receptor specificity. Thus, we analyzed human pancreatic lymph nodes (pLN) using mass cytometry and single cell RNA sequencing (scRNAseq) with combined proteomic and T cell receptor (TCR) profiling. Cytometric analysis revealed an enriched population of T stem-cell memory (TSCM)-like cells (CD8+CD45RA+CD27+CD28+CCR7+CXCR3+ T cells) in T1D pLNs. scRNAseq profiling indicated an elevated inflammatory cytokine gene signature (IFITM3, LTB) along with regulators of terminal differentiation (BCL6, BCL3), coupled with reduced expression of exhaustion-associated genes (DUSP2, NR4A2, TSC22D3) in CD8+ T cells in T1D pLN. Additionally, effector CD8+ T cells expressed features of progenitor exhausted cells (BCL2) in T1D pLN. Immune Response Enrichment Analysis (IREA) indicated IL-15 signaling as a significant driver of these phenotypes. Integrated TCR and transcriptomic analysis revealed a cluster of diverse naive-like CD8+ T cell clones in T1D pLN. When comparing pLN and pancreatic slice cellular isolates, we observed sharing of effector CD8+ T cells, with upregulation of terminal effector signatures detected within the pancreas relative to paired pLN samples. Multiplex imaging revealed differential localization of TCF1 and TOX expressing T cells in the pancreas, with TCF1+TOX+ cells located in closer proximity to the islets and displaying a mixture of activation and exhaustion-associated phenotypes. Thus, we provide multimodal cellular profiles enriched in T1D tissues for consideration in therapeutic targeting.