Kidney International Reports

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

Background: ADTKD-MUC1 is one of the major entities of ADTKD caused by frameshift variants in the MUC1 VNTR that standard short-read sequencing fails to detect. Existing 59dupC-targeted probe-extension assays do not allow for broad screening and cannot detect atypical non-dupC variants. Recently, VNtyper, a Kestrel-based genotyping pipeline with optional code-adVNTR cross-validation for MUC1 VNTR genotyping from short-read sequencing data allowed to circumvent this diagnostic limitation, but needed further development for easy access and rapid sample processing. Methods: We developed VNtyper 2, by refactoring VNtyper into a modular, production-grade tool with a companion web platform, VNtyper-Online (https://vntyper.org), for freely available browser-based analysis with short turnaround time and without local bioinformatics infrastructure. We validated VNtyper 2 on 400 simulated samples generated with MucOneUp and 142 clinical exomes with independently confirmed genotypes. Results: In simulation, VNtyper 2 detected the canonical 59dupC variant with 96% sensitivity and 100% specificity. Reference-standard validation on 142 samples yielded 90.6% sensitivity and 98.2% specificity overall, with cohort-dependent performance across the Twist Exome v2 French-German cohort (98% sensitivity, 87.5% specificity) and the KAPA HyperExome V2 (Roche) Czech-US cohort (79.4% sensitivity, 100% specificity). Screening of 3582 exomes and targeted panels from international CKD referral programmes identified 51 positive individuals, including 9 with atypical non-dupC frameshift variants that would have been missed by 59dupC-targeted probe-extension assays. In unselected CKD cohorts, a descriptive random-effects summary estimated a detection rate of 1.4% (95% CI 0.6 to 3.1%). Conclusions: VNtyper 2 and VNtyper-Online are open-source tools for MUC1 VNTR genotyping from short-read data and can support locally validated workflows when VNTR coverage is adequate. By improving accessibility and turnaround time, these tools democratize MUC1 diagnostics at global scale. For its integration into routine diagnostics, we propose an expert-informed two-pathway workflow developed through European ADTKD-Net consortium consensus.

Introduction: APOL1 high-risk variants markedly increase susceptibility to kidney disease among individuals of African ancestry; however, only a subset of carriers develops clinically significant CKD or ESKD. This discrepancy highlights a gap between genetic risk and clinical trajectory. Current prognostic tools rely primarily on eGFR and albuminuria, which incompletely reflect the underlying biological processes driving APOL1-associated kidney injury. We hypothesized that plasma biomarkers reflecting inflammatory and tubular injury pathways could identify biologically active disease states within this genetically high-risk population and improve prognostic stratification. Methods: Participants from the Mount Sinai BioMe Biobank carrying two APOL1 high-risk alleles (G1, G1; G1, G2; or G2 G2) were followed for a median of 6 years. Baseline plasma biomarkers of inflammation and tubular injury (TNFR1, TNFR2, KIM-1, MCP-1, YKL-40, IL-18, suPAR) were measured. The composite outcome was sustained 40% decline in eGFR or ESKD. Multivariable Cox models assessed associations between biomarkers and outcomes. A weighted biomarker risk score was derived from tertile-based hazard ratios and categorized into low-, moderate-, and high-risk groups. Results: Among 498 participants (median eGFR 83 ml/min/1.73 m2), 80 (16.1%) reached the composite outcome. Higher concentrations of TNFR1, TNFR2, suPAR, KIM-1, and IL-18 were independently associated with kidney events after multivariable adjustment. Event rates were 7% in the low-risk group, 16% in the moderate-risk group, and 36% in the high-risk group. Conclusions: Plasma biomarkers reflecting inflammatory and tubular injury pathways reveal marked heterogeneity in kidney outcomes among individuals with high-risk APOL1 genotypes. Integration of these signals into a biology-weighted score identifies distinct prognostic phenotypes beyond genotype and traditional clinical measures, supporting multidomain biomarker frameworks for risk stratification and potential trial enrichment in APOL1-associated kidney disease.

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.

Background.Renoprotective therapies - SGLT2 inhibitors, finerenone, and renin-angiotensin system inhibitors (RASi) - remain underutilisedin chronic kidney disease (CKD). Large language models (LLMs) may detect therapy omissions, but their performance acrossCKD severity strata and at clinical decision boundaries has not been evaluated.Methods.We constructed 100 synthetic CKD vignettes (G3a-G5D; 75 with prespecified omissions, 25 decoys) and queried four LLMsthree times each at temperature 0 (1,200 calls). Omission criteria were adapted from KDIGO 2024, including an investigator-defined gray-zone RASi initiation criterion at eGFR<15. Two nephrologists independently classified a stratified 20-casesubset.Results.For SGLT2 inhibitor and finerenone omissions, all models achieved near-ceiling sensitivity (97-100%). For RASi, performancediverged at the eGFR<15 boundary: Grok 4.1 Fast 85% versus GPT-5.4 55%, Gemini 10%, DeepSeek 10%. Gap-detectioninter-rater agreement was perfect (kappa = 1.000). Clinically incorrect reasoning rates ranged from 0% (GPT-5.4) to 27%(DeepSeek R1); of 52 instances, 31 were factual pharmacology errors and 21 reflected conservative boundary-discordantreasoning. Reproducibility (Jaccard) ranged from 0.74 to 0.93.Conclusions.This boundary-aware synthetic benchmark showed that aggregate sensitivity can conceal clinically important operational-rulediscordance. Rule-based SGLT2 inhibitor and finerenone omissions were detected with near-ceiling sensitivity, whereas aninvestigator-defined gray-zone RASi criterion at eGFR<15 exposed model-specific boundary behaviour. Evaluation of LLM-based CKD decision support should report boundary-specific performance, reproducibility, and clinically incorrect reasoningalongside aggregate metrics.

Non-HLA donor-recipient (D-R) genetic mismatches contribute to kidney allograft injury and long-term graft loss, but their clinical use is limited by the unavailability of donor DNA after transplantation. We tested whether non-invasively obtained, recipient-derived samples could be used to infer donor genotype and D-R mismatches. Genomic DNA (g-DNA) of 11 unselected kidney transplant recipients and donors underwent whole-exome sequencing (100x). Additional customized probes were added for intronic coverage (300x) of 55 targeted non-HLA genes of reported clinical relevance. Variants identified from sequencing results were compared with plasma cell-free DNA (cfDNA), urine cell-pellet DNA (U-DNA) obtained from the same recipients. Genome-wide-, exonic-, or non-synonymous exonic- mismatches in transmembrane or secreted proteins, and mismatches within target genes were benchmarked using donor g-DNA to generate mismatch scores for each D-R pair. Within each of these genomic scales of mismatch, U-DNA identified D-R mismatches significantly better than the corresponding cfDNA (P<0.001 for each comparison). U-DNA also identified gene-level mismatches in the LIMS1 gene, and correctly inferred established donor-origin risk alleles, including SHROOM3 and APOL1. Our findings demonstrate proof-of-concept that U-DNA in tandem with recipient genome, can non-invasively infer relevant non-HLA loci/mismatches circumventing the need for the donor genomic DNA.

Background and hypothesis: Sodium-glucose cotransporter-2 inhibitors (SGLT2-inhibitors) slow chronic kidney disease progression, but evidence in non-diabetic kidney transplant recipients is limited. We evaluated associations between SGLT2-inhibitor use and major adverse kidney events (MAKE), major adverse cardiovascular events (MACE), and all-cause mortality. Methods: In this retrospective cohort study using the TriNetX federated research network, adult non-diabetic kidney transplant recipients transplanted between January 2015 and January 2022 were identified. SGLT2-inhibitor users initiating therapy [&ge;]1000 days post-transplant were compared with non-users after 1:1 propensity score matching. The primary outcome was MAKE, defined as dialysis initiation or death. Secondary outcomes included all-cause mortality and MACE. Results: Propensity score matching yielded 867 pairs of SGLT2-inhibitor users and non-users. SGLT2-inhibitor use was associated with lower risks of MAKE (adjusted hazard ratio [aHR] 0.64, 95% CI 0.45-0.91) and all-cause mortality (aHR 0.55, 95% CI 0.36-0.85). No significant association was observed for MACE (aHR 0.86, 95% CI 0.64-1.17). No increased risk of urinary tract infections was observed among SGLT2-inhibitor users. Conclusion: SGLT2-inhibitor use was associated with lower risks of MAKE and all-cause mortality in non-diabetic kidney transplant recipients.

Secondary hyperparathyroidism persists in the majority of kidney transplant recipients and is associated with adverse graft and cardiovascular outcomes. The immunosuppressive drug class used post-transplant may modulate parathyroid hormone (PTH) levels through distinct mechanisms: calcineurin inhibitors (CNI) stabilize PTH mRNA, while mTOR inhibitors (mTORi) suppress parathyroid cell proliferation in experimental models. We report supporting evidence from two independent analyses. In a multinational real-world database analysis (TriNetX Global Collaborative Network), kidney transplant recipients with documented mTORi use and eGFR in the target range had lower PTH than those on CNI across eGFR strata examined (15-30, 30-45, 45-60, 60-75, >75 mL/min/1.73 m2), with risk ratios for PTH >130 pg/mL ranging from 0.47 to 0.67 in propensity-matched analyses (all p < 0.05). The known confounders - calcium (higher in CNI) and phosphate (higher in mTORi) - both act to oppose this pattern, strengthening the possibility of a drug effect. In a longitudinal single-center cohort (n = 118; 796 PTH measurements), a linear mixed-effects model with time-varying mTORi exposure confirmed a 42% lower PTH during on-mTORi periods after adjustment for eGFR, transplant vintage, diabetes, age, and sex (fold-change 0.58 [95% CI 0.50-0.68]; p < 0.0001). These findings suggest a direct PTH-lowering effect of mTORi. Immunosuppression choice may be considered in the management of post-transplant hyperparathyroidism in selected patients.

Background: Clinical LLM benchmarks rarely test whether algorithmic rankings agree with expert clinical judgment. We developed a trap-embedded peritoneal dialysis (PD) benchmark comparing multiple scoring constructs with blinded nephrologist ratings. Methods: We generated 125 synthetic PD cases containing 13 ISPD-aligned trap types. Five LLMs (Claude Sonnet 4.5, GPT-5.4, Gemini 3.1 Pro, DeepSeek-R1, Grok 4.1 Fast) evaluated each case three times at temperature 0 (1,875 calls). Primary outcome was must-identify TDR_must, analyzed with GEE and case-clustered bootstrap. Secondary analyses included a verbosity-sensitive alarm-burden proxy, WCS, relaxed-match scoring, WCS sensitivity analyses, and a 25-output blinded expert adequacy substudy. Must-identify kappa was 0.89 in Stage 1 and 0.92 in Stage 2. Results: Rankings were discordant. Recall ranked Claude (0.977) and GPT-5.4 (0.955) above the other models (0.86-0.90, p<0.0001). The alarm-burden proxy favored concise models (Grok 0.689; 21.6 vs 2.4 issues/case), while WCS produced a third ordering. In the expert substudy, inter-rater concordance was strong (rho 0.977), but WCS did not show a positive association with expert adequacy (rho -0.17, p=0.41). Conclusion: Clinical LLM rankings in PD prescription review depend strongly on scoring construct. Algorithmic metrics should be reported alongside blinded expert adequacy ratings and should not alone determine deployment.

Background: Renal effects of statins in type 2 diabetes mellitus (T2DM) remain uncertain. We evaluated whether statin exposure is associated with time to dialysis initiation. Methods: We conducted a retrospective cohort study of adults with T2DM, indexing follow-up at diagnosis during first hospital admission (day 0) between january 2017 and march 2025. Statin use was modeled as time-varying from statin days; (classified in 3 categories: baseline users, new users, and never users). The primary outcome was dialysis. Analysis estimated cause-specific hazards, censoring deaths; proportional hazards were checked with prespecified windows of statin exposure (0?1, 1?3, > 3 years). Competing-risk analyses (Fine?Gray) assessed the sub-distribution hazard of dialysis with death as a competing event in two models: (i) prevalent users at baseline and (ii) new-users with post-initiation intervals of 30 and 90 days. An Observational Medical Outcomes Partnership Common Data Model standardized dataset of a Brazilian quaternary hospital, and the Real-World Data tool MD Clone were used in the study. Results: Of 36,246 adults identified, 32,125 entered the time-varying cohort (39,943 risk intervals; 656 dialysis events); median follow-up among censored patients was 753 days. At baseline, 70.3% never used statins, 5.5% were users (? 0 days), and 24.2% initiated after diagnosis. Crude dialysis incidence was 4.51 vs. 12.31 per 1,000 patient-years during unexposed vs. exposed time. In the adjusted time-varying Cox model, current statin exposure was associated with a modestly higher hazard of dialysis (HR = 1.043, 95% CI 1.011?1.077). In the new-users analysis, HRs were 0.83 (95% CI 0.66?1.05), and 0.73 (95% CI 0.57?0.92) with a 30-day and 90-day intervals, respectively. Conclusions: In this retrospective cohort of hospitalized diabetic patients at baseline, statin initiation at least 90-days in advance is associated with reduced indication of renal replacement therapy.

Nephronophthisis (NPH) is n rare recessive kidney disease caused by biallelic variants in more than 25 NPHP genes encoding proteins that localize to primary cilia. It is characterized by three different forms depending on the age of onset and kidney lesions: infantile (cystic), juvenile/late onset (fibrotic). To date, the pathways linking altered primary cilia function to progressive kidney scarring in NPH remain poorly defined and therapeutic options are lacking. To address these questions, we generated two new mouse NPH models by inactivating Nphp3 specifically in kidney tubules either during embryogenesis or in adult, recapitulating the infantile and juvenile forms of the disease, respectively. Embryonic inactivation produced a rapid and severe cystic phenotype with tubular dedifferentiation, progressive interstitial fibrosis, inflammation and kidney failure, while postnatal inactivation led to a slowly progressive tubulointerstitial nephropathy characterized by tubular atrophy, fibrosis and immune cell infiltration without cyst formation. Strikingly, cilia were preserved in the early stages of both models, indicating that ciliogenesis impairment is not a primary driver of NPH3 pathogenesis. Transcriptomic profiling of the juvenile model revealed that disease initiation is driven by mitochondrial dysfunction, innate immune activation and aberrant cell cycle progression, while epithelial-to-mesenchymal transition and Wnt/{beta}-catenin remodelling emerges only at later stages of disease progression. Therapeutic intervention with the PGE1 (alprostadil) failed to rescue the cystic/infantile model but significantly attenuated fibrosis, inflammation and interstitial fibrosis in the fibrotic/juvenile model. The ability to recapitulate both disease forms through temporal modulation of gene inactivation suggests that primary cilia serve distinct, stage-specific functions in kidney tubular homeostasis, with different cellular processes being selectively vulnerable depending on the causative gene or variant. Collectively, these findings uncover early pathogenic mechanisms that may constitute tractable therapeutic targets for the treatment of nephronophthisis.

Background: Patients with CKD and polypharmacy face high rates of drug-related problems, yet comprehensive medication review remains time-intensive and inconsistently performed. Large language models (LLMs) may augment this process, but existing benchmarks use multiple-choice formats that do not reflect open-ended, nephrology-specific review. We developed a trap-embedded synthetic CKD benchmark and evaluated five current-generation LLMs (GPT-5.4, Claude Sonnet 4.6, Gemini 3.1 Pro, Grok 4.1 Fast, DeepSeek R1; tested April-May 2026) for open-ended medication review. Methods: Fifty synthetic CKD cases across three complexity groups (G3a-G3b [n=20], G4 [n=15], G5/G5D/transplant [n=15]) with 8-12 medications and [&ge;]2 embedded clinical traps each were scored against nephrologist-adjudicated gold standards. Each model produced three independent responses per case (temperature 0; 750 total outputs). Primary endpoint was per-case macro F1; secondary endpoints were safety-critical omission rate, PI-adjudicated hallucination rate, and intra-model consistency. Blinded inter-rater reliability for gold-standard item detection was assessed on a 30% sample. Results: Consensus-level macro F1 ranged from 0.41 (Claude Sonnet 4.6) to 0.49 (Grok 4.1 Fast) (Friedman P < 0.001). Phosphate binder timing (11%) and hyperkalemia combinations (33%) were poorly detected across all models. Safety-critical omission rate ranged from 22% to 48% (P < 0.001); PI-adjudicated hallucination ranged from 0% (GPT-5.4) to 54% (DeepSeek R1), including fabricated dose caps and non-existent guideline citations. Blinded reliability for gold-standard item detection was high (kappa = 0.934, n = 92). Conclusions: This nephrology-specific benchmark exposes clinically important LLM blind spots that generic multiple-choice evaluations would not detect. Heterogeneous hallucination and omission rates indicate that model selection and domain-specific guardrails should precede any clinical deployment of LLM-assisted CKD medication review. Prospective validation with real patient data and human comparators is required before deployment recommendations can be made.

In the United States, sickle cell disease (SCD) is a rare inherited hemoglobinopathy affecting about 100,000 individuals, mostly with African ancestry. SCD causes damage to multiple organ systems and SCD nephropathy (SCDN) is a common complication associated with early mortality. We previously performed a genome-wide association study (GWAS) for SCDN and identified a modest number of genome-wide significant loci. Here, we leveraged the ancestral composition of participants from two well-characterized adult SCD cohorts to boost statistical power and perform a local ancestry-aware GWAS for estimated glomerular filtration rate (eGFR), resulting in the identification of novel genome-wide significant loci within the African (AFR) and European (EUR) ancestral components of participants. Meta-analysis identified 12 significant genomic regions in the AFR tract, including PPIL6, ARHGAP24, RAB11A, and STEAP3, and 38 regions in the EUR tract, including UBLCP1, ADAMTS6, JAZF1, MYO7B, MYO1C, PDGFA, GPC5, LRP1B, KANK1, and TRPV5. The identified regions encompass genes affecting inflammation, extracellular matrix (ECM) integrity, iron metabolism, magnesium ion homeostasis, B cell apoptosis, tumor necrosis factor (TNF) production, and estrogen signaling. Many of these genes and pathways are important not only for renal function, but also for SCD biology, providing additional support for the hypothesis that SCDN pathophysiology is unique from other forms of kidney disease. This study represents the largest local ancestry-aware analysis of SCDN to date, furthers our understanding of the genetic risk factors underlying SCDN, and proposes new targets that could be useful for the early identification and treatment of kidney dysfunction in SCD patients.

Importance: Several professional medical societies have removed race and ethnicity from widely used clinical algorithms with implications for millions of patients. Yet the opinions of patients and the public regarding the tensions underlying these pivotal changes have not been systematically explored. Objective: To assess global public opinion on the use of race or ethnicity in clinical algorithms, including preferences for different approaches to algorithmic reform and perceptions of alternative predictors. Design: Cross-sectional survey study. Setting: Multinational opt-in online survey conducted via Prolific in January 2026. Participants: A volunteer convenience sample with quota sampling to achieve approximately equal participation by sex at birth and across ten categories of self-identified race and ethnicity. Main Outcomes and Measures: Self-reported comfort with demographic and social predictors in clinical calculators, with net comfort defined as percentage extremely or somewhat comfortable minus percentage extremely or somewhat uncomfortable; preferences for race-specific versus race-free algorithms; perceptions of algorithmic harm or benefit. Results: Of 1,050 responses, 994 (94.7%) met eligibility criteria. Participants resided in 43 countries with a median age of 32.0 years (IQR, 26-41). Net comfort with the use of race or ethnicity in a hypothetical cancer risk calculator was +62.4% (95% CI: +57.8% to +66.9%), compared with +14.5% (95% CI: +9.1% to +19.9%) for postal or ZIP code. Overall, 87.9% (95% CI: 85.9% to 90.0%) were comfortable with race or ethnicity if a clinician explained its use and only 12.8% agreed race and ethnicity should never be used clinically. Across spirometry, kidney function, and cardiovascular risk calculators, 40.0% to 47.6% preferred race-specific versions, whereas 16.7% to 28.2% preferred race-free alternatives. Furthermore, a substantial proportion disagreed that they were well-represented by race and ethnicity categories, ranging from 22.1% for osteoporotic fracture risk equations to 42.9% for cardiovascular risk equations. These findings were consistent across countries, self-identified race and ethnicity, and among participants reporting prior experiences of racism in healthcare. Conclusions and Relevance: In our diverse multinational survey study, respondents were comfortable with the use of race and ethnicity across application areas, but often did not feel represented by existing categories and were less comfortable with the use of alternatives based on postal or ZIP codes.

Chronic kidney disease (CKD) confers disproportionate cardiovascular risk. In non-dialysis CKD, calcification accumulates primarily within the intimal layer. Clinical studies indicate that intimal calcification correlates with hyperphosphatemia, yet the cellular and molecular pathways remain unclear. Given evidence that osteocytes sense phosphate via fibroblast growth factor receptor 1 (FGFR1), we hypothesized that FGFR1-expressing vascular immune cells, especially neutrophils, act as mediators linking high phosphate to plaque mineralization. In vitro, phosphate triggered FGFR1-dependent signaling in human and murine neutrophils, inducing neutrophil extracellular traps (NETs). Activated neutrophils promoted the depletion of Fetuin-A, a major inhibitor of calcium-phosphate complexation, creating a milieu permissive to mineral nucleation. Newly formed calcium-phosphate particles amplified NETs through gasdermin D (GSDMD), establishing a feed-forward loop that enhanced mineralization and endothelial injury in co-culture assays. Human arteriosclerotic plaques from CKD patients showed NETs markers co-localizing with calcified deposits. In vivo, pharmacological FGFR inhibition attenuated arterial intimal calcification and suppressed NET formation in CKD mice. These findings identify phosphate sensing via neutrophil FGFR1 and subsequent crystal-induced GSDMD signaling as drivers of intimal vascular calcification in CKD. Targeting phosphate-sensing pathways, NET formation, and neutrophil-driven mineralization may mitigate vascular calcification and reduce cardiovascular risk in CKD.

Background: Psychological distress is common in chronic kidney disease (CKD) and is associated with reduced quality of life, treatment non-adherence, and worse clinical outcomes. Distress in CKD is also linked to difficulties adjusting to the demands of illness management. Despite this, psychological support remains inconsistently integrated within kidney care pathways, and existing interventions often lack clear theoretical specification and explicit targeting of mechanisms underpinning adjustment to CKD. Objectives: To describe the systematic development of iADJUST, a theory-informed patient co-designed digital psychological intervention targeting key cognitive and behavioural mechanisms involved in adjustment to CKD. Methods: Intervention development was guided by the Medical Research Council framework for complex interventions. A structured, iterative process integrated empirical evidence, psychological theory, and patient and public involvement and engagement. The Common-Sense Model of Self-Regulation and cognitive behavioural theories informed the identification of modifiable maintaining mechanisms associated with adjustment to CKD. Intervention components were mapped onto these mechanisms and refined through co-design with people living with CKD. Results: iADJUST is a six-session self-guided digital psychological intervention delivered over 12 weeks and supplemented by therapist contact. The intervention targets illness-related uncertainty, fatigue-related activity dysregulation, catastrophic what-if thinking, self-critical evaluation, and behavioural withdrawal. It integrates psychoeducation, cognitive and behavioural strategies, maintenance planning, and elements from acceptance and commitment therapy and compassion-focused approaches. Content is delivered through video, audio, and guided tasks and activities. Conclusion: iADJUST provides a theory-informed, evidence-based psychological intervention for CKD explicitly mapping intervention components to maintaining cognitive and behavioural mechanisms implicated in adjustment. Feasibility evaluation is underway.

Background Coeliac disease (CD) diagnosis on duodenal biopsies is limited by interobserver variability. We have previously demonstrated pathologist-level performance with our artificial intelligence (AI) model for the histopathological diagnosis of adult CD, but not in paediatric practice. As paediatric CD screening programmes expand internationally, accurate and scalable diagnostic tools are needed. We investigated whether an AI model trained exclusively on adult whole-slide images (WSIs) can generalise to paediatric CD diagnosis across independent centres. Methods A training and validation dataset of 9,958 WSIs from 8,421 adult patients (961 CD) from five centres was used to develop an ensemble of multiple-instance learning models using features from a foundation model. Testing was performed on 708 consecutive paediatric patients (86 CD) from two centres (Edinburgh and Southampton) not included in training. Model calibration was assessed, and probability outputs were grouped into clinically interpretable categories. Findings In adult cross-validation, the AI model achieved an area under the receiver operating characteristic curve (AUC) of 98.7%, sensitivity of 84.9%, specificity of 99.0%, and negative predictive value (NPV) of 98.1%. On testing (paediatric) datasets, performance remained high (AUC 98.8%, sensitivity 80.2%, specificity 98.4%, NPV 97.3%). Restricting analysis to predictions outside the intermediate-probability range (predicted CD probability <10% or [&ge;]65%; 85.3% of cases) improved sensitivity to 100% and specificity to 98.7%. No misclassifications were observed among high-confidence predictions (<2% or [&ge;]85%; 66.0% of cases). The expected calibration error was 0.03. Performance improved significantly when biopsies from both duodenal sites (bulb [D1] and descending [D2/3]) were considered. Interpretation Our AI model, trained on adult biopsies, generalises to paediatric CD diagnosis across centres and scanner platforms. Well-calibrated probability outputs provide clinically interpretable measures of diagnostic confidence and could support safe identification of CD-negative biopsies within defined thresholds. These findings demonstrate the feasibility of applying adult-derived AI models in paediatric populations and reinforce the importance of multi-site (D1 & D2) biopsy sampling.

BackgroundNeonatal sepsis is a major cause of morbidity and mortality, particularly in low- and middle-income countries such as Senegal, where incidence is 78-104 per 1,000 live births and mortality exceeds 20 per 1,000, with case fatality rates around 36%. Diagnosis is difficult due to non-specific clinical signs and lack of molecular biomarkers, highlighting the need for improved early diagnostic molecular markers that could be applied even outside of hospital settings. ObjectivesCompare neonatal and adult serum proteomes to establish a reference and identify serum protein biomarkers of neonatal sepsis. MethodsSerum samples from Senegalese neonates and adults were analyzed using data-independent acquisition (DIA) proteomics on neat serum (Evosep-timsTOF HT platform). The cohort comprised 6 neonates with non-confirmed sepsis (NCS), 22 with confirmed sepsis (CS), 17 healthy newborn controls (HC), 6 unclassified and 20 healthy adults. Downstream analyses included differential protein abundance testing, unsupervised clustering, weighted gene co-expression network analysis (WGCNA), and correlation analyses with clinical parameters. ResultsWe identified 979{+/-}20 proteins in newborns versus 718{+/-}40 in adults. Newborns showed reduced immune-response proteins, a narrower dynamic range, and increased structural proteins such as collagens, consistent with immune immaturity and tissue development. Unsupervised WGCNA analysis led to a 53-protein cluster discriminated CS from NCS/HC. Some of these dysregulated proteins identified have already been reported in independent studies using different approaches in neonatal and/or adult sepsis. Our larger panel however of identified markers maps to three major biological processes involved in sepsis: (i) pathogen sensing (LBP, CD14), and acute-phase inflammation (e.g. CRP, SAA1/2, ORM1/2); (ii) innate immune activation and leukocyte recruitment (e.g., FCGR3A, CSF1R, CD163, CD206) and final platelet exhaustion and metabolic dysregulation, (e.g., PF4, PPBP, THBS1, GP5); (iii) endothelial injury and microvascular dysfunction with tissue remodeling (e.g., ICAM1, VCAM1, VWF, SPARC) and loss of protective lipoproteins and serpins (e.g., APOA1, APOA2, APOM, SERPINA4, SERPINA5) ConclusionThis study provides a very comprehensive neonatal serum proteome characterization and identifies, for the first time, a protein panel of proteins mapped to three major processes in sepsis.

Background: Citrin deficiency, caused by biallelic pathogenic variants in SLC25A13, must be identified early to prevent serious complications such as hyperammonemia and liver failure. However, clinical diagnosis is often delayed due to its nonspecific presentation and limited sensitivity of amino acid-based newborn screening methods. Although genome-based evaluations are being investigated to address these issues, concerns about their cost, turnaround time, variant interpretation ability, and data handling highlight the need for a more practical yet reliable alternative. We investigated the feasibility of applying proteomic approach on dried blood spots (DBS), which are routinely used in newborn screening. Methods: We performed untargeted liquid chromatography-tandem mass spectrometry to analyze the proteome of DBS using a previously developed "non-targeted analysis of non-specifically DBS-absorbed proteins" (NANDA) workflow. SLC25A13 protein abundance was quantified in individuals with biallelic loss-of-function mutations, compound loss-of-function/missense mutations, and heterozygous carriers; this was also evaluated in healthy and diseased controls representing relevant differential diagnoses. To leverage proteomic information, we derived a multivariate proteomic signature using feature selection and evaluated its performance with leave-one-out cross-validation. Biological relevance was assessed by enrichment analysis, and complementary transcriptomics was performed using RNA sequencing. Results: A total of 7,474 proteins, including SLC25A13, were consistently detected in DBS. SLC25A13 was undetectable in individuals with biallelic loss-of-function mutations. However, individuals with compound loss-of-function/missense genotypes showed reduced but measurable SLC25A13 levels, comparable to those observed in heterozygous carriers. In contrast, a compact 15-protein signature accurately identified individuals with compound loss-of-function/missense genotypes (AUC, 0.99; sensitivity, 1.00; specificity, 0.95). The signature was enriched for Ca2+-response, and transcriptomics showed downregulation of genes related to multimodal ion channels in affected individuals compared to controls. Conclusions: DBS-based proteomic profiling may assist in the diagnosis of citrin deficiency through SLC25A13-quantification and a biologically plausible multivariate signature. More broadly, this strategy offers a promising new diagnostic layer for protein disorders, providing a proteomic readout in a clinically practical DBS format with potential utility for future diagnostic and screening applications.

Sphingosine-1-phosphate lyase insufficiency syndrome (SPLIS) is a rare condition causing nephrotic syndrome, neuropathy, and other manifestations. SPLIS is caused by mutations in SGPL1, which encodes sphingosine-1-phosphate lyase (SPL), a pyridoxal 5-phosphate (PLP)-dependent enzyme needed to degrade the bioactive sphingolipid sphingosine-1-phosphate (S1P). Supplementation with the PLP precursor pyridoxine benefits some individuals with PLP-dependent enzymopathies. We sought to establish whether pyridoxine has therapeutic activity in SPLIS. Neurological improvement, plasma S1P normalization, and increased SPL activity in patient-derived fibroblasts were observed after pyridoxine supplementation in a patient with R222Q-variant SPLIS. Additionally, PLP dose-dependently augmented recombinant R222Q-variant SPL activity. To further explore pyridoxines effects, gene editing was employed to create an R222Q-variant SPLIS mouse model. SPLR222Q mice fed pyridoxine-enriched chow lacked obvious phenotypes. However, SPL inactivation, S1P accumulation, wasting, anemia, proteinuria, and glomerulosclerosis developed in SPLR222Q but not WT mice fed chow with reduced pyridoxine. Ultrastructural analysis and super-resolution microscopy showed podocyte loss and foot process effacement. Transcriptional profiling revealed a pattern of cytokine upregulation and extracellular matrix remodeling. Inhibiting S1P production prevented nephrosis in SPLR222Q mice fed chow lacking pyridoxine. Our findings establish a novel SPLIS mouse model that recapitulates R222Q-variant SPLIS, demonstrates its responsiveness to pyridoxine, and implicates S1P in its pathophysiology.