Kidney International Reports

IntroductionThere remains considerable debate as to the cause of the epidemic of Mesoamerican Nephropathy (MeN). We have previously reported early loss of estimated glomerular filtration rate (eGFR) as a surrogate for disease onset in a population-representative cohort study of young-adults at risk of disease from Northwest Nicaragua. Using a nested case-control approach we analysed urine and serum proteins surrounding this timepoint with the aim of gaining insight into the primary disease aetiology. MethodsWe conducted label-free ultra high-performance liquid chromatography mass-spectrometry based proteomics using urine samples collected at the study visit before, and at, first observed eGFR loss amongst cases and compared results to matched controls. We then performed direct protein measurements in a discovery cohort followed by quantification of serum total immunoglobulin E (stIgE) at multiple timepoints in a replication cohort. ResultsProteomic analysis demonstrated no differences in the levels of any single protein between cases and controls (n=25 each), at either timepoint, after correction for multiple comparisons. However, functional enrichment analysis demonstrated upregulation of adaptive immune pathways amongst cases. Direct measurements in the discovery cohort using high-sensitivity PCR-based immunoassay (n=21 controls, 19 cases) demonstrated higher stIgE in cases at the study visit immediately prior to first observed eGFR loss (mean difference 810kU/L, 95% confidence interval (CI): 162-1457kU/L). In the replication cohort (n=22 cases, 21 controls) an stIgE level >500kU/L measured by electrochemiluminescence in study samples from any timepoint in the 3 years prior to the first observed loss of eGFR was independently associated with case status when compared to samples from controls at matched visits (adjusted Odds Ratio: 8.1, 95% CI: 1.4-47.8). DiscussionA high level of stIgE precedes loss of eGFR in those at risk of MeN. Understanding what leads to this rise is likely to be key to understanding the cause of the MeN epidemic. Lay SummaryMesoamerican nephropathy describes an epidemic-level chronic kidney disease impacting rural working age adults in Central America. Although a number of exposures, including occupational heat exposure, have been proposed the cause of the epidemic, there remains much debate as to the primary aetiology of the disease. In this study we interrogated urine and blood samples from individuals from affected communities at risk of disease both before and after they develop kidney dysfunction. Using two different approaches, analysis of both urine and blood samples provide evidence of upregulation of immunoglobulin-E (IgE) related pathways in the 2-3 years before individuals develop evidence of kidney disease. Infections (particularly those involving parasites) and allergic reactions, but not heat exposure, have been reported to increase IgE levels. Going forwards, understanding the cause of this increase in IgE in individuals at risk of disease is likely to provide insight into the cause of Mesoamerican Nephropathy epidemics.

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

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

IntroductionGenome-wide association studies (GWAS) for kidney function have mainly focused on creatinine-based glomerular filtration rate (eGFRcrea), which is affected by variation in muscle mass. Moreover, the genetic basis of the sexual dimorphism of chronic kidney disease is underexplored. MethodsWe performed a GWA meta-analysis for creatinine clearance (CrCl), a muscle mass-independent kidney function phenotype, in 58,976 individuals of European descent from the Lifelines Cohort Study. ResultsWe identified 16 independent loci with 21 genome-wide significant lead single nucleotide polymorphisms (SNPs) associated with CrCl, two of which had not been reported previously in kidney function GWASs: rs146465192, located near the RP1-249F5.3 gene (effect allele frequency (EAF) = 0.01, P = 3.38 x 10-9) and rs117014836, located near the AGPAT4 gene (EAF = 0.02, P = 5.42 x 10-9). Both SNPs were also associated with eGFRcrea in Lifelines (rs146465192: P = 1.34 x 10-8; rs117014836: P = 3.64 x 10-7), but not in previously published eGFR GWASs. In silico follow-up analyses revealed that rs146465192 was associated with plasma IGF2R ({beta} = -0.519, P = 1.40 x 10-6), while rs117014836 was associated with blood expression levels of AGPAT4 (eQTL P = 6.54 x 10-6). Furthermore, we identified two female-specific CrCl loci (t-statistic P < 0.004): rs8002366 (GPC6) and rs12908437 (IGF1R), associated with GPC6 expression in kidney (eQTL P = 8.38 x 10-10) and IGF1R expression in blood (eQTL P = 2.62 x 10-6), respectively. ConclusionThis first large-scale GWAS of CrCl revealed two new genetic variants among both sexes and two female-specific variants influencing kidney function. Lay summaryKidney function is a complex phenotype influenced by many different factors, including genetics. Earlier genetic studies often used the creatinine-based estimated glomerular filtration rate (eGFRcrea) as the measure of kidney function. However, eGFRcrea is influenced not just by kidney function but also by an individuals muscle mass, which may distort the results. Therefore, in this study we used creatinine clearance (CrCl), a measure of kidney function independent of muscle mass, to look for genes in a European-ancestry population. We identified 16 genetic regions; two of which had not been found before. We also found two additional regions that were only related to CrCl in females. This shows the added value of investigating CrCl and suggests sex-based differences in how genetics affect kidney function.

Acute kidney injury (AKI) and chronic kidney disease (CKD) are two interconnected clinical conditions, both defined by degree of functional impairment, but with heterogeneous clinical trajectories. Using new transcriptomic technologies, recent studies have described the cellular diversity in the healthy and injured kidney at the single cell level. Here, we used single nucleus transcriptomics to investigate the molecular diversity and commonalities in kidney biopsies from over 150 participants with AKI and CKD enrolled within the Kidney Precision Medicine Project (KPMP), and did so at the patient participant level. Using an unsupervised approach, we identified two multi-cellular programs associated with clinical and histopathological features of acute injury and chronic damage, respectively. We found that these programs are expressed across patients with AKI and CKD, supporting shared, rather than distinct, underlying molecular mechanisms. These programs capture tissue-level compositional changes towards adaptive and failed-repair states in tubular epithelial cells, as well as intra-cellular molecular changes characteristic of stress in all cell types. We identified subunits of the NFkB and AP-1 complexes, as well as members of the STAT family, as putative upstream regulators of the acute and chronic programs. We were able to link these continuous molecular measures of acute injury and chronic damage with urine and plasma protein profiles obtained at time of biopsy. These non-invasive protein signatures were predictive of renal outcomes in an independent cohort of 44 thousand participants from the UK biobank. In summary, unbiased identification of cellular programs in kidney disease biopsies defined molecular programs of injury cutting across conventional disease categorisation and established a non-invasive molecular link to long term patient outcomes.

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

Individuals with chronic kidney disease (CKD) have higher rates of hip fracture and post-fracture mortality. Although they may develop age-related osteoporosis similar to those without CKD, they may also exhibit CKD-related metabolic bone disease (MBD), characterized by low, high, or mixed turnover at similar levels of bone mineral density (BMD). Because BMD does not provide information about turnover status, clinical decision-making is challenging. This study evaluated the associations between circulating bone-turnover biomarkers and static histomorphometry in patients undergoing hip-fracture surgery. In this cross-sectional study, we enrolled adults with and without CKD, defined as estimated glomerular filtration rate (eGFR) [&le;]60 ml/min/1.73m{superscript 2} (CKD-EPI 2021), undergoing hip-fracture surgery. Blood samples, bone specimens from the femoral head or greater trochanter, and demographic and clinical data were collected at the time of surgery. Plasma biomarkers included -Klotho, bone alkaline phosphatase (BAP), dickkopf-related protein 1 (DKK-1), fibroblast growth factor 23 (FGF23), tartrate-resistant acid phosphatase 5b (TRAP5b), parathyroid hormone (PTH), and sclerostin. Logistic regression models, adjusted for age, gender, eGFR, and osteoporosis, assessed associations with CKD status. Tertiles of osteoblast surface (Ob.S/BS) and eroded surface (ES/BS) were defined in participants without CKD and applied to the full cohort. Multinomial and multivariable linear regression evaluated associations of biomarkers with these histomorphometry parameters. Among 97 enrolled participants (mean age 80 {+/-} 11 years; 67% female), 68% had CKD. Of 75 with complete biomarker and histomorphometry data, 96% demonstrated low bone turnover. CKD was associated with lower trabecular thickness (Tb.Th) and higher osteoid thickness (O.Th), osteoid volume (OV/BV), and osteoid surface (OS/BS), suggesting thinner, largely unmineralized trabeculae. Higher BAP (222.2% difference per doubling; 95% CI 77.2-485.8) and TRAP5b (319.3%; 95% CI 128.3-669.5) were directly associated with Ob.S/BS and ES/BS, whereas sclerostin was inversely associated with ES/BS (-28.9%; 95% CI -44.8 to -7.1). PTH was not associated with bone-turnover measures. These findings suggest that BAP, TRAP5b, and sclerostin may provide useful adjunct information alongside PTH for assessing bone turnover and guiding therapy in patients with and without CKD.

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

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

Introduction Glomerular filtration rate (GFR) is invasive to measure. Therefore, in clinical care, estimated GFR is derived from serum levels of endogenous filtration markers such as creatinine and cystatin C. Multiple studies from high income countries showed differences between estimated glomerular filtration rate based on cystatin C (eGFRcys) and creatinine (eGFRcr). This study aimed to assess the agreement between eGFRcys and eGFRcr in Ethiopian children and identify factors influencing higher eGFRcys and eGFRcr. Method We studied 350 Ethiopian children who were part of the iABC birth cohort study. At the recent follow-up (average age 10 years), serum cystatin C and creatinine were measured. Formulas by Berg (2015) and Hoste (2014) were used to estimate eGFRcys and eGFRcr, respectively, and Bland-Altman plots assessed their agreement. The difference in eGFR (eGFRdiff) was calculated and categorized as less than -15 mL/min/1.73 m2 (higher eGFRcr), between -15 and <15 mL/min/1.73 m2 (concordant), and greater than or equal to 15 mL/min/1.73 m2 (higher eGFRcys). Multinomial logistic regression was used to identify factors associated with higher eGFRcr and higher eGFRcys. Result Estimated glomerular filtration rate (eGFR) showed significant variation based on the estimation formula used. When using formulas by Berg (2015) and Hoste (2014), the median (IQR) eGFRcys and eGFRcr were 99.4 (90.0; 114.1), and 123.2 (110.3; 143.8) mL/min/1.73 m2, respectively. Overall, we observed a poor agreement between eGFRcys and eGFRcr, with only 94 (27.6%) children having concordant results compared to 220 (64.7%) with higher eGFRcr and 26 (7.6%) with higher eGFRcys. If the eGFRcys results are considered reliable, 27.5% of the children had eGFR below 90 mL/min/1.73 m2. Conclusion There was very marked variation in the distributions of estimated eGFRs depending on which formulas for children were used. Agreement between eGFR estimated using cystatin C and creatinine was poor among Ethiopian children. Relative to eGFRcys, kidney function may be overestimated by creatinine-based equation as up to 30ml/min in Ethiopia. Ideally, a validation study with GFR measured by gold standard methods (Inlulin clearance) among children is required. However, because of its invasive nature and financial concerns, Iohexol clearance studies are recommended.

ObjectivesTo develop and validate pediatric adaptations of the Venous Excess Ultrasound Score (P-VExUS) for noninvasive estimation of central venous pressure (CVP) in critically ill children. DesignProspective observational study. SettingPICU of a tertiary-care teaching hospital. PatientsFifty-six mechanically ventilated children (median age 7.4 months, median weight 6.0 kg) with central venous catheters. InterventionsNone. Measurements and Main ResultsVenous Doppler ultrasonography of the inferior vena cava, hepatic, portal, and intrarenal veins was performed at the bedside. Two P-VExUS models were tested: (1) a categorical grading system (0-III) and (2) a semiquantitative point-based score (0-7). Both models showed significant associations with CVP. For predicting elevated CVP (>12 mmHg), model 1 achieved an AUROC of 0.74 (95% CI 0.61-0.85) with 45% sensitivity and 98% specificity, while model 2 demonstrated superior accuracy with an AUROC of 0.94 (95% CI 0.84-0.98), sensitivity 82%, and specificity 91% (p < 0.001). For detecting low CVP (<7 mmHg), model 2 also outperformed model 1 (AUROC 0.80 vs. 0.69, p = 0.02). Among individual venous Doppler components, intrarenal veins had the highest discriminative ability (AUROC 0.92), followed by hepatic (0.89) and portal (0.80) veins. ConclusionsTwo pediatric-specific P-VExUS models were feasible and accurate for estimating CVP in critically ill children. The point-based model (model 2) demonstrated superior diagnostic performance, supporting its potential as a noninvasive tool to assess venous congestion at the bedside. Research in ContextO_LIVenous congestion, reflected by elevated central venous pressure (CVP), is associated with adverse outcomes in critically ill children, including mortality and renal dysfunction. C_LIO_LIThe Venous Excess Ultrasound Score (VExUS) is validated in adults, but pediatric-specific adaptations and cutoff values remain poorly defined. C_LIO_LIThere is a need for noninvasive, bedside tools to estimate CVP in children and guide fluid management in the PICU. C_LI What This Study MeansO_LIThis study validates pediatric-specific adaptations of the Venous Excess Ultrasound Score (P-VExUS) for estimating CVP in critically ill children. C_LIO_LIThe semiquantitative point-based model provided more consistent and accurate discrimination of venous congestion compared with categorical grading. C_LIO_LIThese findings highlight the feasibility and potential clinical utility of venous Doppler ultrasonography as a noninvasive bedside tool in the PICU. C_LI

BackgroundNeonatal jaundice management increasingly relies on transcutaneous bilirubinometry (TcB), yet discrepancies with serum bilirubin (TSB) have limited its clinical reliability. This study introduces Skin Residual Bilirubin Volume (SRBV) as a physiologically grounded framework to enhance TcB interpretation. ObjectiveTo evaluate SRBV as an explanation for TcB-TSB discordance and assess whether incorporating SRBV improves the interpretability and reliability of TcB measurements during diagnosis, phototherapy, and recovery. MethodsTcB readings (MBj20) were calibrated against laboratory TSB in non-jaundiced neonates (TSB <3 mg/dL). Neonates undergoing phototherapy were monitored using paired TcB measurements before and after treatment breaks (TBL-out and TBL-return). TSB was measured before treatment, at mid-treatment, and prior to discharge. Patterns of TcB-TSB disparity and an observed reproducible Recovery Value Flip (RVP) phenomenon were analysed. ResultsAcross 102 neonates, TBL consistently equalled or exceeded TSB, supporting the additive SRBV model. Early in phototherapy, TBL-return > TBL-out, indicating persistent cutaneous bilirubin. A reproducible RVP occurred mid-treatment, after which TBL-return < TBL-out coincided with sustained bilirubin decline. Fractional SRBV contribution increased with baseline bilirubin and persisted into recovery, demonstrating dynamic, patient-specific cutaneous bilirubin retention. ConclusionSRBV provides a biologically plausible explanation for TcB-TSB discordance and dynamic TcB behaviour. Incorporating SRBV into TcB interpretation enables physiologically informed monitoring, improving safety and reliability in laboratory-limited neonatal settings. Significance StatementTranscutaneous bilirubinometry is widely used but limited by disagreement with serum bilirubin. This study introduces SRBV as a physiological explanation for TcB variability and proposes an SRBV-adjusted framework that transforms TcB measurements into actionable, non-invasive clinical guidance.

Background and AimsCholedocholithiasis (CDL) is a common condition that can lead to serious complications, requiring effective risk stratification for timely intervention. While current guidelines use clinical predictors, imaging, and laboratory markers for risk assessment, the role of glutamate dehydrogenase (GLDH) in CDL remains poorly understood. This study aims to evaluate its potential as a clinical biomarker for identifying patients with CDL. MethodsThis single-center cohort study identified 23,103 patients who presented to the emergency department of the University Medical Center Hamburg-Eppendorf and underwent routine abdominal laboratory testing between May 2021 and December 2023. Patients were classified into CDL and other diagnoses. To assess the predictive value of age, sex and laboratory markers for CDL, we developed a random forest machine learning model, conducted a backward stepwise logistic regression and performed receiver operating characteristic (ROC) analysis. Results152 patients were diagnosed with CDL and 22,951 with other diagnoses. In the random forest machine learning model, GLDH emerged as the most significant feature for predicting CDL. ROC analysis revealed that GLDH had the highest area under the curve of 0.93 among laboratory markers. At the upper limit of normal, GLDH demonstrated the best sensitivity (92%) compared to aspartate aminotransferase (AST), alanine aminotransferase (ALT) and bilirubin. High GLDH levels exceeding 150 U/L demonstrate the highest specificity (99%) for CDL, outperforming AST, ALT and bilirubin. ConclusionGLDH outperforms AST, ALT and bilirubin as a screening and predictive marker for CDL, supporting its inclusion in clinical guidelines for risk stratification.

BackgroundThe effects of Banff histological diagnoses on kidney transplant outcome have been well characterized. However, repeated observation of such histological injury across multiple biopsies in kidney transplant recipients remains insufficiently explored. MethodsIn an observational cohort (N=1819 transplantations with 5736 post-transplant biopsies, recurrent event survival models quantified transitions between diagnoses of T-cell mediated rejection (TCMR), antibody-mediated rejection (AMR), DSA-negative C4d-negative microvascular inflammation (MVIDSA-/C4d-), BK polyomavirus nephropathy (BKPyVAN), borderline TCMR (bTCMR), and probable AMR (pAMR), revealing patterns in the disease trajectories. In two observational cohorts (N=1818 transplantations with 5732 biopsies, N=853 transplantations with 975 biopsies), time-dependent cumulative covariates were constructed for TCMR, AMR, MVIDSA-/C4d- and BKPyVAN, enabling estimation of associations of repeated diagnoses with graft failure using multivariable cause-specific Cox models. ResultsThe incidence rate of a diagnosis was most strongly associated with earlier diagnosis of the same type, but associations between different types of diagnoses also occurred. The hazard of kidney graft failure was significantly increased by repeated observation of TCMR in multiple biopsies (HR 7.97, 95% CI 4.94 - 12.86), as well as by repeated AMR (HR 6.19, 95% CI 3.15 - 12.17), repeated MVIDSA-/C4d- (HR 4.53, 95% CI 2.15-9.54) and repeated BKPyVAN (HR 10.90, 95% CI 5.83 - 20.35). The hazard of graft failure was increased more after repeated diagnoses in transplants than after first diagnoses. The effects of repeated TCMR and repeated AMR remained significant even when observed in protocol biopsies in the absence of graft dysfunction. Repeated observation of BKPyVAN was the most detrimental of all diagnoses when observed in indication biopsies, but it was the least harmful when observed in protocol biopsies. ConclusionIncidence of Banff histological diagnoses appears to be affected by earlier diagnoses, especially those of the same type. These repeated observations of a specific diagnosis have an additional effect on the hazard of graft failure, underscoring a critical unmet need for adequate treatment strategies for these recurrent or persistent injury processes. Lay summaryIn two observational cohorts of 1819 and 750 kidney transplant recipients, kidney transplant biopsies were taken at multiple time points after transplantation. Based on the Banff classification for transplant pathology, various post-transplant diseases were diagnosed, often at more than one time point during follow-up. We assessed patterns in the occurrence of diagnoses over time, and related these diagnoses to survival of the kidney grafts using survival models with time-dependent cumulative diagnoses. We found that repeated observation of the same diagnosis was much more common than consecutive observations of different diagnoses. Repeated diagnoses of tissue injury also decreased kidney graft survival more compared to single diagnoses. This indicates that treatment options for patients with repeated or persistent diagnoses are currently inadequate and novel strategies are needed.

BackgroundIn lung transplantation, de novo immunodominant donor-specific anti-HLA antibodies recognizing HLA-DQ antigens (dn-iDSA-DQ) are predominant and can induce chronic lung allograft dysfunction (CLAD). We previously developed a method to measure the active concentration of dn-iDSA-DQ. We aimed to determine whether this new quantitative biomarker is associated with transplantation outcomes. MethodsThis retrospective multicentre cohort study included 90 lung transplant recipients (LTRs) developing dn-iDSA-DQ, evidenced through single antigen flow beads (SAFB) follow-up. We measured the active concentration of dn-iDSA-DQ at the time of their first detection (T0) for all LTRs, and within the 2 years after DSA detection, whenever possible. SAFB dn-iDSA-DQ characteristics and clinical data were retrieved up to 5 years after DSA detection. ResultsWe tested 184 sera with SPR (n=90 at T0, n=94 within the 2 years after DSA detection), among which 63 (34.4%) had a quantifiable concentration of the dn-iDSA-DQ ([&ge;]0.3 nM). The median SAFB mean fluorescence intensity (MFI) of the dn-iDSA-DQ with a concentration [&ge;]0.3 nM was higher (p<0.0001), yet the correlation between SAFB MFI and active concentration was low (r=0.758, p<0.0001). In multivariate analysis, a concentration of the dn-iDSA-DQ [&ge;]0.3 nM at T0 was independently associated with a lower 2-year CLAD-free survival (HR 2.06, p=0.02). A concentration of the dn-iDSA-DQ [&ge;]0.3 nM within the 2 years from DSA detection was associated with a lower graft survival in univariate analysis. ConclusionsActive concentration of dn-iDSA-DQ appears as a valuable biomarker to identify pathogenic DSA at their first detection because of its association with CLAD.

PurposeWhile genomic testing is integral to pediatric inborn errors of immunity (IEI) care, few studies have examined strategies to support its optimal delivery. This study aimed to characterize a pediatric IEI cohort and assess the impact of implementing a mainstream model-of-care (MoC). Materials/MethodsComprehensive chart audit was conducted for patients ([&le;]18y) who received IEI genomic testing in Queensland, Australia, from 2017-2025. Descriptive analyses captured demographic and clinical characteristics, genomic testing and results, and management outcomes. Inferential analyses assessed changes in genomic practices pre-MoC (<2021) and post-MoC ([&ge;]2021). Results322 patients met eligibility criteria (n=481 genomic test). Diagnostic yield (27.6%) varied by testing indication, with the highest rate among phagocytic defects (n=4/4;100%) and severe combined immunodeficiency (n=8/10;80%). Very-early-onset inflammatory bowel disease had the lowest diagnostic yield (n=3/68;4.4%), prompting changes to testing criteria. Molecular diagnosis resulted in management changes for 90.5% patients. Genomic testing was widely used pre-MoC (n=251 genomic tests). All outcomes significantly improved pre-and post-MoC (p<0.05): duplicate testing decreased (13.9% to 0%); variants of uncertain significance reduced (37.7% to 7.1%); informed consent documentation increased (70.5% to 88.4%); and diagnostic yield increased (16.2% to 27.4%). ConclusionTargeted interventions are needed to support delivery of genomic testing and strengthen service effectiveness.

IntroductionAdverse drug reactions (ADRs) remain a major public health issue, and genetic factors contribute importantly to interindividual variability in drug response. Pharmacogenetic testing helps reduce ADR risk by optimizing drug selection and dosage, particularly in monogenic disorders. Material and MethodsWhole-exome sequencing of 6,739 samples from the Russian population was performed using the MGIEasy Universal DNA Library Prep Set on the DNBSEQ-G400 platform (MGI). Variants in 48 genes were examined, focusing on inherited arrhythmias (Long QT syndrome, Short QT syndrome, Timothy syndrome, Andersen-Tawil syndrome, Brugada syndrome, Atrial fibrillation, Catecholaminergic polymorphic ventricular tachycardia), enzyme deficiencies (Glucose-6-Phosphate Dehydrogenase Deficiency [G6PDD], Porphyrias), Dravet Syndrome (DS) and Malignant Hyperthermia (MH). All identified variants had been reported at least once as pathogenic (P) or likely pathogenic (LP) in ClinVar, along with those occasionally classified as variants of uncertain significance (VUS). Each variant was manually re-evaluated according to ACMG criteria. ResultsA total of 75 unique variants in 18 genes were observed in 119 individuals (1.77%), including 21 carriers and 13 women with a G6PD mutation. Of these, 46 variants were classified as P, 21 as LP, and 8 as VUS. Missense variants accounted for the largest proportion (73.33%). The most affected genes were KCNQ1 (24/119), which exhibited the highest number of unique variants (18), G6PD (20/119), SCN1A (15/119), and RYR1 (14/119). Regarding associated conditions, mutations linked to arrhythmias were found in 51 individuals, MH in 27, G6PDD in 20, DS in 15, and Porphyrias in 6. ConclusionsIncorporating genetic information on both common and rare clinically actionable variants into therapeutic decision-making has the potential to improve medication safety, reduce preventable ADRs, and enhance the effectiveness of personalized pharmacotherapy.

BackgroundAmiodarone is a widely used antiarrhythmic which frequently induces thyroid dysfunction, including both amiodarone-induced hypothyroidism (AIH) and thyrotoxicosis (AIT). Whether genetic factors contribute to these adverse drug reactions is unknown. In this study, we aimed to identify genetic variants that influence the risk of amiodarone-induced thyroid dysfunction and to evaluate their potential to support genotype-guided risk screening. MethodsThis pharmacogenetic study comprised two genome-wide meta-analyses of AIH and AIT using five datasets (Copenhagen Hospital Biobank, The Danish Blood Donor Study, Estonian Biobank, deCODE genetics, and Mass General Brigham Biobank). Key measures included the odds ratio (OR) per risk allele, the variants effects on spontaneous thyroid disease and biomarkers, and their clinical predictive ability, assessed by the area under the receiver operating curve (AUC), positive and negative predictive values (PPV and NPV). FindingsThe AIH meta-analysis (880 cases, 4,031 controls) identified three genome-wide significant loci in: FOXE1 (rs36052460; OR 2.58, allele frequency [AF] = 64.3%, P = 2.55 x 10-44), FOXA2 (rs2424459; OR 1.67, AF = 71.3%, P = 2.59 x 10-14), and ADAM32 (rs12681571; OR 1.49, AF = 61.8%, P = 3.05 x 10-9). The AIT meta-analysis (385 cases, 4,936 controls) identified one locus in CAPZB (rs867355; OR 1.63, AF = 66.1%, P = 3.49 x 10-8). In risk prediction models, a polygenic risk score (PRS) of the AIH variants increased the AUC by 9.2% (95% CI 6.6 - 11.9%), which outperformed a genome-wide hypothyroidism PRS (1.5% AUC increase, 95%CI 0.0 - 2.9%). Similarly, the CAPZB variant improved AIT prediction (AUC increase of 4.0%, 95% CI 0.4 - 7.5%) beyond a hyperthyroidism PRS (0.2% AUC increase, 95%CI -0.8 - 1.2%). Genotype-guided screening would identify individuals at low risk (NPVs ranging from 90-95% and PPVs 2-20%). InterpretationWe identified genetic variants that influence the risk of developing amiodarone-induced thyroid dysfunction. Genotype-guided screening offers a potential complement to current strategies and personalize pre-treatment risk assessment for patients initiating amiodarone therapy.

Severe combined immunodeficiency (SCID) is a heterogeneous, recessive disorder, associated with the onset of severe, recurrent infections in the first few months of life. SCID is fatal if left untreated, but outcomes can be significantly improved by prompt diagnosis and treatment, particularly prior to onset of infection. Consequently, SCID is already included in many newborn screening programmes around the world, as well as multiple international genomic newborn screening (gNBS) research programmes. However, there is a vital need to estimate penetrance of SCID variants in population cohorts, to mitigate the potential consequences of reporting low penetrance variants in a genotype-first gNBS setting. This study aimed to assess the penetrance and prevalence of these variants in the UK Biobank population cohort. Whole genome sequencing data from 490,640 individuals was used to interrogate 16 SCID genes for potentially causal variation. We identified 4206 carriers of single heterozygous pathogenic variants ([~]1% of cohort), but only 6 individuals double heterozygous, homozygous or hemizygous for relevant pathogenic variants. 3 individuals would be expected to require further testing had they been identified by gNBS, suggesting that fewer than 1 in 100,000 newborns might require follow-up testing due to SCID variants. Following detailed variant curation, we were able to identify only 2 unabected individuals likely to be harbouring biallelic pathogenic variants, potentially indicative of reduced penetrance. Nonetheless, SCID remains an excellent candidate for inclusion in gNBS studies, due its severity, clinical actionability and expected low false positive rate, although care should be taken when reporting hypomorphic variants.

BackgroundPersonalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) data provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the diagnostic applicability of exome data for pharmacogenomics remains insufficiently studied. Materials and MethodsA retrospective analysis of 6,102 anonymized sequencing datasets obtained between 2020 and 2025 was performed using the DNBSEQ-G400 (MGI) platform and Agilent SureSelect Human All Exon v6/v7/v8 enrichment kits. SNV and indel detection, CNV analysis, high-resolution HLA typing, and diplotype assignment for key pharmacogenes were conducted. Pharmacogenomic annotations were derived from PharmGKB (levels of evidence 1A-2B), CPIC, and PharmVar. Additionally, WES limitations and the feasibility of imputing non-coding pharmacogenetic variants were evaluated. ResultsPopulation frequencies of alleles and metabolic phenotypes were determined for 13 Very Important Pharmacogenes (VIPs), along with the distribution of HLA class I and II alleles. The highest allelic and phenotypic variability was observed in CYP family genes, particularly CYP2D6, CYP2C19, and CYP2B6. A total of 663 pharmacogenomic annotations were identified, predominantly related to drug metabolism (50.38%) and toxicity (29.56%), including psychotropic agents, anticoagulants, statins, opioid analgesics, antineoplastic agents, and immunosuppressants. At least 32 drugs require pharmacogenetic testing based on variants located in non-coding regions, as well as accurate CYP2D6 copy number determination. Linkage disequilibrium analysis demonstrated the inability to reliably impute most non-coding pharmacogenetic variants from WES data. ConclusionThese findings represent one of the largest reference assessments to date of pharmacogenetically significant variant and HLA allele frequencies in the Russian population. The results confirm the utility of WES for population pharmacogenomic screening while simultaneously highlighting its fundamental limitations and the need for alternative genetic diagnostic methods in selected cases.