American Journal of Transplantation

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.

BackgroundIron metabolism disorder is highly prevalent before and after heart transplantation (HTx). The impact of pretransplant and posttransplant iron disorder on posttransplant outcomes is unclear. ObjectivePretransplant serum levels of key regulator proteins of iron metabolism (hepcidin, interleukin-6, erythroferrone) were tested for prediction of the composite outcome 1-year posttransplant all-cause mortality (ACM) or [&ge;]moderate acute cellular rejection (ACR). Furthermore, serum levels of these proteins were measured at 1-year posttransplant to explore their posttransplant course and association with ACR. ResultsIn a multicenter cohort including 276 consecutive HTx recipients, patients with or without outcome (n=118/158, respectively) did not differ for pretransplant demographics, mismatch of donor/recipient sex, mismatch of HLA epitopes, and hepcidin or interleukin-6 levels. However, pretransplant erythroferrone levels were higher (1.40 vs. 1.19 ng/mL; p=0.013) and hemoglobin levels were lower (124.5 vs. 127 g/L; p=0.004) among patients with the composite outcome. Pretransplant erythroferrone levels >2.25 ng/ml (4th-quartile) were significantly associated with the composite outcome in multivariable analysis (OR 2.17; 95% CI 1.19-3.94, p=0.011; reference: 1st-3rd quartiles). In adjusted predicted proportions analysis, the incidence of the composite outcome was higher in 4th-quartile patients when compared to 1-3rd -quartiles patients (58.0 vs. 37.7%; p=0.003). At 1-year posttransplant, 80.4% of patients with pretransplant erythroferrone levels >2.25 ng/ml remained high; 88.4% of patients with pretransplant erythroferrone levels [&le;]2.25 ng/ml had high levels posttransplant. In 1-year survivors with high erythroferrone levels and [&ge;]moderate ACR during the first postoperative year, the ratio of the opponent regulators of hepcidin gene expression, erythroferrone to interleukin-6, was higher when compared to those without ACR (1.18 vs. 0.41; p=0.016). Hepcidin levels were not different between these two subgroups indicating disproportionate ERFE increase. ConclusionHigh pretransplant erythroferrone levels predict the composite posttransplant outcome 1-year ACM and ACR. Disproportionately high posttransplant erythroferrone levels are related with [&ge;]moderate acute cellular rejection.

BackgroundKidney volumetry derived from CT has been proposed as a surrogate of renal function in living kidney donor evaluation. However, clinical integration has been limited by reader-dependent workflows and semiautomatic methods susceptible to image quality. PurposeTo evaluate whether fully automated CT-based segmentation of renal cortex, medulla and total parenchymal volume provides reproducible volumetric biomarkers associated with global and split renal function in living kidney donor candidates. Materials and MethodsIn this retrospective single-center study, 461 living kidney donor candidates (2003-2021) underwent contrast-enhanced abdominal CT. A convolutional neural network was trained to automatically segment cortical, medullary, and total parenchymal volumes on arterial-phase images. Segmentation performance was evaluated against manual reference annotations. Volumes were indexed to body surface area. Associations with eGFR, 24-hour creatinine clearance, cystatin C, and tubular clearance were assessed using Spearman correlation coefficient ({rho}), and side-specific volume fractions were compared with scintigraphy -derived split function. ResultsAutomated segmentation achieved excellent agreement with expert reference segmentations (Dice 0.95 for cortex; 0.90 for medulla). eGFR correlated moderately with cortical ({rho} = 0.46) and total parenchymal volume ({rho} = 0.45), and modestly with medullary volume ({rho} = 0.30). Similar associations were observed for other global measures, with the strongest correlation for cortical volume and tubular clearance ({rho} = 0.53). Side-specific volume fractions correlated with scintigraphy-derived split renal function ({rho} = 0.49-0.56; all p < 0.001). ConclusionAutomated CT-based renal subcompartment segmentation provides reproducible volumetric biomarkers within routine donor evaluation. Cortical volume performs comparably to total parenchymal volume and tracks split renal function at the cohort level, suggesting potential utility in donor assessment.

Background & AimsPerihilar cholangiocarcinoma is an aggressive malignancy with clinical heterogeneity and poor long-term outcomes after resection. Current prognostic assessment relies mainly on anatomical staging and pathological features, which incompletely capture the entire postoperative risk. We aimed to determine whether integrative analysis of clinical, surgical, pathological and tumor genomic data could improve time-resolved, individualized recurrence-risk prediction after curative-intent resection. MethodsWe performed a multicenter retrospective study including patients undergoing curative-intent resection for perihilar cholangiocarcinoma in ten Spanish hospitals (2003-2023). Overall and disease-free survival were analyzed using Cox models. Outcome-agnostic clinical phenotypes were derived by unsupervised clustering of clinical and surgical features. Targeted tumor sequencing of cancer-associated hotspot regions and selected genes was performed. Prognostic models integrating clinical and genomic data were trained and evaluated in independent training/test sets using penalized and latent-component Cox frameworks, with time dependent discrimination. ResultsThe final cohort comprised 142 patients, with a median follow-up of 26.4 months. Recurrence occurred in 61.3% of patients, and 53.5% died during follow-up. Classical pathological factors were strongly associated with survival and recurrence. Unsupervised outcome-agnostic clustering identified three reproducible clinical phenotypes with markedly different recurrence patterns and survival, only partially explained by anatomical staging. Integrative clinical-genomic modelling further improved recurrence-risk prediction, achieving high discrimination in independent validation (time-dependent AUC [~]0.8). Moreover, the integrative model assigned higher risk over time to patients who relapsed. Patients combining unfavorable clinical phenotype with high genomic-derived risk exhibited a high probability of early recurrence. ConclusionsIntegrated clinical phenotyping and targeted genomic profiling substantially refine recurrence-risk stratification after resection of perihilar cholangiocarcinoma beyond anatomical staging alone. This provides a pragmatic framework for risk-adapted postoperative surveillance and therapeutic decision-making. Impact and ImplicationsThis study provides a data-driven framework integrating clinical, surgical and targeted genomic information to refine prognostic stratification after resection of perihilar cholangiocarcinoma, addressing the limitations of anatomy-based staging in capturing biological heterogeneity. The results are particularly relevant for clinicians managing postoperative surveillance and adjuvant strategies, as they identify patient subgroups with markedly different risks of early recurrence despite similar conventional staging. In practical terms, the combination of unsupervised clinical phenotyping and a targeted, biologically informed genomic panel could support risk-adapted follow-up intensity, selection for adjuvant or experimental therapies, and enrolment into clinical trials. While prospective validation is required before routine implementation, this approach offers a feasible and interpretable pathway toward precision postoperative management in a highly aggressive malignancy.

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.

Vaccination frequently elicits suboptimal immunogenicity in organ transplant recipients, particularly those on long-term immunosuppressive therapy, highlighting the need for improved understanding of immunosuppression mechanisms and optimized vaccination strategies. This study enrolled a cohort of 132 individuals and observed significantly lower antibody levels in kidney transplant recipients (KTRs) compared to non-transplant controls (non-KTRs). Antibody levels were inversely associated with both the dosage and duration of immunosuppressive therapy. Complementary small animal studies demonstrated that immunosuppressive treatment dosage-dependently and reversibly impaired antibody production, primarily by depleting immune cells, notably B cells. A single shot of adenoviral vector-based vaccines demonstrated enhanced immunogenicity relative to two shots of alum-adjuvanted protein vaccines, inducing potent neutralizing antibodies (NAbs) and a Th1-biased T-cell response even under continuous immunosuppression. The enhanced response was driven by reduced interference from pre-existing antibodies, sustained transgene expression, and the reprogramming of lipid metabolism to activate T and B cells. Our findings advocate for tailored vaccination strategies, positioning adenoviral vectors as a candidate modality for this vulnerable population.

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.

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.

Amatoxin-induced acute liver failure complicates misidentified foraged mushroom ingestion worldwide; abrupt multisystem collapse punctuates apparent improvement. Our prospective single-arm clinical trial investigated proactive toxicokinetic-based management to preserve elimination capacity: sustained enhanced hydration to maintain renal clearance; fasting plus octreotide to suppress meal-driven enterohepatic circulation; and intravenous silibinin to inhibit OATP1B3-mediated hepatic uptake, enabling safe passage and elimination of gallbladder-confined amatoxin-laden bile. Safety population (N=99) transplant-free recovery (TFR): 88.0% (87 recoveries, 6 transplants, 6 deaths). Protocol-adherent Efficacy population (n=86) TFR: 98.8% (85 recoveries, 1 transplant, 0 deaths). Multivariable analysis identified uninterrupted hydration as strongest TFR predictor (P<0.001), followed by earlier silibinin initiation (P=0.003); octreotide shortened INR recovery by 11 hours (P=0.033). These findings support a toxin elimination model in which preserved renal clearance and biliary sequestration are central recovery determinants. The kinetic balance between renal clearance and hepatic uptake governs both recovery and collapse.

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.

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.

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.

Background and aimsPopulation screening for liver disease in high-risk groups is recommended. Community diagnosis of liver disease is a challenge due to the asymptomatic nature of disease until very advanced stages. Moreover, regional variation in testing availability can result in people with clinically significant liver disease being missed. Machine learning (ML) has been proposed as a method to reduce diagnostic error and automate screening. We present a novel machine learning derived algorithm (ID LIVER-ML) designed to predict the risk of clinically significant liver disease in a high-risk community population to identify those needing further investigations or specialist referral. MethodsUsing data from 2039 patients recruited to two UK cohorts, we created a parsimonious model using investigations that would be available in primary care using liver stiffness measurement as reference standard. The performance of ID LIVER-ML was compared against FIB-4 score in a second unseen hold out cohort (n=327). ResultsID LIVER-ML performed well at identifying patients at risk of clinically significant liver fibrosis (sensitivity 0.90, Specificity 0.43, PPV 0.54, NPV 0.86, AUC 0.83) and outperformed conventional risk scoring systems (FIB-4: AUC 0.65; NAFLD Fibrosis Score: AUC 0.66; APRI: AUC 0.53; BARD: AUC 0.58). ConclusionMachine learning derived algorithms can help screen high risk populations in a community setting for liver fibrosis. ClinicalTrials.gov ID: NCT04666402 Impact and ImplicationsThe prevalence of steatotic liver disease is rising globally and is an increasingly significant challenge for healthcare systems. Existing risk stratification scores are not validated in a real-world cohort where patients have risk factors for multiple aetiologies of liver disease. Our work shows that a machine learning model can predict the risk of clinically significant liver disease using routine primary care data, better than existing non-invasive risk stratification tools in a real-world cohort. This highlights a potential role for machine learning in the automation of fibrosis risk assessment in primary care. Highlights- Machine learning derived algorithms can predict the risk of clinically significant liver disease in an at risk community population with a mixed aetiology of liver diseases. - The performance of the ML algorithm (ID LIVER-ML) is not affected by metabolic, alcohol, or mixed aetiologies. - ID LIVER-ML outperforms traditional risk stratification scoring systems such as FIB-4 and NAFLD fibrosis scores. - Compared to the FIB-4 score, the use of Machine Learning can reduce the need for secondary care investigations by 59%.

IntroductionKidney biopsy reports contain rich information that is clinically actionable and useful for research. However, the narrative format hinders scalable reuse. We here investigated whether open-source large language models (LLMs) can extract relevant, standardized readouts from native kidney biopsy pathology reports. MethodsGerman free-text native kidney biopsy reports were parsed with three open-source LLMs (Llama3 70B, Llama3 8B, MedGemma) to generate structured JSON outputs covering relevant report elements (e.g., diagnosis, glomerular counts, histopathological patterns). Two independent observers manually curated the same report elements; disagreements between the two were resolved by an experienced nephropathologist to create the final ground truth. Performance was assessed using strict and soft matching and summarized accuracy. Inter-rated agreement was quantified using Cohens and Lights Kappa with 95% confidence intervals via 1000-times bootstrapping. ResultsLlama3 70B achieved the highest overall accuracy (93.3% strict, 97.1% soft), followed by MedGemma. These larger models showed near perfect performance for explicit and discrete variables and positivity of immunohistochemistry markers, while accuracy decreased for report elements requiring interpretation (e.g., primary diagnosis, interstitial inflammation in fibrosis vs. non-fibrotic cortex). Human raters showed strong agreement for the primary diagnosis ({kappa} = 0.74, 95% CI 0.64-0.84). Adding Llama3 70B or MedGemma as a third rater increased overall agreement (0.82, 95% CI 0.74-0.89 and 0.78, 95% CI 0.69-0.85, respectively), whereas Llama3 8B reduced it. ConclusionsOpen-source LLMs can accurately transform narrative nephropathology reports into a structured and machine-readable format, potentially supporting scalable retrospective cohort building. While some report elements can be extracted without supervision, interpretation-dependent elements should be supervised by a human observer. Lay SummaryRetrospective data collection from nephropathology reports is essential for building informative cohorts in computational nephropathology research, yet manual processing of narrative reports is time-consuming and limits scalability. In this study, we demonstrate that open-source large language models can reliably extract key diagnostic, quantitative, and descriptive data elements from kidney biopsy reports with high accuracy. While factual and clearly stated report elements can be extracted automatically, findings that require contextual or interpretative judgment still benefit from expert supervision. Overall, this approach substantially reduces manual effort and enables efficient generation of structured datasets from diagnostic routine, facilitating the development of kidney registries and future computational nephropathology research. In addition, such systems could be implemented into the routine diagnostic workflow, to directly transform narrative reports into structured data.

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.

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.

BackgroundPreoperative biliary stenting alters biliary colonization and may reduce the effectiveness of perioperative antibiotic prophylaxis in pancreatoduodenectomy. Although broader-spectrum regimens have been associated with improved infectious outcomes, their microbiological adequacy in routine clinical practice remains poorly defined. We therefore evaluated the real-world adequacy of a prolonged ampicillin-sulbactam protocol, its association with infectious outcomes and survival, and the potential impact of a universal piperacillin-tazobactam strategy. MethodsWe analyzed all consecutive patients who underwent elective pancreatoduodenectomy from 2002 to 2023 at our tertiary center. Demographic, operative, microbiological, and outcome data were retrieved from a prospectively maintained database. Patients were stratified by stent status. Adequacy of prophylaxis was defined as the full in vitro susceptibility of all bile isolates. The outcomes included 30-day infectious morbidity, clinically relevant POPF, PPH, DGE, reoperation, 30- and 90-day mortality and long-term survival. A coverage simulation was performed to compare ampicillin-sulbactam with a hypothetical universal piperacillin-tazobactam. Statistical methods included chi-square/Fishers exact tests, Mann-Whitney U tests, Cox models, McNemars test and Poisson regression. ResultsOf 956 patients, 424 (44%) had a biliary stent. Technical complications were comparable between groups, and rates of POPF and PPH were not increased. However, infectious morbidity was higher in stented patients, including sepsis (RR 1.62, 95% CI 1.05-2.51) and postoperative cholangitis (RR 2.20, 95% CI 1.36-3.56). Thirty- and 90-day mortality were increased (RR 2.88 and 2.73) but lost significance after adjustment. Bile cultures predominantly yielded Enterococcus and Enterobacterales with low ampicillin-sulbactam susceptibility. Overall adequacy was 21.7%. Among patients with bile cultures (n = 474), ampicillin-sulbactam covered 43.7% (207/474) versus 81.2% (385/474) with piperacillin-tazobactam; in stented patients with cultures (n = 397), coverage increased from 41.8% to 78.1%. Adequate ampicillin-sulbactam coverage was not associated with reduced infectious outcomes in Poisson models. ConclusionPreoperative stenting creates a polymicrobial, partially resistant biliary niche that ampicillin-sulbactam does not sufficiently cover. Our data shows that a piperacillin-tazobactam strategy substantially improves coverage and was therefore implemented at our center. Core message- Stented patients exhibit a distinct infectious risk profile characterized by Enterococcus-and Enterobacterales-dominated bile colonization rather than increased rates of technical complications. - In stented patients, real-world microbiological coverage of ampicillin-sulbactam was limited, and in vitro susceptibility did not independently translate into reduced postoperative infectious morbidity. - Broader prophylaxis, such as piperacillin/tazobactam, aligns with the actual flora and nearly doubles theoretical coverage, addressing the mismatch between stent-associated biofilms and narrow regimens.

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.