American Journal of Transplantation

Background: We aimed to identify data-driven FEV1 trajectory phenotypes post-chronic lung allograft dysfunction (CLAD), relate these phenotypes to patient factors and future graft loss, and develop a classification approach for prospective patients. Methods: We studied adult first lung recipients with probable CLAD from two prospective multicenter cohorts: CTOT-20 (n=206) and LTOG (n=1418). FEV1 trajectories over the first nine months post-CLAD were characterized using joint latent class mixed models, jointly modelling time-to-graft loss to account for informative censoring. Models were fit independently in both cohorts and also only among LTOG bilateral recipients. A classification and regression tree (CART) model was derived in LTOG bilateral recipients and applied to CTOT-20 bilateral recipients. Findings: Four distinct early FEV1 trajectory classes were identified in CTOT-20, with large differences in nine month graft loss (72.3%, 31.1%, 2.2%, 0%). In LTOG, similar trajectory patterns were reproduced, with an additional class demonstrating early post-CLAD FEV1 improvement. Among bilateral recipients, trajectory classes showed a clear risk gradient, including a high-risk class with 100% graft loss and a low-risk class with no early graft loss. A CART model incorporating clinical and spirometric variables demonstrated good discrimination in LTOG bilateral recipients (multiclass AUC 0.85) and consistent class assignment and trajectory patterns when applied to CTOT-20. Interpretation: We identified reproducible, clinically meaningful early post-CLAD FEV1 trajectory phenotypes with differential graft loss risk. These phenotypes and a pragmatic classification tool may support risk stratification, trial enrichment, and improved prognostication for patients and clinicians.

Background: Kidney transplantation is the preferred treatment strategy for end-stage kidney disease. Deceased donor kidneys usually undergo cold storage until kidney transplantation, leading to cold ischemia injury that may contribute to poor graft outcomes. However, the molecular characterization of potential mechanisms of cold ischemia injury remains incomplete. Results: To bridge this knowledge gap, we leveraged the 10x Visium spatial transcriptomic technology to perform full transcriptome profiling of murine kidneys subject to varying durations of cold ischemia typical in a deceased donor kidney transplant setting. We developed a computational workflow to identify and compare spatiotemporal transcriptomic changes that accompany the injury pathophysiology in a tissue compartment-specific manner. We identified proportional enrichment of oxidative phosphorylation (OXPHOS) genes with increasing duration of cold ischemia injury within the oxygen-lean inner medulla region, suggestive of atypical metabolic presentation. This was distinct in cold ischemia injury tissue compared to warm ischemia-reperfusion kidney injury tissue. Spatiotemporal trends were validated by qPCR and immunofluorescence in a larger cohort of mice. We provide an interactive online browser at https://jef.works/CellCarto-ColdIschemia/ to facilitate exploration of our results by the broader scientific and clinical community. Conclusions: Altogether, our spatiotemporal transcriptomic analysis identified coordinated molecular changes within metabolic pathways such as OXPHOS deep within the cold ischemic kidney, highlighting the need for increased attention to the inner medulla and potential opportunities for new insights beyond those available from superficial biopsy-focused tissue examinations.

The intestinal microbiome influences immune recovery and long-term outcomes after allogeneic hematopoietic stem cell transplantation (allo-SCT). While reduced bacterial diversity and depletion of immunomodulatory microbial metabolites during peri-engraftment have been linked to acute graft-versus-host disease (aGvHD) and mortality, it remains unclear whether microbiome recovery after engraftment and immune reconstitution is better reflected by bacterial diversity or by microbial metabolic output. We aimed to define microbiome recovery in the late post-transplant period and test whether a metabolite-based biomarker improves the prediction of clinical outcomes, including overall survival (OS) and chronic (c) GvHD. In this two-center longitudinal observational study, serial stool samples were collected from pre-transplant baseline to day +100 after allo-SCT in a discovery cohort (n = 20, Technical University Munich University Hospital (TUM)) and an independent validation cohort (n = 100, University Hospital Regensburg (UKR)). Gut microbiome composition was assessed by 16S rRNA gene amplicon sequencing, with metagenomic profiling in selected patients, and stool metabolites were quantified using targeted mass spectrometry. Patients were classified as RECOVERY or NO RECOVERY based on changes in bacterial richness between baseline and the post-transplant period. To capture microbial metabolic output, the previously established Immune-Modulatory Metabolite Risk Index (IMM-RI), comprising butyric, propionic, and isovaleric acids, desaminotyrosine and indole-3-carboxaldehyde, was adapted to the late post-transplant period (IMM-RI post-TX). Bacterial alpha diversity frequently improved by day +100; however, this did not consistently indicate restoration of baseline community structure and was not paralleled by recovery of stool metabolite profiles. Accordingly, RECOVERY status showed a limited association with survival or transplant-related mortality (TRM). In contrast, IMM-RI post-TX low-risk identified patients with preserved butyrate-associated biosynthetic capacity and was significantly associated with improved OS in both cohorts (UKR: HR 0.2052, 95% CI 0.07703 - 0.5466, p < 0.0001). In the validation cohort, IMM-RI post-TX low-risk was significantly associated with reduced relapse-related mortality. Interestingly, stool butyric-, propionic and valeric acid concentrations were increased in cGvHD of the skin, indicating context-dependent metabolite effects. These findings suggest that metabolite profiling outperforms bacterial diversity for predicting outcomes after allo-SCT and support microbial metabolites as promising biomarkers for risk stratification and actionable candidates for precision microbiome interventions after allo-SCT.

Background: Primary graft dysfunction (PGD) remains one of the leading causes of early mortality after pediatric heart transplant (HT). While neurodevelopmental impacts of congenital heart disease (CHD) are well-characterized, the effect of PGD on long-term neurodevelopmental outcomes in pediatric HT recipients remains unknown. We sought to determine the association between PGD and neurodevelopmental outcomes in this population. Methods: We performed a retrospective cohort study using the United Network for Organ Sharing (UNOS) database. All pediatric (age <18 years) isolated heart transplant recipients from 2010-2025 were included. The most recent pre- and post-transplant neurodevelopmental outcomes including cognitive delay, motor development, academic progress, and function status (stratified by age) were compared between PGD (n=434) and non- PGD groups (n=6956). Results: PGD patients had significantly worse pre-transplant functional status and motor development. Post-transplant, PGD was associated with worse motor development (18.8% vs. 13.0% definite motor delay; p=0.01) and functional status in younger children (39.5% vs. 57.8% able to keep up with peers; p<0.001). Post-transplant stroke occurred 3.5 times more frequently in PGD patients (11.5% vs. 3.3%; p<0.001). Cognitive development (p=0.94) and academic progress (p=0.096) did not differ significantly. Thirty-day (7.8% vs. 1.9%) and 1-year mortality (20.3% vs. 6.4%) were significantly higher in PGD patients (both p<0.001). Conclusions: This is the first study to characterize neurodevelopmental outcomes in pediatric patients undergoing HT with PGD. PGD is associated with significantly worse motor development and functional status independent of pre-transplant baseline. There is a 3.5-fold higher stroke rate providing a plausible neurological mechanism. The findings support targeted developmental surveillance recommendations and early intervention for this high-risk population.

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

BackgroundThe success of hematopoietic stem cell transplantation (HSCT) depends critically on human leukocyte antigen (HLA) matching between donor and recipient. While traditional matching focuses on five classical HLA loci (A, B, C, DRB1, DQB1), clinical practice increasingly considers extended typing at nine loci, including DPA1, DQA1, DPB1, and DRB3/4/5. Furthermore, emerging evidence supports transplantation with up to three HLA mismatches under post-transplant cyclophosphamide (PTCy) regimens. However, current donor search algorithms cannot efficiently identify donors with multiple mismatches across extended HLA loci in real-time. MethodsWe developed GRIMM-II (GRaph IMputation and Matching, version II), which comprises two novel algorithms: ML-GRIM (Multi-Locus GRIM) for HLA imputation across multiple loci, and ML-GRMA (Multi-Locus GRMA) for real-time donor-patient matching with up to three mismatches. Both algorithms employ a two-stage approach that combines efficient candidate reduction through graph-theoretic frameworks with detailed genotype comparison. ML-GRIM partitions genotypes into class I (HLA-A, B, C) and class II (remaining loci) components, enabling memory-efficient storage and rapid candidate identification. ML-GRMA searches a pre-imputed donor graph composed of donor genotypes and their sub-components, then computes asymmetric graft-versus-host (GvH) and host-versus-graft (HvG) mismatch probabilities to provide clinically relevant compatibility assessments. Both imputation and matching tools are available as a web application at https://grimmard.math.biu.ac.il/ and through GitHub repositories at https://github.com/nmdp-bioinformatics/py-graph-imputation (imputation) and https://github.com/nmdp-bioinformatics/py-graph-match (matching). ResultsWe validated ML-GRMA and ML-GRIM using the WMDA3 (World Marrow Donor Association) validation dataset, successfully reproducing all previously reported matches while identifying numerous additional candidate donors not detected by previous algorithms. Further validation of ML-GRMA using 3,000 patients with artificially introduced mismatches (0-3 allele substitutions) demonstrated 100% sensitivity and specificity in identifying matching donors at expected mismatch levels. We validated ML-GRIM using simulated nine-locus typings derived from 8,078,224 US donors in the NMDP registry. The algorithm successfully imputed genotypes across variable numbers of typed loci while incorporating multiethnic haplotype frequencies. The algorithm achieved real-time performance with typical imputation times under one second and matching times of 1-13 seconds per patient for up to three mismatches, even when searching databases exceeding 8 million donors. Notably, ML-GRMA identified substantially more potentially suitable donors than traditional algorithms by accounting for the biological reality that GvH and HvG mismatches often differ, particularly for donors homozygous at specific loci. To evaluate ML-GRIM performance with low-resolution typing, we tested it on simulated 3-locus typings from the same population. The resulting imputation accuracy correlated with the mutual information between typed loci and complete genotypes. ConclusionsGRIMM-II provides a scalable, memory-efficient solution for nine-locus HLA imputation and real-time identification of donors with up to three mismatches. The graph-based framework supports dynamic registry updates and can readily accommodate additional HLA loci and matching criteria as clinical knowledge evolves. By expanding the pool of acceptable donors while maintaining computational efficiency, GRIMM-II addresses a critical need in contemporary transplantation practice, particularly for patients from underrepresented ethnic minorities who face lower probabilities of finding perfectly matched donors.

Introduction: Podocyte injury is central to the pathogenesis of most glomerulonephritides (GN) and causes segmental glomerulosclerotic lesions that predict progression in IgA Nephropathy (IgAN). Recent advances in high-resolution microscopy and AI-assisted image analysis have enabled detailed quantification of podocyte foot process (FP) morphology. However, whether nanoscale podocyte morphometrics can predict disease progression or treatment response in GN has not been investigated. Aim: To evaluate whether nanoscale podocyte morphometric parameters predict clinical characteristics, disease progression, and treatment response in GN, with a focus on IgAN. Method: Podocyte morphometrics were analyzed in kidney biopsies from patients with GN using high-resolution microscopy and the deep learning-based tool Automatic Morphometric Analysis of Podocytes (AMAP). Four morphometric parameters were quantified: slit diaphragm length (SDL), FP area, FP circularity and FP perimeter. These parameters were correlated with clinical characteristics, conventional electron microscopy (EM) findings and longitudinal follow-up data. Results: The study included 37 patients with GN from Danderyd University Hospital (Stockholm, Sweden), with IgAN representing the largest diagnostic subgroup (n = 19). The median follow-up for the cohort was 3.0 years. SDL correlated significantly with urine albumin-to-creatinine ratio (uACR; p = 0.021), whereas conventional EM measurements did not (p = 0.22). Within the IgAN subgroup, lower SDL was associated with a steeper decline in eGFR, higher FP area with increased long-term proteinuria, and higher FP circularity with improvement in uACR during the first year. The association between lower SDL and eGFR decline remained as a trend in IgAN patients not treated with corticosteroids (p = 0.068) but was absent in the treatment group (p = 0.59). Conclusion: In this proof-of-concept study, nanoscale podocyte morphometrics demonstrated greater sensitivity than conventional EM in quantifying podocyte injury and predicting progression in IgAN. These findings suggest that high-resolution morphometrics may improve risk stratification in IgAN but require validation in larger, independent cohorts before clinical implementation.

Vaccine adjuvants are critical for enhancing immune responses and sustaining antibody production. Although their safety profiles are well established, assessments have largely focused on metabolic and excretory organs such as the liver and kidneys, with limited attention to the heart. Here, we systematically evaluated the cardiac effects of five representative adjuvants in mice: alum, MF59, AS03, Sigma Adjuvant Systems, and lipid A. None of the adjuvants impaired baseline cardiac contractile function. Notably, lipid A uniquely enhanced mitochondrial respiratory capacity in rat and human induced pluripotent stem cell-derived cardiomyocytes and promoted mitochondrial membrane hyperpolarization. We next examined its therapeutic potential in a doxorubicin (Dox)-induced heart failure model characterized by mitochondrial dysfunction. Co-administration of lipid A with influenza hemagglutinin (HA) antigen significantly ameliorated cardiac dysfunction. In parallel, lipid A prevented the Dox-induced decline in anti-HA antibody titers, an effect associated with preservation of splenic B cell populations. Collectively, these findings reveal a previously unappreciated cytoprotective dimension of lipid A, demonstrating that it not only potentiates immune responses but also counteracts chemotherapy-induced functional decline by enhancing mitochondrial activity.

BackgroundKidney cell lines are widely used to model kidney physiology and disease; however, their gene expression profiles may differ from primary cells due to immortalization, culture conditions, or experimental treatments. Determining whether a cell line resembles its native cell type is critical for interpreting in vitro findings. We developed a transcriptome-based approach that matches bulk RNA-seq data from kidney cell lines, primary cells, or tissues to reference cell types derived from single-cell RNA-seq (scRNA-seq) datasets. MethodsReference transcriptomic profiles were generated from two human and two murine kidney scRNA-seq datasets by pseudobulk aggregation. Bulk RNA-seq data from microdissected kidney tissue, non-kidney negative controls, and kidney cell lines were matched to these references using three statistical similarity measures (Spearman correlation, Euclidean distance, Poisson distance) and three machine learning classifiers (Random Forest, XGBoost, TabPFN). Each was assessed with global gene expression, curated kidney marker gene lists, and the most variable genes. Matching accuracy was evaluated through a three-step validation strategy: within-dataset matching, cross-reference comparison, and validation against primary kidney tissue and negative controls. ResultsGene expression rank-based Spearman correlation and TabPFN, a foundation model for tabular data, emerged as the most accurate and specific approaches, particularly with curated kidney marker gene lists. Both methods correctly identified microdissected kidney tubule segments and were robust against non-kidney negative controls. Applied to commonly used kidney cell lines, OK cells retained proximal tubule identity, particularly under shear stress, while other proximal tubule lines (HK-2, HKC-8, HKC-11) showed inconsistent matching. Collecting duct-derived mIMCD-3 maintained stable similarity across passages, culture conditions, and genetic modifications. ConclusionWe provide two complementary implementations: CellMatchR, an accessible web-based tool using Spearman correlation for routine use, and comprehensive scripts for TabPFN-based matching (link will be added after peer reviewed publication). Together, these resources enable researchers to make informed decisions about kidney cell culture model selection, interpretation, and stability. Translational StatementKidney cell lines are fundamental tools in nephrology research, yet their transcriptomic similarity to native cell types is rarely validated systematically. We demonstrate that combining bulk RNA-seq data with single-cell reference datasets enables robust assessment of cell line identity using gene expression-rank-based correlation and machine learning approaches. By providing a comprehensive evaluation of matching methods, curated kidney marker gene lists, and reference datasets, our study serves as both a practical resource and a methodological framework for the kidney research community, facilitating informed selection of cell culture models, quality control of experimental conditions, developing new experimental cell culture models, and more reliable translation of in vitro findings to kidney physiology and disease.

Background: Patients with kidney failure undergoing maintenance hemodialysis suffer high rates of major adverse cardiovascular events(MACE) that are not accurately predicted by traditional cardiovascular risk models. There is an urgent need to identify novel, modifiable cardiovascular risk factors for these patients. Methods: We analyzed associations of 6287 circulating proteins with MACE among 1048 participants undergoing hemodialysis in the Chronic Renal Insufficiency Cohort(CRIC) (14-year follow-up) with validation in the Predictors of Arrhythmic and Cardiovascular Risk in End-Stage Renal Disease study(PACE) (7-year follow-up). In both cohorts, proteins were measured shortly after dialysis initiation and one year later. We compared protein-based risk models derived by elastic net regression to the Pooled Cohort Equations(PCE) optimized for these cohorts(Refit PCE), and to an Expanded Refit PCE that included Troponin T and N-terminal pro-B-type natriuretic peptide. Results: In CRIC, 149 proteins were associated with MACE at false discovery rate<0.05. Among 22 proteins significant at Bonferroni p<8x10-6, proteins that validated in PACE included Sushi von Willebrand factor type A EGF and pentraxin domain-containing protein 1(SVEP1), Complement component C7, R-spondin 4, Tenascin, Fibulin-3 and Fibulin-5. Complement pathways were prominent in network analyses. SVEP1 surpassed other markers by statistical significance, with CRIC HR per log2 1.8 (p=2.1x10-12) and HR per annual doubling 1.6 (p=6.8x10-6). For 2-year MACE, AUC(95%CI) for SVEP1 alone was 0.72(0.59, 0.84) in CRIC, and 0.73(0.63, 0.81) in PACE. SVEP1 surpassed the Expanded Refit PCE in CRIC (0.61 (0.48, 0.73)) (p=0.038). In the pooled CRIC + PACE cohort, SVEP1 AUC(95%CI) (0.79(0.70, 0.88)) surpassed Refit PCE (0.61(0.51, 0.72)) (p=0.004). Conclusions: SVEP1, a 390 kDa protein unlikely to be renally cleared, surpassed over 6000 other proteins and by itself outperformed traditional clinical risk models in predicting MACE in two populations of patients undergoing maintenance hemodialysis. Future studies should provide mechanistic insights behind these findings.

Background Cardiac MRI (CMR) is often utilized for patients with suspected cardiac amyloidosis (CA). However, data are lacking for use in patients with advanced renal dysfunction (ARD) (GFR<30 mL/min/1.73 m2, dialysis dependent, or renal transplant). This study evaluates the utility of CMR for diagnosis of CA in this population. Methods Patients with ARD who underwent CMR in a 3T field for suspicion of CA between 2010 and 2024 at our institution were included. A diagnosis of CA was made if any of the following were present a)?PYP scintigraphy grade ? 2, b) positive endomyocardial biopsy, or c) positive extracardiac biopsy with clinical features of CA. Two CMR-trained physicians independently assessed T1 relaxation time, ECV, Ti scout, LGE, and overall likelihood of CA. Results Out of the 65 patients included 14 (22%) had a diagnosis of CA. Although T1 time [1352 (1276-1428) ms] and ECV (40.3% +/- 9.1%) were elevated across the cohort, they were significantly higher in patients with CA (p<0.001 for both). Both ECV and T1 time reliably predicted CA (AUC of 0.87 and 0.88 respectively). ECV of ?45% had 75% sensitivity and 80% specificity for CA. A T1 time ? 1390 ms had 75% sensitivity and 85% specificity for CA. LGE was prevalent and was seen in 86% and 84% patients with and without CA respectively. Of the 31 patients deemed to be unlikely CA by a CMR reader, 6% had CA. However, of the 34 patients read as possible/likely CA, only 35% had confirmed CA. Conclusions In this understudied population of ARD, CMR parametric mapping exhibits high negative predictive value (NPV) for CA and improved positive predictive value (PPV) when higher cutoffs are used for T1 time and ECV. CMR reader overall impression exhibits high NPV but low PPV for CA.

Background: Single-nephron glomerular filtration rate (GFR) represents a nephron-level functional index that may reveal key pathophysiological mechanisms driving progression in patients with diabetic nephropathy. However, its clinical relevance remains incompletely understood. This cross-sectional study assessed single-nephron estimated GFR (eGFR) across different chronic kidney disease (CKD) stages in patients with advanced diabetic nephropathy. Methods: Nephron number was estimated as the number of nonglobally sclerotic glomeruli per kidney using computed tomography-derived cortical volume combined with biopsy stereology. Single-nephron eGFR was calculated by dividing eGFR by the nephron number of both kidneys. Patients were stratified according to CKD stage at kidney biopsy. Associations between CKD stages and single-nephron eGFR were evaluated using multivariable linear regression models adjusted for age, sex, urinary protein excretion, and eGFR. Results: The study included 105 patients with biopsy-proven diabetic nephropathy and overt proteinuria (median age 59 years, 83% male, HbA1c 6.6%, 57% had nephrotic range proteinuria). The percentage of globally sclerotic glomeruli, mesangial expansion score, and prevalence of nodular lesions increased significantly with advancing CKD stage. Median nephron number declined from 529,178 to 224,458 per kidney, whereas glomerular volume remained constant. Single-nephron eGFR decreased markedly with CKD stage and remained significantly inversely associated with CKD stage after adjustment for clinicopathologic covariates (P for trend <0.001). Conclusion: In overt diabetic nephropathy, single-nephron eGFR decreased with advancing CKD stage, despite relatively preserved glomerular volume. At this stage of disease, structural alterations specific to diabetic nephropathy may impair effective single-nephron filtration capacity.

Abstract Background: Despite widespread adoption of contemporary guideline-directed medical therapy (GDMT), patients with heart failure with reduced ejection fraction (HFrEF) continue to experience substantial residual morbidity and mortality. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have demonstrated cardiometabolic benefits in diabetes and obesity, but their role in HFrEF remains uncertain. Objectives: To evaluate whether the addition of GLP-1RAs to optimized GDMT is associated with improved clinical outcomes in patients with HFrEF (NYHA class II-IV). Methods: We conducted a retrospective, multicenter cohort study using the TriNetX Research Network. Adults ([&ge;]18 years) with HFrEF (LVEF [&le;]40%) receiving GDMT between January 2020 and October 2024 were included. Patients treated with GLP-1RAs were compared with those on GDMT alone. After 1:1 propensity score matching, 1,518 patients were included in each cohort. Outcomes over 2 years included all-cause mortality, major adverse cardiovascular events (MACE), critical care utilization, and acute kidney failure. Time-to-event analyses were performed using Kaplan-Meier methods and Cox proportional hazards models. Results: In the matched cohort (mean age [~]63 years, [~]33% female), GLP-1RA use was associated with significantly lower all-cause mortality compared with GDMT alone (12.8% vs 23.8%; hazard ratio [HR] 0.48; 95% CI 0.40-0.57; p<0.001), corresponding to an absolute risk reduction of 11.0%. MACE was also reduced (35.8% vs 47.4%; HR 0.64; 95% CI 0.58-0.72; p<0.001). Additionally, GLP-1RA therapy was associated with lower critical care utilization (18.4% vs 28.9%; HR 0.55; 95% CI 0.47-0.64; p<0.001) and reduced acute kidney failure (29.2% vs 37.3%; HR 0.67; 95% CI 0.59-0.76; p<0.001). Rates of pancreatitis and substance-related disorders were low and not significantly different between groups. Conclusions: Among patients with HFrEF receiving contemporary GDMT, adjunctive GLP-1RA therapy was associated with significant reductions in mortality, cardiovascular events, and healthcare utilization. These findings support the potential role of GLP-1RAs as a novel, mechanism-complementary therapy in HFrEF. Prospective randomized trials are needed to confirm these observations and determine whether GLP-1RAs should be incorporated as a fifth pillar of GDMT.

Background: Coronary artery bypass grafting (CABG) to physiologically non-significant coronary artery stenosis may result in graft failure due to competitive native flow. We evaluated whether an instantaneous wave-free ratio (iFR)-guided revascularization strategy improves graft patency and clinical outcomes compared to conventional angiography-guided CABG. Methods: In this prospective, randomized, single-blinded trial, patients with multivessel disease and at least one angiographically intermediate stenosis (50%-75%) were randomized to either CABG guided by angiography alone or angiography supplemented with iFR assessment groups. The primary endpoint was graft patency (occlusion or hypoperfusion of the graft) evaluated by coronary computed tomography angiography (CCTA) at 2, 12, and 36 months. Results: At 36 months, 78% of the patients completed follow-up. Left internal mammary artery (LIMA)-to-left anterior descending (LAD) artery graft patency was significantly higher in the iFR-guided group than in the angiography-guided group (80.5% vs. 56.8%; absolute risk difference, 23.7% [95% CI, 3.7%-43.8%]; RR, 1.42 [95% CI, 1.03-1.95]; P = 0.03). Saphenous vein graft patency also improved with iFR guidance (90.2% vs. 70.3%; P = 0.046). Major adverse cardiac and cerebrovascular events (MACCE) were similar between groups (28% vs. 20%; RR, 1.40 [95% CI, 0.69-2.85]; P = 0.48). Conclusions: iFR-guided CABG advocates significantly improved mid-term graft patency compared with angiography-guided CABG by optimizing surgical target selection and reducing competitive flow.

Myeloproliferative neoplasms (MPNs) are characterized by progressive myelofibrosis that drives morbidity and mortality. Liquid biopsy approaches to noninvasively monitor fibrotic progression remain limited. We performed comparative transcriptomic profiling of CD45-depleted platelet-enriched and CD45+ leukocyte-enriched fractions from matched peripheral blood samples of 76 individuals (27 primary myelofibrosis, 17 polycythemia vera, 14 essential thrombocythemia, 18 healthy controls). Platelet RNA sequencing was performed in 2018-2020 on Illumina HiSeq 4000, while WBC RNA sequencing was conducted in 2023 on Illumina NovaSeq 6000 from cryopreserved CD45+ enriched fractions of specimens obtained at the identical time and from the same blood sample as the platelet RNA. Despite comparable library preparation protocols and higher sequencing depth in WBC samples, platelet transcriptomes exhibited 5.1-fold more differential expression in myelofibrosis (3,453 versus 681 genes, adjusted p<0.05, |log2FC|>1). Platelet signatures were enriched for proteostasis pathways including endoplasmic reticulum stress and unfolded protein response, reflecting megakaryocyte dysfunction in the fibrotic bone marrow niche. WBC signatures predominantly featured immune activation and proliferative pathways, indicating systemic inflammatory responses. Multinomial LASSO classification demonstrated superior performance of platelet-based models for myelofibrosis diagnosis (AUROC 0.85) compared to WBC-based (AUROC 0.77) or clinical models (AUROC 0.59). Combined platelet+WBC models did not improve performance (AUROC 0.80), indicating complementary but non-additive information. These findings establish platelet transcriptomic profiling as a superior noninvasive biomarker platform for monitoring myelofibrosis in MPNs, capturing megakaryocyte-driven fibrogenesis with greater sensitivity than peripheral leukocyte-based approaches. HighlightsUsing matched WBC and platelet RNA-seq from MPN patients, we identify myelofibrosis-associated transcriptomic signatures specifically enriched in platelets. Multinomial LASSO modeling highlights platelet-derived gene expression as a dominant and predictive biomarker of myelofibrosis, outperforming clinical parameters and WBC signatures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/714941v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d695aborg.highwire.dtl.DTLVardef@fc250forg.highwire.dtl.DTLVardef@1e52e8eorg.highwire.dtl.DTLVardef@15378e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

Cancer remains a major therapeutic challenge despite substantial advances in diagnosis and treatment, including immune checkpoint blockade. Among emerging immunotherapeutic approaches, adoptive cell transfer (ACT) has attracted growing interest. Human peripheral V{gamma}9V{delta}2 T cells are promising candidates for ACT because they combine rapid and potent antitumor functions with major histocompatibility complex (MHC)-independent tumor recognition, enabling allogeneic use with limited risk of graft-versus-host disease. This raises the possibility of generating standardized V{gamma}9V{delta}2 T-cell banks from healthy donors for off-the-shelf immunotherapy. Here, we provide preclinical evidence supporting the suitability of allogeneic human V{gamma}9V{delta}2 T cells for ACT. We characterized peripheral blood V{gamma}9V{delta}2 T cells from healthy donors after successive antigen-specific and non-specific amplification steps, assessing their phenotype, effector functions, and metabolic state. Amplified cells maintained a strong pro-inflammatory Th1-like profile, preserved cytotoxic activity, and did not produce immunoregulatory cytokines. They also displayed high purity, a predominant effector memory phenotype, reduced expression of several inhibitory immune checkpoints, and sustained antitumor reactivity. Altogether, these findings support the development of allogeneic V{gamma}9V{delta}2 T-cell products as a scalable platform for next-generation cancer immunotherapies.

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

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

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

PurposeClinical translation of CAR T cell therapies has accelerated, yet preclinical evidence still often originates from single-center studies lacking sufficient robustness. Preclinical confirmatory multicenter studies have been proposed to improve the translational success, but their feasibility in cellular therapies remains unexplored. MethodsWe performed a confirmatory multicenter study validating C-C-motive-receptor-8 (CCR8) overexpression in CAR T cells--a strategy previously shown to enhance solid tumor infiltration. In vitro experiments covering activation, cytotoxicity, and migration using three CAR constructs were conducted across two centers with harmonized materials, preregistered protocols, randomization, and blinding. ResultsThe data from the two centers confirmed key findings of the exploratory study: CCR8 overexpression in anti-EpCAM and anti-mesothelin CAR T cells leads to enhanced selective migration towards a CCL1-gradient, while not compromising antigen-specific T cell activatory capacity and cytotoxicity in vitro. The study furthermore broadened the applicability of CCR8 overexpression to anti-CEA CAR T cells. ConclusionsThis first-of-its-kind preclinical confirmatory CAR T study demonstrates the feasibility of a multicenter confirmation in cellular therapy, with technical and logistical challenges resolved through transparent communication between all parties involved. Both exploratory and confirmatory studies aim to downselect CAR candidates with the highest clinical success potential, as they compete for limited resources in preclinical research. It is therefore mandatory to clarify the extent of replications required to validate the experimental methodology and identify CAR candidates with most likelihood of success. TRANSLATIONAL RELEVANCEPreclinical evidence for novel CAR T cell therapeutic strategies relies mostly on exploratory single-center studies lacking robustness, with recent findings substantiating their limited predictive value for cellular therapies tested outside hematology. Here, the function of CCR8-armored CARs in vitro was confirmed in a preclinical confirmatory multicenter study, demonstrating the feasibility of such studies in adding value to the transition of preclinical concepts to clinical development. Our first-of-its-kind study may contribute to define new routes for preclinical testing and further raises the general question of what level of preclinical evidence is reasonably achievable in an academic context. It indicates the need for strong collaborative efforts to realize dedicated preclinical infrastructure for clinical translation of reprogrammed immune cellular therapeutics.