Kidney International

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

Background: Microvascular dysfunction contributes to chronic kidney disease (CKD), but reproducible clinical measures are limited. Laser Doppler flowmetry (LDF) provides a noninvasive assessment of cutaneous microvascular blood flow and may reflect systemic microvascular health. Its relationship with kidney function and histopathology in CKD remains unclear. Methods: We assessed cutaneous microvascular function in 150 participants with CKD (eGFR <90 mL/min/1.73 m2) using a standardized forearm LDF protocol. Baseline perfusion was recorded at ~30{degrees}C, followed by local heating to 44{degrees}C to induce hyperemia. Percent change in perfusion units (PU) defined microvascular functional reserve. Associations of LDF measures with eGFR and urine protein-to-creatinine ratio (uPCR) were evaluated using multivariable linear regression. K-means clustering identified microvascular phenotypes. In a subset (n=20), associations with glomerulosclerosis (GS) and interstitial fibrosis/tubular atrophy (IFTA) were examined. Results: The mean (SD) age was 64 (14) years, 46% were female. The mean eGFR was 42 (21) mL/min/1.73m2 and median uPCR was 0.21 (interquartile range (IQR) 0.11 to 1.20) mg/mg. Higher baseline PU ({beta} = -12; 95% CI, -24 to -1) and reduced percentage change in PU ({beta} = 7; 95% CI, 2 to 13) were associated with lower eGFR, independent of covariates. Neither measure was associated with uPCR. Clustering identified four phenotypes with graded differences in perfusion and reserve. In biopsy participants, higher baseline PU and lower percent change were associated with greater GS and IFTA severity. Conclusion: CKD is characterized by elevated resting perfusion and impaired microvascular reserve, which are associated with lower eGFR and histopathologic injury.

Background: 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.

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract that encompasses ulcerative colitis and Crohns disease. Here we identify the cystine/glutamate antiporter xCT as being markedly upregulated in the inflamed intestinal epithelium of patients with IBD. To clarify its functional contribution to disease pathogenesis, we performed genetic loss-of-function study and found that inhibition of xCT confers robust protection against dextran sulfate sodium (DSS)-induced colitis in mice. Intestinal epithelial cell (IEC)-specific deletion of xCT markedly attenuated colitis severity, demonstrating that epithelial xCT upregulation acts as a disease-exacerbating factor in IBD. Mechanistically, xCT deficiency preserved intracellular glutamate levels and protein polyglutamylation, thereby maintaining epithelial barrier integrity and protecting IECs from inflammatory injury. Consistently, pharmacological inhibition of glutamine synthetase, which increases intracellular glutamate, exerted a potent anti-inflammatory effect on the DSS-induced colitis. These findings identify intracellular glutamate retention in IECs as a previously unrecognized mechanism of epithelial protection and highlight both inhibition of xCT-dependent glutamate efflux and suppression of glutamine synthetase as potential therapeutic strategies for IBD.

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.

BackgroundLife-sustaining hemodialysis (HD) is onerous for patients, especially those with multiple co-morbidities and advanced age. A standard HD prescription is 720 minutes per week. Alternative HD regiments have been proposed in attempt to maintain quality of life (QOL). Studies are needed to investigate the efficacy and safety of less frequent HD prescriptions in this population. This is an institution-wide observational study in New Brunswick, Canada to compare HD prescriptions and the impact on QOL and mortality. ObjectiveThe purpose of this study is to assess the current HD prescribing practices at a provincial healthcare institution in relation to patient QOL. DesignProspective Observational Study. SettingSingle centre hospital and satellite hemodialysis units. PatientsVoluntarily consented patients undergoing in-centre hemodialysis treatment. MeasurementsObservational clinical data was collected for each study participant from their hospital and dialysis electronic medical records. The KDQOL-36TM questionnaire was used to assess patient-reported quality of life at the time of consent. MethodsAdults undergoing in-centre or satellite site HD for at least 3 months were eligible to participate. Consenting patient participants were grouped by HD prescription whether they were prescribed 720 minutes or more per week or less than 720 minutes per week. All participants completed the KDQOL-36 TM questionnaire to estimate QOL and groups were compared using the Mann-Whitney U statistical test. Emergency department visits, hospitalizations, and mortality were analyzed using a negative binomial regression or a logistic regression. ResultsWe enrolled 140 patient participants; 41 were undergoing less than 720 minutes per week of HD and 99 were undergoing 720 minutes or more of HD per week. Patients who were undergoing less than 720 minutes per week of HD were older [Median (IQR): 76 (72- 81) yrs. vs. 64 (55 - 75) yrs.; p < 0.001], had higher median (IQR) QOL scores on the Symptoms/ Problems List scale on the KDQOL-36 TM questionnaire [79.2 (70.8 - 88.5 vs. 70.8 (62.5 - 81.3); p = 0.0022], and were less likely to present to the emergency department (incident rate ratio 0.52, 95% confidence interval [CI] 0.33-0.81). Mortality was similar between groups, even when adjusted for age and comorbidity score (odds ratio 1.62, 95% CI 0.59-4.49). LimitationsPatient participant enrollment was limited by the single centre nature of this study. As this was an observational study, we did not account for how long the patients had been prescribed less than 720 minutes of hemodialysis. We did not include a frailty assessment of the study participants. A higher number of study participants may have identified significant trends in mortality. ConclusionsThe results of this study show that patients undergoing less than 720 minutes of weekly HD had a higher QOL score for the KDQOL-36 TM Symptoms/ Problems List scale, were less frequently in the emergency department and were not more likely to die than patients undergoing 720 minutes or more of weekly HD. Further studies are required to assess the feasibility and safety of a conservative model of HD prescribing to improve QOL of patients with palliative care treatment goals.

PURPOSE: Bispecific antibodies (BsAbs) represent a major advancement in the management of relapsed/refractory multiple myeloma (RRMM), offering high response rates even in heavily pretreated patients. However, their use presents operational, safety, and supportive care complexities that require coordinated care teams, and evolving infrastructure. This manuscript summarizes best practice recommendations for adverse event (AE) management, outpatient operational models, referral pathways, and emerging strategies to optimize long-term tolerability. METHODS: Medlive, A PlatformQ Health Brand, conducted qualitative interviews of academic and community-based clinicians. Discussions focused on BsAb implementation, patient selection and counseling, and AE management. Experts provided recommendations on team-based protocols, transitions of care, and inpatient versus outpatient considerations. RESULTS: Ten hematologists/oncologists (academic n=4; community n=6) described practice patterns, barriers, and perspectives on BsAb use. BsAbs were consistently regarded as highly effective across multiple lines of therapy, particularly for patients without alternatives. Cytokine release syndrome (CRS) was the most common acute toxicity, generally low grade and managed effectively with early tocilizumab, including prophylactic use in outpatient settings. Immune effector cell-associated neurotoxicity syndrome (ICANS) was rare, mild, and best mitigated through early recognition and caregiver support. Infections, largely from BCMA-associated hypogammaglobulinemia, frequently interrupted therapy, necessitating antiviral prophylaxis, pneumocystis jirovecii pneumonia (PJP) prophylaxis, and intravenous immunoglobulin (IVIG). Outpatient step-up dosing is expanding, supported by prophylactic strategies and academic-community collaboration. Timely referral was emphasized to preserving eligibility. Major outpatient challenges included sequencing, infrastructure readiness, and standardized caregiver and staff education. CONCLUSION: Effective community implementation of BsAbs requires multidisciplinary coordination, standardized AE protocols, infection prevention, and infrastructure to support monitoring, referrals, and equitable access. These measures are critical to ensure safe, sustainable integration of bispecific therapies and to optimize patient outcomes.

Severe hemolysis is a life-threatening condition with limited therapeutic options. Although haptoglobin and hemopexin sequester hemoglobin and heme, these protective systems are rapidly saturated during acute hemolysis, leading to the accumulation of cytotoxic free heme. In this study, we identify scavenger receptor BI (SR-BI) as a critical mediator of free heme clearance. SR-BI binds heme and facilitates its hepatic uptake under pathological conditions. Mice lacking hepatic SR-BI exhibit impaired heme clearance and increased susceptibility to heme- and hemolysis-induced lethality. Pharmacological upregulation of hepatic SR-BI via imatinib or adenoviral delivery confers protection against heme toxicity. Using a humanized model of sickle cell disease (SCD), we further demonstrate that sickle hepatopathy significantly reduces hepatic SR-BI expression compared to non-SCD littermates, potentially increasing vulnerability to heme-induced injury. Notably, adenoviral-mediated SR-BI upregulation rescues SCD mice from heme toxicity. These findings reveal a previously unrecognized mechanism of heme detoxification via hepatic SR-BI and identify a promising therapeutic target for hemolytic disorders. One-Sentence SummaryIdentification of scavenger receptor BI as a targetable scavenger of heme in hemolysis

Background: Medical imaging, especially computed tomography and magnetic resonance imaging, is essential in clinical care of patients with renal cell carcinoma (RCC). Artificial intelligence (AI) research into computer-aided diagnosis, staging and treatment planning needs curated and annotated datasets. Across literature, The Cancer Genome Atlas (TCGA) datasets are widely used for model training and validation. However, re-annotation is often necessary due to limited access to public annotations, raising entry barriers and hindering comparison with prior work. Methods: We screened 1915 CT scans from three TCGA-RCC databases and employed a segmentation model to annotate kidney lesion. After a meta-data-based exclusion step, we hosted a reader study with all papillary (n=56), chromophobe (n=27) and 200 randomly selected clear cell RCC cases. Two students quality checked and corrected the data as well as annotated tumors and cysts. Uncertain cases were checked by a board-certified radiologist. Results: After data exclusion and quality control a total of 142 annotated CT scans from 101 patients (26 female, 75 male, mean age 56 years) remained. This includes 95 CTs with clear cell RCC, 29 with papillary RCC and 18 with chromophobe RCC. Images and voxel-level annotations of kidneys and lesions are open sourced at https://zenodo.org/records/19630298. Conclusion: By making the annotations open-source, we encourage accessible and reproducible AI research for renal cell carcinoma. We invite other researchers who have previously annotated any of these cohorts to share their annotations.

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

Super-resolution cryogenic correlative light and electron microscopy (SR-cryo-CLEM) integrates molecular specificity and structure on the single-molecule level, but contemporary approaches require low laser powers to preserve specimen vitrification. Here, we perform SR-cryo-CLEM via single molecule localization microscopy (SMLM) on thin biological lamellae and demonstrate that their geometry and minimally-absorbent composition permit excitation laser powers three orders of magnitude higher than standard cryo-EM grids, allowing improved localization precision and imaging speeds.

The spinocerebellar ataxias (SCAs) are a clinically heterogenous group of neurodegenerative disorders that affect movement, vision, speech and balance. Here, we reassign the linkage of SCA30 to 14q32.13 based on a cumulative LOD score >12. Within this interval we identified a 331 kb duplication, absent in population controls and not observed in >800 unrelated individuals with genetically unresolved cerebellar ataxia. RNASeq analysis of patient-derived lymphoblastoid cell lines revealed a splice-mediated chimeric transcript resulting from the duplication event. This transcript joined exon 1 of CLMN to exon 2 of SYNE3. In silico translation predicted that this chimeric transcript would produce a short N-terminal peptide corresponding to exon 1 of CLMN and the usually untranslated region of exon 2 of SYNE3 fused to the complete and in-frame SYNE3 protein. Transient overexpression of SYNE3 or the CLMN::SYNE3 fusion protein, in both HeLa cells and mouse primary cortical neurons, resulted in equivalent cellular outcomes including altered nuclear morphology and chromosomal DNA fragmentation. SYNE3 forms part of the linker of nucleoskeleton and cytoskeleton complex and is not usually expressed in cerebellar Purkyn[e] neurons while, CLMN has a Purkyn[e] specific expression pattern within the brain. Our data suggests that ectopic expression of SYNE3 in cerebellar Purkyn[e] neurons, mediated by the CLMN promoter, leads to cerebellar atrophy and causes spinocerebellar ataxia in the SCA30 family. This is an example of Mendelian disease arising from a novel, chimeric transcript with a likely dominant negative effect. Chimeric transcripts are commonly associated with cancers, but they are not often associated with monogenic disorders. Detection of chimeric transcripts as part of structural variant analysis could increase the genetic diagnostic yield of Mendelian disorders.

The transcription factor p63 is critical for epithelial development and implicated in tumorigenesis. However, our understanding of the role of p63 in development and disease has been complicated by its diverse isoforms. As a member of the p53 family member of genes, TP63 encodes for numerous isoforms, including the N-terminal variants TAp63 and {Delta}Np63, which are generated through alternative promoter usage. TAp63 and {Delta}Np63 share various structural domains, including the DNA-binding domain, and primarily differ in their N-terminus which consists of intrinsically disordered regions (IDRs). The isoforms are known to have different functions, including tumor suppression in the case of TAp63 and pro-tumor formation for {Delta}Np63, but how the N-terminus contributes to isoform-specific gene regulatory effects has yet to be elucidated. Using both genomic and TurboID proximity-labeling proteomic approaches, we show that the N-terminus mediates differential interactions with cofactors that have direct effects on isoform function, specifically the regulation of apoptosis. We find that the N-terminus of TAp63 interacts with more transcriptional machinery, leading to stronger transcriptional activity by TAp63 than {Delta}Np63. However, {Delta}Np63 maintains interactions with coactivators, suggesting it can retain some transactivation capabilities. Strikingly, the N-terminus of TAp63 displays enriched interactions with chromatin modifiers, including the histone acetyltransferase KAT2A, that result in TAp63-specific binding at inaccessible sites. We find that an IDR-mediated interaction with KAT2A is involved in regulation of apoptosis by TAp63. Collectively, our results suggest a model in which TAp63 and {Delta}Np63 broadly share genomic occupancy, but differential interactions with cofactors contribute to isoform-specific regulation by TAp63 and {Delta}Np63.

Background Group A streptococcus (GAS) infections have been associated with neuropsychiatric disorders in epidemiologic studies and animal models, but data in US health care populations are limited. GAS is also associated with autoimmune sequelae, including acute rheumatic fever (ARF)/Sydenham chorea (SC), poststreptococcal reactive arthritis (PSRA), poststreptococcal glomerulonephritis (PSGN), and guttate psoriasis (GP). Epstein-Barr virus (EBV) has been linked to systemic lupus erythematosus (SLE) and multiple sclerosis (MS) and the complexity of these associations parallels that of GAS-associated conditions, providing a useful comparison. Objectives 1) Assess the association between a positive GAS test and incident neuropsychiatric diagnoses within 1 year in a large US health care database. 2) Assess the validity of the same database in detecting well-established disease associations while avoiding false associations. Design, Setting, Participants Retrospective cohort study using TriNetX data from US health care organizations. Patients with positive or negative tests were propensity score-matched (GAS cohort n=178,301; EBV cohort n=64,854). Patients with documented neuropsychiatric diagnoses prior to testing were excluded. To approximate a primary care population, inclusion required at least one well-visit. Exposures Positive vs negative GAS test; positive vs negative EBV test (separate cohorts). Main Outcomes and Validations Main outcome: incident neuropsychiatric diagnoses within 1 year of GAS testing. Positive control outcomes: ARF/SC, PSRA, PSGN, and GP (for GAS cohort); SLE and MS (for EBV cohort). Negative control outcomes: conditions without known association with GAS. Results After matching, a positive GAS test was associated with attention-deficit/hyperactivity disorder (ADHD) (RR: 1.09; 95% CI: 1.03-1.15). Among established poststreptococcal conditions, only GP was associated with prior GAS (RR: 1.75; 95% CI: 1.06-2.89). Case counts were insufficient to evaluate ARF/SC, PSRA, and PSGN. Negative control outcomes showed no association. In the EBV cohort, no association was observed with SLE, and MS showed a decreased risk. Conclusions and Relevance A positive GAS test was associated with ADHD but not with other neuropsychiatric disorders. The database detected poststreptococcal GP but did not identify most established postinfectious autoimmune associations, likely reflecting rarity, heterogeneity, and diagnostic complexity. These findings begin to describe the range of real-world health care databases to evaluate postinfectious neuropsychiatric risk.

Abstract Background Spontaneous coronary artery dissection (SCAD) is a well-recognised cause of acute coronary syndrome particularly among women without conventional cardiovascular risk factors. Increasing evidence indicates a genetic contribution; however, the underlying genetic architecture of SCAD remains insufficiently understood. Objective The aim of this study was to assess the prevalence of rare variants in previously reported SCAD associated genes and to explore the potential presence of novel genetic alterations in well-characterised Swedish patients with SCAD. Methods The study comprised 201 patients enrolled in SweSCAD, a national project examining the clinical characteristics, aetiology, and outcomes of SCAD. All individuals had a confirmed diagnosis based on invasive coronary angiography. Comprehensive exome sequencing was performed to identify rare variants contributing to disease susceptibility. Results Genetic variants that have been associated with SCAD according to current clinical genetics practice for variant reporting were identified in approximately 4 % of patients. In addition, rare potentially relevant variants were detected in almost 60 % of patients in genes associated with vascular integrity and vascular remodelling. Conclusion This study supports SCAD as a genetically complex arteriopathy, driven by rare high?impact variants together with broader polygenic susceptibility. Variants in collagen, vascular extracellular matrix, and oestrogen?responsive pathways provide biologically plausible links to female?predominant disease. Although the diagnostic yield of clearly actionable variants is modest, these findings support broader genomic evaluation beyond overt syndromic presentations and highlight the need for larger integrative genomic and functional studies to refine risk stratification and management.

Chimeric antigen receptor (CAR) T cell therapy utilizes genetically engineered patient-derived T cells to target cancer cells. Despite its clinical successes in multiple cancer types, the underlying molecular mechanisms by which molecules on CAR-T cells and surrounding cells interact with other proteins and collectively determine treatment efficacy remain elusive. Most previous studies have relied on transcriptome profiling, which does not fully reflect protein-level organization and interactions. In this study, we developed an antibody-oligonucleotide conjugate targeting the FMC63 region of CAR and integrated it into molecular pixelation (MPX). This approach enabled profiling of the dynamics of CAR molecules on cell surfaces as well as their colocalization with other proteins at the single-cell level. By applying MPX to longitudinal samples from three patients undergoing CAR-T cell therapy, we characterized the dynamic changes in CAR-associated protein organization in both pre-infusion CAR products and post-infusion peripheral blood. While CAR protein abundance and polarization showed limited variation across clinical courses, remodeling of a CAR-centered co-localization network was observed over time, including different retentions of specific molecular associations between patients with different clinical outcomes. Although derived from a limited cohort, our study identifies insights from this methodological framework beyond those gained by conventional omics analyses and offers results of a systematic investigation to predict and enhance CAR therapeutic outcomes. Key pointsO_LIMolecular pixelation was applied for chimeric antigen receptor (CAR) profiling at single-molecule and single-cell resolutions. C_LIO_LIProtein and transcriptome analyses of the CAR molecule showed dynamic remodeling during CAR-T therapy in patients with non-Hodgkin lymphoma. C_LI

Background: Classification of central nervous system (CNS) tumors has become increasingly complex, raising concerns about the sustainability of comprehensive molecular diagnostics. We have evaluated nanopore whole genome sequencing (nWGS) as a single workflow to replace multiple diagnostic assays. Methods: We performed nWGS on DNA extracted from 90 adult CNS tumor samples (58 retrospective, 32 prospective) and compared the results to findings from standard of care (SoC) diagnostic work-up. Analysis was done through an automated workflow that consolidated diagnostically and therapeutically relevant genomic alterations, including copy-number variation, structural, and single-nucleotide variants, chromosomal aberrations, gene fusions, and methylation-based classification. Results: nWGS supported final diagnostic classification in all samples with >15% tumor cell content, requiring ~3 hours of hands-on library preparation, parallel sample processing, and sequencing times within 72 hours. Methylation-based classification was available within 1 hour and was concordant with the integrated final diagnosis in 89% of cases (80/90). All diagnostically relevant copy-number variations, single-nucleotide variants, and gene fusions were concordant with SoC testing. MGMT promoter methylation status matched in 94% of cases. In addition, nWGS identified prognostic and potentially actionable variants that were not reported or covered by SoC. Conclusions: nWGS delivers comprehensive genetic and epigenetic results with a fast turn-around compared to standard methods. This enables efficient, accurate, and scalable molecular diagnostics of CNS tumors using a single platform. This data supports its implementation in routine clinical practice and may be extended to other cancer types requiring complex genomic profiling.

Defects in RNA metabolism are a defining feature of neurodevelopmental disease, yet the contribution of RNA decay pathways to human brain development remains poorly understood. Notably, mutations in genes encoding ubiquitously expressed RNA surveillance machinery often cause highly tissue-selective disease, underscoring a central paradox in human biology. The RNA exosome is a conserved ribonuclease complex long considered a housekeeping machine for RNA turnover, yet recessive mutations in genes encoding structural subunits of the complex disproportionately cause neurological disease, suggesting an instructive role in nervous system development. Here, we show that the RNA exosome regulates the temporal progression of gene expression programs during human cerebellar differentiation. Using CRISPR-engineered human cerebellar organoids modeling EXOSC3 variants, we find that RNA exosome dysfunction does not broadly alter transcript abundance, but instead disrupts transitions between developmental states. Mutant organoids exhibit persistence of early transcriptional programs, impaired maturation of Purkinje and rhombic lip-derived lineages, and altered cellular composition. These defects are accompanied by disorganized laminar architecture and reduced coordination of neuronal activity, despite preserved intrinsic excitability. More broadly, our findings suggest that defects in RNA decay represent a general mechanism underlying neurodevelopmental disease. Together, this work establishes RNA surveillance as a key determinant of developmental timing, neural identity, and disease.

BackgroundExcessive accumulation of fibrillar collagen causes pathological scarring and fibrosis. A promising anti-fibrotic strategy targets the extracellular assembly of collagen fibrils rather than intracellular synthesis pathways. We previously developed a chimeric monoclonal antibody targeting the C-terminal telopeptide of the 2(I) chain of human collagen I that effectively disrupts fibrillogenesis. This study details the engineering of a humanized antibody variant optimized for therapeutic application, augmented with a collagen-binding peptide (CBP) to enhance targeted retention in fibrotic tissues. MethodsA humanized ACA was engineered by in silico homology modeling, complementarity-determining region grafting, and sequence optimization to eliminate chemical liabilities. Variants were expressed in mammalian cells and evaluated for binding kinetics and specificity. To improve spatial localization, the CBP was fused to the antibody. The lead variant was assessed for in vitro cytotoxicity, matrix retention, and in vivo efficacy using a rabbit model of post-traumatic knee arthrofibrosis. ResultsThe humanized ACA variants maintained high specificity and affinity for the 2Ct target domain. Fusing the CBP to the C-terminus of the light chain (C-cbpACA) successfully enhanced matrix retention without compromising target engagement or causing cellular toxicity. In the rabbit arthrofibrosis model, intra-articular C-cbpACA delivery significantly reduced flexion contracture and decreased total collagen deposition in the joint capsule compared to untreated controls. ConclusionWe successfully engineered a clinically viable, humanized, and matrix-targeted anti-fibrotic antibody that specifically inhibited extracellular collagen assembly and exhibited enhanced localization within fibrotic tissues. This construct represents a promising therapeutic strategy for mitigating pathological scarring and improving post-traumatic functional outcomes.

Background: Heart failure (HF) is a major and growing public health problem, and prior studies support a meaningful genetic contribution to HF susceptibility. Clinically, HF is commonly categorized into the major clinical sub-types of HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF), which differ in pathophysiology and clinical profiles. However, previous genome-wide association studies have focused on autosomal variation and have routinely excluded the X chromosome, leaving X-linked genetic contributions to HF and its subtypes under-characterized. Methods: We performed X-chromosome wide association study (XWAS) utilizing directly genotyped data from 590,568 Million Veteran Program participants, including 90,694 HF cases across European, African, Hispanic, and Asian Americans. Sex- and ancestry-stratified logistic regression was used with XWAS quality control measures, adjusting for age and population structure, followed by fixed-effects multi-ancestry meta-analysis. Functional annotation, gene-based testing, fine-mapping, and colocalization were performed. We replicated genetic associations with all-cause HF in the UK Biobank. Results: In the multi-ancestry meta-analysis, we identified five X-chromosome-wide significant loci for all-cause HF, five for HFrEF, and one locus for HFpEF in males. No loci reached significance in female-specific analyses. In sex-combined analyses, we identified six loci for all-cause HF and four for HFrEF. The strongest and most emphasized signals mapped to genes were BRWD3, FHL1, and CHRDL1. Ancestry-specific analyses revealed additional loci, including NDP and WDR44 in African ancestry and PHF8 in Hispanic ancestry. One locus, BRWD3, was replicated in UK Biobank HF cohort. Integrated post-GWAS analyses (fine-mapping, colocalization and pleiotropy trait association studies) reinforced the biological plausibility of the X-linked signals. Conclusions: This multi-ancestry, sex-stratified XWAS identifies X-linked genetic contributions to HF and its subtypes and highlights the role of X-chromosome in heart failure pathogenesis.