Journal of the American Society of Nephrology

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: 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.

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.

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.

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

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.

Cardiovascular disease (CVD) remains the leading cause of mortality in the United States, despite being largely preventable through effective management of risk factors. This study evaluates the impact of Phase II cardiac rehabilitation (CR) on functional capacity and quality of life, using data from the Montana Outcomes Project Cardiac Rehabilitation Registry. Functional capacity improvements were assessed via the six-minute walk test (6MWT) and Dartmouth COOP questionnaire, with statistical analyses exploring the influence of CR session attendance, demographic factors, and referring diagnoses. Results demonstrated significant gains in 6MWT, with a mean improvement of 330.73 feet (p < .0001), and quality of life scores across all subgroups. A dose-response relationship was observed, indicating greater improvements with increased CR sessions (p < .0001), though diminishing returns were observed beyond 24-35 visits. Demographic factors and complex conditions influenced outcomes, underscoring the need for tailored strategies to enhance CR access and effectiveness. These findings highlight the critical role of CR in improving patient outcomes and emphasize the importance of addressing barriers to participation in underserved populations.

BackgroundGenetic studies using cardiac magnetic resonance (CMR) imaging have identified loci related to cardiac shape, but most focus on static morphology. The value of a dynamic cardiac shape atlas capturing both shape and function remains unknown. MethodsA dynamic shape atlas comprising CMR-derived shape models at end-diastole and end-systole was combined with genetic and outcome data in 36,992 UK Biobank participants. Dynamic shape principal components (PCs) describing >1% of variance were characterized, and tested for associations with prevalent and incident cardiometabolic diseases, including ischemic heart disease (IHD), heart failure (HF), significant atrioventricular block (AVB), and atrial fibrillation (AF), and independent predictive power alongside standard CMR measures. Genome-wide association studies (GWAS) were performed to identify candidate genes and biological pathways, and polygenic risk scores (PRS) were assessed for disease associations. Mendelian randomization (MR) was performed to test causality of observed disease associations. ResultsWe identified 14 dynamic cardiac shape PCs capturing 83.3% of total dynamic cardiac shape variance. These PCs captured distinct functional remodeling patterns such as variation in annular plane systolic excursion, while remaining only modestly correlated with standard CMR measures. All 14 PCs were associated with at least one incident cardiometabolic disease, with the strongest associations observed for incident IHD, HF, and AVB. Notably, incorporating dynamic shape PCs improved the prediction of incident IHD beyond standard CMR measures. GWAS identified 75 genetic loci associated with dynamic shape, including 14 variants previously unreported for cardiac traits, and candidate genes demonstrated enrichment in pathways related to cardiac development and contractile function. PRS derived from dynamic shape loci were significantly associated with multiple outcomes, most prominently HF. MR identified significant causal relationships between several PCs and cardiometabolic disease. ConclusionsDynamic cardiac shape features capture aspects of cardiac structure and function not fully represented by standard CMR measures. These features are strongly associated with incident cardiometabolic disease and provide new insights into the genetic architecture of cardiac remodeling. Clinical perspectiveO_ST_ABSWhat is new?C_ST_ABSO_LIGenetic and outcome relationships with a dynamic statistical shape model capturing both left and right ventricles at end-diastole and end-systole. C_LIO_LIDemonstration of incremental value over existing cardiac shape models, through capture of functional remodeling not represented by standard imaging measures. C_LIO_LIIdentification of genetic susceptibility loci for dynamic cardiac shape, including 14 variants not previously reported for cardiac traits. C_LI What are the clinical implications?O_LIThe results enhance our understanding of the genetic architecture of dynamic cardiac shape and function in the general population and clarify their relationships with other cardiovascular endophenotypes and incident cardiometabolic diseases. C_LIO_LINewly identified candidate genes expand the biological pathways implicated in cardiac remodeling and provide targets for future functional and mechanistic studies. C_LIO_LIThe improved prediction of incident cardiometabolic disease, particularly ischemic heart disease, achieved by adding dynamic shape PCs to traditional CMR measures suggests potential value for their inclusion in evaluation of patients. C_LI

AimsCaveolae are plasmalemmal microdomains regulating stretch-dependent, nitric oxide (NO), and other signalling pathways governing myocardial structure, function and resilience. We have reported that global deletion of the scaffold protein cavin-1 disrupts caveolar biogenesis and impairs ventricular compliance and tolerance to ischaemic injury. However, cardiomyocyte-specific and sex-dependent roles of cavin-1 and caveolar complexes remain unresolved. Methods and ResultsWe generated a floxed Cavin-1 transgenic mouse, enabling cardiomyocyte-specific knockdown via adeno-associated virus (AAV) mediated expression of iCre recombinase driven by a cardiac-specific troponin T promoter. Knockdown was confirmed by RNA, protein, and immunofluorescence analyses, and cardiac function was assessed via echocardiography, left ventricular pressure-volume (PV) catheterisation, and ex vivo PV analysis of perfused hearts. Conditionally deleted hearts and myocytes exhibited up to 50% knockdown of Cavin-1 mRNA together with 15% deficiency in muscle-specific Caveolin-3, 70% depletion of caveolae, and mislocalisation of NO synthase (NOS) within cardiomyocytes. This was associated with elevated heart rate and shortened PR interval; reduced intraventricular and systolic blood pressures and peripheral resistance; and sex-dependent impairment of ventricular filling (females only). Diastolic dysfunction was detectable ex vivo, to a greater extent in male vs. female hearts. Mechanisms were sex-dependent, linked to interstitial fibrosis in females and NOS overactivity (inhibited by 100 {micro}M L-NAME) in males. Female hearts also exhibited increased susceptibility to ischaemia-reperfusion injury. Coronary function appeared preserved in both sexes, with intact reactive hyperaemic responses. ConclusionThis model identifies cardiomyocyte caveolae and cavin-1 as key determinants of myocardial function and compliance, involving sex-dependent remodelling and NOS signalling. By linking cardiomyocyte disruption to whole-organ and -body dysfunction, this model provides mechanistic insight into impaired function in heart failure and ageing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/717104v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1aabf7forg.highwire.dtl.DTLVardef@1026839org.highwire.dtl.DTLVardef@108ad11org.highwire.dtl.DTLVardef@9a6dfd_HPS_FORMAT_FIGEXP M_FIG C_FIG

Increased literature support the pathogenetic role of dysfunctional energetic metabolism in the setup and progression of organ damage and failure. Genetic diseases often offer the possibility to investigate pathogenetic mechanisms. In particular, excessive cardiac damage is the most frequent cause of mortality in Fabry disease (FD), a genetic condition caused by deficient -galactosidase A (GLA) activity, leading to globotriaosylceramide (Gb3) accumulation. Beyond Gb3 storage, metabolic alterations and mitochondrial dysfunction, supported by in vitro evidence or studies in other tissues, may contribute to FD cardiomyopathy. This study investigated, for the first time, the mechanisms of mitochondrial involvement in FD, its role in determining cardiac manifestations, and its potential as a therapeutic target. We used a humanized FD mouse model (R301Q-Tg/GLA knockout), along with derived embryonic fibroblasts and neonatal and adult cardiomyocytes, to assess mitochondrial function across the lifespan. FD cells showed impaired mitophagy, reduced mitochondrial respiration, and increased reactive oxygen species production. Importantly, this mitochondrial dysfunction exacerbated the lysosomal deficit in FD cells, forming a vicious cycle. In cardiomyocytes, these alterations progressed with age, leading to the accumulation of dysfunctional mitochondria, energetic failure, and, in adult hearts, terminal mitochondrial damage and apoptosis. These events ultimately result in cardiac remodeling and dysfunction, including hypertrophy and diastolic impairment. Indeed, L-arginine supplementation, which promotes NO/PGC-1-dependent mitochondrial rescue, prevented the development of cardiac abnormalities in FD mice. Our findings identify early mitochondrial dysfunction as a key driver of FD cardiomyopathy and support mitochondrial targeting, including L-arginine supplementation, as a promising adjuvant therapeutic strategy. The mechanistic link between lysosomal dysfunction, altered mitochondrial turnover, and energetic collapse emerges as a key targetable pathway in organ damage, extending beyond FD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/718770v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@2a5c4borg.highwire.dtl.DTLVardef@1117767org.highwire.dtl.DTLVardef@1b634c5org.highwire.dtl.DTLVardef@1429b6c_HPS_FORMAT_FIGEXP M_FIG C_FIG Cardiac manifestations vs mitochondrial alterations in Fabry disease: the visible tip and the hidden base of the icebergCardiac manifestations in hR301Q Tg/KO mice become evident from 9 months of age. However, mitochondrial homeostasis is perturbed much earlier (neonatal to young stages), with impaired mitophagy, reduced mitochondrial respiration and membrane potential, increased ROS production and PGC-1 downregulation. At later stages, from 6 months of age, mitochondrial dysfunction progresses and begins to impact cellular energetics, as indicated by reduced ETC expression and the onset of energetic deficit (ATP reduction). The resulting energetic collapse, together with progressive mitochondrial leakage, leads to cardiomyocyte hypertrophy, apoptosis, and dysfunction, which become detectable from 9 months of age, when clinical signs emerge. These findings support a mechanistic model in which 1) lysosomal incompetence due to GLA deficit is the initiating event inducing impairment of mitophagy; 2) Unsuccessful mitophagy, induces downregulation of PGC-1a-dependent mitogenesis; 3) exhausted mitochondria accumulate, inducing energetic collapse (able to exacerbate lysosomal dysfunction and further perturb mitophagy in a vitious cycle); 4) ultimate mitochondrial leakage induces Cytochrome C release and apoptosis activation. This cascade of molecular events is responsible for clinical manifestations, and mitochondrial targeting prevents cardiac organ damage. Significance statementFabry disease is a rare genetic disorder in which cardiac complications are a major cause of death, yet underlying mechanisms remain unclear. Here, we identify mitochondrial dysfunction as an early pathogenic event associated with impaired mitophagy, whereby defective mitochondrial quality control both results from and exacerbates lysosomal dysfunction, creating a self-reinforcing cycle that drives disease progression. Using a humanized model, we demonstrate that mitochondrial dysfunction is a key determinant of cardiac phenotype in vivo, driving energetic failure, oxidative stress, and cardiac damage. Importantly, L-arginine treatment restores mitochondrial function and prevents cardiac abnormalities. Our findings define a broadly relevant pathogenic axis linking lysosomal dysfunction, mitophagy failure, and mitochondrial impairment, that lead to impaired energetic metabolism and consequent cardiac hypertrophy, independently from GB3 accumulation. The implications of our study go beyond Fabry disease and support the therapeutic targeting of cellular energy homeostasis to prevent and treat organ damage and failure in chronic diseases. IMPORTANTO_LIManuscripts submitted to Review Commons are peer reviewed in a journal-agnostic way. C_LIO_LIUpon transfer of the peer reviewed preprint to a journal, the referee reports will be available in full to the handling editor. C_LIO_LIThe identity of the referees will NOT be communicated to the authors unless the reviewers choose to sign their report. C_LIO_LIThe identity of the referee will be confidentially disclosed to any affiliate journals to which the manuscript is transferred. C_LI GUIDELINESO_LIFor reviewers: https://www.reviewcommons.org/reviewers C_LIO_LIFor authors: https://www.reviewcommons.org/authors C_LI CONTACTThe Review Commons office can be contacted directly at: office@reviewcommons.org

AbstractO_ST_ABSBackgroundC_ST_ABSLeft ventricular (LV) remodeling in chronic Chagas cardiomyopathy (CCC) is progressive, but whether population-level LV mass dynamics follow nonlinear patterns and whether the loss of dynamic complexity tracks mortality is unknown. MethodsFifty outpatients from SEARCH-Rio cohort were followed-up for 10 years. Serial echocardiography provided paired LV mass measurements fitted to the logistic equation x = {middle dot}x{middle dot}(1-{gamma}{middle dot}x). Lyapunov exponents (LE) were computed from consecutive inter-patient derivatives. A clinical risk score was developed using Firth penalized logistic regression with bootstrap validation (B = 1,000) and Cox-Firth sensitivity analysis. ResultsLV mass remodeling adjusted the logistic equation with = 3.91 {+/-} 0.18 and {gamma} = 1.27 {+/-} 0.06, which was compatible with dynamics near the complexity threshold ( {approx} 3.57). Survivors showed positive LE (+0.339 {+/-} 0.543), and nonsurvivors showed negative LE (-0.825 {+/-} 0.972; p = 0.015). The fixed-point equilibrium of {approx} 280 g was approached by 63 % of patients at follow-up (p = 0.0003), a pattern indistinguishable from regression to the mean in the present design. Firth regression identified EF < 51.7 % and maximum heart rate < 109 bpm as independent predictors (optimism-corrected AUC = 0.959); the derived score showed a monotonic mortality gradient accompanied by lower LE across strata (Spearman {rho} = -0.369, p = 0.004). ConclusionsThese exploratory findings are compatible with nonlinear LV mass remodeling in Chagas disease and the association between loss of dynamic complexity and mortality. Replication in larger cohorts, formal model comparisons, and prospective validation of the score are warranted. Nonstandard Abbreviations and AcronymsASE, American Society of Echocardiography; AUC, area under the receiver operating characteristic curve; CCC, chronic Chagas cardiomyopathy; CHF, congestive heart failure; CI, confidence interval; EF, ejection fraction; HRV, heart rate variability; IQR, interquartile range; IVS, interventricular septum; LA, left atrial; LAHB, left anterior hemiblock; LBBB, left bundle branch block; LE, Lyapunov exponent; LV, left ventricular; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; NSVT, nonsustained ventricular tachycardia; NYHA, New York Heart Association; OR, odds ratio; PSVT, paroxysmal supraventricular tachycardia; PVC, premature ventricular complex; PW, posterior wall; RBBB, right bundle branch block; ROC, receiver operating characteristic; SAECG, signal-averaged electrocardiogram; SD, standard deviation; SDNN, standard deviation of normal-to-normal intervals; SEM, standard error of the mean; SVE, supraventricular ectopy

Mutations in the spliceosomal gene PRPF8 are associated with a range of human diseases. Studies in mouse and zebrafish suggest that Prpf8 also has a developmental function. Here, using a Prpf8 mutant mouse line isolated from a chemical induced mutagenesis screen, we uncover a previously unrecognised and essential role for Prpf8 in heart development, consistent with the embryonic lethality observed in Prpf8N1531S homozygous mutants. Prpf8N1531S mutant embryos display severe defects in ventricular trabeculation and compact zone formation, accompanied by increased cardiomyocyte proliferation specifically in the compact zone. Mutant embryonic hearts also exhibit disrupted cellular organisation, altered cytoskeletal architecture and changes in extracellular matrix protein expression. Notably, these cardiac abnormalities were exacerbated in embryos exhibiting cardiac looping defects. Transcriptomic analysis identified multiple aberrantly spliced transcripts in Prpf8N1531S mutant embryos, among which the cardiac transcription factor Tead1 was selected as a key functional candidate due to it known role in cardiac ventricle wall developemnt. Tead1 mis-splicing generated an in-frame, lower molecular weight protein isoform, associated with reduced overall TEAD1 expression. The Tead1 mis-spliced isoform showed altered nuclear localisation and dysregulation of TEAD1-dependent gene network important for heart development, including known cardiac sarcomeric genes. In addition, we observed reduced levels of the intracellular domain of the NOTCH1 receptor (NICD1), indicating impaired Notch signalling.. These findings suggest that impaired TEAD1-dependent transcription and Notch signalling contribute to abnormal cardiac trabeculation and compact zone development, highlighting a critical role for Prpf8 in maintaining proper heart development through the regulation of cardiac transcription factor expression and associated signalling networks. This study offers new mechanistic insights into congenital heart diseases linked to spliceosomal gene mutations.

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.

IntroductionOver one billion people worldwide have hypertension. In Zimbabwe, prevalence is an estimated 38%, surpassing the global average of 34%, and >50% of hypertensives are undiagnosed. The Community BP groups (Com-BP) study examined whether community groups of people living with hypertension, provided with BP machines and led by trained Facilitators could improve awareness, screening and support for those diagnosed with hypertension, to help blood pressure (BP) control. We present findings from the quantitative evaluation of the Com-BP pilot intervention. MethodsThe acceptability of the Com-BP intervention, its potential effectiveness in improving knowledge, attitudes and practices (KAP) and in reducing BP among hypertensive adults in Zimbabwe, was evaluated. Cross-sectional surveys using standardised questionnaires, and BP and Body Mass Index (BMI) assessments, were done at the start and end of the pilot intervention. Statistical evidence of difference between baseline and follow-up was examined using Wilcoxon signed-rank test for continuous data and McNemars test for categorical data. ResultsFourteen groups (seven urban and seven rural) were formed and 151 participants joined over a median of 5months. Retention in the groups was 97.9% (137/140 recruited at baseline), with approximately equal numbers from the urban and rural sites. Median age at baseline was 54 years (IQR 45-66y; min-max 30-92y) and the majority (79%, n=108) were female. Most participants (82.5%, n=113) rated their experience of the group sessions as excellent. The proportions of participants with changes in KAP from baseline to endline were as follows: 45.3% (n=62) to 81.0% (n=111) (p=0.004) able to identify at least two pre-disposing factors for hypertension; 65.0% (n=89) to 77.4% (n=106) (p=0.02) reporting [&ge;]1day of vigorous physical activity/week; 28.5% (n=39) to 13.9% (n=19) (p=0.001) reporting salt added to meals at the table. There was no statistical evidence of any difference in medication adherence, p=0.06. The proportion of participants with uncontrolled hypertension was 58.1% (n=79) at baseline and reduced to 31.8% (n=43) at follow-up (p<0.001). DiscussionCommunity groups for improving awareness, detection and support are acceptable and led to improvements in self-reported KAP and prevalence of uncontrolled BP. Further research on the sustainability and impact of the intervention is required.

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.

Both splicing and kinase signaling are biochemical processes that fundamentally determine and shape cell physiology. Although there has been some indication that there is an interaction between the two - splicing can alter the availability of exons encoding kinase targets and kinases can phosphorylate splicing factors - it has yet to be established the extent to which altering splicing factor expression impacts kinase signaling networks. In this work, we implemented a data-driven analysis using ENCODE RNA-sequencing data and prior work mapping post-translational modifications onto splice events to identify candidate splice factor perturbations that show extensive alterations to phosphorylation-encoding protein products. We then replicated the ENCODE knockdown experiments and performed global phosphoproteomics for two candidates, U2AF1 and SRSF3, complementing the transcription-level data. Both knockdowns showed extensive changes in phosphorylation and kinase activities, both basally and upon receptor tyrosine kinase stimulation. U2AF1 knockdown drove decreased JNK-associated cell death signaling but elevated chromosome regulation through CSNK2A1, PLK, and EIF2AK4 activity. SRSF3 knockdown, on the other hand, led to decreased cell cycle signaling through CDK and HIPK2 but increased cytoskeletal signaling through various PAKs. In addition, we found a striking enrichment of phosphorylated splicing regulators in both knockdowns that were linked to their splicing activity, such as HNRNPC, suggesting potential feedback and crosstalk between splice factors through signaling pathway activation. Importantly, comparison of differential phosphorylation measurements from this study to mRNA expression and splicing measurements from ENCODE revealed significant knockdown-dependent protein regulation, not captured by transcriptomic measurements alone, underscoring the value of phosphoproteomic profiling after splice factor perturbations. Combined, the transcriptomics and phosphoproteomics reveal deep interconnection between the two processes that are relevant to understanding cell signaling in health and disease.

BackgroundDespite advances in therapy, optimal management of juvenile idiopathic arthritis (JIA) remains challenging. The ability to predict disease progression in JIA can improve personalized treatment decisions, but few reliable clinical predictors have been identified. We developed machine learning approaches to predict disease trajectories in children with JIA. MethodsUsing data from the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry (years 2015-2024), we developed machine learning models to predict attainment of inactive disease in children with non-systemic JIA. We applied Dynamic Bayesian Networks (DBN) to model temporal dependencies and causal relationships, and Convolutional Neural Networks (CNN) to capture complex non-linear patterns. Model input included demographic factors, longitudinal clinical factors, and medication use in the preceding 12 months. FindingsA total of 8,093 participants were included. When tested on an independent test cohort, both DBN (AUC:0.76; precision:0.73; recall:0.83; F1-score:0.78; accuracy:0.71) and CNN (AUC:0.76; precision:0.71; recall:0.63; F1-score:0.67; accuracy:0.70) models achieved comparable performance in predicting inactive disease. Disease activity levels in the preceding 12 months, presence of enthesitis and uveitis were the strongest predictors. Causal relationships captured in the DBN model revealed suboptimal care patterns, likely shaped by insurance constraints and a predominantly reactive approach to JIA management. InterpretationOur study demonstrates that machine learning approaches can predict disease trajectories in JIA with good discriminative performance. Unlike prior studies that predict outcomes at single timepoints, our models are the first to predict inactive disease longitudinally. However, suboptimal care patterns in retrospective data limit models capacity to learn treatment-outcome relationships, underscoring critical opportunities to improve JIA care and the need for prospective comparative studies to better inform prediction models. FundingPatient-Centered Outcomes Research Institute (PCORI) Award (ME-2022C2-25573-IC). RESEARCH IN CONTEXT Evidence before this studyNumerous studies have sought to identify clinical predictors of JIA progression and outcomes. However, few reliable predictors have emerged and existing prediction models demonstrate limited performance. As a result, our ability to personalize treatment decisions based on individual risk of severe disease course remains limited. Added value of this studyWe developed novel machine learning models that predict individualized disease trajectories in children with polyarticular and oligoarticular JIA using data from their preceding 12-month clinical course. These models demonstrated strong discriminative performance and outperformed previously published machine learning approaches in JIA. Unlike prior studies limited to single time-point predictions, our models are the first to predict inactive disease longitudinally, enabling a patient-specific projection of disease progression over time. Importantly, our findings also bright to light patterns of suboptimal care, likely driven by insurance constraints and a reactive treatment paradigm, underscoring critical opportunities to improve JIA management. Implications of all the available evidenceOur models have the potential to support clinical decision-making by enabling early identification of children with JIA at risk for unfavorable disease trajectories. In addition, the suboptimal care patterns and systems-level barriers identified through our analyses highlight priority areas for quality improvement initiatives and policy interventions to reduce gaps in JIA care delivery.

Objective. Menopause is a significant physiological transition with implications for health outcomes (e.g., cardiometabolic), yet gaps remain in understanding the menopause transition, including how menopause timing and type influence health outcomes. Large-scale cohort studies in midlife (age~40-60) females, including the All of Us Research Program (AoURP), provide opportunities to study menopause across diverse populations and data modalities. We characterized menopause-related data in AoURP, focusing on age distributions and concordance between EHR diagnosis codes and self-reported survey responses. Methods. We analyzed menopause-related survey, EHR diagnostic code, and genomic data among ~396,000 participants in AoURP with female sex. We summarized menopause data across modalities, overlap between survey, EHR, and genomic data, and age distributions overall and across sociodemographic characteristics. Results. Among ~396,000 females, surveys captured ~193,000 menopause observations, nearly seven times more than structured EHR diagnoses (~28,000), suggesting under- ascertainement in EHR data. Nearly all females (~99%) with an EHR menopause diagnosis also reported menopause in the survey. Approximately 22,000 participants had intersected EHR, survey, and genomic menopause-related data. Survey-based age patterns matched expectations, with participants <40 years predominantly reporting pre-menopausal status and those >60 years predominantly reporting post-menopausal status. A small subset (N{approx}1,700; 4%) (age>70 years) reported no menopause, suggesting response or recall bias. EHR menopause codes were concentrated after age>45 years, with a notable spike at age 65. Modest differences in survey-based menopause age distributions were observed by sociodemographic characteristics (e.g., race, ancestry). Conclusions. These findings inform sampling strategies, power calculations, phenotype definition, and study design for menopause research using AoURP.

Background: Few studies have examined racioethnic disparities in cardiovascular disease (CVD) in women after breast cancer treatment, who are at higher risk due to cardiotoxic cancer treatment. Methods: Based on the Pathways Heart Study of women with a history of breast cancer, this analysis examines the association between cardiometabolic risk factors (hypertension, diabetes, and dyslipidemia) and CVD events with self-reported race and ethnicity, as well as genetic similarity. Multivariable logistic and Cox proportional hazards regression models were used to test race and ethnicity and genetic similarity with prevalent and incident cardiometabolic risk factors and CVD events. Results: Of the 4,071 patients in this analysis, non-Hispanic Black (NHB), Asian, and Hispanic women were more likely to have prevalent and incident diabetes than non-Hispanic White (NHW) women. Analysis of genetic similarity revealed results consistent with self-reported race and ethnicity. For CVD risk, NHB women were more likely to develop heart failure and cardiomyopathy than NHW women. In contrast, Hispanic women were at lower risk of any incident CVD, serious CVD, arrhythmia, heart failure or cardiomyopathy, and ischemic heart disease, which was consistent with the associations found with Native American ancestry. Conclusions: This is the largest multi-ethnic study of disparities in CVD health in breast cancer survivors, demonstrating corroborating findings between self-reported race and ethnicity and genetic similarity. The results highlight disparities in cardiometabolic risk factors and CVD among breast cancer survivors that warrant more research and clinical attention in these distinct, high-risk populations.

Genome-guided dietary advice is a goal of precision nutrition. However, the contribution of gene-diet interactions (GxDs) to disease risk remains unclear, hindering the identification of diet-outcome pairs more likely amenable to genetic-based recommendations. We thus implemented a two-step approach: first, we comprehensively assessed the contributions of genome-wide GxDs to cardiometabolic outcomes across a broad array of dietary exposures in UK Biobank participants (N = 141,144 to 325,989). Second, we selected the 20 significant diet-outcome pairs from the 713 pairs tested (p < 7.0 x 10-5) and derived GxD polygenic scores. In an independent sample, all scores were nominally associated with their corresponding outcomes, with 12 of 20 polygenic scores Bonferroni significant (p < 0.0025). Further analyses revealed GxD polygenic scores were associated with clinical outcomes such as incident gout, suggesting translational potential. Altogether, these results showcase the promise of GxD scores to inform precision nutrition.