Citations

Abstract Pathogenic variants in cardiomyopathy genes confer substantial disease risk, yet clinical penetrance varies widely. The population-level prevalence, age-specific penetrance, and the extent to which polygenic susceptibility modifies disease risk across diverse ancestries remain poorly defined. This population-based cohort study leveraged genome sequencing and linked electronic health record data from the All of Us Research Program (n=414,830). This study found that P/LP variants in cardiomyopathy-associated genes were present in 0.91% of participants (95% CI, 0.88%–0.94%), with similar prevalence across ancestry groups. Compared with non-carriers, variant carriers had significantly higher odds of all-cause heart failure (ACHF, OR, 2.58; 95% CI, 2.31–2.89), non-ischemic heart failure (NIHF, OR, 2.74; 95% CI, 2.42–3.10), and non-ischemic cardiomyopathy (NICM, OR, 4.99; 95% CI, 4.44–5.63). Among carriers, by age 50 years, 24.5% (95% CI, 14.5%–33.4%) developed ACHF, 17.2% (95% CI, 8.8%–24.8%) developed NIHF, and 30.1% (95% CI, 19.5%–40.2%) developed NICM. Higher polygenic risk for heart failure was independently associated with increased risk of ACHF (OR, 1.81; 95% CI, 1.74–1.89), NIHF (OR, 1.66; 95% CI, 1.58–1.75), and NICM (OR, 1.69; 95% CI, 1.59–1.80). Among carriers with elevated polygenic risk, odds of disease were substantially higher than among non-carriers at average polygenic risk (ACHF: OR, 4.71; 95% CI, 4.17–5.32; NIHF: OR, 4.56; 95% CI, 3.99–5.22; NICM: OR, 8.51; 95% CI, 7.44–9.73). Results showed that P/LP variants in cardiomyopathy genes were relatively common in this large, ancestrally diverse cohort, and conferred increased risk of cardiomyopathy and HF, with incomplete but clinically meaningful penetrance. Polygenic risk for HF independently and additively increased disease risk across ancestries. Integrating both may improve risk stratification and enable more precise, equitable care.

Introduction: The objective of the study was to evaluate the prevalence of cardiovascular, renal, and hepatic biomarkers that fall outside guideline-based thresholds in adults with type 1 diabetes (T1D), and to identify demographic and clinical factors associated with these biomarkers. Methods: This observational study linked data on 2,923 adults with T1D from the T1D Exchange Registry and NorstellaLinQ’s laboratory data (2022–2023). Prevalence of biomarkers outside guideline-recommended thresholds was calculated. Generalized estimating equations (GEE) were used to model associations with age, sex, race/ethnicity, insurance, T1D duration, body mass index (BMI), and hemoglobin A1c (HbA1c), while accounting for within-subject correlation due to repeated measures. Results: Elevated low-density lipoprotein (LDL) cholesterol (≥70 mg/dL, above the recommended goal for individuals with diabetes at high risk for atherosclerotic cardiovascular disease) was common (80.2%), as were overweight (33.8%) and obesity (30.3%). Additional findings included high total cholesterol (≥200 mg/dL, 22.6%), low high-density lipoprotein (HDL) cholesterol (<40 mg/dL males, <50 mg/dL females, 13.4%), elevated urinary albumin-to-creatinine ratio (≥30 mg/g, 13.0%), reduced estimated glomerular filtration rate (<60 mL/min/1.73 m 2 , 6.2%), and elevated fibrosis-4 index (FIB-4) (≥1.3, 14.4%). In adjusted GEE models, higher HbA1c was significantly associated with increased odds of abnormal cardiovascular and renal biomarkers across most measures. Male sex and BMI were linked to lower HDL cholesterol, while older age was strongly associated with elevated FIB-4. Conclusion: Obesity and elevated LDL cholesterol are highly prevalent in adults with T1D, indicating substantial cardiometabolic risk. The lack of outcome trials in this population underscores the need for studies to evaluate strategies to improve weight and lipid management and thereby reduce cardiovascular and renal risk in adults with T1D.

Abstract This work presents a first-of-its-kind artificial intelligence (AI-)integrated MR pulse sequence that detects out-of-voxel (OOV) artifacts in real-time (within-TR) and responds prospectively by updating the crusher gradient scheme. Per Excitation Real-time Execution & Guided Responses with Integrated Neural-network Evaluation (PEREGRINE), allows for deployment of deep learning models and pulse sequence updates. In this study, PEREGRINE operated a time-domain (TD) and frequency-domain (FD) convolutional autoencoder that detect OOV artifacts. Scans without (AI-off) and with (AI-on) updates were collected from the medial prefrontal cortex of healthy volunteers using a MEGA-edited MRS experiment. The degree of OOV contamination (OOV Score) was quantified per transient based upon the prevalence of OOV signals in the TD and FD data. OOV Scores above a user-defined threshold triggered an update of the crusher gradient scheme, iterating through 48 permutations (6 axis transpositions × 8 polarity flips). Within each 2-second TR, PEREGRINE successfully provided single-transient OOV Scores and updated gradients accordingly. No difference was observed between the OOV Scores from the full (“Full” condition) AI-on and AI-off sessions due to the AI-on scan cycling over better and worse gradient permutations relative to the AI-off scan. However, the AI-on scan had significantly lower OOV Scores than the AI-off scan when selecting the transients where PEREGRINE persisted (“Dwell” condition) on a given gradient permutation. Ultimately, Fit Quality Number (FQN) from linear combination modeling improved significantly for the AI-on compared to the AI-off scan. PEREGRINE enabled an adaptive and AI-integrated sequence allowing for real-time evaluation and response to OOV artifacts, identifying gradient modifications that produced less OOV contamination. Graphical Abstract Graphical Abstract Summary PEREGRINE, Per Excitation Real-time Execution & Guided Responses with Integrated Neural-network Evaluation, allows for pulse sequence updates using on-scanner deployed neural networks. To demonstrate the utility, PEREGRINE was used to operate two neural networks (time/frequency domain), trained to detect out-of-voxel artifacts, during a MEGA-edited MRS experiment in the prefrontal cortex. When artifacts were detected, PEREGRINE updated the crusher gradients within the same TR. Real-time, adaptive, and AI-driven MR will provide a long-awaited solution for combatting artifacts and poor data quality. Graphical Abstract Figure

ABSTRACT Macrophages play a central role in determining the outcomes of healing, coordinating regeneration in some injuries and scar formation in others. In both cases, this coordination involves the cross-talk between macrophages and surrounding cells. But what drives the different cross-communication pathways to determine healing outcomes is not well known. In this study, we make use of the mouse digit tip amputation model, in which an amputation through the third phalangeal element (P3) is able to completely regenerate whereas an amputation through the second phalangeal element (P2) forms a scar. We identify a population of macrophages that is specific to the P3 regenerating digit. By integrating single-cell RNAseq, spatial transcriptomics, and metabolomic analyses, we show that this population localizes specifically to the growing bone front, express BMP ligands that drive downstream BMP activation in neighboring osteoblasts and is governed by a two-part metabolic switch involving increased fatty acid oxidation coupled with reduced glycolytic activity. This spatially restricted, BMP-expressing macrophage population is entirely absent in the scar-forming P2 injury, and our data indicate that environmental conditions unique to the regenerating digit are responsible for its emergence. Together these findings identify a regeneration-specific macrophage signaling center for patterned bone formation and suggest that targeting the metabolic conditions that drive this population could improve the efficacy of regenerative therapies.

Background The middle meningeal artery (MMA) has emerged as an endovascular route for treating chronic subdural hematoma (CSDH), meningioma, and refractory headaches. The third ARISE roundtable convened experts from neurology, neurosurgery, neuroradiology, industry, and regulatory agencies to develop consensus guidance on current evidence for MMA-based therapies Methods Over 50 experts participated in a multi-stakeholder discussion. Evidence from randomized and observational studies, early-phase interventional series, and preclinical work was reviewed. Breakout groups focused on four domains: (1) MMA embolization (MMAE) for CSDH, (2) preoperative embolization of meningiomas, (3) MMA-targeted therapies for headache, and (4) transvascular access for endovascular drainage of subdural hematomas. Consensus recommendations were developed by a writing committee Results Randomized trials support MMAE as an adjunct to surgery or medical management for selected patients with non-acute, symptomatic CSDH to reduce recurrence, progression, and reoperation. Evidence remains insufficient to support MMAE for acute or asymptomatic subdural hematomas. For meningioma, observational data suggest that preoperative embolization in experienced centers can reduce blood loss and operative time and may delay recurrence in large, hypervascular tumors with predominant dural or external carotid supply; primary embolization and intra-arterial oncologic therapies remain investigational. Early series of MMA-directed lidocaine infusion for refractory migraine, status migrainosus, and post-subarachnoid hemorrhage headache show short-term benefit, highlighting the need for controlled trials. Preclinical and first-in-human studies of combined MMAE and transvascular drainage for CSDH demonstrate high technical success, rapid radiographic and clinical improvement, and no early recurrences Conclusion The MMA represents a vascular pathway for an expanding spectrum of neurointerventional therapies.

Abstract Background Traumatic brain injury (TBI) in older adults is associated with high mortality and poor functional outcomes. However, optimal management remains uncertain, as evidence comparing surgical and medical strategies is limited, heterogeneous, and extrapolated from younger populations. We conducted a systematic review and meta-analysis to compare outcomes between surgical and medical management in this population. Methods PubMed, Embase, and Web of Science were searched from database inception to December 8, 2025. Studies including adults aged ≥60 years with TBI comparing surgical versus medical management were included. The primary outcome was favorable neurological outcome, while secondary outcomes included hospital length of stay (LOS) and mortality. Pooled estimates were calculated as risk ratios (RR) and mean differences (MD) using random-effects models with restricted maximum likelihood and Hartung–Knapp adjustment. Results Sixteen cohort studies comprising 132,823 patients were included. Surgical management was not associated with improved favorable neurological outcomes at discharge, 3, 6, or 12 months. However, it was associated with longer LOS (MD = 6.35 days, 95% CI: 2.55 to 10.14; p < 0.01). No differences were observed in in-hospital, 30-day, 3-month, 12-month, or 24-month mortality. Notably, surgical management was associated with a reduction in 6-month mortality (RR = 0.68, 95% CI: 0.51–0.92; p = 0.02). Conclusions In older adults with TBI, surgical management was associated with reduced 6-month mortality and longer hospital LOS, but not with improved functional outcomes, highlighting a dissociation between survival and recovery. This dissociation has implications for clinical decision-making and patient and family counseling. Individualized decision-making that incorporates frailty, comorbidities, and potential reversibility of injury is essential, rather than relying solely on age. While this study represents the best available comparative evidence to date on surgical versus non-surgical management in older adults with TBI, findings should be interpreted with caution due to heterogeneity and low to very low certainty of the evidence. High-quality randomized controlled trials are needed to better define the role of surgery in this population.

Importance Amblyopia is the leading cause of monocular decreased best-corrected vision in children. Early detection and intervention are key for optimal treatment outcomes; however, limited access to pediatric eye specialists may hinder timely care and affect visual outcomes. Given the shortage of specialty-trained eye care professionals in the US, there is need to support comprehensive eye care professionals who are willing to examine and treat children with amblyopia. Objective A panel from the Pediatric Eye Disease Investigator Group synthesized relevant literature and incorporated consensus opinion where direct evidence was lacking to create the Amblyopia Navigator Decision-Support Instrument, a free, web-based amblyopia decision support tool for eye care professionals. Evidence Review The decisions related to optimal diagnostic measures, pass/refer criteria, and management recommendations were informed by 147 publications. In areas where direct evidence was lacking, guidance was supplemented with clinical trial protocols or existing professional guidelines. When data were conflicting or unavailable, recommendations were established through committee consensus. A single reviewer independently performed standardized (though not systematic) literature reviews to avoid missing pertinent recent publications. Findings Presented are the process used, supporting evidence, and recommendations for testing methods, refractive correction, amblyopia treatment options, treatment adjustments, and monitoring schedules. Conclusions and Relevance Because amblyopia is common and typically responds well to treatment, decision support tools that optimize its management could increase access to pediatric eye care by facilitating earlier detection, enabling broader participation of primary eye care professionals, and ultimately improving visual outcomes. Through this work and the development of the forthcoming free, web-based application version, Amblyopia Navigator Decision-Support Instrument, the Pediatric Eye Disease Investigator Group has created decision support tools designed to assist optometrists and ophthalmologists in the care of children aged 3 to 17 years with amblyopia.

Introduction: Young-onset esophageal adenocarcinoma (EAC) often presents at advanced stages and is associated with poor outcomes. We aimed to examine the epidemiology of young-onset Barrett’s esophagus (BE) using the TriNetX database. Methods: Young-onset BE patients (age 18 to younger than 50 y) with esophagogastroduodenoscopy (EGD) within 1 year before index BE diagnosis between 2014 and 2023 were included. Negative binomial regression was used to evaluate incident-time trends, and logistic regression to assess for independent predictors of young-onset BE. Results: BE diagnosis was present in 76,691 (3.3%) of 2,337,786 patients that underwent EGD, of which 14,120 (18%) had prevalent young-onset BE. BE dysplasia/EAC was present in 6% of young-onset patients at initial diagnosis. Conventional BE risk factors also predicted young-onset BE: GERD (OR=2.4), White race (OR=2.4), male sex (OR=2.2), smoking (OR=1.2), and obesity (OR=1.1). Each additional risk factor increased the probability of BE prevalence by 74% in young patients versus 54% in older patients. The prevalence of young-onset BE was 4.5% with GERD and ≥3 additional risk factors, and 2.3% when ≥3 risk factors were present. Discussion: Young-onset BE accounts for 18% of all BE cases, demonstrates a striking 6% rate of dysplasia/neoplasia at initial diagnosis, and has a prevalence of 4.5% in those with GERD and ≥3 risk factors. These findings suggest that young-onset BE is an important patient population that merits further study. Additional studies are necessary to study the cost-effectiveness of BE screening in younger patients with multiple risk factors.