Citations

Abstract Alzheimer’s Disease (AD) 1 is a progressive neurodegenerative disorder with limited therapeutic options, driving interest in drug repurposing to accelerate treatment discovery. Drug repurposing has emerged as a promising strategy to accelerate therapeutic discovery by repositioning existing drugs for new clinical indications. Recent computational repurposing approaches, including knowledge graph reasoning, transcriptomic signature analysis, and integrative literature mining, have demonstrated strong predictive capabilities 2 . However, these methods often yield divergent drug rankings, which makes it difficult to decide which candidates to advance for experimental follow-up and results in substantial gaps between computational predictions and feasible in vivo validation 2 .To bridge this computational-experimental gap, we proposed an advanced prioritization framework leveraging large language models (LLMs). Our method systematically evaluated three state-of-the-art (SOTA) and representative computational methods (TxGNN 3 , Composition-based Graph Convolutional Network (CompGCN) 4 , and a regularized logistic regression (RLR) 5 , to analyze both their predictive performance and pharmaceutical class distributions. By integrating the strengths and divergences of these models, we generated a unified, streamlined list of 90 candidate drugs for further prioritization. We then utilized an LLM-based agent to perform evidence synthesis from biomedical literature abstracts for each candidate. This process mimics expert manual curation but significantly reduces human effort and time by efficiently distilling vast textual data into actionable insights. Applying consistent and transparent selection criteria, we obtained a refined and prioritized list of drug candidates suitable for subsequent in vivo experimental validation. The robustness and clinical relevance of our framework were validated using real-world data from Alzheimer’s patient cohorts, clinical trial registries, and expert pharmacological reviews. This comprehensive validation confirmed that our LLM-driven approach enhances efficiency, consistency, scalability, and generalizability. By integrating computational predictions with scalable evidence synthesis and multifaceted validation, our framework facilitated rapid and informed prioritization of repurposed drugs. Our framework can potentially accelerate the translational pathway toward viable AD therapeutics. Moreover, the versatility of our framework can also be applied to drug repurposing efforts for other diseases beyond AD.

Abstract Background Adolescent and young adult (AYA) patients remain underrepresented in neuro-oncology research. Despite being the second most common primary brain tumor in this population, meningiomas have not been studied using age-specific molecular analyses. DNA methylation-based classification and prognostic tools have transformed meningioma care. This study aimed to evaluate the performance of these tools across age groups. Methods We analyzed 1,568 meningiomas with DNA methylation and clinical data, including 18 pediatric patients (<15 years), 195 AYA patients (15-39 years), and 1,355 adult patients (>39 years). Pediatric and AYA (P/AYA) tumors were combined and compared with adult tumors. The performance of established molecular classifiers and recurrence predictors, as well as differences in chromosomal copy number alterations were compared across age groups. Results While histologic grading was comparable between cohorts, P/AYA tumors displayed significantly fewer aggressive molecular groups and lower frequencies of chromosomal arm losses, including 1p, 6q, and 14q. The adult-trained recurrence predictor failed in the P/AYA population (AUC 0.57), despite similar score distributions. Retraining the model on an age-specific cohort using an identical analytic framework improved performance (AUC 0.79) and enabled effective stratification of progression-free survival (P = 0.00054). Importantly, 1p loss retained prognostic significance within the P/AYA group, supporting its clinical utility. Conclusions Molecular tools developed in adult-dominant cohorts do not generalize to younger patients due to both biological divergence and exclusion from model development. These findings underscore the need for age-specific molecular frameworks and highlight the imperative of including P/AYA populations in precision neuro-oncology research to ensure lifespan-equitable care.

BACKGROUND: Although chronic obstructive pulmonary disease (COPD) and heart failure with preserved ejection fraction often coexist with overlapping clinical features, they are usually studied separately. The SPIROMICS HF (Subpopulations and Intermediate Outcome Measures in COPD and Heart Failure Study) is testing hypotheses that new computed tomography emphysema subtypes are associated with specific cardiovascular phenotypes (eg, cor pulmonale , cor pulmonale parvus ), common airway branch variants are associated with right heart dysfunction, and symptomatic tobacco-exposed persons with preserved spirometry have signs of increased left ventricular afterload. METHODS: SPIROMICS is a multicenter observational study of COPD with extensive pulmonary phenotyping of participants with ≥20 pack-years smoking and nonsmoking controls. COPD and COPD severity were defined by standard spirometric criteria and symptomatic tobacco-exposed persons with preserved spirometry by ≥20 pack-years, normal spirometry, and COPD Assessment Test score >10. SPIROMICS HF selected all participants in SPIROMICS visit 5 at major sites. Its comprehensive speckle-tracking echocardiography, which included physiological perturbations of leg raise and low-intensity exercise, was harmonized prospectively with the Multi-Ethnic Study of Atherosclerosis Early Heart Failure and HeartSHARE (Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets) studies. The cardiopulmonary magnetic resonance imaging protocol with gadolinium administration included myocardial fibrosis sequences, pulmonary angiography, time-resolved 3-dimensional cine magnetic resonance imaging (4-dimensional flow) of venous return, and metronome-paced tachypnea to induce dynamic hyperinflation. Coronary artery calcium was assessed on computed tomography scans. The Kansas City Cardiomyopathy Questionnaire was administered. RESULTS: Of the final sample of 753 participants, 57% had COPD (15% mild, 27% moderate, and 15% severe), 18% had symptomatic tobacco-exposed persons with preserved spirometry, 16% were smoking controls, and 8% were nonsmoking controls. Reproducibility of the main measures from speckle-tracking echocardiography (intraclass correlation coefficient, 0.83–0.99), exercise echocardiography (intraclass correlation coefficient, 0.71–0.99) and magnetic resonance imaging (intraclass correlation coefficient, 0.57–0.99) were good-to-excellent, including in severe COPD. CONCLUSIONS: SPIROMICS HF aims to characterize and understand cardiopulmonary interactions in COPD and COPD-related phenotypes to inform targeted treatments for combined cardiopulmonary failure.

Abstract Pancreatic adenocarcinoma remains one of the most lethal malignancies, primarily due to its robust resistance to genotoxic therapies, such as chemotherapy and radiotherapy. Understanding the mechanisms underlying this resistance is essential to improve clinical outcomes. In this study, we identified trimethylguanosine synthase 1 (TGS1), previously known for its role in RNA modification, as a critical mediator of homologous recombination (HR) repair that specifically contributes to resistance in pancreatic adenocarcinoma. TGS1 was significantly overexpressed in pancreatic adenocarcinoma tissues, correlating strongly with advanced disease stages, therapy resistance, and poor patient prognosis. Following DNA damage, ATM kinase phosphorylated TGS1 at serine residues S389 and S531, which mediated its direct interaction with BRCA1 and subsequent recruitment of BRCA1 to DNA damage sites. The phosphorylation-dependent interaction enhanced HR repair efficiency, enabling cancer cells to survive genotoxic stress. Depletion or pharmacologic inhibition of TGS1 induced HR deficiency and markedly enhanced sensitivity to DNA-damaging agents, particularly PARP inhibitors, in pancreatic adenocarcinoma cell lines in vitro and in both cell line– and patient-derived xenograft models in vivo. Collectively, these findings uncover an ATM–TGS1–BRCA1 signaling axis that promotes DNA repair and resistance to genotoxic therapies in pancreatic cancer, positioning TGS1 as a promising predictive biomarker and therapeutic target to enhance treatment efficacy. Significance: The ATM–TGS1–BRCA1 signaling axis is a critical regulator of DNA repair that can be targeted to overcome genotoxic therapy resistance, providing a promising therapeutic strategy that could transform pancreatic cancer treatment.

Background: Pulsed field ablation (PFA) has become a cornerstone for atrial fibrillation ablation. Multiple platforms have been developed and approved worldwide, and routine screening for asymptomatic brain injury (ABI) has been included in several trials as part of the safety assessment of this technology. The incidence by catheter/platform, predictors of occurrence, and clinical impact remain incompletely understood. Research Question: In patients with atrial fibrillation undergoing pulmonary vein isolation, does the incidence of ABI vary between different PFA platforms? Methods: We searched the MEDLINE/PubMed, Embase, and Cochrane Central Register of Controlled Trials databases for studies reporting on patients who underwent PFA and post-procedure brain MRI to screen for ABI. The review was conducted in accordance with PRISMA guidelines. A random-effects proportion meta-analysis was performed, with subgroup analysis based on the PFA platform used. For studies including a thermal ablation control group, risk ratio (RR) was used to compare outcomes. Finally, a meta-regression was conducted to identify potential predictors of ABI incidence. Results: A total of 19 studies reporting data from 742 patients who underwent post-ablation brain MRI were included in this review. The pooled incidence of silent cerebral events (new findings visible only on DWI sequences) and silent cerebral lesions (new findings on both DWI and FLAIR sequences) was 5% each (95% CI, 3%–8%). The pooled incidence of any ABI was 10% (95% CI, 8%–13%). A platform-level subgroup analysis demonstrated comparable outcomes across the platforms with available data (Figure 1). The meta-regression included age, sex, CHA2DS2-VASc score, and incidence of symptomatic stroke/TIA, but no statistically significant associations were identified. In the four studies that included a thermal ablation control group, there was no significant difference in ABI incidence between PFA and thermal ablation (RR: 1.37; 95% CI, 0.68–2.74; P = 0.38; I2 = 16%) (Figure 2). Seven studies reported follow-up MRI in patients who presented with an ABI. Among 20 patients with ABI after ablation, radiologic lesions persisted in 2 patients. Conclusion: ABI is a relatively frequent finding following PFA; however, current evidence does not reveal significant differences between available platforms. Radiologic findings tend to be transient, suggesting a limited long-term clinical impact.

Background: Spontaneous Coronary Artery Dissection (SCAD) is a cause of acute coronary syndrome, particularly among women, and is associated with psychological distress, including depression, anxiety, and post-traumatic stress (PTSD) symptoms. Fibromuscular dysplasia (FMD), a vascular condition that alters the arteries, is often found in patients with SCAD, adding complexity and uncertainty with a second serious diagnosis. This study examined the differences in mental health symptoms between SCAD survivors with and without FMD to better understand their unique psychosocial needs and inform interventions to enhance patient outcomes. Methods: Patients diagnosed with SCAD within the past 3 years were recruited from 6 Canadian cardiac hospitals. Participants completed questionnaires assessing socio-demographics, comorbidities, and validated psychological measures, including Patient Health Questionnaire-9 (PHQ-9) for depression, Generalized Anxiety Disorder-7 (GAD-7) for generalized anxiety, Cardiac Anxiety Questionnaire (CAQ) for cardiac-related anxiety, and PTSD Checklist (PCL-5) for PTSD symptoms. Differences in mental health outcomes between SCAD survivors with and without FMD were analyzed using t-tests for continuous variables and chi-square tests for categorical variables. Results: The study included 326 participants (92.9% female; mean age 53.3 years), with 67 participants (20.6%) having a confirmed diagnosis of FMD at the time of questionnaire completion (39.3% FMD at study completion). Post-SCAD, patients with FMD reported significantly higher scores than patients without FMD on the GAD-7 (6.4±5.9 vs. 4.7±4.9, p = .028), CAQ (29.9±13.1 vs. 26.0±12.3, p = .023), and PCL-5 (17.2±15.4 vs. 13.3± 14.0, p = .048). The proportion of SCAD survivors with FMD scoring in the clinically diagnostic range was significantly higher than those in patients without FMD: 32.8% vs. 20.8% for depression, 31.3% vs. 17.4% for anxiety, 64.2% vs. 49.2% for cardiac anxiety, and 25.4% vs. 11.6% for PTSD (all p < .05). Conclusions: Our findings suggest that SCAD survivors with comorbid FMD experience significantly higher distress —depression, generalized anxiety, cardiac-related anxiety, and PTSD symptoms—compared to those without FMD. Longitudinal research is needed to explore the role of these mental health concerns in long-term mental health and cardiac outcomes. Enhanced psychological interventions for those with FMD may be required.

Background: Cardiac fibrosis is a critical and independent driver of heart failure (HF), characterized by excessive extracellular matrix (ECM) deposition. Decreased CDCP1 (CUB domain-containing protein 1) expression has been associated with myocardial recovery in human genome wide association studies by attenuating PDGF-BB driven cardiac fibroblast proliferation with no effect on canonical TGF-beta mediated transdifferentiation in-vitro. In-vivo, Cdcp1 deletion significantly reduced cardiac fibrosis and dysfunction in an angiotensin II/phenylephrine-induced pressure overload mouse model. However, its upstream regulators and its downstream effects on molecular signaling pathways that modulate ECM remodeling are unknown. Hypothesis: CDCP1 promotes human cardiac fibroblast mediated ECM remodeling in the HF microenvironment. Methods: Human ventricular fibroblasts (HVF) were treated with PDGF-BB (20 ng/ml), TGF-β (10 ng/ml), or Angiotensin II (100 ng/ml) for 48 hours. CDCP1 knockdown (KD) was achieved through siRNA transfection. Gene expression analysis was performed using qRT-PCR and protein quantification by Western blot. Both intact HVF and decellularized ECM were immunostained for collagen 1 to evaluate for ECM compositional changes. Results: Individual and combination treatments with fibrotic stimuli significantly increased CDCP1 expression (Figure 1A-1B). CDCP1 KD resulted in reduction of key ECM markers COL1A1, CTGF, and LOX (Figure 1C) across all fibrotic stimuli . Immunostaining of HVF after treatment with fibrotic stimuli showed reduced collagen 1 production with CDCP1 KD (Figure 1D). Western blot analysis showed increased phosphorylation of Src (tyr416) with 6h of treatment with fibrotic stimuli which was nullified by silencing of CDCP1 (Figure 1E). Conclusion: Our findings demonstrate that CDCP1 is necessary for ECM synthesis and Src signaling across multiple profibrotic pathways. Selective targeting of CDCP1 to modulate Src signaling pathways could provide novel therapeutic avenues for HF and fibrosis treatment.

Introduction/Background: CHIP is a risk factor for cardiovascular (CV) disease, cancer, and all-cause mortality. Previous work has shown that CHIP, and particularly larger CHIP clones, are associated with adverse CV outcomes, yet the molecular pathways through which CHIP impacts CV risk are poorly defined. Hypothesis/Research Question: We hypothesize that the integration of whole blood transcriptomics and methylomics will provide novel insights into the pathophysiology of CHIP. Methods/Approach: Whole blood DNA methylation profiling, transcriptomics, and whole exome sequencing with CHIP calling for variant allele frequencies (VAF) of ≥2% (CHIP) and ≥10% (large CHIP) were performed for 507 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. We identified transcriptomic and methylomic differences between participants with CHIP and large CHIP vs no CHIP using DESeq2 and limma, adjusted for age, sex, and race/ethnicity. Gene set enrichment analysis (GSEA) and probe set enrichment analysis (PSEA) were performed to identify pathway-level alterations in transcription and methylation, respectively. Results/Data: Clinical characteristics of study participants are described in Fig 1A . Compared to no CHIP (n=391), transcriptomics identified 6 differentially expressed genes (DEGs) in CHIP (n=116) and 27 DEGs in large CHIP (n=35) (p-adj<0.05; abs(logFC)>0.25) (Fig 1B) . Compared to no CHIP, methylation identified no differentially methylated probes in CHIP and 6 in large CHIP (padj<0.20, abs(logFC)>0.03). GSEA identified 137 pathways significantly different in both CHIP and large CHIP vs. no CHIP (padj<0.05), while PSEA identified 724 and 2356 pathways (padj<0.20), respectively. Given its stronger relationship with methylation and transcription, downstream analyses focused on large CHIP. Integrating these data, we found 58 pathways to be both hypomethylated and transcriptionally upregulated in large CHIP, including azurophil granule-related pathways implicated in neutrophil degranulation (Fig 1C) . Further investigation into the gene-probe pairs driving the azurophil granule pathway enrichment in large CHIP revealed hypomethylation and increased transcription of genes implicated in neutrophil extracellular trap formation, including ELANE, PTRN3, AZU1, and CTSG (Fig 1D) . Conclusions: Integration of the methylome and transcriptome suggests large CHIP is linked to neutrophil-mediated immune pathways in patients with stable coronary artery disease.

Abstract Understanding tumor cell dynamics can improve prognosis and treatment but remains limited for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA sequencing data from 684 NS-LUAD cases and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histologic data further characterized the subtypes. “Steady,” marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver gene alterations, is linked to prolonged survival and low immune evasion. “Proliferative” shows high proliferation markers, TP53 mutations, and gene fusions. “Chaotic,” with high epithelial-to-mesenchymal transition markers, has the worst prognosis, even within stage I tumors. Lacking known molecular or histologic characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the classification and predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving early-stage NS-LUAD prognostication in clinical settings. Significance: The transcriptome of 684 NS-LUAD identifies three subtypes with different cellular dynamics and genomic and morphologic features. A 60-gene signature accurately stratifies subjects for mortality risk, even in stage I, offering a potential clinically applicable tool for treatment decision-making in patients with NS-LUAD. See related commentary by Azizi et al., p. 423

With rapid industrial expansion, air pollution’s adverse neurological effects have gained increasing attention. Children face a greater risk of neurological damage because of their higher breathing rates, developing brains, and limited ability to detoxify harmful substances. Fine particulate matter has been identified as a primary neurotoxic contributor affecting developing brains. Strong evidence connects environmental pollutant exposure to the prevalence of Autism Spectrum Disorder (ASD), a neurodevelopmental condition marked by lasting difficulties with social communication and interaction. This study explores the association between long-term PM2.5 exposure and ASD symptom exacerbation, investigating underlying mechanisms. We hypothesize that long-term PM2.5 exposure exacerbates ASD symptoms through neuroinflammatory activation, leading to neuronal damage and impaired synaptic plasticity. Our investigation employs three complementary approaches: First, integrated analysis combining Global Burden of Disease data with Mendelian randomization demonstrates a significant association between PM2.5 exposure and increased ASD severity risk. Second, utilizing the China High-Resolution Air Pollution Database in conjunction with cohort studies, we provide evidence that ambient air pollution substantially influences autism severity, with PM2.5 identified as the predominant environmental determinant. Third, through network toxicology, single-cell transcriptomics, and animal experimentation, we demonstrate that chronic PM2.5 exposure exacerbates valproic acid-induced autism-like behaviors in murine models, identifying CTNNB1, PTEN, CCR2, AKT1, and mTOR as potential core mediating genes. Importantly, these findings represent preliminary results. Several potential confounding factors such as co-exposure to other pollutants and socioeconomic variables have not been fully addressed. While our multi-modal approach provides converging lines of evidence, further validation in larger, more diverse populations with refined control of confounders will be essential to establish causality and elucidate mechanisms. Nonetheless, these early insights advance our understanding of PM2.5-induced neurotoxicity in the context of ASD and offer timely, albeit preliminary, evidence to inform public health policy.