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Background: Atrial fibrillation (AF) significantly impacts quality of life (QoL) and is often observed in patients with transthyretin amyloid cardiomyopathy (ATTR-CM). Acoramidis achieves near-complete (≥90%) transthyretin (TTR) stabilization and is approved in the USA, the UK, Europe and Japan for the treatment of ATTR-CM in adults. In the phase 3 ATTRibute-CM study (NCT03860935), acoramidis treatment significantly reduced the time to all-cause mortality (ACM) or first cardiovascular-related hospitalization (CVH) at Month 30, and resulted in improved 6-minute walk distance (6MWD), Kansas City Cardiomyopathy Questionnaire-Overall Summary (KCCQ-OS) scores and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels relative to placebo. The clinical efficacy of acoramidis has not yet been reported in patients with ATTR-CM and with an AF or atrial flutter (AFL) diagnosis at baseline. Research Question: How does acoramidis treatment affect ACM or first CVH, 6MWD, KCCQ-OS scores, and NT-proBNP levels at Month 30 in participants with ATTR-CM with or without AF/AFL diagnosis at baseline? Methods: The ATTRibute-CM study design has been previously published. This post hoc analysis included participants in the modified intention-to-treat population (N=611) grouped by AF/AFL diagnosis at baseline (defined as recorded AF medical history or the presence of AF or AFL on an ECG at enrollment). The rate of ACM or first CVH at Month 30 was compared between groups using a stratified Cox proportional hazards model. Changes from baseline to Month 30 in 6MWD, KCCQ-OS scores and NT-proBNP levels were summarized descriptively. Results: Overall, 62.8% (384/611) of participants had an AF/AFL diagnosis at baseline (acoramidis: 255/409, placebo: 129/202). These participants had lower mean 6MWD and KCCQ-OS scores and higher median NT-proBNP levels than those without AF/AFL diagnosis at baseline. Treatment with acoramidis reduced ACM or first CVH, slowed the decline in 6MWD and KCCQ-OS scores and blunted the rise in NT-proBNP compared with placebo, regardless of AF/AFL diagnosis at baseline ( Table ). Conclusions: Acoramidis improved clinical outcomes (ACM, CVH), functional status, QoL and NT-proBNP levels relative to placebo in participants with ATTR-CM, regardless of AF/AFL diagnosis at baseline.

Background: Coronary computed tomography angiography (CCTA) is vital for diagnosing ischemic heart disease, yet its accuracy is affected by varying reader expertise. Artificial Intelligence (AI)-driven automated stenosis assessment offers promise for enhancing diagnostic consistency. Aim: We aim to evaluate an AI-CCTA assessment against invasive coronary angiography, invasive FFR, and expert readings. Methods: We performed a comprehensive search in Web of Science, Scopus, PubMed, Cochrane Library, and EMBASE from inception until March 2025. Two independent reviewers screened articles and extracted data on study design, patient demographics, AI methodology, stenosis thresholds, and outcomes. For statistical analysis, we constructed summary receiver operating characteristic (SROC) curves and used a bivariate random-effects model to derive pooled sensitivity, specificity, diagnostic odds ratios (DOR), and area under the curve (AUC). Forest plots were generated to visualize these metrics. Results: Our meta-analysis included 34 studies with 10,067 patients. AI-based CCTA demonstrated excellent diagnostic performance with an AUC of 0.932 for per-patient analysis. The pooled per-patient sensitivity was 0.89 (95% CI: 0.87–0.91) and specificity was 0.80 (95% CI: 0.74–0.86), with a DOR of 37.07 (95% CI: 24.57–55.92). AI validated against expert readers achieved the highest accuracy (0.94, 95% CI: 0.87-0.98). The >70% stenosis threshold demonstrated superior performance (accuracy: 0.89, specificity: 0.96) compared to the >50% threshold (accuracy: 0.86, specificity: 0.87). Per-vessel analysis showed comparable results with an AUC of 0.905. Conclusion: Our meta-analysis confirms that AI-assisted coronary CT angiography delivers high diagnostic performance for coronary stenosis detection, with strong AUC values, high sensitivity and specificity, and robust diagnostic odds ratios across both per-patient and per-vessel assessments.

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: Patients with variant transthyretin (TTR) amyloid cardiomyopathy (ATTRv-CM) experience early onset disease, rapid progression, and poor outcomes due to amyloid aggregated from destabilized tetrameric TTR. Acoramidis, a highly selective, oral TTR stabilizer, achieves ≥90% TTR stabilization and is approved in the USA, EU, Japan, and UK for adults with wild-type (ATTRwt-CM) or ATTRv-CM. In the phase 3 ATTRibute-CM study and its open-label extension (OLE), acoramidis reduced both the risk of all-cause mortality (ACM) or first cardiovascular-related hospitalization (CVH) through Month 30 and risk of ACM through Month 42 by 36%. Research Question: Is acoramidis efficacy in ATTRv-CM consistent with that observed in the overall ATTRibute-CM population? Methods: In ATTRibute-CM, participants with ATTR-CM were randomized 2:1 to acoramidis HCl 800 mg or PBO, twice daily (BID) for 30 months. After Month 30, all participants enrolled in the OLE received acoramidis HCl 800 mg BID. Genotype (ATTRwt-CM or ATTRv-CM) was captured at randomization; efficacy was analyzed separately in ATTRv-CM. Time-to-event analyses used a stratified Cox model with terms for treatment, baseline 6MWT, genotype, genotype×treatment interaction, stratified by randomization NT-proBNP and eGFR levels. ACM was analyzed at Month 42 (ATTRibute-CM 30 months + OLE 12 months). Results: The ATTRv-CM group comprised 59 patients (39 acoramidis, 20 PBO). Baseline characteristics were mostly similar in both groups ( Table ). The three most common variants reported were p.V142I (n=35), p.I88L (n=7), and p.T80A (n=5). Compared with PBO, acoramidis reduced the risk of ACM/first CVH through Month 30 by 59% (acoramidis, 46.2%; PBO, 75.0%; HR 0.41; 95% CI 0.21–0.81; P =0.011; Fig 1 ) and ACM through Month 42 by 59% (continuous acoramidis, 30.8%; PBO to acoramidis, 60.0%; HR 0.41; 95% CI 0.19–0.93; P =0.032; Fig 2 ) , with Kaplan–Meier curves separating at Months 5 and 10, respectively. Conclusions: In ATTRibute-CM, acoramidis use was associated with clinical benefit in the ATTRv-CM group as demonstrated by a 59% risk reduction in both ACM/first CVH at Month 30, and ACM at Month 42 compared to PBO. These previously unreported findings support the hypothesis that near complete TTR stabilization observed experimentally with acoramidis across multiple TTR mutations translates into improvement in long-term outcomes. Further validation by individual TTR variant is warranted.

Background: Susceptibility to cardiometabolic diseases (CDs) is shaped by genetic, socio-environmental, and lifestyle factors. We evaluated the associations of disease-specific polysocial risk scores (PSSs)— derived from social determinants of health (SDOH) and lifestyle factors—and genetic risk factors with six CDs, across self-identified race/ethnicity (SIRE) groups in the eMERGE IV cohort. Methods: The six CDs included: atrial fibrillation, coronary heart disease, chronic kidney disease, hyperlipidemia, obesity, and type 2 diabetes. Disease-specific PSSs were developed using machine-learning models based on 65 SDOH and lifestyle factors. Participants were grouped based on their SIRE as Asian, Black, Hispanic/Latino, and White. We evaluated PSS distributions across SIRE groups. Genetic risk was assessed through disease-specific polygenic risk scores (PRSs), monogenic etiologies, and family history (FamHx). High PSS and high PRS were defined as the top 5th percentile. Associations were tested using multivariable logistic regression; model performance was assessed using the C-statistic. Results: Among 20178 participants (50±15 years, 68% female, 40% non-White), the most frequently associated PSS components were physical activity, sleep, self-perceived health, and income. PSS distributions varied across SIRE groups, with Whites having the lowest and Black and Hispanic/Latinos the highest scores for most CDs (Figure 1). All PSSs were significantly associated with their respective CDs, independent of confounders (OR per 1 SD increase: 1.19–2.68; Figure 2-A). No significant interactions were observed between PSSs and PRSs or monogenic etiologies. However, significant interactions were noted between PSSs and FamHx for CKD and obesity. PSS and PRS effects on the odds of CDs were independent (Figure 2-B) and additive (Figure 2-C). Incorporating PSSs into models that included clinical and genetic risk factors improved predictive performance of risk prediction models (Figure 3). Conclusion: PSSs, reflecting socio-environmental and lifestyle disadvantage, varied significantly across SIRE groups and were associated with risk of six CDs, independent of and additive to PRS. Given the substantial variation in socio-environmental and lifestyle risks across SIRE groups, integrating these factors into risk prediction models for CDs may help address health disparities and enhance preventive efforts, especially in marginalized populations.

Background: We investigated the impact of genetic risk factors for coronary heart disease (CHD) -polygenic risk score (PRS), familial hypercholesterolemia (FH), and family history (FamHx)- on CHD risk estimates, across the age spectrum, in two diverse cohorts of US adults -eMERGE IV (eIV) and All of Us (AoU). Methods: CHD was defined as myocardial infarction, unstable angina, and coronary revascularization. Self-identified race/ethnicity (SIRE) was used as a population descriptor. We calculated a PRS for CHD (PRS CHD , PGS004698), ascertained FH as the presence of pathogenic/likely pathogenic variants in FH genes, and defined FamHx as early-onset CHD in first-degree relatives. We employed Pooled Cohort Equations (PCE) to estimate the 10y risk of CHD for adults ≥40y and modeled the association of conventional risk factors with CHD in adults <40y. AoU served as the training set, and eIV as the testing set. We analyzed the impact of PRS CHD and FamHx on CHD risk estimates by a) using multivariable logistic regression and Cox proportional hazard models, assessing discrimination and the extent of risk reclassification; and b) net benefit analysis and decision curves to assess the performance of prediction models across actionable thresholds. Results: We analyzed data for 19348 participants from eIV (age 50±15, 68% female, 41% non-White) and 239645 participants from AoU (age 55±17, 61% female, 48% non-White). Genetic risk factors were significantly associated with CHD. PRS CHD performance varied by SIRE groups, while FamHx was consistent. The effects of PRS CHD and FamHx on CHD were independent and additive (Figure 1). In adults ≥40y, incorporating PRS CHD and FamHx into PCE improved discrimination (C-statistic increased from 0.719 to 0.753; P -diff=9.1×10 -3 , Figure 2) and reclassified risk in 19% and 20% of participants at the 7.5% and 10% 10y CHD risk thresholds, respectively. Between the 7.5% and 10% 10y CHD risk thresholds, incorporating PRS CHD and FamHx into the PCE improved the net benefit of the risk prediction models across White, Black, and Hispanic/Latino groups (Figure 3). Conclusion: PRS CHD and FamHx were independently and additively associated with CHD in two large diverse cohorts in the US. Incorporating PRS CHD and FamHx into PCE improved risk discrimination, reclassified risk in a significant portion of participants, and improved net benefit of the PCE across all three major SIRE groups, motivating the addition of these factors to clinical risk calculators.

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.

Introduction: Patients with transthyretin amyloid cardiomyopathy (ATTR-CM) typically have low serum transthyretin (sTTR) levels, worsening heart failure, and increased mortality. A recent study has shown the association of sTTR levels ≥20mg/dL with reduced risk of all-cause mortality and cardiovascular mortality (CVM). It has also been shown that regardless of baseline sTTR level, greater increases in sTTR levels are associated with greater improvements in cardiovascular outcomes. Acoramidis, a near-complete (≥90%) TTR stabilizer, demonstrated a rapid and sustained increase from baseline in sTTR by Day 28 and reduced risk of cardiovascular outcomes in patients with ATTR-CM. Hypothesis: Acoramidis-mediated early increase in sTTR levels ≥20 mg/dL (lower limit of normal) at Day 28 reduces risks of CVM and cardiovascular-related hospitalizations (CVH) in patients with ATTR-CM. Methods: Analyses were conducted in the ATTRibute-CM modified intention-to-treat (mITT) population (acoramidis: 409; placebo: 202). The sTTR concentrations (normal range is 20-40 mg/dL) were assessed using an immunoturbidimetric method (Abbott ARCHITECT system) in a central laboratory. The proportion of participants with sTTR levels below normal at baseline and Day 28 were determined. The relationship between sTTR levels <20 or ≥20 mg/dL, at Day 28 across the pooled acoramidis and placebo treatment groups, and subsequent risk of CVM and of CVH over 30 months were analyzed using a stratified log-rank test. Results: At baseline about 25% of study participants had sTTR levels below normal in both treatment groups. At Day 28, less than 2% of participants had sTTR levels <20 mg/dL in the acoramidis arm compared with 26% in the placebo arm ( Table 1 ). When acoramidis and placebo treatment groups were pooled based on sTTR levels <20 or ≥20 mg/dL at Day 28, participants with sTTR ≥20 mg/dL were associated with a lower risk of the composite endpoint of CVM or first CVH at Month 30 in comparison with <20 mg/dL ( p <0.0001) ( Figure 1A ). Comparable findings were observed for the individual components (CVM, first CVH) ( Figure 1B and C ). Conclusion: Across treatment groups, sTTR levels above normal range (≥20 mg/dL) at Day 28 were associated with a lower risk of cardiovascular outcomes at Month 30, when compared with sTTR levels below normal range (<20 mg/dL). Thus, these observations demonstrate that higher sTTR levels over time may have the potential for clinical benefits in both CVM and CVH.

Abstract Purpose: Mouse models demonstrate a role for RANK and its ligand, RANKL, in osteosarcoma. The primary objective of this single-arm, open-label phase 2 trial was to determine whether denosumab, a RANKL mAb, improved disease control in recurrent osteosarcoma relative to benchmarks derived from historic Children’s Oncology Group clinical trial data. Patients and Methods: Skeletally mature patients ages 11 to 49 years old with measurable disease were eligible for cohort 1, and those with complete surgical resection of all sites of disease were eligible for cohort 2. Patients received denosumab 120 mg subcutaneously every 4 weeks with calcium and vitamin D supplementation. The primary endpoints were RECIST response and remaining event-free for 4 months for cohort 1 and remaining event-free for 12 months for cohort 2. Toxicity, pharmacokinetics, and pharmacodynamic effects were additional endpoints. Results: Fifteen patients in cohort 1 and 38 in cohort 2 were eligible and evaluable for the primary endpoint. One of 15 cohort 1 patients remained event-free at 4 months. There were no objective responses. Ten of 38 cohort 2 patients were event-free at 12 months. The predefined efficacy criteria were not met in either cohort. The most common ≥ grade 3 adverse events were hypocalcemia and hypophosphatemia (8% and 11%, respectively). At steady state, mean serum denosumab trough concentrations were 23.7 to 31 μg/mL in cycles 2 to 7. Serum c-telopeptide and urine n-telopeptide decreased on treatment. Conclusions: Denosumab was well-tolerated with anticipated side effects and pharmacokinetic and pharmacodynamic parameters but had insufficient activity for further development in osteosarcoma.