Arteriosclerosis, Thrombosis, and Vascular Biology

Micro- and nanoplastics (MNPs) are increasingly detected in human tissues, yet their causal contribution to cardiovascular disease remains poorly understood. Here we show that oral exposure to polyethylene (PE) and polyvinyl chloride (PVC) -- the most abundant polymers found in human atheromas -- accelerates atherosclerosis in ApoE-/-mice through distinct, polymer-specific molecular mechanisms. While both polymers increased plaque burden and reduced contractile smooth muscle cell (SMC) markers, single-cell transcriptomic profiling revealed divergent phenotypic trajectories. PE exposure drives SMCs toward a chondromyocyte-like cell (CMC) state, characterized by upregulated osteogenic signaling and markedly increased vascular calcification. Conversely, PVC exposure promotes a fibromyocyte-like program associated with altered collagen metabolism and accelerated cell migration without enhancing calcification. These distinct SMC programs are reflected in the transcriptional signatures of symptomatic human carotid plaques, suggesting clinical relevance for polymer-specific vascular remodeling. Our findings establish a causal link between common environmental plastics and accelerated atherosclerosis, demonstrating that MNP-induced vascular risk is mediated by divergent SMC fate decisions. These results provide a mechanistic framework for assessing the cardiovascular impact of global plastic pollution and identifying potential therapeutic targets to mitigate MNP-associated vascular toxicity.

BackgroundThe comparative roles of triglyceride-rich lipoproteins (TRLs) and low-density lipoproteins (LDLs) in abdominal aortic aneurysm (AAA) pathogenesis are unclear. ObjectivesTo evaluate the putative causal role of TRLs in AAA, quantify the relative effect on AAA risk ("aneurysmogenicity") of TRL vs LDL particles, and prioritize lipid-lowering drug targets for AAA prevention and treatment. MethodsWe performed summary-level and individual-level Mendelian randomization (MR) analyses. Genetic variants were selected from 383,983 UK Biobank participants and ranked into 10 sets of variants where set 1 predominantly affected LDL cholesterol (LDL-C) and set 10 predominantly affected TRL cholesterol (TRL-C; and with mixed effects for intermediate variant sets). AAA outcome data were obtained from AAAgen (37,214 cases), FinnGen (4,439 cases), and the VA Million Veteran Program (MVP; 23,848 cases). Multivariable MR was used to assess the independent roles of LDL-C and TRL-C in AAA. For each set of variants, MR or logistic regression was used to estimate AAA odds ratios (ORs) per 10 mg/dL higher apolipoprotein B (apoB). Interaction analyses were conducted between a statin-like LDL-C-lowering variant set (set 3) and a TRL-C-lowering variant set (set 10). Drug-target MR was performed to evaluate lipid-lowering targets relevant to LDL-C- and TRL-C-lowering. ResultsGenetically predicted LDL-C and TRL-C concentrations were each associated independently with genetic liability for AAA after mutual adjustment, with 3.0 to 5.5 times stronger associations for TRL-C compared to LDL-C on a per-cholesterol basis. In AAAgen, the AAA OR per 10 mg/dL increased apoB concentrations were 1.10 (95% CI, 1.05-1.14) for variant set 1 (LDL-C-predominant) and 1.89 (95% CI, 1.69-2.11) for variant set 10 (TRL-C-predominant). Using the ratio of log(OR) per 10 mg/dL apoB for set 10 versus set 1 as a conservative estimate of relative aneurysmogenicity, TRLs were approximately 3.2 to 6.9 times more aneurysmogenic than LDLs across the three studies. No evidence of interaction was observed between LDLs and TRLs, indicating additive contribution to AAA risk. Drug-target MR supported strong protective associations for genetically proxied inhibition of TRL-pathway targets, particularly APOC3 and LPL, with AAA risk. ConclusionsTRLs are at least threefold more aneurysmogenic than LDLs on a per-particle basis. Therapeutic strategies targeting TRL-C --especially via APOC3 and LPL--should be prioritized for AAA prevention and treatment.

BackgroundHypertension affects over 30% of adults and is the leading risk factor for cardiovascular disease. It often presents without obvious symptoms, meaning that, although effective therapies exist, hypertension remains widely undiagnosed and insufficiently treated. Genomics-based prediction methods have shown only modest benefits for these disorders, but proteomic markers have demonstrated potential for greater predictive and clinical value. MethodsWe applied a novel machine-learning based patient stratification analysis pipeline to proteomics data for 7,086 hypertension patients from UK Biobanks Pharma Proteomics Project cohort (2,911 proteins). We evaluated the contribution of each protein to the output of a tree-based risk model to explore the combinations of protein expression values that naturally separate hypertension cases into clusters and assessed the prevalence of cardiovascular and renal complications within each obtained cluster. ResultsWe identified 10 clusters of hypertension patients segregated by differential expression of HAVCR1, PLAT, PTPRB, REN and RTN4R. Four of these clusters showed statistically significant enrichment for cardiovascular and renal complications, and three of them had significantly lower prevalence of complications than expected among hypertension patients. ConclusionWe hypothesize that the hypertension clusters identified may represent distinct mechanistic subtypes. With further study this could help focus studies on subgroups of hypertension patients with a shared disease etiology, identify more personalized precision medicine treatment options for each subgroup, and develop mechanism-based biomarker tests to support enriched clinical trial recruitment.

BackgroundHDL particles can carry microRNAs (miRNAs), capable of regulating gene expression connected to HDL functions. Despite links to some cardiovascular risk factors, miRNA association with incident acute myocardial infarction (AMI) remains unclear. ObjectivesOur aim was to elucidate the association between HDL-bound miRNAs (HDL-miRNAs) and incident AMI using a non-targeted approach in a population-based study. MethodsWe conducted a case-cohort study including 247 participants from the REGICOR cohort in northeastern Spain (51 AMI cases and a random sample of 196 participants, including seven overlapping AMI cases). HDL-miRNAs were isolated from apolipoprotein B-depleted serum and quantified by whole-genome miRNA sequencing. Associations between HDL-miRNAs and incident AMI were assessed using multivariable Cox proportional hazards model. For AMI-associated HDL-miRNAs (p-value <0.10), we retrieved their experimentally validated targets and assessed pathway enrichment of these targets via over-representation analysis. ResultsTwo HDL-miRNAs were associated with incident AMI after FDR correction: miR-628-3p (HR 1.69, 95% CI 1.30 to 2.19) and miR-28-3p (HR 1.58, 95% CI 1.21 to 2.06). Nine additional HDL-miRNAs were nominally associated with AMI incidence (p-value <0.05), eight with a direct association (miR-93-5p, miR-26b-5p, miR-106a-5p, miR-126-3p, miR-15b-5p, let-7a-5p, let-7e-5p, and let-7f-5p) and one with an inverse association (miR-361-5p). These miRNAs regulate the expression of genes in pathways involved in cholesterol regulation, particularly cholesterol efflux and homeostasis. The AMI group exhibited higher variance and a greater number of significant and strong correlations. ConclusionsTwo HDL-miRNAs (miR-628-3p and miR-28-3p) were significantly associated with AMI incidence. A tighter coregulatory network in cases was observed, underscoring their potential clinical utility in risk prediction and cardiovascular prevention. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIIn a population-based case-cohort study we profiled the HDL-bound miRNome and found two miRNAs (miR-628-3p and miR-28-3p) associated with incident AMI. C_LIO_LIThe use of HDL-enriched serum fractions provided a focused analysis on HDL functionality. These miRNAs regulate the expression of genes in pathways involved in cholesterol efflux and homeostasis (ABCA1, ARL4C, SIRT1, NFKBIA, ANXA2, LRP6) and show a tighter coregulatory network among significant miRNAs among cases, supporting biological coherence. C_LI What Are the Clinical Implications?O_LIHDL-miRNA signatures may complement traditional risk factors to refine AMI risk stratification and provide a rationale for HDL-guided, miRNA-targeted preventive interventions using HDL-like delivery platforms. C_LI

BackgroundSex hormone alterations, such as estrogen deficiency or testosterone excess, substantially increase cardiovascular disease (CVD) risk in females. Dietary fibre and its microbial by-products, short-chain fatty acids (SCFAs), have cardioprotective effects, but it remains unclear whether these benefits extend to females with an altered sex hormone profile. In this study, we aim to investigate whether dietary fibre intake, measured via plasma acetate--the most abundant SCFA--is associated with improved cardiovascular outcomes in females with altered sex hormone profiles. MethodsThis cohort study included 116,235 female participants from the UK Biobank and Biobank Japan with up to 10 years of follow-up. We analysed early menopause (as a surrogate for estrogen insufficiency) and plasma free testosterone (in a subset). The primary outcome was major adverse cardiovascular events (MACE). Secondary outcomes were blood pressure. Proteomics analyses explored potential mechanisms. ResultsAcetate levels were associated with lower 10-year MACE incidence (-0.618/1000 woman-year, HR=0.900, p=0.002) and systolic blood pressure (-0.231 mmHg per 1 SD, p<0.001) in the UK Biobank. High acetate levels attenuated the increased MACE risk associated with early menopause (HR=1.158, p=0.057) compared with low acetate (HR=1.425, p<0.001), with similar patterns replicated in Biobank Japan (high: HR=1.322, p=0.090; low: HR=1.385, p=0.042). Proteomics analyses suggested a mechanism involving pro-inflammatory proteins. Moreover, high acetate levels attenuated the increased MACE associated with elevated free testosterone in the UK Biobank (high: HR=1.238, p=0.024; low: HR=1.056, p=0.666). A significant interaction between acetate and free testosterone on systolic blood pressure indicated that the effect of rising testosterone on blunting acetates effect ({beta}=0.167, 95% CI: [5.212x10-2-2.818x10-1], p=0.004) was partially mediated by central obesity (waist-to-hip ratio). ConclusionsHigher plasma acetate levels were associated with lower cardiovascular risk, particularly in females with early menopause or elevated free testosterone, potentially via inflammatory pathways. These findings underscore the importance of hormonal context in shaping cardiometabolic resilience and support personalised CVD prevention strategies for females with altered sex hormone profiles, including increasing dietary fibre intake.

BackgroundCirculating lipoprotein(a) [Lp(a)] levels are highly heritable and linked to atherosclerotic cardiovascular disease, yet clinical measurement rates remain low (<1%) in the United States. The high heritability of Lp(a) across populations makes genetic prediction an attractive approach for closing this testing gap, but existing polygenic scores transfer poorly across populations. Haplotype-based prediction models, which use standard genome-wide genotype data to capture common-, rare-, and structural-variation at the LPA locus, could bridge this gap, enabling opportunistic identification of individuals with elevated Lp(a) levels across diverse populations within existing large, genotyped cohorts. ObjectivesThis study sought to develop and validate a haplotype-based prediction model using genome-wide genotype data to identify individuals with elevated Lp(a) levels across diverse populations. MethodsWe developed an LPA-haplotype model using data from the All of Us Research Program and validated it in the Penn Medicine BioBank (PMBB), Mass General Brigham Biobank (MGBB), and Mount Sinai BioMe cohorts. Primary outcomes included model performance for predicting continuous Lp(a) concentrations (r{superscript 2}) and identifying elevated Lp(a) levels (>125 nmol/L) through positive predictive value (PPV) and number needed to test (NNT). ResultsAmong PMBB (n = 1856), MGBB (n = 1401), and BioMe (n = 1686) participants with available genotype and Lp(a) measurements, average age was 60 years, and 51% were female. Overall r{superscript 2} of the haplotype model was 0.46 (95% Credible Interval [CrI] 0.32 to 0.6), with similar performance across genetically inferred ancestries and cohorts. For identifying elevated Lp(a) levels >125 nmol/L the overall PPV was 0.81 (95% CrI 0.6 to 0.89), corresponding to a NNT of 1.2 (95% CrI 1.1 to 1.7) individuals predicted to have elevated levels needing to undergo clinical testing to identify one true elevation. In the full PMBB cohort (n = 49310), the haplotype model identified elevated Lp(a) at a rate of 128 per 1000 (95% CrI 125 to 130), corresponding to an estimated 14.4-fold improvement (95% CrI 13.1 to 15.9; P(improvement) = 1) in identification rate compared with the existing rate of clinical assessment. ConclusionsA haplotype-based genetic model effectively identified individuals with elevated Lp(a) levels across diverse populations, with potential utility for opportunistic screening among cohorts where genotype data is available, but Lp(a) testing rates are low.

BackgroundInhaled combusted cannabis and co-use of combusted cannabis and nicotine electronic cigarettes (nECIGs) are on the rise, yet their long-term cardiovascular risk is unclear due to the high prevalence of confounders in observational human studies. Using primary plasma and monocytes and a novel ex vivo mechanistic model of two early steps in atherogenesis, this study examined whether chronic combusted cannabis use is associated with atherogenic changes, as estimated by 1) monocyte transendothelial migration (MTEM), and 2) monocyte-derived foam cell formation (MDFCF), and whether nECIG co-use further amplifies this risk. MethodsA cross-sectional parallel group comparison study was conducted in healthy adults (21-30 years) who chronically 1) used combusted cannabis, 2) co-used both combusted cannabis and nECIGs, and 3) were non-using controls. Using our ex vivo atherogenesis assay, primary outcomes of MTEM, MDFCF, and median fluorescence intensity (MFI) of the lipid-staining fluorochrome BODIPY were determined using primary plasma and autologous primary monocytes from participants. Using flow cytometry and the fluorochrome CELLROX, cellular oxidative stress (COS) in monocytes was determined. ResultsOf the 134 participants, 59 used cannabis, 26 co-used cannabis/nECIG, and 49 were non-using controls. The groups had similar age, sex, and race. Median MTEM was 1.13 fold greater in people who used cannabis compared to non-users 27.8% (IQR 26.1:29.2%) vs 24.5%, (IQR 22.9:27.4%), p<0.0001, and tended to be greater in people who co-used cannabis/nECIG by 1.22-fold 34.1%, (IQR 29.9:38.3%, p=0.17). Median MDFCF and MFI were also increased in people who used cannabis compared to non-users (MDFCF 36.3%, IQR 31.8:35.8%, vs 26.6%, IQR 23.8:25.8%, 1.36-fold and MFI 1163.8, IQR 1042.8:1155.0, vs 940.2 IQR 849.9:1101.4, 1.24-fold) and were further increased in people who co-used cannabis/nECIG (MDFCF 48.7%, IQR 37.3:52.4%, 1.34-fold, MFI 1433.7, IQR 1263.8:1686.4, 1.23-fold; all comparisons p<0.008). Foam cell formation, but not transendothelial migration, was strongly positively correlated with COS. All primary outcomes increased with greater frequency of cannabis and/or nECIG use. ConclusionsIn healthy young adults, exclusive cannabis use is associated with increased atherogenic properties of monocytes and plasma, and this atherogenic effect is further amplified by co-use of nECIGs.

Anti-{beta}2-glycoprotein I (anti-{beta}2GPI) antibodies are central to the pathogenesis of antiphospholipid syndrome (APS), an autoimmune disease characterized by a strong predisposition to venous thromboembolism (VTE). In this study, we conducted a multi-ancestry genome-wide association study (GWAS) of quantitative total anti-{beta}2GPI levels in 5,969 participants enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA) and identified a genome-wide significant association at the APOH locus. Paradoxically, genetically determined increases in anti-{beta}2GPI levels at this locus were associated with lower VTE risk. Fine-mapping and functional genomics prioritized the missense variant rs1801690 (W335S) in {beta}2GPI (apolipoprotein H, [APOH]) as the most likely causal variant. This variant has an allele frequency of 5-6% in European and East Asian ancestries but only 1% in African ancestries. Integrating prior experimental studies, molecular dynamics simulations and structure-based epitope prediction, we propose a dual-effect mechanism whereby W335S reduces thrombotic risk by disrupting phospholipid binding in Domain V, yet increases autoantibody production through conformational changes that enhance epitope exposure in Domains I and II. These findings mechanistically uncouple autoantibody formation from thrombotic risk in carriers of the W335S variant, and suggest that APOH genotype may represent a clinically relevant genetic biomarker with potential utility for thrombotic risk stratification in anti-{beta}2GPI-positive individuals.

Pulmonary hypertension (PH) is a progressive condition characterized by increased pulmonary arterial pressure. Endothelial cell dysfunction is one important characteristic of PH. Recently, capillary endothelial cells, including aerocytes (aCaps) and general capillary cell (gCaps), have been detected in developing lungs but their role and the regulatory mechanisms underlying PH remain poorly understood. The goal of this study was to identify changes in Caps and their effects on hypertensive pulmonary circulation. We set up a Capillary Alveoli Micro-physiological System (CAMS) incorporated with hPSCs(human pluripotent stem cells)-aCaps to show loss of Cap connection under dynamically cultured hypoxic condition. We employed single-cell RNA sequencing (scRNA-seq) and immunofluorescence to demonstrate impaired gCaps differentiation with increased expression of cell membrane receptor CD93 in PH patients and a Sugen 5416/hypoxia (SuHx) rat model. Conditional Knockdown or Lentiviral overexpression of CD93 alleviated the pathology observed in SuHx mice. We also revealed that CD93 overexpression upregulated SMAD2/3 to repress Apelin (APLN) expression by CHIP assay. Finally, supplementation with an APLNR agonist in the PH rat model promoted gCaps-to-aCaps differentiation and improved haemodynamic indices. Overall, our results highlight the potential for promoting capillary cell differentiation with G protein biased APLNR agonist as a therapeutic strategy for pulmonary vascular disease.

BackgroundMetabolic vulnerability index (MVX), a novel biomarker of systemic inflammation and metabolic malnutrition, is associated with mortality in patients with cardiovascular diseases. Nevertheless, little is known about its association with cardiometabolic diseases (CMDs) and multimorbidity (CMM). We aimed to examine the associations of MVX with the risk of individual CMDs, their progression to CMM, and all-cause mortality in the general population. MethodsIn a prospective cohort of 218,635 UK Biobank participants free of CMDs, MVX was calculated based on plasma metabolomics data. CMM was defined as coexistence of two or more CMDs, including coronary heart disease (CHD), stroke, and type 2 diabetes mellitus (T2DM). Cox proportional hazard and multi-state models were employed to evaluate the associations of MVX with the risks of individual CMDs, CMM, and all-cause mortality. ResultsDuring a median follow-up of 14.4 years, 27,805 (12.7%) participants developed at least one CMD, 3,006 (1.4%) progressed to CMM, and 14,211 (6.5%) died. Each standard deviation increase of MVX score was associated with 9% (95% confidence interval: 8%-10%), 11% (7%-15%), and 12% (10%-14%) higher risks of developing CMDs, CMM, and mortality, respectively. The MVX-CMM associations were more prominent in females and in the sequential onset pattern of T2DM followed by CHD or stroke. Multi-state model analysis further uncovered consistent associations between higher scores of MVX and higher risks of transitions from CMDs free to CMD, subsequently to CMM, and to death. ConclusionsHigher MVX scores were significantly associated with higher risks of incident CMDs, their progressions to CMM, and all-cause mortality. These results underscored the potential of MVX in the primary prevention and management of CMDs and CMM.

Gout is driven by an interleukin-1{beta}-mediated intense innate immune reaction to monosodium urate (MSU) crystals (MSUc). In cell culture models of inflammatory gout there is a synergistic effect of phagocytosis of MSUc and TLR2 and TLR4 activation by agonists such as free fatty acid and lipopolysaccharide (LPS) in NLRP3-inflammasome activation and IL-1{beta} secretion. A substantial number of gout patients do not report a dietary trigger, and observational studies associate airborne particulate matter with incident gout and flares. Airborne particulate matter contains LPS and airborne-derived particulate matter stimulates IL-1{beta} secretion in cell culture. We hypothesized that air-borne particulate matter could co-stimulate, with MSUc, IL-1{beta} secretion and inflammation. We tested the hypothesis using MSUc with extracted airborne PM4 in human cells (the THP-1 monocyte cell line, primary human monocytes and PBMCs) or carbon black particles with ozone (CB+O3) in a murine foot-pad injection model of gout. There was strong NLRP3-inflammasome-dependent co-stimulation of IL-1{beta} secretion in THP-1 cells with PM4+MSUc and a moderate additive effect in primary human PBMCs. However, there was no added effect on IL-1{beta} secretion of PM4 in isolated primary human monocytes. Inhalation of CB+O3 persistently exacerbated MSUc-induced murine paw inflammation, with an increase of alveolar/lavage macrophages that contained CB+O3 particles and increased lavage expression of IL-1{beta}. In conclusion, airborne-derived PM4 particulate matter enhanced MSUc-induced IL-1{beta} secretion in THP-1 cells and PBMCs. Combined with exacerbation of MSUc-induced inflammation by fine particulate matter in in vivo experiments, these data provide evidence that exposure to fine particulate matter may play a role in the etiology of gout.

BackgroundEvolocumab promotes coronary plaque regression in patients with coronary artery disease, but little is known regarding carotid plaques (CP). This study aimed to evaluate the impact of evolocumab on top of lipid-lowering therapy (ELLT) on carotid morphological stabilization (MS) and plaque regression (PR) compared to lipid-lowering therapy (LLT) alone. MethodsAsymptomatic patients with internal carotid stenosis[&ge;]50% and LDL-C[&ge;]100 mg/dL were randomized to ELLT or LLT and monitored by serial duplex ultrasound. The primary endpoint was a composite of 6-month-MS (i.e., switch from morphologic types I-II to III-IV) and/or 12-month-PR (i.e., reduction of carotid stenosis by at least 5% compared to baseline). The secondary endpoint was LDL-C change at 12 months. Major adverse vascular events (MAVE, i.e., cardiac death, stroke, myocardial infarction, carotid or coronary or peripheral revascularization) were recorded. ResultsA total of 170 patients were randomized. Mean carotid stenosis was 57%. At 6 months, MS occurred in the ELLT group (10.3%) only (p=0.29). At 12 months, PR was numerically more frequent in the ELLT group, without reaching statistical significance (43% versus 35.1%, p=0.42). The primary endpoint was met in 44.3% versus 35.1% (p=0.26). As compared to baseline, 6 and 12-month shifts from low to high-risk types were significantly higher in the LLT group (p=0.03). The 12-month LDL-C percentage reduction was -73.5% with ELLT, and -48.3% with LLT (p=0.0001). At 1 year, MAVE were significantly more frequent with LLT (14.6% versus 2.4%, p=0.005), and the absence of evolocumab was the only predictor (OR 7, p=0.014). ConclusionsIn patients with CP[&ge;]50% and LDL-C[&ge;]100 mg/dL, ELLT compared to LLT was associated with numerically but not statistically higher 6-month MS and/or 12-month PR. In the LLT group, 6- and 12-month changes from low to high-risk types, LDL-C, and MAVE were significantly higher. According to these results, evolocumab should be considered standard treatment for patients with CP[&ge;]50%. The study was registered at www.clinicaltrials.gov (NCT04730973) and Eudract (2020-005663-31). SHORT ABSTRACTPatients with carotid stenosis[&ge;]50% and LDL-C[&ge;]100 mg/dL were randomized to evolocumab on top of optimal lipid-lowering therapy (ELLT) or optimal lipid-lowering therapy (LLT) alone to assess the impact of ELLT on carotid plaque morphological stabilization (MS) and plaque regression (PR). At 6 and 12 months, MS and PR occurred in both groups, but were numerically higher in the ELLT group, without reaching statistical significance. In the LLT group, 6- and 12-month changes from low to high-risk types were significantly higher, and the rate of adverse vascular events was sevenfold higher. Evolocumab might become the standard treatment for patients with carotid artery stenosis [&ge;]50%. CLINICAL PERSPECTIVEO_ST_ABSWhat is new?C_ST_ABSO_LIThe CARUSO is the largest randomized trial evaluating the impact of evolocumab on top of lipid-lowering therapy (ELLT) on carotid morphological stabilization (MS) and plaque regression (PR) monitored by serial duplex ultrasound. C_LIO_LIThe primary endpoint was a composite of 6-month-MS (i.e., switch from morphologic types I-II to III-IV) and/or 12-month-PR (i.e., reduction of carotid stenosis by at least 5% compared to baseline) and was numerically higher in the ELLT group compared to lipid-lowering therapy (LLT) alone, without reaching statistical significance. C_LIO_LIThe 1-year rate of major adverse vascular events (MAVE) was sevenfold higher in the LLT group. C_LI What are the clinical implications?O_LICarotid plaque morphology is a dynamic event, and 6 and 12-month shifts from low to high-risk morphological types were significantly higher in the LLT group, thus suggesting that evolocumab added to LLT may prevent morphological deterioration. C_LIO_LIThe absence of evolocumab was the only independent predictor of MAVE; according to our results, ELLT might become the standard treatment for patients with carotid plaques [&ge;]50% and LDL-C not at target. C_LIO_LIFuture larger studies are warranted to validate our findings, assess long-term adherence to therapy, and identify subgroups with higher probability of achieving MS and PR. C_LI

BackgroundCardiovascular (CV) disease risk is increased in rheumatoid arthritis (RA) and is the leading cause of mortality. Improved CV risk stratification tools in RA could enhance use of preventative care and improve outcomes. MethodsWe previously studied biomarkers of CV disease - adiponectin, hsCRP, Lp(a), osteoprotegerin (OPG), high-sensitivity cardiac troponin T (hsTnT), serum amyloid A (SAA), YKL-40, soluble TNF receptor1 (sTNFR1) -- that were associated with CV risk. In the current study, these biomarkers were tested in an unrelated external cohort of RA patients followed at a single academic medical center without a history of CV events. CV events were identified through Medicare and Medicaid administrative data or through medical record review of self-reported events. Biomarkers were assessed at cohort entry among a nested cohort of cases and controls, matched 1:1 on sex and age. Analyses were conducted using conditional logistic regression. We examined whether the candidate biomarkers added to clinical CV risk factors improved model prediction, using the area under the curve (AUC) as well as the net reclassification index (NRI). ResultsFrom a cohort of 1,345 eligible patients with RA, we identified 123 patients with confirmed CV events. Cases and matched controls were typical of RA: median age 63 years, 77% women, RA disease duration 11 years, 72% seropositive, 85% used a biologic or conventional disease modifying anti-rheumatic drug, 58% non-steroidal anti-inflammatory drugs, and 30% oral glucocorticoids. From the candidate biomarkers, LASSO regression selected hsTnT and sTNFR1 as associated with CV events. The AUC for models that included only clinical risk factors was 0.758 (95% CI 0.689-0.829); after adding hsTnT and sTNFR1, the AUC increased to 0.802 (95% CI 0.718-0.998). The NRI of the model with biomarkers was 16.3%, with improvement only observed in patients who did not have CV events during follow-up. ConclusionsAdding selected biomarkers to clinical risk factors enhances the discrimination of models predicting CV events among patients with RA. These risk models require prospective testing to see if they have value in clinical practice decision-making regarding preventative care.

Computational growth and remodeling (G&R) models have been extentively used to investigate abdominal aortic aneurysm (AAA) progression and to support clinical decision-making. However, the development of robust predictive models is often limited by the scarcity of large-scale longitudinal imaging datasets. In this study, we propose a physics-based G&R framework to simulate AAA shape evolution and generate a virtual cohort of aneurysms, thereby addressing data limitations and enabling integration with data-driven machine learning approaches for growth prediction. The proposed arterial G&R model incorporates key mechanisms influencing aneurysm progression, including elastin degradation and stress-mediated collagen production. A modified elastin degradation formulation was introduced to generate realistic aneurysm geometries exhibiting clinically relevant features such as asymmetry and tortuosity. By systematically varying parameters governing elastin damage and collagen production, 200 distinct G&R simulations were performed to produce a diverse set of AAA geometries. The dataset was further expanded using kriging-based spatial interpolation to construct a large in silico cohort. The synthetic dataset, combined with longitudinal imaging data from 25 patients, was used to train and validate four machine learning models: Deep Belief Network (DBN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). A two-step training strategy was adopted to predict maximum aneurysm diameter and growth rate based on prior geometric characteristics. The LSTM model achieved the highest performance for maximum diameter prediction (R{superscript 2} = 0.92), while the RNN demonstrated strong overall performance (R{superscript 2} = 0.90 for maximum diameter and 0.89 for growth rate). The DBN and GRU models also showed competitive predictive capability. Overall, this study demonstrates that integrating physics-based G&R simulations with machine learning enables accurate prediction of AAA growth and maximum diameter. The proposed framework provides a scalable strategy for augmenting limited clinical datasets and offers a promising tool to support personalized risk assessment and treatment planning.

Current clinical risk stratification for thoracic aortic aneurysms (TAA) relies primarily on maximum diameter, which is a poor predictor of rupture. Recent fluid-structure interaction studies have identified a dimensionless "flutter instability parameter" (N{omega} ) that accurately classifies abnormal aortic growth. However, this parameter currently serves as a static diagnostic snapshot. In this work, we propose a proof-of-concept computational framework that links flutter instability to microstructural tissue damage via a coupled system of ordinary differential equations (ODEs). We model a feedback loop where flutter-induced energy dissipation drives elastin degradation and collagen remodeling, which in turn reduces wall stiffness and amplifies the instability. To address the challenge of unobservable tissue properties, we implement a Bayesian inference engine to infer model parameters. We demonstrate feasibility on a synthetic patient cohort calibrated to published clinical growth rates and diameters. Our results show that this approach can infer hidden damage parameters and capture the qualitative bifurcation between stabilizing remodeling and runaway aneurysm expansion. While validation on real patient data remains essential, this work establishes the mathematical foundation for transforming a static physiomarker into a personalized prognostic trajectory.

The present study presents a systematic approach for generating data-driven synthetic cerebral aneurysm geometries and evaluating their hemodynamics through computational fluid dynamics. Seven patient-specific aneurysm geometries from the right internal carotid artery were reconstructed from time-of-flight magnetic resonance angiography images and standardized through orientation alignment, followed by non-rigid registration onto a common spherical point cloud as a template. Principal component analysis (PCA) was then applied to the aligned point-cloud data to quantify morphological variability and parameterize shape deformation. The first four principal components captured over 90% of the total variance; however, higher-order components were required to capture the detailed geometrical features of the original geometries. Computational fluid dynamic simulations were performed on the PCA-based synthetic geometries under pulsatile flow conditions to investigate the influence of shape variations on intra-aneurysmal flow patterns, time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI). The first principal component score (PCS1), which was associated with changes in aneurysm height and dome width, had the strongest effects on TAWSS and OSI levels. Lower PCS1 values, which corresponded to taller and more oblique domes, produced slower adjacent flow and elevated OSI, whereas higher PCS1 values increased TAWSS. The second principal component score primarily modulated lateral geometric asymmetry and further influenced OSI distribution for the lower PCS1 values. Collectively, these findings indicate that PCA-based shape parameterization provides a practical approach for generating synthetic aneurysm datasets and systematically assessing how specific morphological features govern hemodynamic behavior. The proposed approach is expected to contribute to the future development of surrogate modeling and data-driven hemodynamic prediction.

BackgroundThe molecular drivers distinguishing valvular heart disease-associated atrial fibrillation (VHD-AF) from other AF etiologies remain poorly defined, with prior transcriptomic studies largely focused on non-valvular AF. MethodsWe performed RNA sequencing on peripheral blood mononuclear cells (PBMCs) from 15 patients with VHD-AF and 15 age- and sex-matched healthy controls. Bioinformatic analyses identified differentially expressed genes (DEGs), enriched pathways, and protein-protein interaction (PPI) networks. ResultsWe identified 3,308 DEGs (2,891 upregulated, 417 downregulated) in VHD-AF patients. Functional enrichment revealed two dominant mechanisms: (i) a pronounced systemic inflammatory response, with significant enrichment in cytokine-cytokine receptor interaction (P=1.2e-15) and TNF signaling pathways (P=3.4e-08); and (ii) a core epigenetic module centered on nucleosome assembly (P=8.9e-12) and histone-related genes. PPI network analysis identified a high-confidence hub module (Cluster 1) overwhelmingly composed of histone genes (e.g., H4C6, H3C13). ConclusionThis first PBMC transcriptomic map of VHD-AF reveals a convergent pathology of chronic inflammation and widespread epigenetic remodeling. The findings nominate TNF inhibition and histone-modifying agents as potential therapeutic strategies and position PBMC-derived signatures as minimally invasive biomarkers for this specific AF population.

Background and aims Iron deficiency (ID) and myocardial iron depletion (MID) are causally linked to heart failure (HF) in the general population and in preclinical models. ID is common amongst pregnant women, but its impact on cardiac adaptations to pregnancy is unknown. This study examines that impact, and its potential relevance to peripartum cardiomyopathy (PPCM). Methods. We provided female mice with iron-replete or iron-deficient diets, and monitored cardiac function and morphology longitudinally in pregnancy and postpartum. In women with no HF (n=64), we explored the associations between antenatal iron parameters and echocardiographic parameters in late pregnancy and at 6-12 months postpartum. We also performed a case (n=55), control (n=170) study comparing iron markers and assessing their association with PPCM risk. Results In mice, ID prevented postpartum reversal of pregnancy-induced hypertrophy, reduced postpartum LVEF, and caused profound MID. In women with no HF, low hepcidin, high transferrin and low serum iron were respectively associated with higher LVESV, lower LVEF and higher CMR T1-mapping (lower myocardial iron) in postpartum. In the PPCM study, serum iron, hepcidin and haemoglobin were significantly lower in cases than controls, and were independently associated with risk of PPCM. Mechanistically, myocardial proteomics revealed that ID caused sustained postpartum activation of pyruvate dehydrogenase kinase 4, a master cardiometabolic switch enzyme with a well-recognised role in HF. Conclusions This study links antenatal maternal ID to postpartum systolic dysfunction, and implicates MID and cardiometabolic switching as potential mechanisms. It suggests these links may potentially contribute to the pathophysiology of PPCM

BackgroundAnthracyclines are central to childhood cancer therapy but predispose patients to cardiotoxicity leading to long-term cardiovascular risk. Endothelial injury and impaired repair contribute to this, yet pediatric data remain limited. ObjectiveTo longitudinally assess endothelial injury and repair in childhood cancer patients treated with anthracyclines by quantifying circulating endothelial cells (CECs) and endothelial progenitor cells (EPCs). MethodsIn a single-centre retrospective cohort, children (<18 years) diagnosed with leukemia (n=35) or lymphoma (n=13) were studied at four timepoints: pre-treatment ("Pre"), [~]1-month- ("End"), 3 months- (3M), and 1 year- (1Y) post-treatment. Peripheral blood mononuclear cells were analyzed by flow cytometry to quantify CECs and EPCs, and EPC fate was assessed by p16 (senescence) and Annexin V (apoptosis). Cardiac injury biomarkers and left ventricular function were assessed at each timepoint. ResultsLongitudinal trends of CEC and EPC counts were similar between leukemia and lymphoma participants. CECs were highest at pre-treatment and declined significantly thereafter, though they remained marginally elevated during remission compared with healthy controls, indicating that endothelial damage had largely subsided following treatment. EPCs were also highest at pre-treatment and decreased to levels below healthy controls during remission, suggesting impaired baseline endothelial maintenance and repair. Furthermore, EPCs were predominantly senescent up to 1-year post-treatment. ConclusionsEndothelial injury resolves by treatment completion, but repair remains impaired during remission with EPC pools dominated by senescent cells. This suggests defective endothelial regeneration, rather than persistent injury, drives long-term cardiovascular complications and underscores the need to restore EPC viability and function in childhood cancer survivors.

BackgroundInflammation plays a key role in atrial fibrillation (AF) pathogenesis. The empirical dietary inflammatory potential (EDIP) score predicts circulating inflammatory biomarkers and adverse cardiac outcomes, but its association with incident AF is unclear. This study aimed to examine the relationship between EDIP score and AF risk. MethodsParticipants from the Atherosclerosis Risk in Communities (ARIC) free of baseline AF who completed a validated food frequency questionnaire were included. Correlation of EDIP with inflammatory biomarkers (factor VIII, fibrinogen, von Willebrand factor, and C-reactive protein) was examined at baseline. Incident AF was ascertained using electrocardiograms, hospital records, and death certificates. Cox proportional hazards models estimated hazard ratios of AF across EDIP quantiles and per SD increase, adjusting for sociodemographic and cardiovascular risk factors. ResultsAmong 8,277 participants (54.1 years old, 51.3% women, 80% white), higher EDIP score correlated with circulating inflammatory biomarkers at baseline. Over a median 24.2 years of follow-up, 1,453 had incident AF (incident rate 8.6 per 1,000 person-years). Compared with the most anti-inflammatory diet (EDIP Q1), the most pro-inflammatory diet (EDIP Q5) was associated with increased AF risk (HR 1.21; 95% CI 1.03-1.43). Sex-stratified analyses showed a stronger association in men (HR 1.43; 95% CI 1.14-1.79), while no significant association was observed in women. ConclusionsPro-inflammatory dietary patterns are independently associated with higher AF risk in a middle-aged cohort. These findings would support incorporating dietary inflammatory load into AF risk stratification. Clinical Perspective What Is New?O_LIHigher Empirical Dietary Inflammatory Potential (EDIP) scores, indicating a more pro inflammatory diet, were associated with an increased long-term risk of atrial fibrillation (AF) in a large, biracial, community-based cohort followed for over two decades. C_LIO_LISex stratified analyses revealed a significant sex difference: higher EDIP scores were consistently associated with increased AF risk in men, whereas no significant association was observed in women, suggesting sex-specific susceptibility to EDIP. C_LIO_LIObesity modified the association between EDIP and AF, with the strongest risk observed among individuals with BMI [&ge;]30, while an inverse or attenuated association was seen among normal weight participants. C_LI What Are the Clinical Implications?O_LIDietary inflammatory load may serve as a meaningful and modifiable upstream AF risk factor, complementing conventional cardiovascular risk assessment, particularly in men and individuals with obesity. C_LIO_LIIncorporating dietary pattern assessment into routine AF risk stratification may help identify individuals who could benefit most from targeted lifestyle interventions. C_LIO_LIPublic health and clinical prevention strategies promoting anti-inflammatory dietary patterns (e.g., increased intake of fruits, vegetables, and whole grains; reduced intake of processed meats and refined carbohydrates) could meaningfully reduce AF incidence. C_LIO_LIRecognition of sex specific differences in AF pathways reinforces the need for personalized preventive strategies, as diet inflammation mechanisms appear to influence AF development more prominently in men. C_LI