Vascular dysfunction contributes to Alzheimer disease (AD) and related dementias (ADRDs), but the underlying mechanisms remain unclear. Previous studies link midlife hemostasis and platelet aggregation measures to late-life dementia risk. We aimed to determine whether platelet aggregation in midlife is associated with imaging markers of AD pathology. In a cross-sectional study, we evaluated associations between platelet aggregation, measured by light transmission aggregometry, and amyloid (11C-Pittsburgh compound B) and tau (18F-flortaucipir) PET uptake in dementia-free, middle-aged adults from the Framingham Heart Study. Co-primary outcomes included amyloid and tau uptake in AD-vulnerable regions. We also examined an MRI-based cortical thickness signature of AD risk as a secondary outcome. We used multivariable regression models adjusted for demographic and clinical factors, considering potential nonlinear associations. Platelet aggregation response was evaluated in 382 participants (mean age 56 ± 8 years, 53% female) approximately 1.2-1.5 years before amyloid and tau PET imaging. MRI data used for the AD signature were acquired together with PET imaging or within several months. The aggregation response exhibited a nonlinear association with AD pathology. Among those in the lowest tertile of adenosine diphosphate (ADP) response, platelet aggregation response was positively associated with increased amyloid in the precuneus (β = 0.047, p = 0.020) and tau in the rhinal (β = 0.077, p = 0.012), entorhinal (β = 0.066, p < 0.020), temporal global (β = 0.063, p = 0.031), and cortical (β = 0.064, p = 0.028) regions. For the secondary outcome analysis (n = 256), platelet aggregation response was negatively associated with the MRI-based cortical thickness signature of AD risk (β = -0.002, p < 0.035), consistent with a neurodegenerative pattern. Our findings indicate that platelet aggregation is linked to PET and MRI markers of AD pathology as early as midlife. These findings support further investigation of platelet-mediated mechanisms in AD pathogenesis.

Cardiovascular Risk Assessment: Practical Tips for the Internal Medicine Specialist.

BackgroundEmerging evidence suggests that dynamic risk assessment may enhance sudden cardiac arrest (SCA) risk stratification. While cardiovascular events, including acute coronary syndrome (ACS) and heart failure (HF) hospitalization, are associated with increased SCA risk, the impact of recurrent events on subsequent SCA risk in a contemporary, real-world population is unknown. This study aimed to assess whether patients with a first-time ACS or HF hospitalization who experience a recurrent cardiovascular event have higher risk of SCA compared to those who do not.MethodsThe Observational Study of Cardiac Arrest Risk (OSCAR) is a prospective cohort study with adjudicated SCA outcomes. In the current study, patients who survived a first ACS or HF hospitalization were categorized into index ACS or HF cohorts. Participants were followed for recurrent cardiovascular events and SCA. Associations between recurrent events and SCA were assessed using Cox models with recurrent event modeled as a time-dependent variable.Findings were validated in the Framingham Heart Study (FHS).ResultsIn the OSCAR discovery cohort, 2946 patients experienced an index ACS event. The incidence rate of SCA was higher following a recurrent ACS event than without (3.70 vs 1.28 per 100 patient-years). Recurrent ACS event was associated with a significantly higher risk of SCA (adjusted HR 3.15, 95% CI 2.06-4.83, p<0.0001). A total of 6711 patients experienced an index HF hospitalization, and the incidence rate of SCA was higher following a recurrent HF event than without (1.35 vs 0.97 per 100 patient-years). Recurrent HF hospitalization was associated with a significantly higher risk of SCA (HR 1.81, 95% CI 1.46-2.26, p<0.0001).In the FHS validation cohorts a recurrent event during follow-up was associated with a significantly higher risk of SCA in the ACS cohort (HR 2.85, 95% CI 1.66-4.90, p=0.0002), but the association was not statistically significant in the HF cohort (HR 1.49, 95% CI 0.73-3.03, p=0.27).ConclusionRecurrent ACS event was associated with more than threefold higher risk of SCA, and a recurrent HF hospitalization with 80% higher risk of SCA. These findings suggest that dynamic clinical trajectories of recurrent cardiovascular events may inform management and prevention of SCA.Clinical PerspectiveWhat is new?In patients with a first acute coronary syndrome (ACS), those with a recurrent ACS event during follow-up had a threefold higher risk of sudden cardiac arrest (SCA) compared with patients without recurrence.Among patients hospitalized for heart failure (HF) for the first time, those with a subsequent HF hospitalization had nearly double the risk of SCA compared with those without recurrence.What are the Clinical Implications?These findings indicate that individuals with recurrent cardiovascular events are at higher risk of sudden cardiac arrest.These dynamic risk trajectories may inform management of these patients as well as improved prevention of sudden cardiac arrest.Future prospective studies are needed to test these findings in larger and more diverse populations.

Mediation analysis is a pivotal tool for elucidating the indirect effect of an environmental factor or treatment on disease through potentially high-dimensional omics data, such as gene expression profiles. However, traditional mediation analysis methods tailored for binary outcomes often rely on the rare disease assumption in logistic regression and provide inadequate measures of total mediation effect when multiple mediators have effects in different directions. In this paper, we develop a MEdiation analysis framework in LOgistic regression for high-Dimensional mediators and a binarY outcome (MELODY). It leverages a second-moment-based measure analogous to theR2for linear models to quantify the total mediation effect. We also develop a variable selection procedure for high-dimensional data to reduce bias introduced by non-mediators. Our comprehensive simulations demonstrate the superior performance of MELODY in scenarios with non-rare disease binary outcomes and high-dimensional mediators. We apply MELODY to the Framingham Heart Study of over 5000 individuals to analyze the mediation effects of metabolomics and transcriptomics data on the pathways from sex to incident coronary heart disease.

Cardiorespiratory fitness is an integrative measure of cardiometabolic health and predictor of survival, yet little is known about its molecular underpinnings. Small molecule metabolites and lipids are increasingly recognized as exercise-stimulated signaling molecules and candidate molecular transducers of cardiorespiratory fitness. We performed nontargeted liquid chromatography-mass spectrometry-based plasma metabolomics in 654 participants (mean age, 35 years; 55% women) from the HERITAGE Family Study (Health, Risk Factors, Exercise Training, and Genetics) who had cardiorespiratory fitness (maximal oxygen uptake [VO2max]) measured by cardiopulmonary exercise testing and underwent 20 weeks of supervised endurance training. Metabolite-VO2max relationships were assessed using linear regression and tested for replication in FHS (Framingham Heart Study) participants who also underwent cardiopulmonary exercise testing. Metabolite relationships with incident all-cause mortality ascertained in JHS (Jackson Heart Study) and MESA (Multi-Ethnic Study of Atherosclerosis) were tested using Cox regression. Experimental studies of cellular respiration and mitochondrial function were performed in C2C12 myotubes. An unknown mass spectrometry peak (mass-to-charge, 385.3056; retention time, 3.69 minutes) had the strongest, positive relationship with VO2max (mL×kg-1min-1) after adjustment for age, sex, race, and lean body mass (β=1.29; false discovery rate q=5.3×10-6); was identified as N-palmitoyl glutamine (NPG) using tandem mass spectrometry and bioinformatics; and was confirmed with an authentic chemical standard. The biological role of NPG has not been described previously. The relationship of NPG with VO2max was validated in 408 participants from the FHS (β=1.2; P=3.8×10-5), and its levels increased after exercise training (log fold change=0.22; q=5.3×10-12). NPG levels were inversely associated with all-cause mortality in JHS and MESA (hazard ratio, 0.91 and 0.65 [P=0.029 and P=0.028], respectively). Previous studies have shown that structurally related biochemicals modulate energy homeostasis; thus, we performed mitochondrial experiments. NPG administration led to a dose-dependent increase in mitochondrial:nuclear DNA ratio compared with control treated cells (15% and 20% increases at 6.5 nM and 26 nM NPG, respectively [P=0.04 and P=0.02]) and improved bioenergetics (NPG at 26 nM increased the phosphate:oxygen ratio across ADP concentrations from 0 to 100 μM; ANOVA P=0.0027). We identified a novel, lipidated amino acid, NPG, that is positively associated with VO2max, increases after regular aerobic exercise, and is inversely associated with incident mortality. NPG stimulates mitochondrial biogenesis and efficiency, demonstrating its potential role as an exercise-stimulated transducer of cardiorespiratory fitness.

Mild manifestations of individual cerebral small vessel disease (CSVD) markers are common and may not denote increased risk, but high CSVD burden identifies individuals at increased risk of stroke and dementia. Scores incorporating multiple individual CSVD markers may better identify a person's risk. We related a multimarker CSVD score to risk of incident stroke and compared it with the Framingham Stroke Risk Profile (FSRP) in community-dwelling individuals. Framingham Heart Study participants aged ≥55 years, free of stroke and dementia, and with brain magnetic resonance imaging ratings of CSVD markers were included. A multimarker CSVD score reflecting increasing CSVD burden was used, assigning 1 point each for presence of cerebral microbleeds, severe perivascular spaces, extensive white matter hyperintensities, covert brain infarcts, and cortical superficial siderosis. Multivariable Cox proportional hazards regression analyses were used to relate CSVD score to incident stroke. Among 1154 participants (46% men, mean age 70.9±8.7 years), 92 (8%) developed stroke over a median follow-up of 8.6 years (Q1-Q3: 5.1-12.5). In models adjusting for age, sex, time interval between clinic exam and magnetic resonance imaging, Framingham cohort, and FSRP, those with ≥3 markers had increased risk of stroke (hazard ratio [HR], 2.62 [95% CI, 1.17-5.88]). In comparison, a 5% increase in FSRP was also associated with increased risk (adjusted HR, 1.16 [95% CI, 1.04-1.29]). The FSRP and CSVD score had similar model discrimination metrics. Higher CSVD burden is associated with increased risk of stroke, beyond the effect explained by risk factors in the FSRP. These findings support consideration of CSVD burden to identify risk of stroke in community-dwelling individuals for early implementation of preventive strategies.

Age-related hearing loss is a potentially modifiable risk factor for cognitive impairment and dementia. To investigate the association of hearing loss with brain structure changes, cognitive function, and incident dementia. This cohort study included Framingham Heart Study Offspring Study participants attending their sixth quadrennial examination (1995-1998) divided into 2 partially overlapping samples. Sample 1 participants underwent brain magnetic resonance imaging and cognitive assessment at their seventh and eighth quadrennial examinations. Sample 2 included participants aged 60 years or older at pure tone average (PTA) analysis and subsequently followed up for incident dementia. The data analysis was performed between January 12, 2024, and August 24, 2025. Hearing loss. The main outcomes were changes in brain volume on MRI, cognitive performance on neuropsychological testing, and incident all-cause dementia. Multivariable linear regressions were used to compare PTA and hearing loss categories with neuropsychological measures and total cerebral, hippocampal, and white matter hyperintensity brain volumes. Cox proportional hazards regression was used to examine longitudinal associations between PTA and hearing loss categories and incident dementia. Sample 1 included 1656 participants (mean [range] age, 58.1 [29.7-85.6] years; 903 female [54.5%]), and sample 2 included 935 participants (mean [range] age, 67.6 [60.0-85.6] years; 518 female [55.4%]). Participants with mild or greater hearing loss, compared with those with no or only slight hearing loss, had significantly smaller brain volumes (β [SE], -4.10 [1.76]) and declines in executive function (β [SE], -0.04 [0.01]). Participants with at least slight hearing loss, compared with those with no hearing loss, had significant increases in white matter hyperintensity volume (β [SE], 0.02 [0.01]) and a higher risk of developing all-cause dementia (hazard ratio, 1.71; 95% CI, 1.01-2.90) over 15 years of follow-up, particularly among those with at least 1 apolipoprotein E ε4 allele (hazard ratio, 2.86; 95% CI, 1.12-7.28). This cohort study found that midlife hearing loss was associated with smaller brain volumes, accelerated worsening in executive function, and an increased risk of dementia, suggesting that it may be an early marker of brain aging and dementia risk.

Background: Prediabetes and diabetes are associated with increased risk for hypertension (HTN) and cardiovascular disease, especially in women. Relations of glycemic variability and other glycemic phenotypes with these diseases have not been well studied in individuals without diabetes. Methods: Framingham Heart Study (FHS) Third Generation, New Offspring Spouse, and Omni 2 participants attending Exam 4 Year 1 (n=1291) were invited to wear a Dexcom G6 Pro continuous glucose monitor (CGM) for 10 days. We included individuals who wore CGM for ≥3 full days (n=1038). Participants were excluded if they had diabetes, took glucose-lowering medication (n=133) or did not complete a mixed meal tolerance test (MMTT, n=53), resulting in a final analytic sample of 852 participants. We performed multivariable linear and logistic regression to examine associations of glucose measures (fasting and 2h-post MMTT) and CGM-metrics with blood pressure (BP) variables and prevalent HTN (defined as stage 2 HTN or taking BP medication). We standardized all predictors to 1SD, log-transformed CGM time above range &gt;140mg/dL (TAR140), and adjusted all regression models for age, smoking status, and body mass index (BMI), stratifying by sex. Results: Among 852 FHS participants (56.9% women; average age 60.3 years), the average BMI was 27.9 kg/m 2 , and 30.5% had hypertension. In multivariable regression models, TAR140, mean CGM glucose, and higher blood glucose at fasting and 2h-MMTT were associated with higher odds of HTN (OR=1.20-1.38, all p&lt;0.05). Among those without HTN (n=583), exploratory heatmaps (Figure) provide visualization of the unadjusted correlations of CGM and blood glucose related metrics with BP measures. In multivariable regression models in men and women without HTN (n=583), fasting and 2h-MMTT blood glucose were associated with systolic BP (β=1.65-2.56, p&lt;0.001). In women only, TAR140, mean CGM glucose, coefficient of variation (CV), mean amplitude of glycemic excursion (MAGE), and mean of daily differences (MODD) were associated with pulse pressure (β=0.97-1.31, all p&lt;0.05) and TAR140, mean CGM glucose, and MODD were also associated with systolic BP (β=1.54-1.94, all p&lt;0.01). These associations were not significant in men (β=-0.56-0.28, all p&gt;0.5). Conclusions: Among individuals without diabetes or HTN, associations of CGM metrics with BP measures were observed in women, not in men, which may reveal mechanistic differences in cardiometabolic disease progression by sex.

Introduction: The American Heart Association’s (AHA) Life’s Simple 7 (LS7) score defines cardiovascular health (CVH) and promotes healthy lifestyle behaviors through seven key components (Circulation, PMID: 20089546). Intrinsic frequencies (IFs) derived from carotid pressure waveforms are shown to be associated with cardiovascular performance in the Framingham Heart Study (Hypertension, PMID: 33390053). Here, we study whether IFs derived from carotid pressure waveforms relate to the AHA CVH score in a large community cohort. Methods: The study population was drawn from the Original, Offspring, and Third Generation Cohorts of the Framingham Heart Study where all the required metrics were available (N=5460; mean age 48 years). Per AHA LS7, we calculated CVH scores using fasting glucose, cholesterol, blood pressure, BMI, smoking status, and physical activity (excluding diet). Carotid pressure waveforms were acquired using an arterial tonometry device. From each non-calibrated waveform, we computed IF parameters: ω 1c , IF of the coupled heart and vascular system during systole corrected by systolic period; ω 2c , IF of the decoupled vasculature during diastole corrected by cardiac period; and △ω c , the difference between the two, which is a metric for left ventricle (LV)-arterial coupling. The association between AHA CVH score, and carotid-derived IFs was evaluated using box-and-whisker plots. Box plots were used to visualize the distribution of IFs across CVH score groups, with red lines connecting the group medians to highlight trends. Statistical significance across groups was assessed using either ANOVA or Kruskal–Wallis tests. Results: All three IF parameters showed clear, systematic trends across the CVH score groups. Specifically, ω 1c declined, ω 2c increased, and △ω c exhibited a steep decreasing trend with increasing the AHA CVH score (Figs. 1–3), reflecting improved LV-arterial coupling and vascular function with better cardiovascular health. Both one-way ANOVA and Kruskal–Wallis tests confirmed statistically significant differences (p &lt; 0.0001) across the CVH score groups for all three IF parameters. Conclusion: Our results revealed that IFs of carotid pressure waveforms are associated with AHA CVH scores. The observed trends between IFs and CVH score were consistent with previous clinical and preclinical studies where higher ω 1 and △ω but lower ω 2 were associated with higher risk for incident composite cardiovascular disease events and incident heart failure.

Introduction: Accurate assessment of cardiac output (CO), a standard cardiovascular performance index, is essential for diagnosing and managing a wide range of cardiovascular conditions, including heart failure, shock, and valvular disease (Eur Heart J.PMID: 2092985). However, standard methods such as echocardiography or thermodilution are either operator-dependent, resource-intensive, or invasive. This limits their use in routine screening and outpatient monitoring. A noninvasive, rapid method to estimate CO from a single arterial pressure waveform could transform cardiovascular care by enabling continuous or point-of-care evaluation. Aim: This study aimed to develop and validate a noninvasive method for estimating cardiac output using features extracted from a single carotid pressure waveform captured with a tonometry measurement device. Methods: A cohort of 2448 individuals (age range: 19–90 years) from the Framingham Heart Study was analyzed. All participants had consistent CO measurements across multiple echocardiographic recordings. Carotid pressure waveforms were obtained using an arterial tonometry device and calibrated using cuff-based brachial pressures. Reference aortic flow values were computed by first measuring the left ventricular outflow tract diameter from 2D echocardiography (parasternal long-axis view) to calculate the cross-sectional area. Then, the pulsed Doppler velocity waveform from the apical 5-chamber view is multiplied by this area to generate the aortic flow waveform over time. CO values were computed by averaging the flow waveform over the entire cardiac cycle. Intrinsic frequency (IF) parameters were computed from the carotid waveforms and used as inputs for machine learning models. Eighty percent of the data was used for model training, and the remaining twenty percent was reserved for blind testing. Results: Single-waveform CO estimation showed a Pearson correlation of 0.76, limits of agreement of ±1.09, and a bias of 0.00 compared to reference values in the blinded test set (Fig. 1 and 2). Conclusions: Estimating cardiac output from a single carotid pressure waveform offers a non-invasive and scalable tool for hemodynamic monitoring. This method may improve early detection and management of various cardiovascular conditions where cardiac output is critical, such as heart failure, cardiogenic shock, and myocardial infarction. This method is well-suited for both in-patient and remote patient monitoring.

Background: Obesity is heterogeneous, with cardiovascular disease (CVD) risk driven by ectopic fat distribution rather than total adiposity. Epicardial Adipose Tissue (EAT) and Visceral Adipose Tissue (VAT) are key mediators of cardiometabolic risk through pro-inflammatory pathways. Despite this, clinical risk stratification relies on body mass index (BMI), which fails to differentiate high-risk obesity phenotypes. We assessed whether EAT and VAT identify distinct obesity phenotypes with differing CVD risk profiles and quantified the role of systemic inflammation in mediating this risk. Hypothesis: We hypothesized that individuals with concurrently high EAT and VAT represent a high-risk obesity phenotype with significantly greater CVD risk compared to Metabolically Healthy Obesity (MHO), and that systemic inflammation mediates ≥30% of this increased risk. Methods: We analyzed 47,091 participants from three cohorts: Framingham Heart Study (N=3,489), Dallas Heart Study (N=3,072), and UK Biobank (N=40,530). EAT volume and VAT area were measured by CT/MRI. Systemic inflammation biomarkers (hs-CRP, IL-6) were assayed. Obesity phenotypes were defined as: High-risk (EAT ≥125 cm3 and VAT ≥75th percentile); MHO (VAT ≥75th percentile and insulin resistance); and MHO (BMI ≥30 kg/m2 and low EAT/VAT [below high-risk thresholds]). Multivariable Cox models (adjusted for age, sex, race, diabetes, smoking, SES) Estimated Hazard Ratios (HRs) for incident CVD (MI, stroke, or HF). Mediation used the product-of-coefficients method. Results: High EAT (≥125 cm3) was associated with a 2.1-fold higher CVD risk (95% CL: 1.6–2.8; p&lt;0.001). Concurrently high EAT and VAT conferred a 4.5-fold increased heart failure risk (95% CL: 2.8–7.3; p&lt;0.001). MUO demonstrated a 3.8-fold higher CVD risk versus MHO (95% CL: 3.1–4.6; p&lt;0.001), while MHO showed no significant risk elevation (HR 1.1; 95% CL: 0.9–1.4; p=0.32). Systemic inflammation mediated 38% of the EAT–CVD association (p&lt;0.001) and 42% of the EAT–heart failure association (p&lt;0.001). Conclusion: EAT and VAT identify high-risk obesity phenotypes with markedly elevated CVD and heart failure risk, whereas metabolically healthy obesity confers no excess risk. Systemic inflammation explains over one-third of the EAT/VAT–CVD relationship. These findings advocate for integrating EAT/VAT imaging into clinical risk stratification, prioritizing anti-inflammatory therapies in high-risk populations, and expanding access to advanced imaging.

Introduction: Several glycemic traits indicate risk for type 2 diabetes (T2D). Although previous studies have identified many genes associated with glycemic traits, the underlying molecular mechanisms remain unclear. Identifying gene expression signatures, both protein-coding mRNAs and long non-coding RNAs (lncRNAs), associated with glycemic traits may provide insight into the biological pathways that contribute to glycemic regulation and the development of T2D. Methods: Whole blood RNA-seq data were analyzed from Framingham Heart Study (FHS, N=3,469; 55% female, discovery cohort) and Women’s Health Initiative (WHI, N=1,699; female only, replication cohort) participants. Glycemic traits examined included fasting glucose, fasting insulin, Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), and glycosylated hemoglobin. Associations between gene expression (mRNAs and lncRNAs) and glycemic traits were assessed using linear mixed models, excluding participants with prevalent T2D and adjusting for age, age squared, body mass index, batch effects, family structure, and sex. Sex-specific analyses were also conducted. Two-sample Mendelian Randomization (MR) was used to infer putative causal relations between gene expression and glycemic traits. Gene ontology analysis was performed to identify enriched biological functions and pathways. Results: In the discovery cohort we identified 2,022 protein-coding mRNA and 172 lncRNA associated with glycemic traits (FDR&lt;0.01), of which 129 protein-coding mRNAs and 11 lncRNA replicated (FDR&lt; 0.05). When limiting the discovery sample to women (N=1,929), 140 mRNAs and 8 lncRNAs were significant in discovery, and 51 mRNAs and 6 lncRNAs replicated. Glycemic signatures were significantly enriched for genes involving mitochondrial synthesis, immune function, and protein synthesis. MR further identified 87 of the 144 replicated genes as causal for the corresponding glycemic trait (P MR &lt;0.05). ADM, which encodes for adrenomedullin, was associated with insulin and identified as the top mRNA in MR analysis. AL357033.4, which is associated with immune-related functions and cancer, was associated with HOMA-IR and identified as the top lncRNA in the MR analysis. Conclusion: These findings reveal mRNAs and lncRNA associations with glycemic traits that may provide insights into molecular mechanism underlying diabetes risk and highlight promising therapeutic targets for treatment and prevention of T2D.

Background: Aortic valve calcification (AVC) is an early marker of aortic stenosis but is not routinely scored and reported in coronary artery calium (CAC) scans. Traditional manual quantification methods are time-consuming and subject to inter-reader variability, limiting their scalability in clinical practice. The AI-CVD initiative (see figure 1) aims to extract all useful opportunistic screening information from CAC scans to maximize prediction of cardiovascular diseases (CVD). Hypothesis: We hypothesized that the AI-CVD measurements of AVC in CAC scans performs comparably to manual measurements by human experts. Methods: We analyzed 742 CAC scans from the Framingham Heart Study Offspring cohort, acquired between 2002 and 2005 who also had an echocardiogram with aortic valve analysis. The AI model was trained to segment each aortic valve leaflet and quantify calcification using the Agatston criteria (&gt;130HU and ≥1mm2). Manual AVC scores were previously computed by trained huamn experts. The primary outcome was clinically diagnosed aortic stenosis, identified cross-sectionally from health records. We compared the performance of AI-CVD and manual AVC scores using the area under the receiver operating characteristic (AUC) analysis and confusion matrix metrics, including sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Results: Among 742 participants, 22 had a clinical diagnosis of aortic stenosis. 18 cases of aortic stenosis were correctly identified by AI-measured AVC compared to 15 cases by manual measurements. The AUC for aortic stenosis diagnosis for AI-CVD AVC was 0.934 vs. 0.883 for huamn experts. Confusion matrices and ROC curves support the improved accuracy and lower false negative rate of AI-based measurement versus human experts. Conclusion: AI-CVD AVC score detects aortic stenosis comparably to manual measurements by huamn experts in the Framingham Heart Study Offspring Cohort. These findings support the integration of AI-enabled opportunistic screening into CAC scans to maximize CVD prediction beyond the CAC score.

Background and Research Question: Increasing pulse pressure (PP) occurs with aging and is a risk factor for CVD. PP is shown to fall to a nadir in midlife with subsequent increase with age thereafter. This increase is notably sharper in women compared to men. Sex hormones have been proposed as a vasculo-protective factor in women that is lost during menopause. Thus, we sought to evaluate the temporal patterns of age, sex, and time of menopause on age-associated PP widening in a longitudinal cohort of adults across midlife. Methods/Approach: We evaluated participants from the Framingham Third Generation, Omni-2, and New Offspring Spouse cohorts. Participants attended up to 3 study visits over 14 years that included non-invasive hemodynamic measurements with arterial tonometry. Supine brachial PP was measured after 5 minutes of rest. Menopause age was self-reported. Women were subdivided into 4 groups based on age of menopause: persistently premenopausal, early (&lt;25 th percentile, age &lt;48 years), average (25 th -74 th percentile, age 48 to 52), or late-onset menopause (≥75 th percentile, age ≥53), with men as reference. Participants were excluded for missing or incomplete covariate or tonometry data. Data were analyzed using repeated-measures linear mixed models adjusted for age, age 2 , menopause group, and CVD risk factors. Results: Date from 6222 participants with 47.7% women (mean 1 st visit age = 47.9 years) and 52.3% men (mean 1 st visit age = 50.5 years) were analyzed. Modeled PP nadirs in women, regardless of menopause group, occurred about a decade earlier in women compared to men (Figure 1 and 2). There were minimal differences in PP nadir age (average age = 37.1 years) among post-menopausal groups. Predicted PP nadir age was unrelated to the age of menopause, with PP nadir occurring 6.1, 13.5, 18.8 years prior to menopause onset in the early, average, and late menopause groups respectively (Figure 1). Conclusion: The estimated nadir of PP occurs nearly a decade earlier in women than men and several years prior to menopause onset in all 3 groups of postmenopausal women. While there were some marginal associations between menopause age and PP widening, it is likely other factors play a larger role in the accelerated increase in PP in women after early adulthood. Further studies are needed to establish mechanisms of the early transition and sharper increase in PP among women.

Introduction/Background: Urine biomarkers of kidney function may predict the progression of kidney dysfunction and risk of cardiovascular disease. Methods: We measured 14 urine biomarkers in 2948 Framingham Heart Study (FHS) participants (mean age 59, 53% women )at a routine examination in 1995-1998. Fourteen urine biomarkers (indexed to urine creatinine) (Table 1) were tested for association with new-onset of: 1) chronic kidney disease (CKD), 2) microalbuminuria, 3) coronary heart disease (CHD), 4) atherosclerotic cardiovascular disease (asCVD) , 5) congestive heart failure (CHF), 6) stroke, 7) cancer, and 8) all-cause mortality. We applied age-specific estimated glomerular filtration rate (eGFR) cut-points to define CKD (eGFRcr values of 70, 60, 45 (ml/min/1.73m2 ) for age groups: &lt;55, 55-65, &gt;= 65, respectively). We applied Cox models to assess associations with outcomes by quartile of urine biomarkers and tested for trend across quartiles after adjusting for age, sex, blood pressures, hypertension treatment, total and HDL cholesterol, lipid treatment, diabetes, cigarette smoking, alcohol use, eGFRcr, and dip-stick albuminuria. Statistical significance was defined by linear trend p value &lt;0.05. Results: Higher urine TFF3 was associated with risk of new-onset CKD (Fig-1). Higher A1M, CTGF, KIM1, NGAL, TIMP1, and VEGF were associated with risk of microalbuminuria. Higher A1M, KIM1, and NGAL were associated with risk of CHF. OPN was inversely associated with new-onset stroke (Fig-1). Nine biomarkers were associated with all-cause death (Fig- 2). Conclusions: Multiple kidney-related biomarkers were associated with new-onset kidney dysfunction, CHF, and death and suggest value of urine biomarkers to identify risk for kidney dysfunction and CVD.

Background: Stiffening of large arteries is a key pathophysiologic precursor of micro- and macrovascular disease. Increased arterial stiffness (AoS) and central pressure pulsatility (CPP) can precede the development of atherosclerosis, heart failure, cardiometabolic disease, and renal failure. Further research into the underlying biology of arterial stiffening will improve our ability to target this important risk factor for disease. Proteome-wide evaluation of circulating factors may uncover insights into underlying mechanisms of AoS, as well as markers that modify its risk of disease. Objective: To identify plasma proteins related to and potential mediators of AoS and CPP as potential biomarkers and novel mechanistic mediators Methods: We evaluated 1072 participants from the Framingham Heart Study Generation 2 Exam 10 (2019-2021) who had completed proteomic profiling by SomaScan 7K platform and arterial tonometry measurements of AoS [carotid-femoral pulse wave velocity (CFPWV), augmentation index (AI)] and CPP. Using multiple linear regression, we assessed the association between 7335 detected proteins with (1) inverse-transformed CFPWV and log-transformed (2) CPP and (3) AI. Models were adjusted for either (1) batch and plate, or (2) batch, plate, and age. We subsequently identified proteins significantly associated with CFPWV, AI and CPP by multiplicity-corrected p-value &lt; 0.05. Results: Mean age was 76±7 years, 45% were male. We identified 333 unique proteins significantly associated with elevated CFPWV, AI and CPP (Batch/plate: 319 proteins, Age-adjusted: 57 proteins) and 70 proteins with their reduction (Batch/plate: 62 proteins, Age-adjusted: 26 proteins). Many proteins are endocrine or paracrine factors in pathways important to alteration in the extracellular matrix of arterial vasculature (MMP12, CTSD, CHRDL1, CTSD, TAGLN), vascular calcification (SVEP1, PTN, HTRA1, SOST, MSC, BMP9, DDK2), endothelial dysfunction (FABP3, FABP4, RARRES2, ADAMTS13, PLAT, RSPO1, ANGPTL3, ADIPOQ), and inflammation (CRP, TREM2, LGALS3BP, NEGR1, APCS). Conclusions: We identified numerous circulating proteins strongly associated with change in AoS and CPP, many of which are paracrine and endocrine factors in mechanistic pathways leading to loss of arterial elasticity. Further investigations of these proteins may reveal putative biomarkers of AoS and CPP and new molecular pathways for therapeutic targeting.

Introduction: Healthy Vascular Aging (HVA) refers to the preservation of vascular function with advancing age, challenging the common belief that hypertension and increased arterial stiffness are unavoidable outcomes of aging (Hypertension, PMID: 28559398). This definition identifies individuals who retain young vascular characteristics beyond midlife. While traditional clinical metrics are used to assess HVA, waveform-derived biomarkers, such as cardiovascular intrinsic frequencies (IFs), may provide a non-invasive and physiologically grounded alternative. IFs extracted from carotid pressure waveforms have previously been shown to be associated with cardiovascular function and vascular health (Hypertension, PMID: 33390053). In this study, we examine the association between carotid-derived IFs and the HVA status. Methods: The study sample was drawn from the Original (Exam 26), Offspring (Exam 7), and Third Generation (Exam 1) cohorts of the Framingham Heart Study. As established in the literature, we assigned HVA to the individuals with age ≥ 50 years, systolic blood pressure &lt;140 mmHg, diastolic blood pressure &lt;90 mmHg (without hypertension medication), and a carotid-femoral pulse wave velocity &lt;7.6 m/s. After applying these criteria, a total of N = 2,242 participants remained for analysis. Carotid pressure waveforms were acquired using applanation tonometry. We used these waveforms and computed the IF metrics for each individual: ω 1c (IF during systole, related to left ventricular inotropic function and LV-arterial coupling) and ω 2c (IF during diastole, related to arterial function). The associations between the HVA status and carotid-derived IFs were assessed using box-and-whisker plots and the Mann–Whitney U test. Results: The carotid-based IF metrics showed statistically significant differences between individuals with and without HVA (p &lt; 0.0001 for all comparisons). The group-wise distributions of these parameters are illustrated in Figure 1, highlighting distinct shifts in IF values between the HVA and no-HVA groups. Lower ω 1c but higher ω 2c were observed in the HVA group. Conclusion: Our results demonstrated that Intrinsic frequencies of carotid pressure waveforms are associated with the status of vascular aging. The findings of this study support the potential utility of IFs as a non-invasive approach to assess vascular health aging.

Introduction/Background: The AI-CVD initiative aims to extract opportunistic screening information from coronary artery calcium scans to improve cardiovascular disease prediction. Thoracic aortic calcification (TAC) is a known marker of atherosclerotic burden but remains underutilized in routine coronary artery calcium scan interpretation. Automated quantification of TAC using artificial intelligence may enhance cardiovascular risk prediction, particularly when integrated with conventional risk scores. Research Questions: We evaluated whether AI-derived TAC from coronary artery calcium scans independently predicts incident cardiovascular disease in the Framingham Heart Study Offspring cohort. Goals: To assess whether automated TAC measured by the AutoTAC component of AI-CVD predicts future cardiovascular events independently of coronary artery calcium and traditional cardiovascular risk factors. Methods: Baseline coronary artery calcium scans from 1,002 asymptomatic participants in the Framingham Heart Study Offspring cohort were analyzed using AI-enabled thoracic ascending aortic calcification quantification. TAC scores were categorized as 0, 1–99, 100–299, 300–999, and ≥1000. Cox proportional hazards models estimated hazard ratios for cardiovascular disease across TAC categories using unadjusted, age-adjusted, and fully adjusted models accounting for coronary artery calcium and established risk factors. Results: 296 CVD events accrued over 17 years follow-up. In fully adjusted models, compared to participants with zero TAC scores, participants with TAC scores of 100–299 had a hazard ratio of 2.05 (95% CI: 1.19–3.54), those with scores 300–999 had a hazard ratio of 2.29 (95% CI: 1.32–3.97), and those with scores ≥1000 had a hazard ratio of 2.85 (95% CI: 1.66–4.89). Lower categories (1–99) were not statistically significant after adjustment (HR 1.21, 95% CI: 0.73–2.03). The risk of cardiovascular disease increased progressively with higher TAC burden. Conclusion(s): In the FHS Offspring cohort, AI-measured TAC from coronary artery calcium scans was independently associated with future cardiovascular disease events over 17 years of follow-up. These findings support the utility of opportunistic AI-enabled aortic calcification assessment as an adjunct to traditional coronary artery calcium scoring in enhancing long-term risk stratification.

The associations of coffee and tea intake with long-term risk of dementia have not been thoroughly established. Additionally, the potential mediating roles of circulating inflammatory biomarkers in these associations remain less explored. We included 6,001 participants from the Health and Retirement Study (HRS, 2013-2020) and 2,650 participants from the Framingham Heart Study Offspring cohort (FOS, 1998-2018), all free of dementia at baseline. Coffee and tea intake was assessed using a semi-quantitative food frequency questionnaire in both cohorts. Dementia diagnosis was ascertained using a validated algorithm and clinical review panel. Cox proportional hazard models were utilized to evaluate the associations of coffee and tea intake with dementia. Mediation analysis was conducted to examine whether circulating inflammatory biomarkers mediated these associations. During a median follow-up of 7.0 years in HRS and 11.1 years in FOS, 231 individuals in HRS and 204 in FOS developed all-cause dementia. Compared with intake of less than 1 cup of coffee per day, consuming ≥ 2 cups daily had a 28-37% lower risk of dementia (Hazards ratio [HR] = 0.72, 95% confidence interval [CI]: 0.52, 0.99, P-trend = 0.045 in HRS; HR = 0.63, 95% CI: 0.45, 0.90, P-trend = 0.015 in FOS). Compared to non-consumers, moderate tea consumption was associated with a lower dementia risk in HRS (HR = 0.65, 95% CI: 0.48, 0.89 for > 0 to < 1 cup/day; HR = 0.53, 95% CI: 0.30, 0.94 for ≥ 1 to < 2 cups/day), but no significant association was observed in FOS. In the mediation analysis, the association between coffee intake and dementia was partially mediated by interleukin-10 (IL-10, 29.30%), Cystatin C (24.45%), C-reactive protein (CRP, 16.54%), interleukin-1 receptor antagonist (IL-1RA, 11.06%), and soluble tumor necrosis factor receptor-1 (sTNFR-1, 10.78%). In conclusion, higher coffee consumption (≥ 2 cups per day) is associated with a lower risk of dementia, partially mediated by a set of inflammatory biomarkers. Moderate intake of tea (0-2 cups per day) may relate to a lower risk of dementia. Further large-scale observational and interventional studies are warranted to confirm these findings.

Abstract Opioid drugs, prescribed for pain management or opioid use disorder, have been associated with decreased bone mineral density (BMD) and increased fracture risk. Changes in circulating microRNA (miRNA) levels have been observed in opioid-treated patients, and miRNAs are crucial regulators of bone metabolism, but the effects of circulating miRNAs on BMD in the context of opioid use remains unexplored. This study aims to identify circulating miRNAs differentially expressed with opioid use that may explain opioid use effects on BMD. We conducted a cross-sectional analysis of 5,692 participants from the Framingham Heart Study Offspring and Third Generation cohorts for which 412 miRNA profiles were obtained via quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR). BMD measurements were obtained using dual-energy X-ray absorptiometry (DXA) for most participants, among whom opioid use was reported in 62 (1.1%). We modeled miRNA as a function of opioid use and/or BMD, adjusting for age, sex, and body mass index, in linear or logistic regression models. Significant miRNAs associated with both opioid use and BMD were then analyzed using a novel strategy for pathway enrichment to identify biological functions impacted by these miRNAs. We found a significant inverse association between opioid use and BMD after adjusting for covariates (β = -0.042, 95% CI= -0.075, -0.007, p = 0.017). We identified 64 miRNAs associated with BMD and 28 miRNAs associated with opioid use (p&amp;lt;0.05). Ten miRNAs were significantly (p&amp;lt;0.05) associated with both opioid use and BMD, nine with opposing effects. Pathway enrichment analysis revealed the involvement of thyrotropin-releasing hormones, phosphatidyl serine, vascular endothelial growth factors, integrins, and modulation of calcium and potassium ions. Our study has found preliminary evidence for miRNA-mediated mechanisms by which opioid use impacts bone health, which may guide future translational applications to prevent bone loss in opioid users.