Browse Articles

Abstract MP60: Associations between Chronic Stress, Resilience Factors and Cardiovascular Health among Young Adults in Puerto Rico

Introduction: The association between stress, resilience and cardiovascular health (CVH), as defined by the American Heart Association Life’s Essential 8 (LE8) metric, has not been well studied. We studied these associations among young adults in PR. Hypothesis: Chronic stress is associated with suboptimal CVH among young adults in PR; however, culture-relevant resilience factors, including optimism, spirituality, religiosity, and social support, help mitigate this association. Methods: Participants, aged 18-29 y and living in PR, completed assessments between September 2020 and November 2023 (60.8% female, n= 2,179). Participants completed measures of chronic stress (Chronic Burden scale, score dichotomized: low=0-1, high: > 2), optimism (LOT-R; score range: 0-24), spirituality (DSES; scores: 1-80), religiosity (1 item; score: 0-2), and social support from family and friends (Walen&Lachman; score: 1-8). Resilience scores were treated as continuous variables. CVH (LE8) scores were derived from surveys, laboratory assays, and physical exams (scores:0-100, suboptimal = <80). Multivariable logistic regression was used to assess the association between chronic stress and CVH, followed by mediation analysis to determine whether resilience factors mitigated this association. Bias-corrected and accelerated 95% confidence intervals (CI) for the mediated proportions were estimated using bootstrapping with 1,000 replications. All models controlled for sex, age, subjective social standing, and mother’s education. Results: Overall, 36% of participants had high scores for chronic stress. The mean and standard deviations for the resilient factors were 14.7 (4.3) for optimism, 35.4 (18.1) spirituality, 1.3 (0.7) religiosity, and 6.5 (1.1) social support, and 72.5% of participants had suboptimal CVH. In the adjusted analysis, chronic stress was significantly associated with suboptimal CVH (OR=1.42; 95%CI:1.16-1.75). Mediation analyses showed that 19% (95%CI:4.58-55.9) of this association was mediated by optimism and 13.7% (95% CI: 4.0-45.8) by social support. Conclusion: The experience of chronic stress is associated with suboptimal CVH among young adults in PR. However, this association is mitigated by optimism and social support from friends and family. To increase the evidence base for preventive interventions, future research should assess longitudinal trajectories of these associations and pathways by which chronic stress and resilience factors may impact CVH.

Abstract P2105: Polygenic risk scores for obstructive sleep apnea relying separately on BMI- adjusted and -unadjusted genetic associations reveal separate pathways of cardiovascular disease risk

Background: OSA is a heterogeneous disease, with obesity a significant risk factor in many but not all cases of OSA, via increased airway collapsibility, reduced lung volumes, and possibly body fat distribution. Research question: We sought to develop PRSs that summarize the genetic liability to OSA that include and exclude obesity related pathways, and to study the associations of these PRSs with OSA comorbid cardiometabolic and CVD outcomes. Approach: Using 1.2 million race/ethnic diverse samples from the Million Veteran Program, FinnGen, TOPMed, All of Us (AoU), Geisinger’s MyCode, MGB Biobank, and the Human Phenotype Project (HPP), we developed, selected, and assessed PRSs for OSA, relying on genome wide association studies both adjusted and unadjusted for BMI: BMIadjOSA and BMIunadjOSA PRS. We tested their associations with cardiometabolic and CVD outcomes in AoU. Results: In association with OSA, adjusted odds ratios (ORs) per 1 standard deviation of the PRSs ranged from 1.38 to 2.75, all statistically significant (Figure). The associations of BMIadjOSA and BMIunadjOSA PRSs with CVD outcomes in AoU shared both common and distinct patterns. For example, BMIunadjOSA PRS was associated with type 2 diabetes, heart failure, and coronary artery disease, but the associations of BMIadjOSA PRS with these outcomes were statistically insignificant with estimated OR close to 1. In contrast, both BMIadjOSA and BMIunadjOSA PRSs were associated with hypertension and stroke. Sex stratified analyses revealed that BMIadjOSA PRS association with hypertension was driven by data from females: females had OR=1.1, p-value=0.002, but males OR=1.01 and statistically insignificant. OSA PRSs were also associated with dual-energy X-ray absorptiometry (DXA) body fat measures. In BMI adjusted analysis, BMIadjOSA PRS was associated with higher visceral adipose tissue (VAT) proportion of total body fat mass (TFM), with lower proportion of gynoid fat mass out of TFM, higher proportion of android fat mass out of TFM, and lower gynoid to android fat mass. In females only, the PRS was associated with higher VAT to SAT ratio (Figure). Conclusions: Distinct components of OSA genetic risk are related to obesity and body fat distribution, and may influence clinical outcomes. These may explain differing OSA risk and associations with cardiometabolic and CVD morbidities between sex groups.

Monkeys increase scratching when encountering unexpected good fortune

Dact1 induces Dishevelled oligomerization to facilitate binding partner switch and signalosome formation during convergent extension

Abstract 077: Effect of Vitamin D Supplementation on Cardiovascular Health in Pregnant Women and Offspring Based on the Gestational Diabetes Mellitus Status

Aims Women with gestational diabetes mellitus (GDM) are at increased risk for impaired cardiovascular health (CVH) during pregnancy and may face a higher likelihood of cardiovascular disease (CVD) later in life. Our study explored the possible protective effects of vitamin D supplementation on cardiovascular health in pregnant women and offspring, focusing on GDM status. Methods and Results We randomly assigned women with a serum 25-hydroxyvitamin D concentration <75 nmol/L during gestational weeks 24-28 to receive 1200 IU/d of vitamin D 3 or the recommended 400-600 IU/d for two months. These groups were subdivided based on their GDM status: vitamin D + GDM, vitamin D + non-GDM, control + GDM, and control + non-GDM. There were 1563 participants. Women in the vitamin D + GDM group had lower concentrations of total cholesterol (mean difference with 95 % confidence interval [CI]: [-0.38 (-0.64, -0.12) mmol/L]), triglycerides [-0.34 (-0.61, -0.09) mmol/L], hypersensitive C-reactive protein [-0.82 (-1.55, -0.10) mg/L], and systolic blood pressure [-1.97 (-3.66, -0.14) mm Hg] than the control + GDM group after supplementation. Women in the vitamin D + GDM group had less severe gestational CVH than those in the control + GDM group, indicated by the gestational CVH score, the number of women with all “ideal” CVH metrics, and the mean ten-year atherosclerotic cardiovascular disease risk prediction ( P < 0.05). The macrosomia prevalence and the cord blood hypersensitive C-reactive protein concentration were significantly decreased in the vitamin D + GDM group. Conclusion: Vitamin D supplementation during pregnancy might improve CVH in women with GDM and their offspring, which is beneficial for the primary prevention of CVD later in life.

Abstract 063: Short-term Repeatability of Artificial Intelligence Estimated Electrocardiographic Age

Background: Artificial intelligence (AI) models produce precise interpretations of electrocardiogram (ECG) data and can estimate cardiac age from raw ECG waveforms (ECG-age). Although research suggests potential for cardiovascular disease (CVD) risk assessment, research on the short-term repeatability of ECG-age over time is scarce. Assessing the short-term repeatability of ECG-age is essential for establishing its precision and stability. Methods: We trained a convolutional neural network machine learning model to predict ECG-age using 18,869 patients from the publicly available German PTB-XL dataset with 10-second digital 12-lead ECG recordings. The model was adapted for one-dimensional signals to capture how aging impacts ECG waveforms, resembling a residual network used in image classification. The model was applied to two 10-second 12-lead ECGs taken at each of two separate visits, collected 1-2 weeks apart, from participants at the University of North Carolina at Chapel Hill’s General Clinical Research Center. The intraclass correlation coefficient (ICC), standard error of measurement (SEM), and minimally detectable change (MDC) estimated repeatability. Estimated variance was decomposed into between-participant, between-visit, and within-visit components. Results: Data to estimate ECG-age were available for 58 participants free of cardiovascular or metabolic conditions (mean age = 52±5 years; 55% female; 66% White). The mean (SD) ECG-age at visit 1 and visit 2 were 43.5 (4.1) and 44.0 (4.5) years, respectively. ECG-age demonstrated moderate repeatability between visit 1 and visit 2 (ICC=0.64; 95% confidence interval: 0.52, 0.76). The SEM was 2.6 years and MDC was 7.2 years. Between-participant variance accounted for the largest source of variation, followed by within-visit variation (Table 1). Discussion: ECG-age had moderate short-term repeatability, with consistency between visits. Notable within-visit variation suggests that measurement error or environmental and technical factors may influence repeated ECG-age assessments. These findings provide an important foundation for validating this novel AI metric in CVD research. Future studies should focus on strategies to minimize within-visit variation, improving the reliability of ECG-age as a potential clinical tool.

Abstract P3088: Neighborhood characteristics and incident myocardial infarction in US older adults: evaluation in two nationwide cohorts

Background: Many studies link adverse neighborhood context with racial myocardial infarction (MI) disparities. Research may reflect strong publication bias for chance associations in main or race-specific effects. Hypothesis: We theorized that associations would vary in direction as well as magnitude across two national cohorts due to differences in sample composition, outcome ascertainment, and parent study sampling schema. Methods: We compared results from the REasons for Geographic and Racial Differences in Stroke (REGARDS, n=25,143, aged ≥ 45 years, 42% Non-Hispanic (NH) Black; 2003-2018) study to the Health and Retirement Study (HRS, n=14,1941, aged > 50 years, 13% Non-Hispanic Black; 2004-2018). We estimated Cox models predicting MI for 51 American Community Survey (ACS) census tract (CT) variables and evaluated consistency of main and racially-stratified estimates between cohorts. Results: Follow-up in REGARDS (median=11.5 years; IQR: 6.5, 13.6) was similar to HRS (median=13.1; IQR: 8.3, 14.1), as was cumulative MI incidence (6.2% and 7.1%). The proportions of NH White and NH Black adults were at least moderately collinear in both samples ( r among White REGARDS participants-0.95, among Black REGARDS participants=-0.94, among White HRS participants= -0.63, and among Black HRS participants-=0.82). Sixteen ACS variables had estimated effects with incident MI that differed by at least 0.05 between cohorts. The estimated effect of the percentage of adults with less than a high school diploma was stronger in REGARDS (HR per SD: 1.10; 95% CI: 1.04, 1.17) than HRS (HR per SD: 1.04; 95% CI: 0.94, 1.15); the estimated effect of the percentage of residents in poverty was attenuated in REGARDS (HR per SD: 1.05; 95% 1.00, 1.11) compared to HRS (HR per SD: 1.17; 95% 1.07, 1.27). Differences in the estimated effects for 12 ACS variables across racial strata (p<0.05) identified in REGARDS were not corroborated in HRS. Conclusions: Neighborhood socioeconomic associations with MI across two national studies broadly replicated in direction but differed in magnitude. Inadequate statistical power and sample differences at the level of participant as well as of neighborhood likely contributed to inconsistent estimated effects by race.

Dynamic change of estrogen and progesterone metabolites in human urine during pregnancy

Glyphosate is a transformation product of a widely used aminopolyphosphonate complexing agent

Abstract Diethylenetriamine penta(methylenephosphonate) (DTPMP) and related aminopolyphosphonates (APPs) are widely used as chelating agents in household and industrial applications. Recent studies have linked APP emissions to elevated levels of the herbicide glyphosate in European surface waters. However, the transformation processes and products of APPs in the environment are largely unknown. We show that glyphosate is formed from DTPMP by reaction with manganese at near neutral pH in pure water and in wastewater. Dissolved Mn 2+ and O 2 or suspended MnO 2 lead to the formation of glyphosate, which remains stable after complete DTPMP conversion. Glyphosate yields vary with the reaction conditions and reach up to 0.42 mol%. The ubiquitous presence of manganese in natural waters and wastewater systems underscores the potential importance of Mn-driven DTPMP transformation as a previously overlooked source of glyphosate in aquatic systems. These findings challenge the current paradigm of herbicide application as the sole source of glyphosate contamination and necessitate a reevaluation of water resource protection strategies.

Abstract P1122: Reducing Sedentary Behavior and Cardiometabolic Biomarkers: Results from the RESET BP Trial

Introduction: Sedentary behavior is associated with cardiovascular disease and diabetes, yet evidence from randomized controlled trials (RCT) demonstrating a causal effect of sedentary behavior on cardiometabolic biomarkers is scarce. Hypothesis: A 3-month sedentary behavior reduction intervention will improve cardiometabolic biomarkers compared to controls. Methods: The Reducing Sedentary Behavior on Blood Pressure (RESET BP) RCT tested the effect of a multi-component sedentary behavior reduction intervention on blood pressure (primary outcome) and other cardiometabolic risk factors after 3 months among 271 desk workers with high blood pressure. Primary findings revealed no evidence of a blood pressure reduction despite a 1.2 hours/day greater reduction in sedentary behavior. Here we considered secondary/exploratory outcomes including aldosterone, plasma renin activity (PRA), lipids, insulin and glucose, and HOMA-IR. Blood samples were obtained at baseline and 3-month follow-up, after an overnight fast and a 30-minute seated rest, stored at -80°F until the end of the study, and analyzed by a central laboratory using standardized assays. We performed analysis of covariance with adjustment for baseline values for comparing groups. Results: RESET BP participants had mean age 45 years, mean blood pressure 129/83 mmHg, were 60% female, and 83% White. Among those with cardiometabolic biomarkers (n=173-188), intervention participants had a 14.97 ng/mL greater reduction in aldosterone (p=0.037) and 0.23 ng/mL/hour in PRA (p=0.046) over follow-up compared to controls, indicating a favorable change. Changes in other biomarkers showed no evidence of an intervention vs. control difference: LDL cholesterol (-2.35 mg/dL; p=0.443); HDL cholesterol (-0.72 mg/dL; p=0.543); triglycerides (3.52 mg/dL, p=0.627); glucose (-1.98 mg/dL; p=0.225); insulin (0.44 IU; p=0.723); and HOMA-IR (-0.10; p=0.808) Conclusions: Despite no evidence of improvement in resting blood pressure or other biomarkers, intervention-related decreases in aldosterone and PRA may suggest a novel mechanism of benefit to the renin-angiotensin-aldosterone system with sedentary behavior reduction.

Abstract P2023: Cannabis Use In Adolescence Is Not Associated With Differences In BMI Z-Scores

Introduction: Literature on cannabis use among adolescents and body mass index (BMI) is mixed; some but not all studies show a negative association between cannabis use and BMI. Yet, studies in adults show a consistent negative association between cannabis use and BMI. Therefore, we investigated associations between cannabis use and body mass index z-scores (BMI Z-scores) among adolescents. Hypothesis: We hypothesized that cannabis use in the past year is associated with lower BMI Z-scores in adolescents. Methods: Children of the Nurses’ Health Study II ages 9 to 14 in 1996 were recruited to participate in the Growing Up Today Study (GUTS 1). The GUTS 1 cohort investigated how diet and exercise influence weight changes over the lifecycle. This analysis included participants who had at least one BMI Z-score between the ages of 12 and 20 during the years in which cannabis use was assessed, 1999, 2001, 2003, and 2005; at the 1999 survey, participants were 12-17 years of age. Cannabis use was assessed with the question “Have you ever used marijuana in the past year.” Cannabis use was coded into a binary variable of yes/no. Self-reported weight and height were used to calculate BMI Z-scores for age. We used a linear mixed model with a random effect for participant ID to assess if cannabis use in the past year was associated with BMI Z-scores, and adjusted for age, sex assigned at birth, sexual orientation, cigarette smoking, alcohol use, physical activity, and sibling in the study. Missing data was handled with the missing indicator method. Results: A total of 13,432 participants had at least one BMI Z-score and contributed 30,756 observations in the model. In 1999, past year cannabis users (n=1128) had a mean age of 15.8 years, tended to smoke cigarettes (75.1%), met physical activity guidelines of 7+ hours of moderate to vigorous activity/week (77.2%) and consumed alcohol (68.1%). In 2005, past year cannabis users (n=2848) had a mean age of 20.5 years, tended to smoke cigarettes (68.2%), met physical activity guidelines of 7+ hours of moderate to vigorous activity/week (52.7%) and consumed alcohol (88.4%). Adjusting for age and natal sex, cannabis use was not associated with BMI Z-scores (b: 0.030; 95% CI: -0.010, 0.070 p=0.14) and was not materially different in the fully adjusted model (b: 0.026; 95% CI:-0.022 ,0.073; p=0.28) Conclusions: Among the GUTS 1 cohort, past year cannabis use was not associated with differences in BMI Z-scores among adolescents

Abstract P2050: Neighborhood-Level Racial and Ethnic Residential Segregation and Incidence of Atrial Fibrillation: The Multi-Ethnic Study of Atherosclerosis (MESA)

Introduction: Atrial fibrillation (AF) is the most common arrhythmia, affecting up to 6 million in the US, and is associated with significant morbidity and mortality. Despite higher rates of AF clinical and social risk factors, underrepresented racial and ethnic group (UREG) individuals have lower AF incidence. Structural factors, such as neighborhood-level racial/ethnic residential segregation, have been associated with incident cardiometabolic disease, particularly among UREG individuals. However, data on segregation and incident AF is sparse. Hypothesis: We hypothesized that adults living in more segregated neighborhoods would have a higher incidence of AF. Goals/Aims: We examined whether AF incidence differed across segregation categories among racial and ethnic groups. Methods: Administrative and clinical data from the Multi-Ethnic Study of Atherosclerosis (MESA; baseline 2000-2002) were used to identify those with a diagnosis of AF during follow-up. Own-group racial/ethnic segregation was defined by local GI* statistic, which compares the percent of each racial/ethnic group in a current census tract to the surrounding area. Racial/ethnic-stratified Cox proportional hazard models were created to estimate hazard ratios comparing across segregation levels. Models were adjusted for demographic factors, individual and neighborhood level socioeconomic factors, and clinical factors. Results: Our final cohort comprised 6,100 participants (27% Black, 12% Chinese, 22% Hispanic, 39% White). During a median follow-up of 14.2 years, 1,203 participants (19.7%) were diagnosed with AF. Black and Hispanic participants had the highest prevalence of AF risk factors at baseline. Black, Hispanic, and Chinese participants were more likely to reside in segregated neighborhoods (Table). After adjusting for demographic, socioeconomic and clinical factors, among all racial groups, neighborhood segregation was not associated with incident AF ( Table ). Conclusions: In this longitudinal analysis we did not observe a statistically significant association between residential segregation and AF incidence for any racial and ethnic groups in adjusted models. Further research is needed to understand how individual factors may intersect with clinical, healthcare, and structural factors to drive previously described differential incidence of AF.

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand

Abstract This study aims to construct a prediction model for the demand for medical and daily care services of the elderly and to explore the factors that affect the demand for medical and daily care services of the elderly. In this study, a questionnaire survey on the demand for medical and daily care services of 1291 elderly was conducted using multi-stage stratified whole cluster random sampling. SPSS21.0 statistical analysis software was used to describe the basic data of the elderly statistically, and univariate analysis was used to screen variables for model construction and binary logistic regression analysis. The acquired dataset has class imbalance, and to handle this issue, Synthetic Minority Over Sampling Technique with TomekLink (SMOTE-TomekLink) was adopted to resample the dataset for class-balancing. To improve computational efficiency, we used three algorithms to develop prediction models, including Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Light Gradient Boosting Machine (LightGBM) algorithms. The performance of each model was measured, and the performance of the prediction model was obtained using the following performance metrics: accuracy (ACC), recall (R), precision (P), F1-score, and area under the receiver operating characteristic (AUC). The prediction models for the medical and daily care services demand of the elderly were developed and validated using 12 and 13 key features, respectively. The LightGBM algorithm emerged as the superior prediction model for estimating the service needs of the elderly. For the medical service demand prediction model, LightGBM achieved an AUC of 0.910 and F1-score of 0.841. In the daily care services demand prediction model, LightGBM demonstrated an AUC of 0.906 and an F1-score of 0.819. In the LightGBM model, the analysis of feature importance indicates that the number of chronic diseases, education level, and financial sources emerge as the most significant predictors for the demand of healthcare services, encompassing both medical and daily care services. Based on questionnaire information combined with feature selection, unbalanced data processing and machine learning methods, this study constructed a machine learning model for predicting the demand for medical and daily care services for the elderly, and analyzed the influencing factors of the demand for medical and daily care services for the elderly, providing a reference for the construction and verification of future prediction models for the demand for medical and daily care services for the elderly.

PTN activity in quiescent neural stem cells mediates Shank3 overexpression-induced manic behavior

Abstract P1141: Breastfeeding and Postpartum Cardiovascular Health Behaviors at 3 Months in the Postpartum 24/7 Cohort

Introduction: Breastfeeding promotes long-term cardiovascular health (CVH), but breastfeeding or using a breast pump as a primary infant feeding method may limit a mother’s capacity to engage in healthy CVH behaviors during the postpartum period. This study aimed to evaluate whether breastfeeding status defined as direct or indirect (pumping) at 3 months postpartum is associated with Life’s Essential 8 (LE8) CVH behaviors, including physical activity, sleep, diet, and avoidance of nicotine. Hypothesis: Those breastfeeding at 3 months postpartum will have less optimal physical activity, sleep, and diet scores, but better nicotine exposure scores. Methods: This is a secondary analysis of the Postpartum 24/7 cohort (n=50) at 3 months postpartum. Breastfeeding status was self-reported (yes/no). CVH behavior scores were assessed using the LE8 framework, which included device-based measures of physical activity (activPAL), self-reported sleep duration (Pittsburgh Sleep Quality Index), a diet assessment tool (Mediterranean Eating Pattern for Americans), and self-reported past and current nicotine exposure. Each CVH behavior was scored from 0 (least healthy) to 100 (most healthy) and an overall mean score was calculated by averaging scores across components. Multiple linear regression evaluated the association between breastfeeding and CVH behavior score, adjusting for pre-pregnancy BMI, race, and education. Mann-Whitney U tests evaluated differences by breastfeeding status and each CVH component. Results: At 3 months postpartum, 80% of the cohort (n=40) reported breastfeeding. Adjusted models showed that overall mean CVH behavior scores were similar and moderate (ranged 50-79) for both breastfeeding [69.3 ± 2.9 (SE)] and non-breastfeeding [68.1 ± 5.1] groups (p=.81). For specific CVH behaviors, nicotine exposure scores were highest while diet scores were lowest (see Figure). Breastfeeding and non-breastfeeding groups also had similar median scores for sleep and nicotine exposure. However, breastfeeding mothers had higher median scores for diet and physical activity that were possibly clinically meaningful though not statistically significant. Conclusion: Overall, breastfeeding status was not associated with CVH behavior scores at three months postpartum. As postpartum women had only moderate CVH behavior scores, this indicates a significant opportunity in the life course for promoting CVH behaviors, and particularly diet, regardless of breastfeeding.

Abstract 033: Serum metabolite-based signatures of childhood cardiovascular risk factor burdens associate with subclinical cardiac structure in midlife: Findings from the Bogalusa Heart Study

Introduction: Childhood cardiovascular risk factors (CVRF) are known to independently contribute to the risk of cardiovascular disease (CVD) later in life. However, childhood data is often unavailable when assessing adult risk. While CVRFs significantly impact the metabolome, metabolomic signatures of childhood CVRF burdens have not been identified. Hypothesis: This study aimed to identify metabolomics signatures reflecting cumulative childhood CVRF burden and assess their associations with subclinical cardiac structure in midlife. Methods: This study included 1,068 participants from the Bogalusa Heart Study (BHS) who underwent untargeted serum metabolomics profiling in midlife and had repeated childhood (aged 4-17 years) measures of clinical CVRFs, including BMI, systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), and glucose. The cumulative childhood burden of CVRFs was estimated as the area under the curve (AUC). Elastic net regression was used to construct metabolomic signatures for each childhood CVRF AUC, with 80% of the data used for training and 20% for testing. Associations were examined between metabolomic signatures of childhood CVRF AUCs and midlife subclinical cardiac structure, including left ventricular (LV) mass index (LVMI), relative wall thickness (RWT), and left ventricular geometry (LVG). Results: Metabolomic signatures of AUCs for childhood BMI, SBP, LDL-C, TGs, and glucose consisted of 18, 2, 11, 20, and 40 metabolites, explaining 15%, 1%, 12%, 23% and 38% of the variance in the testing dataset, respectively (p<0.001, except SBP AUC signature: p=0.038). Consistent with prior findings in the BHS, AUCs for childhood BMI, SBP, and TGs were associated with midlife LVMI, RWT and LVG, after adjusting for demographic and lifestyle risk factors (data not shown). Increases in the metabolomic signatures for childhood AUCs of BMI, SBP, and TGs were also significantly associated with elevated LVMI, RWT, and higher odds of LVG (all p<0.001, Table ). Notably, most associations for childhood BMI AUC remained significant after adjusting for midlife clinical measures, including known mediators of childhood burden's effect on adult LV changes ( Table ). Conclusion: Metabolite-based signatures capture childhood CVRF burden and are associated with midlife changes in cardiac structure, independent of adult exposure. These signatures show potential as surrogates when childhood exposure data is unavailable.

Abstract P1074: Assessing Health Literacy and the Role of Race and Social Determinants in Cardiac Patients.

Background: Health literacy is a crucial factor influencing the care outcomes of patients with cardiovascular disease (CVD). This study aimed to explore how socioeconomic factors, particularly income, education, and digital health literacy, contribute to patients’ understanding of their diagnosis and treatment following acute cardiac events. Methods: Over 3 months, we surveyed 50 patients at their first clinical visit post-hospitalization. The information was analyzed, social determinants were evaluated using Fisher's t-test, and logistic regression was used to study the predictive power of various factors. Results: The median age was 55 years, with 52% male and 50% identifying as African American. Education and income were key factors: 66.7% of participants had a high school or lower education level, and 71% had an annual income below $50,000. Notably, 50% of patients accessed their healthcare records via a digital patient portal, while 20% reported conducting personal research to better understand their condition. While 60% of participants expressed a good understanding of their diagnosis, 36% understood their treatment plans, and just 8% comprehended all aspects of their care, including expected clinical outcomes. Digital health literacy, specifically accessing healthcare records through the portal, was strongly associated with a better understanding of treatment plans. Income and educational attainment also played significant roles, with lower levels linked to greater challenges in understanding care instructions. Conclusion: Contrary to expectations, race and gender were not significant predictors of health literacy in this study. These findings suggest the need for targeted interventions focused on improving digital health literacy and supporting patients with lower education and income levels to enhance their understanding of cardiac care.

Risk factors and protective strategies for hypotony following preserflo microshunt implantation

Sub-minute synthesis and modulation of β/λ-MxTi3-xO5 ceramics towards accessible heat storage

Abstract P1063: Association of Demographic and Clinical Factors with SARS-CoV-2 Anti-Nucleocapsid Antibody Response Among Previously Infected US Adults: The C4R Study

Background: Despite the availability of effective vaccines and a recent decrease in annual deaths, coronavirus disease-2019 (COVID-19) remains a leading cause of death. Serological studies of anti-nucleocapsid (N) antibody response to infection provide insights into host immunobiology of adaptive immune response, which holds promise for identifying high-risk individuals for adverse acute and chronic COVID-19 outcomes. Hypothesis: Among participants previously infected with SARS-CoV-2, traditional vascular disease risk factors are associated with higher anti-N antibodies while vaccination is associated with lower anti-N antibodies. Methods: Among previously infected participants, anti-N antibodies were measured from dried blood spots collected between February 2021-February 2023 among 1,419 Collaborative Cohort of Cohorts for COVID-19 Research (C4R) participants with prior SARS-CoV-2 infection. We measured anti-N IgG antibodies reported as median fluorescence intensity (MFI) units; reactivity (i.e., seropositivity) was defined based on MFI above a validated threshold. Vascular disease risk factors were assessed via pre-pandemic in-person examination, questionnaires, and medical record review. Multivariable generalized linear models regressed anti-N reactivity (modified Poisson) or LN transformed MFI (linear). Results: Among 1,419 participants with prior infection, mean age (standard deviation) was 65.8(12.1) years, 61% were women, and 42.8% were self-reported from a race/ethnicity minority group. Participant reactivity to nucleocapsid peaked at 69% by 4 months post-infection and waned to only 44% ≥12 months after infection. After multivariable adjustment, higher anti-N antibody response was associated with older age, Hispanic (vs. White) or American Indian (vs. White) race/ethnicity, lower income and education, former smoking, and higher anti-spike antibody levels. Asian race (vs. White) and vaccination ( even after infection ) were associated with lower nucleocapsid reactivity; common cardiometabolic co-morbidities were not associated with anti-N reactivity or levels (Figures 1 and 2). Conclusions: Among participants previously infected with SARS-CoV-2, select sociodemographic and behavioral risk factors were associated with higher anti-N antibody levels while vaccination was associated with lower anti-N antibody levels. The observation that vaccination, even after infection, is related to lower anti-N antibody levels merits further investigation.