Browse Articles

Abstract P1097: Geographic Variation of Healthcare Expenditures Among U.S. Adults with Heart Failure, 2012-2022

Introduction: Heart failure is a public health burden that currently affects over 6 million individuals in the United States and is estimated to continue to increase over the coming decade. Despite improvements in clinical outcomes, heart failure is associated with increased morbidity and mortality that place a significant financial strain on individuals and the healthcare system. However, little is known about the geographic variation in healthcare expenditures for heart failure. Methods: Data from the Medical Expenditure Panel Survey (MEPS) from 2012-2022 were used to estimate the national and regional (Northeast, Midwest, South, West) heart failure-attributable healthcare expenditures. A two-part model, adjusted for demographics, comorbidities, and time, was applied to estimate the total healthcare expenditures for individuals with heart failure, as well as service-specific expenditures, including inpatient stays, outpatient care, emergency room visits, physician office visits, home care visits, and prescription medication. Results: In the final sample, 1,180 adults (0.80%) were identified as having heart failure. After adjusting for demographics and clinical comorbidities, the estimated incremental cost of heart failure in adults was $7,586 ± 1571 per person. There was significant regional variation in total heart failure-related expenditures: the Midwest exhibited the highest total incremental costs at $10,309 ± 2,974, followed by the Northeast ($7,303 ± 1,530), the South ($6,467 ± 18.92), and the West ($6,371 ± 3,388), which had the lowest expenditures. Similar differences in incremental costs by geographic regions throughout the nation were exhibited in service-specific expenditures. Conclusion: Heart failure related healthcare expenditures varied throughout the nation, with the Midwest region experiencing higher expenditures. This variation highlights the need for target interventions in these specific states. Understanding the geographic differences in overall and service-specific expenditures will have important implications for resource allocation and healthcare policy, with the ultimate goal of reducing the financial burden on affected individuals.

Abstract MP62: Health Behaviors Among Nulliparas With Planned and Unplanned Pregnancies

Introduction: The relationship between pregnancy planning and health behaviors in the preconception and antepartum periods remains unclear. This study aimed to compare health behaviors before and during pregnancy between nulliparous individuals with planned and unplanned pregnancies. Methods: This is a secondary analysis of the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be. The present study included nulliparas who indicated whether their pregnancy was planned or unplanned. Preconception and antepartum health behaviors were compared between planned and unplanned pregnancies using bivariate and multivariate analyses. Results: Among the 8,765 participants included, 5,202 (59.3%) had planned pregnancies, and 3,563 (40.7%) had unplanned pregnancies. Planned pregnancies were associated with older age, lower body mass index, white race, college education, higher income, and commercial insurance (p≤.001). Participants with unplanned pregnancies were more likely to have chronic hypertension and pregestational diabetes, and to be Hispanic or Latino, unmarried or unpartnered, and unemployed (p≤.001). In bivariate analysis, tobacco use, secondhand smoke exposure, and illicit drug use were more frequent among unplanned pregnancies three months preconception and throughout all three trimesters whereas engagement in physical activity was higher among planned pregnancies. Healthy Eating Index-2010 scores were also higher pre-pregnancy among planned pregnancies (Table). After adjusting for maternal age, education, marital status, income, commercial insurance, employment, chronic hypertension, and pregestational diabetes, these associations persisted (Table). Conclusion: Nulliparas with planned pregnancies demonstrated healthier behaviors that included less tobacco use, secondhand smoke exposure, and illicit drug use and greater engagement in physical activity and healthy eating. These associations persisted beyond the preconception period throughout pregnancy. This underscores the importance of preconception counseling and interventions as they not only improve health behaviors before pregnancy but also sustain these healthy practices throughout pregnancy.

Deletion of pcnB affects antibiotic susceptibility in resistant Escherichia coli by reducing copy number of ColE1-family plasmids

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Abstract 072: Plasma Metabolome Predicts Long-term Body Weight Gain and Type 2 Diabetes in Non-Obese Individuals

Introduction: Body weight is known to modulate the human blood metabolome, although whether certain plasma metabolomic profiles predict long-term weight change remains unknown. Hypothesis: We hypothesize that there are inter-relationships between plasma metabolome, current weight, weight change, and incident type 2 diabetes (T2D). Methods: We measured 260 annotated metabolites among 7, 499 participants in Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow-up Study using nontargeted LC-MS. We assessed the associations of these metabolites and BMI trajectory since blood draw during 26.0 years of follow-up using a mixed-effect model, also by BMI groups at blood draw (lean: 18.5-24.9 kg/m 2 , overweight: 25.0-29.9 kg/m 2 , and obese: ≥30 kg/m 2 ). A metabolomic score reflecting BMI change slope was identified using elastic net regression with a training/testing approach. Associations between the metabolomic scores and T2D were evaluated using Cox proportional hazards regression. Results: Cross-sectionally, metabolites associated with current BMI level among lean, overweight, and obese individuals minimally overlapped (of 260 metabolites, 2 overlapping among the three groups). Distinct metabolomic profiles associated with BMI trajectories were also identified among the three groups. While 46 metabolites significantly predicted BMI change slope in the lean group, only 20 and 13 metabolites predicted the slope among overweight and obese groups, respectively, with no metabolites overlapping among the three groups. Among lean individuals, the elastic net regression identified 82 metabolites, predominantly lipids and organic acids, to construct a score that reflected faster BMI gain. The score was significantly associated with the BMI slope in lean group (training: Spearman r = 0.33; testing: Spearman r = 0.20), but the correlation was weaker among overweight, and obese groups (Spearman r = 0.15, and 0.08, respectively). The metabolomic score was significantly associated with a higher risk of T2D in the lean group (aHR per 1SD: 1.41 [95% CI 1.25-1.59]) and overweight group (aHR per 1SD: 1.29 [95% CI 1.17-1.42]) groups, but not in the obese group. Conclusions: Metabolomic profiles associated with current BMI and BMI trajectory differ significantly among lean, overweight, and obese individuals. A metabolomic score that predicts BMI change is associated with higher T2D risk in lean and overweight individuals, but not among obese individuals.

Abstract P1062: Pre-Pandemic Thrombo-inflammatory Biomarkers and Risk of Severe Covid-19: the Collaborative Cohort of Cohorts for Covid-19 Research (C4R)

Background: Thrombo-inflammation is a hallmark of acute Covid-19, with higher thrombo-inflammatory markers during infection associated with adverse outcomes. We hypothesized that higher pre-pandemic biomarkers, reflecting a higher thrombo-inflammatory setpoint, might identify people at greater risk of severe manifestations of Covid-19. Hypothesis: Pre-pandemic inflammation markers are associated with risk of hospitalized or fatal (hereafter, “severe”) Covid-19 in a multi-ethnic US sample. Methods: From 2020-2023, C4R harmonized pre-pandemic measures and ascertained Covid-19 across 14 longstanding cohort studies. In 12 cohorts, we assessed biomarker data and covariates from the study visit closest to the pandemic for 6 analytes shown in the Table. HRs of severe Covid-19 by pre-pandemic biomarkers were estimated using cause-specific Cox regression, treating non-severe Covid-19 as a competing risk, and adjusting for pre-pandemic sociodemographic and clinical characteristics. Results: Biomarkers were measured a mean of 20 years before the pandemic with different sample sizes for each (Table footnote). Mean age at the start of the pandemic was in the 60s or 70s depending on the biomarker. The most represented race or ethnic groups were White and Black. The largest sample was for C-reactive protein, and there were 1,001 severe Covid-19 cases among 38,784 participants. In the adjusted models, considered individually, higher CRP, leukocyte count, factor VIII and fibrinogen, but not other markers, were associated with greater risk of severe Covid-19 (Table).Associations were robust across subgroups and time since biomarker measurement (example for C-reactive protein in Figure). Conclusions: In this prospective multi-study analysis of a multi-ethnic population, higher basal levels of thrombo-inflammation markers were associated with greater risk of severe Covid-19. Since we considered non-severe Covid-19 as a competing risk, associations may reflect factors related to progression to more serious Covid-19 illness.

Multiple item representations in visual working memory simultaneously guide attention

Resilient tree-planting strategies for carbon dioxide removal under compounding climate and economic uncertainties

To meet decarbonization targets, nations around the globe have made ambitious commitments to expand forested land. Operationalizing these commitments requires choosing a planting strategy: How many trees should be planted, of which species, and where? Given those choices must be made now but have long-term consequences, such decisions are plagued by uncertainty. For example, species that are well suited to present conditions may perform poorly under future climates, yet those future climates are themselves highly uncertain. Using the exemplar of the United Kingdom, a nation committed to achieving net zero emissions by midcentury, we quantify key uncertainties pertaining to coevolving climate and economic conditions and examine how modern methods of decision-making under uncertainty can advise on planting choices. Our analysis reveals that the best planting strategy assuming a “high-emissions” future is radically different to that for a future that remains on a “near-historic” path. Planting for the former while experiencing the latter results in substantial net costs to UK society. Assimilating uncertainty into decision-making identifies planting strategies that diversify risk and significantly reduce the probability of high-cost outcomes. Importantly, our research reveals that the scope for mitigating risk through choice of planting strategy is relatively limited. Despite this persistent risk, we find that tree planting remains a highly cost-effective carbon removal solution when compared to alternative technologies, even when those alternatives are assumed to be riskless.

Abstract MP34: Circulating Adipocyte-Derived Extracellular Vesicles Increase with Overweight and Obesity and are Associated Endothelial Dysfunction

The prevalence of overweight/obesity continues to increase in the United States. With increased adiposity there is a shift in the phenotype and biology of adipose tissue resulting in an adipocyte secretome with proatherogenic consequences. Clinical interest in adipocyte-derived extracellular vesicles (Ad-EVs) has intensified due to their potential as systemic mediators of overweight- and obesity-related cardiometabolic dysfunction. While there are experimental data to suggest that Ad-EVs contribute to cardiovascular risk, to date there are no clinical data establishing a link between circulating Ad-EVs and vascular endothelial function. The purpose of this ongoing study is to determine: 1) if circulating Ad-EV levels are elevated in adults with overweight and obesity, independent of other cardiometabolic risk factors; and if so, 2) whether circulating Ad-EVs are associated with adiposity-related endothelial vasodilator dysfunction. Twenty-four sedentary, mid-life adults (45-66 years) were studied: 8 normal weight (4M/4F; age: 56 + 3 yr; BMI: 21.2 + 0.7 kg/m 2 ); 8 overweight (4M/4F; 56 + 2 yr; 28.4 + 0.3 kg/m 2 ); and 8 obese (4M/4F; 57 + 2 yr; 31.5 + 0.8 kg/m 2 ). All subjects were free of overt cardiometabolic disease. Ad-EV identification (perilipin A + vesicles) and concentration in peripheral blood were determined by flow cytometry. Forearm blood flow (FBF: via plethysmography) was assessed in response to intra-arterial infusions of acetylcholine (4.0, 8.0 and 16.0 μg/100 mL tissue/min) and sodium nitroprusside (1.0, 2.0 and 4.0 μg/100 mL tissue/min). Circulating Ad-EVs were markedly higher (P<0.001) in overweight (236 + 35 Ad-EV/µL) and obese (417±57 Ad-EV/µL) compared with normal weight (107±11 Ad-Ev/µL) adults. Additionally, Ad-EVs were higher (P<0.004) in the obese vs overweight adults. FBF response to acetylcholine was significantly lower (~35%) in the overweight (from 4.5±0.3 to 11.5±0.8 mL/100 mL tissue/min) and obese (from 4.7±0.3 to 9.7±0.8 mL/100 mL tissue/min) vs normal weight group (from 5.0±0.4 to 16.1±1.1 mL/100 mL tissue/min). Ad-EVs were strongly and inversely associated with the vasodilator response to acetylcholine (r=-0.74; P<0.001). In conclusion, increased adiposity, independent of other cardiometabolic risk factors, is associated with elevated circulating levels of Ad-EVs. Moreover, these circulating Ad-EVs may serve as a biomarker of, and possible contributor to, adiposity-related endothelial dysfunction and vascular disease risk.

Abstract P1095: Hair Cortisol Concentration, Perceived Stress, and Physical Activity Among Patients with Heart Failure

Introduction: Patients with heart failure (HF) often experience chronic stress arising from symptom burden and distress about the future. Chronic stress can be measured subjectively through questionnaires and objectively through biomarkers such as hair cortisol concentration (HCC). Cortisol, a catabolic hormone associated with skeletal muscle loss, may be associated with a decrease in physical activity (PA) tolerance. The interplay between chronic stress and PA may vary across different HF etiologies, including heart failure with reduced and preserved ejection fraction (HFpEF and HFrEF), and combined HF, due to differing underlying contributing factors. Therefore, this study aimed to examine the associations between perceived stress, HCC, and PA among patients with different HF etiologies. Methods: In this cross-sectional study, perceived stress was measured using The Perceived Stress Scale (PSS-10). HCC (pg/mg) was derived from cortisol collected from hair samples (3cm long, 20mg in weight) and analyzed using enzyme immunoassay. The International Physical Activity Questionnaire Short form (s-IPAQ) was used to measure PA. Results: The sample included 28 patients with HFrEF (mean EF: 41 ± 9%), 7 patients with HFpEF (mean EF: 54 ± 6%), and 11 patients with combined HF (mean EF: 43 ± 8%). Overall, participants were 71.8 + 11.2 years old, 44% female, 87% White, 4% Black, and 9% Hispanic. HCC was not significantly associated with perceived stress in any group. However, HCC was strongly and positively associated with PA among patients with HFpEF ( r = 0.91, p < 0.005), but not among patients with HFrEF ( r = -0.09, p = 0.64) or combined HF ( r = 0.26, p = 0.44). Conclusions: The absence of correlation between perceived stress and HCC suggests a potential dissociation between psychological and physiological stress in HF patients which could be due to a blunted stress response in chronic illness or to use of adaptive coping. Despite a small sample, PA was significantly and positively associated with HCC among patients with HFpEF, which was unexpected. PA in HFpEF patients may serve as a physiological stressor that increases cortisol production to help regulate metabolism. Because HFpEF is often associated with chronic inflammation, metabolic syndrome, and other morbidities, physical exertion may also augment the stress response. Further research examining the association between chronic stress and PA with larger samples and objectively measured PA measures is needed.

On the effectiveness of electrical characterization of mature Staphylococcal Biofilm

In the activation of HPV-specific human B cells HPV-VLP vaccines mimic membrane-associated antigens

B cell responses to membrane-presented antigens appear to be strongly favored over soluble antigens in vivo suggesting that vaccines that mimic membrane-presented antigens may be highly efficacious. We recently demonstrated that human B cell responses to membrane-associated but not to soluble antigens in vitro depended on the expression and activity of the plasma membrane mechanosensitive ion channel, Piezo1. Here, we provide evidence that the efficacy of the current human papillomavirus virus-like particle (HPV VLP) vaccines may be due in part to their inherent ability to mimic Piezo1-dependent membrane presentation of antigens to B cells. We compared HPV-specific human B cell responses to HPV VLPs versus soluble HPV pentameric capsomeres and showed that although both induced calcium responses, only HPV VLP-induced responses were blocked by Piezo1 inhibitors. The kinetics of internalization of HPV-VLP and capsomeres into HPV-specific B cells were similar and neither required Piezo1 function as shown by small interfering RNA (siRNA)-mediated knockdown of Piezo. However, trafficking of HPV-VLPs into intracellular major histocompatibility complex (MHC) class II, lysosomal associated membrane protein 1 (LAMP1) + antigen-processing compartments was Piezo1-dependent, whereas trafficking of capsomeres was not. In addition, a time course of intracellular trafficking suggested that colocalization of HPV-VLP with MHC classII was more stable over time as compared to capsomeres. Taken together these findings suggest that the ability of HPV-VLP vaccines to mimic Piezo1-dependent membrane antigen presentation may be exploited in the design of highly effective human vaccines.

Abstract P1031: Impact of Psychosocial and Socioeconomic Stress on Metabolic Health and Body Mass Phenotypes: Insights from the Hispanic Community Health Study/Study of Latinos

Background: Chronic psychosocial stress and low socioeconomic status (SES) are linked to adverse health outcomes, including cardiometabolic diseases. This study investigates how these stressors impact metabolic health and body mass (MHBM) phenotypes in Hispanic/Latino adults. Objective: To assess the associations between chronic stress, SES, and MHBM phenotypes in Hispanic/Latino adults. Methods: A cross-sectional analysis was conducted using data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sociocultural Ancillary Study (SCAS) (N=4,712, mean age 45.3±10.4 years, 52% female). Chronic stress was measured via the Chronic Burden Scale, SES was evaluated by education and income, and MHBM was assessed using BMI, waist circumference, blood pressure, lipid profiles, and glucose. Multivariable polytomous logistic regression models were used to assess associations between chronic stress, SES, and MHBM phenotypes. Results: Metabolically unhealthy phenotypes were prevalent (40% MUOB; 31% MUOW), while healthier phenotypes (MHNW, MHOW, MHOB) represented smaller proportions (4-7%). Table 1 shows that chronic stress was significantly associated with increased odds of MHOB (OR=1.19, 95% CI: 1.01–1.40) and MUOB (OR=1.19, 95% CI: 1.06–1.34); however, losing significance after adjustment. Low SES compared with high SES was significantly associated with higher odds of MUOB in both unadjusted (OR=2.37, 95% CI: 1.46–3.87) and adjusted models (aOR=2.37, 95% CI: 1.46–3.87). Low SES was also significantly associated with MUNW (OR=2.15, 95% CI: 1.33–3.50) and MHOW (OR=2.14, 95% CI: 1.38–3.32) in unadjusted models but not in adjusted models. Moderate SES compared to high SES was not significantly associated with any phenotypes in either model. Conclusion: This study highlights the lasting impact of chronic stress and low SES on metabolic health in Hispanic/Latino adults. Interventions targeting stress reduction and social risk may help prevent and manage metabolic disorders in this population.

Abstract P1091: Association of NSAIDs Use, Pain Interference, and Incident Heart Failure among REGARDS Participants with Diabetes.

Background: Diabetes mellitus (DM) is a risk factor for heart failure (HF). People with DM frequently have chronic pain, often treated with non-steroidal anti-inflammatory drugs (NSAID). Past research suggests that NSAID use among people with DM may be associated with cardiomyopathy. Therefore, we examined the association of NSAID use with incident HF hospitalization overall and by HF subtype among adults with DM. Methods: Incident HF hospitalizations and HF deaths were expert-adjudicated in the REasons for Geographic and Racial Differences in Stroke (REGARDS) biracial cohort (age ≥ 45 years), recruited in 2003-07 from the continental US. Baseline DM was defined by fasting or random serum glucose, anti-diabetic medication use, and/or self-report. Baseline NSAIDs use came from medication bottle review at an in-home visit and baseline pain interference was self-reported using the SF-12 scale. Propensity for NSAIDs use was computed using 54 baseline participant characteristics. Cox proportional hazards regression, adjusted for propensity score for NSAID use, examined risk for HF overall, by pain interference, and by opioid use. Results: We studied 5483 HF-free REGARDS participants with DM, aged 64 years; 53% female, 56% Black, 15% on NSAIDs, and 27% reporting pain interference in the past week. Over median 15-year follow up, there were 584 incident HF events. We observed no statistically significant associations between NSAID use and incident HF overall (TABLE). However, among those with high pain interference, NSAID use was associated with 1.5-fold increased risk of incident HF compared to similar NSAID nonusers, without differences by HF subtype. NSAID use was associated with 2-fold higher risk of incident HF among prescription opioid users compared to nonusers. Conclusions: Among adults with DM, NSAID use was associated with increased risk of incident HF among those with higher pain interference or concurrent opioid intake. NSAIDs should be used in people with DM with caution.

Production, isolation, optimization, and characterization of microbial PHA from Bacillus australimaris

Abstract Population explosion in recent years has driven the environment to overuse nondegradable substances. Microbial polyesters known as polyhydroxyalkanoates (PHAs) are generated and retained as cytoplasmic granules in microorganisms with restricted nutritional availability and can be used to manufacture bioplastics. The current study attempts to screen soil isolates for PHA production and optimize their media parameters. Among all the isolates, 17 were identified and confirmed by Sudan black staining, as they are screening for PHA production and are identified by their colony characteristics. The isolation of the most promising strain, GS-14, was achieved through the sodium hypochlorite method, and subsequent quantification involved establishing a standard curve of crotonic acid. Notably, isolate GS-14 presented the highest yield, which was determined by extrapolating its data onto the standard curve. Characterization of the PHA polymer was subsequently performed, and the results were used to discern its properties. FTIR confirmed characteristic PHA absorption bands, with a prominent C = O stretching peak at 1732 cm⁻¹. LC-MS detected a molecular mass of 641.6 g/mol, indicative of an oligomeric species, while the actual polymer molecular weight is estimated between 5,000 and 20,000 Da. DSC revealed an exothermic peak at 174 °C, allowing the calculation of crystallinity, a key determinant of mechanical properties. Furthermore, the PHA-producing organism was identified as Bacillus australimaris through the sequencing of 16 S ribosomal RNA. The media optimization was performed via Minitab software, with statistical analyses employed to interpret the resulting data comprehensively.

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Abstract P2074: The Association of Lipoprotein(a) with Atherosclerotic Cardiovascular Disease Events and All-cause Mortality in US Hispanics/Latinos: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

Background: Lipoprotein(a) [Lp(a)] is associated with atherosclerotic cardiovascular disease (ASCVD). An Lp(a) threshold of ≥125 nmol/L is commonly used to identify those at higher risk, but there is paucity of data on Hispanic/Latino individuals. Methods: We evaluated the association between Lp(a) and myocardial infarction (MI), ischemic stroke (IS), and all-cause mortality (ACM) among 16,117 self-identified Hispanic/Latino HCHS/SOL participants. Event rates were compared across Lp(a) quintiles and below/above median IQR. Multivariable Cox proportional hazard models assessed the relationship between events and Lp(a) (log-transformed, per quintiles and above/below 125 nmol/L). Kaplan-Meier curves showed outcome-free survival across quintiles. Sampling weights and survey methods were used to accommodate the stratified probability sampling of the cohort. Results: Among HCHS/SOL participants (median age 41.1 years, 52.4% female), the median Lp(a) was 19.7 nmol/L (IQR 7.3-60.6), 11.4% had an Lp(a) over 125 nmol/L, and the highest quintile of Lp(a) was >77 nmol/L. Over a median of 9.8 years, 883 events (135 MI, 99 stroke, 649 ACM) occurred. Incident MI and ACM, but not IS, occurred more often in those in the highest quintile of Lp(a) compared with other quintiles. In multivariable models, continuous log-transformed Lp(a) and categorial Lp(a) (fifth quintile) were independently associated with incident MI but not IS or ACM. Lp(a) ≥125 nmol/L was associated with a higher risk of both incident MI and ACM. Outcome-free survival was significantly lower for the highest Lp(a) quintiles, Figure 1. Conclusion: Hispanic/Latino individuals with elevated Lp(a) are at increased risk of MI and ACM. Although Lp(a) ≥125 nmol/L is a valid risk threshold, Hispanics/Latinos show an increased risk at a lower Lp(a) threshold.

Abstract 040: Statin Initiation Is Not Associated With Gut Microbiome Changes: Findings from the Baltimore Longitudinal Study of Aging

Introduction: Gut microbiome (GMB) has been implicated in the cholesterol-lowering effects of statins. Observational studies and animal models suggest statins increase GMB diversity and alter GMB composition. However, secondary analyses of a rosuvastatin trial (N=20/arm) did not support these findings. This trial was limited in demographics (Norwegian women) and GMB measurement (16s rRNA sequencing, which lacks data on species and function). We sought to emulate a randomized trial of statins on GMB in a longitudinal cohort with greater demographic inclusion and higher-resolution GMB sequencing. Hypothesis: Statins increase GMB diversity and alter GMB composition and function. Methods: We selected statin initiator and non-initiator-matched participants from the Baltimore Longitudinal Study of Aging. Eligible participants had to have 2+ GMB samples (collected between 2013 and 2019), be statin naïve at start of collection, have non-missing matching covariate data, and be statin eligible at their baseline visit (using 2013 ACC/AHA Guidelines). We used a 1:1 matching algorithm on the baseline propensity score, with nearest-neighbor matching on age, BMI, education, LDL-c, and ASCVD lifetime risk category (Yes/No/Prior ASCVD event); and exact matching on sex, diabetes status, smoking, and race. We measured GMB features (diversity, composition, and functional genes) using shotgun sequencing. We tested associations of statin initiation with post-treatment GMB alpha diversity and with changes in GMB beta diversity using ANCOVA g-computation, and with differential abundance of microbial species and functional genes using ANCOM-BC2. We adjusted models for the baseline matching covariates; alpha diversity models were further adjusted for baseline alpha diversity. Results: We identified N=30 matched pairs (N=60 total; 40% female, 30% Black). Matching covariates were well-balanced (all absolute standardized mean differences <0.1). Samples were also balanced on baseline GMB features. Among treated participants, statins lowered LDL-c (B: -40.7, 95%CI: -53.8 to -27.6), but did not affect other lipids. Statins were not associated with GMB diversity. Statins decreased Bifidobacterium pseudocatenulatum and altered 10 functional genes (mostly increased fatty acid biosynthesis) (all p <0.05); however, these associations were not significant at FDR <0.20. Conclusions: Using an emulated randomized trial, statins did not alter GMB diversity, but may induce changes in GMB function.

Navigating artificial general intelligence development: societal, technological, ethical, and brain-inspired pathways

Cluster dynamical mean-field study of intra-unit-cell charge nematicity in hole-doped cuprates

Recent scanning-tunneling microscopy on hole-doped Bi 2 Sr 2 CaCu 2 O 8 , one of the materials of the cuprate family, finds a long-range ordered spontaneous splitting of the energy levels of oxygen orbitals inside the CuO 2 unit cells [S. Wang et al ., Nat. Mat. 23, 492–498 (2024)]. This spontaneous intra-unit-cell orbital ordering, also known as electronic nematicity, breaks C 4 symmetry and is thought to arise from the Coulomb interaction (denoted by V pp ) between oxygen p x and p y electrons. In this work, we study the spontaneous emergence of electronic nematicity within the three-band Hubbard [aka the Emery-VSA (Varma-Schmitt-Rink-Abrahams) model], using cluster dynamical mean-field theory. This method incorporates short-range electronic correlations and gives us access to the density of states, a quantity that is directly probed in experiments. We argue that there is a delicate competition between V pp and V pd (the latter being the Coulomb interaction between copper d x 2 − y 2 and oxygen p x , y electrons) that must be taken into account in order to find a Zhang-Rice singlet band well-resolved from the upper Hubbard band, and a splitting of the charge-transfer band (one of the signatures of charge nematicity) by roughly 50 meV, as observed recently.