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Background: Haptoglobin has three common genotypes: Hp 1-1, Hp 2-1, and Hp 2-2. The Hp 2-2 genotype, known to have poorer antioxidizing capacity, is associated with worse cardiovascular outcomes in select patients with diabetes. In this study, we explore the association between various cardiometabolic biomarker profiles and the three Hp genotypes in a multiethnic population. Methods: A cross-sectional analysis was performed for all participants with diabetes in the Dallas Heart Study and Multi-Ethnic Study of Atherosclerosis cohorts. Hp genotype was measured in 1,158 participants (399 from DHS and 759 from MESA) using ELISA technique (Savyon Diagnostics, Ltd). Associations between Hp genotype and 26 cardiometabolic circulating and imaging biomarkers were assessed by ANOVA and stratified by ethnicity. Results: The study included 51% women, 44% Black (513 of 1,158: Hp 1-1=45%, Hp 2-1=35%, Hp 2-2=20%), 26% Hispanic (300 of 1,158: Hp 1-1=25%, Hp 2-1=49%, Hp 2-2=26%), 20% White (237 of 1,158: Hp 1-1=16%, Hp 2-1=56%, Hp 2-2=28%), and 9.2% Asian/Pacific Islander/East Indian (107 of 1,158: Hp 1-1=15%, Hp 2-1=36%, Hp 2-2=49%) participants. Significant differences were seen in lipid metabolism as well as atherosclerosis, inflammatory, structural, and endothelial markers with no significant differences seen in imaging biomarkers. In White participants, Hp 1-1 was associated with elevated total cholesterol (p=0.016), LDL-p (p=0.001), and LDL-C (p=0.004). In Asian/Pacific Islander/East Indian participants, Hp 2-2 was associated with elevated systolic blood pressure (p=0.029), BMI (p=0.029), and inflammatory markers such as IL-6 (p=0.018) and D-dimer (p=0.027). In Black participants, Hp 2-2 was associated with elevated ICAM (p=0.048) and BMI (p=0.007). Lastly, in Hispanic participants, no significant associations were seen. In exploratory analysis, when comparing Hp 1-1 and Hp 2-1 with Hp 2-2, there was greater magnitude effect size of certain biomarkers in Black and Asian participants, suggesting potential differential effects by ethnicity. Conclusion: Associations between Hp genotype and various cardiometabolic biomarkers are varied and ethnicity dependent with further studies needed to investigate the underlying physiologic mechanisms.

Background: Prior prognostic models for acute decompensated HF (ADHF) have incorporated race as a covariate may not have completely account for the social and biological factors that underlie the racial disparities in outcomes. We developed race-specific models to improve risk prediction and better identify race-specific predictors of mortality in patients with ADHF using machine learning (ML) methods. Methods: Race-specific ML-models for in-hospital mortality were developed and validated in ADHF patients enrolled in the GWTG-HF registry between 2007 to 2020 (14,586 Black and 50,351 Non-Black adults) using over 40 candidate variables. External validation was performed among participants from the ARIC study with ADHF (n=1,115 Black and 2,028 Non-Black adults). The discrimination and calibration was compared with a previously validated risk score and cohort-specific logistic regression (LR) models. The changes in model reclassification performance with addition of zip-code level data of socioeconomic (SES) parameters was also assessed. Results: In the GWTG-HF cohort, the ML models had superior performance in both Black and Non-Black participants compared with the traditional GWTG-HF risk score ( Table ). The superior performance of the ML-model was also observed in the external validation cohort as compared with the other LR models ( Table ). Addition of measures of SES did not meaningfully change the performance but improved the reclassification metrics of the ML-models with net up-classification of risk in Black [NRI = 0.21 (0.07, 0.35)] and down-classification in Non-Black patients [NRI = -0.08 (-0.12, -0.04)]. SES was responsible for 21.7% of the total attributable mortality risk in Black adults compared to 0.4% in Non-Black adults. Conclusion: Race-specific, ML-based mortality models demonstrated superior performance when compared to traditional HF mortality risk models. Socioeconomic distress is an important contributor to risk in Black adults.

Introduction: Hepatic steatosis (HS) is associated with coronary artery disease (CAD) and cardiovascular (CV) events. Previously, we have demonstrated that granular measures of lipids (lipoprotein particle number/size) are associated with CAD and CV events and incremental to traditional lipid measures. Hypothesis: Granular measures of lipids are associated with HS detected by cardiac computed tomography (CT) and with HS detected by histopathology. Methods: We included 1524 subjects from the PROMISE trial. HS was defined as CT attenuation of the liver Results: Subjects with HS (n=413) were slightly younger (59±8 vs 61±8 yrs) and more likely men (53 vs 44%) as compared to controls (n=1111). Three lipoprotein factors were associated with HS: LDL/LDL particle size (OR 1.36, 95%CI 1.21-1.53, p Conclusions: We found association of small LDL, large HDL and large TG particles, previously associated with CV event risk, with HS phenotyped by CT and histopathology. These results suggest that use of lipoprotein subclasses may improve CV risk assessment in patients with HS.

Background: The 2013 ACC/AHA Cholesterol Guidelines departed from prior ATPIII guidelines, recommending statin treatment based on patients’ predicted 10-year ASCVD risk and de-emphasizing LDL-C targets. However, the degree to which these new guidelines have been adopted by clinicians in community practice is unknown. Methods: We surveyed 522 clinicians in 133 cardiology, primary care, and endocrinology practices participating in the Patient and Provider Assessment of Lipid Management (PALM) Registry. Clinicians were asked about their likelihood of prescribing statins in 4 hypothetical patient scenarios. Results: Among responders, 79% were physicians (60% cardiologists, 38% primary care or general practice, 2% endocrinology), 18% were advanced practice providers, and 3% trainees. When queried, 73% of providers reported primarily using the 2013 ACC/AHA Guidelines to guide lipid management. However, only half reported “often” or “always” calculating 10-year ASCVD risk to aid lipid management decisions for primary prevention. When presented with a high 10-year ASCVD risk patient (>15%) with a high LDL-C (150 mg/dL), 92% of providers recommended statins. Similarly, 83% of providers would use statins in a diabetic patient with a LDL-C of 140 mg/dL. Yet, only 37% reported they would prescribe a statin to an older adult (age 70) for whom guidelines recommend statin based on high 10-year ASCVD risk alone (10.1%). And up to 40% would prescribe a statin to a younger (age 40) with a low 10-year risk, but a high LDL (165 mg/dL) who would not otherwise meet criteria for statin therapy under the new guidelines. Cardiologists and non-cardiologists were similarly likely prescribe statins in most scenarios with the exception of to the younger patient with elevated LDL-C were cardiologists used statins more commonly (32% vs. 42%. OR 1.5, 95% CI 1.1-2.2, p=0.02). Conclusion: Initial survey results show that while most clinicians claim adoption of the 2013 ACC/AHA Guidelines, reported practices are not always adherent to these guidelines. Providers do not always calculate 10-year ASCVD risk to guide lipid management and many do not prescribe statins to patients eligible based on 10-year ASCVD risk.

A new method is presented that combines dual fluorescence microscopy and single-particle tracking (SPT) to investigate the impact of spatial inhomogeneities in membranes on lateral diffusion within Langmuir monolayers. Incontrast to previous SPT experiments, random walks of individual fluorescent tracer particles and the structure of the membrane are simultaneously imaged. Monolayers of 1,2-dimyristoyl-sn-glycero-2-phosphoethanolamine (DMPE) in the liquid condensed/liquid expanded phase are used to model the inhomogeneous plasma membrane, while the fluorescent particles embedded in the membrane serve as model proteins. The interactions between tracers and the domain boundary and the resulting change in their random walks are directly observed. Since this technique permits systematic SPT studies of diffusion in inhomogeneous monolayers, its extensions to more biologically relevant monolayers are laid out as well.

Background: Anticoagulation rates remain suboptimal for patients with atrial fibrillation (AF). Although these rates could potentially be improved with performance measures, there is no universal algorithm for identifying AF patients at risk for stroke using the electronic medical record. Methods: Patients with AF seen between 6/1/2011-5/31/2012 were identified. CHADS¬2 and CHA2DS2-Vasc scores were calculated with a broader algorithm that uses codes dating back 10 years, and a restrictive algorithm requiring comorbidity diagnoses within the past year. The accuracies of a claims-based AF definition and of each of four stroke risk classification algorithms (broad and restrictive each using CHADS¬2 and CHA2DS2-Vasc scores ≥2) were evaluated using data obtained from manual chart reviews for 300 patients. Electronic medication data were used to evaluate rates of anticoagulation among AF patients identified as at risk for stroke. Results: 6397 patients with prevalent AF were identified. Chart reviews confirmed a diagnosis of AF or atrial flutter in 95.7%. Patients with AF at risk for stroke were most accurately assessed using a restrictive algorithm based on a CHA2DS2-Vasc score ≥2 (PPV 97.5%, NPV 65.1%). The PPV of the broader algorithm based on CHADS2 score was 88.0%; 12% of those identified as high-risk electronically had CHADS2 scores Discussion: Automated methods can be used to identify patients with prevalent AF indicated for anticoagulation, but may suffer from misclassification of up to 12%. Misclassification is minimized by requiring a diagnosis of AF within the prior year and using a CHA2DS2-Vasc based algorithm. Despite differences in accuracy between definitions, system-wide anticoagulation rates assessed using these definitions were similar. The diagnosis codes validated in this study can be applied for internal quality improvement and observational studies, and might be adapted for use in nationwide quality reporting programs.