Cardiovascular Disease Phenotypes Research Articles

High-intensity exercise training using a rotarod instrument (RotaHIIT)significantly improves exercise capacity in mice.

Voluntary or forced exercise training in mice is used to assess functional capacity as well as potential disease-modifying effects of exercise over a range of cardiovascular disease phenotypes. Compared to voluntary wheel running, forced exercise training enables precise control of exercise workload and volume, and results in superior changes in cardiovascular performance. However, the use of a shock grid with treadmill-based training is associated with stress and risk of injury, and declining compliance with longer periods of training time for many mouse strains. With these limitations in mind, we designed a novel, high-intensity interval training modality (HIIT) for mice that is carried out on a rotarod. Abbreviated as RotaHIIT, this protocol establishes interval workload intensities that are not time or resource intensive, maintains excellent training compliance over time, and results in improved exercise capacity independent of sex when measured by treadmill graded exercise testing (GXT) and rotarod specific acceleration and endurance testing. This protocol may therefore be useful and easily implemented for a broad range of research investigations. As RotaHIIT training was not associated cardiac structural or functional changes, or changes in oxidative capacity in cardiac or skeletal muscle tissue, further studies will be needed to define the physiological adaptations and molecular transducers that are driving the training effect of this exercise modality.

Gut Microbiome and Its Role in Valvular Heart Disease: Not a "Gutted" Relationship.

The role of the gut microbiome (GM) and oral microbiome (OM) in cardiovascular disease (CVD) has been increasingly being understood in recent years. It is well known that GM is a risk factor for various CVD phenotypes, including hypertension, dyslipidemia, heart failure and atrial fibrillation. However, its role in valvular heart disease (VHD) is less well understood. Research shows that, direct, microbe-mediated and indirect, metabolite-mediated damage as a result of gut dysbiosis and environmental factors results in a subclinical, chronic, systemic inflammatory state, which promotes inflammatory cell infiltration in heart valves and subsequently, via pro-inflammatory molecules, initiates a cascade of reaction, resulting in valve calcification, fibrosis and dysfunction. This relationship between GM and VHD adds a pathophysiological link to the pathogenesis of VHD, which can be aimed therapeutically, in order to prevent or regress any risk for valvular pathologies. Therapeutic interventions include dietary modifications and lifestyle interventions, in order to influence environmental factors that can promote gut dysbiosis. Furthermore, the combination of probiotics and prebiotics, as well as fecal m transplantation and targeted treatment with inducers or inhibitors of microbial enzymes have showed promising results in animal and/or clinical studies, with the potential to reduce the inflammatory state and restore the normal gut flora in patients. This review, thus, is going to discuss the pathophysiological links behind the relationship of GM, CVD and VHD, as well as explore the recent data regarding the effect of GM-altering treatment in CVD, cardiac function and systemic inflammation.

Abstract 3462: Mendelian randomization analysis of 27 cardiometabolic trait related polygenic scores identifies genetic risk for cardiometabolic and cardiovascular events in a large prospective study of breast cancer survivors

Abstract Background: CVD is the most common cause of non-cancer death in breast cancer patients. Due to cancer treatment-related cardiotoxicities, breast cancer survivors are at increased risk of cardiometabolic disease (CMD) and cardiovascular disease (CVD). In addition to treatment-related factors, behavioral risk factors such as diet, smoking, and obesity are shared between CVD and breast cancer. While clinical factors influencing the risk of CVD in breast cancer patients are well studied, the effects of genetic factors are less known. Methods: To investigate genetic factors contributing to risk of CMD and CVD in women with a history of breast cancer, we performed a Mendelian randomization analysis to explore the relationships between 27 polygenic scores (PGS) for CMD and CVD phenotypes selected from the PGS Catalog and literature and 13 incident CMD and CVD events in a large prospective cohort of 3,699 breast cancer survivors in the Pathways Study. Fine-Gray sub-distribution hazard ratios (HRs) and 95% confidence intervals (CIs) associated with one standard deviation of PGS were derived with adjustment for epidemiologic, clinical, and treatment factors. The time scale was defined as time since date of breast cancer diagnosis to first of incident event, health plan disenrollment, death, or end of study (12/31/2019). The proportional hazards assumption was tested using Schoenfeld residuals, and no violation was found. Results: We identified 19 PGS-CMD/CVD associations that met Bonferroni significance (P<1.17 × 10−4). Five PGS were associated with increased risk of dyslipidemia: apolipoprotein B (HR=1.52, 95% CI,1.38-1.65), LDL cholesterol (1.49, 1.36-1.63), total cholesterol (1.43, 1.31-1.56), triglyceride levels (1.24, 1.14-1.34), and coronary artery disease (1.22, 1.13-1.33). Four PGS were associated with increased risk of hypertension: systolic blood pressure (1.36, 1.25-1.48), diastolic blood pressure (1.21, 1.11-1.32), fasting glucose adjusted for BMI (1.19, 1.09-1.30), and hypertension (1.41, 1.29-1.54). PGS for atrial fibrillation was associated with increased risk of arrhythmia (1.40, 1.25-1.57) and any cardiovascular disease (1.22, 1.12-1.32). PGS for coronary artery disease and myocardial infarction were both associated with increased risk of ischemic heart disease (1.43, 1.21-1.70 and 1.38, 1.17-1.62, respectively). Conclusion: Our study provides strong evidence for the potential use of PGS to predict the risk of CVD and CMD in women with a history of breast cancer. Future studies may explore the use of PGS to identify women with breast cancer at high risk of CVD-related outcomes and strategies to mitigate this risk. Citation Format: Peter N. Fiorica, Haiyang Sheng, Cecile A. Laurent, Janise M. Roh, Valerie S. Lee, Alexa Zimbalist, Isaac J. Ergas, Qianqian Zhu, Richard K. Cheng, Eileen Rillamas-Sun, Carlos Iribarren, Jamal S. Rana, Mai Nguyen-Huynh, Dawn L. Hershman, Lawrence H. Kushi, Christine B. Ambrosone, Marilyn L. Kwan, Heather Greenlee, Song Yao. Mendelian randomization analysis of 27 cardiometabolic trait related polygenic scores identifies genetic risk for cardiometabolic and cardiovascular events in a large prospective study of breast cancer survivors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3462.

Prevalence of Cardiovascular Disease and Rate of Major Adverse Cardiovascular Events in Severe Alpha-1 Antitrypsin Deficiency COPD.

Alpha-1 antitrypsin deficiency is an autosomal co-dominant condition that predisposes individuals to early-onset emphysema. As with COPD, AATD-COPD is associated with pulmonary exacerbations, which impacts on overall mortality and quality of life. Though there is evidence that COPD is associated with a higher prevalence of cardiovascular disease and major adverse cardiovascular events (MACE), it is unclear if this is true for patients with AATD-COPD. Prevalence of cardiovascular disease was determined in two separate severe AATD cohorts: AlphaNet, USA and the Birmingham AATD registry, UK. All patients had preexisting lung disease. Cardiovascular disease was defined as presence of any of the following: heart failure, ischaemic heart disease, atrial fibrillation, stroke, and myocardial infarction. A Cox proportional hazards model was used to assess the impact of prior cardiovascular disease and frequent exacerbator phenotype on risk of future MACE. Out of 3493 patients with severe AATD, 14.7% had prior cardiovascular disease, including stroke (2.3%), myocardial infarction (2.2%), and heart failure (2.5%). Frequent exacerbators were more likely to have preexisting cardiovascular disease compared with those with one or no exacerbations in the preceding year (63% vs 44.8%, p = 0.001). There was increased risk of future MACE in frequent exacerbators (HR 1.85, 95% CI 1.24 to 2.75), former and current smokers (HR 1.80, 95% CI 1.07 to 3.02, p = 0.026, and HR 4.04, 95% CI 1.44 to 11.32, p = 0.008, respectively), and those with prior cardiovascular disease (HR 3.81, 95% CI 2.60 to 5.58, p < 0.001). In severe AATD-COPD, MACE are associated with an increased exacerbation frequency, previous cardiovascular disease, and a history of smoking.

Kiosk 6R-TC-09 - The Associations of Bone Health with Cardiovascular Disease and Imaging Phenotypes in the UK Biobank

Kiosk 6R-TC-09 - The Associations of Bone Health with Cardiovascular Disease and Imaging Phenotypes in the UK Biobank

Rationale and design of the CONFIRM2 (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) study

BackgroundIn the last 15 years, large registries and several randomized clinical trials have demonstrated the diagnostic and prognostic value of coronary computed tomography angiography (CCTA). Advances in CT scanner technology and developments of analytic tools now enable accurate quantification of coronary artery disease (CAD), including total coronary plaque volume and low attenuation plaque volume. The primary aim of CONFIRM2, (Quantitative COroNary CT Angiography Evaluation For Evaluation of Clinical Outcomes: An InteRnational, Multicenter Registry) is to perform comprehensive quantification of CCTA findings, including coronary, non-coronary cardiac, non-cardiac vascular, non-cardiac findings, and relate them to clinical variables and cardiovascular clinical outcomes. DesignCONFIRM2 is a multicenter, international observational cohort study designed to evaluate multidimensional associations between quantitative phenotype of cardiovascular disease and future adverse clinical outcomes in subjects undergoing clinically indicated CCTA. The targeted population is heterogenous and includes patients undergoing CCTA for atherosclerotic evaluation, valvular heart disease, congenital heart disease or pre-procedural evaluation. Automated software will be utilized for quantification of coronary plaque, stenosis, vascular morphology and cardiac structures for rapid and reproducible tissue characterization. Up to 30,000 patients will be included from up to 50 international multi-continental clinical CCTA sites and followed for 3–4 years. SummaryCONFIRM2 is one of the largest CCTA studies to establish the clinical value of a multiparametric approach to quantify the phenotype of cardiovascular disease by CCTA using automated imaging solutions.

The relationship between diabetes, obesity and cardiovascular disease phenotypes: a UK Biobank cohort study

Abstract Background Obesity and diabetes mellitus (DM) frequently co-exist, yet their individual contributions to cardiovascular risk remain debated. Purpose We explored cardiovascular disease biomarkers, events and mortality in a large cohort stratified by body mass index (BMI) and DM. We hypothesised that DM with normal BMI is associated with a cardiovascular phenotype and event rate comparable to obesity without DM. Methods 451,355 UK Biobank participants were stratified by ethnicity-specific BMI categories (normal, overweight, obese) and DM status. We examined cardiovascular biomarkers including: carotid intima-media thickness (CIMT); arterial stiffness; left ventricular ejection fraction (LVEF) and cardiac contractility index (CCI). Poisson regression models estimated adjusted incidence rate ratios (IRR) for myocardial infarction, ischaemic stroke and cardiovascular death, with normal weight non-DM as comparator. Correlation matrices of Poisson model’s coefficients were used to assess correlations between covariates. Results 5% of participants had DM (10% normal weight, 34% overweight and 55% obese; versus 34%, 43% and 23%, respectively, in non-DM). In the non-DM group, overweight/obesity was associated with higher CIMT, arterial stiffness and CCI, and lower LVEF (p&amp;lt;0.05); these relationships were diminished in the DM group. Within BMI classes, DM was associated with adverse cardiovascular phenotype (p&amp;lt;0.05), particularly in the normal weight group. After 5,323,190 person-years follow-up, incident myocardial infarction, ischaemic stroke and cardiovascular mortality all rose across increasing BMI categories in the DM and non-DM groups (p&amp;lt;0.05). However, normal weight DM had higher cardiovascular mortality than obese non-DM (IRR 2.81 [95% confidence interval: 2.24-3.54] vs IRR 1.84 [1.70-1.98]). Pairwise correlation analysis demonstrated the strongest correlates of cardiovascular parameters were markers of adiposity; this was apparent in the DM and non-DM groups, although these remained modest with Pearson’s correlation coefficients of no more than 0.25. Conclusions Obesity and DM are additively associated with adverse cardiovascular biomarkers and mortality risk. Whilst adiposity metrics are more strongly correlated with cardiovascular biomarkers than diabetes-oriented metrics, both correlate weakly, suggesting other factors underpin the high cardiovascular risk of normal-weight diabetes. Ideal target range for metrics of adiposity may therefore be lower than currently proposed in people with DM.Table 1:Adjusted IRR of CV deathFigure 1:KM Curve for CV death

Abstract 12881: Lnc(RNA)-ing COX-2 and Cardioprotection: A PACERR Story

NSAIDs are amongst the most commonly used drugs by adults, but their use is complicated by an increased risk of adverse cardiovascular events that are consequent to suppression of cyclooxygenase-2 (COX-2) dependent prostaglandin (PG) formation, particularly prostacyclin (PGI 2 ). Amongst the mechanisms HDL may help to mediate cardiovascular risk is via its regulated expression of COX-2 and production of PGI 2 by vascular cells. This affords restraint on thrombogenesis, atherogenesis and hypertension. Another might be to accelerate cholesterol efflux by macrophages in the atherosclerotic plaque. Depletion of COX-2 has been reported to reduce efflux coincident with an altered HDL phenotype that fosters atherogenesis. Long non-coding RNAs (lncRNAs) contribute to the regulation of essential cellular processes, such as the progression of cardiovascular disease. Through the investigation of lncRNAs involved in the cellular response to HDL we have uncovered a regulatory role for a lncRNA encoded on the opposite strand of COX-2, called PACERR. Examining the human GTEx database, we found PACERR is most highly expressed in vascular tissues including aorta with several cis -eQTLs modulating aortic PACERR expression. Patients in the Penn Medicine Biobank with these SNPs exhibit an increase in odds ratio towards vascular inflammatory traits including polyarteritis nodosa (PAN). HDL induces the expression of PACERR in vascular cells, signifying its potential role in mitigating risk towards cardiovascular disease phenotypes. Using gain-and-loss of function approaches we have found that PACERR modulates HDL induced COX-2 and prostaglandin formation by smooth muscle and endothelial cells under flow as well as HDL mediated cholesterol efflux by macrophages via the regulation of the cholesterol transporter ABCG1. By modulating the expression of PACERR in vitro and in vivo, we have elucidated a mechanism by which both HDL and COX-2 have a linked cardio-protective effect contributing to our understanding of the heterogeneous effects of current drugs used to raise HDL cholesterol levels and the cardiotoxicity of NSAIDs observed in clinical trials.

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports.

The rapidly increasing and vast quantities of biomedical reports, each containing numerous entities and rich information, represent a rich resource for biomedical text-mining applications. These tools enable investigators to integrate, conceptualize, and translate these discoveries to uncover new insights into disease pathology and therapeutics. In this protocol, we present CaseOLAP LIFT, a new computational pipeline to investigate cellular components and their disease associations by extracting user-selected information from text datasets (e.g., biomedical literature). The software identifies sub-cellular proteins and their functional partners within disease-relevant documents. Additional disease-relevant documents are identified via the software's label imputation method. To contextualize the resulting protein-disease associations and to integrate information from multiple relevant biomedical resources, a knowledge graph is automatically constructed for further analyses. We present one use case with a corpus of ~34 million text documents downloaded online to provide an example of elucidating the role of mitochondrial proteins in distinct cardiovascular disease phenotypes using this method. Furthermore, a deep learning model was applied to the resulting knowledge graph to predict previously unreported relationships between proteins and disease, resulting in 1,583 associations with predicted probabilities >0.90 and with an area under the receiver operating characteristic curve (AUROC) of 0.91 on the test set. This software features a highly customizable and automated workflow, with a broad scope of raw data available for analysis; therefore, using this method, protein-disease associations can be identified with enhanced reliability within a text corpus.

Socioeconomic inequalities in cardiovascular disease: a causal perspective.

Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Cardiovascular disease (CVD) is caused by a multitude of complex and largely heritable conditions. Identifying key genes and understanding their susceptibility to CVD in the human genome can assist in early diagnosis and personalized treatment of the relevant patients. Heart failure (HF) is among those CVD phenotypes that has a high rate of mortality. In this study, we investigated genes primarily associated with HF and other CVDs. Achieving the goals of this study, we built a cohort of thirty-five consented patients, and sequenced their serum-based samples. We have generated and processed whole genome sequence (WGS) data, and performed functional mutation, splice, variant distribution, and divergence analysis to understand the relationships between each mutation type and its impact. Our variant and prevalence analysis found FLNA, CST3, LGALS3, and HBA1 linked to many enrichment pathways. Functional mutation analysis uncovered ACE, MME, LGALS3, NR3C2, PIK3C2A, CALD1, TEK, and TRPV1 to be notable and potentially significant genes. We discovered intron, 5ʹ Flank, 3ʹ UTR, and 3ʹ Flank mutations to be the most common among HF and other CVD genes. Missense mutations were less common among HF and other CVD genes but had more of a functional impact. We reported HBA1, FADD, NPPC, ADRB2, ADBR1, MYH6, and PLN to be consequential based on our divergence analysis.

Relationship Among Diabetes, Obesity, and Cardiovascular Disease Phenotypes: A UK Biobank Cohort Study.

Obesity and diabetes frequently coexist, yet their individual contributions to cardiovascular risk remain debated. We explored cardiovascular disease biomarkers, events, and mortality in the UK Biobank stratified by BMI and diabetes. A total of 451,355 participants were stratified by ethnicity-specific BMI categories (normal, overweight, obese) and diabetes status. We examined cardiovascular biomarkers including carotid intima-media thickness (CIMT), arterial stiffness, left ventricular ejection fraction (LVEF), and cardiac contractility index (CCI). Poisson regression models estimated adjusted incidence rate ratios (IRRs) for myocardial infarction, ischemic stroke, and cardiovascular death, with normal-weight nondiabetes as comparator. Five percent of participants had diabetes (10% normal weight, 34% overweight, and 55% obese vs. 34%, 43%, and 23%, respectively, without diabetes). In the nondiabetes group, overweight/obesity was associated with higher CIMT, arterial stiffness, and CCI and lower LVEF (P < 0.005); these relationships were diminished in the diabetes group. Within BMI classes, diabetes was associated with adverse cardiovascular biomarker phenotype (P < 0.005), particularly in the normal-weight group. After 5,323,190 person-years follow-up, incident myocardial infarction, ischemic stroke, and cardiovascular mortality rose across increasing BMI categories without diabetes (P < 0.005); this was comparable in the diabetes groups (P-interaction > 0.05). Normal-weight diabetes had comparable adjusted cardiovascular mortality to obese nondiabetes (IRR 1.22 [95% CI 0.96-1.56]; P = 0.1). Obesity and diabetes are additively associated with adverse cardiovascular biomarkers and mortality risk. While adiposity metrics are more strongly correlated with cardiovascular biomarkers than diabetes-oriented metrics, both correlate weakly, suggesting that other factors underpin the high cardiovascular risk of normal-weight diabetes.

Effects of first presentations of 12 cardiovascular disease phenotypes on cardiovascular, non-cardiovascular and all-cause mortality in the general population

Abstract Funding Acknowledgements Type of funding sources: None. Background Cardiovascular diseases (CVD) present as diverse phenotypes, which have considerably different effects on subsequent prognosis. However, studies quantifying these differences in prognosis after various first presentations of CVD are so far lacking. Purpose Our main study objective was to investigate the effects of first presentations of 12 distinct CVD phenotypes on the risk of cardiovascular mortality (primary outcome) and non-cardiovascular as well as all-cause-mortality (secondary outcomes) in the general population. Further objectives were to assess whether the effects differ by sex, age and ethnicity and to what extent referral to cardiac rehabilitation within 6 months can mitigate the effects. Methods Based on England-wide linked electronic health records, we set up a cohort study of 1,310,518 people aged 30 years and older who were initially free of CVD. We followed them up from 2010 to 2016 for 12 validated CVD phenotypes (exposures) and cardiovascular as well as non-cardiovascular mortality (outcomes). We estimated hazard rate ratios (HRRs) and 95% confidence intervals (CIs) using Cox’s proportional hazards models with CVD presentations as time-dependent variables. Results During a median follow-up of 4.2 years, 10,906 cardiovascular deaths and 81,516 first presentations of CVD phenotypes occurred. Presentations of all 12 phenotypes increased cardiovascular mortality, with HRRs (95% CIs) ranging from 1.67 (1.47-1.89) for stable angina and 1.68 (1.44-1.95) for transient ischaemic attack to 7.85 (6.62-9.31) for haemorrhagic stroke. Non-cardiovascular and all-cause mortality also increased with all phenotypes, but to a lesser extent. Subgroup analyses indicate CVD phenotypes with markedly heterogeneous impact on prognosis in women and men, middle and older age groups and ethnic groups. Referral to cardiac rehabilitation recorded in 3,018 (3.70%) first CVD presentations attenuated the effects of haemorrhagic stroke, heart failure and myocardial infarction (HRRs (95% CIs): 2.46 (1.55-3.90), 2.22 (1.37-3.60) and 0.89 (0.57 -1.40), respectively) on cardiovascular mortality when compared to no referral (HRRs (95% CIs): 8.18 (6.80-9.83), 6.50 (6.10-6.92) and 4.32 (3.90-4.80), respectively). Conclusions First presentations of 12 CVD phenotypes are associated with heterogeneous but significantly increased risks of cardiovascular mortality. Referral to cardiac rehabilitation is a missed opportunity in high-risk CVD phenotype presentations.

Impact of metabolic factors on risk of cardiovascular disease in nondiabetic metabolic dysfunction-associated fatty liver disease

Changing terminology of non-alcoholic fatty liver disease (NAFLD) to metabolic dysfunction-associated fatty liver disease (MAFLD) is recently proposed by expert panels based on metabolic dysregulations. However, clinical evidences for the risk of cardiovascular disease (CVD) in MAFLD are limited. The aim of this study is evaluating the association of cardiovascular risk in these two terminology and subgroups of MAFLD. A total of 2133 individuals who underwent ultrasound and cardiac computed tomography contemporaneously were included at a single medical checkup center. Ultrasound was used to define fatty liver, and coronary artery calcification (CAC) defined a coronary artery calcium score above 0 was used to estimate the cardiovascular risk. Overall, 911 participants were diagnosed with fatty liver. In the unadjusted analysis, NAFLD (OR = 1.4, 95% confidence interval [CI] = 1.05-1.85, p = 0.019) and MAFLD (OR = 1.55, 95% CI = 1.29-1.86, p = 0.046) were significantly associated with CAC. However, in sex and age-adjusted analyses, only MAFLD was associated with CAC (adjusted OR [aOR] = 1.38, 95% CI = 1.14-1.69, p = 0.001). Of the three subgroups of MAFLD (diabetic, nondiabetic overweight/obese, and nondiabetic normal weight/lean with at least two metabolic abnormalities), only diabetic MAFLD was associated with CAC (aOR = 2.65, 95% CI = 1.98-3.55, p < 0.001). When the minimal number of metabolic risk abnormalities increased to three, nondiabetic normal-weight/lean MAFLD was associated with CAC (aOR = 1.35, 95% CI = 1.02-1.77, p = 0.034). Diabetic MAFLD predicted high-risk CVD phenotypes the best. Metabolic risk abnormalities in nondiabetic MAFLD patients were independently associated with the risk of CVD. The proposed diagnostic criteria for nondiabetic MAFLD need further investigation in terms of CVD risk.

Increased Risk of Cardiovascular Complications in Chronic Kidney Disease: Introduction to a Compendium.

Increased Risk of Cardiovascular Complications in Chronic Kidney Disease: Introduction to a Compendium.

Abstract P248: Plasma Proteins Associated With Depressive Symptoms and Perceived Global Stress Among African American Adults in the Jackson Heart Study

Introduction: Analyzing plasma proteins is a novel approach to uncover molecular mechanisms by which psychosocial stress may lead to chronic illness, including cardiometabolic disease. Proteomic analyses of cardiometabolic disease have been reported; however, proteomic studies of stress and depressive symptoms are limited. Hypothesis: We hypothesized that plasma protein concentrations are both positively and negatively associated with greater depressive symptoms and perceived global stress, respectively, in African American adults from the Jackson Heart Study (JHS). Methods: Participants from exam 1 (2000-2004) with SomaScan 1.3k platform proteomics data were utilized (n=2143, mean age=55.3). Depressive symptoms and global stress scores were measured via the 20-item Centers for Epidemiological Studies (CES-D) Scale and an 8-item global perceived stress scale adapted for the JHS, respectively. Multivariable linear models were used to test the association between depressive symptoms and global stress scores and proteins, controlling for age, sex, and proteomics batch. Bonferroni correction was used to adjust the p-value threshold for multiple testing (3.78e-5, for 1,322 tested proteins). Results: Six (6) proteins were found to be significantly associated with either depressive symptoms or perceived global stress. Angiopoietin-2 (β=0.014, SE=0.003, p =1.33e-5), growth/differentiation factor 15 or MIC-1 (β=0.014, SE=0.003, p=7.08e-8), and kynureninase (β=0.014, SE=0.003, p =1.55e-5) were positively associated with depressive symptoms. Contactin-5 (β=-0.017, SE=0.003, p =1.40e-7) and neural cell adhesion molecule 1 (120 kDa isoform) (β=-0.016, SE=0.003, p =6.74e-7) were negatively associated with depressive symptoms. Leukotriene A-4 hydrolase or LKHA4 (β=0.024, SE=0.005, p =2.72e-6) was positively associated with perceived stress. We note that several of these proteins which are associated with higher levels of stress or depression symptoms have also been associated with cardiovascular disease and related phenotypes; for example, LKHA4 was the lead association with left ventricular mass in previous JHS analyses. Conclusions: JHS proteomic profiles revealed differences in protein concentrations by psychosocial measures. We will next explore the extent to which identified proteins may mediate relationships between stress and depressive symptoms and cardiovascular endpoints. Future investigations may identify potentially targetable proteomic mechanisms by which psychosocial stressors manifest into disease.

Association of Cardiovascular Disease and Physical Activity Phenotypes with Falls among Midlife and Older Adults: 2018 Behavioral Risk Factor Surveillance System

ABSTRACT Background The role of physical activity (PA) in mitigating fall risk among adults with cardiovascular disease (CVD) is unclear. Purpose We examined the associations of CVD–PA phenotypes with falls. Methods Adults ≥ 45 years (n = 295,282; N = 130,103,093) from the 2018 Behavioral Risk Factor Surveillance System who self-reported CVD, leisure-time PA, and falls were examined. The weighted prevalence ratio (PR) of any, recurrent, and injurious falls across CVD–PA phenotypes (no CVD–PA, no CVD–no PA, CVD–PA, CVD–no PA) was estimated. Results The likelihood of any, recurrent, and injurious falls was higher across unhealthier CVD–PA phenotypes in fully adjusted models. In the total sample, no CVD–no PA (PR: 1.30; 95% CI: 1.10, 1.50), CVD–PA (PR: 1.35; 95% CI: 1.10, 1.60), and CVD–no PA (PR: 1.39; 95% CI: 1.11, 1.67) phenotypes were more likely to report injurious falls than no CVD–PA phenotype. Discussion Engaging in leisure-time PA may be an important lifestyle strategy for fall prevention in midlife and older adults who are at risk of CVD. Translations to Health Education Practice Our findings could be useful for health education in providing evidence on future fall prevention programs in adults who are at risk for CVD and falls.

Novel Classification of Thrombotic Disorders Based on Molecular Hemostasis and Thrombogenesis Producing Primary and Secondary Phenotypes of Thrombosis.

Thrombosis, the common and deadliest disorder among human diseases, develops as a result of the intravascular hemostasis following an intravascular injury, which can be caused by a variety of trauma, non-traumatic insults or clinical illnesses. Thrombosis can occur at any location of the vascular system supplied by blood from the heart to large and smallest arterial and venous systems and may affect the function and anatomy of the organ and tissue. It more commonly occurs in the smaller circulatory system of the vascular tree such as arterioles and capillaries, and venules of the organs, especially in the brain, lungs, heart, pancreas, muscle and kidneys, and sinusoids of the liver. Thrombosis has been referred as the disease of "blood clots", which concept is incompletely defined, but represents many different hemostatic diseases from microthrombosis to fibrin clot disease, macrothrombosis, and combined micro-macrothrombosis. Thrombosis is produced following an intravascular injury via one or more combination of four different mechanisms of thrombogenesis: microthrombogenesis, fibrinogenesis, macrothrombogenesis and micro-macrothrombogenesis initiated by normal physiological hemostasis in vivo. The clinical phenotype expression of thrombosis is determined by: (1) depth of the intravascular wall injury, (2) extent of the injury affecting the vascular tree system, (3) physiological character of the involved vascular system, (4) locality of the vascular injury, and (5) underlying non-hemostatic conditions interacting with hemostasis. Recent acquisition of "two-path unifying theory" of hemostasis and "two-activation theory of the endothelium" has opened a new frontier in science of medicine by identifying the pathophysiological mechanism of different thrombotic disorders and also contributing to the better understanding of many poorly defined human diseases, including different phenotypes of stroke and cardiovascular disease, trauma, sepsis and septic shock, multiorgan dysfunction syndrome, and autoimmune disease, and others. Reviewed are the fundamentals in hemostasis, thrombogenesis and thrombosis based on hemostatic theories, and proposed is a novel classification of thrombotic disorders.

Cardiovascular disease-wide association study to investigate shared genetics with peak oxygen uptake

Abstract Introduction Cardiorespiratory fitness, measured as peak oxygen uptake (VO2peak), is a strong predictor of cardiovascular disease (CVD) morbidity and mortality and is estimated to have a large genetic component (∼60%). However, the genetic determinants are yet to be established. Our research group recently identified novel genetic variants associated with directly measured VO2peak. Interestingly, most were specific to females. Looking into genetic pleiotropy between VO2peak and CVD can help elucidate the biological mechanisms explaining the link between this fitness related trait and disease, and potentially identify new therapeutic targets. Purpose The association study aims to investigate if genetic variants found to be associated with VO2peak in women is associated with any cardiovascular disease phenotypes. Methods 34,188 female participants with genotype data from the Trøndelag Health Study (HUNT) were included in this study. ICD-coded hospital data related to cardiovascular disease was collected on each participant and the ICD codes were mapped to Phecodes, resulting in 100 disease-specific phenotypes. 26 single nucleotide polymorphisms (SNPs) previously found to be associated with directly measured VO2peak (p&amp;lt;5e-6) were included in the analyses, all common variants (minor allele frequency ≥1%). Each of the 26 genetic variants were tested for association with the 100 phenotypes using a logistic mixed model as implemented in SAIGE. The analysis was adjusted for birthyear and ten principal components of ancestry. The Benjamini-Hochberg false discovery rate (FDR) procedure controlling the FDR at 0.05 was used to correct for the number of tested SNPs and phenotypes. Results After testing each of the 26 SNPs for association with 100 cardiovascular disease phenotypes, 133 SNP-phenotype associations were nominally significant (p&amp;lt;0.05). The association between rs17066736 and myocarditis had the lowest p-value (1.7e-4). Among the other tested SNP-phenotype pairs were phenotypes related to ischemic heart disease, cardiac conduction disorders, heart failure, cerebrovascular disease, and diseases of arteries and veins. However, when adjusting for multiple testing, none reached overall statistical significance. Conclusions The findings showed no statistically significant associations between genetic variants associated with VO2peak and cardiovascular disease phenotypes in women. The role of inborn VO2peak in prediction of CVD (in women) needs further assessment. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): NTNU biotechnology

Abstract P1118: Genetic Validation Of Cardiac Cytoskeleton And Extracellular Matrix Targets For Drug Discovery

Currently, cardiovascular disease (CVD) drug discovery has focused primarily on addressing the inflammation and immunopathology aspects inherent to various CVD phenotypes such as cardiac fibrosis and coronary artery disease. However, recent findings suggest new biological pathways for cytoskeletal and extracellular matrix (ECM) regulation across diverse CVDs, such as the roles of matricellular proteins (e.g. tenascin-C) in regulating the cellular microenvironment. The success of anti-inflammatory drugs like colchicine, which targets microtubule polymerization, further suggests that the cardiac cytoskeleton and ECM provide prospective therapeutic opportunities. In this Abstract, we will present genetic validation evidence supporting the efficacy of pharmaceutical modulation of the cytoskeleton and the associated ECM that supports its cellular architecture to find new computationally-derived therapeutics in the treatment of CVD using integrated in-silico, in-vitro, and in-vivo methods. Our focus will be on the dynamic role that the cytoskeleton and ECM play in CVD pathophysiology, highlighting how novel target discovery in cytoskeletal and ECM-related genes enables new therapeutics development to alter the regulation of cellular architecture in plaque formation and rupture, cardiac contractility, and other molecular mechanisms.