Evaluation of Plasma Biomarkers for Causal Association With Peripheral Artery Disease.

BACKGROUND: Hundreds of biomarkers for peripheral artery disease (PAD) have been reported in the literature; however, the observational nature of these studies limits causal inference due to the potential of reverse causality and residual confounding. We sought to evaluate the potential causal impact of putative PAD biomarkers identified in human observational studies through genetic causal inference methods. METHODS: Putative circulating PAD biomarkers were identified from human observational studies through a comprehensive literature search based on terms related to PAD using PubMed, Cochrane, and Embase. Genetic instruments were generated from publicly available genome-wide association studies of circulating biomarkers. Two-sample Mendelian randomization was used to test the association of genetically determined biomarker levels with PAD using summary statistics from a genome-wide association study of 31 307 individuals with and 211 753 individuals without PAD in the Veterans Affairs Million Veteran Program and replicated in data from FinnGen comprised of 11 924 individuals with and 288 638 individuals without PAD. RESULTS: We identified 204 unique circulating biomarkers for PAD from the observational literature, of which 173 were genetically instrumented using genome-wide association study results. After accounting for multiple testing (false discovery rate, <0.05), 10 of 173 (5.8%) biomarkers had significant associations with PAD. These 10 biomarkers represented categories including plasma lipoprotein regulation, lipid homeostasis, and protein-lipid complex remodeling. Observational literature highlighted different pathways including inflammatory response, negative regulation of multicellular organismal processes, and regulation of response to external stimuli. CONCLUSIONS: Integrating human observational studies and genetic causal inference highlights several key pathways in PAD pathophysiology. This work demonstrates that a substantial portion of biomarkers identified in observational studies are not well supported by human genetic evidence and emphasizes the importance of triangulating evidence to understand PAD pathophysiology. Although the identified biomarkers offer insights into atherosclerotic development in the lower limb, their specificity to PAD compared with more widespread atherosclerosis requires further study.

Major Depressive Disorder Impacts Peripheral Artery Disease Risk Through Intermediary Risk Factors.

BACKGROUND: Major depressive disorder (MDD) has been identified as a causal risk factor for multiple forms of cardiovascular disease. Although observational evidence has linked MDD to peripheral artery disease (PAD), causal evidence of this relationship is lacking. METHODS AND RESULTS: Inverse variance weighted 2-sample Mendelian randomization was used to test the association the between genetic liability for MDD and genetic liability for PAD. Genetic liability for MDD was associated with increased genetic liability for PAD (odds ratio [OR], 1.17 [95% CI, 1.06-1.29]; P=2.6×10-3). Genetic liability for MDD was also associated with increased genetically determined lifetime smoking (ß=0.11 [95% CI, 0.078-0.14]; P=1.2×10-12), decreased alcohol intake (ß=-0.078 [95% CI, -0.15 to 0]; P=0.043), and increased body mass index (ß=0.10 [95% CI, 0.02-0.19]; P=1.8×10-2), which in turn were associated with genetic liability for PAD (smoking: OR, 2.81 [95% CI, 2.28-3.47], P=9.8×10-22; alcohol: OR, 0.77 [95% CI, 0.66-0.88]; P=1.8×10-4; body mass index: OR, 1.61 [95% CI, 1.52-1.7]; P=1.3×10-57). Controlling for lifetime smoking index, alcohol intake, and body mass index with multivariable Mendelian randomization completely attenuated the association between genetic liability for MDD with genetic liability for PAD. CONCLUSIONS: This work provides evidence for a possible causal association between MDD and PAD that is dependent on intermediate risk factors, adding to the growing body of evidence suggesting that effective management and treatment of cardiovascular diseases may require a composite of physical and mental health interventions.

Gamification-augmented home-based exercise for peripheral artery disease: Rationale and design of the GAMEPAD Study.

BACKGROUND: Supervised exercise therapy improves walking performance, functional capacity, and quality of life in patients with peripheral artery disease (PAD). However, few patients with PAD are enrolled in supervised exercise programs, and there are a number of logistical and financial barriers to their participation. A home-based walking intervention is likely to be more accessible to patients with PAD, but no fully home-based walking program has demonstrated efficacy. Concepts from behavioral economics have been used to design scalable interventions that increase daily physical activity in patients with atherosclerotic vascular disease, but whether a similar program would be effective in patients with PAD is uncertain. STUDY DESIGN AND OBJECTIVES: GAMEPAD (NCT04536012) is a pragmatic, virtual, randomized controlled trial designed to evaluate the effectiveness of a gamification strategy informed by concepts from behavioral economics to increase daily physical activity in patients with PAD who are seen in cardiology and vascular surgery clinics affiliated with the University of Pennsylvania Health System. Patients are contacted by email or text message, and complete enrollment and informed consent on the Penn Way to Health online platform. A GAMEPAD substudy will evaluate the effectiveness of opt-in versus opt-out framing when approaching patients for study participation. Patients are then provided with a wearable fitness tracker, establish a baseline daily step count, set a goal to increase daily step count by 33%-50%, and are randomized 1:1 to the gamification or control arms. Interventions continue for 16 weeks, including a 4-week period during which goal step count is gradually increased in the gamification arm, with follow-up for an additional 8 weeks to evaluate the durability of behavior change. The trial has met its enrollment goal of 102 participants, with a primary endpoint of change from baseline in daily steps over the 16-week intervention period. Key secondary endpoints include change from baseline in daily steps over the 8-week postintervention follow-up period and changes in patient-reported measures of PAD symptoms and quality of life over the intervention and follow-up periods. CONCLUSIONS: GAMEPAD is a virtual, pragmatic randomized clinical trial of a novel, fully home-based walking intervention informed by concepts from behavioral economics to increase physical activity and PAD-specific quality of life in patients with PAD. Its results will have important implications for the application of behavioral economic concepts to scalable home-based strategies to promote physical activity in patients with PAD and other disease processes where physical activity is limited by exertional symptoms. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov; NCT04536012.

Proteomic Associations of Adverse Outcomes in Human Heart Failure.

BACKGROUND: Identifying novel molecular drivers of disease progression in heart failure (HF) is a high-priority goal that may provide new therapeutic targets to improve patient outcomes. The authors investigated the relationship between plasma proteins and adverse outcomes in HF and their putative causal role using Mendelian randomization. METHODS AND RESULTS: The authors measured 4776 plasma proteins among 1964 participants with HF with a reduced left ventricular ejection fraction enrolled in PHFS (Penn Heart Failure Study). Assessed were the observational relationship between plasma proteins and (1) all-cause death or (2) death or HF-related hospital admission (DHFA). The authors replicated nominally significant associations in the Washington University HF registry (N=1080). Proteins significantly associated with outcomes were the subject of 2-sample Mendelian randomization and colocalization analyses. After correction for multiple testing, 243 and 126 proteins were found to be significantly associated with death and DHFA, respectively. These included small ubiquitin-like modifier 2 (standardized hazard ratio [sHR], 1.56; P<0.0001), growth differentiation factor-15 (sHR, 1.68; P<0.0001) for death, A disintegrin and metalloproteinase with thrombospondin motifs-like protein (sHR, 1.40; P<0.0001), and pulmonary-associated surfactant protein C (sHR, 1.24; P<0.0001) for DHFA. In pathway analyses, top canonical pathways associated with death and DHFA included fibrotic, inflammatory, and coagulation pathways. Genomic analyses provided evidence of nominally significant associations between levels of 6 genetically predicted proteins with DHFA and 11 genetically predicted proteins with death. CONCLUSIONS: This study implicates multiple novel proteins in HF and provides preliminary evidence of associations between genetically predicted plasma levels of 17 candidate proteins and the risk for adverse outcomes in human HF.

Titin-Truncating variants Predispose to Dilated Cardiomyopathy in Diverse Populations.

Importance: The effect of high percentage spliced in (hiPSI) TTN truncating variants (TTNtvs) on risk of dilated cardiomyopathy (DCM) has historically been studied among population subgroups defined by genetic similarity to European reference populations. This has raised questions about the effect of TTNtvs in diverse populations, especially among individuals genetically similar to African reference populations. Objective: To determine the effect of TTNtvs on risk of DCM in diverse population as measured by genetic distance (GD) in principal component (PC) space. Design: Cohort study. Setting: Penn Medicine Biobank (PMBB) is a large, diverse biobank. Participants: Participants were recruited from across the Penn Medicine healthcare system and volunteered to have their electronic health records linked to biospecimen data including DNA which has undergone whole exome sequencing. Main Outcomes and Measures: Risk of DCM among individuals carrying a hiPSI TTNtv. Results: Carrying a hiPSI TTNtv was associated with DCM among PMBB participants across a range of GD deciles from the 1000G European centroid; the effect estimates ranged from odds ratio (OR) = 3.29 (95% confidence interval [CI] 1.26 to 8.56) to OR = 9.39 (95% CI 3.82 to 23.13). When individuals were assigned to population subgroups based on genetic similarity to the 1000G reference populations, hiPSI TTNtvs conferred significant risk of DCM among those genetically similar to the 1000G European reference population (OR = 7.55, 95% CI 4.99 to 11.42, P<0.001) and individuals genetically similar to the 1000G African reference population (OR 3.50, 95% CI 1.48 to 8.24, P=0.004). Conclusions and Relevance: TTNtvs are associated with increased risk of DCM among a diverse cohort. There is no significant difference in effect of TTNtvs on DCM risk across deciles of GD from the 1000G European centroid, suggesting genetic background should not be considered when screening individuals for titin-related DCM.

Mendelian Randomization as a Tool for Cardiovascular Research: A Review.

Importance: Mendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease. Observations: MR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed. Conclusions and Relevance: This review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

Genome-wide association meta-analysis identifies risk loci for abdominal aortic aneurysm and highlights PCSK9 as a therapeutic target.

Abdominal aortic aneurysm (AAA) is a common disease with substantial heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 141 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis explained AAA risk beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in AAA pathogenesis. These genes also indicate overlap between the development of AAA and other monogenic aortopathies, particularly via transforming growth factor ß signaling. Motivated by the strong evidence for the role of lipid metabolism in AAA, we used Mendelian randomization to establish the central role of nonhigh-density lipoprotein cholesterol in AAA and identified the opportunity for repurposing of proprotein convertase, subtilisin/kexin-type 9 (PCSK9) inhibitors. This was supported by a study demonstrating that PCSK9 loss of function prevented the development of AAA in a preclinical mouse model.

Relationships between body fat distribution and metabolic syndrome traits and outcomes: A mendelian randomization study.

BACKGROUND: Obesity is a complex, multifactorial disease associated with substantial morbidity and mortality worldwide. Although it is frequently assessed using BMI, many epidemiological studies have shown links between body fat distribution and obesity-related outcomes. This study examined the relationships between body fat distribution and metabolic syndrome traits using Mendelian Randomization (MR). METHODS/FINDINGS: Genetic variants associated with visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and gluteofemoral adipose tissue (GFAT), as well as their relative ratios, were identified from a genome wide association study (GWAS) performed with the United Kingdom BioBank. GWAS summary statistics for traits and outcomes related to metabolic syndrome were obtained from the IEU Open GWAS Project. Two-sample MR and BMI-controlled multivariable MR (MVMR) were performed to examine relationships between each body fat measure and ratio with the outcomes. Increases in absolute GFAT were associated with a protective cardiometabolic profile, including lower low density lipoprotein cholesterol (ß: -0.19, [95% CI: -0.28, -0.10], p < 0.001), higher high density lipoprotein cholesterol (ß: 0.23, [95% CI: 0.03, 0.43], p = 0.025), lower triglycerides (ß: -0.28, [95% CI: -0.45, -0.10], p = 0.0021), and decreased systolic (ß: -1.65, [95% CI: -2.69, -0.61], p = 0.0019) and diastolic blood pressures (ß: -0.95, [95% CI: -1.65, -0.25], p = 0.0075). These relationships were largely maintained in BMI-controlled MVMR analyses. Decreases in relative GFAT were linked with a worse cardiometabolic profile, with higher levels of detrimental lipids and increases in systolic and diastolic blood pressures. CONCLUSION: A MR analysis of ASAT, GFAT, and VAT depots and their relative ratios with metabolic syndrome related traits and outcomes revealed that increased absolute and relative GFAT were associated with a favorable cardiometabolic profile independently of BMI. These associations highlight the importance of body fat distribution in obesity and more precise means to categorize obesity beyond BMI.

Endothelial lipid droplets suppress eNOS to link high fat consumption to blood pressure elevation.

Metabolic syndrome, today affecting more than 20% of the US population, is a group of 5 conditions that often coexist and that strongly predispose to cardiovascular disease. How these conditions are linked mechanistically remains unclear, especially two of these: obesity and elevated blood pressure. Here, we show that high fat consumption in mice leads to the accumulation of lipid droplets in endothelial cells throughout the organism and that lipid droplet accumulation in endothelium suppresses endothelial nitric oxide synthase (eNOS), reduces NO production, elevates blood pressure, and accelerates atherosclerosis. Mechanistically, the accumulation of lipid droplets destabilizes eNOS mRNA and activates an endothelial inflammatory signaling cascade that suppresses eNOS and NO production. Pharmacological prevention of lipid droplet formation reverses the suppression of NO production in cell culture and in vivo and blunts blood pressure elevation in response to a high-fat diet. These results highlight lipid droplets as a critical and unappreciated component of endothelial cell biology, explain how lipids increase blood pressure acutely, and provide a mechanistic account for the epidemiological link between obesity and elevated blood pressure.

Using a polygenic score to account for genomic risk factors in a model to detect individuals with dilated ascending thoracic aortas.

Background: Ascending thoracic aortic dilation is a complex trait that involves modifiable and non-modifiable risk factors and can lead to thoracic aortic aneurysm and dissection. Clinical risk factors have been shown to predict ascending thoracic aortic diameter. Polygenic scores (PGS) are increasingly used to assess clinical risk for multifactorial diseases. The degree to which a PGS can improve aortic diameter prediction is not known. In this study we tested the extent to which the addition of a PGS to clinical prediction algorithms improves the prediction of aortic diameter. Methods: The patient cohort comprised 6,790 Penn Medicine Biobank (PMBB) participants with available echocardiography and clinical data linked to genome-wide genotype data. Linear regression models were used to integrate PGS weights derived from a large genome wide association study of thoracic aortic diameter in the UK biobank and were compared to the performance of the standard and a reweighted variation of the recently published AORTA Score. Results: Cohort participants were 56% male, had a median age of 61 years (IQR 52-70) with a mean ascending aortic diameter of 3.4 cm (SD 0.5). Compared to the AORTA Score which explained 28.4% (95% CI 28.1% to 29.2%) of the variance in aortic diameter, AORTA Score + PGS explained 28.8%, (95% CI 28.1% to 29.6%), the reweighted AORTA score explained 30.4% (95% CI 29.6% to 31.2%), and the reweighted AORTA Score + PGS explained 31.0% (95% CI 30.2% to 31.8%). The addition of a PGS to either the AORTA Score or the reweighted AORTA Score improved model sensitivity for the identifying individuals with a thoracic aortic diameter ≥ 4 cm. The respective areas under the receiver operator characteristic curve for the AORTA Score + PGS (0.771, 95% CI 0.756 to 0.787) and reweighted AORTA Score + PGS (0.785, 95% CI 0.770 to 0.800) were greater than the standard AORTA Score (0.767, 95% CI 0.751 to 0.783) and reweighted AORTA Score (0.780 95% CI 0.765 to 0.795). Conclusions: We demonstrated that inclusion of a PGS to the AORTA Score results in a small but clinically meaningful performance enhancement. Further investigation is necessary to determine if combining genetic and clinical risk prediction improves outcomes for thoracic aortic disease.

Deciphering the genetic architecture of atrial fibrillation offers insights into disease prediction, pathophysiology and downstream sequelae.

Aims: The study aimed to discover novel genetic loci for atrial fibrillation (AF), explore the shared genetic etiologies between AF and other cardiovascular and cardiometabolic traits, and uncover AF pathogenesis using Mendelian randomization analysis. Methods and results: We conducted a genome-wide association study meta-analysis including 109,787 AF cases and 1,165,920 controls of European ancestry and identified 215 loci, among which 91 were novel. We performed Genomic Structural Equation Modeling analysis between AF and four cardiovascular comorbidities (coronary artery disease, ischemic stroke, heart failure, and vneous thromboembolism) and found 189 loci shared across these diseases as well as a universal genetic locus shared by atherosclerotic outcomes (i.e., rs1537373 near CDKN2B). Three genetic loci (rs10740129 near JMJD1C, rs2370982 near NRXN3, and rs9931494 near FTO) were associated with AF and cardiometabolic traits. A polygenic risk score derived from this genome-wide meta-analysis was associated with AF risk (odds ratio 2.36, 95% confidence interval 2.31-2.41 per standard deviation increase) in the UK biobank. This score, combined with age, sex, and basic clinical features, predicted AF risk (AUC 0.784, 95% CI 0.781-0.787) in Europeans. Phenome-wide association analysis of the polygenic risk score identified many AF-related comorbidities of the circulatory, endocrine, and respiratory systems. Phenome-wide and multi-omic Mendelian randomization analyses identified associations of blood lipids and pressure, diabetes, insomnia, obesity, short sleep, and smoking, 27 blood proteins, one gut microbe (genus.Catenibacterium), and 11 blood metabolites with risk to AF. Conclusions: This genome-wide association study and trans-omic Mendelian randomization analysis provides insights into disease risk prediction, pathophysiology and downstream sequelae.

Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum.

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

Multi-response Mendelian randomization: Identification of shared and distinct exposures for multimorbidity and multiple related disease outcomes.

The existing framework of Mendelian randomization (MR) infers the causal effect of one or multiple exposures on one single outcome. It is not designed to jointly model multiple outcomes, as would be necessary to detect causes of more than one outcome and would be relevant to model multimorbidity or other related disease outcomes. Here, we introduce multi-response Mendelian randomization (MR2), an MR method specifically designed for multiple outcomes to identify exposures that cause more than one outcome or, conversely, exposures that exert their effect on distinct responses. MR2 uses a sparse Bayesian Gaussian copula regression framework to detect causal effects while estimating the residual correlation between summary-level outcomes, i.e., the correlation that cannot be explained by the exposures, and vice versa. We show both theoretically and in a comprehensive simulation study how unmeasured shared pleiotropy induces residual correlation between outcomes irrespective of sample overlap. We also reveal how non-genetic factors that affect more than one outcome contribute to their correlation. We demonstrate that by accounting for residual correlation, MR2 has higher power to detect shared exposures causing more than one outcome. It also provides more accurate causal effect estimates than existing methods that ignore the dependence between related responses. Finally, we illustrate how MR2 detects shared and distinct causal exposures for five cardiovascular diseases in two applications considering cardiometabolic and lipidomic exposures and uncovers residual correlation between summary-level outcomes reflecting known relationships between cardiovascular diseases.

Genome-wide association study of thoracic aortic aneurysm and dissection in the Million Veteran Program.

The current understanding of the genetic determinants of thoracic aortic aneurysms and dissections (TAAD) has largely been informed through studies of rare, Mendelian forms of disease. Here, we conducted a genome-wide association study (GWAS) of TAAD, testing ~25 million DNA sequence variants in 8,626 participants with and 453,043 participants without TAAD in the Million Veteran Program, with replication in an independent sample of 4,459 individuals with and 512,463 without TAAD from six cohorts. We identified 21 TAAD risk loci, 17 of which have not been previously reported. We leverage multiple downstream analytic methods to identify causal TAAD risk genes and cell types and provide human genetic evidence that TAAD is a non-atherosclerotic aortic disorder distinct from other forms of vascular disease. Our results demonstrate that the genetic architecture of TAAD mirrors that of other complex traits and that it is not solely inherited through protein-altering variants of large effect size.

Evaluation of the Performance of the RECODe Equation with the Addition of Polygenic Risk Scores for Adverse Cardiovascular Outcomes in Individuals with Type II Diabetes.

Aims/Hypothesis: Individuals with T2D are at an increased risk of developing cardiovascular complications; early identification of individuals can lead to an alteration of the natural history of the disease. Current approaches to risk prediction tailored to individuals with T2D are exemplified by the RECODe algorithms which predict CVD outcomes among individuals with T2D. Recent efforts to improve CVD risk prediction among the general population have included the incorporation of polygenic risk scores (PRS). This paper aims to investigate the utility of the addition of a coronary artery disease (CAD), stroke and heart failure risk score to the current RECODe model for disease stratification. Methods: We derived PRS using summary statistics for ischemic stroke (IS) from the coronary artery disease (CAD) and heart failure (HF) and tested prediction accuracy in the Penn Medicine Biobank (PMBB). A Cox proportional hazards model was used for time-to-event analyses within our cohort, and we compared model discrimination for the RECODe model with and without a PRS using AUC. Results: The RECODe model alone demonstrated an AUC [95% CI] of 0.67 [0.62-0.72] for ASCVD; the addition of the three PRS to the model demonstrated an AUC [95% CI] of 0.66 [0.63-0.70]. A z-test to compare the AUCs of the two models did not demonstrate a detectable difference between the two models (p=0.97). Conclusions/Interpretation: In the present study, we demonstrate that although PRS associate with CVD outcomes independent of traditional risk factors among individuals with T2D, the addition of PRS to contemporary clinical risk models does not specifically improve the predictive performance as compared to the baseline model.

Comparison of the structure-function properties of wild-type human apoA-V and a C-terminal truncation associated with elevated plasma triglycerides.

Background: Plasma triglycerides (TGs) are causally associated with coronary artery disease and acute pancreatitis. Apolipoprotein A-V (apoA-V, gene APOA5) is a liver-secreted protein that is carried on triglyceride-rich lipoproteins and promotes the enzymatic activity of lipoprotein lipase (LPL), thereby reducing TG levels. Little is known about apoA-V structure-function; naturally occurring human APOA5 variants can provide novel insights. Methods: We used hydrogen-deuterium exchange mass spectrometry to determine the secondary structure of human apoA-V in lipid-free and lipid-associated conditions and identified a C-terminal hydrophobic face. Then, we used genomic data in the Penn Medicine Biobank to identify a rare variant, Q252X, predicted to specifically eliminate this region. We interrogated the function of apoA-V Q252X using recombinant protein in vitro and in vivo in apoa5 knockout mice. Results: Human apoA-V Q252X carriers exhibited elevated plasma TG levels consistent with loss of function. Apoa5 knockout mice injected with AAV vectors expressing wildtype and variant APOA5-AAV recapitulated this phenotype. Part of the loss of function is due to reduced mRNA expression. Functionally, recombinant apoA-V Q252X was more readily soluble in aqueous solutions and more exchangeable with lipoproteins than WT apoA-V. Despite lacking the C-terminal hydrophobic region (a putative lipid binding domain) this protein also decreased plasma TG in vivo. Conclusions: Deletion of apoA-V's C-terminus leads to reduced apoA-V bioavailability in vivo and higher TG levels. However, the C-terminus is not required for lipoprotein binding or enhancement of intravascular lipolytic activity. WT apoA-V is highly prone to aggregation, and this property is markedly reduced in recombinant apoA-V lacking the C-terminus.

Sleep duration, daytime napping, and risk of peripheral artery disease: multinational cohort and Mendelian randomization studies.

Aims: Sleep duration has been associated with cardiovascular disease, however the effect of sleep on peripheral artery disease (PAD) specifically remains unestablished. We conducted observational and Mendelian randomization (MR) analyses to assess the associations of sleep duration and daytime napping with PAD risk. Methods and results: Sleep traits were assessed for associations with incident PAD using cohort analysis among 53 416 Swedish adults. Replicated was sought in a case-control study of 28 123 PAD cases and 128 459 controls from the veterans affairs Million Veteran Program (MVP) and a cohort study of 452 028 individuals from the UK Biobank study (UKB). Two-sample Mendelian randomization (MR) was used for casual inference-based analyses of sleep-related traits and PAD (31 307 PAD cases 211 753 controls). Observational analyses demonstrated a U-shaped association between sleep duration and PAD risk. In Swedish adults, incident PAD risk was higher in those with short sleep [<5 h; hazard ratio (HR) 1.74; 95% confidence interval (CI) 1.31-2.31] or long sleep (≥8 h; HR 1.24; 95% CI 1.08-1.43), compared to individuals with a sleep duration of 7 to <8 h/night. This finding was supported by the analyses in MVP and UKB. Observational analysis also revealed positive associations between daytime napping (HR 1.32, 95% CI 1.18-1.49) with PAD. MR analysis supported an inverse association between sleep duration [odds ratio (OR) per hour increase: 0.79, 95% CI, 0.55, 0.89] and PAD and an association between short sleep and increased PAD (OR 1.20, 95% CI, 1.04-1.38). Conclusion: Short sleep duration was associated with an increased risk of PAD.

Genetics of atrial fibrillation.

PURPOSE OF REVIEW: Atrial fibrillation is the most common cardiac arrhythmia worldwide. There is considerable interest in better understanding the molecular genetics and biology of atrial fibrillation to inform the development of new therapies and improve clinical management. This review summarizes recent advances in our understanding of the genetic basis of atrial fibrillation and new efforts to utilize genetics to inform clinical management. RECENT FINDINGS: Genome-wide association studies in diverse populations have increased the number of genetic loci associated with atrial fibrillation and its specific subtypes. Large-scale biobanks with deep phenotyping have provided invaluable data to study the impact of both common and rare variants on atrial fibrillation, susceptibility, and prognosis. Polygenic risk scores help improve individual atrial fibrillation risk stratification and prognostication. SUMMARY: Our understanding of atrial fibrillation genetics is rapidly improving with larger and more diverse genome-wide association studies. Translating genetic discoveries into molecular pathways and new therapeutic targets remains a bottleneck in the development of new therapies for atrial fibrillation. Genetic risk scores have shown early promise in improving atrial fibrillation risk stratification; however, their broader utility for the general population remains unclear.