Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program

Polygenic risk score informed clinical model for improving abdominal aortic aneurysm screening

INTRODUCTION

Abdominal aortic aneurysm (AAA) is a complex disease with environmental and genetic risk factors. Polygenic risk scores (PRS) based on disease-specific risk-associated single nucleotide variants (SNVs) have demonstrated effectiveness in stratifying individual-level disease risk for cardiovascular diseases. This prospective cohort study assessed associations of PRS of AAA (PRSAAA) with risk of incident AAA, analyzed the effectiveness of a combined clinical-genetic risk model, and explored the clinical utility of the model in identifying high-risk individuals for AAA screening.

METHODS

PRSAAA was calculated using 911,440 SNVs and PRSCAD was calculated using 2,324,683 SNVs derived from mixed ancestry genome wide association studies. The UK Biobank was used as the study cohort. All individuals with complete genetic data available and no diagnosis of AAA at time of recruitment were included in the analysis and followed prospectively to assess for incident AAA. A PRS informed clinical model, Prob-AAA, was developed using clinically significant variables and PRSAAA.

RESULTS

481,105 individuals were included in the analysis with 2,668 incident AAA cases. Incident AAA increased from 0.30% to 0.93% between the lowest and highest decile of PRSAAA; similarly, severe AAA, requiring surgery and/or presenting with rupture, increased from 23% to 39% of incident AAA cases across deciles. PRSAAA was a predictor of incident AAA diagnosis (HR 2.06 [1.70 - 2.48]) independent of other clinical risk factors including male sex, older age, and smoking history. Prob-AAA was an independent predictor of incident AAA (HR 1.92 [1.69 - 2.20]), and identified 9.6% of cases of incident AAA compared to only 4.2% by PRSAAA. Current screening guidelines captured 5.7% of the overall cohort, with an incident AAA rate of approximately 3.2%. Amongst males not included by current guidelines, Prob-AAA identified an additional cohort, approximately 2% of the overall cohort, with a similar rate of incident AAA.

CONCLUSIONS

Prob-AAA, a PRS informed clinical model for AAA, improved upon the predictive power of current, clinical risk factor informed, screening guidelines for AAA.

Abdominal aortic aneurysm and cardiometabolic traits share strong genetic susceptibility to lipid metabolism and inflammation

Abdominal aortic aneurysm has a high heritability and often co-occurs with other cardiometabolic disorders, suggesting shared genetic susceptibility. We investigate this commonality leveraging recent GWAS studies of abdominal aortic aneurysm and 32 cardiometabolic traits. We find significant genetic correlations between abdominal aortic aneurysm and 21 of the cardiometabolic traits investigated, including causal relationships with coronary artery disease, hypertension, lipid traits, and blood pressure. For each trait pair, we identify shared causal variants, genes, and pathways, revealing that cholesterol metabolism and inflammation are shared most prominently. Additionally, we show the tissue and cell type specificity in the shared signals, with strong enrichment across traits in the liver, arteries, adipose tissues, macrophages, adipocytes, and fibroblasts. Finally, we leverage drug-gene databases to identify several lipid-lowering drugs and antioxidants with high potential to treat abdominal aortic aneurysm with comorbidities. Our study provides insight into the shared genetic mechanism between abdominal aortic aneurysm and cardiometabolic traits, and identifies potential targets for pharmacological intervention.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by cardiovascular, anthropometric, lung function, and lifestyle-related risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Therapeutic potential of natural products and underlying targets for the treatment of aortic aneurysm

Aortic aneurysm is a vascular disease characterized by irreversible vasodilatation that can lead to dissection and rupture of the aortic aneurysm, a life-threatening condition. Thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) are two main types. The typical treatments for aortic aneurysms are open surgery and endovascular aortic repair, which are only indicated for more severe patients. Most patients with aneurysms have an insidious onset and slow progression, and there are no effective drugs to treat this stage. The inability of current animal models to perfectly simulate all the pathophysiological states of human aneurysms may be the key to this issue. Therefore, elucidating the molecular mechanisms of this disease, finding new therapeutic targets, and developing effective drugs to inhibit the development of aneurysms are the main issues of current research. Natural products have been applied for thousands of years to treat cardiovascular disease (CVD) in China and other Asian countries. In recent years, natural products have combined multi-omics, computational biology, and integrated pharmacology to accurately analyze drug components and targets. Therefore, the multi-component and multi-target complexity of natural products have made them a potentially ideal treatment for multifactorial diseases such as aortic aneurysms. Natural products have regained popularity worldwide. This review provides an overview of the known natural products for the treatment of TAA and AAA and searches for potential cardiovascular-targeted natural products that may treat TAA and AAA based on various cellular molecular mechanisms associated with aneurysm development.

Cancer Incidence After Diagnosis of Abdominal Aortic Aneurysm-Brief Report

BACKGROUND

Epidemiological and mechanistic data support a potential causal link between cardiovascular disease (CVD) and cancer. Abdominal aortic aneurysms (AAAs) represent a common form of CVD with at least partially distinct genetic and biologic pathogenesis from other forms of CVD. The risk of cancer and how this risk differs compared with other forms of CVD, is unknown among AAA patients. We conducted a retrospective cohort study using the IBM MarketScan Research Database to test whether individuals with AAA have a higher cancer risk independent of traditional shared risk factors.

METHODS

All individuals ≥18 years of age with ≥36 months of continuous coverage between 2008 and 2020 were enrolled. Those with potential Mendelian etiologies of AAA, aortic aneurysm with nonspecific anatomic location, or a cancer diagnosis before the start of follow-up were excluded. A subgroup analysis was performed of individuals having the Health Risk Assessment records including tobacco use and body mass index. The following groups of individuals were compared: (1) with AAA, (2) with non-AAA CVD, and (3) without any CVD.

RESULTS

The propensity score-matched cohort included 58 993 individuals with AAA, 117 986 with non-AAA CVD, and 58 993 without CVD. The 5-year cumulative incidence of cancer was 13.1% (12.8%-13.5%) in participants with AAA, 10.1% (9.9%-10.3%) in participants with non-AAA CVD, and 9.6% (9.3%-9.9%) in participants without CVD. Multivariable-adjusted Cox proportional hazards regression models found that patients with AAA exhibited a higher cancer risk than either those with non-AAA CVD (hazard ratio, 1.28 [95% CI, 1.23-1.32]; P<0.001) or those without CVD (hazard ratio, 1.32 [95% CI, 1.26-1.38]; P<0.001). Results remained consistent after excluding common smoking-related cancers and when adjusting for tobacco use and body mass index.

CONCLUSIONS

Patients with AAA may have a unique risk of cancer requiring further mechanistic study and investigation of the role of enhanced cancer screening.

From Atherosclerosis to Spontaneous Coronary Artery Dissection: Defining a Clinical and Genetic Risk Spectrum for Myocardial Infarction

PURPOSE OF REVIEW

Spontaneous coronary artery dissection (SCAD) has been increasingly recognized as a significant cause of acute myocardial infarction (AMI) in young and middle-aged women and arises through mechanisms independent of atherosclerosis. SCAD has a multifactorial etiology that includes environmental, individual, and genetic factors distinct from those typically associated with coronary artery disease. Here, we summarize the current understanding of the genetic factors contributing to the development of SCAD and highlight those factors which differentiate SCAD from atherosclerotic coronary artery disease.

RECENT FINDINGS

Recent studies have revealed several associated variants with varying effect sizes for SCAD, giving rise to a complex genetic architecture. Associated genes highlight an important role for arterial cells and their extracellular matrix in the pathogenesis of SCAD, as well as notable genetic overlap between SCAD and other systemic arteriopathies such as fibromuscular dysplasia and vascular connective tissue diseases. Further investigation of individual variants (including in the associated gene PHACTR1) along with polygenic score analysis have demonstrated an inverse genetic relationship between SCAD and atherosclerosis as distinct causes of AMI. SCAD represents an increasingly recognized cause of AMI with opposing clinical and genetic risk factors from that of AMI due to atherosclerosis, and it is often associated with complex underlying genetic conditions. Genetic study of SCAD on a larger scale and with more diverse cohorts will not only further our evolving understanding of a newly defined genetic spectrum for AMI, but it will also inform the clinical utility of integrating genetic testing in AMI prevention and management moving forward.

Sleep Pattern, Genetic Susceptibility, and Abdominal Aortic Aneurysm in UK Biobank Participants: Large-Scale Cohort Study

Background

Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality.

Objectives

The authors aimed to explore the associations between sleep patterns and genetic susceptibility to AAA.

Methods

We included 344,855 UK Biobank study participants free of AAA at baseline. A sleep pattern was defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness, and an overall sleep score was constructed with a range from 0 to 5, where a high score denotes a healthy sleep pattern. Polygenic risk score based on 22 single nucleotide polymorphisms was categorized into tertiles and used to evaluate the genetic risk for AAA. Cox proportional hazards regression models were used to assess the association between sleep, genetic factors, and the incidence of AAA.

Results

During a median of 12.59 years of follow-up, 1,622 incident AAA cases were identified. The HR per 1-point increase in the sleep score was 0.91 (95% CI: 0.86-0.96) for AAA. Unhealthy sleep patterns, defined as a sleep score ranging from 0 to 3, were found to be associated with a higher risk of AAA for the intermediate (HR: 1.18, 95% CI: 1.06-1.31) and poor sleep patterns (HR: 1.40, 95% CI: 1.13-1.73), respectively, compared to the healthy pattern. Participants with poor sleep patterns and high genetic risks had a 2.5-fold higher risk of AAA than those with healthy sleep patterns and low genetic risk.

Conclusions

In this large prospective study, healthy sleep patterns were associated with a lower risk of AAA among participants with low, intermediate, or high genetic risk.

Molecular mechanisms of perilipin protein function in lipid droplet metabolism

Perilipins are abundant lipid droplet (LD) proteins present in all metazoans and also in Amoebozoa and fungi. Humans express five perilipins, which share a similar domain organization: an amino-terminal PAT domain and an 11-mer repeat region, which can fold into amphipathic helices that interact with LDs, followed by a structured carboxy-terminal domain. Variations of this organization that arose during vertebrate evolution allow for functional specialization between perilipins in relation to the metabolic needs of different tissues. We discuss how different features of perilipins influence their interaction with LDs and their cellular targeting. PLIN1 and PLIN5 play a direct role in lipolysis by regulating the recruitment of lipases to LDs and LD interaction with mitochondria. Other perilipins, particularly PLIN2, appear to protect LDs from lipolysis, but the molecular mechanism is not clear. PLIN4 stands out with its long repetitive region, whereas PLIN3 is most widely expressed and is used as a nascent LD marker. Finally, we discuss the genetic variability in perilipins in connection with metabolic disease, prominent for PLIN1 and PLIN4, underlying the importance of understanding the molecular function of perilipins.

Major depressive disorder and aneurysm: A genetic study of association and causality

BACKGROUND

Association between depression and aneurysm has been implicated but the specific role of depression in aneurysm remains unclear. We aimed to comprehensively characterize the relation of major depressive disorder (MDD) with aneurysm by subtype.

METHODS

Harnessing summary statistics from genome-wide association studies (Ncase/Ncontrol = 7603/317,899 for aortic aneurysm; 7321/317,899 for thoracic aortic aneurysm; 3201/317,899 for abdominal aortic aneurysm; 1788/317,899 for cerebral aneurysm; and 246,363/561,190 for major depressive disorder), we estimated the genetic correlation between MDD and each of four aneurysm subtypes via LD Score Regression and tested the causality via various estimators under the bi-directional Mendelian randomization (MR) framework.

RESULTS

Positive genetic correlation of statistical significance, ranging between 0.15 (with thoracic aortic aneurysm, P = 0.005) and 0.25 (with abdominal aortic aneurysm, P = 0.001), was consistently observed for MDD with each aneurysm subtype. In the MR analysis of MDD as an exposure, genetic liability to MDD causally increased the risk of cerebral (odds ratio: 1.71; 95 % confidence interval: 1.26-2.34) but not aortic aneurysm. Replication analysis of an independent dataset (Ncase/Ncontrol = 6242/59,418) corroborated this signal. In contrast, causal effect was not evident for any neurysm subtype on susceptibility to MDD.

LIMITATIONS

Aneurysm could have been underdiagnosed if asymptomatic, leading to an underestimated causal impact on MDD. Non-linearity of the causal effect was not tested due to the lack of individual-level data.

CONCLUSIONS

Depression and aneurysm may share common pathomechanisms. Screening depressed population and improving the clinical management for depression may benefit the primary prevention of cerebral aneurysm.

Diagnosis and treatment of cardiovascular disease in patients with heritable connective tissue disorders or heritable thoracic aortic diseases

Patients with heritable connective tissue disorders (HCTDs), represented by Marfan syndrome, can develop fatal aortic and/or arterial complications before age 50. Therefore, accurate diagnosis, appropriate medical treatment, and early prophylactic surgical treatment of aortic and arterial lesions are essential to improve prognosis. Patients with HCTDs generally present with specific physical features due to connective tissue abnormalities, while some patients with heritable thoracic aortic diseases (HTADs) have few distinctive physical characteristics. The development of genetic testing has made it possible to provide accurate diagnoses for patients with HCTDs/HTADs. This review provides an overview of the diagnosis and treatment of HCTDs/HTADs, including current evidence on cardiovascular interventions for this population.

Effectiveness of educational interventions for diabetes-related foot disease: A systematic review and meta-analysis

This systematic review and meta-analysis pooled evidence from randomised controlled trials (RCTs) on the effectiveness of educational programs for people with or at risk of diabetes-related foot disease (DFD). A systematic search identified RCTs evaluating the effectiveness of educational programs in preventing or managing DFD. The primary outcome was risk of developing a foot ulcer. Secondary outcomes included any amputation, mortality, changes in cardiovascular risk factors, foot-care knowledge and self-care behaviours. Meta-analyses were performed using random effects models. Risk of bias was assessed using Cochrane's ROB-2 tool. Education programs were tested in 29 RCTs (n = 3891) and reduced risk of a foot ulcer by approximately half although the upper 95% confidence interval (CI) reached 1.00 (odds ratio [OR], OR 0.54; 95% CI 0.29, 1.00, I2  = 65%). Education programs reduced risk of any amputation (OR 0.34; 95% CI 0.13, 0.88, I2  = 38%) and HbA1c levels (standardized mean difference -0.73; 95% CI -1.26, -0.20, I2  = 93%) without affecting all-cause mortality (OR 1.09; 95% CI 0.57, 2.07, I2  = 0%). Education programs mostly significantly improved DFD knowledge (13 of 16 trials) and self-care behaviour scores (19 of 20 trials). Only one trial was deemed at low risk of bias. Previously tested education programs have mostly effectively improved participants' knowledge and self-care behaviours and reduced risk of foot ulceration and amputation. Larger high quality trials with longer follow-up are needed.

Matrisome and Immune Pathways Contribute to Extreme Vascular Outcomes in Williams-Beuren Syndrome

BACKGROUND

Supravalvar aortic stenosis (SVAS) is a characteristic feature of Williams-Beuren syndrome (WBS). Its severity varies: ~20% of people with Williams-Beuren syndrome have SVAS requiring surgical intervention, whereas ~35% have no appreciable SVAS. The remaining individuals have SVAS of intermediate severity. Little is known about genetic modifiers that contribute to this variability.

METHODS AND RESULTS

We performed genome sequencing on 473 individuals with Williams-Beuren syndrome and developed strategies for modifier discovery in this rare disease population. Approaches include extreme phenotyping and nonsynonymous variant prioritization, followed by gene set enrichment and pathway-level association tests. We next used GTEx v8 and proteomic data sets to verify expression of candidate modifiers in relevant tissues. Finally, we evaluated overlap between the genes/pathways identified here and those ascertained through larger aortic disease/trait genome-wide association studies. We show that SVAS severity in Williams-Beuren syndrome is associated with increased frequency of common and rarer variants in matrisome and immune pathways. Two implicated matrisome genes (ACAN and LTBP4) were uniquely expressed in the aorta. Many genes in the identified pathways were previously reported in genome-wide association studies for aneurysm, bicuspid aortic valve, or aortic size.

CONCLUSIONS

Smaller sample sizes in rare disease studies necessitate new approaches to detect modifiers. Our strategies identified variation in matrisome and immune pathways that are associated with SVAS severity. These findings suggest that, like other aortopathies, SVAS may be influenced by the balance of synthesis and degradation of matrisome proteins. Leveraging multiomic data and results from larger aorta-focused genome-wide association studies may accelerate modifier discovery for rare aortopathies like SVAS.

A linear weighted combination of polygenic scores for a broad range of traits improves prediction of coronary heart disease

Polygenic scores (PGS) for coronary heart disease (CHD) are constructed using GWAS summary statistics for CHD. However, pleiotropy is pervasive in biology and disease-associated variants often share etiologic pathways with multiple traits. Therefore, incorporating GWAS summary statistics of additional traits could improve the performance of PGS for CHD. Using lasso regression models, we developed two multi-PGS for CHD: 1) multiPGSCHD, utilizing GWAS summary statistics for CHD, its risk factors, and other ASCVD as training data and the UK Biobank for tuning, and 2) extendedPGSCHD, using existing PGS for a broader range of traits in the PGS Catalog as training data and the Atherosclerosis Risk in Communities Study (ARIC) cohort for tuning. We evaluated the performance of multiPGSCHD and extendedPGSCHD in the Mayo Clinic Biobank, an independent cohort of 43,578 adults of European ancestry which included 4,479 CHD cases and 39,099 controls. In the Mayo Clinic Biobank, a 1 SD increase in multiPGSCHD and extendedPGSCHD was associated with a 1.66-fold (95% CI: 1.60-1.71) and 1.70-fold (95% CI: 1.64-1.76) increased odds of CHD, respectively, in models that included age, sex, and 10 PCs, whereas an already published PGS for CHD (CHD_PRSCS) increased the odds by 1.50 (95% CI: 1.45-1.56). In the highest deciles of extendedPGSCHD, multiPGSCHD, and CHD_PRSCS, 18.4%, 17.5%, and 16.3% of patients had CHD, respectively.

Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease

Aortic disease, including dissection, aneurysm, and rupture, carries significant morbidity and mortality and is a notable cause of sudden cardiac death. Much of our knowledge regarding the genetic basis of aortic disease has relied on the study of individuals with Mendelian aortopathies and, until recently, the genetic determinants of population-level variance in aortic phenotypes remained unclear. However, the application of machine learning methodologies to large imaging datasets has enabled researchers to rapidly define aortic traits and mine dozens of novel genetic associations for phenotypes such as aortic diameter and distensibility. In this review, we highlight the emerging potential of genomics for identifying causal genes and candidate drug targets for aortic disease. We describe how deep learning technologies have accelerated the pace of genetic discovery in this field. We then provide a blueprint for translating genetic associations to biological insights, reviewing techniques for locus and cell type prioritization, high-throughput functional screening, and disease modeling using cellular and animal models of aortic disease.

Air pollutants, genetic susceptibility, and abdominal aortic aneurysm risk: a prospective study

BACKGROUND AND AIMS

Air pollutants are important contributors to cardiovascular diseases, but associations between long-term exposure to air pollutants and the risk of abdominal aortic aneurysm (AAA) are still unknown.

METHODS

This study was conducted using a sample of 449 463 participants from the UK Biobank. Hazard ratios and 95% confidence intervals for the risk of AAA incidence associated with long-term exposure to air pollutants were estimated using the Cox proportional hazards model with time-varying exposure measurements. Additionally, the cumulative incidence of AAA was calculated by using the Fine and Grey sub-distribution hazards regression model. Furthermore, this study investigated the combined effects and interactions between air pollutants exposure and genetic predisposition in relation to the risk of AAA onset.

RESULTS

Long-term exposure to particulate matter with an aerodynamic diameter <2.5 µm [PM2.5, 1.21 (1.16, 1.27)], particulate matter with an aerodynamic diameter <10 µm [PM10, 1.21 (1.16, 1.27)], nitrogen dioxide [NO2, 1.16 (1.11, 1.22)], and nitrogen oxides [NOx, 1.10 (1.05, 1.15)] was found to be associated with an elevated risk of AAA onset. The detrimental effects of air pollutants persisted even in participants with low-level exposure. For the joint associations, participants with both high levels of air pollutants exposure and high genetic risk had a higher risk of developing AAA compared with those with low concentrations of pollutants exposure and low genetic risk. The respective risk estimates for AAA incidence were 3.18 (2.46, 4.12) for PM2.5, 3.09 (2.39, 4.00) for PM10, 2.41 (1.86, 3.13) for NO2, and 2.01 (1.55, 2.61) for NOx.

CONCLUSIONS

In this study, long-term air pollutants exposure was associated with an increased risk of AAA incidence.

Mendelian randomization for cardiovascular diseases: principles and applications

Large-scale genome-wide association studies conducted over the last decade have uncovered numerous genetic variants associated with cardiometabolic traits and risk factors. These discoveries have enabled the Mendelian randomization (MR) design, which uses genetic variation as a natural experiment to improve causal inferences from observational data. By analogy with the random assignment of treatment in randomized controlled trials, the random segregation of genetic alleles when DNA is transmitted from parents to offspring at gamete formation is expected to reduce confounding in genetic associations. Mendelian randomization analyses make a set of assumptions that must hold for valid results. Provided that the assumptions are well justified for the genetic variants that are employed as instrumental variables, MR studies can inform on whether a putative risk factor likely has a causal effect on the disease or not. Mendelian randomization has been increasingly applied over recent years to predict the efficacy and safety of existing and novel drugs targeting cardiovascular risk factors and to explore the repurposing potential of available drugs. This review article describes the principles of the MR design and some applications in cardiovascular epidemiology.

Advancements in the Genetics of Spontaneous Coronary Artery Dissection

PURPOSE OF REVIEW

Spontaneous coronary artery dissection (SCAD) is a significant cause of acute myocardial infarction that is increasingly recognized in young and middle-aged women. The etiology of SCAD is likely multifactorial and may include the interaction of environmental and individual factors. Here, we summarize the current understanding of the genetic factors contributing to the development of SCAD.

RECENT FINDINGS

The molecular findings underlying SCAD have been demonstrated to include a combination of rare DNA sequence variants with large effects, common variants contributing to a complex genetic architecture, and variants with intermediate impact. The genes associated with SCAD highlight the role of arterial cells and their extracellular matrix in the pathogenesis of the disease and shed light on the relationship between SCAD and other disorders, including fibromuscular dysplasia and connective tissue diseases. While up to 10% of affected individuals may harbor a rare variant with large effect, SCAD most often presents as a complex genetic condition. Analyses of larger and more diverse cohorts will continue to improve our understanding of risk susceptibility loci and will also enable consideration of the clinical utility of genetic testing strategies in the management of SCAD.

Single-Molecule Spatial Transcriptomics of Human Thoracic Aortic Aneurysms Uncovers Calcification-Related CARTPT-Expressing Smooth Muscle Cells

BACKGROUND

Although single-cell RNA-sequencing is commonly applied to dissect the heterogeneity in human tissues, it involves the preparation of single-cell suspensions via cell dissociation, causing loss of spatial information. In this study, we employed high-resolution single-cell transcriptome imaging to reveal rare smooth muscle cell (SMC) types in human thoracic aortic aneurysm (TAA) tissue samples.

METHODS

Single-molecule spatial distribution of transcripts from 140 genes was analyzed in fresh-frozen human TAA samples with region and sex-matched controls. In vitro studies and tissue staining were performed to examine human CART prepropeptide (CARTPT) regulation and function.

RESULTS

We captured thousands of cells per sample including a spatially distinct CARTPT-expressing SMC subtype enriched in male TAA samples. Immunoassays confirmed human CART (cocaine- and amphetamine-regulated transcript) protein enrichment in male TAA tissue and truncated CARTPT secretion into cell culture medium. Oxidized low-density lipoprotein, a cardiovascular risk factor, induced CARTPT expression, whereas CARTPT overexpression in human aortic SMCs increased the expression of key osteochondrogenic transcription factors and reduced contractile gene expression. Recombinant human CART treatment of human SMCs further confirmed this phenotype. Alizarin red staining revealed calcium deposition in male TAA samples showing similar localization with human CART staining.

CONCLUSIONS

Here, we demonstrate the feasibility of single-molecule imaging in uncovering rare SMC subtypes in the diseased human aorta, a difficult tissue to dissociate. We identified a spatially distinct CARTPT-expressing SMC subtype enriched in male human TAA samples. Our functional studies suggest that human CART promotes osteochondrogenic switch of aortic SMCs, potentially leading to medial calcification of the thoracic aorta.

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 β 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.

Impact of patient demographics and intraoperative characteristics on abdominal aortic aneurysm sac following endovascular repair

BACKGROUND

Endovascular aortic repair (EVAR) has become the preferred treatment for abdominal aortic aneurysm (AAA). Its main aim is to seal the perfusion of the aneurysmal sac and, thus, induce sac regression and subsequent aortic remodelling. Aneurysmal sac regression has been linked to the short- and long-term clinical outcomes post-EVAR. It has also been shown to be influenced by endograft device choice, with several of these available commercially. This review summarises and discusses current evidence on the influence of pre- and intraoperative factors on sac regression. Additionally, this review aims to highlight the device-specific variations in sac regression to provide an overall holistic approach to treating AAAs with EVAR.

METHODS

A comprehensive literature search was conducted using multiple electronic databases to identify and extract relevant data.

RESULTS

Female sex, >70 mm original sac diameters, higher pre-procedural fibrinogen levels, smoking and low intra-aneurysmal pressure were found to positively impact sac regression. Whereas renal impairment, ischemic heart disease, high intra-aneurysmal pressure and aneurysm neck thrombus negatively influenced sac regression. Patent lumbar arteries, age, statins and hypercholesterolaemia displayed conflicting evidence regarding sac regression. Regarding the EVAR endografts compared, newer generation devices such as the Anaconda mainly showed the most optimal results.

CONCLUSION

Sac regression following EVAR in AAA is an important prognostic factor for morbidity and mortality. Nevertheless, several pre- and intraoperative factors can have an influence on sac regression. Therefore, it is necessary to take them into account when assessing AAA patients for EVAR to optimise outcomes. The choice of EVAR stent-graft can also affect sac regression, with evidence suggesting that the Fenestrated Anaconda is associated with the most favourable results.

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.

Pathogenesis and management of abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) causes ∼170 000 deaths annually worldwide. Most guidelines recommend asymptomatic small AAAs (30 to <50 mm in women; 30 to <55 mm in men) are monitored by imaging and large asymptomatic, symptomatic, and ruptured AAAs are considered for surgical repair. Advances in AAA repair techniques have occurred, but a remaining priority is therapies to limit AAA growth and rupture. This review outlines research on AAA pathogenesis and therapies to limit AAA growth. Genome-wide association studies have identified novel drug targets, e.g. interleukin-6 blockade. Mendelian randomization analyses suggest that treatments to reduce low-density lipoprotein cholesterol such as proprotein convertase subtilisin/kexin type 9 inhibitors and smoking reduction or cessation are also treatment targets. Thirteen placebo-controlled randomized trials have tested whether a range of antibiotics, blood pressure-lowering drugs, a mast cell stabilizer, an anti-platelet drug, or fenofibrate slow AAA growth. None of these trials have shown convincing evidence of drug efficacy and have been limited by small sample sizes, limited drug adherence, poor participant retention, and over-optimistic AAA growth reduction targets. Data from some large observational cohorts suggest that blood pressure reduction, particularly by angiotensin-converting enzyme inhibitors, could limit aneurysm rupture, but this has not been evaluated in randomized trials. Some observational studies suggest metformin may limit AAA growth, and this is currently being tested in randomized trials. In conclusion, no drug therapy has been shown to convincingly limit AAA growth in randomized controlled trials. Further large prospective studies on other targets are needed.

Comparison of Genes Associated with Thoracic and Abdominal Aortic Aneurysms

Aneurysms impacting the ascending thoracic aorta and the abdominal aorta affect patient populations with distinct clinical characteristics. Through a literature review, this paper compares the genetic associations of ascending thoracic aortic aneurysm (ATAA) with abdominal aortic aneurysms (AAA). Genes related to atherosclerosis, lipid metabolism, and tumor development are associated specifically with sporadic AAA, while genes controlling extracellular matrix (ECM) structure, ECM remodeling, and tumor growth factor β function are associated with both AAA and ATAA. Contractile element genes uniquely predispose to ATAA. Aside from known syndromic connective tissue disease and poly-aneurysmal syndromes (Marfan disease, Loeys-Dietz syndrome, and Ehlers-Danlos syndrome), there is only limited genetic overlap between AAA and ATAA. The rapid advances in genotyping and bioinformatics will elucidate further the various pathways associated with the development of aneurysms affecting various parts of the aorta.

Mendelian randomization analyses clarify the effects of height on cardiovascular diseases

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested causal association. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized a well-powered set of genetic instruments for human stature, comprising >1,800 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 0.02). However, multivariable analyses demonstrated independent effects of height on other cardiovascular traits beyond CAD, consistent with epidemiologic associations and univariable MR experiments. In contrast with published reports, we observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest the impact of height on CAD risk beyond previously established cardiovascular risk factors is minimal and not explained by lung function measures.

Genetics and mechanisms of thoracic aortic disease

Aortic disease has many forms including aortic aneurysm and dissection, aortic coarctation or abnormalities in aortic function, such as loss of aortic distensibility. Genetic analysis in humans is one of the most important experimental approaches in uncovering disease mechanisms, but the relative infrequency of thoracic aortic disease compared with other cardiovascular conditions such as coronary artery disease has hindered large-scale identification of genetic associations. In the past decade, advances in machine learning technology coupled with large imaging datasets from biobank repositories have facilitated a rapid expansion in our capacity to measure and genotype aortic traits, resulting in the identification of dozens of genetic associations. In this Review, we describe the history of technological advances in genetic discovery and explain how newer technologies such as deep learning can rapidly define aortic traits at scale. Furthermore, we integrate novel genetic observations provided by these advances into our current biological understanding of thoracic aortic disease and describe how these new findings can contribute to strategies to prevent and treat aortic disease.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Proteomics Analysis of Genetic Liability of Abdominal Aortic Aneurysm Identifies Plasma Neogenin and Kit Ligand: The ARIC Study

BACKGROUND

Genome-wide association studies have reported 23 gene loci related to abdominal aortic aneurysm (AAA)-a potentially lethal condition characterized by a weakened dilated vessel wall. This study aimed to identify proteomic signatures and pathways related to these risk loci to better characterize AAA genetic susceptibility.

METHODS

Plasma concentrations of 4870 proteins were determined using a DNA aptamer-based array. Linear regression analysis estimated the associations between the 23 risk alleles and plasma protein levels with adjustments for potential confounders in a race-stratified analysis of 1671 Black and 7241 White participants. Significant proteins were then evaluated for their prediction of clinical AAA (454 AAA events in 11 064 individuals), and those significantly associated with AAA were further interrogated using Mendelian randomization analysis.

RESULTS

Risk variants proximal to PSRC1-CELSR2-SORT1, PCIF1-ZNF335-MMP9, RP11-136O12.2/TRIB1, ZNF259/APOA5, IL6R, PCSK9, LPA, and APOE were associated with 118 plasma proteins in Whites and 59 were replicated in Black participants. Novel associations with clinical AAA incidence were observed for kit ligand (HR, 0.59 [95% CI, 0.42-0.82] for top versus first quintiles) and neogenin (HR, 0.64 [95% CI, 0.46-0.88]) over a median 21.2-year follow-up; neogenin was also associated with ultrasound-detected asymptomatic AAA (N=4295; 57 asymptomatic AAA cases). Mendelian randomization inverse variance weighted estimates suggested that AAA risk is promoted by lower levels of kit ligand (OR per SD=0.67; P=1.4×10-5) and neogenin (OR per SD=0.50; P=0.03).

CONCLUSIONS

Low levels of neogenin and kit ligand may be novel risk factors for AAA development in potentially causal pathways. These findings provide insights and potential targets to reduce AAA susceptibility.

Predictive models for abdominal aortic aneurysms using polygenic scores and PheWAS-derived risk factors

Abdominal aortic aneurysms (AAA) are common enlargements of the abdominal aorta which can grow larger until rupture, often leading to death. Detection of AAA is often by ultrasonography and screening recommendations are mostly directed at men over 65 with a smoking history. Recent large-scale genome-wide association studies have identified genetic loci associated with AAA risk. We combined known risk factors, polygenic risk scores (PRS) and precedent clinical diagnoses from electronic health records (EHR) to develop predictive models for AAA, and compared performance against screening recommendations. The PRS included genome-wide summary statistics from the Million Veteran Program and FinnGen (10,467 cases, 378,713 controls of European ancestry), with optimization in Vanderbilt's BioVU and validated in the eMERGE Network, separately across both White and Black participants. Candidate diagnoses were identified through a temporally-oriented Phenome-wide association study in independent EHR data from Vanderbilt, and features were selected via elastic net. We calculated C-statistics in eMERGE for models including PRS, phecodes, and covariates using regression weights from BioVU. The AUC for the full model in the test set was 0.883 (95% CI 0.873-0.892), 0.844 (0.836-0.851) for covariates only, 0.613 (95% CI 0.604-0.622) when using primary USPSTF screening criteria, and 0.632 (95% CI 0.623-0.642) using primary and secondary criteria. Brier scores were between 0.003 and 0.023 for our models indicating good calibration, and net reclassification improvement over combined primary and secondary USPSTF criteria was 0.36-0.60. We provide PRS for AAA which are strongly associated with AAA risk and add to predictive model performance. These models substantially improve identification of people at risk of a AAA diagnosis compared with existing guidelines, with evidence of potential applicability in minority populations.

Linking single nucleotide polymorphisms to signaling blueprints in abdominal aortic aneurysms

Abdominal aortic aneurysms (AAA) is a multifactorial complex disease with life-threatening consequences. While Genome-wide association studies (GWAS) have revealed several single nucleotide polymorphisms (SNPs) located in the genome of individuals with AAA, the link between SNPs with the associated pathological signals, the influence of risk factors on their distribution and their combined analysis is not fully understood. We integrated 86 AAA SNPs from GWAS and clinical cohorts from the literature to determine their phenotypical vulnerabilities and association with AAA risk factors. The SNPs were annotated using snpXplorer AnnotateMe tool to identify their chromosomal position, minor allele frequency, CADD (Combined Annotation Dependent Depletion), annotation-based pathogenicity score, variant consequence, and their associated gene. Gene enrichment analysis was performed using Gene Ontology and clustered using REVIGO. The plug-in GeneMANIA in Cytoscape was applied to identify network integration with associated genes and functions. 15 SNPs affecting 20 genes with a CADD score above ten were identified. AAA SNPs were predominantly located on chromosome 3 and 9. Stop-gained rs5516 SNP obtained high frequency in AAA and associated with proinflammatory and vascular remodeling phenotypes. SNPs presence positively correlated with hypertension, dyslipidemia and smoking history. GO showed that AAA SNPs and their associated genes could regulate lipid metabolism, extracellular matrix organization, smooth muscle cell proliferation, and oxidative stress, suggesting that part of these AAA traits could stem from genetic abnormalities. We show a library of inborn SNPs and associated genes that manifest in AAA. We uncover their pathological signaling trajectories that likely fuel AAA development.

Fibromuscular Dysplasia and Abdominal Aortic Aneurysms Are Dimorphic Sex-Specific Diseases With Shared Complex Genetic Architecture

BACKGROUND

The risk of arterial diseases may be elevated among family members of individuals having multifocal fibromuscular dysplasia (FMD). We sought to investigate the risk of arterial diseases in families of individuals with FMD.

METHODS

Family histories for 73 probands with FMD were obtained, which included an analysis of 463 total first-degree relatives focusing on FMD and related arterial disorders. A polygenic risk score for FMD (PRSFMD) was constructed from prior genome-wide association findings of 584 FMD cases and 7139 controls and evaluated for association with an abdominal aortic aneurysm (AAA) in a cohort of 9693 AAA cases and 294 049 controls. A previously published PRSAAA was also assessed among the FMD cases and controls.

RESULTS

Of all first degree relatives of probands, 9.3% were diagnosed with FMD, aneurysms, and dissections. Aneurysmal disease occurred in 60.5% of affected relatives and 5.6% of all relatives. Among 227 female first-degree relatives of probands, 4.8% (11) had FMD, representing a relative risk (RR)FMD of 1.5 ([95% CI, 0.75-2.8]; P=0.19) compared with the estimated population prevalence of 3.3%, though not of statistical significance. Of all fathers of FMD probands, 11% had AAAs resulting in a RRAAA of 2.3 ([95% CI, 1.12-4.6]; P=0.014) compared with population estimates. The PRSFMD was found to be associated with an AAA (odds ratio, 1.03 [95% CI, 1.01-1.05]; P=2.6×10-3), and the PRSAAA was found to be associated with FMD (odds ratio, 1.53 [95% CI, 1.2-1.9]; P=9.0×10-5) as well.

CONCLUSIONS

FMD and AAAs seem to be sex-dimorphic manifestations of a heritable arterial disease with a partially shared complex genetic architecture. Excess risk of having an AAA according to a family history of FMD may justify screening in family members of individuals having FMD.

The HUNT study: A population-based cohort for genetic research

The Trøndelag Health Study (HUNT) is a population-based cohort of ∼229,000 individuals recruited in four waves beginning in 1984 in Trøndelag County, Norway. Approximately 88,000 of these individuals have available genetic data from array genotyping. HUNT participants were recruited during four community-based recruitment waves and provided information on health-related behaviors, self-reported diagnoses, family history of disease, and underwent physical examinations. Linkage via the Norwegian personal identification number integrates digitized health care information from doctor visits and national health registries including death, cancer and prescription registries. Genome-wide association studies of HUNT participants have provided insights into the mechanism of cardiovascular, metabolic, osteoporotic, and liver-related diseases, among others. Unique features of this cohort that facilitate research include nearly 40 years of longitudinal follow-up in a motivated and well-educated population, family data, comprehensive phenotyping, and broad availability of DNA, RNA, urine, fecal, plasma, and serum samples.

Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.

Genetic and clinical determinants of abdominal aortic diameter: genome-wide association studies, exome array data and Mendelian randomization study

Progressive dilation of the infrarenal aortic diameter is a consequence of the ageing process and is considered the main determinant of abdominal aortic aneurysm (AAA). We aimed to investigate the genetic and clinical determinants of abdominal aortic diameter (AAD). We conducted a meta-analysis of genome-wide association studies in 10 cohorts (n = 13 542) imputed to the 1000 Genome Project reference panel including 12 815 subjects in the discovery phase and 727 subjects [Partners Biobank cohort 1 (PBIO)] as replication. Maximum anterior-posterior diameter of the infrarenal aorta was used as AAD. We also included exome array data (n = 14 480) from seven epidemiologic studies. Single-variant and gene-based associations were done using SeqMeta package. A Mendelian randomization analysis was applied to investigate the causal effect of a number of clinical risk factors on AAD. In genome-wide association study (GWAS) on AAD, rs74448815 in the intronic region of LDLRAD4 reached genome-wide significance (beta = -0.02, SE = 0.004, P-value = 2.10 × 10-8). The association replicated in the PBIO1 cohort (P-value = 8.19 × 10-4). In exome-array single-variant analysis (P-value threshold = 9 × 10-7), the lowest P-value was found for rs239259 located in SLC22A20 (beta = 0.007, P-value = 1.2 × 10-5). In the gene-based analysis (P-value threshold = 1.85 × 10-6), PCSK5 showed an association with AAD (P-value = 8.03 × 10-7). Furthermore, in Mendelian randomization analyses, we found evidence for genetic association of pulse pressure (beta = -0.003, P-value = 0.02), triglycerides (beta = -0.16, P-value = 0.008) and height (beta = 0.03, P-value < 0.0001), known risk factors for AAA, consistent with a causal association with AAD. Our findings point to new biology as well as highlighting gene regions in mechanisms that have previously been implicated in the genetics of other vascular diseases.

Single-cell Transcriptomics Reveals Dynamic Role of Smooth Muscle Cells and Enrichment of Immune Cell Subsets in Human Abdominal Aortic Aneurysms

OBJECTIVE

To determine cell-specific gene expression profiles that contribute to development of abdominal aortic aneurysms (AAAs).

BACKGROUND

AAAs represent the most common pathological aortic dilation leading to the fatal consequence of aortic rupture. Both immune and structural cells contribute to aortic degeneration, however, gene specific alterations in these cellular subsets are poorly understood.

METHODS

We performed single-cell RNA sequencing (scRNA-seq) analysis of AAAs and control tissues. AAA-related changes were examined by comparing gene expression profiles as well as detailed receptor-ligand interactions. An integrative analysis of scRNA-seq data with large genome-wide association study data was conducted to identify genes critical for AAA development.

RESULTS

Using scRNA-seq we provide the first comprehensive characterization of the cellular landscape in human AAA tissues. Unbiased clustering analysis of transcriptional profiles identified seventeen clusters representing 8 cell lineages. For immune cells, clustering analysis identified 4 T-cell and 5 monocyte/macrophage subpopulations, with distinct transcriptional profiles in AAAs compared to controls. Gene enrichment analysis on immune subsets identified multiple pathways only expressed in AAA tissue, including those involved in mitochondrial dysfunction, proliferation, and cytokine secretion. Moreover, receptor-ligand analysis defined robust interactions between vascular smooth muscle cells and myeloid populations in AAA tissues. Lastly, integrated analysis of scRNA-seq data with genome-wide association study studies determined that vascular smooth muscle cell expression of SORT1 is critical for maintaining normal aortic wall function.

CONCLUSIONS

Here we provide the first comprehensive evaluation of single-cell composition of the abdominal aortic wall and reveal how the gene expression landscape is altered in human AAAs.

Repair of Abdominal Aortic Aneurysms: JACC Focus Seminar, Part 1

Abdominal aortic aneurysms (AAAs), defined by an aortic diameter >3 cm, affect >1 million people in the United States. Risk factors for AAA include male sex, family history of AAA, smoking, Caucasian ethnicity, and age. Patients with known AAA should undergo regular surveillance via ultrasonography. Medical management, including smoking cessation and blood pressure management, is recommended for asymptomatic patients who do not meet the threshold for intervention. Repair options include endovascular aortic repair and open surgical repair, with good outcomes in long-term follow-up. Men with AAA >5.5 cm and women with AAA >5.0 cm in general should undergo elective repair. Medical management, including smoking cessation and blood pressure management, is recommended for asymptomatic patients who do not meet the threshold for intervention.

Association of cardiovascular risk factors and lifestyle behaviors with aortic aneurysm: A Mendelian randomization study

Objective: To examine the causality between hypertension, diabetes, other cardiovascular risk factors, lifestyle behaviors, and the aortic aneurysm among patients of European ancestry.

Methods: We performed two-sample Mendelian randomization (MR) analysis to investigate the causality of 12 modifiable risk factors with aortic aneurysm, including hypertension, body mass index (BMI), waist–hip ratio (WHR), diabetes, tobacco smoking, alcohol and coffee consumption, physical activity, and sleep duration. Genome-wide significant genetic instruments (p < 5 × 10^–8) for risk factors were extracted from European-descent genome-wide association studies, whereas aortic aneurysm genetic instruments were selected from the UK Biobank and FinnGen cohort. The inverse-variance weighted MR was used as the main analysis, and MR-Egger (MRE), weighted median MR, MR pleiotropy residual sum and outlier, and Phenoscanner searching were performed as sensitivity analyses. Furthermore, we calculated MRE intercept to detect pleiotropy and Cochran’s Q statistics to assess heterogeneity and conducted bidirectional MR and MR Steiger tests to exclude the possibility of reverse causality.

Results: We observed significantly higher risks for the aortic aneurysm in hypertension [pooled OR: 4.30 (95% CI 2.84–6.52)], BMI [OR: 1.58 (95% CI 1.37–1.81)], WHR [OR: 1.51 (95% CI 1.21–1.88)], WHR adjusted for BMI (WHRadjBMI) [OR: 1.35 (95% CI 1.12–1.63)], age of smoking initiation [OR: 1.63 (95% CI 1.18–2.26)], and tobacco use (initiation, cessation, and heaviness) [OR: 2.88 (95% CI 1.85–2.26)]. In sensitivity analysis, the causal effects of hypertension, BMI, WHRadjBMI, and tobacco use (initiation, cessation, and heaviness) remained robust.

Conclusion: There was a positive causal relationship between hypertension, BMI, WHR, and WHRadjBMI and aortic aneurysm.

Human abdominal aortic aneurysm (AAA): Evidence for an autoimmune antigen-driven disease

Abdominal aortic aneurism (AAA) is a complex immunological disease with a strong genetic component, and one of the ten leading causes of death of individuals 55-74 years old worldwide. Strong evidence has been accumulated suggesting that AAA is an autoimmune specific antigen-driven disease. Mononuclear cells infiltrating AAA lesions comprised of T and B lymphocytes and other cells expressing early-, intermediate- and late-activation antigens, and the presence of antigen-presenting cells have been documented, demonstrating an ongoing immune response. The three components of the trimolecular complex, T-cell receptor (TCR)/peptide (antigen)/HLA have been identified in AAA, and specifically: (i) clonal expansions of T-cell clones in AAA lesions; (ii) the association of AAA with particular HLA Class I and Class II; and (iii) self or nonself putative AAA-associated antigens. IgG autoantibodies recognizing proteins present in normal aortic tissue have been reported in patients with AAA. Molecular mimicry, defined as the sharing of antigenic epitopes between microorganisms (bacteria, viruses) and self antigens, maybe is responsible for T-cell responses and antibody production in AAA. Also, the frequency and the suppressor activity of CD4 + CD25 + FOXP3+ Tregs and the expression of FOXP3 transcripts and protein have been reported to be significantly impaired in AAA patients vs normal donors.

High heritability of ascending aortic diameter and trans-ancestry prediction of thoracic aortic disease

Enlargement of the aorta is an important risk factor for aortic aneurysm and dissection, a leading cause of morbidity in the developed world. Here we performed automated extraction of ascending aortic diameter from cardiac magnetic resonance images of 36,021 individuals from the UK Biobank, followed by genome-wide association. We identified lead variants across 41 loci, including genes related to cardiovascular development (HAND2, TBX20) and Mendelian forms of thoracic aortic disease (ELN, FBN1). A polygenic score significantly predicted prevalent risk of thoracic aortic aneurysm and the need for surgical intervention for patients with thoracic aneurysm across multiple ancestries within the UK Biobank, FinnGen, the Penn Medicine Biobank and the Million Veterans Program (MVP). Additionally, we highlight the primary causal role of blood pressure in reducing aortic dilation using Mendelian randomization. Overall, our findings provide a roadmap for using genetic determinants of human anatomy to understand cardiovascular development while improving prediction of diseases of the thoracic aorta.

Endothelial Dysfunction in the Pathogenesis of Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA), defined as a focal dilation of the abdominal aorta beyond 50% of its normal diameter, is a common and potentially life-threatening vascular disease. The molecular and cellular mechanisms underlying AAA pathogenesis remain unclear. Healthy endothelial cells (ECs) play a critical role in maintaining vascular homeostasis by regulating vascular tone and maintaining an anti-inflammatory, anti-thrombotic local environment. Increasing evidence indicates that endothelial dysfunction is an early pathologic event in AAA formation, contributing to both oxidative stress and inflammation in the degenerating arterial wall. Recent studies utilizing single-cell RNA sequencing revealed heterogeneous EC sub-populations, as determined by their transcriptional profiles, in aortic aneurysm tissue. This review summarizes recent findings, including clinical evidence of endothelial dysfunction in AAA, the impact of biomechanical stress on EC in AAA, the role of endothelial nitric oxide synthase (eNOS) uncoupling in AAA, and EC heterogeneity in AAA. These studies help to improve our understanding of AAA pathogenesis and ultimately may lead to the generation of EC-targeted therapeutics to treat or prevent this deadly disease.

Genetic Predisposition to Diabetes and Abdominal Aortic Aneurysm: A Two Stage Mendelian Randomisation Study

OBJECTIVE

Observational studies demonstrate an inverse association between type II diabetes and abdominal aortic aneurysm (AAA) for reasons that are unclear. The aim of this study was to clarify the causal association between type II diabetes predisposition and AAA using Mendelian randomisation.

METHODS

Effect estimates for single nucleotide polymorphisms (SNPs) associated with diabetes were obtained from the DIAbetes Meta-ANalysis of Trans-Ethnic association studies (DIAMANTE) consortium to construct a genetic instrumental variable. Corresponding effect estimates for associations of these SNPs with AAA were obtained from the International Aneurysm Consortium comprising six separate AAA genomewide association studies (4 972 cases and 99 858 controls). Mendelian randomisation estimates were calculated using inverse variance, weighted median, and MR-Egger methods, and compared against recently published observational estimates.

RESULTS

A genetic risk score was constructed from 206 SNPs associated with diabetes. All three Mendelian randomisation models showed no effect of genetic liability to diabetes and risk of AAA (inverse variance: odds ratio 1.04 per unit higher log odds, 95% 0.98 - 1.11, p = .19; MR-Egger slope p = .33; weighted median p = .50). Results were similar after excluding the TCF7L2 locus (inverse variance p = .075). Findings from the Mendelian randomisation analysis differed from previous observational reports of an inverse association (pdif < .001).

CONCLUSION

Lifelong genetic predisposition to diabetes does not appear to protect against AAA. These findings differ from traditional epidemiological studies showing an inverse association between diabetes and AAA, for reasons that remain unclear.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

The Role of Epigenetic Modifications in Abdominal Aortic Aneurysm Pathogenesis

Abdominal aortic aneurysm (AAA) is a life-threatening disease associated with high morbidity and mortality in the setting of acute rupture. Recently, advances in surgical and endovascular repair of AAA have been achieved; however, pharmaceutical therapies to prevent AAA expansion and rupture remain lacking. This highlights an ongoing need to improve the understanding the pathological mechanisms that initiate formation, maintain growth, and promote rupture of AAA. Over the past decade, epigenetic modifications, such as DNA methylation, posttranslational histone modifications, and non-coding RNA, have emerged as important regulators of cellular function. Accumulating studies reveal the importance of epigenetic enzymes in the dynamic regulation of key signaling pathways that alter cellular phenotypes and have emerged as major intracellular players in a wide range of biological processes. In this review, we discuss the roles and implications of epigenetic modifications in AAA animal models and their relevance to human AAA pathology.

Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a common and severe disease with major genetic risk factors. In this study we generated enhancer-promoter contact data to identify regulatory elements in AAA-relevant cell types and identified changes in their predicted chromatin accessibility between AAA patients and controls. We integrated this information with disease-associated variants in regulatory elements and gene bodies to further understand the etiology and pathogenetic mechanisms of AAA. Our study combined whole-genome sequencing data with gene regulatory relations in disease-relevant cell types to reveal the important roles of the interleukin 6 pathway and ERG and KLF regulation in AAA pathogenesis.

Abdominal aortic aneurysm (AAA) is a common degenerative cardiovascular disease whose pathobiology is not clearly understood. The cellular heterogeneity and cell-type-specific gene regulation of vascular cells in human AAA have not been well-characterized. Here, we performed analysis of whole-genome sequencing data in AAA patients versus controls with the aim of detecting disease-associated variants that may affect gene regulation in human aortic smooth muscle cells (AoSMC) and human aortic endothelial cells (HAEC), two cell types of high relevance to AAA disease. To support this analysis, we generated H3K27ac HiChIP data for these cell types and inferred cell-type-specific gene regulatory networks. We observed that AAA-associated variants were most enriched in regulatory regions in AoSMC, compared with HAEC and CD4⁺ cells. The cell-type-specific regulation defined by this HiChIP data supported the importance of ERG and the KLF family of transcription factors in AAA disease. The analysis of regulatory elements that contain noncoding variants and also are differentially open between AAA patients and controls revealed the significance of the interleukin-6-mediated signaling pathway. This finding was further validated by including information from the deleteriousness effect of nonsynonymous single-nucleotide variants in AAA patients and additional control data from the Medical Genome Reference Bank dataset. These results shed important insights into AAA pathogenesis and provide a model for cell-type-specific analysis of disease-associated variants.

Clinical utility of polygenic risk scores for coronary artery disease

Over the past decade, substantial progress has been made in the discovery of alleles contributing to the risk of coronary artery disease. In addition to providing causal insights into disease, these endeavours have yielded and enabled the refinement of polygenic risk scores. These scores can be used to predict incident coronary artery disease in multiple cohorts and indicate the clinical response to some preventive therapies in post hoc analyses of clinical trials. These observations and the widespread ability to calculate polygenic risk scores from direct-to-consumer and health-care-associated biobanks have raised many questions about responsible clinical adoption. In this Review, we describe technical and downstream considerations for the derivation and validation of polygenic risk scores and current evidence for their efficacy and safety. We discuss the implementation of these scores in clinical medicine for uses including risk prediction and screening algorithms for coronary artery disease, prioritization of patient subgroups that are likely to derive benefit from treatment, and efficient prospective clinical trial designs.

The total and direct effects of systolic and diastolic blood pressure on cardiovascular disease and longevity using Mendelian randomisation

The 2017 American College of Cardiology/American Heart Association (ACC/AHA) blood pressure (BP) guidelines lowered the hypertension threshold to ≥ 130/80 mmHg, but the role of diastolic BP remains contested. This two-sample mendelian randomisation study used replicated genetic variants predicting systolic and diastolic BP applied to the UK Biobank and large genetic consortia, including of cardiovascular diseases and parental lifespan, to obtain total and direct effects. Systolic and diastolic BP had positive total effects on CVD (odds ratio (OR) per standard deviation 2.15, 95% confidence interval (CI) 1.95, 2.37 and OR 1.91, 95% CI 1.73, 2.11, respectively). Direct effects were similar for systolic BP (OR 1.83, 95% CI 1.48, 2.25) but completely attenuated for diastolic BP (1.18, 95% CI 0.97, 1.44), although diastolic BP was associated with coronary artery disease (OR 1.24, 95% CI 1.03, 1.50). Systolic and diastolic BP had similarly negative total (- 0.20 parental attained age z-score, 95% CI - 0.22, - 0.17 and - 0.17, 95% CI - 0.20, - 0.15, respectively) and direct negative effects on longevity. Our findings suggest systolic BP has larger direct effects than diastolic BP on CVD, but both have negative effects (total and direct) on longevity, supporting the 2017 ACC/AHA guidelines lowering both BP targets.