A Genome-Wide Association Study of Idiopathic Dilated Cardiomyopathy in African Americans

Using Omics to Identify Novel Therapeutic Targets in Heart Failure

Omics refers to the measurement and analysis of the totality of molecules or biological processes involved within an organism. Examples of omics data include genomics, transcriptomics, epigenomics, proteomics, metabolomics, and more. In this review, we present the available literature reporting omics data on heart failure that can inform the development of novel treatments or innovative treatment strategies for this disease. This includes polygenic risk scores to improve prediction of genomic data and the potential of multiomics to more efficiently identify potential treatment targets for further study. We also discuss the limitations of omic analyses and the barriers that must be overcome to maximize the utility of these types of studies. Finally, we address the current state of the field and future opportunities for using multiomics to better personalize heart failure treatment strategies.

Burden from Study Questionnaire on Patient Fatigue in Qualitative Congestive Heart Failure Research

Mixed methods research forms the backbone of translational research methodologies. Qualitative research and subjective data lead to hypothesis generation and ideas that are then proven via quantitative methodologies and gathering objective data. In this vein, clinical trials that generate subjective data may have limitations, when they are not followed through with quantitative data, in terms of their ability to be considered gold standard evidence and inform guidelines and clinical management. However, since many research methods utilise qualitative tools, an initial factor is that such tools can create a burden on patients and researchers. In addition, the quantity of data and its storage contributes to noise and quality issues for its primary and post hoc use. This paper discusses the issue of the burden of subjective data collected and fatigue in the context of congestive heart failure (CHF) research. The CHF population has a high baseline morbidity, so no doubt the focus should be on the content; however, the lengths of the instruments are a product of their vigorous validation processes. Nonetheless, as an important source of hypothesis generation, if a choice of follow-up qualitative assessment is required for a clinical trial, shorter versions of the questionnaire should be used, without compromising the data collection requirements; otherwise, we need to invest in this area and find suitable solutions.

The Importance of Cultural Awareness in the Management of Heart Failure: A Narrative Review

Heart failure is a commonly encountered clinical syndrome arising from a range of etiologic cardiovascular diseases and manifests in a phenotypic spectrum of varying degrees of systolic and diastolic ventricular dysfunction. Those affected by this life-limiting illness are subject to an array of burdensome symptoms, poor quality of life, prognostic uncertainty, and a relatively onerous and increasingly complex treatment regimen. This condition occurs in epidemic proportions worldwide, and given the demographic trend in societal ageing, the prevalence of heart failure is only likely to increase. The marked upturn in international migration has generated other demographic changes in recent years, and it is evident that we are living and working in ever more ethnically and culturally diverse communities. Professionals treating those with heart failure are now dealing with a much more culturally disparate clinical cohort. Given that the heart failure disease trajectory is unique to each individual, these clinicians need to ensure that their proposed treatment options and responses to the inevitable crises intrinsic to this condition are in keeping with the culturally determined values, preferences, and worldviews of these patients and their families. In this narrative review, we describe the importance of cultural awareness across a range of themes relevant to heart failure management and emphasize the centrality of cultural competence as the basis of appropriate care provision.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), 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, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA 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 global data, 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.

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

BACKGROUND

African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans.

METHODS

Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation.

RESULTS

We observed genome-wide significant (P-value < 5.0E-8) SNPs associations near AADACL2 and miRNA (MIR5186) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA (MIR4458) gene in chromosome 5 were also associated with stroke (P-value < 1.0E-6). The putative genes near AADACL2, MIR5186, and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 (P-value < 1.0E-6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) (P-value < 1.0E-6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping.

CONCLUSIONS

Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke's risk prediction and development of new targeted interventions to prevent or treat stroke.

Challenges of Health Data Use in Multidisciplinary Chronic Disease Care: Perspective from Heart Failure Care

The healthcare sector generates approximately 30% of all the world's data volume, mostly for record keeping, compliance and regulatory requirements, and patient care. Healthcare data often exist in silos or on different systems and platforms due to decentralised storage and data protection laws, limiting accessibility for health service research. Thus, both the lack of access to data and more importantly the inability to control data quality and explore post-trial (phase IV) data or data with translational relevance have an impact on optimising care and research of congestive heart failure (CHF). We highlight that for some diseases, such as CHF, generating non-traditional data has significant importance, but is hindered by the logistics of accessing chronic disease data from separate health silos and by various levels of data quality. Modern multidisciplinary healthcare management of cardiovascular diseases-especially when spanning across community hubs to tertiary healthcare centres-increases the complexities involved between data privacy and access to data for healthcare and health service research. We call for an increased ability to leverage health data across systems, devices, and countries.

The H2Bub1-deposition complex is required for human and mouse cardiogenesis

De novo variants affecting monoubiquitylation of histone H2B (H2Bub1) are enriched in human congenital heart disease. H2Bub1 is required in stem cell differentiation, cilia function, post-natal cardiomyocyte maturation and transcriptional elongation. However, how H2Bub1 affects cardiogenesis is unknown. We show that the H2Bub1-deposition complex (RNF20-RNF40-UBE2B) is required for mouse cardiogenesis and for differentiation of human iPSCs into cardiomyocytes. Mice with cardiac-specific Rnf20 deletion are embryonic lethal and have abnormal myocardium. We then analyzed H2Bub1 marks during differentiation of human iPSCs into cardiomyocytes. H2Bub1 is erased from most genes at the transition from cardiac mesoderm to cardiac progenitor cells but is preserved on a subset of long cardiac-specific genes. When H2Bub1 is reduced in iPSC-derived cardiomyocytes, long cardiac-specific genes have fewer full-length transcripts. This correlates with H2Bub1 accumulation near the center of these genes. H2Bub1 accumulation near the center of tissue-specific genes was also observed in embryonic fibroblasts and fetal osteoblasts. In summary, we show that normal H2Bub1 distribution is required for cardiogenesis and cardiomyocyte differentiation, and suggest that H2Bub1 regulates tissue-specific gene expression by increasing the amount of full-length transcripts.

Cardiomyopathy in Asian Cohorts: Genetic and Epigenetic Insights

Previous studies on cardiomyopathies have been particularly valuable for clarifying pathological mechanisms in heart failure, an etiologically heterogeneous disease. In this review, we specifically focus on cardiomyopathies in Asia, where heart failure is particularly pertinent. There has been an increase in prevalence of cardiomyopathies in Asia, in sharp contrast with the decline observed in Western countries. Indeed, important disparities in cardiomyopathy incidence, clinical characteristics, and prognosis have been reported in Asian versus White cohorts. These have been accompanied by emerging descriptions of a distinct rare and common genetic basis for disease among Asian cardiomyopathy patients marked by an increased burden of variants with uncertain significance, reclassification of variants deemed pathogenic based on evidence from predominantly White cohorts, and the discovery of Asian-specific cardiomyopathy-associated loci with underappreciated pathogenicity under conventional classification criteria. Findings from epigenetic studies of heart failure, particularly DNA methylation studies, have complemented genetic findings in accounting for the phenotypic variability in cardiomyopathy. Though extremely limited, findings from Asian ancestry-focused DNA methylation studies of cardiomyopathy have shown potential to contribute to general understanding of cardiomyopathy pathophysiology by proposing disease and cause-relevant pathophysiological mechanisms. We discuss the value of multiomics study designs incorporating genetic, methylation, and transcriptomic information for future DNA methylation studies in Asian cardiomyopathy cohorts to yield Asian ancestry-specific insights that will improve risk stratification in the Asian population.

A Bayesian genomic selection approach incorporating prior feature ordering and population structures with application to coronary artery disease

Coronary artery disease is one of the most common types of cardiovascular disease. Death from coronary heart disease is influenced by genetic factors in both women and men. In this article, we propose a novel Bayesian variable selection framework for the identification of important genetic variants associated with coronary artery disease disease status. Instead of treating each feature independently as in conventional Bayesian variable selection methods, we propose an innovative prior for the inclusion probabilities of genetic variants that accounts for their ordering structure. We assume that neighboring variants are more likely to be selected together as they tend to be highly correlated and have similar biological functions. Additionally, we propose to group participating subjects based on underlying population structure and fit separate regressions, so that the regression coefficients can better reflect different disease risks in different population groups. Our approach borrows strength across regression models through an innovative prior inspired by the Markov random fields. The proposed framework can improve variable selection and prediction performances as demonstrated in the simulation studies. We also apply the proposed framework to the CATHeterization GENetics data with binary Coronary artery disease disease status.

CCND1 Overexpression in Idiopathic Dilated Cardiomyopathy: A Promising Biomarker?

Cardiomyopathy, a disorder of electrical or heart muscle function, represents a type of cardiac muscle failure and culminates in severe heart conditions. The prevalence of dilated cardiomyopathy (DCM) is higher than that of other types (hypertrophic cardiomyopathy and restrictive cardiomyopathy) and causes many deaths. Idiopathic dilated cardiomyopathy (IDCM) is a type of DCM with an unknown underlying cause. This study aims to analyze the gene network of IDCM patients to identify disease biomarkers. Data were first extracted from the Gene Expression Omnibus (GEO) dataset and normalized based on the RMA algorithm (Bioconductor package), and differentially expressed genes were identified. The gene network was mapped on the STRING website, and the data were transferred to Cytoscape software to determine the top 100 genes. In the following, several genes, including VEGFA, IGF1, APP, STAT1, CCND1, MYH10, and MYH11, were selected for clinical studies. Peripheral blood samples were taken from 14 identified IDCM patients and 14 controls. The RT-PCR results revealed no significant differences in the expression of the genes APP, MYH10, and MYH11 between the two groups. By contrast, the STAT1, IGF1, CCND1, and VEGFA genes were overexpressed in patients more than in controls. The highest expression was found for VEGFA, followed by CCND1 (p < 0.001). Overexpression of these genes may contribute to disease progression in patients with IDCM. However, more patients and genes need to be analyzed in order to achieve more robust results.

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.

Cardiac micro-RNA and transcriptomic profile of a novel swine model of chronic kidney disease and left ventricular diastolic dysfunction

Chronic kidney disease (CKD) is an independent risk factor for the development of heart failure, but the underlying mechanisms remain unknown. Using a novel translational swine model of CKD and cardiac dysfunction, we hypothesize that CKD alters the cardiac miRNA and transcriptomic profile that associate with cardiac remodeling and metabolic processes implicated in the development of left ventricular diastolic dysfunction (CKD-LVDD). CKD-LVDD and normal control pigs (n = 6 each) were studied for 14 wk. Renal and cardiac hemodynamics were quantified by multidetector CT and echocardiography. In randomly selected pigs (n = 3/group), cardiac miRNA- and mRNA-sequencing (seq) was performed, validated (qPCR), and followed by confirmatory ex vivo studies. Differential expression analysis identified nine miRNAs and 125 mRNAs upregulated and 17 miRNAs and 172 mRNAs downregulated [fold-change ≥ 2, and false discovery rate (FDR) ≤ 0.05] in CKD-LVDD versus normal controls. Integrated miRNA-/mRNA-seq analysis identified 71 overlappings downregulated mRNA targets of miRNAs upregulated, and 39 overlappings upregulated mRNA targets of miRNAs downregulated in CKD-LVDD versus controls. Functional analysis showed that these genes were primarily implicated in processes associated with cardiac remodeling, including ubiquitination, ATP and fatty acid synthesis, and extracellular matrix remodeling. In agreement, hearts of CKD-LVDD pigs exhibited abnormal diastolic relaxation, mitochondrial injury, moderate LV fibrosis, and myocardial lipid accumulation. Our work comprehensively characterizes the cardiac micro-RNA and transcriptomic profile of a translational model of CKD-LVDD. Our data may set the foundation for new targeted studies to further elucidate LVDD pathophysiology and assist to develop therapeutic interventions.NEW & NOTEWORTHY Chronic kidney disease (CKD) is a progressive disorder in which more than 50% of deaths are attributed to cardiovascular disease. Using a swine model of CKD that develops left ventricular dysfunction (CKD-LVDD), we characterize the cardiac micro-RNA and transcriptomic profile, identifying dysregulated genes associated with cardiac remodeling and fatty acid metabolism that might be post-transcriptionally regulated early in the disease. These findings pinpointed pathological pathways that may open new avenues toward therapeutic research to reduce cardiovascular morbidity in CKD.

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 AI in Characterizing the DCM Phenotype

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

A Role for Genetics in Racial Disparities of Therapy-Related Cardiomyopathy

Cardiomyopathy is a significant source of morbidity and early mortality among survivors of childhood cancer, and may disproportionately affect minorities. However, there have been few studies evaluating these outcomes among racially and ethnically diverse survivor populations. A study by Sapkota and colleagues systematically characterizes disparities in the incidence of treatment-associated cardiomyopathy on the basis of genetic ancestry and investigates genetic variants responsible for this inequality. The noteworthy findings include a disproportionate risk of cardiomyopathy among African-American childhood cancer survivors and the identification of inherited genetic variants, which may confer increased susceptibility to cardiomyopathy among these individuals. Although larger studies are needed to confirm these findings, incorporating this knowledge into clinical risk profiles may help focus attention on patient populations who are particularly vulnerable to adverse cardiovascular outcomes and most likely to benefit from preventive strategies.See related article by Sapkota et al., p. 2556.

Genome-wide association analysis in dilated cardiomyopathy reveals two new players in systolic heart failure on chromosomes 3p25.1 and 22q11.23

AIMS

Our objective was to better understand the genetic bases of dilated cardiomyopathy (DCM), a leading cause of systolic heart failure.

METHODS AND RESULTS

We conducted the largest genome-wide association study performed so far in DCM, with 2719 cases and 4440 controls in the discovery population. We identified and replicated two new DCM-associated loci on chromosome 3p25.1 [lead single-nucleotide polymorphism (SNP) rs62232870, P = 8.7 × 10-11 and 7.7 × 10-4 in the discovery and replication steps, respectively] and chromosome 22q11.23 (lead SNP rs7284877, P = 3.3 × 10-8 and 1.4 × 10-3 in the discovery and replication steps, respectively), while confirming two previously identified DCM loci on chromosomes 10 and 1, BAG3 and HSPB7. A genetic risk score constructed from the number of risk alleles at these four DCM loci revealed a 3-fold increased risk of DCM for individuals with 8 risk alleles compared to individuals with 5 risk alleles (median of the referral population). In silico annotation and functional 4C-sequencing analyses on iPSC-derived cardiomyocytes identify SLC6A6 as the most likely DCM gene at the 3p25.1 locus. This gene encodes a taurine transporter whose involvement in myocardial dysfunction and DCM is supported by numerous observations in humans and animals. At the 22q11.23 locus, in silico and data mining annotations, and to a lesser extent functional analysis, strongly suggest SMARCB1 as the candidate culprit gene.

CONCLUSION

This study provides a better understanding of the genetic architecture of DCM and sheds light on novel biological pathways underlying heart failure.

The Complex and Diverse Genetic Architecture of Dilated Cardiomyopathy

Our insight into the diverse and complex nature of dilated cardiomyopathy (DCM) genetic architecture continues to evolve rapidly. The foundations of DCM genetics rest on marked locus and allelic heterogeneity. While DCM exhibits a Mendelian, monogenic architecture in some families, preliminary data from our studies and others suggests that at least 20% to 30% of DCM may have an oligogenic basis, meaning that multiple rare variants from different, unlinked loci, determine the DCM phenotype. It is also likely that low-frequency and common genetic variation contribute to DCM complexity, but neither has been examined within a rare variant context. Other types of genetic variation are also likely relevant for DCM, along with gene-by-environment interaction, now established for alcohol- and chemotherapy-related DCM. Collectively, this suggests that the genetic architecture of DCM is broader in scope and more complex than previously understood. All of this elevates the impact of DCM genetics research, as greater insight into the causes of DCM can lead to interventions to mitigate or even prevent it and thus avoid the morbid and mortal scourge of human heart failure.

The impact of non-additive genetic associations on age-related complex diseases

Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.

Heart Disease and Stroke Statistics-2021 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 2021 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, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 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, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Genetic Variants Associated with Therapy-Related Cardiomyopathy among Childhood Cancer Survivors of African Ancestry

Cardiomyopathy occurs at significantly higher rates in survivors of childhood cancer than the general population, but few studies have evaluated racial or ethnic disparities, and none have assessed potential genetic factors contributing to this outcome. In this study, childhood cancer survivors of African ancestry exposed to cardiotoxic therapies (anthracyclines and/or heart radiotherapy; n = 246) were compared with cardiotoxic-exposed survivors of European ancestry (n = 1,645) in the St. Jude Lifetime Cohort. Genetic variants were examined using whole-genome sequencing data among survivors of African ancestry, first based on ejection fraction (EF) as a continuous outcome, followed by clinical history of cardiomyopathy. Survivors of African ancestry showed 1.53- and 2.47-fold risks of CTCAE grade 2-4 and grade 3-4 cardiomyopathy than survivors of European ancestry. A novel locus at 1p13.2 showed significant association with EF (rs6689879*C: EF reduction = 4.2%; P = 2.8 × 10^-8) in 246 survivors of African ancestry, which was successfully replicated in 1,645 survivors of European ancestry but with attenuated magnitude (EF reduction = 0.4%; P = 0.042). In survivors of African ancestry, rs6689879*C showed a 5.43-fold risk of cardiomyopathy and 1.31-fold risk in those of European ancestry. Among survivors of African ancestry with rs6689879*C and CTCAE grade 2-4 cardiomyopathy, the PHTF1 promoter region was hypomethylated. Similar results were observed in survivors of European ancestry, albeit with reduced magnitudes of hypomethylation among those with rs6689879*C and CTCAE grade 2-4 cardiomyopathy. PHTF1 was upregulated in human-induced pluripotent stem cell-derived cardiomyocytes from patients with doxorubicin-induced cardiomyopathy. These findings have potential implications for long-term cardiac surveillance and up-front cancer care for patients of African ancestry. SIGNIFICANCE: Childhood cancer survivors of African ancestry are at higher risk of cardiomyopathy than those of European ancestry, and a novel locus at 1p13.2 is associated with therapy-related cardiomyopathy specifically in African-American survivors.See related commentary by Brown and Richard, p. 2272.

Lymphangiogenic therapy prevents cardiac dysfunction by ameliorating inflammation and hypertension

The lymphatic vasculature is involved in the pathogenesis of acute cardiac injuries, but little is known about its role in chronic cardiac dysfunction. Here, we demonstrate that angiotensin II infusion induced cardiac inflammation and fibrosis at 1 week and caused cardiac dysfunction and impaired lymphatic transport at 6 weeks in mice, while co-administration of VEGFCc156s improved these parameters. To identify novel mechanisms underlying this protection, RNA sequencing analysis in distinct cell populations revealed that VEGFCc156s specifically modulated angiotensin II-induced inflammatory responses in cardiac and peripheral lymphatic endothelial cells. Furthermore, telemetry studies showed that while angiotensin II increased blood pressure acutely in all animals, VEGFCc156s-treated animals displayed a delayed systemic reduction in blood pressure independent of alterations in angiotensin II-mediated aortic stiffness. Overall, these results demonstrate that VEGFCc156s had a multifaceted therapeutic effect to prevent angiotensin II-induced cardiac dysfunction by improving cardiac lymphatic function, alleviating fibrosis and inflammation, and ameliorating hypertension.

Clinical Implications of the Genetic Architecture of Dilated Cardiomyopathy

PURPOSE OF REVIEW

Dilated cardiomyopathy (DCM) frequently involves an underlying genetic etiology, but the clinical approach for genetic diagnosis and application of results in clinical practice can be complex.

RECENT FINDINGS

International sequence databases described the landscape of genetic variability across populations, which informed guidelines for the interpretation of DCM gene variants. New evidence indicates that loss-of-function mutations in filamin C (FLNC) contribute to DCM and portend high risk of ventricular arrhythmia. A clinical framework aids in referring patients for DCM genetic testing and applying results to patient care. Results of genetic testing can change medical management, particularly in a subset of genes that increase risk for life-threatening ventricular arrhythmias, and can influence decisions for defibrillator therapy. Clinical screening and cascade genetic testing of family members should be diligently pursued to identify those at risk of developing DCM.

Understanding the Complexity of Heart Failure Risk and Treatment in Black Patients

Although care of patients with heart failure (HF) has improved in the past decade, important disparities in HF outcomes persist based on race/ethnicity. Age-adjusted HF-related cardiovascular disease death rates are higher for Black patients, particularly among young Black men and women whose rates of death are 2.6- and 2.97-fold higher, respectively, than White men and women. Similarly, the rate of HF hospitalization for Black men and women is nearly 2.5-fold higher when compared with Whites, with costs that are significantly higher in the first year after HF hospitalization. While the relative rate of HF hospitalization has improved for other race/ethnic minorities, the disparity in HF hospitalization between Black and White patients has not decreased during the last decade. Although access to care and socioeconomic status have been traditional explanations for the observed racial disparities in HF outcomes, contemporary data suggest that novel factors including genetic susceptibility as well as social determinants of health and implicit bias may play a larger role in health outcomes than previously appreciated. The purpose of this review is to describe the complex interplay of factors that influence racial disparities in HF incidence, prevalence, and disease severity, with a highlight on evolving knowledge that will impact the clinical care and address future research needs to improve HF disparities in Blacks.

The regulatory genome constrains protein sequence evolution: implications for the search for disease-associated genes

The development of explanatory models of protein sequence evolution has broad implications for our understanding of cellular biology, population history, and disease etiology. Here we analyze the GTEx transcriptome resource to quantify the effect of the transcriptome on protein sequence evolution in a multi-tissue framework. We find substantial variation among the central nervous system tissues in the effect of expression variance on evolutionary rate, with highly variable genes in the cortex showing significantly greater purifying selection than highly variable genes in subcortical regions (Mann-Whitney U p = 1.4 × 10^-4). The remaining tissues cluster in observed expression correlation with evolutionary rate, enabling evolutionary analysis of genes in diverse physiological systems, including digestive, reproductive, and immune systems. Importantly, the tissue in which a gene attains its maximum expression variance significantly varies (p = 5.55 × 10^-284) with evolutionary rate, suggesting a tissue-anchored model of protein sequence evolution. Using a large-scale reference resource, we show that the tissue-anchored model provides a transcriptome-based approach to predicting the primary affected tissue of developmental disorders. Using gradient boosted regression trees to model evolutionary rate under a range of model parameters, selected features explain up to 62% of the variation in evolutionary rate and provide additional support for the tissue model. Finally, we investigate several methodological implications, including the importance of evolutionary-rate-aware gene expression imputation models using genetic data for improved search for disease-associated genes in transcriptome-wide association studies. Collectively, this study presents a comprehensive transcriptome-based analysis of a range of factors that may constrain molecular evolution and proposes a novel framework for the study of gene function and disease mechanism.

The contribution of non-coding regulatory elements to cardiovascular disease

Cardiovascular disease collectively accounts for a quarter of deaths worldwide. Genome-wide association studies across a range of cardiovascular traits and pathologies have highlighted the prevalence of common non-coding genetic variants within candidate loci. Here, we review genetic, epigenomic and molecular approaches to investigate the contribution of non-coding regulatory elements in cardiovascular biology. We then discuss recent insights on the emerging role of non-coding variation in predisposition to cardiovascular disease, with a focus on novel mechanistic examples from functional genomics studies. Lastly, we consider the clinical significance of these findings at present, and some of the current challenges facing the field.

Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports on 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 2020 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, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.

RESULTS

Each of the 26 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, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Impact of copy number variation on human neurocognitive deficits and congenital heart defects: A systematic review

Copy number variant (CNV) syndromes are often associated with both neurocognitive deficits (NCDs) and congenital heart defects (CHDs). Children and adults with cardiac developmental defects likely to have NCDs leading to increased risk of hospitalisation and reduced level of independence. To date, the association between these two phenotypes have not been explored in relation to CNV syndromes. In order to address this question, we systematically reviewed the prevalence of CHDs in a range of CNV syndromes associated with NCDs. A meta-analysis showed a relationship with the size of CNV and its association with both NCDs and CHDs, and also inheritance pattern. To our knowledge, this is the first review to establish association between NCD and CHDs in CNV patients, specifically in relation to the severity of NCD. Importantly, we also found specific types of CHDs were associated with severe neurocognitive deficits. Finally, we discuss the implications of these results for patients in the clinical setting which warrants further exploration of this association in order to lead an improvement in the quality of patient's life.

Genome-wide linkage analysis of carotid artery traits in exceptionally long-lived families

BACKGROUND AND AIMS

Atherosclerosis develops with age and is partially controlled by genetics. Research to date has identified common variants with small effects on atherosclerosis related traits. We aimed to use family-based genome-wide linkage analysis to identify chromosomal regions potentially harboring rare variants with larger effects for atherosclerosis related traits.

METHODS

Participants included 2205 individuals from the Long Life Family Study (LLFS), which recruited families with exceptional longevity from Boston, New York, Pittsburgh, and Denmark. Participants underwent B-mode ultrasonography of the carotid arteries to measure intima-media thickness (IMT), inter-adventitial diameter (IAD), and plaque presence and severity. We conducted residual heritability and genome-wide linkage analyses adjusted for age, age², sex, and field center using pedigree-based maximum-likelihood methods in SOLAR.

RESULTS

All carotid traits were significantly heritable with a range of 0.68 for IAD to 0.38 for IMT. We identified three chromosomal regions with linkage to IAD (3q13; max LOD 5.3), plaque severity (17q22-q23, max LOD 3.2), and plaque presence (17q24, max LOD 3.1). No common allelic variants within these linkage peaks were associated with the carotid artery traits.

CONCLUSIONS

We identified three chromosomal regions with evidence of linkage to carotid artery diameter and atherosclerotic plaque in exceptionally long-lived families. Since common allelic variants within our linkage peaks did not account for our findings, future follow-up resequencing of these regions in LLFS families should help advance our understanding of atherosclerosis, CVD, and healthy vascular aging.