The genetics of congestive heart failure

Clinical impact of echocardiography parameters and molecular biomarkers in heart failure: Correlation of ACE2 and MCP-1 polymorphisms with echocardiography parameters: A comparative study

Heart failure is still the leading cause of hospitalization in patients over 65 years of age and is defined as a multifactorial pathology which involves environmental factors and also genetic predispositions. The aim of the present study was to evaluate a possible correlation between single nucleotide polymorphisms (SNPs) of angiotensin converting enzyme 2 (ACE2) and monocyte chemoattractant protein-1 (MCP-1) genes and cardiac remodeling in Caucasian patients diagnosed with heart failure. Our comparative translational research study included 116 patients diagnosed with heart failure and was carried out in Cluj-Napoca, Romania between September 2017 and March 2019. Three SNPs, namely rs4646156, rs4646174 and rs1024611, were genotyped using a Taqman real-time PCR technique. Our results showed that carriers of the AA genotype for ACE2 rs4646156 had a significant dilatation of the left ventricle (LV) with signs of LV hypertrophy (LVH), while TT carriers had a significant left atrial dilatation. For ACE2 rs4646174, homozygotes for the C allele presented a dilated LV with signs of LVH with statistical significance and had a tendency towards a lower ejection fraction. MCP-1 rs1024611 AA variant carriers had a significant LVH in the dominant model. In conclusion, our study showed a strong association between echocardiographic parameters of cardiac remodeling and SNPs rs4646156, rs4646174 of ACE2 and rs1024611 of MCP-1.

DNA methylation reprograms cardiac metabolic gene expression in end-stage human heart failure

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide. As a multifactorial syndrome with unpredictable clinical outcomes, identifying the common molecular underpinnings that drive HF pathogenesis remains a major focus of investigation. Disruption of cardiac gene expression has been shown to mediate a common final cascade of pathological hallmarks wherein the heart reactivates numerous developmental pathways. Although the central regulatory mechanisms that drive this cardiac transcriptional reprogramming remain unknown, epigenetic contributions are likely. In the current study, we examined whether the epigenome, specifically DNA methylation, is reprogrammed in HF to potentiate a pathological shift in cardiac gene expression. To accomplish this, we used paired-end whole genome bisulfite sequencing and next-generation RNA sequencing of left ventricle tissue obtained from seven patients with end-stage HF and three nonfailing donor hearts. We found that differential methylation was localized to promoter-associated cytosine-phosphate-guanine islands, which are established regulatory regions of downstream genes. Hypermethylated promoters were associated with genes involved in oxidative metabolism, whereas promoter hypomethylation enriched glycolytic pathways. Overexpression of plasmid-derived DNA methyltransferase 3A in vitro was sufficient to lower the expression of numerous oxidative metabolic genes in H9c2 rat cardiomyoblasts, further supporting the importance of epigenetic factors in the regulation of cardiac metabolism. Last, we identified binding-site competition via hypermethylation of the nuclear respiratory factor 1 (NRF1) motif, an established upstream regulator of mitochondrial biogenesis. These preliminary observations are the first to uncover an etiology-independent shift in cardiac DNA methylation that corresponds with altered metabolic gene expression in HF.NEW & NOTEWORTHY The failing heart undergoes profound metabolic changes because of alterations in cardiac gene expression, reactivating glycolytic genes and suppressing oxidative metabolic genes. In the current study, we discover that alterations to cardiac DNA methylation encode this fetal-like metabolic gene reprogramming. We also identify novel epigenetic interference of nuclear respiratory factor 1 via hypermethylation of its downstream promoter targets, further supporting a novel contribution of DNA methylation in the metabolic remodeling of heart failure.

A Multi-Trait Approach Identified Genetic Variants Including a Rare Mutation in RGS3 with Impact on Abnormalities of Cardiac Structure/Function

Heart failure is a major cause for premature death. Given the heterogeneity of the heart failure syndrome, identifying genetic determinants of cardiac function and structure may provide greater insights into heart failure. Despite progress in understanding the genetic basis of heart failure through genome wide association studies, the heritability of heart failure is not well understood. Gaining further insights into mechanisms that contribute to heart failure requires systematic approaches that go beyond single trait analysis. We integrated a Bayesian multi-trait approach and a Bayesian networks for the analysis of 10 correlated traits of cardiac structure and function measured across 3387 individuals with whole exome sequence data. While using single-trait based approaches did not find any significant genetic variant, applying the integrative Bayesian multi-trait approach, we identified 3 novel variants located in genes, RGS3, CHD3, and MRPL38 with significant impact on the cardiac traits such as left ventricular volume index, parasternal long axis interventricular septum thickness, and mean left ventricular wall thickness. Among these, the rare variant NC_000009.11:g.116346115C > A (rs144636307) in RGS3 showed pleiotropic effect on left ventricular mass index, left ventricular volume index and maximal left atrial anterior-posterior diameter while RGS3 can inhibit TGF-beta signaling associated with left ventricle dilation and systolic dysfunction.

Genetics and genomics of dilated cardiomyopathy and systolic heart failure

Heart failure is a major health burden, affecting 40 million people globally. One of the main causes of systolic heart failure is dilated cardiomyopathy (DCM), the leading global indication for heart transplantation. Our understanding of the genetic basis of both DCM and systolic heart failure has improved in recent years with the application of next-generation sequencing and genome-wide association studies (GWAS). This has enabled rapid sequencing at scale, leading to the discovery of many novel rare variants in DCM and of common variants in both systolic heart failure and DCM. Identifying rare and common genetic variants contributing to systolic heart failure has been challenging given its diverse and multiple etiologies. DCM, however, although rarer, is a reasonably specific and well-defined condition, leading to the identification of many rare genetic variants. Truncating variants in titin represent the single largest genetic cause of DCM. Here, we review the progress and challenges in the detection of rare and common variants in DCM and systolic heart failure, and the particular challenges in accurate and informed variant interpretation, and in understanding the effects of these variants. We also discuss how our increasing genetic knowledge is changing clinical management. Harnessing genetic data and translating it to improve risk stratification and the development of novel therapeutics represents a major challenge and unmet critical need for patients with heart failure and their families.

Decoding the complex genetic causes of heart diseases using systems biology

The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene-gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode ( http://CardiacCode.victorchang.edu.au/ ). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.