Genomic enhancers in cardiac development and disease

Active enhancers: recent research advances and insights into disease

Precise regulation of gene expression is crucial to development. Enhancers, the core of gene regulation, determine the spatiotemporal pattern of gene transcription. Since many disease-associated mutations are characterized in enhancers, the research on enhancer will provide clues to precise medicine. Rapid advances in high-throughput sequencing technology facilitate the characterization of enhancers at genome wide, but understanding the functional mechanisms of enhancers remains challenging. Herein, we provide a panorama of enhancer characteristics, including epigenetic modifications, enhancer transcripts, and enhancer-promoter interaction patterns. Furthermore, we outline the applications of high-throughput sequencing technology and functional genomics methods in enhancer research. Finally, we discuss the role of enhancers in human disease and their potential as targets for disease prevention and treatment strategies.

SCAR-6 elncRNA locus epigenetically regulates PROZ and modulates coagulation and vascular function

In this study, we characterize a novel lncRNA-producing gene locus that we name Syntenic Cardiovascular Conserved Region-Associated lncRNA-6 (scar-6) and functionally validate its role in coagulation and cardiovascular function. A 12-bp deletion of the scar-6 locus in zebrafish (scar-6gib007Δ12/Δ12) results in cranial hemorrhage and vascular permeability. Overexpression, knockdown and rescue with the scar-6 lncRNA modulates hemostasis in zebrafish. Molecular investigation reveals that the scar-6 lncRNA acts as an enhancer lncRNA (elncRNA), and controls the expression of prozb, an inhibitor of factor Xa, through an enhancer element in the scar-6 locus. The scar-6 locus suppresses loop formation between prozb and scar-6 sequences, which might be facilitated by the methylation of CpG islands via the prdm14-PRC2 complex whose binding to the locus might be stabilized by the scar-6 elncRNA transcript. Binding of prdm14 to the scar-6 locus is impaired in scar-6gib007Δ12/Δ12 zebrafish. Finally, activation of the PAR2 receptor in scar-6gib007Δ12/Δ12 zebrafish triggers NF-κB-mediated endothelial cell activation, leading to vascular dysfunction and hemorrhage. We present evidence that the scar-6 locus plays a role in regulating the expression of the coagulation cascade gene prozb and maintains vascular homeostasis.

Cardiac Aging Is Promoted by Pseudohypoxia Increasing p300-Induced Glycolysis

BACKGROUND

Heart failure is typical in the elderly. Metabolic remodeling of cardiomyocytes underlies inexorable deterioration of cardiac function with aging: glycolysis increases at the expense of oxidative phosphorylation, causing an energy deficit contributing to impaired contractility. Better understanding of the mechanisms of this metabolic switching could be critical for reversing the condition.

METHODS

To investigate the role of 3 histone modifications (H3K27ac, H3K27me3, and H3K4me1) in the metabolic remodeling occurring in the aging heart, we cross-compared epigenomic, transcriptomic, and metabolomic data from mice of different ages. In addition, the role of the transcriptional coactivator p300 (E1A-associated binding protein p300)/CBP (CREB binding protein) in cardiac aging was investigated using a specific inhibitor of this histone acetyltransferase enzyme.

RESULTS

We report a set of species-conserved enhancers associated with transcriptional changes underlying age-related metabolic remodeling in cardiomyocytes. Activation of the enhancer region of Hk2-a key glycolysis pathway gene-was fostered in old age-onset mouse heart by pseudohypoxia, wherein hypoxia-related genes are expressed under normal O2 levels, via increased activity of P300/CBP. Pharmacological inhibition of this transcriptional coactivator before the onset of cardiac aging led to a more aerobic, less glycolytic, metabolic state, improved heart contractility, and overall blunting of cardiac decline.

CONCLUSIONS

Taken together, our results suggest how epigenetic dysregulation of glycolysis pathway enhancers could potentially be targeted to treat heart failure in the elderly.

Genome-wide polygenic risk scores for hypertensive disease during pregnancy can also predict the risk for long-term cardiovascular disease

BACKGROUND

Hypertensive disorders during pregnancy are associated with the risk of long-term cardiovascular disease after pregnancy, but it has not yet been determined whether genetic predisposition for hypertensive disorders during pregnancy can predict the risk for long-term cardiovascular disease.

OBJECTIVE

This study aimed to evaluate the risk for long-term atherosclerotic cardiovascular disease according to polygenic risk scores for hypertensive disorders during pregnancy.

STUDY DESIGN

Among UK Biobank participants, we included European-descent women (n=164,575) with at least 1 live birth. Participants were divided according to genetic risk categorized by polygenic risk scores for hypertensive disorders during pregnancy (low risk, score ≤25th percentile; medium risk, score 25th∼75th percentile; high risk, score >75th percentile), and were evaluated for incident atherosclerotic cardiovascular disease, defined as the new occurrence of one of the following: coronary artery disease, myocardial infarction, ischemic stroke, or peripheral artery disease.

RESULTS

Among the study population, 2427 (1.5%) had a history of hypertensive disorders during pregnancy, and 8942 (5.6%) developed incident atherosclerotic cardiovascular disease after enrollment. Women with high genetic risk for hypertensive disorders during pregnancy had a higher prevalence of hypertension at enrollment. After enrollment, women with high genetic risk for hypertensive disorders during pregnancy had an increased risk for incident atherosclerotic cardiovascular disease, including coronary artery disease, myocardial infarction, and peripheral artery disease, compared with those with low genetic risk, even after adjustment for history of hypertensive disorders during pregnancy.

CONCLUSION

High genetic risk for hypertensive disorders during pregnancy was associated with increased risk for atherosclerotic cardiovascular disease. This study provides evidence on the informative value of polygenic risk scores for hypertensive disorders during pregnancy in prediction of long-term cardiovascular outcomes later in life.

Proximity-inducing modalities: the past, present, and future

Living systems use proximity to regulate biochemical processes. Inspired by this phenomenon, bifunctional modalities that induce proximity have been developed to redirect cellular processes. An emerging example of this class is molecules that induce ubiquitin-dependent proteasomal degradation of a protein of interest, and their initial development sparked a flurry of discovery for other bifunctional modalities. Recent advances in this area include modalities that can change protein phosphorylation, glycosylation, and acetylation states, modulate gene expression, and recruit components of the immune system. In this review, we highlight bifunctional modalities that perform functions other than degradation and have great potential to revolutionize disease treatment, while also serving as important tools in basic research to explore new aspects of biology.

A comparative study of model-centric and data-centric approaches in the development of cardiovascular disease risk prediction models in the UK Biobank

Aims

A diverse set of factors influence cardiovascular diseases (CVDs), but a systematic investigation of the interplay between these determinants and the contribution of each to CVD incidence prediction is largely missing from the literature. In this study, we leverage one of the most comprehensive biobanks worldwide, the UK Biobank, to investigate the contribution of different risk factor categories to more accurate incidence predictions in the overall population, by sex, different age groups, and ethnicity.

Methods and results

The investigated categories include the history of medical events, behavioural factors, socioeconomic factors, environmental factors, and measurements. We included data from a cohort of 405 257 participants aged 37-73 years and trained various machine learning and deep learning models on different subsets of risk factors to predict CVD incidence. Each of the models was trained on the complete set of predictors and subsets where each category was excluded. The results were benchmarked against QRISK3. The findings highlight that (i) leveraging a more comprehensive medical history substantially improves model performance. Relative to QRISK3, the best performing models improved the discrimination by 3.78% and improved precision by 1.80%. (ii) Both model- and data-centric approaches are necessary to improve predictive performance. The benefits of using a comprehensive history of diseases were far more pronounced when a neural sequence model, BEHRT, was used. This highlights the importance of the temporality of medical events that existing clinical risk models fail to capture. (iii) Besides the history of diseases, socioeconomic factors and measurements had small but significant independent contributions to the predictive performance.

Conclusion

These findings emphasize the need for considering broad determinants and novel modelling approaches to enhance CVD incidence prediction.

A comprehensive revisit of the machine-learning tools developed for the identification of enhancers in the human genome

Enhancers are non-coding DNA elements that play a crucial role in enhancing the transcription rate of a specific gene in the genome. Experiments for identifying enhancers can be restricted by their conditions and involve complicated, time-consuming, laborious, and costly steps. To overcome these challenges, computational platforms have been developed to complement experimental methods that enable high-throughput identification of enhancers. Over the last few years, the development of various enhancer computational tools has resulted in significant progress in predicting putative enhancers. Thus, researchers are now able to use a variety of strategies to enhance and advance enhancer study. In this review, an overview of machine learning (ML)-based prediction methods for enhancer identification and related databases has been provided. The existing enhancer-prediction methods have also been reviewed regarding their algorithms, feature selection processes, validation techniques, and software utility. In addition, the advantages and drawbacks of these ML approaches and guidelines for developing bioinformatic tools have been highlighted for a more efficient enhancer prediction. This review will serve as a useful resource for experimentalists in selecting the appropriate ML tool for their study, and for bioinformaticians in developing more accurate and advanced ML-based predictors.

The role of noncoding genetic variants in cardiomyopathy

Cardiomyopathies remain one of the leading causes of morbidity and mortality worldwide. Environmental risk factors and genetic predisposition account for most cardiomyopathy cases. As with all complex diseases, there are significant challenges in the interpretation of the molecular mechanisms underlying cardiomyopathy-associated genetic variants. Given the technical improvements and reduced costs of DNA sequence technologies, an increasing number of patients are now undergoing genetic testing, resulting in a continuously expanding list of novel mutations. However, many patients carry noncoding genetic variants, and although emerging evidence supports their contribution to cardiac disease, their role in cardiomyopathies remains largely understudied. In this review, we summarize published studies reporting on the association of different types of noncoding variants with various types of cardiomyopathies. We focus on variants within transcriptional enhancers, promoters, intronic sites, and untranslated regions that are likely associated with cardiac disease. Given the broad nature of this topic, we provide an overview of studies that are relatively recent and have sufficient evidence to support a significant degree of causality. We believe that more research with additional validation of noncoding genetic variants will provide further mechanistic insights on the development of cardiac disease, and noncoding variants will be increasingly incorporated in future genetic screening tests.

Cardiovascular utility of single cell RNA-Seq

PURPOSE OF REVIEW

Cardiovascular diseases remain the leading causes of morbidity and mortality globally. Single-cell RNA sequencing has the potential to improve diagnostics, risk stratification, and provide novel therapeutic targets that have the potential to improve patient outcomes.

RECENT FINDINGS

Here, we provide an overview of the basic processes underlying single-cell RNA sequencing, including library preparation, data processing, and downstream analyses. We briefly discuss how the technique has been adapted to related medical disciplines, including hematology and oncology, with short term translational impact. We discuss potential applications of this technology within cardiology as well as recent innovative research within the field. We also discuss future directions to translate this technology to other high impact clinical areas.

SUMMARY

The use of single-cell RNA sequencing technology has made significant advancements in the field of cardiology, with ongoing growth in terms of applications and uptake. Most of the current research has focused on structural or atherosclerotic heart disease. Future areas that stand to benefit from this technology include cardiac electrophysiology and cardio-oncology.

Insights into circular RNAs : Biogenesis, function and their regulatory roles in cardiovascular disease

As a distinctive member of the noncoding RNA family, circular RNAs (circRNAs) are generated from single-stranded, covalently closed structures and are ubiquitous in mammalian cells and tissues. Due to its atypical circular architecture, it was conventionally deemed insignificant dark matter for a prolonged duration. Nevertheless, studies conducted over the last decade have demonstrated that this abundant, structurally stable and tissue-specific RNA has been increasingly relevant in diverse diseases, including cancer, neurological disorders, diabetes mellitus and cardiovascular diseases (CVDs). Therefore, regulatory pathways controlled by circRNAs are widely involved in the occurrence and pathological processes of CVDs through their function as miRNA sponges, protein sponges and protein scaffolds. To better understand the role of circRNAs and their complex regulatory networks in CVDs, we summarize current knowledge of their biogenesis and function and the latest research on circRNAs in CVDs, with the hope of paving the way for the identification of promising biomarkers and therapeutic strategies for CVDs.

Single-cell transcriptomes in the heart: when every epigenome counts

The response of an organ to stimuli emerges from the actions of individual cells. Recent cardiac single-cell RNA-sequencing studies of development, injury, and reprogramming have uncovered heterogeneous populations even among previously well-defined cell types, raising questions about what level of experimental resolution corresponds to disease-relevant, tissue-level phenotypes. In this review, we explore the biological meaning behind this cellular heterogeneity by undertaking an exhaustive analysis of single-cell transcriptomics in the heart (including a comprehensive, annotated compendium of studies published to date) and evaluating new models for the cardiac function that have emerged from these studies (including discussion and schematics that depict new hypotheses in the field). We evaluate the evidence to support the biological actions of newly identified cell populations and debate questions related to the role of cell-to-cell variability in development and disease. Finally, we present emerging epigenomic approaches that, when combined with single-cell RNA-sequencing, can resolve basic mechanisms of gene regulation and variability in cell phenotype.

Genetic architecture in neonatal intensive care unit patients with congenital heart defects: a retrospective study from the China Neonatal Genomes Project

BACKGROUND

Congenital heart defects (CHDs) are the most common type of birth defects. The genetic aetiology of CHD is complex and incompletely understood. The overall distribution of genetic causes in patients with CHD from neonatal intensive care units (NICUs) needs to be studied.

METHODS

CHD cases were extracted from the China Neonatal Genomes Project (2016-2021). Next-generation sequencing results and medical records were retrospectively evaluated to note the frequency of genetic diagnosis and the respective patient outcomes.

RESULTS

In total, 1795 patients were included. The human phenotype ontology term of atrial septal defect, patent ductus arteriosus and ventricular septal defect account for a large portion of the CHD subtype. Co-occurring extracardiac anomalies were observed in 35.1% of patients. 269 of the cases received genetic diagnoses that could explain the phenotype of CHDs, including 172 copy number variations and 97 pathogenic variants. The detection rate of trio-whole-exome sequencing was higher than clinical exome sequencing (21.8% vs 14.5%, p<0.05). Further follow-up analysis showed the genetic diagnostic rate was higher in the deceased group than in the surviving group (29.0% vs 11.9%, p<0.05).

CONCLUSION

This is the largest cohort study to explore the genetic spectrum of patients with CHD in the NICU in China. Our findings may benefit future work on improving genetic screening and counselling for NICU patients with CHD.

Emerging epigenetic therapies of cardiac fibrosis and remodelling in heart failure: from basic mechanisms to early clinical development

Cardiovascular diseases and specifically heart failure (HF) impact global health and impose a significant economic burden on society. Despite current advances in standard of care, the risks for death and readmission of HF patients remain unacceptably high and new therapeutic strategies to limit HF progression are highly sought. In disease settings, persistent mechanical or neurohormonal stress to the myocardium triggers maladaptive cardiac remodelling, which alters cardiac function and structure at both the molecular and cellular levels. The progression and magnitude of maladaptive cardiac remodelling ultimately leads to the development of HF. Classical therapies for HF are largely protein-based and mostly are targeted to ameliorate the dysregulation of neuroendocrine pathways and halt adverse remodelling. More recently, investigation of novel molecular targets and the application of cellular therapies, epigenetic modifications, and regulatory RNAs has uncovered promising new avenues to address HF. In this review, we summarize the current knowledge on novel cellular and epigenetic therapies and focus on two non-coding RNA-based strategies that reached the phase of early clinical development to counteract cardiac remodelling and HF. The current status of the development of translating those novel therapies to clinical practice, limitations, and future perspectives are additionally discussed.

An atlas of transcribed human cardiac promoters and enhancers reveals an important role of regulatory elements in heart failure

A deeper knowledge of the dynamic transcriptional activity of promoters and enhancers is needed to improve mechanistic understanding of the pathogenesis of heart failure and heart diseases. In this study, we used cap analysis of gene expression (CAGE) to identify and quantify the activity of transcribed regulatory elements (TREs) in the four cardiac chambers of 21 healthy and ten failing adult human hearts. We identified 17,668 promoters and 14,920 enhancers associated with the expression of 14,519 genes. We showed how these regulatory elements are alternatively transcribed in different heart regions, in healthy versus failing hearts and in ischemic versus non-ischemic heart failure samples. Cardiac-disease-related single-nucleotide polymorphisms (SNPs) appeared to be enriched in TREs, potentially affecting the allele-specific transcription factor binding. To conclude, our open-source heart CAGE atlas will serve the cardiovascular community in improving the understanding of the role of the cardiac gene regulatory networks in cardiovascular disease and therapy.

RNA modifications in cardiovascular health and disease

RNA is not always a faithful copy of DNA. Advances in tools enabling the interrogation of the exact RNA sequence have permitted revision of how genetic information is transferred. We now know that RNA is a dynamic molecule, amenable to chemical modifications of its four canonical nucleotides by dedicated RNA-binding enzymes. The ever-expanding catalogue of identified RNA modifications in mammals has led to a burst of studies in the past 5 years that have explored the biological relevance of the RNA modifications, also known as epitranscriptome. These studies concluded that chemical modification of RNA nucleotides alters several properties of RNA molecules including sequence, secondary structure, RNA-protein interaction, localization and processing. Importantly, a plethora of cellular functions during development, homeostasis and disease are controlled by RNA modification enzymes. Understanding the regulatory interface between a single-nucleotide modification and cellular function will pave the way towards the development of novel diagnostic, prognostic and therapeutic tools for the management of diseases, including cardiovascular disease. In this Review, we use two well-studied and abundant RNA modifications - adenosine-to-inosine RNA editing and N⁶-methyladenosine RNA methylation - as examples on which to base the discussion about the current knowledge on installation or removal of RNA modifications, their effect on biological processes related to cardiovascular health and disease, and the potential for development and application of epitranscriptome-based prognostic, diagnostic and therapeutic tools for cardiovascular disease.