Inherited Cardiomyopathies and the Role of Mutations in Non-coding Regions of the Genome

Role of non-coding variants in cardiovascular disease

Cardiovascular diseases (CVDs) constitute one of the significant causes of death worldwide. Different pathological states are linked to CVDs, which despite interventions and treatments, still have poor prognoses. The genetic component, as a beneficial tool in the risk stratification of CVD development, plays a role in the pathogenesis of this group of diseases. The emergence of genome-wide association studies (GWAS) have led to the identification of non-coding parts associated with cardiovascular traits and disorders. Variants located in functional non-coding regions, including promoters/enhancers, introns, miRNAs and 5'/3' UTRs, account for 90% of all identified single-nucleotide polymorphisms associated with CVDs. Here, for the first time, we conducted a comprehensive review on the reported non-coding variants for different CVDs, including hypercholesterolemia, cardiomyopathies, congenital heart diseases, thoracic aortic aneurysms/dissections and coronary artery diseases. Additionally, we present the most commonly reported genes involved in each CVD. In total, 1469 non-coding variants constitute most reports on familial hypercholesterolemia, hypertrophic cardiomyopathy and dilated cardiomyopathy. The application and identification of non-coding variants are beneficial for the genetic diagnosis and better therapeutic management of CVDs.

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.

Understanding the molecular basis of cardiomyopathy

Inherited cardiomyopathies are a major cause of mortality and morbidity worldwide and can be caused by mutations in a wide range of proteins located in different cellular compartments. The present review is based on Dr. Ju Chen's 2021 Robert M. Berne Distinguished Lectureship of the American Physiological Society Cardiovascular Section, in which he provided an overview of the current knowledge on the cardiomyopathy-associated proteins that have been studied in his laboratory. The review provides a general summary of the proteins in different compartments of cardiomyocytes associated with cardiomyopathies, with specific focus on the proteins that have been studied in Dr. Chen's laboratory.

Multi-factor regulatory network and different clusters in hypertrophic obstructive cardiomyopathy

BACKGROUND

Practical biosignatures and thorough understanding of regulatory processes of hypertrophic obstructive cardiomyopathy (HOCM) are still lacking.

METHODS

Firstly, public data from GSE36961 and GSE89714 datasets of Gene Expression Omnibus (GEO), Gene database of NCBI (National Center of Biotechnology Information) and Online Mendelian Inheritance in Man (OMIM) database were merged into a candidate gene set of HOCM. Secondly, weighted gene co-expression network analysis (WGCNA) for the candidate gene set was carried out to determine premier co-expressed genes. Thirdly, significant regulators were found out by virtue of a multi-factor regulatory network of long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), microRNAs (miRNAs) and transcription factors (TFs) with molecule interreactions from starBase v2.0 database and TRRUST v2 database. Ultimately, HOCM unsupervised clustering and "tsne" dimensionality reduction was employed to gain hub genes, whose classification performance was evaluated by a multinomial model of lasso logistic regression analysis binded with receiver operating characteristic (ROC) curve.

RESULTS

Two HOCM remarkably-interrelated modules were from WGCNA, followed by the recognition of 32 crucial co-expressed genes. The multi-factor regulatory network disclosed 7 primary regulatory agents, containing lncRNAs (XIST, MALAT1, and H19), TFs (SPI1 and SP1) and miRNAs (hsa-miR-29b-39 and has-miR-29a-3p). Four clusters of HOCM and 4 hub genes (COMP, FMOD, AEBP1 and SULF1) significantly expressing in preceding four subtypes were obtained, while ROC curve demonstrated satisfactory performance of clustering and 4 genes.

CONCLUSIONS

Our consequences furnish valuable resource which may bring about prospective mechanistic and therapeutic anatomization in HOCM.

Prospects Of Non-Coding Elements In Genomic Dna Based Gene Therapy

Gene therapy has made significant development since the commencement of the first clinical trials a few decades ago and has remained a dynamic area of research regardless of obstacles such as immune response and insertional mutagenesis. Progression in various technologies like next-generation sequencing (NGS) and nanotechnology has established the importance of non-coding segments of a genome, thereby taking gene therapy to the next level. In this review, we have summarized the importance of non-coding elements, highlighting the advantages of using full-length genomic DNA loci (gDNA) compared to complementary DNA (cDNA) or minigene, currently used in gene therapy. The focus of this review is to provide an overview of the advances and the future of potential use of gDNA loci in gene therapy, expanding the therapeutic repertoire in molecular medicine.

Genetic Restrictive Cardiomyopathy: Causes and Consequences-An Integrative Approach

The sarcomere as the smallest contractile unit is prone to alterations in its functional, structural and associated proteins. Sarcomeric dysfunction leads to heart failure or cardiomyopathies like hypertrophic (HCM) or restrictive cardiomyopathy (RCM) etc. Genetic based RCM, a very rare but severe disease with a high mortality rate, might be induced by mutations in genes of non-sarcomeric, sarcomeric and sarcomere associated proteins. In this review, we discuss the functional effects in correlation to the phenotype and present an integrated model for the development of genetic RCM.

Role of Non-Coding Variants in Brugada Syndrome

Brugada syndrome (BrS) is an inherited electrical heart disease associated with a high risk of sudden cardiac death (SCD). The genetic characterization of BrS has always been challenging. Although several cardiac ion channel genes have been associated with BrS, SCN5A is the only gene that presents definitive evidence for causality to be used for clinical diagnosis of BrS. However, more than 65% of diagnosed cases cannot be explained by variants in SCN5A or other genes. Therefore, in an important number of BrS cases, the underlying mechanisms are still elusive. Common variants, mostly located in non-coding regions, have emerged as potential modulators of the disease by affecting different regulatory mechanisms, including transcription factors (TFs), three-dimensional organization of the genome, or non-coding RNAs (ncRNAs). These common variants have been hypothesized to modulate the interindividual susceptibility of the disease, which could explain incomplete penetrance of BrS observed within families. Altogether, the study of both common and rare variants in parallel is becoming increasingly important to better understand the genetic basis underlying BrS. In this review, we aim to describe the challenges of studying non-coding variants associated with disease, re-examine the studies that have linked non-coding variants with BrS, and provide further evidence for the relevance of regulatory elements in understanding this cardiac disorder.

MYBPC3 Haplotype Linked to Hypertrophic Cardiomyopathy in Rhesus Macaques (Macaca mulatta)

In humans, abnormal thickening of the left ventricle of the heart clinically defines hypertrophic cardiomyopathy (HCM), a common inherited cardiovascular disorder that can precede a sudden cardiac death event. The wide range of clinical presentations in HCM obscures genetic variants that may influence an individual's susceptibility to sudden cardiac death. Although exon sequencing of major sarcomere genes can be used to detect high-impact causal mutations, this strategy is successful in only half of patient cases. The incidence of left ventricular hypertrophy (LVH) in a managed research colony of rhesus macaques provides an excellent comparative model in which to explore the genomic etiology of severe HCM and sudden cardiac death. Because no rhesus HCM-associated mutations have been reported, we used a next-generation genotyping assay that targets 7 sarcomeric rhesus genes within 63 genomic sites that are orthologous to human genomic regions known to harbor HCM disease variants. Amplicon sequencing was performed on 52 macaques with confirmed LVH and 42 unrelated, unaffected animals representing both the Indian and Chinese rhesus macaque subspecies. Bias-reduced logistic regression uncovered a risk haplotype in the rhesus MYBPC3 gene, which is frequently disrupted in both human and feline HCM; this haplotype implicates an intronic variant strongly associated with disease in either homozygous or carrier form. Our results highlight that leveraging evolutionary genomic data provides a unique, practical strategy for minimizing population bias in complex disease studies.

Gene polymorphisms in calcium-calmodulin pathway: Focus on cardiovascular disease

Cardiovascular disease is the leading cause of death in industrialized countries and affects an increasing number of people. Several risk factors play an important role in the etiology of this disease, such as an unhealthy lifestyle. It is increasingly clear that genetic factors influencing the molecular basis of excitation-contraction mechanisms in the heart could contribute to modify the individual's risk. Thanks to the progress that has been made in understanding calcium signaling in the heart, it is assumed that calmodulin can play a crucial role in the excitation-contraction coupling. In fact, calmodulin (CaM) binds calcium and consequently regulates calcium channels. Several works show how some polymorphic variants can be considered predisposing factors to complex pathologies. Therefore, we hypothesize that the identification of polymorphic variants of proteins involved in the CaM pathway could be important for understanding how genetic traits can influence predisposition to myocardial infarction. This review considers each pathway of the three different isoforms of calmodulin (CaM1; CaM2; CaM3) and focuses on some common proteins involved in the three pathways, with the aim of analyzing the polymorphisms studied in the literature and understanding if they are associated with cardiovascular disease.

Associations between TAB2 gene polymorphisms and dilated cardiomyopathy in a Chinese population

Aim: The present study aimed to investigate the role of TAB2 gene polymorphisms in dilated cardiomyopathy (DCM) susceptibility and prognosis in a Chinese population. Materials & methods: A total of 343 DCM patients and 451 controls were enrolled and had their blood genotyped. Survival analysis was evaluated with Kaplan-Meier curves and Cox regression analysis. Results: G carriers (AG/GG) and AG genotype of rs237028 had a higher DCM susceptibility as well as a worse DCM prognosis. Additionally, C carriers (CT/CC) of rs652921 and G carriers (TG/GG) of rs521845 had a higher DCM risk and CC homozygote of rs652921 had a worse DCM prognosis. These associations were still significant after adjustment for the Bonferroni correction. Conclusion: TAB2 gene polymorphisms were associated with DCM susceptibility and prognosis in the Chinese population.

Protein Thermodynamic Destabilization in the Assessment of Pathogenicity of a Variant of Uncertain Significance in Cardiac Myosin Binding Protein C

In the era of next generation sequencing (NGS), genetic testing for inherited disorders identifies an ever-increasing number of variants whose pathogenicity remains unclear. These variants of uncertain significance (VUS) limit the reach of genetic testing in clinical practice. The VUS for hypertrophic cardiomyopathy (HCM), the most common familial heart disease, constitute over 60% of entries for missense variants shown in ClinVar database. We have studied a novel VUS (c.1809T>G-p.I603M) in the most frequently mutated gene in HCM, MYBPC3, which codes for cardiac myosin-binding protein C (cMyBPC). Our determinations of pathogenicity integrate bioinformatics evaluation and functional studies of RNA splicing and protein thermodynamic stability. In silico prediction and mRNA analysis indicated no alteration of RNA splicing induced by the variant. At the protein level, the p.I603M mutation maps to the C4 domain of cMyBPC. Although the mutation does not perturb much the overall structure of the C4 domain, the stability of C4 I603M is severely compromised as detected by circular dichroism and differential scanning calorimetry experiments. Taking into account the highly destabilizing effect of the mutation in the structure of C4, we propose reclassification of variant p.I603M as likely pathogenic. Looking into the future, the workflow described here can be used to refine the assignment of pathogenicity of variants of uncertain significance in MYBPC3.

Bioinformatics analysis of the regulatory lncRNA‑miRNA‑mRNA network and drug prediction in patients with hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a complex inherited cardiovascular disease. The present study investigated the long noncoding (lnc)RNA/microRNA (mi)RNA/mRNA expression pattern of patients with HCM and aimed to identify key molecules involved in the development of this condition. An integrated strategy was conducted to identify differentially expressed miRNAs (DEmiRs), differentially expressed lncRNAs (DElncs) and differentially expressed genes (DEGs) based on the GSE36961 (mRNA), GSE36946 (miRNA), GSE68316 (lncRNA/mRNA) and GSE32453 (mRNA) expression profiles downloaded from the Gene Expression Omnibus datasets. Bioinformatics tools were employed to perform function and pathway enrichment analysis, protein-protein interaction, lncRNA-miRNA-mRNA and hub gene networks. Subsequently, DEGs were used as targets to predict drugs. The results indicated that a total of 2,234 DElncs (1,120 upregulated and 1,114 downregulated), 5 DEmiRs (2 upregulated and 3 downregulated) and 42 DEGs (35 upregulated and 7 downregulated) were identified in 4 microarray profiles. Gene ontology analysis revealed that DEGs were mainly involved in actin filament and stress fiber formation and in calcium ion binding, whereas Kyoto Encyclopedia of Genes and Genomes pathway analysis identified the hypoxia inducible factor-1, transforming growth factor-β and tumor necrosis factor signaling pathways as the main pathways involved in these processes. The hub genes were screened using cytoHubba. A total of 1,086 lncRNA-miRNA-mRNA interactions including 67 lncRNAs, 5 miRNAs and 25 mRNAs were mined in the present study based on prediction websites. Drug prediction indicated that the targeted drugs mainly included angiotensin converting enzyme inhibitors or β-blockers. A comprehensive bioinformatics analysis of the molecular regulatory lncRNA-miRNA-mRNA network was performed and potential therapeutic applications of drugs were predicted in HCM patients. The data may unravel the future molecular mechanism of HCM.