The contribution of non-coding regulatory elements to cardiovascular disease

Cardiovascular disease-associated non-coding variants disrupt GATA4-DNA binding and regulatory functions

Genome-wide association studies have identified thousands of cardiovascular disease (CVD)-associated variants, with over 90% of them being mapped within the non-coding genome. Non-coding variants in regulatory regions of the genome, such as promoters, enhancers, silencers, and insulators, can alter the function of tissue-specific transcription factors (TFs) and their gene regulatory function. In this work, we used a computational approach to identify and test CVD-associated single-nucleotide polymorphisms (SNPs) that alter the DNA binding of the human cardiac transcription factor GATA4. Using a gapped k-mer support vector machine (GKM SVM) model, we scored CVD-associated SNPs localized in gene regulatory elements in expression quantitative trait loci (eQTL) detected in cardiac tissue to identify variants altering GATA4-DNA binding. We prioritized four variants that resulted in a total loss of GATA4 binding (rs1506537 and rs56992000) or the creation of new GATA4 binding sites (rs2941506 and rs2301249). The identified variants also resulted in significant changes in transcriptional activity proportional to the altered DNA-binding affinities. In summary, we present a comprehensive analysis comprising in silico, in vitro, and cellular evaluation of CVD-associated SNPs predicted to alter GATA4 function.

Macrophage-derived lncRNAs in cancer: regulators of tumor progression and therapeutic targets

Macrophages are key tumor microenvironment (TME) regulators, exhibiting remarkable plasticity that enables them to either suppress or promote cancer progression. Emerging evidence highlights the critical role of macrophage-derived long non-coding RNAs (lncRNAs) in shaping tumor immunity, influencing macrophage polarization, immune evasion, angiogenesis, metastasis, and therapy resistance. This review comprehensively elucidates the functional roles of M1- and M2-associated lncRNAs, detailing their molecular mechanisms and impact on cancer pathogenesis. In summary, elucidating the roles of lncRNAs derived from macrophages in cancer progression offers new avenues for therapeutic strategies, significantly improving patient outcomes in the fight against the disease. Further research into the functional significance of these lncRNAs and the development of targeted therapies is essential to harness their potential fully in clinical applications. We further explore their potential as biomarkers for cancer prognosis and therapeutic targets for modulating macrophage activity to enhance anti-cancer immunity. Targeting macrophage-derived lncRNAs represents a promising avenue for precision oncology, offering novel strategies to reshape the TME and improve cancer treatment outcomes.

Computational analysis of congenital heart disease associated SNPs: unveiling their impact on the gene regulatory system

Congenital heart disease (CHD) is a prevalent condition characterized by defective heart development, causing premature death and stillbirths among infants. Genome-wide association studies (GWASs) have provided insights into the role of genetic variants in CHD pathogenesis through the identification of a comprehensive set of single-nucleotide polymorphisms (SNPs). Notably, 90-95% of these variants reside in the noncoding genome, complicating the understanding of their underlying mechanisms. Here, we developed a systematic computational pipeline for the identification and analysis of CHD-associated SNPs spanning both coding and noncoding regions of the genome. Initially, we curated a thorough dataset of SNPs from GWAS-catalog and ClinVar database and filtered them based on CHD-related traits. Subsequently, these CHD-SNPs were annotated and categorized into noncoding and coding regions based on their location. To study the functional implications of noncoding CHD-SNPs, we cross-validated them with enhancer-specific histone modification marks from developing human heart across 9 Carnegie stages and identified potential cardiac enhancers. This approach led to the identification of 2,056 CHD-associated putative enhancers (CHD-enhancers), 38.9% of them overlapping with known enhancers catalogued in human enhancer disease database. We identified heart-related transcription factor binding sites within these CHD-enhancers, offering insights into the impact of SNPs on TF binding. Conservation analysis further revealed that many of these CHD-enhancers were highly conserved across vertebrates, suggesting their evolutionary significance. Utilizing heart-specific expression quantitative trait loci data, we further identified a subset of 63 CHD-SNPs with regulatory potential distributed across various cardiac tissues. Concurrently, coding CHD-SNPs were represented as a protein interaction network and its subsequent binding energy analysis focused on a pair of proteins within this network, pinpointed a deleterious coding CHD-SNP, rs770030288, located in C2 domain of MYBPC3 protein. Overall, our findings demonstrate that SNPs have the potential to disrupt gene regulatory systems, either by affecting enhancer sequences or modulating protein-protein interactions, which can lead to abnormal developmental processes contributing to CHD pathogenesis.

LRP1 Repression by SNAIL Results in ECM Remodeling in Genetic Risk for Vascular Diseases

BACKGROUND

Genome-wide association studies implicate common genetic variations in the LRP1 (low-density lipoprotein receptor-related protein 1 gene) locus at risk for multiple vascular diseases and traits. However, the underlying biological mechanisms are unknown.

METHODS

Fine mapping analyses included Bayesian colocalization to identify the most likely causal variant. Human induced pluripotent stem cells were genome-edited using CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated protein 9) to delete or modify candidate enhancer regions and generate LRP1 knockout cell lines. Cells were differentiated into smooth muscle cells through a mesodermal lineage. Transcription regulation was assessed using luciferase reporter assay, transcription factor knockdown, and chromatin immunoprecipitation. Phenotype changes in cells were conducted using cellular assays, bulk RNA sequencing, and mass spectrometry.

RESULTS

Multitrait colocalization analyses pointed at rs11172113 as the most likely causal variant in LRP1 for fibromuscular dysplasia, migraine, pulse pressure, and spontaneous coronary artery dissection. We found the rs11172113-T allele to associate with higher LRP1 expression. Genomic deletion in induced pluripotent stem cell-derived smooth muscle cells supported rs11172113 to locate in an enhancer region regulating LRP1 expression. We found transcription factors MECP2 (methyl CpG binding protein 2) and SNAIL (Zinc Finger Protein SNAI1) to repress LRP1 expression through an allele-specific mechanism, involving SNAIL interaction with disease risk allele. LRP1 knockout decreased induced pluripotent stem cell-derived smooth muscle cell proliferation and migration. Differentially expressed genes were enriched for collagen-containing extracellular matrix and connective tissue development. LRP1 knockout and deletion of rs11172113 enhancer showed potentiated canonical TGF-β (transforming growth factor beta) signaling through enhanced phosphorylation of SMAD2/3 (Mothers against decapentaplegic homolog 2/3). Analyses of the protein content of decellularized extracts indicated partial extracellular matrix remodeling involving enhanced secretion of CYR61 (cystein rich angiogenic protein 61), a known LRP1 ligand involved in vascular integrity and TIMP3 (Metalloproteinase inhibitor 3), implicated in extracellular matrix maintenance and also known to interact with LRP1.

CONCLUSIONS

Our findings support allele-specific LRP1 expression repression by the endothelial-to-mesenchymal transition regulator SNAIL. We propose decreased LRP1 expression in smooth muscle cells to remodel the extracellular matrix enhanced by TGF-β as a potential mechanism of this pleiotropic locus for vascular diseases.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Understanding genomic medicine for thoracic aortic disease through the lens of induced pluripotent stem cells

Thoracic aortic disease (TAD) is often silent until a life-threatening complication occurs. However, genetic information can inform both identification and treatment at an early stage. Indeed, a diagnosis is important for personalised surveillance and intervention plans, as well as cascade screening of family members. Currently, only 20% of heritable TAD patients have a causative mutation identified and, consequently, further advances in genetic coverage are required to define the remaining molecular landscape. The rapid expansion of next generation sequencing technologies is providing a huge resource of genetic data, but a critical issue remains in functionally validating these findings. Induced pluripotent stem cells (iPSCs) are patient-derived, reprogrammed cell lines which allow mechanistic insights, complex modelling of genetic disease and a platform to study aortic genetic variants. This review will address the need for iPSCs as a frontline diagnostic tool to evaluate variants identified by genomic discovery studies and explore their evolving role in biological insight through to drug discovery.

Prioritizing cardiovascular disease-associated variants altering NKX2-5 and TBX5 binding through an integrative computational approach

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are heavily influenced by genetic factors. Genome-wide association studies have mapped >90% of CVD-associated variants within the noncoding genome, which can alter the function of regulatory proteins, such as transcription factors (TFs). However, due to the overwhelming number of single-nucleotide polymorphisms (SNPs) (>500,000) in genome-wide association studies, prioritizing variants for in vitro analysis remains challenging. In this work, we implemented a computational approach that considers support vector machine (SVM)-based TF binding site classification and cardiac expression quantitative trait loci (eQTL) analysis to identify and prioritize potential CVD-causing SNPs. We identified 1535 CVD-associated SNPs within TF footprints and putative cardiac enhancers plus 14,218 variants in linkage disequilibrium with genotype-dependent gene expression in cardiac tissues. Using ChIP-seq data from two cardiac TFs (NKX2-5 and TBX5) in human-induced pluripotent stem cell-derived cardiomyocytes, we trained a large-scale gapped k-mer SVM model to identify CVD-associated SNPs that altered NKX2-5 and TBX5 binding. The model was tested by scoring human heart TF genomic footprints within putative enhancers and measuring in vitro binding through electrophoretic mobility shift assay. Five variants predicted to alter NKX2-5 (rs59310144, rs6715570, and rs61872084) and TBX5 (rs7612445 and rs7790964) binding were prioritized for in vitro validation based on the magnitude of the predicted change in binding and are in cardiac tissue eQTLs. All five variants altered NKX2-5 and TBX5 DNA binding. We present a bioinformatic approach that considers tissue-specific eQTL analysis and SVM-based TF binding site classification to prioritize CVD-associated variants for in vitro analysis.

Prioritizing Cardiovascular Disease-Associated Variants Altering NKX2-5 Binding through an Integrative Computational Approach

Cardiovascular diseases (CVDs) are the leading cause of death worldwide and are heavily influenced by genetic factors. Genome-wide association studies (GWAS) have mapped > 90% of CVD-associated variants within the non-coding genome, which can alter the function of regulatory proteins, like transcription factors (TFs). However, due to the overwhelming number of GWAS single nucleotide polymorphisms (SNPs) (>500,000), prioritizing variants for in vitro analysis remains challenging. In this work, we implemented a computational approach that considers support vector machine (SVM)-based TF binding site classification and cardiac expression quantitative trait loci (eQTL) analysis to identify and prioritize potential CVD-causing SNPs. We identified 1,535 CVD-associated SNPs that occur within human heart footprints/enhancers and 9,309 variants in linkage disequilibrium (LD) with differential gene expression profiles in cardiac tissue. Using hiPSC-CM ChIP-seq data from NKX2-5 and TBX5, two cardiac TFs essential for proper heart development, we trained a large-scale gapped k-mer SVM (LS-GKM-SVM) predictive model that can identify binding sites altered by CVD-associated SNPs. The computational predictive model was tested by scoring human heart footprints and enhancers in vitro through electrophoretic mobility shift assay (EMSA). Three variants (rs59310144, rs6715570, and rs61872084) were prioritized for in vitro validation based on their eQTL in cardiac tissue and LS-GKM-SVM prediction to alter NKX2-5 DNA binding. All three variants altered NKX2-5 DNA binding. In summary, we present a bioinformatic approach that considers tissue-specific eQTL analysis and SVM-based TF binding site classification to prioritize CVD-associated variants for in vitro experimental analysis.

Leveraging epigenomes and three-dimensional genome organization for interpreting regulatory variation

Understanding the impact of regulatory variants on complex phenotypes is a significant challenge because the genes and pathways that are targeted by such variants and the cell type context in which regulatory variants operate are typically unknown. Cell-type-specific long-range regulatory interactions that occur between a distal regulatory sequence and a gene offer a powerful framework for examining the impact of regulatory variants on complex phenotypes. However, high-resolution maps of such long-range interactions are available only for a handful of cell types. Furthermore, identifying specific gene subnetworks or pathways that are targeted by a set of variants is a significant challenge. We have developed L-HiC-Reg, a Random Forests regression method to predict high-resolution contact counts in new cell types, and a network-based framework to identify candidate cell-type-specific gene networks targeted by a set of variants from a genome-wide association study (GWAS). We applied our approach to predict interactions in 55 Roadmap Epigenomics Mapping Consortium cell types, which we used to interpret regulatory single nucleotide polymorphisms (SNPs) in the NHGRI-EBI GWAS catalogue. Using our approach, we performed an in-depth characterization of fifteen different phenotypes including schizophrenia, coronary artery disease (CAD) and Crohn's disease. We found differentially wired subnetworks consisting of known as well as novel gene targets of regulatory SNPs. Taken together, our compendium of interactions and the associated network-based analysis pipeline leverages long-range regulatory interactions to examine the context-specific impact of regulatory variation in complex phenotypes.

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.

POSTRE: a tool to predict the pathological effects of human structural variants

Understanding the pathological impact of non-coding genetic variation is a major challenge in medical genetics. Accumulating evidences indicate that a significant fraction of genetic alterations, including structural variants (SVs), can cause human disease by altering the function of non-coding regulatory elements, such as enhancers. In the case of SVs, described pathomechanisms include changes in enhancer dosage and long-range enhancer-gene communication. However, there is still a clear gap between the need to predict and interpret the medical impact of non-coding variants, and the existence of tools to properly perform these tasks. To reduce this gap, we have developed POSTRE (Prediction Of STRuctural variant Effects), a computational tool to predict the pathogenicity of SVs implicated in a broad range of human congenital disorders. By considering disease-relevant cellular contexts, POSTRE identifies SVs with either coding or long-range pathological consequences with high specificity and sensitivity. Furthermore, POSTRE not only identifies pathogenic SVs, but also predicts the disease-causative genes and the underlying pathological mechanism (e.g, gene deletion, enhancer disconnection, enhancer adoption, etc.). POSTRE is available at https://github.com/vicsanga/Postre.

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.

Disease-associated non-coding variants alter NKX2-5 DNA-binding affinity

Genome-wide association studies (GWAS) have mapped over 90 % of disease- or trait-associated variants within the non-coding genome, like cis-regulatory elements (CREs). Non-coding single nucleotide polymorphisms (SNPs) are genomic variants that can change how DNA-binding regulatory proteins, like transcription factors (TFs), interact with the genome and regulate gene expression. NKX2-5 is a TF essential for proper heart development, and mutations affecting its function have been associated with congenital heart diseases (CHDs). However, establishing a causal mechanism between non-coding genomic variants and human disease remains challenging. To address this challenge, we identified 8475 SNPs predicted to alter NKX2-5 DNA-binding using a position weight matrix (PWM)-based predictive model. Five variants were prioritized for in vitro validation; four of them are associated with traits and diseases that impact cardiovascular health. The impact of these variants on NKX2-5 binding was evaluated with electrophoretic mobility shift assay (EMSA) using purified recombinant NKX2-5 homeodomain. Binding curves were constructed to determine changes in binding between variant and reference alleles. Variants rs7350789, rs7719885, rs747334, and rs3892630 increased binding affinity, whereas rs61216514 decreased binding by NKX2-5 when compared to the reference genome. Our findings suggest that differential TF-DNA binding affinity can be key in establishing a causal mechanism of pathogenic variants.

Emerging technologies for prenatal diagnosis: The application of whole genome and RNA sequencing

DNA sequencing technologies for clinical genetic testing have been rapidly evolving in recent years, and steadily become more important within the field of prenatal diagnostics. This review aims to give an overview of recent developments and to describe how they have the potential to fill the gaps of the currently clinically implemented methods for prenatal diagnosis of various genetic disorders. It has been shown for postnatal testing that whole genome sequencing provides a set of added benefits compared to exome sequencing, and it is to be expected that this will be the case for prenatal testing as well. RNA-sequencing, already used postnatally, can provide valuable complementary data to DNA-based testing, and aid in variant interpretation. While not ready for clinical implementation, emerging technologies such as long-read and Hi-C sequencing analyses might add to the toolbox for interpreting the expanding genetic data sets generated by genome-wide sequencing. Lastly, we also discuss some more practical implications of introducing these emerging technologies, which generate larger and larger genomic data sets, in the prenatal field.

Deciphering pathogenicity of variants of uncertain significance with CRISPR-edited iPSCs

Genetic variants play an important role in conferring risk for cardiovascular diseases (CVDs). With the rapid development of next-generation sequencing (NGS), thousands of genetic variants associated with CVDs have been identified by genome-wide association studies (GWAS), but the function of more than 40% of genetic variants is still unknown. This gap of knowledge is a barrier to the clinical application of the genetic information. However, determining the pathogenicity of a variant of uncertain significance (VUS) is challenging due to the lack of suitable model systems and accessible technologies. By combining clustered regularly interspaced short palindromic repeats (CRISPR) and human induced pluripotent stem cells (iPSCs), unprecedented advances are now possible in determining the pathogenicity of VUS in CVDs. Here, we summarize recent progress and new strategies in deciphering pathogenic variants for CVDs using CRISPR-edited human iPSCs.

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.

The role of resistance to inhibitors of cholinesterase 8b in the control of heart rate

We have assessed the role of ric-b8 in the control of heart rate after the gene was implicated in a recent genome-wide association study of resting heart rate. We developed a novel murine model in which it was possible to conditionally delete ric-8b in the sinoatrial (SA) node after the addition of tamoxifen. Despite this, we were unable to obtain homozygotes and thus studied heterozygotes. Haploinsufficiency of ric-8b in the sinoatrial node induced by the addition of tamoxifen in adult animals leads to mice with a reduced heart rate. However, other electrocardiographic intervals (e.g., PR and QRS) were normal, and there was no apparent arrhythmia such as heart block. The positive chronotropic response to isoprenaline was abrogated, whereas the response to carbachol was unchanged. The pacemaker current I_f (funny current) has an important role in regulating heart rate, and its function is modulated by both isoprenaline and carbachol. Using a heterologous system expressing HCN4, we show that ric-8b can modulate the HCN4 current. Overexpression of ric-8b led to larger HCN4 currents, whereas silencing ric-8b led to smaller currents. Ric-8b modulates heart rate responses in vivo likely via its actions on the stimulatory G-protein.