Genetics of human cardiovascular disease

Multi-modality risk prediction of cardiovascular diseases for breast cancer cohort in the All of Us Research Program

OBJECTIVE

This study leverages the rich diversity of the All of Us Research Program (All of Us)'s dataset to devise a predictive model for cardiovascular disease (CVD) in breast cancer (BC) survivors. Central to this endeavor is the creation of a robust data integration pipeline that synthesizes electronic health records (EHRs), patient surveys, and genomic data, while upholding fairness across demographic variables.

MATERIALS AND METHODS

We have developed a universal data wrangling pipeline to process and merge heterogeneous data sources of the All of Us dataset, address missingness and variance in data, and align disparate data modalities into a coherent framework for analysis. Utilizing a composite feature set including EHR, lifestyle, and social determinants of health (SDoH) data, we then employed Adaptive Lasso and Random Forest regression models to predict 6 CVD outcomes. The models were evaluated using the c-index and time-dependent Area Under the Receiver Operating Characteristic Curve over a 10-year period.

RESULTS

The Adaptive Lasso model showed consistent performance across most CVD outcomes, while the Random Forest model excelled particularly in predicting outcomes like transient ischemic attack when incorporating the full multi-model feature set. Feature importance analysis revealed age and previous coronary events as dominant predictors across CVD outcomes, with SDoH clustering labels highlighting the nuanced impact of social factors.

DISCUSSION

The development of both Cox-based predictive model and Random Forest Regression model represents the extensive application of the All of Us, in integrating EHR and patient surveys to enhance precision medicine. And the inclusion of SDoH clustering labels revealed the significant impact of sociobehavioral factors on patient outcomes, emphasizing the importance of comprehensive health determinants in predictive models. Despite these advancements, limitations include the exclusion of genetic data, broad categorization of CVD conditions, and the need for fairness analyses to ensure equitable model performance across diverse populations. Future work should refine clinical and social variable measurements, incorporate advanced imputation techniques, and explore additional predictive algorithms to enhance model precision and fairness.

CONCLUSION

This study demonstrates the liability of the All of Us's diverse dataset in developing a multi-modality predictive model for CVD in BC survivors risk stratification in oncological survivorship. The data integration pipeline and subsequent predictive models establish a methodological foundation for future research into personalized healthcare.

Modification of coronary artery disease clinical risk factors by coronary artery disease polygenic risk score

BACKGROUND

The extent to which the relationships between clinical risk factors and coronary artery disease (CAD) are altered by CAD polygenic risk score (PRS) is not well understood. Here, we determine whether the interactions between clinical risk factors and CAD PRS further explain risk for incident CAD.

METHODS

Participants were of European ancestry from the UK Biobank without prevalent CAD. An externally trained genome-wide CAD PRS was generated and then applied. Clinical risk factors were ascertained at baseline. Cox proportional hazards models were fitted to examine the incident CAD effects of CAD PRS, risk factors, and their interactions. Next, the PRS and risk factors were stratified to investigate the attributable risk of clinical risk factors.

FINDINGS

A total of 357,144 individuals of European ancestry without prevalent CAD were included. During a median of 11.1 years of follow-up (interquartile range 10.4-14.1 years), CAD PRS was associated with 1.35-fold (95% confidence interval [CI] 1.332-1.368) risk per SD for incident CAD. The prognostic relevance of the following risk factors was relatively diminished for those with high CAD PRS on a continuous scale: type 2 diabetes (hazard ratio [HR]interaction 0.91, 95% CIinteraction 0.88-0.94), increased body mass index (HRinteraction 0.97, 95% CIinteraction 0.96-0.98), and increased C-reactive protein (HRinteraction 0.98, 95% CIinteraction 0.96-0.99). However, a high CAD PRS yielded joint risk increases with low-density lipoprotein cholesterol (HRinteraction 1.05, 95% CIinteraction 1.04-1.06) and total cholesterol (HRinteraction 1.05, 95% CIinteraction 1.03-1.06).

CONCLUSION

The CAD PRS is associated with incident CAD, and its application improves the prognostic relevance of several clinical risk factors.

FUNDING

P.N. (R01HL127564, R01HL151152, and U01HG011719) is supported by the National Institutes of Health.

A bibliometric and visual analysis of research trends and hotspots of familial hypertrophic cardiomyopathy: A review

Familial hypertrophic cardiomyopathy (FHCM) is an inherited cardiac disease caused by mutations of sarcomere proteins and can be the underlining substrate for major cardiovascular events. Early identification and diagnosis of FHCM are essential to reduce sudden cardiac death. So, this paper summarized the current knowledge on FHCM, and displayed the analysis via bibliometrics method. The relevant literature on FHCM were screened searched via the Web of Science Core Collection database from 2012 to 2022. The literatures were was summarized and analyzed via the bibliometrics method analyzed via CiteSpace and VOSviewer according to topic categories, distribution of spatiotemporal omics and authors, as well as references. Since 2012, there are 909 research articles and reviews related to FHCM. The number of publication for the past 10 years have shown that the development of FHCM research has been steady, with the largest amount of literature in 2012. The most published papers were from the United States, followed by the United Kingdom and Italy. The University of London (63 papers) was the institution that published the most research articles, followed by Harvard University (45 papers) and University College London (45 papers). Keywords formed 3 clusters, focused on the pathogenesis of FHCM, the diagnosis of FHCM, FHCM complications, respectively. The bibliometric analysis and visualization techniques employed herein highlight key trends and focal points in the field, predominantly centered around FHCM's pathogenesis, diagnostic approaches, and its complications. These insights are instrumental in steering future research directions in this area.

Variants in FOXC1 and FOXC2 identified in patients with conotruncal heart defects

Conotruncal heart defects (CTD), subtypes of congenital heart disease, result from abnormal cardiac outflow tract development (OFT). FOXC1 and FOXC2 are closely related members of the forkhead transcription factor family and play essential roles in the development of OFT. We confirmed their expression pattern in mouse and human embryos, identifying four variants in FOXC1 and three in FOXC2 by screening these two genes in 605 patients with sporadic CTD. Western blot demonstrated expression levels, while Dual-luciferase reporter assay revealed affected transcriptional abilities for TBX1 enhancer in two FOXC1 variants and three FOXC2 variants. This might result from the altered DNA-binding abilities of mutant proteins. These results indicate that functionally impaired FOXC1 and FOXC2 variants may contribute to the occurrence of CTD.

Discrimination of Multiple Homologous Sequences Based on DNA Logic Gate and Elemental Labeling Technology

The simultaneous discrimination of multiple homologous sequences faces challenges due to the high similarity of sequences and the complexity of the discrimination system in most reported works. Herein, a simple and ingenious analysis method was developed to identify eight miRNAs of the let-7 family by combining logic gates and entropy-driven catalytic (EDC)-based lanthanide labeling inductively coupled plasma mass spectrometry (ICP-MS) technology. Specifically, eight miRNAs were first divided into four types according to the difference of bases in the domains 2 and 3 on sequences. To identify the type of targets, a DNA logic gate was constructed with two strand displacement reactions on magnetic beads that could be initiated by different types of targets. Based on the difference of the output signals after two strand displacement reactions, the type of targets was distinguished preliminarily. Then, the discrimination of a specific target was achieved with EDC-based lanthanide labeling ICP-MS detection. By labeling the different magnetic probes with different elemental tags, a specific element signal released from magnetic beads after EDC could be detected by ICP-MS, and therefore, simultaneous detection of homologous sequences was completed. This work provided a novel and simple method for highly specific identification of homologous sequences with the assistance of a logic gate and can promote further development of elemental labeling ICP-MS in the field of multiple analysis.

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases

BACKGROUND

Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD.

METHODS

Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets.

RESULTS

Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure.

CONCLUSIONS

This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

A contemporary review of snoRNAs in cardiovascular health: RNA modification and beyond

As cardiovascular diseases continue to be the leading cause of death worldwide, groundbreaking research is being conducted to mitigate their effects. This review looks into the potential of small nucleolar RNAs (snoRNAs) and the opportunity to use these molecular agents as therapeutic biomarkers for cardiovascular issues specific to the heart. Through an investigation of snoRNA biogenesis, functionality, and roles in cardiovascular diseases, this review relates our past and present knowledge of snoRNAs to the current scientific literature. Considering the initial discovery of snoRNAs and the studies thereafter analyzing the roles of snoRNAs in disease, we look forward to uncovering many other noncanonical functions that could lead researchers closer to finding preventive and curative solutions for cardiovascular diseases.

Association of APO B gene polymorphisms with the development of myocardial infarction in Pakistani population

Myocardial infarction (MI) is when a blood clot in the coronary artery obstructs blood flow to a specific part of the heart, leading to the death of myocardium in that area. The development of MI is influenced by various environmental factors, genetic components, and their interactions, even though the exact cause has not been fully established. This is the first case-control study examining the possible association between the human Apo B gene and MI in the Punjab region of Pakistan. The study included 100 patients and 50 healthy individuals. Genomic DNA was isolated from blood samples using manual extraction methods. Subsequently, primers were optimized, and genotyping was performed using PCR, followed by DNA sequencing and RFLP analysis. The research focused on two specific APO B gene SNPs, codon 4154 G/A (rs1801701) and codon 2488 G/A (rs1042031). Both SNPs involved the substitution of guanine with adenine. It was found that individuals carrying the minor allele A of SNP rs1801701 (p < 0.001) and the minor allele A of rs1042031 (p < 0.001) had a significantly higher risk of developing MI. Additionally, haplotype analysis revealed that the AA haplotype (comprising both rs1801701 and rs1042031 SNPs) was associated with a substantially increased risk of MI (OR = 3.845). In conclusion, the study provides evidence supporting the association between specific mutations in the APOB gene and the risk of myocardial infarction in the Pakistani population.

The Inclusion of Underrepresented Populations in Cardiovascular Genetics and Epidemiology

Novel genetic risk markers have helped us to advance the field of cardiovascular epidemiology and refine our current understanding and risk stratification paradigms. The discovery and analysis of variants can help us to tailor prognostication and management. However, populations underrepresented in cardiovascular epidemiology and cardiogenetics research may experience inequities in care if prediction tools are not applicable to them clinically. Therefore, the purpose of this article is to outline the barriers that underrepresented populations can face in participating in genetics research, to describe the current efforts to diversify cardiogenetics research, and to outline strategies that researchers in cardiovascular epidemiology can implement to include underrepresented populations. Mistrust, a lack of diverse research teams, the improper use of sensitive biodata, and the constraints of genetic analyses are all barriers for including diverse populations in genetics studies. The current work is beginning to address the paucity of ethnically diverse genetics research and has already begun to shed light on the potential benefits of including underrepresented and diverse populations. Reducing barriers for individuals, utilizing community-driven research processes, adopting novel recruitment strategies, and pushing for organizational support for diverse genetics research are key steps that clinicians and researchers can take to develop equitable risk stratification tools and improve patient care.

The therapeutic potential of dietary intervention: based on the mechanism of a tryptophan derivative-indole propionic acid on metabolic disorders

Tryptophan (TRP) contributes to individual immune homeostasis and good condition via three complex metabolism pathways (5-hydroxytryptamine (5-HT), kynurenine (KP), and gut microbiota pathway). Indole propionic acid (IPA), one of the TRP derivatives of the microbiota pathway, has raised more attention because of its impact on metabolic disorders. Here, we retrospect increasing evidence that TRP metabolites/IPA derived from its proteolysis impact host health and disease. IPA can activate the immune system through aryl hydrocarbon receptor (AHR) and/or Pregnane X receptor (PXR) as a vital mediator among diet-caused host and microbe cross-talk. Different levels of IPA in systemic circulation can predict the risk of NAFLD, T2DM, and CVD. IPA is suggested to alleviate cognitive impairment from oxidative damage, reduce gut inflammation, inhibit lipid accumulation and attenuate the symptoms of NAFLD, putatively enhance the intestinal epithelial barrier, and maintain intestinal homeostasis. Now, we provide a general description of the relationships between IPA and various physiological and pathological processes, which support an opportunity for diet intervention for metabolic diseases.

Genomic insights into heart health: Exploring the genetic basis of cardiovascular disease

Cardiovascular diseases (CVDs) are considered as the leading cause of death worldwide. CVD continues to be a major cause of death and morbidity despite significant improvements in its detection and treatment. Therefore, it is strategically important to be able to precisely characterize an individual's sensitivity to certain illnesses. The discovery of genes linked to cardiovascular illnesses has benefited from linkage analysis and genome-wide association research. The last 20 years have seen significant advancements in the field of molecular genetics, particularly with the development of new tools like genome-wide association studies. In this article we explore the profound impact of genetic variations on disease development, prognosis, and therapeutic responses. And the significance of genetics in cardiovascular risk assessment and the ever-evolving realm of genetic testing, offering insights into the potential for personalized medicine in this domain. Embracing the future of cardiovascular care, the article explores the implications of pharmacogenomics for tailored treatments, the promise of emerging technologies in cardiovascular genetics and therapies, including the transformative influence of nanotechnology. Furthermore, it delves into the exciting frontiers of gene editing, such as CRISPR/Cas9, as a novel approach to combat cardiovascular diseases. And also explore the potential of stem cell therapy and regenerative medicine, providing a holistic view of the dynamic landscape of cardiovascular genomics and its transformative potential for the field of cardiovascular medicine.

Multi-chamber cardioids unravel human heart development and cardiac defects

The number one cause of human fetal death are defects in heart development. Because the human embryonic heart is inaccessible and the impacts of mutations, drugs, and environmental factors on the specialized functions of different heart compartments are not captured by in vitro models, determining the underlying causes is difficult. Here, we established a human cardioid platform that recapitulates the development of all major embryonic heart compartments, including right and left ventricles, atria, outflow tract, and atrioventricular canal. By leveraging 2D and 3D differentiation, we efficiently generated progenitor subsets with distinct first, anterior, and posterior second heart field identities. This advance enabled the reproducible generation of cardioids with compartment-specific in vivo-like gene expression profiles, morphologies, and functions. We used this platform to unravel the ontogeny of signal and contraction propagation between interacting heart chambers and dissect how mutations, teratogens, and drugs cause compartment-specific defects in the developing human heart.

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.

Computational exploration of novel ROCK2 inhibitors for cardiovascular disease management; insights from high-throughput virtual screening, molecular docking, DFT and MD simulation

Cardiovascular disorders are the world's major cause of death nowadays. To treat cardiovascular diseases especially coronary artery diseases and hypertension, researchers found potential ROCK2 (Rho-associated coiled-coil-containing protein kinase 2) target due to its substantial role in NO-cGMP and RhoA/ROCK pathway. Available drugs for ROCK2 are less effective and some of them depict side effects. Therefore, a set of novel compounds were screened that can potentially inhibit the activity of ROCK2 and help to treat cardiovascular diseases by employing In-silico techniques. In this study, we undertook ligand based virtual screening of 50 million compound's library, to that purpose shape and features (contain functional groups) based pharmacophore query was modelled and validated by Area Under Curve graph (AUC). 2000 best hits were screened for Lipinski's rule of 5 compliance. Subsequently, these selected compounds were docked into the binding site of ROCK2 to gain insights into the interactions between hit compounds and the target protein. Based on binding affinity and RMSD scores, a final cohort of 15 compounds were chosen which were further refined by pharmacokinetics, ADMET and bioactivity scores. 2 potential hits were screened using density functional theory, revealing remarkable biological and chemical activity. Potential inhibitors (F847-0007 and 9543495) underwent rigorous examination through MD Simulations and MMGBSA analysis, elucidating their stability and strong binding affinities. Results of current study unveil the potential of identified novel hits as promising lead compounds for ROCK2 associated with cardiovascular diseases. These findings will further investigate via In-vitro and In-vivo studies to develop novel druglike molecules against ROCK2.

The Autosomal Short Tandem Repeat Polymorphisms Are Potentially Associated with Cardiovascular Disease Predisposition in the Latin American Population: A Mini Review

According to the World Health Organization, cardiovascular diseases (CVDs) are the leading cause of death worldwide across nearly all ethnic groups. Inherited cardiac conditions comprise a wide spectrum of diseases that affect the heart, including abnormal structural features and functional impairments. In Latin America, CVDs are the leading cause of death within the region. Factors such as population aging, unhealthy diet, obesity, smoking, and a sedentary lifestyle have increased the risk of CVD. The Latin American population is characterized by its diverse ethnic composition with varying percentages of each ancestral component (African, European, and Native American ancestry). Short tandem repeats (STRs) are DNA sequences with 2-6 base pair repetitions and constitute ~3% of the human genome. Importantly, significant allele frequency variations exist between different populations. While studies have described that STRs are in noncoding regions of the DNA, increasing evidence suggests that simple sequence repeat variations may be critical for proper gene activity and regulation. Furthermore, several STRs have been identified as potential disease predisposition markers. The present review is aimed at comparing and describing the frequencies of autosomal STR polymorphisms potentially associated with cardiovascular disease predisposition in Latin America compared with other populations.

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Cardiovascular disease (CVD) is caused by a multitude of complex and largely heritable conditions. Identifying key genes and understanding their susceptibility to CVD in the human genome can assist in early diagnosis and personalized treatment of the relevant patients. Heart failure (HF) is among those CVD phenotypes that has a high rate of mortality. In this study, we investigated genes primarily associated with HF and other CVDs. Achieving the goals of this study, we built a cohort of thirty-five consented patients, and sequenced their serum-based samples. We have generated and processed whole genome sequence (WGS) data, and performed functional mutation, splice, variant distribution, and divergence analysis to understand the relationships between each mutation type and its impact. Our variant and prevalence analysis found FLNA, CST3, LGALS3, and HBA1 linked to many enrichment pathways. Functional mutation analysis uncovered ACE, MME, LGALS3, NR3C2, PIK3C2A, CALD1, TEK, and TRPV1 to be notable and potentially significant genes. We discovered intron, 5' Flank, 3' UTR, and 3' Flank mutations to be the most common among HF and other CVD genes. Missense mutations were less common among HF and other CVD genes but had more of a functional impact. We reported HBA1, FADD, NPPC, ADRB2, ADBR1, MYH6, and PLN to be consequential based on our divergence analysis.

Triple-recognition strategy for one-pot detection of single nucleotide variants by aligner-mediated cleavage-triggered exponential amplification

The detection of single nucleotide variants (SNVs) is important for the diagnosis and treatment of cancer. To date, researchers have devised several methods to detect SNVs, but most of them are complex and time-consuming. To improve SNVs detection specificity and sensitivity, we developed a triple-recognition strategy, which facilitates aligner-mediated cleavage-triggered exponential amplification (Trec-AMC-EXPAR) for the rapid, specific, and one-pot detection of SNV. Under optimized conditions, Trec-AMC-EXPAR detected two clinically significant SNVs, PIK3CAH1047R and EGFR L858R within 80 min, with a reliable detection of 0.1% SNV in the wide type, which is lower than that of allele-specific PCR (AS-PCR) for detecting SNV. Finally, by spiking into normal human serum samples, mutants mixed with the wild-type targets in different ratios were analyzed, resulting in the relative standard deviation (RSD) of recovery ratios <3%. The findings suggested the potential application of Trec-AMC-EXPAR in clinical disease diagnosis. In summary, the proposed Trec-AMC-EXPAR technique provides a novel fast and convenient method for one-pot detection of SNV with high sensitivity and specificity.

A New Era of Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated Protein 9 Gene Editing Technology in Cardiovascular Diseases: Opportunities, Challenges, and Perspectives

Cardiovascular diseases (CVDs) remain major causes of global mortality in the world. Genetic approaches have succeeded in the discovery of the molecular basis of an increasing number of cardiac diseases. Genome-editing strategies are one of the most effective methods for assisting therapeutic approaches. Potential therapeutic methods of correcting disease-causing mutations or of knocking out specific genes as approaches for the prevention of CVDs have gained substantial attention using genome-editing techniques. Recently, the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system has become the most widely used genome-editing technology in molecular biology due to its benefits such as simple design, high efficiency, good repeatability, short cycle, and cost-effectiveness. In the present review, we discuss the possibilities of applying the CRISPR/Cas9 genome-editing tool in the CVDs.

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.

Applying an evolutionary mismatch framework to understand disease susceptibility

Noncommunicable diseases (NCDs) are on the rise worldwide. Obesity, cardiovascular disease, and type 2 diabetes are among a long list of "lifestyle" diseases that were rare throughout human history but are now common. The evolutionary mismatch hypothesis posits that humans evolved in environments that radically differ from those we currently experience; consequently, traits that were once advantageous may now be "mismatched" and disease causing. At the genetic level, this hypothesis predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions, with different health effects in "ancestral" versus "modern" environments. To identify such loci, we advocate for combining genomic tools in partnership with subsistence-level groups experiencing rapid lifestyle change. In these populations, comparisons of individuals falling on opposite extremes of the "matched" to "mismatched" spectrum are uniquely possible. More broadly, the work we propose will inform our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and cultures.

Comparative Analysis of Heart Regeneration: Searching for the Key to Heal the Heart-Part II: Molecular Mechanisms of Cardiac Regeneration

Cardiovascular diseases are the leading cause of death worldwide, among which ischemic heart disease is the most representative. Myocardial infarction results from occlusion of a coronary artery, which leads to an insufficient blood supply to the myocardium. As it is well known, the massive loss of cardiomyocytes cannot be solved due the limited regenerative ability of the adult mammalian hearts. In contrast, some lower vertebrate species can regenerate the heart after an injury; their study has disclosed some of the involved cell types, molecular mechanisms and signaling pathways during the regenerative process. In this 'two parts' review, we discuss the current state-of-the-art of the main response to achieve heart regeneration, where several processes are involved and essential for cardiac regeneration.

Genetically Predicted Vegetable Intake and Cardiovascular Diseases and Risk Factors: An Investigation with Mendelian Randomization

BACKGROUND

The associations between vegetable intake and cardiovascular diseases have been demonstrated in observational studies, but less sufficiently in randomized trials. Mendelian randomization has been considered a promising alternative in causal inference. The separate effects of cooked and raw vegetable intake remain unclear. This study aimed to investigate the associations between cooked and raw vegetable intake with cardiovascular outcomes using MR.

METHODS

We identified 15 and 28 genetic variants statistically and biologically associated with cooked and raw vegetable intake, respectively, from previous genome-wide association studies, which were used as instrumental variables to estimate associations with coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF). The independent effects of genetically predicted cooked and raw vegetable intake were examined using multivariable MR analysis. We performed one-sample and two-sample MR analyses and combined their results using meta-analysis. Bonferroni correction was applied for multiple comparisons. We performed two-sample MR analysis for cardiometabolic risk factors (serum lipids, blood pressure, body mass index, and glycemic traits) to explore the potential mechanisms.

RESULTS

In the MR meta-analysis of 1.2 million participants, we found null evidence for associations between genetically predicted cooked and raw vegetable intake with CHD, HF, or AF. Raw vegetable intake was nominally associated with stroke (odds ratio [95% confidence interval] 0.82 [0.69-0.98] per 1 daily serving increase, p = 0.03), but this association did not pass the corrected significance level. We found consistently null evidence for associations with serum lipids, blood pressure, body mass index, or glycemic traits.

CONCLUSIONS

We found null evidence for associations between genetically predicted vegetable intake with CHD, AF, HF, or cardiometabolic risk factors in this MR study. Raw vegetable intake may reduce risk of stroke, but this warrants more research. True associations between vegetable intake and CVDs cannot be completely ruled out, and future investigations are required for causal inference in nutritional research.

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.

Comparative Analysis of Heart Regeneration: Searching for the Key to Heal the Heart-Part I: Experimental Injury Models to Study Cardiac Regeneration

Cardiovascular diseases are the leading cause of death worldwide, among which, ischemic heart disease is the most prevalent. Myocardial infarction results from occlusion of a coronary artery, which leads to an insufficient blood supply to the myocardium. As is well known, the massive loss of cardiomyocytes cannot be solved due the limited regenerative ability of the adult mammalian heart. In contrast, some lower vertebrate species can regenerate the heart after injury; their study has disclosed some of the involved cell types, molecular mechanisms and signaling pathways during the regenerative process. In this two-part review, we discuss the current state of the principal response in heart regeneration, where several involved processes are essential for full cardiac function in recovery.

Polygenic risk scores point toward potential genetic mechanisms of type 2 myocardial infarction in people with HIV

BACKGROUND

People with human immunodeficiency virus (HIV) infection (PWH) are at higher risk of myocardial infarction (MI) than those without HIV. About half of MIs in PWH are type 2 (T2MI), resulting from mismatch between myocardial oxygen supply and demand, in contrast to type 1 MI (T1MI), which is due to primary plaque rupture or coronary thrombosis. Despite worse survival and rising incidence in the general population, evidence-based treatment recommendations for T2MI are lacking. We used polygenic risk scores (PRS) to explore genetic mechanisms of T2MI compared to T1MI in PWH.

METHODS

We derived 115 PRS for MI-related traits in 9541 PWH enrolled in the Centers for AIDS Research Network of Integrated Clinical Systems cohort with adjudicated T1MI and T2MI. We applied multivariate logistic regression analyses to determine the association with T1MI and T2MI. Based on initial findings, we performed gene set enrichment analysis of the top variants composing PRS associated with T2MI.

RESULTS

We found that T1MI was strongly associated with PRS for cardiovascular disease, lipid profiles, and metabolic traits. In contrast, PRS for alcohol dependence and cholecystitis, significantly enriched in energy metabolism pathways, were predictive of T2MI risk. The association remained after the adjustment for actual alcohol consumption.

CONCLUSIONS

We demonstrate distinct genetic traits associated with T1MI and T2MI among PWH further highlighting their etiological differences and supporting the role of energy regulation in T2MI pathogenesis.

Human gain-of-function variants in HNF1A confer protection from diabetes but independently increase hepatic secretion of atherogenic lipoproteins

Loss-of-function mutations in hepatocyte nuclear factor 1A (HNF1A) are known to cause rare forms of diabetes and alter hepatic physiology through unclear mechanisms. In the general population, 1:100 individuals carry a rare, protein-coding HNF1A variant, most of unknown functional consequence. To characterize the full allelic series, we performed deep mutational scanning of 11,970 protein-coding HNF1A variants in human hepatocytes and clinical correlation with 553,246 exome-sequenced individuals. Surprisingly, we found that ∼1:5 rare protein-coding HNF1A variants in the general population cause molecular gain of function (GOF), increasing the transcriptional activity of HNF1A by up to 50% and conferring protection from type 2 diabetes (odds ratio [OR] = 0.77, p = 0.007). Increased hepatic expression of HNF1A promoted a pro-atherogenic serum profile mediated in part by enhanced transcription of risk genes including ANGPTL3 and PCSK9. In summary, ∼1:300 individuals carry a GOF variant in HNF1A that protects carriers from diabetes but enhances hepatic secretion of atherogenic lipoproteins.

Application of next generation sequencing in cardiology: current and future precision medicine implications

Inherited cardiovascular diseases are highly heterogeneous conditions with multiple genetic loci involved. The application of advanced molecular tools, such as Next Generation Sequencing, has facilitated the genetic analysis of these disorders. Accurate analysis and variant identification are required to maximize the quality of the sequencing data. Therefore, the application of NGS for clinical purposes should be limited to laboratories with a high level of technological expertise and resources. In addition, appropriate gene selection and variant interpretation can result in the highest possible diagnostic yield. Implementation of genetics in cardiology is imperative for the accurate diagnosis, prognosis and management of several inherited disorders and could eventually lead to the realization of precision medicine in this field. However, genetic testing should also be accompanied by an appropriate genetic counseling procedure that clarifies the significance of the genetic analysis results for the proband and his family. In this regard, a multidisciplinary collaboration among physicians, geneticists, and bioinformaticians is imperative. In the present review, we address the current state of knowledge regarding genetic analysis strategies employed in the field of cardiogenetics. Variant interpretation and reporting guidelines are explored. Additionally, gene selection procedures are accessed, with a particular emphasis on information concerning gene-disease associations collected from international alliances such as the Gene Curation Coalition (GenCC). In this context, a novel approach to gene categorization is proposed. Moreover, a sub-analysis is conducted on the 1,502,769 variation records with submitted interpretations in the Clinical Variation (ClinVar) database, focusing on cardiology-related genes. Finally, the most recent information on genetic analysis's clinical utility is reviewed.

Transcriptome-wide association study reveals novel susceptibility genes for coronary atherosclerosis

Background

Genetic risk factors substantially contributed to the development of coronary atherosclerosis. Genome-wide association study (GWAS) has identified many risk loci for coronary atherosclerosis, but the translation of these loci into therapeutic targets is limited for their location in non-coding regions. Here, we aimed to screen the potential coronary atherosclerosis pathogenic genes expressed though TWAS (transcriptome wide association study) and explore the underlying mechanism association.

Methods

Four TWAS approaches (PrediXcan, JTI, UTMOST, and FUSION) were used to screen genes associated with coronary atherosclerosis. Enrichment analysis of TWAS-identified genes was applied through the Metascape website. The summary-data-based Mendelian randomization (SMR) analysis was conducted to provide the evidence of causal relationship between the candidate genes and coronary atherosclerosis. At last, the cell type-specific expression of the intersection genes was examined by using human coronary artery single-cell RNA-seq, interrogating the immune microenvironment of human coronary atherosclerotic plaque at different stages of maturity.

Results

We identified 19 genes by at least three approaches and 1 gene (NBEAL1) by four approaches. Enrichment analysis enriching the genes identified at least by two TWAS approaches, suggesting that these genes were markedly enriched in asthma and leukocyte mediated immunity reaction. Further, the summary-data-based Mendelian randomization (SMR) analysis provided the evidence of causal relationship between NBEAL1 gene and coronary atherosclerosis, confirming the protecting effects of NBEAL1 gene and coronary atherosclerosis. At last, the single cell cluster analysis demonstrated that NBEAL1 gene has differential expressions in macrophages, plasma cells and endothelial cells.

Conclusion

Our study identified the novel genes associated with coronary atherosclerosis and suggested the potential biological function for these genes, providing insightful guidance for further biological investigation and therapeutic approaches development in atherosclerosis-related diseases.

A review of standardized high-throughput cardiovascular phenotyping with a link to metabolism in mice

Cardiovascular diseases cause a high mortality rate worldwide and represent a major burden for health care systems. Experimental rodent models play a central role in cardiovascular disease research by effectively simulating human cardiovascular diseases. Using mice, the International Mouse Phenotyping Consortium (IMPC) aims to target each protein-coding gene and phenotype multiple organ systems in single-gene knockout models by a global network of mouse clinics. In this review, we summarize the current advances of the IMPC in cardiac research and describe in detail the diagnostic requirements of high-throughput electrocardiography and transthoracic echocardiography capable of detecting cardiac arrhythmias and cardiomyopathies in mice. Beyond that, we are linking metabolism to the heart and describing phenotypes that emerge in a set of known genes, when knocked out in mice, such as the leptin receptor (Lepr), leptin (Lep), and Bardet-Biedl syndrome 5 (Bbs5). Furthermore, we are presenting not yet associated loss-of-function genes affecting both, metabolism and the cardiovascular system, such as the RING finger protein 10 (Rfn10), F-box protein 38 (Fbxo38), and Dipeptidyl peptidase 8 (Dpp8). These extensive high-throughput data from IMPC mice provide a promising opportunity to explore genetics causing metabolic heart disease with an important translational approach.

Development of a Structural Equation Model to Examine the Relationships between Genetic Polymorphisms and Cardiovascular Risk Factors

Genome-wide association studies (GWASs) have been used to discover genetic polymorphisms that affect cardiovascular diseases (CVDs). Structural equation modelling (SEM) has been identified as a robust multivariate analysis tool. However, there is a paucity of research that has conducted SEM in African populations. The purpose of this study was to create a model that may be used to examine the relationships between genetic polymorphisms and their respective cardiovascular risk (CVR) factors. The procedure involved three steps. Firstly, the creation of latent variables and the hypothesis model. Next, confirmatory factor analysis (CFA) to examine the relationships between the latent variables, SNPs, dyslipidemia and metabolic syndrome, with their respective indicators. Then finally, model fitting using JASP statistical software v.0.16.4.0. The indicators for the SNPs and dyslipidemia all indicated significant factor loadings, -0.96 to 0.91 (p = <0.001) and 0.92 to 0.96 (p ≤ 0.001), respectively. The indicators for metabolic syndrome also had significant coefficients of 0.20 (p = 0.673), 0.36 (p = 0.645) and 0.15 (p = 0.576), but they were not statistically significant. There were no significant relationships observed between the SNPs, dyslipidemia and metabolic syndrome. The SEM produced an acceptable model according to the fit indices.

Prediction of mammalian tissue-specific CLOCK-BMAL1 binding to E-box DNA motifs

The Brain and Muscle ARNTL-Like 1 protein (BMAL1) forms a heterodimer with either Circadian Locomotor Output Cycles Kaput (CLOCK) or Neuronal PAS domain protein 2 (NPAS2) to act as a master regulator of the mammalian circadian clock gene network. The dimer binds to E-box gene regulatory elements on DNA, activating downstream transcription of clock genes. Identification of transcription factor binding sites and genomic features that correlate to DNA binding by BMAL1 is a challenging problem, given that CLOCK-BMAL1 or NPAS2-BMAL1 bind to several distinct binding motifs (CANNTG) on DNA. Using three different types of tissue-specific machine learning models with features based on (1) DNA sequence, (2) DNA sequence plus DNA shape, and (3) DNA sequence and shape plus histone modifications, we developed an interpretable predictive model of genome-wide BMAL1 binding to E-box motifs and dissected the mechanisms underlying BMAL1-DNA binding. Our results indicated that histone modifications, the local shape of the DNA, and the flanking sequence of the E-box motif are sufficient predictive features for BMAL1-DNA binding. Our models also provide mechanistic insights into tissue specificity of DNA binding by BMAL1.

Identification of allele-specific KIV-2 repeats and impact on Lp(a) measurements for cardiovascular disease risk

The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging. In this study, we present the DRAGEN KIV-2 CN caller, which utilizes short reads. Data across 166 WGS show that the caller has high accuracy, compared to optical mapping and can further phase ~50% of the samples. We compared KIV-2 CN numbers to 24 previously postulated KIV-2 relevant SNVs, revealing that many are ineffective predictors of KIV-2 copy number. Population studies, including USA-based cohorts, showed distinct KIV-2 CN, distributions for European-, African-, and Hispanic-American populations and further underscored the limitations of SNV predictors. We demonstrate that the CN estimates correlate significantly with the available Lp(a) protein levels and that phasing is highly important.

Discovery of Transacting Long Noncoding RNAs That Regulate Smooth Muscle Cell Phenotype

BACKGROUND

Smooth muscle cells (SMC), the major cell type in atherosclerotic plaques, are vital in coronary artery diseases (CADs). SMC phenotypic transition, which leads to the formation of various cell types in atherosclerotic plaques, is regulated by a network of genetic and epigenetic mechanisms and governs the risk of disease. The involvement of long noncoding RNAs (lncRNAs) has been increasingly identified in cardiovascular disease. However, SMC lncRNAs have not been comprehensively characterized, and their regulatory role in SMC state transition remains unknown.

METHODS

A discovery pipeline was constructed and applied to deeply strand-specific RNA sequencing from perturbed human coronary artery SMC with different disease-related stimuli, to allow for the detection of novel lncRNAs. The functional relevance of a select few novel lncRNAs were verified in vitro.

RESULTS

We identified 4579 known and 13 655 de novo lncRNAs in human coronary artery SMC. Consistent with previous long noncoding RNA studies, these lncRNAs overall have fewer exons, are shorter in length than protein-coding genes (pcGenes), and have relatively low expression level. Genomic location of these long noncoding RNA is disproportionately enriched near CAD-related TFs (transcription factors), genetic loci, and gene regulators of SMC identity, suggesting the importance of their function in disease. Two de novo lncRNAs, ZIPPOR (ZEB-interacting suppressor) and TNS1-AS2 (TNS1-antisense 2), were identified by our screen. Combining transcriptional data and in silico modeling along with in vitro validation, we identified CAD gene ZEB2 as a target through which these lncRNAs exert their function in SMC phenotypic transition.

CONCLUSIONS

Expression of a large and diverse set of lncRNAs in human coronary artery SMC are highly dynamic in response to CAD-related stimuli. The dynamic changes in expression of these lncRNAs correspond to alterations in transcriptional programs that are relevant to CAD, suggesting a critical role for lncRNAs in SMC phenotypic transition and human atherosclerotic disease.

Evaluation of rs1748195 ANGPTL3 gene polymorphism in patients with angiographic coronary artery disease compared to healthy individuals

SUBJECT

The Angiopoietin-like 3 (ANGPTL3) gene has been reported to be associated with cardiovascular risk. This study is designed to compare the genetic variant (rs1748195) of the ANGPTL3 gene and the presence of a coronary artery occlusion of >50% in Iranian nation.

METHOD

In this study, 184 patients underwent angiography and 317 healthy individuals were evaluated for polymorphism of rs1748195 the ANGPTL3 gene using Tetra-ARMs PCR. Coronary patients who experience angiography were categorized into two groups: 54 patients who had an angiography indication for the first time and coronary occlusion was <50% (Angio-) and 134 patients who formerly underwent coronary stent implanting at least 1 month before with coronary occlusion of ≥50% that again have an angiography indication (Angio+). In addition, individuals with angio+ are categorized in two groups: (1) non-in-stent restenosis (NISR); patient with a patent stent (N = 92). (2) in-stent restenosis (ISR); in-stent stenosis >50% (N = 42).

RESULT

The fundamental of characteristics of our study design population was categorized based on undergoing angiography or not. In the present study, we investigated that the CC genotype, and also the A allele corresponding to rs1748195 at the ANGPTL3 gene loci, was associated with negative angiogram and directly related to the risk of coronary occlusion >50%. In contrast, this result was not significant in genotypes of ANGPTL3 between non-ISR and ISR groups.

CONCLUSION

The outcomes of this study showed that rs1748195 polymorphism at the ANGPTL3 gene loci is associated with an elevated risk for the existence of a coronary occlusion of >50%.

Evolutionary mismatch and the role of GxE interactions in human disease

Globally, we are witnessing the rise of complex, non-communicable diseases (NCDs) related to changes in our daily environments. Obesity, asthma, cardiovascular disease, and type 2 diabetes are part of a long list of "lifestyle" diseases that were rare throughout human history but are now common. A key idea from anthropology and evolutionary biology-the evolutionary mismatch hypothesis-seeks to explain this phenomenon. It posits that humans evolved in environments that radically differ from the ones experienced by most people today, and thus traits that were advantageous in past environments may now be "mismatched" and disease-causing. This hypothesis is, at its core, a genetic one: it predicts that loci with a history of selection will exhibit "genotype by environment" (GxE) interactions and have differential health effects in ancestral versus modern environments. Here, we discuss how this concept could be leveraged to uncover the genetic architecture of NCDs in a principled way. Specifically, we advocate for partnering with small-scale, subsistence-level groups that are currently transitioning from environments that are arguably more "matched" with their recent evolutionary history to those that are more "mismatched". These populations provide diverse genetic backgrounds as well as the needed levels and types of environmental variation necessary for mapping GxE interactions in an explicit mismatch framework. Such work would make important contributions to our understanding of environmental and genetic risk factors for NCDs across diverse ancestries and sociocultural contexts.

The oft-overlooked cardiovascular complications of inflammatory bowel disease

INTRODUCTION

Inflammatory bowel disease (IBD) may be associated with several extraintestinal comorbidities, including cardiovascular disease (CVD). Chronic inflammation is recognized as an important factor in atherogenesis, thrombosis, and myocarditis.

AREAS COVERED

IBD patients may be at increased risk for developing early atherosclerosis, cardiovascular events, peripheral artery disease, venous thromboembolism, myocarditis, and arrhythmias. Anti-tumor necrosis factor agents and thiopurines have been shown to have a protective effect against acute arterial events, but more research is needed. However, an increased risk of venous thromboembolism and major cardiovascular events has been described with the use of Janus kinase inhibitors.

EXPERT OPINION

CVD risk is slightly increased in patients with IBD, especially during flares. Thromboprophylaxis is strongly recommended in hospitalized patients with active disease as the benefit of anticoagulation outweighs the risk of bleeding. The pathogenetic relationship between CVD and IBD and the impact of IBD drugs on CVD outcomes are not fully elucidated. CVD risk doesn't have the strength to drive a specific IBD treatment. However, proper CVD risk profiling should always be done and the best strategy to manage CVD risk in IBD patients is to combine appropriate thromboprophylaxis with early and durable remission of the underlying IBD.

Impact of cardiovascular health and genetic risk on coronary artery disease in Chinese adults

OBJECTIVE

To examine whether adherence to ideal cardiovascular health (CVH) can mitigate the genetic risk of coronary artery disease (CAD) in non-European populations.

METHODS

Fine and Grey's models were used to calculate HRs and their corresponding 95% CIs, as well as the lifetime risk of CVH metrics across Polygenic Risk Score (PRS) categories.

RESULTS

We included 39 755 individuals aged 30-75 years in Chinese prospective cohorts. 1275 CAD cases were recorded over a mean follow-up of 12.9 years. Compared with unfavourable CVH profile (zero to three ideal CVH metrics), favourable CVH profile (six to seven ideal CVH metrics) demonstrated similar relative effects across PRS categories, with the HRs of 0.40 (95% CI 0.24 to 0.67), 0.41 (95% CI 0.32 to 0.52) and 0.36 (95% CI 0.26 to 0.52) in low (bottom quintile of PRS), intermediate (two to four quintiles of PRS) and high (top quintile of PRS) PRS categories, respectively. For the absolute risk reduction (ARR), individuals with high PRS achieved the greatest benefit from favourable CVH, mitigating the risk to the average level of population (from 21.1% to 8.7%), and the gradient was strengthened in individuals at the top 5% of PRS. Moreover, compared with individuals at low PRS, those at high PRS obtained longer CAD-free years (2.6 vs 1.1) from favourable CVH at the index age of 35 years.

CONCLUSION

Favourable CVH profile reduced the CAD relative risk by similar magnitude across PRS categories, while the ARR from favourable CVH was most pronounced in high PRS category. Attaining favourable CVH should be encouraged for all individuals, especially in individuals with high genetic susceptibility.

Targeting mitochondrial impairment for the treatment of cardiovascular diseases: From hypertension to ischemia-reperfusion injury, searching for new pharmacological targets

Mitochondria and mitochondrial proteins represent a group of promising pharmacological target candidates in the search of new molecular targets and drugs to counteract the onset of hypertension and more in general cardiovascular diseases (CVDs). Indeed, several mitochondrial pathways result impaired in CVDs, showing ATP depletion and ROS production as common traits of cardiac tissue degeneration. Thus, targeting mitochondrial dysfunction in cardiomyocytes can represent a successful strategy to prevent heart failure. In this context, the identification of new pharmacological targets among mitochondrial proteins paves the way for the design of new selective drugs. Thanks to the advances in omics approaches, to a greater availability of mitochondrial crystallized protein structures and to the development of new computational approaches for protein 3D-modelling and drug design, it is now possible to investigate in detail impaired mitochondrial pathways in CVDs. Furthermore, it is possible to design new powerful drugs able to hit the selected pharmacological targets in a highly selective way to rescue mitochondrial dysfunction and prevent cardiac tissue degeneration. The role of mitochondrial dysfunction in the onset of CVDs appears increasingly evident, as reflected by the impairment of proteins involved in lipid peroxidation, mitochondrial dynamics, respiratory chain complexes, and membrane polarization maintenance in CVD patients. Conversely, little is known about proteins responsible for the cross-talk between mitochondria and cytoplasm in cardiomyocytes. Mitochondrial transporters of the SLC25A family, in particular, are responsible for the translocation of nucleotides (e.g., ATP), amino acids (e.g., aspartate, glutamate, ornithine), organic acids (e.g. malate and 2-oxoglutarate), and other cofactors (e.g., inorganic phosphate, NAD⁺, FAD, carnitine, CoA derivatives) between the mitochondrial and cytosolic compartments. Thus, mitochondrial transporters play a key role in the mitochondria-cytosol cross-talk by leading metabolic pathways such as the malate/aspartate shuttle, the carnitine shuttle, the ATP export from mitochondria, and the regulation of permeability transition pore opening. Since all these pathways are crucial for maintaining healthy cardiomyocytes, mitochondrial carriers emerge as an interesting class of new possible pharmacological targets for CVD treatments.

iDHU-Ensem: Identification of dihydrouridine sites through ensemble learning models

Background

Dihydrouridine (D) is one of the most significant uridine modifications that have a prominent occurrence in eukaryotes. The folding and conformational flexibility of transfer RNA (tRNA) can be attained through this modification.

Objective

The modification also triggers lung cancer in humans. The identification of D sites was carried out through conventional laboratory methods; however, those were costly and time-consuming. The readiness of RNA sequences helps in the identification of D sites through computationally intelligent models. However, the most challenging part is turning these biological sequences into distinct vectors.

Methods

The current research proposed novel feature extraction mechanisms and the identification of D sites in tRNA sequences using ensemble models. The ensemble models were then subjected to evaluation using k-fold cross-validation and independent testing.

Results

The results revealed that the stacking ensemble model outperformed all the ensemble models by revealing 0.98 accuracy, 0.98 specificity, 0.97 sensitivity, and 0.92 Matthews Correlation Coefficient. The proposed model, iDHU-Ensem, was also compared with pre-existing predictors using an independent test. The accuracy scores have shown that the proposed model in this research study performed better than the available predictors.

Conclusion

The current research contributed towards the enhancement of D site identification capabilities through computationally intelligent methods. A web-based server, iDHU-Ensem, was also made available for the researchers at https://taseersuleman-idhu-ensem-idhu-ensem.streamlit.app/.

Extensive Summary of the Important Roles of Indole Propionic Acid, a Gut Microbial Metabolite in Host Health and Disease

Increasing evidence suggests that metabolites produced by the gut microbiota play a crucial role in host-microbe interactions. Dietary tryptophan ingested by the host enters the gut, where indole-like metabolites such as indole propionic acid (IPA) are produced under deamination by commensal bacteria. Here, we summarize the IPA-producing bacteria, dietary patterns on IPA content, and functional roles of IPA in various diseases. IPA can not only stimulate the expression of tight junction (TJ) proteins to enhance gut barrier function and inhibit the penetration of toxic factors, but also modulate the immune system to exert anti-inflammatory and antioxidant effects to synergistically regulate body physiology. Moreover, IPA can act on target organs through blood circulation to form the gut-organ axis, which helps maintain systemic homeostasis. IPA shows great potential for the diagnosis and treatment of various clinical diseases, such as NAFLD, Alzheimer's disease, and breast cancer. However, the therapeutic effect of IPA depends on dose, target organ, or time. In future studies, further work should be performed to explore the effects and mechanisms of IPA on host health and disease to further improve the existing treatment program.

The missing link between genetic association and regulatory function

The genetic basis of most traits is highly polygenic and dominated by non-coding alleles. It is widely assumed that such alleles exert small regulatory effects on the expression of cis-linked genes. However, despite the availability of gene expression and epigenomic datasets, few variant-to-gene links have emerged. It is unclear whether these sparse results are due to limitations in available data and methods, or to deficiencies in the underlying assumed model. To better distinguish between these possibilities, we identified 220 gene-trait pairs in which protein-coding variants influence a complex trait or its Mendelian cognate. Despite the presence of expression quantitative trait loci near most GWAS associations, by applying a gene-based approach we found limited evidence that the baseline expression of trait-related genes explains GWAS associations, whether using colocalization methods (8% of genes implicated), transcription-wide association (2% of genes implicated), or a combination of regulatory annotations and distance (4% of genes implicated). These results contradict the hypothesis that most complex trait-associated variants coincide with homeostatic expression QTLs, suggesting that better models are needed. The field must confront this deficit and pursue this 'missing regulation.'

Familial Hypercholesterolemia and Its Current Diagnostics and Treatment Possibilities: A Literature Analysis

Familial hypercholesterolemia (FH) is a common, inherited disorder of cholesterol metabolism. This pathology is usually an autosomal dominant disorder and is caused by inherited mutations in the APOB, LDLR, and PCSK9 genes. Patients can have a homozygous or a heterozygous genotype, which determines the severity of the disease and the onset age of cardiovascular disease (CVD) manifestations. The incidence of heterozygous FH is 1: 200-250, whereas that of homozygous FH is 1: 100.000-160.000. Unfortunately, FH is often diagnosed too late and after the occurrence of a major coronary event. FH may be suspected in patients with elevated blood low-density lipoprotein cholesterol (LDL-C) levels. Moreover, there are other criteria that help to diagnose FH. For instance, the Dutch Lipid Clinical Criteria are a helpful diagnostic tool that is used to diagnose FH. FH often leads to the development of early cardiovascular disease and increases the risk of sudden cardiac death. Therefore, early diagnosis and treatment of this disease is very important. Statins, ezetimibe, bile acid sequestrants, niacin, PCSK9 inhibitors (evolocumab and alirocumab), small-interfering-RNA-based therapeutics (inclisiran), lomitapide, mipomersen, and LDL apheresis are several of the available treatment possibilities that lower LDL-C levels. It is important to say that the timeous lowering of LDL-C levels can reduce the risk of cardiovascular events and mortality in patients with FH. Therefore, it is essential to increase awareness of FH in order to reduce the burden of acute coronary syndrome (ACS).

Cardiovascular disease and subsequent risk of psychiatric disorders: a nationwide sibling-controlled study

Background

The association between cardiovascular disease (CVD) and selected psychiatric disorders has frequently been suggested while the potential role of familial factors and comorbidities in such association has rarely been investigated.

Methods

We identified 869,056 patients newly diagnosed with CVD from 1987 to 2016 in Sweden with no history of psychiatric disorders, and 910,178 full siblings of these patients as well as 10 individually age- and sex-matched unrelated population controls (N = 8,690,560). Adjusting for multiple comorbid conditions, we used flexible parametric models and Cox models to estimate the association of CVD with risk of all subsequent psychiatric disorders, comparing rates of first incident psychiatric disorder among CVD patients with rates among unaffected full siblings and population controls.

Results

The median age at diagnosis was 60 years for patients with CVD and 59.2% were male. During up to 30 years of follow-up, the crude incidence rates of psychiatric disorder were 7.1, 4.6, and 4.0 per 1000 person-years for patients with CVD, their siblings and population controls. In the sibling comparison, we observed an increased risk of psychiatric disorder during the first year after CVD diagnosis (hazard ratio [HR], 2.74; 95% confidence interval [CI], 2.62-2.87) and thereafter (1.45; 95% CI, 1.42-1.48). Increased risks were observed for all types of psychiatric disorders and among all diagnoses of CVD. We observed similar associations in the population comparison. CVD patients who developed a comorbid psychiatric disorder during the first year after diagnosis were at elevated risk of subsequent CVD death compared to patients without such comorbidity (HR, 1.55; 95% CI, 1.44-1.67).

Conclusions

Patients diagnosed with CVD are at an elevated risk for subsequent psychiatric disorders independent of shared familial factors and comorbid conditions. Comorbid psychiatric disorders in patients with CVD are associated with higher risk of cardiovascular mortality suggesting that surveillance and treatment of psychiatric comorbidities should be considered as an integral part of clinical management of newly diagnosed CVD patients.

Funding

This work was supported by the EU Horizon 2020 Research and Innovation Action Grant (CoMorMent, grant no. 847776 to UV, PFS, and FF), Grant of Excellence, Icelandic Research Fund (grant no. 163362-051 to UV), ERC Consolidator Grant (StressGene, grant no. 726413 to UV), Swedish Research Council (grant no. D0886501 to PFS), and US NIMH R01 MH123724 (to PFS).

Genetic Factors for Coronary Heart Disease and Their Mechanisms: A Meta-Analysis and Comprehensive Review of Common Variants from Genome-Wide Association Studies

Genome-wide association studies (GWAS) have discovered 163 loci related to coronary heart disease (CHD). Most GWAS have emphasized pathways related to single-nucleotide polymorphisms (SNPs) that reached genome-wide significance in their reports, while identification of CHD pathways based on the combination of all published GWAS involving various ethnicities has yet to be performed. We conducted a systematic search for articles with comprehensive GWAS data in the GWAS Catalog and PubMed, followed by a meta-analysis of the top recurring SNPs from ≥2 different articles using random or fixed-effect models according to Cochran Q and I² statistics, and pathway enrichment analysis. Meta-analyses showed significance for 265 of 309 recurring SNPs. Enrichment analysis returned 107 significant pathways, including lipoprotein and lipid metabolisms (rs7412, rs6511720, rs11591147, rs1412444, rs11172113, rs11057830, rs4299376), atherogenesis (rs7500448, rs6504218, rs3918226, rs7623687), shared cardiovascular pathways (rs72689147, rs1800449, rs7568458), diabetes-related pathways (rs200787930, rs12146487, rs6129767), hepatitis C virus infection/hepatocellular carcinoma (rs73045269/rs8108632, rs56062135, rs188378669, rs4845625, rs11838776), and miR-29b-3p pathways (rs116843064, rs11617955, rs146092501, rs11838776, rs73045269/rs8108632). In this meta-analysis, the identification of various genetic factors and their associated pathways associated with CHD denotes the complexity of the disease. This provides an opportunity for the future development of novel CHD genetic risk scores relevant to personalized and precision medicine.

Myocardial infarction from a tissue engineering and regenerative medicine point of view: A comprehensive review on models and treatments

In the modern world, myocardial infarction is one of the most common cardiovascular diseases, which are responsible for around 18 million deaths every year or almost 32% of all deaths. Due to the detrimental effects of COVID-19 on the cardiovascular system, this rate is expected to increase in the coming years. Although there has been some progress in myocardial infarction treatment, translating pre-clinical findings to the clinic remains a major challenge. One reason for this is the lack of reliable and human representative healthy and fibrotic cardiac tissue models that can be used to understand the fundamentals of ischemic/reperfusion injury caused by myocardial infarction and to test new drugs and therapeutic strategies. In this review, we first present an overview of the anatomy of the heart and the pathophysiology of myocardial infarction, and then discuss the recent developments on pre-clinical infarct models, focusing mainly on the engineered three-dimensional cardiac ischemic/reperfusion injury and fibrosis models developed using different engineering methods such as organoids, microfluidic devices, and bioprinted constructs. We also present the benefits and limitations of emerging and promising regenerative therapy treatments for myocardial infarction such as cell therapies, extracellular vesicles, and cardiac patches. This review aims to overview recent advances in three-dimensional engineered infarct models and current regenerative therapeutic options, which can be used as a guide for developing new models and treatment strategies.

Knowledge, Attitude, and Practice Toward Cardiovascular Diseases in the Lebanese Population

Background & Objective:

Cardiovascular diseases (CVD) are the leading cause of death globally. Assessing CVD knowledge, attitude, and practice (KAP) is necessary to spread awareness about CVD in Lebanon, their corresponding risk factors, and behaviors in which individuals can avoid or minimize the possibility of developing a CVD.

Subjects & Methods:

This was a case-control analytical study that targeted 921 CVD and non-CVD subjects. A questionnaire form was used to collect data related to patients’ demographics, socioeconomic status, habits, medical and family history, KAP towards CVD, and source of information. Data was analyzed using SPSS v.25.

Results:

Data from 921 participants were distributed over the CVD group (52.6% males aged 58.3 ± 13.7 years [n = 460]) and the non-CVD group (47.7% males aged 36.3 ± 15.4 years [n = 461]). CVD patients were significantly older than non-CVD subjects (p < 0.001). All three KAP scores of both groups were of poor to fair levels. Both CVD knowledge and attitude mean scores in CVD patients (26.6 ± 5.2 over 40 [66.50%] and 63.3 ± 10.2 over 85 [74.47%], respectively) were significantly higher than the ones of non-CVD subjects (23.5 ± 7.9 over 40 [58.75%] and 61.4 ± 12.4 over 85 [72.74%], respectively, p < 0.001). However, the CVD mean practice score was significantly lower in CVD patients (6.0 ± 1.7 over 9 [66.67%]) than the one of non-CVD subjects (6.3 ± 2.2 over 9 [70.00%] p < 0.001). Mostly, educational level (p < 0.001), governorate (p < 0.01), and smoking (p < 0.001) were predictors of KAP CVD in both groups.

Conclusion:

With an overall limited knowledge, attitude, and practice toward CVDs, the Lebanese population (with CVD or non-CVD) needs targeted national campaigns about CVD according to the identified predictors of CVD KAP to prevent and to alleviate the complications due to CVDs.

Unfolding the genotype-to-phenotype black box of cardiovascular diseases through cross-scale modeling

Complex traits such as cardiovascular diseases (CVD) are the results of complicated processes jointly affected by genetic and environmental factors. Genome-wide association studies (GWAS) identified genetic variants associated with diseases but usually did not reveal the underlying mechanisms. There could be many intermediate steps at epigenetic, transcriptomic, and cellular scales inside the black box of genotype-phenotype associations. In this article, we present a machine-learning-based cross-scale framework GRPath to decipher putative causal paths (pcPaths) from genetic variants to disease phenotypes by integrating multiple omics data. Applying GRPath on CVD, we identified 646 and 549 pcPaths linking putative causal regions, variants, and gene expressions in specific cell types for two types of heart failure, respectively. The findings suggest new understandings of coronary heart disease. Our work promoted the modeling of tissue- and cell type-specific cross-scale regulation to uncover mechanisms behind disease-associated variants, and provided new findings on the molecular mechanisms of CVD.

•

We defined one type of cross-scale genotype-to-phenotype regulation path

•

We designed a framework GRPath to uncover putative regulation paths for diseases

•

GRPath helped uncover molecular mechanisms for two major types of heart failure

A glance at the application of CRISPR/Cas9 gene-editing technology in cardiovascular diseases

Cardiovascular diseases (CVDs) remain major causes of global mortality in the world. Genetic approaches have succeeded in discovery of the molecular basis of an increasing number of cardiac diseases. Genome editing strategies are one of the most effective methods for assisting therapeutic approaches. Potential therapeutic methods of correcting disease-causing mutations or of knocking out specific genes as approaches for the prevention of CVDs have gained substantial attention using genome editing techniques. Recently, the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system has become the most widely used genome-editing technology in molecular biology due to its benefits such as simple design, high efficiency, good repeatability, short-cycle, and costeffectiveness. In the present review, we discuss on the possibilities of applying the CRISPR/Cas9 genome editing tool in the CVDs.

Cardiovascular disease in chronic obstructive pulmonary disease: a narrative review

Patients with chronic obstructive pulmonary disease (COPD) are at increased risk of cardiovascular disease (CVD) and concomitant disease leads to reduced quality of life, increased hospitalisations and worse survival. Acute pulmonary exacerbations are an important contributor to COPD burden and are associated with increased cardiovascular (CV) events. Both COPD and CVD represent a significant global disease impact and understanding the relationship between the two could potentially reduce this burden. The association between CVD and COPD could be a consequence of (1) shared risk factors (environmental and/or genetic) (2) shared pathophysiological pathways (3) coassociation from a high prevalence of both diseases (4) adverse effects (including pulmonary exacerbations) of COPD contributing to CVD and (5) CVD medications potentially worsening COPD and vice versa. CV risk in COPD has traditionally been associated with increasing disease severity, but there are other relevant COPD subtype associations including radiological subtypes, those with frequent pulmonary exacerbations and novel disease clusters. While the prevalence of CVD is high in COPD populations, it may be underdiagnosed, and improved risk prediction, diagnosis and treatment optimisation could lead to improved outcomes. This state-of-the-art review will explore the incidence/prevalence, COPD subtype associations, shared pathophysiology and genetics, risk prediction, and treatment of CVD in COPD.