Gene expression analysis of cardiovascular diseases: novel insights into biology and clinical applications

CRISPR-Cas9 in Cardiovascular Medicine: Unlocking New Potential for Treatment

Cardiovascular diseases (CVDs) remain a significant global health challenge, with many current treatments addressing symptoms rather than the genetic roots of these conditions. The advent of CRISPR-Cas9 technology has revolutionized genome editing, offering a transformative approach to targeting disease-causing mutations directly. This article examines the potential of CRISPR-Cas9 in the treatment of various CVDs, including atherosclerosis, arrhythmias, cardiomyopathies, hypertension, and Duchenne muscular dystrophy (DMD). The technology's ability to correct single-gene mutations with high precision and efficiency positions it as a groundbreaking tool in cardiovascular therapy. Recent developments have extended the capabilities of CRISPR-Cas9 to include mitochondrial genome editing, a critical advancement for addressing mitochondrial dysfunctions often linked to cardiovascular disorders. Despite its promise, significant challenges remain, including off-target effects, ethical concerns, and limitations in delivery methods, which hinder its translation into clinical practice. This article also explores the ethical and regulatory considerations surrounding gene editing technologies, emphasizing the implications of somatic versus germline modifications. Future research efforts should aim to enhance the accuracy of CRISPR-Cas9, improve delivery systems for targeted tissues, and ensure the safety and efficacy of treatments in the long term. Overcoming these obstacles could enable CRISPR-Cas9 to not only treat but also potentially cure genetically driven cardiovascular diseases, heralding a new era in precision medicine for cardiovascular health.

Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine

Personalized interventions are deemed vital given the intricate characteristics, advancement, inherent genetic composition, and diversity of cardiovascular diseases (CVDs). The appropriate utilization of artificial intelligence (AI) and machine learning (ML) methodologies can yield novel understandings of CVDs, enabling improved personalized treatments through predictive analysis and deep phenotyping. In this study, we proposed and employed a novel approach combining traditional statistics and a nexus of cutting-edge AI/ML techniques to identify significant biomarkers for our predictive engine by analyzing the complete transcriptome of CVD patients. After robust gene expression data pre-processing, we utilized three statistical tests (Pearson correlation, Chi-square test, and ANOVA) to assess the differences in transcriptomic expression and clinical characteristics between healthy individuals and CVD patients. Next, the recursive feature elimination classifier assigned rankings to transcriptomic features based on their relation to the case-control variable. The top ten percent of commonly observed significant biomarkers were evaluated using four unique ML classifiers (Random Forest, Support Vector Machine, Xtreme Gradient Boosting Decision Trees, and k-Nearest Neighbors). After optimizing hyperparameters, the ensembled models, which were implemented using a soft voting classifier, accurately differentiated between patients and healthy individuals. We have uncovered 18 transcriptomic biomarkers that are highly significant in the CVD population that were used to predict disease with up to 96% accuracy. Additionally, we cross-validated our results with clinical records collected from patients in our cohort. The identified biomarkers served as potential indicators for early detection of CVDs. With its successful implementation, our newly developed predictive engine provides a valuable framework for identifying patients with CVDs based on their biomarker profiles.

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.

Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility

Atrial fibrillation (AF) and heart failure (HF) contribute to about 45% of all cardiovascular disease (CVD) deaths in the USA and around the globe. Due to the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. To improve the deciphering of CVD mechanisms, we need to deeply investigate well-known and identify novel genes that are responsible for CVD development. With the advancements in sequencing technologies, genomic data have been generated at an unprecedented pace to foster translational research. Correct application of bioinformatics using genomic data holds the potential to reveal the genetic underpinnings of various health conditions. It can help in the identification of causal variants for AF, HF, and other CVDs by moving beyond the one-gene one-disease model through the integration of common and rare variant association, the expressed genome, and characterization of comorbidities and phenotypic traits derived from the clinical information. In this study, we examined and discussed variable genomic approaches investigating genes associated with AF, HF, and other CVDs. We collected, reviewed, and compared high-quality scientific literature published between 2009 and 2022 and accessible through PubMed/NCBI. While selecting relevant literature, we mainly focused on identifying genomic approaches involving the integration of genomic data; analysis of common and rare genetic variants; metadata and phenotypic details; and multi-ethnic studies including individuals from ethnic minorities, and European, Asian, and American ancestries. We found 190 genes associated with AF and 26 genes linked to HF. Seven genes had implications in both AF and HF, which are SYNPO2L, TTN, MTSS1, SCN5A, PITX2, KLHL3, and AGAP5. We listed our conclusion, which include detailed information about genes and SNPs associated with AF and HF.

Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for translational research and precision medicine

Cardiovascular disease (CVD) is the leading cause of mortality and loss of disability adjusted life years (DALYs) globally. CVDs like Heart Failure (HF) and Atrial Fibrillation (AF) are associated with physical effects on the heart muscles. As a result of the complex nature, progression, inherent genetic makeup, and heterogeneity of CVDs, personalized treatments are believed to be critical. Rightful application of artificial intelligence (AI) and machine learning (ML) approaches can lead to new insights into CVDs for providing better personalized treatments with predictive analysis and deep phenotyping. In this study we focused on implementing AI/ML techniques on RNA-seq driven gene-expression data to investigate genes associated with HF, AF, and other CVDs, and predict disease with high accuracy. The study involved generating RNA-seq data derived from the serum of consented CVD patients. Next, we processed the sequenced data using our RNA-seq pipeline and applied GVViZ for gene-disease data annotation and expression analysis. To achieve our research objectives, we developed a new Findable, Accessible, Intelligent, and Reproducible (FAIR) approach that includes a five-level biostatistical evaluation, primarily based on the Random Forest (RF) algorithm. During our AI/ML analysis, we have fitted, trained, and implemented our model to classify and distinguish high-risk CVD patients based on their age, gender, and race. With the successful execution of our model, we predicted the association of highly significant HF, AF, and other CVDs genes with demographic variables.

RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

Background

Heart failure (HF) is one of the most common complications of cardiovascular diseases (CVDs) and among the leading causes of death in the US. Many other CVDs can lead to increased mortality as well. Investigating the genetic epidemiology and susceptibility to CVDs is a central focus of cardiology and biomedical life sciences. Several studies have explored expression of key CVD genes specially in HF, yet new targets and biomarkers for early diagnosis are still missing to support personalized treatment. Lack of gender-specific cardiac biomarker thresholds in men and women may be the reason for CVD underdiagnosis in women, and potentially increased morbidity and mortality as a result, or conversely, an overdiagnosis in men. In this context, it is important to analyze the expression and enrichment of genes with associated phenotypes and disease-causing variants among high-risk CVD populations.

Methods

We performed RNA sequencing focusing on key CVD genes with a great number of genetic associations to HF. Peripheral blood samples were collected from a broad age range of adult male and female CVD patients. These patients were clinically diagnosed with CVDs and CMS/HCC HF, as well as including cardiomyopathy, hypertension, obesity, diabetes, asthma, high cholesterol, hernia, chronic kidney, joint pain, dizziness and giddiness, osteopenia of multiple sites, chest pain, osteoarthritis, and other diseases.

Results

We report RNA-seq driven case–control study to analyze patterns of expression in genes and differentiating the pathways, which differ between healthy and diseased patients. Our in-depth gene expression and enrichment analysis of RNA-seq data from patients with mostly HF and other CVDs on differentially expressed genes and CVD annotated genes revealed 4,885 differentially expressed genes (DEGs) and regulation of 41 genes known for HF and 23 genes related to other CVDs, with 15 DEGs as significantly expressed including four genes already known (FLNA, CST3, LGALS3, and HBA1) for HF and CVDs with the enrichment of many pathways. Furthermore, gender and ethnic group specific analysis showed shared and unique genes between the genders, and among different races. Broadening the scope of the results in clinical settings, we have linked the CVD genes with ICD codes.

Conclusions

Many pathways were found to be enriched, and gender-specific analysis showed shared and unique genes between the genders. Additional testing of these genes may lead to the development of new clinical tools to improve diagnosis and prognosis of CVD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00367-8.

Insight into atrial fibrillation through analysis of the coding transcriptome in humans

Atrial fibrillation is the most common sustained cardiac arrhythmia in humans, and its prevalence continues to increase because of the aging of the world population. Much still needs to be learned about the molecular pathways involved in the development and the persistence of the disease. Analysis of the transcriptome of cardiac tissue has provided valuable insight into diverse aspects of atrial remodeling, in particular concerning electrical remodeling-related to ion channels-and structural remodeling identified by dysregulation of processes linked to inflammation, fibrosis, oxidative stress, and thrombogenesis. The huge amount of data produced by these studies now represents a valuable source for the identification of novel potential therapeutic targets. In addition, the shift from cardiac tissue to peripheral blood as a substrate for transcriptome analysis revealed this strategy as a promising tool for improved diagnosis and therefore better patient care.

Single-molecule analysis of nucleic acid biomarkers - A review

Nucleic acids are important biomarkers for disease detection, monitoring, and treatment. Advances in technologies for nucleic acid analysis have enabled discovery and clinical implementation of nucleic acid biomarkers. However, challenges remain with technologies for nucleic acid analysis, thereby limiting the use of nucleic acid biomarkers in certain contexts. Here, we review single-molecule technologies for nucleic acid analysis that can be used to overcome these challenges. We first discuss the various types of nucleic acid biomarkers important for clinical applications and conventional technologies for nucleic acid analysis. We then discuss technologies for single-molecule in vitro and in situ analysis of nucleic acid biomarkers. Finally, we discuss other ultra-sensitive techniques for nucleic acid biomarker detection.

Extra Virgin Olive Oil: Lesson from Nutrigenomics

Extra virgin olive oil (EVOO) consumption has a beneficial effect on human health, especially for prevention of cardiovascular disease and metabolic disorders. Here we underscore the peculiar importance of specific cultivars used for EVOO production since biodiversity among cultivars in terms of fatty acids and polyphenols content could differently impact on the metabolic homeostasis. In this respect, the nutrigenomic approach could be very useful to fully dissect the pathways modulated by different EVOO cultivars in terms of mRNA and microRNA transcriptome. The identification of genes and miRNAs modulated by specific EVOO cultivars could also help to discover novel nutritional biomarkers for prevention and/or prognosis of human disease. Thus, the nutrigenomic approach depicts a novel scenario to investigate if a specific EVOO cultivar could have a positive effect on human health by preventing the onset of cardiovascular disease and/or chronic inflammatory disorders also leading to cancer.

Endothelial nitric oxide synthase gene polymorphisms are associated with cardiovascular risks in prehypertensives

Though endothelial nitric oxide synthase (eNOS) gene polymorphism is documented in the causation of hypertension, its role in prehypertension has not been investigated. The present study was conducted in 172 subjects divided into prehypertensives (n = 57) and normotensives (n = 115). Cardiovascular (CV) parameters including baroreflex sensitivity (BRS) by continuous BP variability assessment and sympathovagal imbalance (SVI) by heart rate variability analysis were recorded. Biochemical parameters for insulin resistance (homeostatic model for assessment of insulin resistance), oxidative stress, lipid risk factors, renin, and inflammatory parameters were measured. Genotyping for eNOS polymorphisms rs1799983 (298G>T) and rs2070744 (-786T>C) was performed by polymerase chain reaction-restriction fragment length polymorphism method. Multiple regression analysis was done to assess the association between SVI and metabolic markers, and multivariate logistic regression was done to determine the prediction of prehypertension status by genotype, BRS, and ratio of low-frequency to high-frequency in these subjects. The BP variability, heart rate variability, and biochemical parameters were significantly altered in prehypertensives. The eNOS polymorphisms were found to be associated with prehypertension. BRS, the marker of SVI, was significantly associated with BP, homeostatic model for assessment of insulin resistance, and tumor necrosis factor alpha in 298GG genotype of prehypertensive population. The eNOS gene polymorphisms appear to be associated with prehypertension. 298G>T and -786T>C contribute to SVI in young prehypertensives attributed by insulin resistance and inflammation. The CV risks were associated with prehypertension status in prehypertensives expressing both 298GG and -786TT genotypes. Association of CV risks with SVI appears to be stronger in prehypertensives expressing GG genotype.

Understanding the progression of atherosclerosis through gene profiling and co-expression network analysis in Apob(tm2Sgy)Ldlr(tm1Her) double knockout mice

The objective of the study was to gain molecular insights into the progression of atherosclerosis in Apob(tm2Sgy)Ldlr(tm1Her) mice, using transcriptome profiles. Weighted gene co network analysis (WGCNA) and time course analysis using limma were used to study disease progression from 0 to 20weeks. Five co-expression modules were identified by WGCNA using the expression values of 2153 genes. Genes associated with autophagy, endoplasmic reticulum stress, inflammation and lipid metabolism were differentially expressed at early stages of atherosclerosis. Time course analysis highlighted activation of inflammatory gene signaling at 4weeks, cell proliferation and calcification at 8weeks, amyloid like structures and oxidative stress at 14weeks and enhanced production of inflammatory cytokines at 20weeks. Our results suggest that maximum gene perturbations occur during early atherosclerosis which could be the danger signals associated with subclinical disease. Understanding these genes and associated pathways can help in improvement of diagnostic and therapeutic targets for atherosclerosis.

Effect of olive oil phenolic compounds on the expression of blood pressure-related genes in healthy individuals

PURPOSE

To investigate whether the ingestion of olive oil having different phenolic contents influences the expression of blood pressure-related genes, involved in the renin-angiotensin-aldosterone system, in healthy humans.

METHODS

A randomized, double-blind, crossover human trial with 18 healthy subjects, who ingested 25 mL/day of olive oils (1) high (366 mg/kg, HPC) and (2) low (2.7 mg/kg, LPC) in phenolic compounds for 3 weeks, preceded by 2-week washout periods. Determination of selected blood pressure-related gene expression in peripheral blood mononuclear cells (PBMNC) by qPCR, blood pressure and systemic biomarkers.

RESULTS

HPC decreased systolic blood pressure compared to pre-intervention values and to LPC, and maintained diastolic blood pressure values compared to LPC. HPC decreased ACE and NR1H2 gene expressions compared with pre-intervention values, and IL8RA gene expression compared with LPC.

CONCLUSIONS

The introduction to the diet of an extra-virgin olive oil rich in phenolic compounds modulates the expression of some of the genes related to the renin-angiotensin-aldosterone system. These changes could underlie the decrease in systolic blood pressure observed.

Regulation of smooth muscle cells in development and vascular disease: current therapeutic strategies

Vascular smooth muscle cells (SMCs) exhibit extensive phenotypic diversity and rapid growth during embryonic development, but maintain a quiescent, differentiated state in adult. The pathogenesis of vascular proliferative diseases involves the proliferation and migration of medial vascular SMCs into the vessel intima, possibly reinstating their embryonic gene expression programs. Multiple mitogenic stimuli induce vascular SMC proliferation through cell cycle progression. Therapeutic strategies targeting cell cycle progression and mitogenic stimuli have been developed and evaluated in animal models of atherosclerosis and vascular injury, and several clinical studies. Recent discoveries on the recruitment of vascular progenitor cells to the sites of vascular injury suggest new therapeutic potentials of progenitor cell-based therapies to accelerate re-endothelialization and prevent engraftment of SMC-lineage progenitor cells. Owing to the complex and multifactorial nature of SMC regulation, combinatorial antiproliferative approaches are likely to be used in the future in order to achieve maximal efficacy and reduce toxicity.

Network topology reveals key cardiovascular disease genes

The structure of protein-protein interaction (PPI) networks has already been successfully used as a source of new biological information. Even though cardiovascular diseases (CVDs) are a major global cause of death, many CVD genes still await discovery. We explore ways to utilize the structure of the human PPI network to find important genes for CVDs that should be targeted by drugs. The hope is to use the properties of such important genes to predict new ones, which would in turn improve a choice of therapy. We propose a methodology that examines the PPI network wiring around genes involved in CVDs. We use the methodology to identify a subset of CVD-related genes that are statistically significantly enriched in drug targets and "driver genes." We seek such genes, since driver genes have been proposed to drive onset and progression of a disease. Our identified subset of CVD genes has a large overlap with the Core Diseasome, which has been postulated to be the key to disease formation and hence should be the primary object of therapeutic intervention. This indicates that our methodology identifies "key" genes responsible for CVDs. Thus, we use it to predict new CVD genes and we validate over 70% of our predictions in the literature. Finally, we show that our predicted genes are functionally similar to currently known CVD drug targets, which confirms a potential utility of our methodology towards improving therapy for CVDs.

Microarray analysis in cardiac arrhythmias: a new perspective?

The opportunity to distinguish an accurate set of genes associated with multigenic diseases such as cardiomyopathies or cardiac arrhythmias was very limited before the genomic era. Numerous methods of measuring RNA abundance exist, including northern blotting, multiplex polymerase chain reaction (PCR), and quantitative real-time reverse transcriptase-PCR. However, these techniques might be used to assess the expression levels of only 10-50 genes at time. Today, DNA microarrays provide us with opportunity to simultaneously analyze tens of thousands of genes, giving a remarkable possibility to investigate the genomic contribution to cardiovascular diseases. A particular tissue at any stage of health or disease may be used to generate a genomic profile. Microarray techniques are already used in infectious diseases, oncology, and pharmacology to facilitate clinicians, risk-stratify patients, as well as to predict and assess therapeutic responses to drugs. In this paper, we describe recent advances in the use of various types of microarray technique in the diagnosis of arrhythmogenic heart disease. We also highlight other strategies and methods of differential gene typing comparing with pros and cons of microarray analysis.

Pharmacogenetics of statins: achievements, whole-genome analyses and future perspectives

Statins are the most commonly prescribed class of drug worldwide and therapy is highly effective in reducing low-density lipoprotein cholesterol levels and cardiovascular events. However, there is large variability in clinical response to statin treatment. Recent research provides evidence that genetic variation contributes to this variable response to statin treatment. Until recently, pharmacogenetic studies have used mainly candidate gene approaches to investigate these effects. Since candidate gene studies explain only a small part of the observed variation and results have often been inconsistent, genome-wide association (GWA) studies may be a better approach. In this paper the most important candidate gene studies and the first published GWA studies assessing statin response are discussed. Moreover, we describe the PHASE study, an EU-funded GWA study that will investigate the genetic variation responsible for the variation in response to pravastatin in a large randomized clinical trial.

Next steps in cardiovascular disease genomic research--sequencing, epigenetics, and transcriptomics

BACKGROUND

Genomic research in cardiovascular disease (CVD) has progressed rapidly over the last 5 years. In most cases, however, these groundbreaking observations have not yet been accompanied by clinically applicable tools for risk prediction, diagnosis, or therapeutic interventions.

CONTENT

We reviewed the scientific literature published in English for novel methods and promising genomic targets that would permit large-scale screening and follow-up of recent genomic findings for CVD. We anticipate that advances in 3 key areas will be critical for the success of these projects. First, exome-centered and whole-genome next-generation sequencing will identify rare and novel genetic variants associated with CVD and its risk factors. Improvements in methods will also greatly advance the field of epigenetics and gene expression in humans. Second, research is increasingly acknowledging that static DNA sequence variation explains only a fraction of the inherited phenotype. Therefore, we expect that multiple epigenetic and gene expression signatures will be related to CVD in experimental and clinical settings. Leveraging existing large-scale consortia and clinical biobanks in combination with electronic health records holds promise for integrating epidemiological and clinical genomics data. Finally, a systems biology approach will be needed to integrate the accumulated multidimensional data.

SUMMARY

Novel methods in sequencing, epigenetics, and transcriptomics, plus unprecedented large-scale cooperative efforts, promise to generate insights into the complexity of CVD. The rapid accumulation and integration of knowledge will shed light on a considerable proportion of the missing heritability for CVD.

Correlations between clinical variables and gene-expression profiles in carotid plaque instability

OBJECTIVE

Strokes, a major cause of disability, are often caused by embolism from unstable carotid plaques. The aim of this study was to validate a biobank of human carotid endarterectomies as a platform for further exploration of pathways for plaque instability. For this purpose, we investigated the relationship between clinical parameters of plaque instability and expression of genes previously shown to be associated with either plaque instability or healing processes in the vessel wall.

METHODS

A database of clinical information and gene-expression microarray data from 106 carotid endarterectomies were used.

RESULTS

Expression of matrix metalloproteinase (MMP)-9 and MMP-7 was 100-fold higher in plaques than in normal artery. In general, genes associated with inflammation (such as RANKL and CD68) were overexpressed in symptomatic compared with asymptomatic plaques. Plaques obtained from patients undergoing surgery within 2 weeks after an embolic event showed up-regulation of genes involved in healing reactions in the vessel wall (including elastin and collagen). Statin treatment, as well as echodense lesions, were associated with a more stable phenotype.

CONCLUSION

Here, we demonstrate that gene-expression profiles reflect clinical parameters. Our results suggest that microarray technology and clinical variables can be used for the future identification of central molecular pathways in plaque instability.

The emerging role of microRNAs in drug responses

In recent years, pharmacogenomic research has begun to integrate genetics, gene expression and pharmacological phenotypes. MicroRNAs (miRNAs), 21- to 25-nucleotide, non-coding RNAs that are present in almost all metazoan genomes, are a class of gene regulators that downregulate gene expression at the post-transcriptional level. Experimental evidence for the role of miRNAs in regulating pharmacology-related genes and drug responses is increasing. Given the universal roles of miRNAs in various diseases, including cancer, miRNAs (eg, chemotherapy) are anticipated to have potential therapeutic effects in various diseases. The incorporation of miRNAs into pharmacogenomic research could provide improved insight into drug responses. However, more studies are necessary to evaluate the effects of these molecules in patients.

Genomic approaches to coronary artery disease

Coronary artery disease (CAD) is a leading cause of death and disability worldwide. In addition to lifestyle and environmental factors which are major aetiologic determinants, there is considerable familial clustering of the disease indicating a genetic component in its causation. Although the total genetic contribution to CAD risk can be quantified, the determination of the size and number of contributing effects is impossible without identifying all CAD susceptibility genes. However, despite extensive studies, strong evidence of a molecular genetic association with coronary artery disease or myocardial infarction remains elusive. Genome wide association studies have been successful in identifying robust associations of single nucleotide polymorphisms (SNP) with CAD. Identifying the causal variant and dissecting pathways linking these variants to disease process is a major challenge. Technologies from whole genome sequencing, proteomics, transcriptomics and metabolomics are now available to extend analysis to a more complete range of potential susceptibility variants, and to support more explicit modelling of the joint effects of genes and environment. The availability of these high throughput technologies does not diminish the importance of rigorous phenotyping and appropriate study designs in all the endeavours to understand the aetiopathogenesis of CAD. Combining classical epidemiology with modern genomics will require collaborative efforts within the cardiovascular disease community at both bench and bedside and this will have the potential to expand our understanding of CAD and translate discoveries into clinically useful applications that will have a major impact on public health.

Exprtarget: an integrative approach to predicting human microRNA targets

Variation in gene expression has been observed in natural populations and associated with complex traits or phenotypes such as disease susceptibility and drug response. Gene expression itself is controlled by various genetic and non-genetic factors. The binding of a class of small RNA molecules, microRNAs (miRNAs), to mRNA transcript targets has recently been demonstrated to be an important mechanism of gene regulation. Because individual miRNAs may regulate the expression of multiple gene targets, a comprehensive and reliable catalogue of miRNA-regulated targets is critical to understanding gene regulatory networks. Though experimental approaches have been used to identify many miRNA targets, due to cost and efficiency, current miRNA target identification still relies largely on computational algorithms that aim to take advantage of different biochemical/thermodynamic properties of the sequences of miRNAs and their gene targets. A novel approach, ExprTarget, therefore, is proposed here to integrate some of the most frequently invoked methods (miRanda, PicTar, TargetScan) as well as the genome-wide HapMap miRNA and mRNA expression datasets generated in our laboratory. To our knowledge, this dataset constitutes the first miRNA expression profiling in the HapMap lymphoblastoid cell lines. We conducted diagnostic tests of the existing computational solutions using the experimentally supported targets in TarBase as gold standard. To gain insight into the biases that arise from such an analysis, we investigated the effect of the choice of gold standard on the evaluation of the various computational tools. We analyzed the performance of ExprTarget using both ROC curve analysis and cross-validation. We show that ExprTarget greatly improves miRNA target prediction relative to the individual prediction algorithms in terms of sensitivity and specificity. We also developed an online database, ExprTargetDB, of human miRNA targets predicted by our approach that integrates gene expression profiling into a broader framework involving important features of miRNA target site predictions.

FOS expression in blood as a LDL-independent marker of statin treatment

OBJECTIVES

The expression of FOS, a gene critical for monocyte and macrophage function, can be inhibited by statins through the disruption of a cholesterol-independent signaling pathway. In this pilot study, we hypothesized that blood FOS mRNA levels will be sensitive to statin treatment independent of LDL cholesterol levels.

METHODS

Three cohorts at increased risk of or with cardiovascular disease (CVD) were studied. Blood FOS mRNA levels were measured before and after statin treatment or in patients under stable treatment.

RESULTS

Statin treatment for three months significantly reduced blood FOS mRNA and LDL cholesterol levels. However, in subjects with similar LDL levels achieved by different doses of long term statin treatment, there was an inverse relationship between statin dose and FOS expression.

CONCLUSIONS

FOS mRNA levels appear to be a sensitive marker of statin treatment that is dissociated from cholesterol levels.

Secondary prevention strategies for coronary heart disease

Patients with established coronary heart disease (CHD) have a high risk of subsequent cardiovascular events, including myocardial infarction (MI), stroke, and death from cardiovascular disease. Adherence to evidence-based secondary prevention therapies for CHD has improved in recent years but still remains suboptimal. Mortality from CHD in the United States (US) has decreased substantially in recent decades. The decline in US deaths from CHD from 1980 through 2000 has been attributed to reductions in major risk factors and utilization of evidence-based medical therapies. It has been estimated that optimization of secondary prevention strategies could save as many as 80,000 more lives per year in the US. The American College of Cardiology (ACC) and American Heart Association (AHA) updated its guidelines for secondary prevention for patients with atherosclerotic vascular disease in 2006. The guidelines emphasize evidence-based developments in the field of CHD secondary prevention and also reinforce the need to implement these recommendations in actual clinical practice through programs such as the ACC's Guidelines Applied to Practice and the AHA's Get With The Guidelines. This review will discuss the epidemiology and risk assessment of CHD, current pharmacologic and nonpharmacologic strategies available for the secondary prevention of CHD, and summarize the guidelines and evidence that support these treatment options. There will be an emphasis on antiplatelet therapy given the important role of thrombosis in clinical cardiovascular events.

Modulation of gene expression in endothelial cells by hyperlipaemic postprandial serum from healthy volunteers

A single high-fat challenge induces plasmatic pro-inflammatory and pro-oxidative responses in the postprandial state, even in healthy men. This period is also associated with vascular endothelial dysfunction, which is an early event in the development of cardiovascular diseases. However, knowledge about the mechanisms involved in postprandial hyperlipaemia-induced endothelial dysfunction is sparse. An objective of our study was to characterize the behaviour and gene expression of vascular endothelial cells exposed to postprandial hyperlipaemic sera. Human umbilical vein endothelial cells (HUVECs) were cultured in media containing 10% serum from healthy men withdrawn either before or 4 h after a high-fat challenge. Endothelial cell proliferation, adhesion and migration were then assessed. The transcriptomic profiles of endothelial cells exposed to pre and postprandial sera were also compared. Exposure to postprandial hyperlipaemic sera significantly decreased HUVEC proliferation when compared to preprandial serum (P < 0.0001), while no changes in migration or endothelial/monocyte interactions were observed. The transcriptomic analysis revealed changes in the expression of 675 genes, of which 431 have a known function. Among them, a set of differentially expressed genes was linked to cell cycle regulation and apoptosis and are regulated in favour of cell cycle arrest or death. This result was confirmed by measuring the induction of apoptosis after postprandial sera exposure (P = 0.011). Taken together, the transcriptomic results and pathway analysis showed that postprandial serum promotes apoptosis in HUVECs, potentially through the activation of the p53 network. We conclude that upon postprandial serum exposure, vascular endothelial cells transcriptionally regulate genes involved in the control of cell cycle and death to favour growth arrest and apoptosis. These findings support the hypothesis that postprandial hyperlipaemia is associated with vascular dysfunction and offer new insights into the mechanisms involved.

ELECTRONIC SUPPLEMENTARY MATERIAL

The online version of this article (doi:10.1007/s12263-010-0166-x) contains supplementary material, which is available to authorized users.

Gene expression signatures diagnose influenza and other symptomatic respiratory viral infections in humans

Acute respiratory infections (ARIs) are a common reason for seeking medical attention, and the threat of pandemic influenza will likely add to these numbers. Using human viral challenge studies with live rhinovirus, respiratory syncytial virus, and influenza A, we developed peripheral blood gene expression signatures that distinguish individuals with symptomatic ARIs from uninfected individuals with >95% accuracy. We validated this "acute respiratory viral" signature-encompassing genes with a known role in host defense against viral infections-across each viral challenge. We also validated the signature in an independently acquired data set for influenza A and classified infected individuals from healthy controls with 100% accuracy. In the same data set, we could also distinguish viral from bacterial ARIs (93% accuracy). These results demonstrate that ARIs induce changes in human peripheral blood gene expression that can be used to diagnose a viral etiology of respiratory infection and triage symptomatic individuals.

Variation in the 4q25 chromosomal locus predicts atrial fibrillation after coronary artery bypass graft surgery

BACKGROUND

Atrial fibrillation (AF) is the most common adverse event following coronary artery bypass graft surgery. A recent study identified chromosome 4q25 variants associated with AF in ambulatory populations. However, their role in postoperative AF is unknown. We hypothesized that genetic variants in the 4q25 chromosomal region are independently associated with postoperative AF after coronary artery bypass graft surgery.

METHODS AND RESULTS

Two prospectively collected cohorts of patients undergoing coronary artery bypass graft surgery, with or without concurrent valve surgery, at 3 US centers. From a discovery cohort of 959 patients, clinical and genomic multivariate predictors of postoperative AF were identified by genotyping 45 single-nucleotide polymorphisms (SNPs) encompassing the 4q25 locus. Three SNPs were then assessed in a separately collected validation cohort of 494 patients. After adjustment for clinical predictors of postoperative AF and multiple comparisons, rs2200733, rs13143308, and 5 other linked SNPs independently predicted postoperative AF in the discovery cohort. Additive odds ratios for the 7 associated 4q25 SNPs ranged between 1.57 and 2.17 (P=8.0x10(-4) to 3.4x10(-6)). Association with postoperative AF were measured and replicated for rs2200733 and rs13143308 in the validation cohort.

CONCLUSIONS

In 2 independently collected cardiac surgery cohorts, noncoding SNPs within the chromosome 4q25 region are independently associated with postoperative AF after coronary artery bypass graft surgery after adjusting for clinical covariates and multiple comparisons.

Ion-channel mRNA-expression profiling: Insights into cardiac remodeling and arrhythmic substrates

Membrane ion channels and transporters are key determinants of cardiac electrical function. Their expression is affected by cardiac region, hemodynamic properties, heart-rate changes, neurohormones and cardiac disease. One of the important determinants of ion-channel function is the level of ion-channel subunit mRNA expression, which governs the production of ion-channel proteins that traffic to the cell-membrane to form functional ion-channels. Ion-channel mRNA-expression profiling can be performed with cDNA microarrays or high-throughput reverse transcription/polymerase chain reaction (PCR) methods. Expression profiling has been applied to evaluate the dependence of ion-channel expression on cardiac region, revealing the molecular basis of regionally-controlled electrical properties as well as the molecular determinants of specialized electrical functions like pacemaking activity. Ion-channel remodeling occurs with cardiac diseases like heart failure, congenital repolarization abnormalities, and atrial fibrillation, and expression profiling has provided insights into the mechanisms by which these conditions affect cardiac electrical stability. Expression profiling has also shown how hormonal changes, antiarrhythmic drugs, cardiac development and altered heart rate affect ion-channel expression patterns to modify cardiac electrical function and sometimes to produce cardiac rhythm disturbances. This article reviews the information obtained to date with the application of cardiac ion-channel expression profiling. With increasing availability and efficiency of high-throughput PCR methods for ion-channel subunit mRNA-expression characterization, it is likely that the application of ion-channel expression profiling will increase and that it will provide important new insights into the determinants of cardiac electrical function in both physiological and pathological situations.

Cardiovascular biomarkers: increasing impact of laboratory medicine in cardiology practice

The practice of cardiology is in continual evolution, in parallel with the progress achieved by medical research in understanding the pathophysiology of cardiovascular disease and in developing new therapeutic procedures. Consequently, manufacturers of cardiac biomarkers are pressed with new demands to improve the performance of the existing and the development of novel ones. Several highly sensitive and/or specific assays for myocardial ischemic damage and myocardial function detection have already become commercially available. Moreover, an increasing number of novel risk factors have been added to the classical risk factors of cardiovascular disease. Finally, the recent surge of genetic analysis procedures will likely soon provide the clinical cardiologist with a number of laboratory tests for defining the molecular diagnosis, assessing new risk factors, and better targeting the pharmaceutical approaches in patients with cardiovascular disease. In this review, we first present the general characteristics of a biomarker followed by the analytical and clinical performance of assay methods.

Tobacco use induces anti-apoptotic, proliferative patterns of gene expression in circulating leukocytes of Caucasian males

Background

Strong epidemiologic evidence correlates tobacco use with a variety of serious adverse health effects, but the biological mechanisms that produce these effects remain elusive.

Results

We analyzed gene transcription data to identify expression spectra related to tobacco use in circulating leukocytes of 67 Caucasian male subjects. Levels of cotinine, a nicotine metabolite, were used as a surrogate marker for tobacco exposure. Significance Analysis of Microarray and Gene Set Analysis identified 109 genes in 16 gene sets whose transcription levels were differentially regulated by nicotine exposure. We subsequently analyzed this gene set by hyperclustering, a technique that allows the data to be clustered by both expression ratio and gene annotation (e.g. Gene Ontologies).

Conclusion

Our results demonstrate that tobacco use affects transcription of groups of genes that are involved in proliferation and apoptosis in circulating leukocytes. These transcriptional effects include a repertoire of transcriptional changes likely to increase the incidence of neoplasia through an altered expression of genes associated with transcription and signaling, interferon responses and repression of apoptotic pathways.

Genetic polymorphisms of matrix metalloproteinases in lung, breast and colorectal cancer

The matrix metalloproteinases (MMPs) can degrade various components of the extracellular matrix and are implicated in the development and progression of cancer. There is evidence suggesting an association of MMP gene polymorphisms with cancer susceptibility and/or metastasis. This paper reviews the findings on several single nucleotide polymorphisms in the collagenase, stromelysin and gelatinase genes in lung cancer, breast cancer and colorectal cancer.

Identifying the most suitable endogenous control for determining gene expression in hearts from organ donors

BACKGROUND

Quantitative real-time reverse transcription PCR (qRT-PCR) is a useful tool for assessing gene expression in different tissues, but the choice of adequate controls is critical to normalise the results, thereby avoiding differences and maximizing sensitivity and accuracy. So far, many genes have been used as a single reference gene, without having previously verified their value as controls. This practice can lead to incorrect conclusions and recent evidence indicates a need to use the geometric mean of data from several control genes. Here, we identified an appropriate set of genes to be used as an endogenous reference for quantifying gene expression in human heart tissue.

RESULTS

Our findings indicate that out of ten commonly used reference genes (GADPH, PPIA, ACTB, YWHAZ, RRN18S, B2M, UBC, TBP, RPLP and HPRT), PPIA, RPLP and GADPH show the most stable gene transcription levels in left ventricle specimens obtained from organ donors, as assessed using geNorm and Normfinder software. The expression of TBP was found to be highly regulated.

CONCLUSION

We propose the use of PPIA, RPLP and GADPH as reference genes for the accurate normalisation of qRT-PCR performed on heart tissue. TBP should not be used as a control in this type of tissue.

Differential display fingerprints: new approach to characterize smooth muscle cells and human coronary atherectomy tissues

AIM OF THE STUDY

Smooth muscle cells build up the normal media and stabilize atherosclerotic lesions whereas an inflammatory component is determinant for unstable angina. Smooth muscle cells, currently identified by alpha-actin, present a phenotypic heterogeneity and alpha-actin can be reduced in pathology. We tried to characterize vascular cell types, particularly smooth muscle cells, and coronary atherosclerotic tissues, by random genes expression fingerprints.

MATERIALS AND METHODS

Expression fingerprints (cDNA electrophoresis) were performed by differential display reverse transcriptase-polymerase chain reaction. Variability of fingerprints was studied for a panel of arterial muscle cell phenotypes and comparisons were made with fingerprints from other cell types (endothelial cells and macrophages). The technique was then applied to human coronary atherectomy samples compared to control human arterial (mammary) smooth muscle.

RESULTS

Arterial smooth muscle cells fingerprints were overall similar whatever the cell phenotype (native contractile, dedifferentiated in culture or epithelioid). Moreover, with two primer pairs, the muscular fingerprints markedly differed from the endothelial and the monocytic fingerprints. Application of differential display to coronary atherectomy samples was feasible. Interestingly, the pathological tissues exhibited either smooth muscle-like or smooth muscle-divergent fingerprints.

CONCLUSIONS

Smooth muscle cells and inflammatory cells exhibited distinct differential display fingerprint patterns. Thus, a simple expression profile of arbitrary genes provides a molecular bar code tool (pattern signature) useful to characterize vascular cell cultures or tissues. The present work proposes a method to analyze coronary atherectomy samples which estimates their whole quality, muscular versus non muscular (inflammatory), this is of interest for clinical research.

Altered expression of early cardiac marker genes in circulating cells of patients with hypertrophic cardiomyopathy

BACKGROUND

Early cardiac marker genes, such as cardiac-specific homeobox (Csx/Nkx2.5), myocardin, homeodomain only protein, GATA4, and myocyte enhancer factor 2C, are thought to participate in cardiomyocyte differentiation and to contribute to heart hypertrophy in animal models. In this study, we investigated whether the expression of early cardiac genes is altered in the peripheral blood of patients with hypertrophic cardiomyopathy.

METHODS

Peripheral blood mononuclear cells were isolated from 30 consecutive hypertrophic cardiomyopathy patients and 20 healthy controls, and gene expression was determined by quantitative real-time reverse transcription-polymerase chain reaction.

RESULTS

Csx/Nkx2.5, myocardin, and GATA4 expressions were significantly higher in hypertrophic cardiomyopathy patients by 5.14+/-0.89 (P<.001), 1.65+/-0.21 (P<.05), and 2.04+/-0.41 (P<.04) times, respectively, while homeodomain only protein showed a fourfold decrease in expression (P<.02) compared to controls. In addition, expression of the differentiation-specific marker genes beta-myosin heavy chain and smooth muscle myosin heavy chain was significantly higher in hypertrophic cardiomyopathy patients by 3.72+/-0.82 (P<.02) and 2.57+/-0.72 (P<.05) times, respectively, compared to controls. Myocyte enhancer factor 2C expression was not different between patients and controls. Furthermore, increased expression of GATA4, myocardin, and beta-myosin heavy chain positively correlated with increased left ventricular mass.

CONCLUSIONS

In conclusion, we found altered expressions of early cardiac marker genes and differentiation-specific marker genes in peripheral blood mononuclear cells of hypertrophic cardiomyopathy patients compared to control individuals, possibly reflecting changes in response to disease.

Update on advances in atherothrombosis

The study of atherothrombosis is a rapidly evolving field, and significant progress was achieved in various aspects of the disease during the past year. In the area of diagnostic imaging, MRI and multidetector CT were actively used to evaluate the characteristics of the arterial wall, including calcified and noncalcified lesions, and both in the coronary and extracoronary vascular territories. There was also extensive research into the application of imaging modalities to visualize cellular or molecular disease processes, known as molecular imaging. Considerable efforts were devoted to the identification of novel biomarkers that reflect different components of atherothrombosis, namely inflammation, thrombogenicity, oxidative stress and reparative ability, predicting the presence of early disease or the risk of clinical events. In the therapeutic arena, substantial evidence accumulated on the beneficial effects of several pharmacologic agents, most significantly statins. Finally, important advances were also made in the understanding of the roles of immunity and neovascularization in atherogenesis, including the development and progression of disease at different stages. Awareness of these recent advances and new lines of active research is fundamental for health professionals involved in the care of patients with atherothrombosis. In this Review we present an overview of data in these areas.