Rationale and study design of the CardioGene Study: genomics of in-stent restenosis

Vascular Proteomics Reveal Novel Proteins Involved in SMC Phenotypic Change: OLR1 as a SMC Receptor Regulating Proliferation and Inflammatory Response

Neointimal hyperplasia of vascular smooth muscle cells (VSMC) plays a critical role in atherosclerotic plaque formation and in-stent restenosis, but the underlying mechanisms are still incompletely understood. We performed a proteomics study to identify novel signaling molecules organizing the VSMC hyperplasia. The differential proteomics analysis in a balloon-induced injury model of rat carotid artery revealed that the expressions of 44 proteins are changed within 3 days post injury. The combination of cellular function assays and a protein network analysis further demonstrated that 27 out of 44 proteins constitute key signaling networks orchestrating the phenotypic change of VSMC from contractile to epithelial-like synthetic. Among the list of proteins, the in vivo validation specifically revealed that six proteins (Rab15, ITR, OLR1, PDHβ, PTPε) are positive regulators for VSMC hyperplasia. In particular, the OLR1 played dual roles in the VSMC hyperplasia by directly mediating oxidized LDL-induced monocyte adhesion via NF-κB activation and by assisting the PDGF-induced proliferation/migration. Importantly, OLR1 and PDGFRβ were associated in close proximity in the plasma membrane. Thus, this study elicits the protein network organizing the phenotypic change of VSMC in the vascular injury diseases such as atherosclerosis and discovers OLR1 as a novel molecular link between the proliferative and inflammatory responses of VSMCs.

Systemic inflammation as a predictor of clinical outcomes after lower extremity angioplasty/stenting

OBJECTIVE

The activation state of the systemic inflammatory milieu has been proposed as a critical regulator of vascular repair after injury. We evaluated the early inflammatory response after endovascular intervention for symptomatic peripheral arterial disease to determine its association with clinical success or failure.

METHODS

Blood samples were obtained from 14 patients undergoing lower extremity angioplasty/stenting and analyzed using high-throughput gene arrays, multiplex serum protein analyses, and flow cytometry.

RESULTS

Time-dependent plasma protein and monocyte phenotype analyses demonstrated endovascular revascularization had a modest influence on the overall activation state of the systemic inflammatory system, with baseline variability exceeding the perturbations induced by the intervention. In contrast, specific time-dependent changes in the monocyte genome are evident in the initial 28 days, predominately in those genes associated with leukocyte extravasation. Investigating the relationship between inflammation and the 1-year success or failure of the intervention showed no single plasma protein was correlated with outcome, but a more comprehensive cluster analysis revealed a clear pattern of protein expression that was closely related to the clinical phenotype. Corresponding examination of the monocyte genome identified a gene subset at 1 day postprocedure that was predictive of clinical outcome, with most of these genes active in cell-cycle signaling.

CONCLUSIONS

Although the global influence of angioplasty/stenting on systemic inflammation was modest, circulating cytokine and monocyte genome analyses support a pattern of early inflammation that is associated with ultimate intervention success vs failure. Molecular profiles incorporating genes involved in monocyte cell-cycle progression and homing, or proinflammatory cytokines, or both, offer the most promise for the development of class prediction tools for clinical application.

Automatic Spot Identification for High Throughput Microarray Analysis

High throughput microarray analysis has great potential in scientific research, disease diagnosis, and drug discovery. A major hurdle toward high throughput microarray analysis is the time and effort needed to accurately locate gene spots in microarray images. An automatic microarray image processor will allow accurate and efficient determination of spot locations and sizes so that gene expression information can be reliably extracted in a high throughput manner. Current microarray image processing tools require intensive manual operations in addition to the input of grid parameters to correctly and accurately identify gene spots. This work developed a method, herein called auto-spot, to automate the spot identification process. Through a series of correlation and convolution operations, as well as pixel manipulations, this method makes spot identification an automatic and accurate process. Testing with real microarray images has demonstrated that this method is capable of automatically extracting subgrids from microarray images and determining spot locations and sizes within each subgrid, regardless of variations in array patterns and background noises. With this method, we are one step closer to the goal of high throughput microarray analysis.

A genome-wide association study identifies a region at chromosome 12 as a potential susceptibility locus for restenosis after percutaneous coronary intervention

Percutaneous coronary intervention (PCI) has become an effective therapy to treat obstructive coronary artery diseases (CAD). However, one of the major drawbacks of PCI is the occurrence of restenosis in 5-25% of all initially treated patients. Restenosis is defined as the re-narrowing of the lumen of the blood vessel, resulting in renewed symptoms and the need for repeated intervention. To identify genetic variants that are associated with restenosis, a genome-wide association study (GWAS) was conducted in 295 patients who developed restenosis (cases) and 571 who did not (controls) from the GENetic Determinants of Restenosis (GENDER) study. Analysis of ~550 000 single nucleotide polymorphisms (SNPs) in GENDER was followed by a replication phase in three independent case-control populations (533 cases and 3067 controls). A potential susceptibility locus for restenosis at chromosome 12, including rs10861032 (P(combined) = 1.11 × 10(-7)) and rs9804922 (P(combined) = 1.45 × 10(-6)), was identified in the GWAS and replication phase. In addition, both SNPs were also associated with coronary events (rs10861032, P(additive) = 0.005; rs9804922, P(additive) = 0.023) in a trial based cohort set of elderly patients with (enhanced risk of) CAD (PROSPER) and all-cause mortality in PROSPER (rs10861032, P(additive) = 0.007; rs9804922, P(additive) = 0.013) and GENDER (rs10861032, P(additive) = 0.005; rs9804922, P(additive) = 0.023). Further analysis suggests that this locus could be involved in regulatory functions.

Time course analysis of gene expression identifies multiple genes with differential expression in patients with in-stent restenosis

BACKGROUND

The vascular disease in-stent restenosis (ISR) is characterized by formation of neointima and adverse inward remodeling of the artery after injury by coronary stent implantation. We hypothesized that the analysis of gene expression in peripheral blood mononuclear cells (PBMCs) would demonstrate differences in transcript expression between individuals who develop ISR and those who do not.

METHODS AND RESULTS

We determined and investigated PBMC gene expression of 358 patients undergoing an index procedure to treat in de novo coronary artery lesions with bare metallic stents, using a novel time-varying intercept model to optimally assess the time course of gene expression across a time course of blood samples. Validation analyses were conducted in an independent sample of 97 patients with similar time-course blood sampling and gene expression data. We identified 47 probesets with differential expression, of which 36 were validated upon independent replication testing. The genes identified have varied functions, including some related to cellular growth and metabolism, such as the NAB2 and LAMP genes.

CONCLUSIONS

In a study of patients undergoing bare metallic stent implantation, we have identified and replicated differential gene expression in peripheral blood mononuclear cells, studied across a time series of blood samples. The genes identified suggest alterations in cellular growth and metabolism pathways, and these results provide the basis for further specific functional hypothesis generation and testing of the mechanisms of ISR.

New perspectives for synergy research with the "omic"-technologies

Synergistic effects, understood as true overadditive effects, are often observed in experimental and clinical studies using phytopharmaceuticals. The introduction of the "omic"-technologies is now opening new perspectives in rationalizing these effects and making use of them in the development of a new generation of phytopharmaceuticals. This review describes possible mechanism of synergistic actions of herbal drugs by mono- and multitargeting and by the activation of signal cascades. It examines the possibilities of the standardization of single and multi component plant extracts and the prediction and assessment of the toxicity and safety of plant extracts with the support of the "omic"-technologies. It further discusses the use of phytopharmaceuticals in the context of an "individualized medicine". It makes proposals how to use the "omic"-technologies to rationalize and develop combination therapies of phytopharmaceuticals and synthetic drugs to minimize adverse reactions (ARs) or improve the therapeutic efficacy. Examples of clinical studies are given which explore already the potential of such co-medications. Modern medical therapy has acknowledged for quite some time the usefulness of combination therapies in the treatment of multifactorial diseases like cancer, cardiovascular or rheumatic diseases. The term "synergy" is rarely used in this context, the combinatory mechanisms of actions seldom completely understood and the potentially occurring adverse reactions feared. A systematic exploitation of synergy effects of phytomedical interventions alone or in combination with synthetic drugs should lead in a long term perspective to the discovery and development of more rational evidence-based interventions in the prevention and therapy of multifactorial diseases and should thereby enrich modern pharmacotherapy.

Genomics, haplotypes and cardiovascular disease

Cardiovascular disease has a complex genetic and environmental origin. Single-gene mutations have been identified for a variety of disorders, including several forms of sudden cardiac death, atrial fibrillation, hypertrophic cardiomyopathy and coronary artery disease. The recent availability of haplotype data has further enabled genomic approaches to mapping genetic variants associated with the more common polygenic forms of cardiovascular disease. Genome-wide association studies have identified single nucleotide polymorphisms associated with coronary artery disease and are being applied to a variety of clinical problems such as in-stent restenosis. The combination of high-throughput genomic tools such as high density microarrays, genomic information such as sequence and haplotype data, and the careful clinical definition of phenotypes provides the framework for realizing the goals of personalized medicine.

Multistage Sampling for Genetic Studies

In the past, to study Mendelian diseases, segregating families have been carefully ascertained for segregation analysis, followed by collecting extended multiplex families for linkage analysis. This would then be followed by association studies, using independent case-control samples and/or additional family data. Recently, for complex diseases, the initial sampling has been for a genome-wide linkage analysis, often using independent sib-pairs or nuclear families, to identify candidate regions for follow-up with association studies, again using case-control samples and/or additional family data. We now have the ability to conduct genome-wide association studies using 100,000-500,000 diallelic genetic markers. For such studies we focus especially on efficient two-stage association sampling designs, which can retain nearly optimal statistical power at about half the genotyping cost. Similarly, beginning an association study by genotyping pooled samples may also be a viable option if the cost of accurately pooling DNA samples outweighs genotyping costs. Finally, we note that the sampling of family data for linkage analysis is not a practice that should be automatically discontinued.

Cardiovascular proteomics: past, present, and future

With cardiovascular (CV)-related disorders accounting for the highest mortality rates in the world, affecting the quantity and quality of life of patients and creating an economic burden of prolonged therapeutic intervention, there is great significance in understanding the cellular and molecular alterations that influence the progression of these pathologies. The cellular genotype is regulated by the DNA component, whilst the cellular phenotype is influenced by the protein complement. By improving the understanding of the molecular mechanisms that influence the protein profile, the pathologies that influence the intrinsic functions of the CV system may be detected earlier or managed more efficiently. This is achievable with technologies encompassed by 'proteomics.' Proteomic investigations of CV diseases, including dilated cardiomyopathy (DCM), atherosclerosis, and ischemia/reperfusion (I/R) injury, have identified candidate proteins altered with the pathologic states, complementing past biochemical and physiologic observations. Whilst proteomics is still a relatively new discipline to be applied to the basic scientific investigation of CV diseases, it is emerging as a technique to screen for potential biomarkers in both tissues/cells and biologic fluids (biofluids), as well as to identify the targets of existing therapeutics. By enabling the separation of complex mixtures over numerous dimensions, exploiting the intrinsic properties of proteins, including charge state, molecular mass, and hydrophobicity, in addition to cellular location, the discrete alterations within the cell may be resolved. Proteomics has shown alterations to myofilament proteins including troponin I and myosin light chain, correlating with the reduction in contractility in the myocardium from DCM and I/R. The diverse cell types that coalesce to induce atherosclerotic plaque formation have been investigated both collectively and individually to elucidate the influence of the modifications to single cell types on the developing plaque as a whole. Proteomics has also been used to observe changes to biofluids occurring with these pathologies, a new potential link between basic science and clinical applications. The development of CV proteomics has helped to identify a number of possible protein candidates, and offers the potential to treat and diagnose CV disease more effectively in the future.

Genomic and proteomic determinants of lower extremity revascularization failure: rationale and study design

This translational research program applies a working model of advanced functional genomics/proteomics and bioinformatics to human peripheral arterial occlusive disease (PAOD). It is a multidisciplinary collaborative effort of clinicians, scientists, and statisticians with an advisory panel consisting of experts in inflammation biology, vascular biology, molecular genetics, bioinformatics, clinical trial design, and epidemiology. The proposed human initiative is designed to study 300 symptomatic patients with PAOD undergoing medical management with or without vascular intervention by lower extremity angioplasty/stenting or vein graft bypass. The study aims to test the hypothesis that the systemic inflammatory response after vascular intervention influences the local milieu responsible for vascular repair and adaptation. The expectation is that this response is not uniform in all patients but, rather, is modulated by either preoperative genetic predisposition or postprocedure differential regulation of the innate immune response to injury that promotes a maladaptive phenotype leading to intervention failure. Therefore, some of these differences may be present and detectable before intervention and amenable to class prediction and prospective treatment strategies, whereas others may be detectable in the early postprocedural period, before the onset of clinical failure, permitting interventions to prevent an adverse outcome. The combination of genomic/proteomic data together with functional and quality-of-life outcome measures to define a critical model for class prediction and analysis should lead to new knowledge about failure mechanisms of vascular intervention and new strategies to improve existing approaches to lower extremity revascularization.

The effect of HapMap on cardiovascular research and clinical practice

The Haplotype Genetic Map (HapMap) is an invaluable resource to the cardiovascular researcher, enabling a decrease in cost and an increase in the efficiency and speed of discoveries in the laboratory. As cardiologists, we need to understand the vocabulary of genomics because the translation of scientific findings using HapMap could provide insight for improved care and therapeutic guidance of our patients. Genomics is the evaluation of genes as a dynamic system, in which genes interact to influence biologic pathways, networks and physiology. The HapMap promises to increase the efficiency of genomics in identifying cardiovascular-disease-related genes that could become vital for choosing relevant tests and providing preventative and curative therapies. In this Review, the HapMap will be described, to provide insight into the relevance of this work to cardiovascular practice, to clinical research in cardiovascular disease and to future discoveries in diagnostic and therapeutic modalities.

Thematic review series: Systems Biology Approaches to Metabolic and Cardiovascular Disorders. Proteomics approaches to the systems biology of cardiovascular diseases

Proteins play a central role in a systems view of biologic processes. This review provides an overview of proteomics from a systems perspective. We survey the key tools and methodologies used, present examples of how these are currently being used in the systems biology context, and discuss future directions.

Genomic analysis of circulating cells: a window into atherosclerosis

Translational studies using genomic techniques in cardiovascular diseases are still in their infancy. Access to disease-associated cardiovascular tissues from patients has been a major impediment to progress in contrast to the diagnostic advances made by oncologists using gene expression on readily available tumor samples. Nonetheless, progress is being made for atherosclerosis by carefully designed experiments utilizing diseased tissue or surrogate specimens. This review details the rationale and findings of a study utilizing freshly isolated blood mononuclear cells from patients undergoing carotid endarterectomy due to atherosclerotic stenosis and from matched healthy subjects. By querying this cardiovascular tissue surrogate, the messenger RNA levels of the Finkel-Biskis-Jenkins osteosarcoma gene in circulating monocytes were found to correlate with atherosclerosis severity in patients and with 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor (statin) therapy in healthy subjects. The major finding of this investigation is discussed in relation to observations from other human atherosclerosis gene expression studies. These distinct studies converge to demonstrate the unequivocal importance of inflammation in atherosclerosis. Although the clinical utility of the specific findings remains open, the identification of similar genes by different investigations serves to validate our report. They also provide us with insights into pathogenesis that may impact future translational applications.

Blood genomic profiling: novel diagnostic and therapeutic strategies for stroke?

Findings from gene expression profiling studies are leading to new diagnostic and therapeutic strategies that can be applied in medical practice, especially in the field of oncology. Promising results of gene expression profiling of the peripheral blood in patients with ischaemic stroke have been obtained in recent pilot studies, demonstrating a partially reproducible gene signature of acute cerebral ischaemia. However, questions remain. Given that blood is at least in part a surrogate tissue for ischaemic stroke, the specificity of these signatures needs to be evaluated. Furthermore, it needs to be determined whether standardization of this methodology is required and whether clinical signatures can be identified that are improvements over the tools currently used in clinical practice. Clinically useful signatures would include those of haemorrhagic as well as ischaemic stroke, reclassification of stroke type and prognosis, and vascular disease risk. If these conditions are met, then it should be possible to develop cost-effective and rapid assays.

Transcription factor and kinase-mediated signaling in atherosclerosis and vascular injury

Our understanding of the molecular signaling pathways regulating the initiation and progression of atherosclerosis or remodeling in response to injury has begun to cross the boundaries from regulation of well-described canonical pathways to the interplay between these pathways. The focus of this review is to summarize our current understanding of a finite group of transcription factors and kinases involved in vascular injury and atherosclerosis, including nuclear factor-kappaB (NF-kappaB), early growth response factor-1 (Egr-1), activator protein-1 (AP-1), hypoxia inducible factor-1alpha (HIF-1alpha), homeobox, and T cell factor/lymphoid enhancer factor (Tcf-Lef), as well as the kinases janus kinase/signal transducers and activators of transcription (JAK/STAT), protein kinase C (PKC), p38, Rho, ERK5, JNK, p44/p42, and phosphoinositide 3 (PI3) kinase/AKT.

Gene and protein expression in the myometrium in pregnancy and labor

Microarray technologies widen our comprehension of the major structural and metabolic transformations which affect the myometrium from the very beginning of pregnancy until parturition. The results are coherent with the mass of information which was accumulated previously, primarily on the basis of studies of selected critical factors. They highlight the activation of precise signaling pathways, some of which may have been previously under evaluated. The remodelling and maturation processes that the myometrium undergoes in pregnancy appear clearly as phenomena which last during the full course of gestation. Comparatively, the onset of labor is perhaps the phenomenon which remains the least well described by these methods of analysis. Nevertheless, genomic studies constitute a necessary first step of orientation and help establishing new links between the generic signaling pathways that are activated during the normal or pathological gestation. These studies also represent an indicative step that will have to be paralleled, in the future, with the results of the systematic proteomic analysis of the myometrium.

On Averaging Power for Genetic Association and Linkage Studies

A power calculation is crucial in planning genetic studies. In genetic association studies, the power is often calculated using the expected number of individuals with each genotype calculated from an assumed allele frequency under Hardy-Weinberg equilibrium. Since the allele frequency is often unknown, the number of individuals with each genotype is random and so a power calculation assuming a known allele frequency may be incorrect. Ambrosius et al. recently showed that the power ignoring this randomness may lead to studies with insufficient power and proposed averaging the power due to the randomness. We extend the method of averaging power in two directions. First, for testing association in case-control studies, we use the Cochran-Armitage trend test and find that the time needed for calculating the averaged power is much reduced compared to the chi-square test with two degrees of freedom studied by Ambrosius et al. A real study is used for illustration of the method. Second, we extend the method to linkage analysis, where the number of identical-by-descent alleles shared by siblings is random. The distribution of identical-by-descent numbers depends on the underlying genetic model rather than the allele frequency. The robust test for linkage analysis is also examined using the averaged powers. We also recommend a sensitivity analysis when the true allele frequency or the number of identical-by-descent alleles is unknown.

Genetics, genomics and proteomics in atherosclerosis research

Atherosclerosis and its clinical manifestations are the leading cause of death in Western countries. Atherosclerosis is a multifactorial disease characterized by endothelial dysfunction, smooth muscle cell (SMC) proliferation and migration, inflammation, lipid and matrix accumulation and thrombus formation. Multiple genetic and environmental features and interactions between these factors influence the disease process. To understand fundamental pathobiological mechanisms in atherogenesis and to develop and target new therapies, information on genetic factors (atherogenetics), gene expression patterns (atherogenomics) and protein expression patterns (atheroproteomics) are needed. This review will summarize current knowledge in these areas of atherosclerosis research with a special emphasis on microarray technology.