[A practical approach to the diagnosis of cardiomyopathy: a roadmap from the phenotype]. / Un approccio pratico alla diagnosi di cardiomiopatia: una roadmap a partire dal fenotipo.

Cardiomyopathies are a heterogeneous group of cardiac diseases for which diagnosis and treatment are not always simple. The diagnosis of cardiomyopathy, in particular the etiology, comes from an integration between symptoms and results collected by several instrumental exams. The brain storming for the diagnosis includes also the identification of the "red flags", i.e. the pathognomonic features for each etiology that can drive the choice of appropriate diagnostic tests and therapy. In this review, we provide a step by step approach in order to help cardiologists, not specifically dedicated to cardiomyopathies, to draw the diagnosis, therapy and follow-up. This approach will be accompanied by the consultation of other specialists to discuss together the results of the exams performed and to deepen extracardiac signs and symptoms.

[Coronary allograft vasculopathy: pathophysiological interaction between the immune system, infections and metabolic syndrome]. / La malattia coronarica del cuore trapiantato: interazione fisiopatologica tra sistema immunitario, infezioni e sindrome metabolica.

Cardiac allograft vasculopathy is still the main cause of long-term graft loss after heart transplantation. Indeed, recent advances in immunosuppression management led to a significant improvement in short-term survival, while long-term death rate did not change significantly in the last 20 years. In this paper, we will review the latest advances in the understanding of this peculiar form of atherosclerosis, focusing on the mechanisms that can be potentially targeted by specific therapeutic interventions.

Interplay between systemic inflammation and markers of insulin resistance in cardiovascular prognosis after heart transplantation.

BACKGROUND: Metabolic and immuno-inflammatory risk factors contribute to cardiac allograft vasculopathy (CAV) pathogenesis. Although systemic inflammation, as detected by C-reactive protein (CRP), predicts CAV development, the relationship between CRP and markers of metabolic abnormalities remains unexplored. METHODS: CRP and the entire metabolic panel were evaluated in 98 consecutive heart transplant recipients at the time of annual coronary angiography, 5.8 years after transplant (range, 1-12 years). A ratio of triglycerides (TG) to high-density lipoproteins (HDL) of 3.0 or more was considered a marker of insulin resistance. CAV prevalence was defined by angiography, and subsequent prognosis was evaluated as incidence of major cardiac adverse events. RESULTS: CRP was higher in the 34 patients with angiographic CAV than in those without CAV (1.10 +/- 0.20 vs 0.50 +/- 0.05 mg/dl, p < 0.001). Patients with insulin resistance had higher CRP concentrations (p = 0.023) and higher CAV prevalence (p = 0.005). High CRP and a TG/HDL of 3.0 or more were independently associated with an increased likelihood of CAV (odds ratio, > or = 3.9; p = 0.02) and predicted an increased risk of major cardiac adverse events. The combination of high CRP and a TG/HDL of 3.0 or more identified a subgroup of patients having a 4-fold increased risk for CAV and a 3-fold increased risk for major cardiac adverse events compared with patients with low CRP and normal values for metabolic indicators. CONCLUSIONS: Both CRP and insulin resistance, as estimated by TG/HDL, appear to be strong, synergic risk factors for CAV and for major cardiac adverse events. These findings support the hypothesis that in heart transplant recipients, systemic inflammation may be an important mediator of graft vascular injury associated with metabolic syndrome.

Network analysis of human in-stent restenosis.

BACKGROUND: Recent successes in the treatment of in-stent restenosis (ISR) by drug-eluting stents belie the challenges still faced in certain lesions and patient groups. We analyzed human coronary atheroma in de novo and restenotic disease to identify targets of therapy that might avoid these limitations. METHODS AND RESULTS: We recruited 89 patients who underwent coronary atherectomy for de novo atherosclerosis (n=55) or in-stent restenosis (ISR) of a bare metal stent (n=34). Samples were fixed for histology, and gene expression was assessed with a dual-dye 22,000 oligonucleotide microarray. Histological analysis revealed significantly greater cellularity and significantly fewer inflammatory infiltrates and lipid pools in the ISR group. Gene ontology analysis demonstrated the prominence of cell proliferation programs in ISR and inflammation/immune programs in de novo restenosis. Network analysis, which combines semantic mining of the published literature with the expression signature of ISR, revealed gene expression modules suggested as candidates for selective inhibition of restenotic disease. Two modules are presented in more detail, the procollagen type 1 alpha2 gene and the ADAM17/tumor necrosis factor-alpha converting enzyme gene. We tested our contention that this method is capable of identifying successful targets of therapy by comparing mean significance scores for networks generated from subsets of the published literature containing the terms "sirolimus" or "paclitaxel." In addition, we generated 2 large networks with sirolimus and paclitaxel at their centers. Both analyses revealed higher mean values for sirolimus, suggesting that this agent has a broader suppressive action against ISR than paclitaxel. CONCLUSIONS: Comprehensive histological and gene network analysis of human ISR reveals potential targets for directed abrogation of restenotic disease and recapitulates the results of clinical trials of existing agents.

Pathway analysis of coronary atherosclerosis.

Large-scale gene expression studies provide significant insight into genes differentially regulated in disease processes such as cancer. However, these investigations offer limited understanding of multisystem, multicellular diseases such as atherosclerosis. A systems biology approach that accounts for gene interactions, incorporates nontranscriptionally regulated genes, and integrates prior knowledge offers many advantages. We performed a comprehensive gene level assessment of coronary atherosclerosis using 51 coronary artery segments isolated from the explanted hearts of 22 cardiac transplant patients. After histological grading of vascular segments according to American Heart Association guidelines, isolated RNA was hybridized onto a customized 22-K oligonucleotide microarray, and significance analysis of microarrays and gene ontology analyses were performed to identify significant gene expression profiles. Our studies revealed that loss of differentiated smooth muscle cell gene expression is the primary expression signature of disease progression in atherosclerosis. Furthermore, we provide insight into the severe form of coronary artery disease associated with diabetes, reporting an overabundance of immune and inflammatory signals in diabetics. We present a novel approach to pathway development based on connectivity, determined by language parsing of the published literature, and ranking, determined by the significance of differentially regulated genes in the network. In doing this, we identify highly connected "nexus" genes that are attractive candidates for therapeutic targeting and followup studies. Our use of pathway techniques to study atherosclerosis as an integrated network of gene interactions expands on traditional microarray analysis methods and emphasizes the significant advantages of a systems-based approach to analyzing complex disease.

Signature patterns of gene expression in mouse atherosclerosis and their correlation to human coronary disease.

The propensity for developing atherosclerosis is dependent on underlying genetic risk and varies as a function of age and exposure to environmental risk factors. Employing three mouse models with different disease susceptibility, two diets, and a longitudinal experimental design, it was possible to manipulate each of these factors to focus analysis on genes most likely to have a specific disease-related function. To identify differences in longitudinal gene expression patterns of atherosclerosis, we have developed and employed a statistical algorithm that relies on generalized regression and permutation analysis. Comprehensive annotation of the array with ontology and pathway terms has allowed rigorous identification of molecular and biological processes that underlie disease pathophysiology. The repertoire of atherosclerosis-related immunomodulatory genes has been extended, and additional fundamental pathways have been identified. This highly disease-specific group of mouse genes was combined with an extensive human coronary artery data set to identify a shared group of genes differentially regulated among atherosclerotic tissues from different species and different vascular beds. A small core subset of these differentially regulated genes was sufficient to accurately classify various stages of the disease in mouse. The same gene subset was also found to accurately classify human coronary lesion severity. In addition, this classifier gene set was able to distinguish with high accuracy atherectomy specimens from native coronary artery disease vs. those collected from in-stent restenosis lesions, thus identifying molecular differences between these two processes. These studies significantly focus efforts aimed at identifying central gene regulatory pathways that mediate atherosclerotic disease, and the identification of classification gene sets offers unique insights into potential diagnostic and therapeutic strategies in atherosclerotic disease.