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    Autophagy and Mitophagy in Cardiovascular Disease. Bravo-San Pedro José Manuel,Kroemer Guido,Galluzzi Lorenzo Circulation research Autophagy contributes to the maintenance of intracellular homeostasis in most cells of cardiovascular origin, including cardiomyocytes, endothelial cells, and arterial smooth muscle cells. Mitophagy is an autophagic response that specifically targets damaged, and hence potentially cytotoxic, mitochondria. As these organelles occupy a critical position in the bioenergetics of the cardiovascular system, mitophagy is particularly important for cardiovascular homeostasis in health and disease. Consistent with this notion, genetic defects in autophagy or mitophagy have been shown to exacerbate the propensity of laboratory animals to spontaneously develop cardiodegenerative disorders. Moreover, pharmacological or genetic maneuvers that alter the autophagic or mitophagic flux have been shown to influence disease outcome in rodent models of several cardiovascular conditions, such as myocardial infarction, various types of cardiomyopathy, and atherosclerosis. In this review, we discuss the intimate connection between autophagy, mitophagy, and cardiovascular disorders. 10.1161/CIRCRESAHA.117.311082
    Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach. Vilne Baiba,Schunkert Heribert Frontiers in cardiovascular medicine Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought to contribute to disease risk. It is likely that non-linear and complex interactions occur between these multiple factors, involving simultaneous pathological changes in diverse cell types, tissues, and organs, at multiple molecular levels. Recent technological advances have exponentially expanded the breadth of available -omics data, from genome, epigenome, transcriptome, proteome, metabolome to even the microbiome. Integration of multiple layers of information across several -omics domains, i.e., the so-called multi-omics approach, currently holds the promise as a path toward precision medicine. Indeed, a more meaningful interpretation of genotype-phenotype relationships and the development of successful therapeutics tailored to individual patients are urgently needed. In this review, we will summarize recent findings and applications of integrative multi-omics in elucidating the etiology of CAD/MI; with a special focus on established disease susceptibility loci sequentially identified in genome-wide association studies (GWAS) over the last 10 years. Moreover, in addition to the autosomal genome, we will also consider the genetic variation in our "second genome"-the mitochondrial genome. Finally, we will summarize the current challenges in the field and point to future research directions required in order to successfully and effectively apply these approaches for precision medicine. 10.3389/fcvm.2018.00089
    NLRP3 Inflammasome Biomarker-Could Be the New Tool for Improved Cardiometabolic Syndrome Outcome. Suceveanu Andra-Iulia,Mazilu Laura,Katsiki Niki,Parepa Irinel,Voinea Felix,Pantea-Stoian Anca,Rizzo Manfredi,Botea Florin,Herlea Vlad,Serban Dragos,Suceveanu Adrian-Paul Metabolites Metabolomics, the research area studying chemical processes involving metabolites, finds its utility in inflammasome biomarker discovery, thus representing a novel approach for cardiometabolic syndrome pathogeny acknowledgements. Metabolite biomarkers discovery is expected to improve the disease evolution and outcome. The activation of abundantly expressed NLRP3 inflammasome represents the background process of the diabetes mellitus disturbances like hyperglycemia and insulin resistance, as well as for myocardial cell death and fibrosis, all of them being features characteristic for cardiometabolic syndrome. Many molecules like troponins, brain natriuretic protein (BNP), ST2/IL-33, C-reactive protein (CRP), TNF, IL-1β, and IL-18 cytokines have been already examined as molecular markers for diagnosing or predicting different cardiac disturbances like myocardial infarction, heart failure, or myocarditis. In addition, metabolomics research comes with new findings arguing that NLRP3 inflammasome becomes a promising molecular tool to use for clinical and therapeutical management providing new targets for therapies in cardiometabolic syndrome. Inflammasome markers analyses, along with other molecular or genetic biomarkers, will result in a better understanding of cardiometabolic syndrome pathogenesis and therapeutic targets. Screening, diagnostic, and prognostic biomarkers resulted from inflammasome biomarker research will become standard of care in cardiometabolic syndrome management, their utility becoming the first magnitude. 10.3390/metabo10110448
    Metabolomic strategies to study lipotoxicity in cardiovascular disease. Waterman Claire L,Kian-Kai Cheng,Griffin Julian L Biochimica et biophysica acta Cardiovascular disease arises from a combination of dyslipidaemia and systemic inflammation in both humans and mouse models of the disease. Given the strong metabolic component and also the strong interaction between diet and disease, one would expect strategies based on the global profiling of metabolism should hold substantial promise in defining the mechanism involved in this collection of pathologies. This review examines how metabolomics is being used both as a research tool to understand mechanisms of pathology and as an approach for biomarker discovery in cardiovascular disease. While the lipid fraction of blood plasma has a profound influence on the development of cardiovascular disease, there is also a growing body of evidence that the aqueous fraction of metabolites also have a role in following the effects of myocardial infarction and monitoring the development of atherosclerosis. Metabolomics has also been used in conjunction with proteomics and transcriptomics as part of a systems biology description of cardiovascular disease and in high-throughput approaches to profile large numbers of patients as part of epidemiology studies to understand how the genome interacts with the development of atherosclerosis. 10.1016/j.bbalip.2009.11.004
    Vascular proteomics. Barderas Maria G,Vivanco Fernando,Alvarez-Llamas Gloria Methods in molecular biology (Clifton, N.J.) Cardiovascular diseases constitute the largest of death in developed countries, being atherosclerosis the major contributor. Atherosclerosis is a process of chronic inflammation, characterized by the accumulation of lipids, cells, and fibrous elements in medium and large arteries. There is a continuum in atherosclerotic cardiovascular pathology that extends from the initial endothelial damage to diseases such as angina, myocardial infarction, and stroke. The extent of inflammation, proteolysis, calcification, and neovascularization influences the development of advanced lesions (atheroma plaques) on the arteries. Plaque rupture and the ensuing thrombosis cause the acute complications of atherosclerosis, i.e., myocardial infarction and cerebral ischemia. Thus, identification of early biomarkers of plaque unstability and susceptibility to rupture is of capital importance in preventing acute events. In recent years proteomics has been successfully applied to study proteins involved in these pathological processes. Thus, proteomic studies have been carried out focusing on different elements such as vascular tissues (arteries), artery layers, cells looking at proteomes and secretomes, plasma/serum, exosomes, lipoproteins, and metabolites. This chapter will provide an overview of latest advances in proteomic studies of atherosclerosis and related vascular diseases. 10.1007/978-1-62703-405-0_1
    A practical guide to metabolomic profiling as a discovery tool for human heart disease. Heather Lisa C,Wang Xinzhu,West James A,Griffin Julian L Journal of molecular and cellular cardiology Metabolomics has refreshed interest in metabolism across biology and medicine, particularly in the areas of functional genomics and biomarker discovery. In this review we will discuss the experimental techniques and challenges involved in metabolomic profiling and how these technologies have been applied to cardiovascular disease. Open profiling and targeted approaches to metabolomics are compared, focusing on high resolution NMR spectroscopy and mass spectrometry, as well as discussing how to analyse the large amounts of data generated using multivariate statistics. Finally, the current literature on metabolomic profiling in human cardiovascular disease is reviewed to illustrate the diversity of approaches, and discuss some of the key metabolites and pathways found to be perturbed in plasma, urine and tissue from patients with these diseases. This includes studies of coronary artery disease, myocardial infarction, and ischemic heart disease. These studies demonstrate the potential of the technology for biomarker discovery and elucidating metabolic mechanisms associated with given pathologies, but also in some cases provide a warning of the pitfalls of poor study design. This article is part of a Special Issue entitled "Focus on Cardiac Metabolism". 10.1016/j.yjmcc.2012.12.001
    Metabolomic profiling for the identification of novel biomarkers and mechanisms related to common cardiovascular diseases: form and function. Shah Svati H,Kraus William E,Newgard Christopher B Circulation 10.1161/CIRCULATIONAHA.111.060368
    Implementing cardiovascular risk reduction in patients with cardiovascular disease and diabetes mellitus. Nandish Shailesh,Wyatt Jamison,Bailon Oscar,Smith Mike,Oliveros Rene,Chilton Robert The American journal of cardiology The role of cardiovascular risk reduction in patients with diabetes mellitus is significant as several factors have been found to promote accelerated atherosclerosis in persons with diabetes including hyperglycemia-induced endothelial dysfunction, impaired fibrinolysis, increased platelet aggregation, plaque instability, dysfunctional arterial remodeling, and fibrotic and calcified coronary arteries. Recent attention has focused on identifying a cardiovascular biomarker that would propose a better noninvasive way to detect or visualize subclinical cardiovascular disease and prevent cardiovascular events. This article reviews the use of commonly used cardiovascular risk assessment tools and emerging biomarkers including coronary artery calcium scanning, metabolomics, genomics, and the role of optimal revascularization and risk reduction strategies and their impact on reducing risk in patients with cardiovascular disease and diabetes. 10.1016/j.amjcard.2011.03.015
    Metabolomics as a tool for cardiac research. Griffin Julian L,Atherton Helen,Shockcor John,Atzori Luigi Nature reviews. Cardiology Metabolomics represents a paradigm shift in metabolic research, away from approaches that focus on a limited number of enzymatic reactions or single pathways, to approaches that attempt to capture the complexity of metabolic networks. Additionally, the high-throughput nature of metabolomics makes it ideal to perform biomarker screens for diseases or follow drug efficacy. In this Review, we explore the role of metabolomics in gaining mechanistic insight into cardiac disease processes, and in the search for novel biomarkers. High-resolution NMR spectroscopy and mass spectrometry are both highly discriminatory for a range of pathological processes affecting the heart, including cardiac ischemia, myocardial infarction, and heart failure. We also discuss the position of metabolomics in the range of functional-genomic approaches, being complementary to proteomic and transcriptomic studies, and having subdivisions such as lipidomics (the study of intact lipid species). In addition to techniques that monitor changes in the total sizes of pools of metabolites in the heart and biofluids, the role of stable-isotope methods for monitoring fluxes through pathways is examined. The use of these novel functional-genomic tools to study metabolism provides a unique insight into cardiac disease progression. 10.1038/nrcardio.2011.138
    NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort. Vignoli Alessia,Tenori Leonardo,Giusti Betti,Takis Panteleimon G,Valente Serafina,Carrabba Nazario,Balzi Daniela,Barchielli Alessandro,Marchionni Niccolò,Gensini Gian Franco,Marcucci Rossella,Luchinat Claudio,Gori Anna Maria BMC medicine BACKGROUND:Risk stratification and management of acute myocardial infarction patients continue to be challenging despite considerable efforts made in the last decades by many clinicians and researchers. The aim of this study was to investigate the metabolomic fingerprint of acute myocardial infarction using nuclear magnetic resonance spectroscopy on patient serum samples and to evaluate the possible role of metabolomics in the prognostic stratification of acute myocardial infarction patients. METHODS:In total, 978 acute myocardial infarction patients were enrolled in this study; of these, 146 died and 832 survived during 2 years of follow-up after the acute myocardial infarction. Serum samples were analyzed via high-resolution H-nuclear magnetic resonance spectroscopy and the spectra were used to characterize the metabolic fingerprint of patients. Multivariate statistics were used to create a prognostic model for the prediction of death within 2 years after the cardiovascular event. RESULTS:In the training set, metabolomics showed significant differential clustering of the two outcomes cohorts. A prognostic risk model predicted death with 76.9% sensitivity, 79.5% specificity, and 78.2% accuracy, and an area under the receiver operating characteristics curve of 0.859. These results were reproduced in the validation set, obtaining 72.6% sensitivity, 72.6% specificity, and 72.6% accuracy. Cox models were used to compare the known prognostic factors (for example, Global Registry of Acute Coronary Events score, age, sex, Killip class) with the metabolomic random forest risk score. In the univariate analysis, many prognostic factors were statistically associated with the outcomes; among them, the random forest score calculated from the nuclear magnetic resonance data showed a statistically relevant hazard ratio of 6.45 (p = 2.16×10). Moreover, in the multivariate regression only age, dyslipidemia, previous cerebrovascular disease, Killip class, and random forest score remained statistically significant, demonstrating their independence from the other variables. CONCLUSIONS:For the first time, metabolomic profiling technologies were used to discriminate between patients with different outcomes after an acute myocardial infarction. These technologies seem to be a valid and accurate addition to standard stratification based on clinical and biohumoral parameters. 10.1186/s12916-018-1240-2