%0 Journal Article
%T Metabonomics-based omics study and atherosclerosis
%A Duo-jiao Wu
%A Bi-jun Zhu
%A Xiang-dong Wang
%J Journal of Clinical Bioinformatics
%D 2011
%I BioMed Central
%R 10.1186/2043-9113-1-30
%X Living systems are dynamic and complex, and their behavior may be hard to predict from the properties of individual parts. Systems biology is the strategy of integrating complex data about the interactions in systems of biological components from diverse experimental sources using interdisciplinary tools and personnel [1]. Atherosclerosis is one of the leading causes responsible for cardiovascular morbidity and mortality, a complicated and multifactorial disease associated with genotypes and environmental factors [2,3]. It has been suggested that lipid and inflammatory component play an important role in the pathogenesis of atherosclerosis. Metabonomics is the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification [4]. It is expected that metabonomics will become a more and more important global systems biology tool. Recently metabonomics has been used in conjunction with proteomics and transcriptomics as part of a systems biology description of cardiovascular disease. It utilizes 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 [5]. Various metabolites have been identified as indicators for a variety of diseases [6,7]. The concentrations of metabolites often vary in response to therapy or disease stage. Furthermore, the metabolites could be used as biomarkers to carry information about the sites and mechanisms of disease. Metabolites have also been used as predictive model for disease risk, individual susceptibility, or as markers of recovery from an illness [8].Metabolomics requires the employment of efficient analytical tools simultaneously together with bioinformatics. Nevertheless, there is not a single analytical platform nowadays capable of analyzing the full set of metabolites in a biological sample. Metabonomics, and the related field of metab
%K Metabonomics
%K metabolomics
%K atherosclerosis
%K metabolic disturbances
%K inflammation
%U http://www.jclinbioinformatics.com/content/1/1/30