RESUMO
Heart failure is the end stage of many cardiovascular diseases. It seriously affects the safety and quality of life of nearly 40 million people worldwide. At present, the clinical and pathophysiological characteristics of some types of heart failure are unknown, and there is no effective diagnosis and treatment. In recent years, genomics, transcriptomics, epigenomics, proteomics, metabolomics and other omics technologies have been widely used in disease research, providing new opportunities for the prevention, diagnosis and treatment of diseases. These strategies have also brought hope for the reduction in heart failure mortality. Based on the current status of clinical treatment of heart failure, this article reviews the roles and potential applications of these various omics technologies and their opportunities in the study of the pathogenesis of heart failure, clinical diagnosis and treatment, and related drug pharmacodynamics and mechanism of action.
RESUMO
The study was designed to explore the influence of high-fat diet on the metabolism profile of feces and intestinal contents of golden hamster to provide new information for the mechanism of drug action. Twelve golden hamsters fed with high-fat diet and twelve golden hamsters fed with normal diet were used as model group and control group, respectively. Serum samples were collected from the normal group and the model group at 2 weeks, 4 weeks and 8 weeks after the induction of high-fat diet. Serum biochemical parameters were measured in the control and model groups. The levels of triglyceride (TG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C) levels in model group were higher than the control group. After 8 weeks, the feces and intestine contents were taken. The intestine was divided into four sections:jejunum, ileum, cecum and colon. The changes of endogenous metabolites in intestinal contents were analyzed by 1H NMR based metabolomics combined with multivariate statistical analysis to find the significant differences in metabolites. The metabolic profiles of hyperlipidemia model group and control group were significantly distinguished by the othorgonal partial least squares-discriminate analysis, (OPLS-DA). Compared with the control group, the endogenous metabolites in feces such as amino acids, fatty acids, tricarboxylic acid cycle intermediates and nucleotides related to intestinal microflora were changed significantly (PP<0.05). The data suggest that the intestinal microflora plays an important role in the development of hyperlipidemia in golden hamsters from the molecular level of metabolites. This result provides useful information for the clinical treatment of hyperlipidemia and development of hyperlipidemia drug.