The Risk Factors Exploration And LC-TOF-MS Based Metabolomics Analysis In Metabolic Syndrome Of Police

Objective1. To investigate the relationship between phenomenon of aggregation on multiple metabolic abnormalities (abnormal BMI, hypertension, abnormal glucose metabolism, dyslipidemia and central obesity) of metabolic syndrome in police and their family history and behaviors.2. Comparison metabolites change in serum and urine between metabolic syndrome patients and health subject, exploring the possible pathogenesis of metabolic syndrome.Methods1. In the cross sectional survey,6300police were randomly selected. All study subjects were screened with a detailed medical history, physical examination, and hematological and biochemical profile. At the same time, Standard police health questionnaire was acquired to be written. Multiple correspondence analyses were used to explore the aggregation of multiple metabolic abnormalities among police. Corresponding relationships between objects and their family history and behaviors were also analyzed.2. MetS patients and sex, age matched non-MetS healthy subjects were selected as study object. Metabonomics by using the technological platform of liquid chromatography time-of-flight mass spectrometry (LC-TOF-MS), the metabolite profiles of MS patients and healthy controls’ serum and urine samples are obtained under the multivariate statistical mode. Moreover, principal component analysis (PCA) and partial least-square discriminant analysis (PLS-DA) were applied to analyze the differences of the metabolic profile between the MS patients and healthy controls. The difference metabolites were identified. The MetS possible pathogenesis were explored by important difference metabolites.Results1. Cronbach’s alpha levels were0.692and0.603together with Eigen values as2.824 and2.289in two dimensions on the correspondence analysis of the polices’ and their parents’ multiple metabolic abnormalities; Cronbach’s alpha levels were0.707and0.416together with Eigen values as2.799and1.608in two dimensions on the correspondence analysis of the polices’ and their behaviorss; Cronbach’s alpha levels were0.694and0.595together with Eigen values as2.952and2.309in two dimensions on the correspondence analysis of the polices’ and their family history and behaviorss. There was an aggregation of variety metabolic abnormalities in both polices and their parents but not between objects and their parents; different behaviorsal factors clustered with different metabolic abnormalities.2. Separation trend of metabolite profiles in serum and urine can be detected between patients and healthy subjects, while obvious difference can be detected by PLS-DA. In ESI+mode, the serum PLS-DA R2Y (cum)=0.771, Q2(cum)=0.559, the urine PLS-DA R2Y (cum)=0.980, Q2(cum)=0.748; In ESI-mode, the serum PLS-DA R2Y (cum)=0.661, Q2(cum)=0.421,the urine PLS-DA R2Y (cum)=0.973, Q2(cum)=0.978.3. These were32important metabolites in patients’ serum after the LC-TOF-MS based metabonomic analysis,11of them were Lysophosphatidylcholine,3were lysophosphatidylethanolamine,4were carnitine and8were fatty acid. These were important substances for lipid synthesis and decomposition, bile acid synthesis and oxidative stress. In urine metabonomic analysis,68metabolites were preliminary identification which were involved in tricarboxylic acid cycle, fatty acid metabolism and oxidative stress.50of them increased in patients, which took part in TAC and fatty acid metabolism;18of them were decreased which were related to uric acid metabolism and some amino acid metabolism.Conclusion1. There was an aggregation of variety metabolic abnormalities in both polices and their parents, and the central obesity aggregated appeared more obviously with hyperlipidemia. Family histories of metabolic abnormalities played a moderate role in the generations suffering from multiple metabolic abnormalities, the prevalence of metabolic disease increased with increasing age.2. LC-TOF-MS-based metabolomics with serum and urine metabolic profiling can be used for the study of the metabolic syndrome.3. Energy metabolism and oxidative stress were important metabolic changes in metabolic syndrome patients.