A Metabonomics Study About Metformin In Healthy Volunteers Based On UPLC/Q-TOF-MS

Metformin is the foundation medication for type 2 diabetes, and its mechanism is not fully understood. The majority view is that the effect of metformin on AMPK pathways, reduces the active adipose tissue hormone-sensitive lipase and the expression of liver-related enzymes, while acting on the muscle tissue, enhances glucose transport, ultimately lowering free fatty acids, blood fat and blood glucose. In recent years, more and more evidence shows that metformin has the effects of anti-inflammatory, anti-tumor, anti-aging and other biological effects. Its mechanism of action has attracted more and more attention. Since the role of metformin ranges widely with certain systemic, it should be noted the wide range of effects of metformin from whole organism level.Metabolomics(or metabonomics) is a new branch of science under the development of system biology recently. Based on the high throughput and highly sensitive analytical technology, metabolomics studies all metabolites(endogenous and exogenous metabolites) in biological systems, reflects the final results of perturbations upstream or directly from environment andreveals and resolves drug action pathways. Metabolomics has become an important tool for analyzing changes in drug metabolism pathways,particularly in the application of the mechanism of drug action research increasingly widespread.Objective:In this study, high sensitivity, high accuracy, high resolution, fast,automated UPLC/Q-TOF-MS research platform for the metabolomics analysis of metformin taking groups and the healthy volunteer’s serum samples, to analysis the changes in serum metabolites levels of metformin in the healthy human body, and find possible differences in metabolites. To provide a basis for finding metformin mechanism of its action.Methods:Based on the platform of UPLC/Q-TOF-MS, a comprehensive metabolomics approach has been applied to explore the changes of metabolic profiling on short-term metformin group(n = 18, 4h dosed with metformin), long-term metformin group(n = 18, 72 h dosed with metformin)and control group(n = 36, none dosed with metformin) in serum. By the software of Marker View V1.2.1 on experimental raw data were extracted and normalized. Principal component analysis was performed using the software SIMCA-P13.0(PCA), using the PCA model to distinguish among the overall samples of its differences, preliminary knowing about the grouping of the samples. Using orthogonal partial least squaresdiscriminant analysis(OPLS-DA) to establish statistical models, and further analysis of the differences among samples. According to the important projection(VIP) of the OPLS-DA model, VIP screening greater than the variable 1, combined with SPSS nonparametric test screen differences metabolites.Results:The metformin taking groups and controls can separated in the score plots of PCA and OPLS-DA models. In the 4h dosed with metformin group,16 potential biomarkers of the increase in the levels of Cer(d18:0/16:0),Cer(d18:0/14:0), Cer(d18:0/16:0), phytosphingosine, palmitic amide,phenylalanylphenylalanine, creatinine, allolithocholic acid, 8,9-DiHETrE,14,15-DiHETrE, 3beta-hydroxypregn-5-en-20-one sulfate, palmitoleoyl ethanolamide, L-acetyl carnitine, L-carnitine and decresed in the levels of D-glucose, o-tyrosine were found. In the 72 h dosed with metformin group,18 potential biomarkers of the increase in the levels of Cer(d18:0/16:0),Cer(d18:0/14:0), Cer(d18:0/14:0), alpha-linolenic acid, bovinic acid,arachidonate, phytosphingosine, betaine, choline, palmitic amide,8,9-DiHETrE, 14,15-DiHETrE, 12-oxo-20-trihydroxy-leukotriene B4,leukotriene F4, 10,11-dihydro-12-oxo-LTB4, bovinic acid, 3-Methylindole,L-carnitine and decreased in the levels of L-histidine were identified.Conclusions:Metformin into a healthy body 4h, 72 h, through the amino acids, fattyacids, carbohydrates and other metabolic pathways, we found differences in metabolites of anti-inflammatory, anti-tumor and anti-aging, we also found differences of metabolites with diabetes, cardiovascular disease, mental illness and so on. By analyzing metformin’s metabolites in healthy volunteers, under the premise of exclusion of disease’s affecting to look for the mechanism of action of metformin, broaden metformin’s therapeutic spectrum, and provide new ideas for the treatment of different diseases.