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The Metabolome Profiling and Pathway Analysis in Metabolic International Journal of Obesity (2015) 39, 1241–1248 © 2015 Macmillan Publishers Limited All rights reserved 0307-0565/15 www.nature.com/ijo ORIGINAL ARTICLE The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity H-H Chen1, YJ Tseng2,3,4,5, S-Y Wang3,5, Y-S Tsai6, C-S Chang6,7, T-C Kuo4,5, W-J Yao8, C-C Shieh6, C-H Wu7,9 and P-H Kuo1,10 OBJECTIVES: Mechanisms of the development of abnormal metabolic phenotypes among obese population are not yet clear. In this study, we aimed to screen metabolomes of both healthy and subjects with abnormal obesity to identify potential metabolic pathways that may regulate the different metabolic characteristics of obesity. METHODS: We recruited subjects with body mass index (BMI) over 25 from the weight-loss clinic of a central hospital in Taiwan. Metabolic healthy obesity (MHO) is defined as without having any form of hyperglycemia, hypertension and dyslipidemia, while metabolic abnormal obesity (MAO) is defined as having one or more abnormal metabolic indexes. Serum-based metabolomic profiling using both liquid chromatography–mass spectrometry and gas chromatography–mass spectrometry of 34 MHO and MAO individuals with matching age, sex and BMI was performed. Conditional logistic regression and partial least squares discriminant analysis were applied to identify significant metabolites between the two groups. Pathway enrichment and topology analyses were conducted to evaluate the regulated pathways. RESULTS: A differential metabolite panel was identified to be significantly differed in MHO and MAO groups, including L-kynurenine, glycerophosphocholine (GPC), glycerol 1-phosphate, glycolic acid, tagatose, methyl palmitate and uric acid. Moreover, several metabolic pathways were relevant in distinguishing MHO from MAO groups, including fatty acid biosynthesis, phenylalanine metabolism, propanoate metabolism, and valine, leucine and isoleucine degradation. CONCLUSION: Different metabolomic profiles and metabolic pathways are important for distinguishing between MHO and MAO groups. We have identified and discussed the key metabolites and pathways that may prove important in the regulation of metabolic traits among the obese, which could provide useful clues to study the underlying mechanisms of the development of abnormal metabolic phenotypes. International Journal of Obesity (2015) 39, 1241–1248; doi:10.1038/ijo.2015.65 INTRODUCTION individuals share a similar total body fat percentage, but the MHO 6,7 Worldwide, obesity is associated with increased mortality and high group has lower visceral fat content than the MAO group. prevalence of metabolic-related diseases. In particular, there is an Moreover, the MHO group shows a significantly lower percentage 6,7 increased risk of insulin resistance, hypertension and dyslipidemia of ectopic fat, especially in the muscle and liver. The MHO group in the obese population.1 Nevertheless, about 10–30% of also exhibits a higher level of physical activity in comparison with obese individuals are reported to be insulin sensitive, having the MAO group.3 Our current knowledge about the causes and normal blood pressure and lipid profiles. In other words, a certain regulation pathways of different obesity-related metabolic profiles proportion of obese individuals possess a relatively healthy is still limited, despite the increasing awareness of disparate metabolic status.2,3 Previous studies have shown that the clinical outcomes of the two obese groups. Therefore, using a metabolically healthy obesity (MHO) group has a lower mortality more innovative and comprehensive screening tool is essential to and has a lower risk of developing metabolic diseases explore the differences between the MHO and MAO groups. (for example, diabetes and hypertension) compared with the Among numerous 'omics' technologies, metabolomics is often metabolic abnormal obesity (MAO)4,5 group. used to profile small endogenous molecules, or metabolites that Although the underlying mechanisms of the metabolic regula- are present in biological samples. Metabolites are the intermedi- tion are not yet clear, several attempts have been made to ates or products of different metabolic pathways. Therefore, their investigate relevant factors for distinguishing the MHO and MAO, concentrations could be influenced by innate genetic predisposi- such as adipose hormone, fat tissue distribution and life style. tion, environmental exposures or stimuli, as well as interactions For instance, higher level of adiponectin is associated with MHO between the two. Unlike genomics, the metabolome represents status, and this effect is independent of obesity severity.2 When the organisms’ conditions at any given time, and thus is able to considering body composition, metabolic healthy and abnormal capture the dynamic physiological condition corresponding to the 1Department of Public Health and Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan; 2School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; 3Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan; 4Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Taipei, Taiwan; 5The Metabolomics Core Laboratory, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan; 6Institute of Clinical Medicine, National Cheng Kung University Medical College, Tainan, Taiwan; 7Department of Family Medicine, National Cheng Kung University Hospital, Tainan, Taiwan; 8Department of Nuclear Medicine, National Cheng Kung University Hospital, Tainan, Taiwan; 9Institute of Behavioral Medicine, National Cheng Kung University Medical College, Tainan, Taiwan and 10Research Center for Genes, Environment and Human Health, National Taiwan University, Taipei, Taiwan. Correspondence: Dr C-H Wu, Department of Family Medicine, National Cheng Kung University Hospital, 138 Sheng-Li Road, Tainan, Taiwan or Professor P-H Kuo, Department of Public Health, Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University; Room 521, No. 17 Xuzhou Road, Taipei 100, Taiwan. E-mail: [email protected] or [email protected] Received 23 September 2014; revised 23 March 2015; accepted 12 April 2015; accepted article preview online 24 April 2015; advance online publication, 26 May 2015 Metabolome profiling for metabolic healthy obesity H-H Chen et al 1242 behavioral and clinical outcomes of interests. The development of except in the WC.16 On the contrary, individuals who had one or more obesity and its related metabolic phenotypes is a process involved abnormal metabolic indexes were placed in the MAO group. with both genetic and environmental (for example, diet and life style) factors. To investigate the complex molecular differences Metabolome profile between the MAO and MHO groups, conducting a global analysis The metabolomic profiling experiments were conducted by the Metabo- of metabolites provides an ideal way to uncover the underlying lomics Core Laboratory at Center of Genomic Medicine at National Taiwan mechanisms for the development of abnormal metabolic status University. Plasma samples were obtained after 8 h of fasting and stored at in obese individuals.8 Previously, metabolomics studies have been − 80 °C. LC-MS and GC-MS were used to perform the metabolomics profile applied to search for relevant metabolic pathways for obesity, analysis. The quality controls of samples were obtained by pooling aliquots diabetes and dyslipidemia.9–14 However, to the best of our from each plasma sample. All of the samples were extracted with 400 μlof knowledge, this approach has not yet been directly applied to methanol and analyzed using an Agilent 1290 UHPLC system coupled to a investigate the metabolomic profiles of the MAO and MHO 6540-QTOF (Agilent Technologies, Santa Clara, CA, USA). An Acquity HSS T3 μ groups. column (100 × 2.1 mm, 1.8 m; Waters, Milford, MA, USA) was used for the In the present study, we have aimed to identify important separation and the column was maintained at 40 °C. For sample ionization, a Jet Stream electrospray ionization source was used with a capillary metabolites to distinguish a normal metabolic state from an voltage of 4.0 kV in positive and negative mode. The MS parameters abnormal obesity metabolome. Both a targeted and untargeted were set as follows: gas temperature, 325 °C; gas flow, 5 l min−1; Nebulizer, analysis was employed in this study. The targeted analysis was 40 p.s.i.; sheath gas temperature, 325 °C; sheath gas flow, 10 l min−1; and compared against a library of 820 metabolites. We also mapped fragmentor, 120 V. A scan range of 50–1700 m/z was set. relevant metabolites to their corresponding metabolic pathways GC-MS was also applied. Plasma samples were extracted with 400 μl fi of methanol and derivatized using methoxyamine hydrochloride to pro le the underlying mechanisms of metabolic regulation −1 among obese individuals. To achieve our objective, we conducted (40 mg ml ) and derivatization agent (BSTFA+TMCS, 99:1). The instrument a metabolomics study in an age, sex and BMI paired sample of used an Agilent 7890 A gas chromatograph system (Agilent Technologies) coupled to an Agilent 5975 MSD mass spectrometer (Agilent Technolo- MAO and MHO individuals using both liquid chromatography/ gies). The column used for separation was a 10-m Duragard integrated fl time-of- ight mass spectrometry (LC-MS) and gas chromatogra- Agilent 122-5532G DB5-MS (30
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