ObjectiveMetabolomics is a promising approach to the identification of biomarkers in plasma. Here, we performed a population-based, cross-sectional study to identify potential biomarkers of alcohol intake and alcohol-induced liver injury by metabolomic profiling using capillary electrophoresis-mass spectrometry (CE-MS).MethodsFasting plasma samples were collected from 896 Japanese men who participated in the baseline survey of the Tsuruoka Metabolomics Cohort Study, and 115 polar metabolites were identified and absolutely quantified by CE-MS. Information on daily ethanol intake was collected through a standardized, self-administered questionnaire. The associations between ethanol intake and plasma concentration of metabolites were examined. Relationships between metabolite concentrations or their ratios and serum liver enzyme levels in the highest ethanol intake group (>46.0 g/day) were then examined by linear regression analysis. Replication analysis was conducted in 193 samples collected from independent population of this cohort.ResultsNineteen metabolites were identified to have an association with daily alcohol consumption both in the original and replication population. Three of these metabolites (threonine, glutamine, and guanidinosuccinate) were found to associate well with elevated levels of serum liver enzymes in the highest ethanol intake group, but not in the non-drinker group. We also found that the glutamate/glutamine ratio had a much stronger relation to serum γ-glutamyltransferase, aspartate transaminase, and alanine transaminase than glutamate or glutamine alone (standardized beta = 0.678, 0.558, 0.498, respectively).ConclusionsWe found 19 metabolites associated with alcohol intake, and three biomarker candidates (threonine, guanidinosuccinate and glutamine) of alcohol-induced liver injury. Glutamate/glutamine ratio might also be good biomarker.Electronic supplementary materialThe online version of this article (doi:10.1007/s12199-015-0494-y) contains supplementary material, which is available to authorized users.

BackgroundCohort studies with metabolomics data are becoming more widespread, however, large-scale studies involving 10,000s of participants are still limited, especially in Asian populations. Therefore, we started the Tsuruoka Metabolomics Cohort Study enrolling 11,002 community-dwelling adults in Japan, and using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography–mass spectrometry. The CE-MS method is highly amenable to absolute quantification of polar metabolites, however, its reliability for large-scale measurement is unclear. The aim of this study is to examine reproducibility and validity of large-scale CE-MS measurements. In addition, the study presents absolute concentrations of polar metabolites in human plasma, which can be used in future as reference ranges in a Japanese population.MethodsMetabolomic profiling of 8,413 fasting plasma samples were completed using CE-MS, and 94 polar metabolites were structurally identified and quantified. Quality control (QC) samples were injected every ten samples and assessed throughout the analysis. Inter- and intra-batch coefficients of variation of QC and participant samples, and technical intraclass correlation coefficients were estimated. Passing-Bablok regression of plasma concentrations by CE-MS on serum concentrations by standard clinical chemistry assays was conducted for creatinine and uric acid.Results and conclusionsIn QC samples, coefficient of variation was less than 20% for 64 metabolites, and less than 30% for 80 metabolites out of the 94 metabolites. Inter-batch coefficient of variation was less than 20% for 81 metabolites. Estimated technical intraclass correlation coefficient was above 0.75 for 67 metabolites. The slope of Passing-Bablok regression was estimated as 0.97 (95% confidence interval: 0.95, 0.98) for creatinine and 0.95 (0.92, 0.96) for uric acid. Compared to published data from other large cohort measurement platforms, reproducibility of metabolites common to the platforms was similar to or better than in the other studies. These results show that our CE-MS platform is suitable for conducting large-scale epidemiological studies.

ObjectivePhysical activity is known to be preventive against various non-communicable diseases. We investigated the relationship between daily physical activity level and plasma metabolites using a targeted metabolomics approach in a population-based study.MethodsA total of 1,193 participants (male, aged 35 to 74 years) with fasting blood samples were selected from the baseline survey of a cohort study. Information on daily total physical activity, classified into four levels by quartile of metabolic equivalent scores, and sedentary behavior, defined as hours of sitting per day, was collected through a self-administered questionnaire. Plasma metabolite concentrations were quantified by capillary electrophoresis mass spectrometry method. We performed linear regression analysis models with multivariable adjustment and corrected p-values for multiple testing in the original population (n = 808). The robustness of the results was confirmed by replication analysis in a separate population (n = 385) created by random allocation.ResultsHigher levels of total physical activity were associated with various metabolite concentrations, including lower concentrations of amino acids and their derivatives, and higher concentrations of pipecolate (FDR p <0.05 in original population). The findings persisted after adjustment for age, body mass index, smoking, alcohol intake, and energy intake. Isoleucine, leucine, valine, 4-methyl-2-oxoisopentanoate, 2-oxoisopentanoate, alanine, and proline concentrations were lower with a shorter sitting time.ConclusionsPhysical activity is related to various plasma metabolites, including known biomarkers for future insulin resistance or type 2 diabetes. These metabolites might potentially play a key role in the protective effects of higher physical activity and/or less sedentary behavior on non-communicable diseases.

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Objective:The aim of the study was to investigate the associations of amino acids and other polar metabolites with metabolic syndrome (MetS) in postmenopausal women in a lean Asian population.Methods:The participants were 1,422 female residents enrolled in a cohort study from April to August 2012. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III modified for Japanese women. Associations were examined between MetS and 78 metabolites assayed in fasting plasma samples using capillary electrophoresis-mass spectrometry. Replication analysis was performed to confirm the robustness of the results in a separate population created by random allocation.Results:Analysis was performed for 877 naturally postmenopausal women, including 594 in the original population and 283 in the replication population. The average age, body mass index, and levels of high- and low-density lipoprotein cholesterol of the entire population were 64.6 years, 23.0 kg/m2, 72.1 mg/dL, and 126.1 mg/dL, respectively. There was no significant difference in low-density lipoprotein cholesterol levels between women with and without MetS. Thirteen metabolites were significantly related to MetS: multiple plasma amino acids were elevated in women with MetS, including branched-chain amino acids, alanine, glutamate, and proline; and alpha-aminoadipate, which is generated by lysine degradation, was also significantly increased.Conclusions:Our large-scale metabolomic profiling indicates that Japanese postmenopausal women with MetS have abnormal polar metabolites, suggesting altered catabolic pathways. These results may help to understand metabolic disturbance, including in persons with normal body mass index and relatively high levels of high-density lipoprotein cholesterol, and may have clinical utility based on further studies.