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The Tsuruoka Metabolomics Cohort Study (TMCS) is an ongoing population-based cohort study being conducted in the rural area of Yamagata Prefecture, Japan. This study aimed to enhance the precision prevention of multi-factorial, complex diseases, including non-communicable and aging-associated diseases, by improving risk stratification and prediction measures. At baseline, 11,002 participants aged 35-74 years were recruited in Tsuruoka City, Yamagata Prefecture, Japan, between 2012 and 2015, with an ongoing follow-up survey. Participants underwent various measurements, examinations, tests, and questionnaires on their health, lifestyle, and social factors. This study uses an integrative approach with deep molecular profiling to identify potential biomarkers linked to phenotypes that underpin disease pathophysiology and provide better mechanistic insights into social health determinants. The TMCS incorporates multi-omics data, including genetic and metabolomic analyses of 10,933 participants, and comprehensive data collection ranging from physical, psychological, behavioral, and social to biological data. The metabolome is used as a phenotypic probe because it is sensitive to changes in physiological and external conditions. The TMCS focuses on collecting outcomes for cardiovascular disease, cancer incidence and mortality, disability and functional decline due to aging and disease sequelae, and the variation in health status within the body represented by omics analysis that lies between exposure and disease. It contains several sub-studies on aging, heated tobacco products, and women's health. This study is notable for its robust design, high participation rate (89%), and long-term repeated surveys. Moreover, it contributes to precision prevention in Japan and East Asia as a well-established multi-omics platform.

Currently, large-scale cohort studies for metabolome analysis have been launched globally. However, only a few studies have evaluated the reliability of urinary metabolome analysis. This study aimed to establish the reliability of urinary metabolomic profiling in cohort studies. In the Tsuruoka Metabolomics Cohort Study, 123 charged metabolites were identified and routinely quantified using capillary electrophoresis-mass spectrometry (CE-MS). We evaluated approximately 750 quality control (QC) samples and 6,720 participants' spot urine samples. We calculated inter- and intra-batch coefficients of variation in the QC and participant samples and technical intraclass correlation coefficients (ICC). A correlation of metabolite concentrations between spot and 24-h urine samples obtained from 32 sub-cohort participants was also evaluated. The coefficient of variation (CV) was less than 20% for 87 metabolites (70.7%) and 20-30% for 19 metabolites (15.4%) in the QC samples. There was less than 20% inter-batch CV for 106 metabolites (86.2%). Most urinary metabolites would have reliability for measurement. The 96 metabolites (78.0%) was above 0.75 for the estimated ICC, and those might be useful for epidemiological analysis. Among individuals, the Pearson correlation coefficient of 24-h and spot urine was more than 70% for 59 of the 99 metabolites. These results show that the profiling of charged metabolites using CE-MS in morning spot human urine is suitable for epidemiological metabolomics studies.

Background: Cohort 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., Methods: Metabolomic 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 Conclusions: In 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.

Objective: Physical 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., Methods: A 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., Results: Higher 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., Conclusions: Physical 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., Competing Interests: The authors have declared that no competing interests exist.

Objective: Metabolomics 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). Methods: Fasting 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. Results: Nineteen 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). Conclusions: We 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. [ABSTRACT FROM AUTHOR]

Branched-chain amino acids (BCAAs) play a key role in energy homeostasis. We aimed to investigate the association between plasma BCAA levels and dyslipidemia in the Japanese population without diabetes mellitus. This cross-sectional study included 4952 participants without diabetes mellitus, enrolled in the Tsuruoka Metabolomic Cohort Study. Plasma BCAA levels were measured by capillary electrophoresis–mass spectrometry. Correlations between lipid and BCAA profiles were evaluated by sex-stratified multiple linear regression analyses, after adjusting for confounders. Logistic regression was used to identify associations between BCAAs and metabolic dyslipidemia (MD) defined as triglyceride levels ≥150 mg/dL, high-density lipoprotein cholesterol levels ≤40 mg/dL for men and ≤50 mg/dL for women, or low-density lipoprotein cholesterol (LDL-C) levels ≥140 mg/dL. In both sexes, the levels of individual BCAAs and the total BCAA levels correlated positively with triglyceride levels and negatively with high-density lipoprotein cholesterol levels. Valine, leucine, and total BCAA levels were weakly and positively correlated with LDL-C levels. Increased BCAA levels showed positive associations with MD. However, associations between BCAAs and elevated LDL-C levels were unclear. Furthermore, the associations between BCAA levels and MD regardless of fasting blood sugar (FBS) levels (high or low). Although valine, leucine, and total BCAA levels were weakly associated with elevated LDL-C levels in the high-FBS group, no such association was observed in the low-FBS group. BCAAs might be associated with MD independently of the FBS level and might play an important role in lipid metabolism and dyslipidemia. • Overall and individual BCAA plasma levels correlate with triglyceride levels. • They also correlate inversely with levels of HDL-cholesterol. • High BCAA levels increase risk of dyslipidemia, especially metabolic dyslipidemia. • These relationships are not affected by age, sex, or fasting blood sugar. • BCAAs might play an important role in lipid metabolism. [ABSTRACT FROM AUTHOR]

Background: Emerging evidence has shown that charged metabolites, such as amino acids, may play an important role in the pathogenesis of various metabolic disorders, many of which women in the postmenopausal period are at high risk of developing. This study examined the metabolic profile of middle-aged Japanese women to investigate alterations in charged metabolites induced by menopausal transition.Methods: The participants were 1193 female residents aged 40-60 at the baseline survey of the Tsuruoka Metabolomics Cohort Study. We investigated the cross-sectional association of menopausal status with 94 metabolomic biomarkers assayed in fasting plasma samples via capillary electrophoresis time-of-flight mass spectrometry using linear regression analysis.Results: Among the participants, 529 were premenopausal, 132 were in menopausal transition (MT), and 532 were postmenopausal. Significant differences were found in age, blood pressure, glucose and lipid levels, and smoking and drinking habits among the three groups. The concentrations of 5 metabolites in the MT group and 15 metabolites in the postmenopausal group were significantly higher than those in the premenopausal group after adjusting for confounding factors. When classified into pathways, these metabolites were related to the tricarboxylic cycle, urea cycle, and homocysteine metabolism, some of which are linked to arteriosclerosis.Conclusion: Multiple charged metabolites were associated with women's menopausal status, showing a gradual increase as women shifted from pre-, to peri-, to postmenopause. These findings might reflect the early changes behind the increased risk of dyslipidemia, diabetes, cardiovascular disease, and osteoporosis in later life. [ABSTRACT FROM AUTHOR]