Published papers

Background: The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies. Method: We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure. Result: Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle). Conclusion: These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Objectives To date, the association between accumulated unhealthy behaviours and insomnia in individuals stratified according to the presence or absence of major cardiovascular risk factors is unclear. This study aimed to examine the effect of accumulated unhealthy behaviours on insomnia in Japanese dwellers. Design Cross-sectional study. Setting Baseline data between April 2012 and March 2015. Participants Our study used cross-sectional data among Japanese aged 35-74 years in a rural community (N=9565), the attendees of annual municipal or work site health check-up programmes. Main outcome measures Insomnia was assessed by Athens Insomnia Scale, which was set at 6 points and greater; other scales were given. Participants were categorised into three groups by their number of unhealthy behaviours (no exercise habit, smoking, alcohol drinking, skipping breakfast and obesity): 0-1, 2-3, 4 or more. The association between accumulated unhealthy behaviours and insomnia was estimated by logistic regression analysis. Further analysis was done after stratification of cardiovascular risk factors assessed by anthropometrics and clinical biochemistry measurements. Results The overall prevalence of insomnia was 13.3% for men and 19.3% for women. Men with unhealthy behaviour factors were more likely to have insomnia after adjusting for potential confounders, compared with the least unhealthy group (trend p=0.013). Women with four or more unhealthy behaviour factors were more likely to have insomnia, compared with the lowest groups (OR 1.175, 95% CI 1.077 to 1.282). Insomnia has an association with the unhealthy behaviours among men without cardiovascular risk factors (lowest groups: OR 1.133, 95% CI 1.037 to 1.238, trend p=0.026). Women without hypertension were more likely to have suspected insomnia, compared with the lowest group (OR 1.215, 95% CI 1.101 to 1.341). Conclusion The results showed accumulated unhealthy behaviours were associated with increased risk of insomnia in Japanese dwellers. For healthy population without cardiovascular risk factors, unhealthy behaviours should be considered as background conditions for insomnia.

Aims: The categories in the comprehensive lipid and risk management guidelines were proposed by the Japan Atherosclerosis Society (JAS Guidelines 2017), which adopted the estimated 10 year absolute risk of coronary artery disease (CAD) incidence in the Suita score. We examined whether those categories were concordant with the degree of arterial stiffness. Methods: In 2014, the cardio-ankle vascular index (CAVI), an arterial stiffness parameter, was measured in 1,972 Japanese participants aged 35–74 years in Tsuruoka City, Yamagata Prefecture, Japan. We examined the mean CAVI and the proportion and odds ratios (ORs) of CAVI ≥ 9.0 on the basis of the following three management classifications using the analysis of variance and logistic regression: “Category I (Low risk),” “Category II (Middle risk),” and “Category III (High risk).” Results: The mean CAVI and proportion of CAVI ≥ 9.0 were 8.6 and 34.8% among males and 8.1 and 18.3% among females, respectively. The mean CAVI and proportion of CAVI ≥ 9.0 were associated with an estimated 10 year absolute risk for CAD among males and females, excluding High risk for females. These results were similar to the management classification by the guideline: the multivariable-adjusted ORs (95% confidence intervals) of CAVI ≥ 9.0 among Category II and Category III compared with those among Category I were 2.96 (1.61–5.43) and 7.33 (4.03–13.3) for males and 3.99 (2.55–6.24) and 3.34 (2.16–5.16) for females, respectively. Conclusions: The risk stratification, which was proposed in the JAS Guidelines 2017, is concordant with the arterial stiffness parameter.

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/m, 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.

© 2019 Japan Atherosclerosis Society. Metabolomics has developed as a powerful tool for investigating the complex pathophysiology underlying atherosclerosis and cardiovascular disease. Many epidemiological studies have applied this technique to accurately and comprehensively assess the effects of environmental factors on health outcomes, which used to be a perpetual challenge. Metabolites are defined as small molecules which are intermediate products of metabolic reactions catalyzed by numerous enzymes occurring within cells. Consequent to both genetic variation and environment, they allow us to explore the gene–environment interactions and to gain a better understanding of multifactorial diseases like cardiovascular disease. This review article highlights the findings of well-known prospective cohort studies around the world that have utilized metabolomics for a wide range of purposes, including biomarker discovery, improving cardiovascular risk prediction and early disease diagnosis, and exploring detailed mechanisms of disease onset and progression. However, technical challenges still exist in applying them clinically. One limitation is due to various analytical platforms that are used based on the judgment of each study; comparative assessments among different platforms need to be conducted in order to correctly interpret and validate each data externally. Secondly, metabolite levels obtained in most high-throughput metabolomics profiling studies are often semiquantitative rather than fully quantitative concentrations, which makes it difficult to compare and combine results among different studies and to determine the levels for practical use. In 2014, the Consortium of Metabolomics Studies was developed, which is expected to take the lead in overcoming these issues.

© 2019 National Lipid Association Background: Branched-chain amino acids (BCAAs) play a key role in energy homeostasis. Objective: We aimed to investigate the association between plasma BCAA levels and dyslipidemia in the Japanese population without diabetes mellitus. Methods: 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. Results: 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. Conclusions: BCAAs might be associated with MD independently of the FBS level and might play an important role in lipid metabolism and dyslipidemia.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Rapid lifestyle and dietary changes have contributed to a rise in the global prevalence of metabolic syndrome (MetS), which presents a potential healthcare crisis, owing to its association with an increased burden of multiple cardiovascular and neurological diseases. Prior work has identified the role that genetic, lifestyle, and environmental factors can play in the prevalence of MetS. Metabolomics is an important tool to study alterations in biochemical pathways intrinsic to the pathophysiology of MetS. We undertook a metabolomic study of MetS in serum samples from two ethnically distinct, well-characterized cohorts—the Baltimore Longitudinal Study of Aging (BLSA) from the U.S. and the Tsuruoka Metabolomics Cohort Study (TMCS) from Japan. We used multivariate logistic regression to identify metabolites that were associated with MetS in both cohorts. Among the top 25 most significant (lowest p-value) metabolite associations with MetS in each cohort, we identified 18 metabolites that were shared between TMCS and BLSA, the majority of which were classified as amino acids. These associations implicate multiple biochemical pathways in MetS, including branched-chain amino acid metabolism, glutathione production, aromatic amino acid metabolism, gluconeogenesis, and the tricarboxylic acid cycle. Our results suggest that fundamental alterations in amino acid metabolism may be central features of MetS.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Metabolic syndrome (MetS) affects an increasing number of older adults worldwide. Cross-cultural comparisons can provide insight into how factors, including genetic, environmental, and lifestyle, may influence MetS prevalence. Metabolomics, which measures the biochemical products of cell processes, can be used to enhance a mechanistic understanding of how biological factors influence metabolic outcomes. In this study we examined associations between serum metabolite concentrations, representing a range of biochemical pathways and metabolic syndrome in two older adult cohorts: The Tsuruoka Metabolomics Cohort Study (TMCS) from Japan (n = 104) and the Baltimore Longitudinal Study of Aging (BLSA) from the United States (n = 146). We used logistic regression to model associations between MetS and metabolite concentrations. We found that metabolites from the phosphatidylcholines-acyl-alkyl, sphingomyelin, and hexose classes were significantly associated with MetS and risk factor outcomes in both cohorts. In BLSA, metabolites across all classes were uniquely associated with all outcomes. In TMCS, metabolites from the amino acid, biogenic amines, and free fatty acid classes were uniquely associated with MetS, and metabolites from the sphingomyelin class were uniquely associated with elevated triglycerides. The metabolites and metabolite classes we identified may be relevant for future studies exploring disease mechanisms and identifying novel precision therapy targets for individualized medicine.

© 2018 Harada et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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.

Epigenetic regulatory mechanisms are a current focus in studies investigating cancer. Chromatin remodeling alters chromatin structure and regulates gene expression, and aberrant chromatin remodeling is involved in carcinogenesis. AT-rich interactive domain-containing protein 1A (ARID1A) and SWItch/sucrose non-fermentable-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4 are remodeling factors that are mutated in numerous types of cancer. In gynecological cancer, ARID1A mutations have been identified in 46-57% of clear cell carcinoma and 30% of endometrioid carcinoma. Mutations of chromodomain helicase, DNA-binding protein 4 have been detected in 17-21% of endometrial serous cancer, and mutations of ARID1A and mixed-lineage leukemia 3 occur in 36 and 27% of uterine carcinosarcoma, respectively. These data suggest that aberrant chromatin remodeling is a potential cause of cancer, and have led to the development of novel proteins targeting these processes. Additional accumulation of information on the mechanisms of chromatin remodeling and markers for these events may promote personalized anticancer therapies.

The increasing incidence of obesity and diabetes due to changes in diet, earlier menarche, delayed menopause, late marriage, and declining birth rate have resulted in an increase in the number of endometrial cancer cases over the last few decades. Although surgical therapy is sufficient for early endometrial cancer, there is no effective therapy for patients with advanced and recurrent endometrial cancer. The oncogenic mechanism of endometrial cancer involves microsatellite instability (MSI) caused by dysfunction of DNA mismatch repair genes in 30% of patients. Immune checkpoint inhibitors, including anti-programmed death (PD)-1 and anti-PD-ligand 1 antibodies, are of interest as novel anticancer drugs; however, these drugs are currently expensive, and there is a need to select patients who will benefit from their use. The use of MSI analysis as a predictive biomarker for the therapeutic efficacy of these drugs may be useful for reducing the costs of drug therapy.

Drug repositioning is an alternative strategy redirecting existing drugs for new disease. We have previously reported an antitumor effect of statins, antidyslipidemic drugs, on ovarian cancer in vitro and in vivo. In this study, we investigated the antitumor effects of other mevalonate pathway inhibitors and the mechanism of the antitumor effect from a metabolic perspective. The effects of inhibitors of the mevalonate pathway on tumor cell growth were evaluated in vitro. Bisphosphonates that inhibit this pathway are commonly used as antiosteoporotic drugs, and antitumor effects of the bisphosphonate were examined in vitro and in vivo. Metabolites in SKOV3 ovarian cancer cells were analyzed before and after lovastatin treatment, using capillary electrophoresis-mass spectrometry. All mevalonate pathway inhibitors showed concentration-dependent inhibitory effects on tumor cell growth. Particularly marked effects were obtained with inhibitors of farnesyltransferase and geranylgeranyltransferase. The bisphosphonate was also shown to have an antitumor effect in vivo. The expression of autophagy marker LC3A/3B was increased in cells after treatment. In metabolomics analysis, lovastatin treatment increased the metabolites involved in the tricarboxylic acid cycle while reducing the metabolites associated with glycolysis. Also it decreased glutathione and resulted to work with chemotherapeutic agents synergistically. Inhibition at any point in the mevalonate pathway, and especially of farnesyl pyrophosphate and geranylgeranyl pyrophosphate, suppresses growth of ovarian cancer cells. Inhibition of this pathway may induce autophagy, cause a shift to activation of the tricarboxylic acid cycle and enhance susceptibility to chemotherapy. Drug repositioning targeting mevalonate pathway for ovarian cancer deserves consideration for clinical application.

Cancer typically develops due to genetic abnormalities, but a single gene abnormality cannot completely account for the onset of cancer. The Cancer Genome Atlas (CGA) project was conducted for the cross-sectional genome-wide analysis of numerous genetic abnormalities in various types of cancer. This approach has facilitated the identification of novel AT-rich interaction domain 1A gene mutations in ovarian clear cell carcinoma, frequent tumor protein 53 (TP53) gene mutations in high-grade ovarian serous carcinoma, and Kirsten rat sarcoma and B-rapidly accelerated fibrosarcoma proto-oncogene, serine/threonine kinase gene mutations in low-grade ovarian serous carcinoma. Genome-wide analysis of endometrial cancers has led to the establishment of four subgroups: Polymerase ultramutated, microsatellite instability hypermutated, genome copy-number low and genome copy-number high. These results may facilitate the improvement of the prediction of patient prognosis and therapeutic sensitivity in various types of gynecologic cancer. The enhanced use of currently available therapeutic agents and the development of novel drugs may be facilitated by the novel classification of ovarian cancer based on TP53 mutations, the efficacy of poly (ADP-ribose) polymerase inhibitors for tumors with breast cancer 1/2 mutations and the effect of phosphoinositide-3-kinase (PI3K)/mammalian target of rapamycin inhibitors for tumors with mutations in the PI3K/protein kinase B signaling pathway. Important results have been revealed by genome-wide analyses; however, the pathogenic underlying mechanisms of gynecologic cancer will require further studies and multilateral evaluation using epigenetic, transcriptomic and proteomic analyses, in addition to genomic analysis.

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.

The AT-rich interacting domaincontaining protein 1A gene (ARID1A) encodes ARID1A, a member of the SWI/SNF chromatin remodeling complex. Mutation of ARID1A induces changes in expression of multiple genes (CDKN1A, SMAD3, MLH1 and PIK3IP1) via chromatin remodeling dysfunction, contributes to carcinogenesis, and has been shown to cause transformation of cells in association with the PI3K/AKT pathway. Information on ARID1A has emerged from comprehensive genomewide analyses with nextgeneration sequencers. ARID1A mutations have been found in various types of cancer and occur at high frequency in endometriosisassociated ovarian cancer, including clear cell adenocarcinoma and endometrioid adenocarcinoma, and also occur at endometrial cancer especially in endometrioid adenocarcinoma. It has also been suggested that ARID1A mutation occurs at the early stage of canceration from endometriosis to endometriosisassociated carcinoma in ovarian cancer and also from atypical endometrial hyperplasia to endometrioid adenocarcinoma in endometrial cancer. Therefore, development of a screening method that can detect mutations of ARID1A and activation of the PI3K/AKT pathway might enable early diagnosis of endometriosisassociated ovarian cancers and endometrial cancers. Important results may also emerge from a current clinical trial examining a multidrug regimen of temsirolimus, a small molecule inhibitor of the PI3K/AKT pathway, for treatment of advanced ovarian clear cell adenocarcinoma with ARID1A mutation and PI3K/AKT pathway activation. Also administration of sorafenib, a multikinase inhibitor, can inhibit cancer proliferation with PIK3CA mutation and resistance to mTOR inhibitors and GSK126, a moleculartargeted drug can inhibit proliferation of ARID1Amutated ovarian clear cell adenocarcinoma cells by targeting and inhibiting EZH2. Further studies are needed to determine the mechanism of chromatin remodeling dysregulation initiated by ARID1A mutation, to develop methods for early diagnosis, to investigate new cancer therapy targeting ARID1A, and to examine the involvement of ARID1A mutations in development, survival and progression of cancer cells.