論文

Aims: Nonalcoholic fatty liver disease (NAFLD) is known to be associated with atherosclerosis. This study focused on upstream changes in the process by which NAFLD leads to atherosclerosis. The study aimed to confirm the association between NAFLD and the cardio-ankle vascular index (CAVI), an indicator of subclinical atherosclerosis, and explore metabolites involved in both by assessing 94 plasma polar metabolites.Methods: A total of 928 Japanese community-dwellers (306 men and 622 women) were included in this study. The association between NAFLD and CAVI was examined using a multivariable regression model adjusted for confounders. Metabolites commonly associated with NAFLD and CAVI were investigated using linear mixed-effects models in which batch numbers of metabolite measurements were used as a random-effects variable, and false discovery rate-adjusted p-values were calculated. To determine the extent to which these metabolites mediated the association between NAFLD and CAVI, mediation analysis was conducted.Results: NAFLD was positively associated with CAVI (coefficients [95% Confidence intervals (CI)]=0.23 [0.09–0.37]; p=0.001). A total of 10 metabolites were involved in NAFLD and CAVI, namely, branched-chain amino acids (BCAAs; valine, leucine, and isoleucine), aromatic amino acids (AAAs; tyrosine and tryptophan), alanine, proline, glutamic acid, glycerophosphorylcholine, and 4-methyl-2-oxopentanoate. Mediation analysis showed that BCAAs mediated more than 20% of the total effect in the association between NAFLD and CAVI.Conclusions: NAFLD was associated with a marker of atherosclerosis, and several metabolites related to insulin resistance, including BCAAs and AAAs, could be involved in the process by which NAFLD leads to atherosclerosis.

Objectives: Underweight or obesity is associated with infertility in women, but large cohort studies with a life course perspective are rare. We explored the association between body mass index (BMI) at age 18 and subsequent infertility among Japanese women. Study design: In total, 15,907 married women aged 30–44 years who participated in a prospective cohort baseline survey during 2001–2007 were cross-sectionally analyzed. Those with a history of cancer, and those with a partner with infertility or missing data were excluded. All data were obtained from self-reported questionnaires. Main outcome measures: The main outcome measure was infertility, defined as a self-reported history of infertility for at least 2 years. Age and cause of infertility were also recorded. Results: Overall, 2825 participants (17.8 %) reported being infertile. The proportions of women who were underweight (BMI <18.5 kg/m2), overweight (BMI ≥25 and < 30 kg/m2), and obese (BMI ≥ 30 kg/m2) at age 18 were 12.8 %, 4.5 %, and 0.4 %, respectively. Multiple logistic regression analysis revealed a 1.31-fold and a 1.82-fold increase in the rate of infertility in those women who were underweight or obese during adolescence, respectively, compared with those of normal weight. Further analysis by cause of infertility revealed no significant associations with overweight or obesity at age 18, but being underweight was positively associated with infertility of unknown cause. Conclusions: Being underweight or obese at adolescence is a potential risk factor for subsequent infertility among Japanese women. In particular, being underweight during adolescence may be a contributing factor to unexplained infertility later in life.

Aims: The association between alcohol consumption and the risk of cardiovascular disease (CVD) varies according to the presence of underlying cardiovascular risk factors. Incorporating such risk factors may be important to effectively reduce harmful alcohol use through health guidance. However, whether the risk of alcohol consumption is affected due to renal impairment remains unclear. Methods: A total of 10,583 community-dwelling Japanese adults (mean age 59.4 (SD 10.1) years; 46% men) were followed for 10 years. Alcohol consumption was categorized into five groups for men: never drinkers, former drinkers, light drinkers (＜20 g/day), moderate drinkers (20-39 g/day), and heavy drinkers (≥ 40 g/day), and four groups for women with moderate and heavy combined. Cox proportional hazards models estimated hazard ratios for incident CVD stratified by the presence or absence of reduced estimated glomerular filtration rate (eGFR) (＜60 mL/min/1.73m2) and proteinuria, with adjustment for confounders. Results: Among men with proteinuria, alcohol consumption was associated with a higher risk of atherosclerotic CVD, whereas an inverse association was observed in men without proteinuria [hazard ratio (95% confidence interval): moderate drinkers without proteinuria, 0.58 (0.34-0.97); moderate drinkers with proteinuria, 3.49 (1.15-10.56)]. Moderate to heavy drinking increased the risk of intracerebral hemorrhage irrespective of the renal status. In women, moderate to heavy drinking was associated with an increased CVD risk only when proteinuria was present. In contrast, a reduced eGFR did not clearly affect the association in either sex. Conclusions: The CVD risk associated with alcohol consumption may differ according to the renal status, particularly depending on the presence or absence of proteinuria.

Aims/Introduction: Obesity is a known risk factor for several chronic diseases, including type 2 diabetes mellitus, which results from increased insulin resistance and impaired insulin secretion. However, the association between obesity and insulin resistance in Asian populations has not yet been fully elucidated. Therefore, we aimed to investigate the causal relationship between body mass index (BMI) and glycemic traits using Mendelian randomization (MR). Materials and Methods: We performed individual-level MR analyses using genetic risk scores based on BMI-related variants in 3,745 individuals without diabetes mellitus from a Japanese cohort. We examined heterogeneity through subgroup analyses based on potential modifiers and determined the shape of the causal relationship using nonlinear MR analyses to further assess the impact of BMI on the homeostasis model assessment of insulin resistance (HOMA-IR). Results: MR analyses revealed a significant positive association between BMI and HOMA-IR (β = 0.077; 95% confidence interval, 0.014–0.141; P = 0.016; outcome variable was log-transformed and standardized). Additional analyses revealed heterogeneity among subgroups differentiated by age, sex, lifestyle habits, and cardiometabolic traits. Nonlinear MR analyses suggested a potential J-shaped causal relationship between BMI and HOMA-IR. Conclusions: Our findings demonstrated that obesity and low BMI may contribute to increased insulin resistance. Furthermore, the impact of BMI on insulin resistance could vary owing to effect modification. Managing BMI is crucial in individuals at high risk of increased insulin resistance and may have important implications for preventing type 2 diabetes, especially given the low insulin secretory capacity observed in East Asian populations.

Plasma amino acids (AAs) have emerged as promising biomarkers for metabolic disorders, yet their causality remains unclear. We aimed to investigate the genetic determinants of AA levels in a cohort of 10,333 individuals and their causal effects on cardiometabolic traits using Mendelian randomization (MR). Plasma levels of 20 AAs were quantified using capillary electrophoresis mass spectrometry. Genome-wide association studies were conducted using BOLT-LMM and heritability estimation via LDSC analysis. Causal effects of AAs on 11 cardiometabolic traits were examined using two-sample MR analyses. We identified 85 locus-metabolite associations across 43 genes for 18 AAs, including 44 novel loci linked to metabolic genes. Heritability for AAs was estimated at 16%. MR analysis demonstrated cystine to positively associate with systolic blood pressure (SBP) (β = 0.056, SE = 0.010), while serine indicated protective effects on SBP (β = − 0.040, SE = 0.011), diastolic BP (β = − 0.044, SE = 0.010), and coronary artery disease (odds ratio 0.888, SE = 0.028). We identified potentially novel genetic loci associated with AA levels and demonstrated robust causal associations between several AAs and cardiometabolic traits. These findings reinforce the importance of AAs as potential biomarkers and therapeutic targets in cardiometabolic health.

Context: Previous metabolomics studies suggest potential associations between menopausal changes in lipids and an increased risk of metabolic syndrome (MetS). However, longitudinal data on other key metabolites, such as branched-chain amino acids (BCAAs) and homocysteine, remain limited, and most studies lack long-term follow-up across the menopause transition. Objective: This study aimed to investigate longitudinal changes in circulating metabolites during menopause over a mean follow-up of 5 years and assess their associations with subsequent MetS development. Methods: Premenopausal women from the Tsuruoka Metabolomics Cohort Study who participated in at least one follow-up survey were included. Menopausal status, data on MetS, and plasma metabolites profiled using capillary electrophoresis mass spectrometry were assessed at each visit. Thirty-one metabolites were examined for associations with menopausal status using mixed-effects models. The association of these menopause-related metabolites with MetS development was examined via logistic regression analysis adjusted for follow-up duration. Results: Among 953 women (aged 43.8 ± 5.4 years), 316 (33.2%) reached menopause during follow-up (5.0 ± 1.1 years). Eighteen metabolites changed significantly with menopause, particularly those related to BCAA metabolism, urea cycle, and homocysteine metabolism. Of 695 women without MetS at baseline, 65 (9.4%) developed MetS. Glutamate (odds ratio [95% CI]: 1.95 [1.49-2.57]) was associated with higher MetS risk. Higher levels of glutamate, valine, leucine, and cystine were significantly associated with the development of hyperglycemia. Conclusion: Longitudinal changes in charged metabolites occur across the menopausal transition, with specific metabolites such as glutamate possibly contributing to the metabolic alterations underlying increased MetS risk.

Background: Heated tobacco products (HTPs) have gained global popularity, but their health risks remain unclear. Therefore, the current study aimed to identify plasma metabolites associated with smoking and HTP use in a large Japanese population to improve health risk assessment. Methods: Metabolomics data from 9,922 baseline participants of the Tsuruoka Metabolomics Cohort Study (TMCS) were analyzed to determine the association between smoking habits and plasma metabolites. Moreover, alterations in smoking-related metabolites among HTP users were examined based on data obtained from 3,334 participants involved from April 2018 to June 2019 in a follow-up survey. Results: Our study revealed that cigarette smokers had metabolomics profiles distinct from never smokers, with 22 polar metabolites identified as candidate biomarkers for smoking. These biomarker profiles of HTP users were closer to those of cigarette smokers than those of never smokers. The concentration of glutamate was higher in cigarette smokers, and biomarkers involved in glutamate metabolism were also associated with cigarette smoking and HTP use. Network pathway analysis showed that smoking was associated with the glutamate pathway, which could lead to endothelial dysfunction and atherosclerosis of the vessels. Conclusion: Our study showed that the glutamate pathway is affected by habitual smoking. These changes in the glutamate pathway may partly explain the mechanism by which cigarette smoking causes cardiovascular disease. HTP use was also associated with glutamate metabolism, indicating that HTP use may contribute to the development of cardiovascular disease through mechanisms similar to those in cigarette use.

Studies examining long-term longitudinal metabolomic data and their reliability in large-scale populations are limited. Therefore, we aimed to evaluate the reliability of repeated measurements of plasma metabolites in a prospective cohort setting and to explore intra-individual concentration changes at three time points over a 6-year period. The study participants included 2999 individuals (1317 men and 1682 women) from the Tsuruoka Metabolomics Cohort Study, who participated in all three surveys—at baseline, 3 years, and 6 years. In each survey, 94 plasma metabolites were quantified for each individual and quality control (QC) sample. The coefficients of variation of QC, intraclass correlation coefficients, and change rates of QC were calculated for each metabolite, and their reliability was classified into three categories: excellent, fair to good, and poor. Seventy-six percent (71/94) of metabolites were classified as fair to good or better. Of the 39 metabolites grouped as excellent, 29 (74%) in men and 26 (67%) in women showed significant intra-individual changes over 6 years. Overall, our study demonstrated a high degree of reliability for repeated metabolome measurements. Many highly reliable metabolites showed significant changes over the 6-year period, suggesting that repeated longitudinal metabolome measurements are useful for epidemiological studies.

OBJECTIVE Body weight variability is linked to cardiometabolic outcomes, but its renal impact in type 2 diabetes remains uncertain. We tested whether the magnitude of seasonal BMI fluctuation is independently associated with kidney function decline. RESEARCH DESIGN AND METHODS We analyzed a nationwide, multicenter Japanese cohort (2014-2020). Monthly BMI was modeled using seasonal-trend locally estimated scatterplot smoothing to quantify each participant’s within-year peak-to-trough difference. The primary outcome was ≥40% decline in estimated glomerular filtration rate (eGFR). Secondary outcomes were ≥30% eGFR decline, creatinine doubling, incident chronic kidney disease (CKD) stage ≥3, and kidney failure. Associations were estimated using multivariable Cox models with clinic as a random effect. RESULTS Among 6,700 outpatients (median follow-up: 6.8 years), 779 reached the primary end point. Each 1-SD increase in BMI fluctuation was associated with higher risk of ≥40% eGFR decline (hazard ratio [HR] 1.23, 95% CI 1.16-1.31). The highest versus lowest tertile showed a 1.7-fold increased risk (HR 1.72, 95% CI 1.42-2.09). Patterns were consistent for ≥30% eGFR decline (HR 1.18, 95% CI 1.13-1.23), creatinine doubling (HR 1.30, 95% CI 1.17-1.45), and incident CKD stage ≥3 (HR 1.11, 95% CI 1.07-1.16). Longitudinal analyses showed steeper eGFR decline in the highest-fluctuation group. Results were robust across sensitivity analyses, including models for time-varying medication exposure. CONCLUSIONS In type 2 diabetes, larger intra-annual BMI fluctuations were independently and dose-dependently associated with kidney function decline. Seasonal BMI amplitude may identify higher-risk individuals; whether reducing seasonal BMI fluctuations improves kidney outcomes warrants prospective evaluation.

BACKGROUND The role of the apoptosis inhibitor of macrophages (AIM) in human lipid metabolism remains unclear. OBJECTIVE This study aimed to investigate the cross-sectional associations between serum AIM and plasma metabolites and to determine if baseline AIM concentrations predict incident dyslipidemia. METHODS This study used a community-based cohort of 3139 participants for cross-sectional metabolomic analysis. Among them, 1292 participants without dyslipidemia at baseline were followed prospectively for up to 8.5 years. Cox proportional hazards models were used to estimate hazard ratios for incident high low-density lipoprotein cholesterol (LDL-C) and metabolic dyslipidemia (high triglycerides and/or low high-density lipoprotein cholesterol [HDL-C]) across AIM tertiles. RESULTS Cross-sectionally, higher AIM concentrations were associated with elevated acylcarnitines and tricarboxylic acid cycle intermediates. Longitudinally, higher baseline AIM was associated with an increased risk of developing metabolic dyslipidemia in women (highest vs lowest tertile hazard ratio, 1.84) and showed a similar but smaller nonsignificant trend in men. The risk for high LDL-C was significantly increased in women but not in men. These associations remained robust after multivariable adjustment. CONCLUSION Elevated baseline AIM concentrations were prospectively associated with the development of metabolic dyslipidemia in women, with a similar but nonsignificant trend in men, and with high LDL-C in women. The related metabolomic profile suggests enhanced lipolysis and altered lipid metabolism. Therefore, AIM may serve as a biomarker for future dyslipidemia, particularly for triglyceride and HDL-C dysregulation.

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.

Background & Aims: Aminotransferases are widely used for metabolic dysfunction-associated steatotic liver disease (MASLD) evaluation, especially in type 2 diabetes mellitus (T2DM). Whether within-person seasonal variation affects classification near commonly used thresholds or relates to long-term metabolic outcomes remains unclear. Methods: This registry-based cohort analysed monthly aspartate aminotransferase (AST) and alanine aminotransferase (ALT) measurements from 6039 adults with T2DM in the Japan Diabetes Clinical Data Management registry (2014–2020). Classification discordance across the 30 IU/L threshold was compared between winter-mean and summer-mean values. Individual seasonal amplitude was derived from seasonal-trend decomposition of multiply imputed monthly time series. Final glycated haemoglobin (HbA1c) and non-achievement of HbA1c < 7% were analysed using multivariable regression. Results: Both AST and ALT showed significant seasonal variation, with the highest values in late autumn to early winter and the lowest in summer (p < 0.001). Approximately one in nine patients with borderline ALT values showed discordant winter-summer classification. Each 1-SD increase in AST amplitude was associated with 0.06 percentage points higher final HbA1c (95% CI, 0.04–0.08) and higher odds of not achieving HbA1c < 7% (odds ratio, 1.14; 95% CI, 1.08–1.21; p < 0.001). ALT amplitude showed a similar but weaker, less consistent association. Conclusions: AST and ALT exhibited reproducible seasonal variation peaking in late autumn to early winter, with approximately one in nine patients near the MASLD screening threshold reclassified depending on season. Greater seasonal amplitude, especially AST, was independently associated with poorer glycemic control, supporting season-aware interpretation in routine clinical practice.