BACKGROUND: Natural disasters may have negative health effects on survivors. However, long-term observations on this are lacking. Therefore, this study investigated the association between the degree of housing damage caused by the Great East Japan Earthquake (GEJE) and all-cause mortality using the data from the cohort study conducted by the Tohoku Medical Megabank (TMM) Project in disaster-stricken areas. METHODS: The community-based cohort study of the TMM Project which conducted a baseline survey from May 2013 to March 2016 collected data using questionnaires and blood and urine tests. The present large-scale prospective cohort study was a follow-up survey in which the degree of house damage and all-cause mortality were analysed using Cox proportional hazards regression, adjusting for sex, age and other potentially confounding variables. The degree of house damage was categorised into 'did not live in the disaster area', 'no damage', 'small-scale damage' and 'large-scale damage'. Among the 58 320 participants, 1763 deaths were confirmed during the follow-up which averaged 6.5 years. RESULTS: The multivariate analysis showed a hazard ratio (95% CI) of 0.96 (0.82 to 1.13) for those who did not live in the disaster area, 0.98 (0.87 to 1.10) for small-scale damage and 0.98 (0.85 to 1.14) for large-scale damage, compared with no damage, but no significant association with all-cause mortality was observed. CONCLUSION: The results of this large-scale prospective cohort study of GEJE survivors showed no significant relationship between the degree of house damage and all-cause mortality. Further long-term follow-up studies are needed to examine the long-term health effects of natural disasters on survivors.

BACKGROUND: The primary prevention of atrial fibrillation (AF), which increases mortality through complications including stroke and heart failure, is important. Excessive salt intake and low potassium intake are risk factors for cardiovascular disease; however, their association with AF remains inconclusive. This study investigated the association between sodium- and potassium-related urinary markers and AF prevalence. METHODS AND RESULTS: Data from the Tohoku Medical Megabank Project Community-based Cohort Study were used in this cross-sectional study. The urinary sodium-to-potassium (Na/K) ratio and estimated 24-h sodium and potassium excretion were calculated using spot urine samples and categorized into quartiles (Q1-Q4). The prevalence of AF was the primary outcome. Of the 26,506 participants (mean age 64.8 years; 33.2% males) included in this study, 630 (2.4%) had AF. Using Q1 as the reference group, the odds ratios for AF prevalence in Q4 were 1.35 (95% confidence interval [CI] 1.07-1.73) and 1.59 (95% CI 1.20-2.12) for 24-h estimated urinary Na/K ratio and estimated 24-h sodium excretion, respectively. Estimated 24-h potassium excretion was not associated with AF prevalence. CONCLUSIONS: AF prevalence was positively associated with the urinary Na/K ratio and estimated 24-h urinary sodium excretion, but not with estimated 24-h urinary potassium excretion. Although further prospective studies are warranted, the findings of this study suggest that salt intake may be a modifiable risk factor for AF.

OBJECTIVES: Previous studies have assessed the impact of active smoking on mortality using the population-attributable fraction (PAF). However, these studies have not included second-hand smoking (SHS), potentially underestimating smoking's impact. We compared the PAF from active smoking alone with the PAF, including SHS exposure. DESIGN: Prospective cohort study. SETTING: A community-based cohort study in Japan. PARTICIPANTS: 40 796 participants aged ≥20 years. MAIN OUTCOME MEASURES: SHS was defined as inhaling someone else's cigarette smoke at the workplace or home in the past year. We classified smoking status and SHS into ten categories: never-smoker without SHS, never-smoker with SHS, past smoker without SHS, past smoker with SHS, current smoker 1-9 cigarettes/day without SHS, current smoker 1-9 cigarettes/day with SHS, 10-19 cigarettes/day without SHS, 10-19 cigarettes/day with SHS, ≥20 cigarettes/day without SHS and ≥20 cigarettes/day with SHS. The main outcome was all-cause mortality. RESULTS: During the median follow-up period of 6.5 (5.7-7.5) years, 788 men and 328 women died. For men, compared with never-smokers without SHS, past smokers without SHS (HR, 1.39 [95% CI, 1.11 to 1.73]) and past smokers with SHS (HR, 1.48 (95% CI, 1.10 to 2.00)) were associated with all-cause mortality. For women, never-smokers with SHS had a significantly higher risk of all-cause mortality (HR, 1.36 (95% CI, 1.00 to 1.84)). Without considering SHS, 28.0% and 2.3% of all-cause mortality in men and women, respectively, were attributable to past and current smoking. Including SHS, PAF increased to 31.3% in men and 8.4% in women. CONCLUSIONS: We clarified that smoking's impact was underestimated by not accounting for SHS, especially in women. Information on SHS is crucial for understanding smoking's health impact. This study supports the importance of avoiding smoking and preventing SHS.

BACKGROUND: Studies investigating whether respiratory syncytial virus (RSV) infection, non-RSV respiratory infections, respiratory-related disorders, and non-respiratory-related disorders are associated with subsequent wheezing are limited in Japan. We aimed to elucidate the relationship between hospitalization for RSV infection, non-RSV respiratory infections, respiratory-related disorders, as well as non-respiratory-related disorders and subsequence wheezing in Japanese children. METHODS: This study included 7340 children and was conducted under the TMM BirThree Cohort Study (Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study). Data was collected from birth records and questionnaires. We categorized hospitalization history into five categories: "no hospitalization," hospitalizations for "RSV infection," "non-RSV respiratory infections," "respiratory-related disorders," and "non-respiratory-related disorders." The association of the five categories with later wheezing at 3 years of age was evaluated using multivariable logistic regression analysis. RESULTS: After adjusting for covariates, an association was shown between hospitalization under 2 years of age and later wheezing (odds ratio [OR] = 2.78; 95% confidence interval [CI] = 1.97-3.88 for "RSV infection"; OR = 2.61; 95% CI = 1.44-4.57 for "non-RSV respiratory infections"; and OR = 3.33; 95% CI = 2.43-4.54 for "respiratory-related disorders"). CONCLUSION: Hospitalization of children under 2 years of age for RSV infection as well as non-RSV respiratory infections and respiratory-related disorders were associated with subsequent wheezing.

BACKGROUND: Various disease prediction models have been developed, capitalizing on the wide use of electronic health records, but environmental factors that are important in the development of noncommunicable diseases are rarely included in the prediction models. Hypertensive disorders of pregnancy are leading causes of maternal morbidity and mortality and are known to cause several serious complications later in life. OBJECTIVE: This study aims to develop early hypertensive disorders of pregnancy prediction models using comprehensive environmental factors based on self-report questionnaires in early pregnancy. STUDY DESIGN: We developed machine learning and artificial intelligence models for the early prediction of hypertensive disorders of pregnancy using early pregnancy data from approximately 23,000 pregnancies in the Tohoku Medical Megabank Birth and Three Generation Cohort Study. We clarified the important features for prediction based on regression coefficients or Gini coefficients of the interpretable artificial intelligence models (i.e., logistic regression, random forest and XGBoost models) among our developed models. RESULTS: The performance of the early hypertensive disorders of pregnancy prediction models reached an area under the receiver operating characteristic curve of 0.93, demonstrating that the early hypertensive disorders of pregnancy prediction models developed in this study retain sufficient performance in hypertensive disorders of pregnancy prediction. Among the early prediction models, the best performing model was based on self-reported questionnaire data in early pregnancy (mean of 20.2 gestational weeks at filling) which consist of comprehensive lifestyles. The interpretation of the models reveals that both eating habits were dominantly important for prediction. CONCLUSION: We have developed high-performance models for early hypertensive disorders of pregnancy prediction using large-scale cohort data from the Tohoku Medical Megabank project. Our study clearly revealed that the use of comprehensive lifestyles from self-report questionnaires led us to predict hypertensive disorders of pregnancy risk at the early stages of pregnancy, which will aid early intervention to reduce the risk of hypertensive disorders of pregnancy.

BACKGROUND: Chronic kidney disease (CKD) contributes to decreased life expectancy. We examined the association between leisure-time physical activity (LTPA), non-leisure-time physical activity (non-LTPA) and kidney function. METHODS: This was a cross-sectional study including 32 162 community-dwelling adults aged ≥ 20 years from the Tohoku Medical MegaBank community-based cohort study. Kidney function was evaluated using cystatin C-based estimated glomerular filtration rate (eGFR) as well as self-reported LTPA and non-LTPA. CKD was defined as either eGFR decline (≤ 60 mL/min/1.73 m2) or presence of albuminuria (albumin-creatinine ≥ 30 mg/g). The association between domain-specific physical activity and kidney function, and CKD prevalence was examined using multivariable-adjusted ordinary least squares and modified Poisson models. RESULTS: The mean eGFR was 98.1 (± 13.2) mL/min/1.73 m2. 3 185 (9.9%) participants were classified as having CKD. The mean LTPA and non-LTPA levels were 2.9 (± 4.2) and 16.6 (± 14.2) METs-hour/day, respectively. For LTPA, in the adjusted model, the quartile groups with higher levels had a higher kidney function (β, 0.36; 95% confidence intervals [CI], [0.06, 0.66]; p = 0.019 for the 2nd quartile, β, 0.82; 95% CI, [0.51, 1.14]; p < 0.001 for the 3rd quartile, and β, 1.16; 95% CI, [0.83, 1.49]; p < 0.001 for the 4th quartile), whereas there were no apparent associations for prevalence of CKD. For non-LTPA, 4th quartile was associated with decreased eGFR (β, -0.42; 95% CI, [-0.72, -0.11]; p = 0.007) and higher prevalence of CKD prevalence (Prevalence ratio, 1.12; 95% CI, [1.02, 1.24]; p = 0.022). These associations with kidney function remained consistent in the subgroup analyses divided by demographic and biological variables. CONCLUSIONS: We observed a positive association between higher LTPA levels and better kidney function, but not association with CKD prevalence. In contrast, higher non-LTPA was negatively associated with both kidney function and CKD prevalence. These findings suggest that promoting LTPA is beneficial for kidney function.

OBJECTIVE: To investigate the inter-relationships among genetic risk, healthy lifestyle adherence, and hyperuricaemia susceptibility. METHODS: This prospective cohort study was conducted with 7,241 hyperuricaemia-free individuals aged ≥ 20 years from the Tohoku Medical Megabank Community-based cohort study. A comprehensive lifestyle score included body mass index, smoking, drinking, and physical activity, and a polygenic risk score (PRS) was constructed based on uric acid loci from a previous genome-wide association study meta-analysis. A multiple logistic regression model was used to estimate the association between genetic risk, healthy lifestyle, and hyperuricaemia incidence and calculate the area under the receiver operating characteristic curve (AUROC). Hyperuricaemia was defined as a uric acid level ≥7.0 mg/dl or a self-reported history of hyperuricaemia. RESULTS: Of the 7,241 adults (80.7% females; mean [SD] age: 57.7 [12.6] years), 217 (3.0%) developed hyperuricaemia during 3.5 years of follow-up. Genetic risk correlated with hyperuricaemia development (P for interaction = 0.287), and lifestyle risks were independently associated. Those with a high genetic risk and poor lifestyle had the highest risk (odds ratio: 5.34; 95% confidence interval [CI]: 2.61-12.10). Although not statistically significant, incorporating the PRS in the model with lifestyle information improved predictive ability (AUROC = 0.771, 95% CI: 0.736-0.806 for lifestyle; AUROC = 0.785, 95% CI: 0.751-0.819 for lifestyle and PRS; p = 0.07). CONCLUSION: : A healthy lifestyle to prevent hyperuricaemia, irrespective of genetic risk, may mitigate the genetic risk. Genetic risk may complement lifestyle factors in identifying individuals at a heightened hyperuricaemia risk.

This study aimed to investigate the association of combination of birth weight and current body mass index (BMI) with the risk of hypertension in adulthood. This cross-sectional study used data from the Tohoku Medical Megabank Community-based Cohort Study conducted in Japan. A total of 10,688 subjects aged ≥20 years were eligible. We calculated the least square (LS) means of systolic blood pressure (SBP) and trend tests were performed to evaluate the linear relationships between birth weight categories and SBP. We also used a multivariate logistic regression analysis to assess the risk of hypertension associated with the combination of birth weight and current BMI. There was a statistically inverse association between birth weight and SBP in the 20-64 age group, but no significant association in the ≥65 age group. Low birth weight (LBW) with normal BMI group had a higher risk of hypertension than the normal or high birth weight groups with normal BMI. Furthermore, the group with LBW and BMI ≥25.0 kg/m2 was the highest risk for hypertension (adjusted odds ratio: 2.73; 95% CI, 2.04-3.65) compared to the reference group (birth weight 2500-3499 g and BMI 18.5-24.9 kg/m2). There was a significant association between LBW and subsequent risk of hypertension. In addition, participants with lower birth weights had a higher risk of hypertension than those with higher birth weights. However, even in participants with a lower birth weight, the risk of hypertension could be reduced when they maintained an optimal BMI.

No study, to our knowledge, has constructed a polygenic risk score based on clinical blood pressure and investigated the association of genetic and lifestyle risks with home hypertension. We examined the associations of combined genetic and lifestyle risks with hypertension and home hypertension. In a cross-sectional study of 7027 Japanese individuals aged ≥20 years, we developed a lifestyle score based on body mass index, alcohol consumption, physical activity, and sodium-to-potassium ratio, categorized into ideal, intermediate, and poor lifestyles. A polygenic risk score was constructed with the target data (n = 1405) using publicly available genome-wide association study summary statistics from BioBank Japan. Using the test data (n = 5622), we evaluated polygenic risk score performance and examined the associations of combined genetic and lifestyle risks with hypertension and home hypertension. Hypertension and home hypertension were defined as blood pressure measured at a community-support center ≥140/90 mmHg or at home ≥135/85 mmHg, respectively, or self-reported treatment for hypertension. In the test data, 2294 and 2322 participants had hypertension and home hypertension, respectively. Both polygenic risk and lifestyle scores were independently associated with hypertension and home hypertension. Compared with those of participants with low genetic risk and an ideal lifestyle, the odds ratios for hypertension and home hypertension in the low genetic risk and poor lifestyle group were 1.94 (95% confidence interval, 1.34-2.80) and 2.15 (1.60-2.90), respectively. In summary, lifestyle is important to prevent hypertension; nevertheless, participants with high genetic risk should carefully monitor their blood pressure despite a healthy lifestyle.

INTRODUCTION: The Tohoku Medical Megabank (TMM) was established for creative reconstruction from the Great East Japan Earthquake and tsunami in 2011. Two prospective genome cohort studies in Miyagi prefecture have successfully recruited approximately 127,000 participants. The health status of these individuals was evaluated at the initial recruitment, and follow-up health checkups have been conducted every 5 years. During these health checkups, unexpected critical values were encountered, which prompted us to develop an urgent notification system. METHODS: We analyzed the frequency of critical values observed in home blood pressure (HBP) test in an urgent notification office (UNO). We returned the critical values by urgent notification before the notifications of regular results. In addition, the impact of the TMM urgent notification on the participants was evaluated. RESULTS: We issued urgent notifications of the critical values of extremely high HBP. Of the 21,061 participants who underwent HBP measurements, 256 (1.2%) met the criteria for urgent notification. It was found that abnormalities in blood sugar levels, renal function, and lipid values were frequently concurrent with the abnormal HBP readings. Annual questionnaires administered after the urgent notification, approximately 60% of those went to hospitals or clinics. CONCLUSIONS: The urgent notification system for hypertensive emergency with HBP in the TMM was well accepted by the participants and encouraged them to seek medical care. The system has been useful in addressing the prolonged healthcare problems and in promoting health care in large-scale disaster damaged areas.

Depression is comorbid with somatic diseases; however, the relationship between depressive symptoms and hypertension (HT), a risk factor for cardiovascular events, remains unclear. Home blood pressure (BP) is more reproducible and accurately predictive of cardiovascular diseases than office BP. Therefore, we focused on home BP and investigated whether depressive symptoms contributed to the future onset of home HT. This prospective cohort study used data from the Tohoku Medical Megabank Community-Cohort Study (conducted in the Miyagi Prefecture, Japan) and included participants with home normotension (systolic blood pressure (SBP) < 135 mmHg and diastolic blood pressure (DBP) < 85 mmHg). Depressive symptoms were evaluated using the Center for Epidemiologic Studies Depression Scale-Japanese version at the baseline survey. In the secondary survey, approximately 4 years later, the onset of home HT was evaluated (SBP ≥ 135 mmHg or DBP ≥ 85 mmHg) and was compared in participants with and without depressive symptoms. Of the 3 082 (mean age: 54.2 years; females: 80.9%) participants, 729 (23.7%) had depressive symptoms at the baseline survey. During the 3.5-year follow-up, 124 (17.0%) and 388 (16.5%) participants with and without depressive symptoms, respectively, developed home HT. Multivariable adjusted odds ratios were 1.37 (95% confidence interval (CI): 1.02-1.84), 1.18 (95% CI: 0.86-1.61), and 1.66 (95% CI: 1.17-2.36) for home, morning, and evening HT, respectively. This relationship was consistent in the subgroup analyses according to age, sex, BP pattern, and drinking habit. Depressive symptoms increased the risk of new-onset home HT, particularly evening HT, among individuals with home normotension. This prospective cohort study revealed that depressive symptoms are risk factors for new-onset home hypertension, particularly evening hypertension among individuals with home normotension. Assessing home blood pressure in individuals with depressive symptoms is important for the prevention of hypertension and concomitant cardiovascular diseases.

AIM: This study examined the relationship between genetic risk, healthy lifestyle, and risk of developing diabetes. METHODS: This prospective cohort study included 11,014 diabetes-free individuals ≥ 20 years old from the Tohoku Medical Megabank Community-based cohort study. Lifestyle scores, including the body mass index, smoking, physical activity, and gamma-glutamyl transferase (marker of alcohol consumption), were assigned, and participants were categorized into ideal, intermediate, and poor lifestyles. A polygenic risk score (PRS) was constructed based on the type 2 diabetes loci from the BioBank Japan study. A multiple logistic regression model was used to estimate the association between genetic risk, healthy lifestyle, and diabetes incidence and to calculate the area under the receiver operating characteristic curve (AUROC). RESULT: Of the 11,014 adults included (67.8% women; mean age [standard deviation], 59.1 [11.3] years old), 297 (2.7%) developed diabetes during a mean 4.3 (0.8) years of follow-up. Genetic and lifestyle score is independently associated with the development of diabetes. Compared with the low genetic risk and ideal lifestyle groups, the odds ratio was 3.31 for the low genetic risk and poor lifestyle group. When the PRS was integrated into a model including the lifestyle and family history, the AUROC significantly improved to 0.719 (95% confidence interval [95% CI]: 0.692-0.747) compared to a model including only the lifestyle and family history (0.703 [95% CI, 0.674-0.732]). CONCLUSION: Our findings indicate that adherence to a healthy lifestyle is important for preventing diabetes, regardless of genetic risk. In addition, genetic risk might provide information beyond lifestyle and family history to stratify individuals at high risk of developing diabetes.

AIM: To evaluate the association between housing and psychological damage caused by the Great East Japan Earthquake (GEJE) and modifiable risk factors (MRFs) of dementia for general population of older adults. METHODS: This cross-sectional study enrolled 29 039 community-dwelling older adults (mean age 69.1 ± 2.9 years, 55.5% women). We evaluated disaster-related damage (by complete or not complete housing damage) and psychological damage (by post-traumatic stress reaction [PTSR]) after the GEJE using a self-report questionnaire. MRFs encompassed the presence of depression, social isolation, physical inactivity, smoking, and diabetes. We examined the association between disaster-related damage and MRFs using ordinary least squares and modified Poisson regression models adjusted for sociodemographic and health status variables. RESULTS: Complete housing damage and PTSR were identified in 2704 (10.0%) and 855 (3.2%) individuals, respectively. The number of MRFs was significantly larger for the individuals with complete housing damage (β = 0.23; 95% confidence interval [CI]: 0.19-0.27) and PTSR (β = 0.60; 95% CI: 0.53-0.67). Prevalence ratios (PRs) for depression and physical inactivity were higher in individuals with complete housing damage. The PRs for all domains of the MRFs were significantly higher in individuals with PTSR. CONCLUSIONS: Housing and psychological damage caused by the GEJE were associated with an increased risk factor of dementia. To attenuate the risk of dementia, especially among older victims who have experienced housing and psychological damage after a disaster, multidimensional support across various aspects of MRFs is required. Geriatr Gerontol Int 2024; ••: ••-••.

BACKGROUND/AIMS: The objective of this research is to examine factors related to irritable bowel syndrome (IBS) prevalence in a large population-based study. METHODS: A cross-sectional study was conducted with participants in the Miyagi part of the Tohoku Medical Megabank Project Community-Based cohort study who completed the Rome II Modular Questionnaire. Multivariate odds ratios (ORs) for the presence of IBS and 95% confidence intervals (95% CIs) for the reference group were calculated for each factor. Additionally, a stratified analysis was performed by sex and age group (20-49 years, 50-64 years, and ≥ 65 years). RESULTS: Among 16 252 participants, 3025 (18.6%) had IBS, comprising 750 men (15.5%) and 2275 women (19.9%). Multivariate ORs for the presence of IBS decreased significantly with each year of age (OR, 0.98; 95% CI, 0.98-0.99). Moreover, compared with the reference group, ORs for the presence of IBS were significantly higher in individuals whose home was partially damaged by the Great East Japan Earthquake, those with < 16 years of education, those who spent less time walking, those with high perceived stress (1.77, 1.57-2.01), those with high psychological distress (1.58, 1.36-1.82), and those with high symptoms of depression (1.76, 1.60-1.94). In stratified analyses, a significant relationship was found between psychological factors and IBS prevalence in all sex and age groups. CONCLUSIONS: This large cross-sectional population-based cohort study identified several factors associated with IBS prevalence. Psychological factors were significantly associated with IBS prevalence across all age groups and sexes.

Recently, many phenotyping algorithms for high-throughput cohort identification have been developed. Prospective genome cohort studies are critical resources for precision medicine, but there are many hurdles in the precise cohort identification. Consequently, it is important to develop phenotyping algorithms for cohort data collection. Hypertensive disorders of pregnancy (HDP) is a leading cause of maternal morbidity and mortality. In this study, we developed, applied, and validated rule-based phenotyping algorithms of HDP. Two phenotyping algorithms, algorithms 1 and 2, were developed according to American and Japanese guidelines, and applied into 22,452 pregnant women in the Birth and Three-Generation Cohort Study of the Tohoku Medical Megabank project. To precise cohort identification, we analyzed both structured data (e.g., laboratory and physiological tests) and unstructured clinical notes. The identified subtypes of HDP were validated against reference standards. Algorithms 1 and 2 identified 7.93% and 8.08% of the subjects as having HDP, respectively, along with their HDP subtypes. Our algorithms were high performing with high positive predictive values (0.96 and 0.90 for algorithms 1 and 2, respectively). Overcoming the hurdle of precise cohort identification from large-scale cohort data collection, we achieved both developed and implemented phenotyping algorithms, and precisely identified HDP patients and their subtypes from large-scale cohort data collection.

BACKGROUND: The relationship between blood cell profiles, including hemoglobin (Hb) levels and inflammatory hematological ratios, and mental health problems currently remains unclear. AIM: This study aimed to investigate the relationship between blood cell profiles and mental health issues, including depressive state and sleep disturbance, while adjusting for potential demographic confounders. METHODOLOGY: This retrospective, cross-sectional, observational study used a population-based medical database from the Tohoku Medical Megabank Project with more than 60,000 volunteers. Data on age, sex, daily tobacco use, body mass index, and self-reported scores on the Kessler Psychological Distress Scale (K6), Athens Insomnia Scale (AIS), and the Center for Epidemiologic Studies Depression Scale (CES-D) were collected. RESULTS: A total of 62,796 volunteers (23,663 males and 39,133 females), aged ≥20 years at the time of the blood test, agreed to participate in this study. Among the evaluated blood cell profiles, Hb, hematocrit, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were significantly correlated with the K6, AIS, and CES-D scores, with strong statistical significance (p<0.0001 for all) in bivariate correlation analyses. A significant adjusted odds ratio (aOR) of the Hb level for elevated CES-D scores (aOR=0.965 [95% CI: 0.949-0.981], p<0.0001) was confirmed after adjusting for demographic data and daily tobacco use using a logistic regression model. Sensitivity analyses revealed that these associations existed in both males and females but were more prominent in the former. In male participants, a low Hb level was significantly associated with an elevated AIS score. The evaluated inflammatory hematological ratios, including NLR, PLR, and monocyte-to-lymphocyte ratio (MLR), also showed significant aORs with the K6, AIS, and CES-D scores after adjusting for demographic background. CONCLUSION: Low Hb levels and elevated inflammatory hematological ratios (NLR, MLR, and PLR) were associated with depressive state and sleep disturbances in the general population.

Risk factors for hypertension have been emphasized in the Japanese Society of Hypertension Guidelines for the Management of Hypertension. However, large-scale studies on the association of smoking, potassium excretion, and gamma-glutamyl transferase level with BP in the Japanese population are limited. We conducted a cross-sectional study to examine the association between hypertension risk factors and systolic blood pressure in the Tohoku Medical Megabank Community-based Cohort Study (23,446 men and 38,921 women aged ≥20 years). A model adjusted for age, body mass index, smoking status, drinking status, estimated daily salt intake, potassium excretion, (or urinary sodium-to-potassium ratio), gamma-glutamyl transferase, physical activity, education level, status of damage to homes during the Great East Japan Earthquake, and residential areas was used. The average age and systolic blood pressure were 62.5 (10.3) years for men and 59.6 (11.3) years for women, 128.9 (16.7) mmHg for men and 124.7 (17.5) mmHg for women, respectively. Body mass index estimated daily salt intake, urinary sodium-to-potassium ratio and gamma-glutamyl transferase levels were positively associated with systolic blood pressure. Compared with never-drinkers, current drinkers who consumed 23-45 g/day and ≥46.0 g/day had significantly increased systolic blood pressure. Conversely, current smokers (1-10 cigarettes/day and 11-20 cigarettes/day) were inversely associated with systolic blood pressure compared to never-smokers. Overall, systolic blood pressure was associated with gamma-glutamyl transferase and hypertension risk factors, including body mass index, alcohol consumption, estimated daily salt intake, urinary sodium-to-potassium ratio, and potassium excretion. Our findings support the notion that lifestyle modifications should be attempted to prevent hypertension.

BACKGROUND: The purpose of this study was to report the basic profile of the Miyagi Prefecture part of a repeated center-based survey during the second period (2nd period survey) of the Tohoku Medical Megabank Community-Based Cohort Study (TMM CommCohort Study), as well as the participants' characteristics based on their participation type in the baseline survey. METHODS: The 2nd period survey, conducted from June 2017 to March 2021, included participants of the TMM CommCohort Study (May 2013 to March 2016). In addition to the questionnaire, blood, urine, and physiological function tests were performed during the 2nd period survey. There were three main ways of participation in the baseline survey: Type 1, Type 1 additional, or Type 2 survey. The 2nd period survey was conducted in the same manner as the Type 2 survey, which was based on the community support center (CSC). RESULTS: In Miyagi Prefecture, 29,383 (57.7%) of 50,967 participants participated in the 2nd period survey. The participation rate among individuals who had visited the CSC was approximately 80%. Although some factors differed depending on the participation type in the baseline survey, the 2nd period survey respondents in the Type 1 and Type 2 survey groups at baseline had similar traits. CONCLUSIONS: The 2nd period survey of the TMM CommCohort Study provided detailed follow-up information. Following up on the health conditions of the participants will clarify the long-term effects of disasters and contribute to personalized prevention.

AIMS: Although fat mass (FM) and fat-free mass (FFM) have an impact on lipid metabolism, the relationship between different body composition phenotypes and lipid profiles is still unclear. By dividing the FM and FFM by the square of the height, respectively, the f at mass index (FMI) and fat-free mass index (FFMI) can be used to determine the variations in body composition. This study aimed to investigate the relationship of combined FMI and FFMI with low-density lipoprotein cholesterol (LDL-C) levels. METHODS: This cross-sectional study comprised 5,116 men and 13,630 women without cardiovascular disease and without treatment for hypertension, and diabetes. Following sex-specific quartile classification, FMI and FFMI were combined into 16 groups. Elevated LDL-C levels were defined as LDL-C ≥ 140 mg/dL and/or dyslipidemia treatment. Multivariable logistic regression models were used to examine the relationships between combined FMI and FFMI and elevated LDL-C levels. RESULTS: Overall, elevated LDL-C levels were found in 1,538 (30.1%) men and 5,434 (39.9%) women. In all FFMI subgroups, a higher FMI was associated with elevated LDL-C levels. Conversely, FFMI was inversely associated with elevated LDL-C levels in most FMI subgroups. Furthermore, the groups with the highest FMI and lowest FFMI had higher odds ratios for elevated LDL-C levels than those with the lowest FMI and highest FFMI. CONCLUSIONS: Regardless of FFMI, FMI was positively associated with elevated LDL-C levels. Conversely, in the majority of FMI subgroups, FFMI was inversely associated with elevated LDL-C levels.

Masked hypertension is a risk factor for cardiovascular diseases. However, masked hypertension is sometimes overlooked owing to the requirement for home blood pressure measurements for diagnosing. Mental status influences blood pressure. To reduce undiagnosed masked hypertension, this study assessed the association between depressive symptoms and masked hypertension. This cross-sectional study used data from the Tohoku Medical Megabank Project Community-Based Cohort Study (conducted in Miyagi Prefecture, Japan, from 2013) and included participants with normotension measured at the research center (systolic blood pressure<140 mmHg and diastolic blood pressure <90 mmHg). Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (Japanese version). Masked hypertension was defined as normotension measured at the research center and home hypertension (home systolic blood pressure ≥135 mmHg or home diastolic blood pressure ≥85 mmHg). The study comprised 6705 participants (mean age: 55.7 ± 13.7 years). Of these participants, 1106 (22.1%) without depressive symptoms and 393 (23.2%) with depressive symptoms were categorized to have masked hypertension. Sex-specific and age-adjusted least mean squares for home blood pressure, not for research blood pressure were significantly higher in the group with depressive symptoms in both sex categories. The multivariate odds ratio for masked hypertension in the patients with depressive symptoms was 1.72 (95% confidence interval: 1.26-2.34) in male participants and 1.30 (95% confidence interval: 1.06-1.59) in female ones. Depressive symptoms were associated with masked hypertension in individuals with normotension measured at the research center. Depressive symptoms may be one of the risk factors for masked hypertension. Depressive symptoms were associated with masked hypertension in individuals with normotension measured at research center.

AIM: The influence of family history of diabetes, probably reflecting genetic and lifestyle factors, on the association of combined genetic and lifestyle risks with diabetes is unknown. We examined these associations. METHODS: This cross-sectional study included 9,681 participants in the Tohoku Medical Megabank Community-based Cohort Study. A lifestyle score, which was categorized into ideal, intermediate, and poor lifestyles, was given. Family history was obtained through a self-reported questionnaire. A polygenic risk score (PRS) was constructed in the target data (n=1,936) using publicly available genome-wide association study summary statistics from BioBank Japan. For test data (n=7,745), we evaluated PRS performance and examined the associations of combined family history and genetic and lifestyle risks with diabetes. Diabetes was defined as non-fasting blood glucose ≥ 200 mmHg, HbA1c ≥ 6.5%, and/or self-reported diabetes treatment. RESULTS: In test data, 467 (6.0%) participants had diabetes. Compared with a low genetic risk and an ideal lifestyle without a family history, the odds ratio (OR) was 3.73 (95% confidence interval [CI], 1.92-7.00) for a lower genetic risk and a poor lifestyle without a family history. Family history was significantly associated with diabetes (OR, 3.58 [95% CI, 1.73-6.98]), even in those with a low genetic risk and an ideal lifestyle. Even among participants who had an ideal lifestyle without a family history, a high genetic risk was associated with diabetes (OR, 2.49 [95% CI, 1.65-3.85]). Adding PRS to family history and conventional lifestyle risk factors improved the prediction ability for diabetes. CONCLUSIONS: Our findings support the notion that a healthy lifestyle is important to prevent diabetes regardless of genetic risk.

BACKGROUND: Low birth weight (LBW) is a leading cause of neonatal morbidity and mortality, and increases various disease risks across life stages. Prediction models of LBW have been developed before, but have limitations including small sample sizes, absence of genetic factors and no stratification of neonate into preterm and term birth groups. In this study, we challenged the development of early prediction models of LBW based on environmental and genetic factors in preterm and term birth groups, and clarified influential variables for LBW prediction. METHODS: We selected 22,711 neonates, their 21,581 mothers and 8,593 fathers from the Tohoku Medical Megabank Project Birth and Three-Generation cohort study. To establish early prediction models of LBW for preterm birth and term birth groups, we trained AI-based models using genetic and environmental factors of lifestyles. We then clarified influential environmental and genetic factors for predicting LBW in the term and preterm groups. RESULTS: We identified 2,327 (10.22%) LBW neonates consisting of 1,077 preterm births and 1,248 term births. Our early prediction models archived the area under curve 0.96 and 0.95 for term LBW and preterm LBW models, respectively. We revealed that environmental factors regarding eating habits and genetic features related to fetal growth were influential for predicting LBW in the term LBW model. On the other hand, we identified that genomic features related to toll-like receptor regulations and infection reactions are influential genetic factors for prediction in the preterm LBW model. CONCLUSIONS: We developed precise early prediction models of LBW based on lifestyle factors in the term birth group and genetic factors in the preterm birth group. Because of its accuracy and generalisability, our prediction model could contribute to risk assessment of LBW in the early stage of pregnancy and control LBW risk in the term birth group. Our prediction model could also contribute to precise prediction of LBW based on genetic factors in the preterm birth group. We then identified parental genetic and maternal environmental factors during pregnancy influencing LBW prediction, which are major targets for understanding the LBW to address serious burdens on newborns' health throughout life.

A system for inputting and storing family information, named “BirThree Enrollment,” was developed to promote a birth and three-generation cohort study (BirThree Cohort Study). In this cohort study, it was necessary to satisfy many operational demands while constantly overwriting and changing input information. Complex kinship information must be quickly and accurately inputed and corrected, and information on those families not yet recruited must be retrieved. For these purposes, many devices are needed, from an input interface to the internal data structure. In the field of genetic statistics, a simple standard expressive form (describe father-child relation and mother-child relation) is used for describing family structure. However, this form doesn't have sufficient information. So we developed a new form in conducting the BirThree Cohort Study. Hence, we expanded the data structure, and constructed the Input control system. Family pedigree information is stored along with initial clinical information, and this enabled the input of all self-reported information to the data base. Operators are able to input this family information before the day is out. As a result, when recruitment is completed, family information will be completed concurrently. Therefore, operators can immediately know certain person's family structure. In this model data correction was improved dramatically, and the system was operated successfully. This study is the first report of the method for storing three generations of family data.

BACKGROUND: Although live-attenuated vaccines are contraindicated under immunosuppression, the immune status of patients with inflammatory bowel disease (IBD) has not been fully assessed prior to immunosuppressive therapy. AIMS: To investigate antiviral serostatus against viruses requiring live vaccines for prevention in IBD patients undergoing immunosuppressive therapy. METHODS: This multicenter study included IBD patients who were aged <40 years and were treated with thiopurine monotherapy, molecular-targeted monotherapy, or combination therapy. Gender- and age-matched healthy subjects (HS) living in the same areas were included as control group. Antibody titers against measles, rubella, mumps, and varicella were measured by enzyme-linked immunosorbent assays. RESULTS: A total of 437 IBD patients (163 ulcerative colitis [UC] and 274 Crohn's disease [CD]) and 225 HS were included in the final analysis. Compared with HS, IBD patients had lower seropositivity rates for measles (IBD vs. HS = 83.91% vs. 85.33%), rubella (77.55% vs. 84.89%), mumps (37.50% vs. 37.78%), and varicella (91.26% vs. 96.44%). Gender- and age-adjusted seropositivity rates were lower in UC patients than in both CD patients and HS for measles (UC, CD, and HS = 81.60%, 85.29%, and 85.33%), rubella (76.40%, 78.23%, and 84.89%), mumps (27.16%, 43.70%, and 37.78%), and varicella (90.80%, 91.54%, and 96.44%); the difference was significant for all viruses except measles. Divided by the degree of immunosuppression, there were no significant differences in seropositivity rates among IBD patients. CONCLUSIONS: IBD patients, especially those with UC, exhibit reduced seropositivity rates and may benefit from screening prior to the initiation of immunosuppressive therapy.

To reveal gene-environment interactions underlying common diseases and estimate the risk for common diseases, the Tohoku Medical Megabank (TMM) project has conducted prospective cohort studies and genomic and multiomics analyses. To establish an integrated biobank, we developed an integrated database called "dbTMM" that incorporates both the individual cohort/clinical data and the genome/multiomics data of 157,191 participants in the Tohoku Medical Megabank project. To our knowledge, dbTMM is the first database to store individual whole-genome data on a variant-by-variant basis as well as cohort/clinical data for over one hundred thousand participants in a prospective cohort study. dbTMM enables us to stratify our cohort by both genome-wide genetic factors and environmental factors, and it provides a research and development platform that enables prospective analysis of large-scale data from genome cohorts.

Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset's allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers' discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide.

UNLABELLED: Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. ABBREVIATIONS: GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.