Identification of risk loci for postpartum depression in a genome-wide association study.

AIM: Genome-wide association studies (GWAS) of postpartum depression (PPD) based on accumulated cohorts with multiple ethnic backgrounds have failed to identify significantly associated loci. Herein, we conducted a GWAS of Japanese perinatal women along with detailed confounding information to uncover PPD-associated loci. METHODS: The first and second cohorts (n = 9260 and n = 8582 perinatal women enrolled in the Tohoku Medical Megabank Project) and the third cohort (n = 997), recruited at Nagoya University, underwent genotyping. Of them, 1421, 1264, and 225 were classified as PPD based on the Edinburgh Postnatal Depression Scale 1 month after delivery. The most influential confounding factors of genetic liability to PPD were selected, and logistic regression analyses were performed to evaluate genetic associations with PPD after adjusting for confounders. RESULTS: A meta-analysis of GWAS results from the three cohorts identified significant associations between PPD and the following loci (P < 5 × 10-8) by integrating the number of deliveries and the number of family members living together as the most influential confounders: rs377546683 at DAB1, rs11940752 near UGT8, rs141172317, rs117928019, rs76631412, rs118131805 at DOCK2, rs188907279 near ZNF572, rs504378, rs690150, rs491868, rs689917, rs474978, rs690118, rs690253 near DIRAS2, rs1435984417 at ZNF618, rs57705782 near PTPRM, and rs185293917 near PDGFB. Pathway analyses indicated that SNPs suggestively associated with PPD were mostly over-represented in categories including long-term depression, GnRH signaling, glutamatergic synapse, oxytocin signaling, and Rap1 signaling. CONCLUSION: The current GWAS study identified eight loci significantly associated with PPD, which may clarify the genetic structure underlying its pathogenesis.

Genetic Risk, Lifestyle Adherence, and Risk of Developing Hyperuricaemia in a Japanese Population.

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.

Genome-wide association study based on clustering by obesity-related variables uncovers a genetic architecture of obesity in the Japanese and the UK populations.

Whether all obesity-related variants contribute to the onset of obesity or one or a few variants cause obesity in genetically heterogeneous populations remains obscure. Here, we investigated the genetic architecture of obesity by clustering the Japanese and British populations with obesity using obesity-related factors. In Step-1, we conducted a genome-wide association study (GWAS) with body mass index (BMI) as the outcome for eligible participants. In Step-2, we assigned participants with obesity (BMI ≥25 kg/m2) to five clusters based on obesity-related factors. Subsequently, participants from each cluster and those with a BMI <25 kg/m2 were combined. A GWAS was conducted for each cluster. Several previously identified obesity-related genes were verified in Step-1. Of the genes detected in Step-1, unique obesity-related genes were detected separately for each cluster in Step-2. Our novel findings suggest that a smaller sample size with increased homogeneity may provide insights into the genetic architecture of obesity.

Machine learning-based reproducible prediction of type 2 diabetes subtypes.

AIMS/HYPOTHESIS: Clustering-based subclassification of type 2 diabetes, which reflects pathophysiology and genetic predisposition, is a promising approach for providing personalised and effective therapeutic strategies. Ahlqvist's classification is currently the most vigorously validated method because of its superior ability to predict diabetes complications but it does not have strong consistency over time and requires HOMA2 indices, which are not routinely available in clinical practice and standard cohort studies. We developed a machine learning (ML) model to classify individuals with type 2 diabetes into Ahlqvist's subtypes consistently over time. METHODS: Cohort 1 dataset comprised 619 Japanese individuals with type 2 diabetes who were divided into training and test sets for ML models in a 7:3 ratio. Cohort 2 dataset, comprising 597 individuals with type 2 diabetes, was used for external validation. Participants were pre-labelled (T2Dkmeans) by unsupervised k-means clustering based on Ahlqvist's variables (age at diagnosis, BMI, HbA1c, HOMA2-B and HOMA2-IR) to four subtypes: severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD). We adopted 15 variables for a multiclass classification random forest (RF) algorithm to predict type 2 diabetes subtypes (T2DRF15). The proximity matrix computed by RF was visualised using a uniform manifold approximation and projection. Finally, we used a putative subset with missing insulin-related variables to test the predictive performance of the validation cohort, consistency of subtypes over time and prediction ability of diabetes complications. RESULTS: T2DRF15 demonstrated a 94% accuracy for predicting T2Dkmeans type 2 diabetes subtypes (AUCs ≥0.99 and F1 score [an indicator calculated by harmonic mean from precision and recall] ≥0.9) and retained the predictive performance in the external validation cohort (86.3%). T2DRF15 showed an accuracy of 82.9% for detecting T2Dkmeans, also in a putative subset with missing insulin-related variables, when used with an imputation algorithm. In Kaplan-Meier analysis, the diabetes clusters of T2DRF15 demonstrated distinct accumulation risks of diabetic retinopathy in SIDD and that of chronic kidney disease in SIRD during a median observation period of 11.6 (4.5-18.3) years, similarly to the subtypes using T2Dkmeans. The predictive accuracy was improved after excluding individuals with low predictive probability, who were categorised as an 'undecidable' cluster. T2DRF15, after excluding undecidable individuals, showed higher consistency (100% for SIDD, 68.6% for SIRD, 94.4% for MOD and 97.9% for MARD) than T2Dkmeans. CONCLUSIONS/INTERPRETATION: The new ML model for predicting Ahlqvist's subtypes of type 2 diabetes has great potential for application in clinical practice and cohort studies because it can classify individuals with missing HOMA2 indices and predict glycaemic control, diabetic complications and treatment outcomes with long-term consistency by using readily available variables. Future studies are needed to assess whether our approach is applicable to research and/or clinical practice in multiethnic populations.

Association of olfactory and cognitive function test scores with hippocampal and amygdalar grey matter volume: a cross-sectional study.

Few population-based studies including younger adults have examined the potential of olfactory function tests to capture the degree of atrophy in memory-associated brain regions, which cannot be adequately explained by cognitive function tests screening for cognitive impairment. This population-based study investigated associations between high-resolution olfactory test data with few odours and grey matter volumes (GMVs) of the left and right hippocampi, amygdala, parahippocampi, and olfactory cortex, while accounting for differences in cognitive decline, in 1444 participants (aged 31-91 years). Regression analyses included intracranial volume (ICV)-normalised GMVs of eight memory-related regions as objective variables and age, sex, education duration, smoking history, olfaction test score, and the Montreal Cognitive Assessment-Japanese version (MoCA-J) score as explanatory variables. Significant relationships were found between olfactory test scores and ICV-normalised GMVs of the left and right hippocampi and left amygdala (p = 0.020, 0.024, and 0.028, respectively), adjusting for the MoCA-J score. The olfactory test score was significantly related to the right amygdalar GMV (p = 0.020) in older adults (age ≥ 65 years). These associations remained significant after applying Benjamini-Hochberg multiple testing correction (false discovery rate < 0.1). Therefore, olfactory and cognitive function tests may efficiently capture the degree of atrophy in the hippocampi and amygdala, especially in older adults.

Genetic Risk Stratification of Primary Open-Angle Glaucoma in Japanese Individuals.

PURPOSE: To assess the impact of genetic risk estimation for primary open-angle glaucoma (POAG) in Japanese individuals. DESIGN: Cross-sectional analysis. PARTICIPANTS: Genetic risk scores (GRSs) were constructed based on a genome-wide association study (GWAS) of POAG in Japanese people. A total of 3625 Japanese individuals, including 1191 patients and 2434 controls (Japanese Tohoku), were used for the model selection. We also evaluated the discriminative accuracy of constructed GRSs in a dataset comprising 1034 patients and 1147 controls (the Japan Glaucoma Society Omics Group [JGS-OG] and the Genomic Research Committee of the Japanese Ophthalmological Society [GRC-JOS]) and 1900 participants from a population-based study (Hisayama Study). METHODS: We evaluated 2 types of GRSs: polygenic risk scores using the pruning and thresholding procedure and a GRS using variants associated with POAG in the GWAS of the International Glaucoma Genetics Consortium (IGGC). We selected the model with the highest areas under the receiver operating characteristic curve (AUC). In the population-based study, we evaluated the correlations between GRS and ocular measurements. MAIN OUTCOME MEASURE: Proportion of patients with POAG after stratification according to the GRS. RESULTS: We found that a GRS using 98 variants, which showed genome-wide significance in the IGGC, showed the best discriminative accuracy (AUC, 0.65). In the Japanese Tohoku, the proportion of patients with POAG in the top 10% individuals was significantly higher than that in the lowest 10% (odds ratio [OR], 6.15; 95% confidence interval [CI], 4.35-8.71). In the JGS-OG and GRC-JOS, we confirmed similar impact of POAG GRS (AUC, 0.64; OR [top vs. bottom decile], 5.81; 95% CI, 3.79-9.01). In the population-based study, POAG prevalence was significantly higher in the top 20% individuals of the GRS compared with the bottom 20% (9.2% vs. 5.0%). However, the discriminative accuracy was low (AUC, 0.56). The POAG GRS was correlated positively with intraocular pressure (r = 0.08: P = 4.0 × 10-4) and vertical cup-to-disc ratio (r = 0.11; P = 4.0 × 10-6). CONCLUSIONS: The GRS showed moderate discriminative accuracy for POAG in the Japanese population. However, risk stratification in the general population showed relatively weak discriminative performance. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses.

Type 2 diabetes (T2D) shows heterogeneous body mass index (BMI) sensitivity. Here, we performed stratification based on BMI to optimize predictions for BMI-related diseases. We obtained BMI-stratified datasets using data from more than 195,000 individuals (nT2D = 55,284) from BioBank Japan (BBJ) and UK Biobank. T2D heritability in the low-BMI group was greater than that in the high-BMI group. Polygenic predictions of T2D toward low-BMI targets had pseudo-R2 values that were more than 22% higher than BMI-unstratified targets. Polygenic risk scores (PRSs) from low-BMI discovery outperformed PRSs from high BMI, while PRSs from BMI-unstratified discovery performed best. Pathway-specific PRSs demonstrated the biological contributions of pathogenic pathways. Low-BMI T2D cases showed higher rates of neuropathy and retinopathy. Combining BMI stratification and a method integrating cross-population effects, T2D predictions showed greater than 37% improvements over unstratified-matched-population prediction. We replicated findings in the Tohoku Medical Megabank (n = 26,000) and the second BBJ cohort (n = 33,096). Our findings suggest that target stratification based on existing traits can improve the polygenic prediction of heterogeneous diseases.

Genetic Risk, Healthy Lifestyle Adherence, and Risk of Developing Diabetes in the Japanese Population.

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.

Associations of combined genetic and lifestyle risks with hypertension and home hypertension.

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.

A fine-scale genetic map of the Japanese population.

Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.

GWAS meta-analysis of kidney function traits in Japanese populations.

BACKGROUND: Genetic epidemiological evidence for the kidney function traits in East Asian population including Japanese remain still relatively unclarified. Especially, the number of GWASs for kidney traits reported still remains limited, and the sample size of each independent study is relatively small. Given the genetic variability between ancestries/ethnicities, implementation of GWAS with sufficiently large sample sizes in specific population of Japanese is considered meaningful. METHODS: We conducted the GWAS meta-analyses of kidney traits by leveraging the GWAS summary data of the representative large genome cohort studies with about 200,000 Japanese participants (n = 202,406 for estimated glomerular filtration rate [eGFR] and n = 200,845 for serum creatinine [SCr]). RESULTS: In the present GWAS meta-analysis, we identified 110 loci with 169 variants significantly associated with eGFR (on chromosomes 1-13 and 15-22; p < 5×10-8), whereas we also identified 112 loci with 176 variants significantly associated with SCr (on chromosomes 1-22; p < 5×10-8), of which one locus (more than 1Mb distant from known loci) with one variant (CD36 rs146148222 on chromosome 7) for SCr was considered as the truly novel finding. CONCLUSIONS: The present GWAS meta-analysis of largest genome cohort studies in Japanese provided some original genomic loci associated with kidney function in Japanese, which may contribute to the possible development of personalized prevention of kidney diseases based on genomic information in the near future.

Progress Report of the Tohoku Medical Megabank Community-based Cohort Study: Study Profile of the Repeated Center-based Survey During Second Period in Miyagi Prefecture.

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 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 second 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 second period survey. There were three main ways of participation in the baseline survey: Type 1, Type 1 additional, or Type 2 survey. The second 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 second 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 second period survey respondents in the Type 1 and Type 2 survey groups at baseline had similar traits. CONCLUSION: The second 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.

Genetic architecture of alcohol consumption identified by a genotype-stratified GWAS and impact on esophageal cancer risk in Japanese people.

An East Asian-specific variant on aldehyde dehydrogenase 2 (ALDH2 rs671, G>A) is the major genetic determinant of alcohol consumption. We performed an rs671 genotype-stratified genome-wide association study meta-analysis of alcohol consumption in 175,672 Japanese individuals to explore gene-gene interactions with rs671 behind drinking behavior. The analysis identified three genome-wide significant loci (GCKR, KLB, and ADH1B) in wild-type homozygotes and six (GCKR, ADH1B, ALDH1B1, ALDH1A1, ALDH2, and GOT2) in heterozygotes, with five showing genome-wide significant interaction with rs671. Genetic correlation analyses revealed ancestry-specific genetic architecture in heterozygotes. Of the discovered loci, four (GCKR, ADH1B, ALDH1A1, and ALDH2) were suggested to interact with rs671 in the risk of esophageal cancer, a representative alcohol-related disease. Our results identify the genotype-specific genetic architecture of alcohol consumption and reveal its potential impact on alcohol-related disease risk.

Influence of Diabetes Family History on the Associations of Combined Genetic and Lifestyle Risks with Diabetes in the Tohoku Medical Megabank Community-Based Cohort Study.

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.

Association Between Olfactory Test Data with Multiple Levels of Odor Intensity and Suspected Cognitive Impairment: A Cross-Sectional Study.

BACKGROUND: Olfactory function decline has recently been reported to be associated with a risk of cognitive impairment. Few population-based studies have included younger adults when examining the association between olfactory test data with multiple odor intensities and suspected cognitive impairment. OBJECTIVE: We investigated the association between high-resolution olfactory test data with fewer odors and suspected cognitive impairments. We also examined the differences between older and younger adults in this association. METHODS: The Japanese version of the Montreal Cognitive Assessment (MoCA-J) was administered to 1,450 participants, with three odor-intensity-level olfactometry using six different odors. Logistic regressions to discriminate suspected cognitive impairment were conducted to examine the association, adjusted for age, sex, education duration, and smoking history. Data were collected from the Program by Tohoku University Tohoku Medical Megabank Organization, with an additional olfactory test conducted between 2019 and 2021. RESULTS: We generally observed that the lower the limit of distinguishable odor intensity was, the higher the MoCA-J score was. The combination of spearmint and stuffy socks contributed most to the distinction between suspected and unsuspected cognitive impairment. Furthermore, the association was significant in women aged 60-74 years (adjusted odds ratio 0.881, 95% confidence interval [0.790, 0.983], p = 0.024). CONCLUSIONS: The results indicate an association between the limit of distinguishable odor intensity and cognitive function. The olfactory test with multiple odor intensity levels using fewer odors may be applicable for the early detection of mild cognitive impairment, especially in older women aged 60-74 years.

Associations between birth weight and lung function in a Japanese adult population: The tohoku medical megabank community-based cohort study.

BACKGROUND: Birth weight, as a measure of intrauterine growth, is commonly used in epidemiological studies and is reported to be associated with adult lung function. However, findings regarding this association in previous studies have been inconsistent. Furthermore, no studies have reported associations stratified by age or smoking status, or adjusted for eosinophil count or other parameters related to type 2 airway inflammation. METHODS: This cross-sectional study included 2632 men and 7237 women aged ≥20 years living in Miyagi Prefecture, Japan. Lung function was assessed based on spirometry. Birth weight data were obtained through a questionnaire survey. Analysis of covariance was used to evaluate the associations between birth weight and lung function, adjusting for potential confounders. Stratified analyses by age and smoking status were also conducted, together with a sub-analysis for low birth-weight participants. RESULTS: Birth weight was positively associated with forced expiratory volume in 1 s (FEV1) for both sexes and with vital capacity in women, after adjusting for height, age, smoking status, and parameters related to type 2 airway inflammation. The stratified analysis for smoking status revealed associations in never-smokers and ex-smokers. When stratified by age, the associations were confirmed in middle-aged participants. The effect of smoking status on the FEV1 of low birth-weight participants was not significant. CONCLUSIONS: Our analysis of a large, Japanese adult population showed that birth weight was independently and positively associated with adult lung function, even after adjustment for age, height, smoking status, and parameters related to type 2 airway inflammation.

Investigating the association between glycaemic traits and colorectal cancer in the Japanese population using Mendelian randomisation.

Observational studies suggest that abnormal glucose metabolism and insulin resistance contribute to colorectal cancer; however, the causal association remains unknown, particularly in Asian populations. A two-sample Mendelian randomisation analysis was performed to determine the causal association between genetic variants associated with elevated fasting glucose, haemoglobin A1c (HbA1c), and fasting C-peptide and colorectal cancer risk. In the single nucleotide polymorphism (SNP)-exposure analysis, we meta-analysed study-level genome-wide associations of fasting glucose (~ 17,289 individuals), HbA1c (~ 52,802 individuals), and fasting C-peptide (1,666 individuals) levels from the Japanese Consortium of Genetic Epidemiology studies. The odds ratios of colorectal cancer were 1.01 (95% confidence interval [CI], 0.99-1.04, P = 0.34) for fasting glucose (per 1 mg/dL increment), 1.02 (95% CI, 0.60-1.73, P = 0.95) for HbA1c (per 1% increment), and 1.47 (95% CI, 0.97-2.24, P = 0.06) for fasting C-peptide (per 1 log increment). Sensitivity analyses, including Mendelian randomisation-Egger and weighted-median approaches, revealed no significant association between glycaemic characteristics and colorectal cancer (P > 0.20). In this study, genetically predicted glycaemic characteristics were not significantly related to colorectal cancer risk. The potential association between insulin resistance and colorectal cancer should be validated in further studies.

Association between the extent of house collapse and urine sodium-to-potassium ratio of victims affected by the 2011 Great East Japan Earthquake and Tsunami: a cross-sectional study.

People who experience natural disasters have a high risk of developing cardiovascular diseases. We investigated the association between the extent of house collapse and urine sodium-to-potassium (UNa/K) ratio of 2011 Great East Japan Earthquake victims. We used the baseline survey data of the Tohoku Medical Megabank Project Community-Based Cohort Study of 29 542 individuals (aged 20-74 years) residing in the affected areas. The UNa/K ratio was calculated using spot urinary electrolyte values. Analysis of covariance was used to calculate the multivariate-adjusted geometric means of the UNa/K ratio in the following groups stratified according to the self-reported extent of house collapse: total collapse (TC), half collapse (HC), partial collapse (PC), and no damage (ND). Multivariable-adjusted odds ratios (ORs) for a high UNa/K ratio were calculated using logistic regression. The TC, HC, PC, and ND groups comprised 5 359 (18.1%), 3 576 (12.1%), 7 331 (24.8%), and 13 276 (44.9%) participants, respectively. The TC (3.33; 95% confidence interval [CI], 3.28-3.38), HC (3.37; 3.30-3.43), and PC (3.32; 3.28-3.37) groups had significantly higher multivariate-adjusted geometric means of the UNa/K ratio than the ND (3.24; 3.21-3.27) group. The multivariable-adjusted ORs (95% CIs) for a high UNa/K ratio in the TC, HC, and PC groups vs. the ND group were 1.07 (0.99-1.15), 1.20 (1.11-1.31), and 1.20 (1.12-1.28), respectively. Similar associations between house collapse and UNa/K ratio were observed for both sexes. We report that victims of a natural disaster tend to have a diet with high sodium-to-potassium ratio.

Genome-wide association study of the risk of chronic kidney disease and kidney-related traits in the Japanese population: J-Kidney-Biobank.

Chronic kidney disease (CKD) is a syndrome characterized by a gradual loss of kidney function with decreased estimated glomerular filtration rate (eGFR), which may be accompanied by an increase in the urine albumin-to-creatinine ratio (UACR). Although trans-ethnic genome-wide association studies (GWASs) have been conducted for kidney-related traits, there have been few analyses in the Japanese population, especially for the UACR trait. In this study, we conducted a GWAS to identify loci related to multiple kidney-related traits in Japanese individuals. First, to detect loci associated with CKD, eGFR, and UACR, we performed separate GWASs with the following two datasets: 475 cases of CKD diagnosed at seven university hospitals and 3471 healthy subjects (dataset 1) and 3664 cases of CKD-suspected individuals with eGFR <60 ml/min/1.73 m2 or urinary protein ≥ 1+ and 5952 healthy subjects (dataset 2). Second, we performed a meta-analysis between these two datasets and detected the following associated loci: 10 loci for CKD, 9 loci for eGFR, and 22 loci for UACR. Among the loci detected, 22 have never been reported previously. Half of the significant loci for CKD were shared with those for eGFR, whereas most of the loci associated with UACR were different from those associated with CKD or eGFR. The GWAS of the Japanese population identified novel genetic components that were not previously detected. The results also suggest that the group primarily characterized by increased UACR possessed genetically different features from the group characterized by decreased eGFR.