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Objective The aim of the present study was to investigate the associations between breastfeeding and the prevalence of metabolic syndrome in community-dwelling parous women and to clarify whether the associations depend on age. Methods The present cross-sectional study included 11,118 women, aged 35–69 years. Participants’ longest breastfeeding duration for one child and their number of breastfed children were assessed using a self-administered questionnaire, and their total breastfeeding duration was approximated as a product of the number of breastfed children and the longest breastfeeding duration. The longest and the total breastfeeding durations were categorized into none and tertiles above 0 months. Metabolic syndrome and cardiovascular risk factors (obesity, hypertension, dyslipidemia, and hyperglycemia) were defined as primary and secondary outcomes, respectively. Associations between breastfeeding history and metabolic syndrome or each cardiovascular risk factor were assessed using multivariable unconditional logistic regression analysis. Results Among a total of 11,118 women, 10,432 (93.8%) had ever breastfed, and 1,236 (11.1%) had metabolic syndrome. In participants aged <55 years, an inverse dose–response relationship was found between the number of breastfed children and the prevalence of metabolic syndrome; multivariable-adjusted odds ratios for 1, 2, 3, and ≥4 breastfed children were 0.60 (95% confidence interval [CI]: 0.31 to 1.17), 0.50 (95% CI: 0.29 to 0.87), 0.44 (95% CI: 0.24 to 0.84), and 0.35 (95% CI: 0.14 to 0.89), respectively. The longest and total breastfeeding durations of longer than 0 months were also associated with lower odds of metabolic syndrome relative to no breastfeeding history in participants aged <55 years. In contrast, all measures of breastfeeding history were not significantly associated with metabolic syndrome and cardiovascular risk factors in participants aged ≥55 years old. Conclusions Breastfeeding history may be relate

Genetic factors play a role in individual differences in pain experience. Here, we performed a genome-wide association study (GWAS) to identify novel loci regulating pain processing. We conducted a 2-stage GWAS and the candidate single-nucleotide polymorphisms (SNPs) association study on pain experience using an exploratory cohort of patients with cancer pain. The confirmatory cohort comprised of participants from the general population with and without habitual use of analgesic medication. In the exploratory cohort, we evaluated pain intensity using a numerical rating scale, recorded daily opioid dosages, and calculated pain reduction rate. In the confirmatory cohort, pain experience was defined as habitual nonsteroidal anti-inflammatory drug usage. Using linear regression models, we identified candidate SNP in the exploratory samples, and tested the association between phenotype and experienced pain in the confirmatory samples. We found 1 novel SNP (rs11764598)—located on the gene encoding for pleiotrophin on chromosome 7—that passed the genome-wide suggestive significance at 20% false discovery rate (FDR) correction in the exploratory samples of patients with cancer pain (P = 1.31 × 10-7, FDR = 0.101). We confirmed its significant association with daily analgesic usage in the confirmatory cohort (P = .028), although the minor allele affected pain experience in an opposite manner. We identified a novel genetic variant associated with pain experience. Further studies are required to validate the role of pleiotrophin in pain processing.

Background: Inflammation is thought to be a risk factor for kidney disease. However, whether inflammatory status is either a cause or an outcome of chronic kidney disease remains controversial. We aimed to investigate the causal relationship between high-sensitivity C-reactive protein (hs-CRP) and estimated glomerular filtration rate (eGFR) using Mendelian randomization (MR) approaches. Methods: A total of 10,521 participants of the Japan Multi-institutional Collaborative Cohort Study was analyzed in this study. We used two-sample MR approaches (the inverse-variance weighted (IVW), the weighted median (WM), and the MR-Egger method) to estimate the effect of genetically determined hs-CRP on kidney function. We selected four and three hs-CRP associated single nucleotide polymorphisms (SNPs) as two instrumental variables (IV): IVCRP and IVAsian, based on SNPs previously identified in European and Asian populations. IVCRP and IVAsian explained 3.4% and 3.9% of the variation in hs-CRP, respectively. Results: Using the IVCRP, genetically determined hs-CRP was not significantly associated with eGFR in the IVW and the WM methods (estimate per 1 unit increase in ln(hs-CRP), 0.000; 95% confidence interval [CI], −0.019 to 0.020 and −0.003; 95% CI, −0.019 to 0.014, respectively). For IVAsian, we found similar results using the IVW and the WM methods (estimate, 0.005; 95% CI, −0.020 to 0.010 and −0.004; 95% CI, −0.020 to 0.012, respectively). The MR-Egger method also showed no causal relationships between hs-CRP and eGFR (IVCRP: −0.008; 95% CI, −0.058 to 0.042; IVAsian: 0.001; 95% CI, −0.036 to 0.036). Conclusion: Our two-sample MR analyses with different IVs did not support a causal effect of hs-CRP on eGFR.

Background: While duodenal ulcer (DU) and gastric cancer (GC) are both H. pylori infection-related diseases, individuals with DU are known to have lower risk for GC. Many epidemiological studies have identified the PSCA rs2294008 T-allele as a risk factor of GC, while others have found an association between the rs2294008 C-allele and risk of DU and gastric ulcer (GU). Following these initial reports, however, few studies have since validated these associations. Here, we aimed to validate the association between variations in PSCA and the risk of DU/GU and evaluate its interaction with environmental factors in a Japanese population. Methods: Six PSCA SNPs were genotyped in 584 DU cases, 925 GU cases, and 8,105 controls from the Japan Multi-Institutional Collaborative Cohort (J-MICC). Unconditional logistic regression models were applied to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between the SNPs and risk of DU/GU. Results: PSCA rs2294008 C-allele was associated with per allele OR of 1.34 (95% CI, 1.18–1.51; P = 2.28 × 10−6) for the risk of DU. This association was independent of age, sex, study site, smoking habit, drinking habit, and H. pylori status. On the other hand, we did not observe an association between the risk of GU and PSCA SNPs. Conclusions: Our study confirms an association between the PSCA rs2294008 C-allele and the risk of DU in a Japanese population.

Traditional observational studies have reported a positive association between higher body mass index (BMI) and the risk of colorectal cancer (CRC). However, evidence from other approaches to pursue the causal relationship between BMI and CRC is sparse. A two-sample Mendelian randomization (MR) study was undertaken using 68 single nucleotide polymorphisms (SNPs) from the Japanese genome-wide association study (GWAS) and 654 SNPs from the GWAS catalogue for BMI as sets of instrumental variables. For the analysis of SNP-BMI associations, we undertook a meta-analysis with 36 303 participants in the Japanese Consortium of Genetic Epidemiology studies (J-CGE), comprising normal populations. For the analysis of SNP-CRC associations, we utilized 7636 CRC cases and 37 141 controls from five studies in Japan, and undertook a meta-analysis. Mendelian randomization analysis of inverse-variance weighted method indicated that a one-unit (kg/m2) increase in genetically predicted BMI was associated with an odds ratio of 1.13 (95% confidence interval, 1.06-1.20; P value <.001) for CRC using the set of 68 SNPs, and an odds ratio of 1.07 (1.03-1.11, 0.001) for CRC using the set of 654 SNPs. Sensitivity analyses robustly showed increased odds ratios for CRC for every one-unit increase in genetically predicted BMI. Our MR analyses strongly support the evidence that higher BMI influences the risk of CRC. Although Asians are generally leaner than Europeans and North Americans, avoiding higher BMI seems to be important for the prevention of CRC in Asian populations.

Background: Renal hypouricemia (RHUC) is characterized by a low serum uric acid (SUA) level and high fractional excretion of uric acid (FEUA). Further studies on FEUA in hypouricemic individuals are needed for a more accurate diagnosis of RHUC. Methods: In 30,685 Japanese health-examination participants, we genotyped the two most common nonfunctional variants of URAT1 (NFV-URAT1), W258X (rs121907892) and R90H (rs121907896), in 1040 hypouricemic individuals (SUA ≤ 3.0 mg/dL) and 2240 individuals with FEUA data. The effects of NFV-URAT1 on FEUA and SUA were also investigated using linear and multiple regression analyses. Results: Frequency of hypouricemic individuals (SUA ≤ 3.0 mg/dL) was 0.97% (male) and 6.94% (female) among 30,685 participants. High frequencies of those having at least one allele of NFV-URAT1 were observed in 1040 hypouricemic individuals. Furthermore, NFV-URAT1 significantly increased FEUA and decreased SUA, enabling FEUA and SUA levels to be estimated. Conversely, FEUA and SUA data of hypouricemic individuals are revealed to be useful to predict the number of NFV-URAT1. Conclusions: Our findings reveal that specific patterns of FEUA and SUA data assist with predicting the number of nonfunctional variants of causative genes for RHUC, and can also be useful for practical diagnosis of RHUC even before genetic tests.

Recent genome-wide association studies (GWAS) on the dietary habits of the Japanese population have shown that an effect rs671 allele was inversely associated with fish consumption, whereas it was directly associated with coffee consumption. Although meat is a major source of protein and fat in the diet, whether genetic factors that influence meat-eating habits in healthy populations are unknown. This study aimed to conduct a GWAS to find genetic variations that affect meat consumption in a Japanese population. We analysed GWAS data using 14 076 participants from the Japan Multi-Institutional Collaborative Cohort (J-MICC) study. We used a semi-quantitative food frequency questionnaire to estimate food intake that was validated previously. Association of the imputed variants with total meat consumption per 1000 kcal energy was performed by linear regression analysis with adjustments for age, sex, and principal component analysis components 1–10. We found that no genetic variant, including rs671, was associated with meat consumption. The previously reported single nucleotide polymorphisms that were associated with meat consumption in samples of European ancestry could not be replicated in our J-MICC data. In conclusion, significant genetic factors that affect meat consumption were not observed in a Japanese population.