👤 Yachiyo Kuwatsuka

Obesity, a risk factor for all-cause and cardiovascular mortality, is a major health concerns among middle-aged men. The aim of this study was to investigate a possible association of dietary habits and obesity related single nucleotide polymorphisms (SNPs) with obesity and metabolic abnormalities. We conducted a retrospective cohort study using annual health examination data of 5112 male workers, obtained between 2007 and 2011. Average dietary energy was estimated using electronically collected meal purchase data from cafeteria. We examined 8 SNPs related to obesity: GHRL rs696217, PPARG rs1175544, ADIPOQ rs2241766, ADIPOQ rs1501299, PPARD rs2016520, APOA5 rs662799, BRAP rs3782886, and ITGB2 rs235326. We also examined whether SNPs that were shown to associate with obesity affect other metabolic abnormalities such as blood pressure (BP), glucose, and lipid profile. Average dietary energy significantly associated with increased abdominal circumference (AC) and body mass index (BMI). The odds ratios (ORs) of overweight and obesity also increased. The major allele of rs696217 significantly increased BMI and an increased OR with obesity, while the minor allele of rs3782886 was associated with significantly decreased AC and the decreased ORs with overweight and obesity. The minor allele of rs3782886 was also associated with significantly decreased systolic BP (SBP), triglyceride (TG), high-density lipoprotein (HDL), and fasting blood sugar (FBS), while rs696217 was not associated with other metabolic abnormalities. Average dietary energy in lunch, rs3782886, and rs696217 were associated with obesity, and rs3782886 was associated with other metabolic abnormalities. Show less

Several single nucleotide polymorphisms (SNPs) have been implicated in the predisposition to chronic kidney disease (CKD). Atherosclerotic disease is deeply involved in the incidence of CKD; however, whether SNPs related to arteriosclerosis are involved in CKD remains unclear. This study aimed to identify SNPs associated with CKD and to examine whether risk allele accumulation is associated with CKD. We conducted a cross-sectional study using data of 4814 male workers to examine the association between estimated glomerular filtration rate (eGFR) and 59 candidate polymorphisms (17 CKD, 42 atherosclerotic diseases). We defined the genetic risk score (GRS) as the total number of risk alleles that showed a significant association in this analysis and examined the relationship with CKD (eGFR < 60 ml/min/1.73m2). Multivariate logistic regression, discrimination by area under the receiver operating characteristic curve, integrated discrimination improvement (IDI), and category-free net reclassification improvement (cNRI) were evaluated. In total, 432 participants were categorized as having CKD. We found eight candidate SNPs with P value < 0.05 (CX3CR1 rs3732379, SHROOM3 rs17319721, MTP rs1800591, PIP5K1B rs4744712, APOA5 rs662799, BRAP rs3782886, SPATA5L1 rs2467853, and MCP1 rs1024611) in the multivariate linear regression adjusted for age, body mass index, systolic blood pressure, and fasting blood glucose. Among these eight SNPs, BRAP rs3782886 and SPATA5L1 rs2467853 were significantly associated with eGFR (false discovery rate < 0.05). GRS was significantly associated with CKD (odds ratio, 1.17; 95% confidence interval, 1.09-1.26). C-statisics improved from 0.775 to 0.780 but showed no statistical significance. However, adding GRS significantly improved IDI and cNRI (0.0057, P = 0.0028, and 0.212, P < 0.001, respectively). After adjustment for clinical factors, kidney function was associated with BRAP rs3782886 and SPATA5L1 rs2467853 and the GRS for CKD that we developed was associated CKD. Show less

Although many single nucleotide polymorphisms (SNPs) have been identified to be associated with metabolic syndrome (MetS), there was only a slight improvement in the ability to predict future MetS by the simply addition of SNPs to clinical risk markers. To improve the ability to predict future MetS, combinational effects, such as SNP-SNP interaction, SNP-environment interaction, and SNP-clinical parameter (SNP × CP) interaction should be also considered. We performed a case-control study to explore novel SNP × CP interactions as risk markers for MetS based on health check-up data of Japanese male employees. We selected 99 SNPs that were previously reported to be associated with MetS and components of MetS; subsequently, we genotyped these SNPs from 360 cases and 1983 control subjects. First, we performed logistic regression analyses to assess the association of each SNP with MetS. Of these SNPs, five SNPs were significantly associated with MetS (P < 0.05): LRP2 rs2544390, rs1800592 between UCP1 and TBC1D9, APOA5 rs662799, VWF rs7965413, and rs1411766 between MYO16 and IRS2. Furthermore, we performed multiple logistic regression analyses, including an SNP term, a CP term, and an SNP × CP interaction term for each CP and SNP that was significantly associated with MetS. We identified a novel SNP × CP interaction between rs7965413 and platelet count that was significantly associated with MetS [SNP term: odds ratio (OR) = 0.78, P = 0.004; SNP × CP interaction term: OR = 1.33, P = 0.001]. This association of the SNP × CP interaction with MetS remained nominally significant in multiple logistic regression analysis after adjustment for either the number of MetS components or MetS components excluding obesity. Our results reveal new insight into platelet count as a risk marker for MetS. Show less