OBJECTIVE: Central obesity predisposes to various cardiometabolic diseases and is a key component of the metabolic syndrome (MetS). We have previously demonstrated that three obesity-susceptible single nucleotide polymorphisms (SNPs), rs10938397 (GNPDA2), rs8050136 (FTO) and rs17782313 (MC4R), were associated with obesity and waist circumference in cross-sectional studies in the Chinese population. In this study, we investigate whether these SNPs could also predict the persistence of central obesity and MetS in subjects from the Hong Kong Cardiovascular Risk Factors Prevalence Study (CRISPS) cohort. DESIGN AND METHODS: We genotyped these SNPs in i) 354 subjects with and 994 subjects without central obesity at both baseline and a 12-year follow-up, ii) 2214 subjects (816 cases and 1398 controls) in an MetS cross-sectional case-control study and iii) 225 subjects with and 1221 subjects without MetS at both baseline and the 12-year follow-up. RESULTS: Both FTO rs8050136 (P(age, sex-adjusted)=0.019; odds ratio (OR) (95% confidence intervals (CI)): 1.35 (1.05, 1.73)) and GNPDA2 rs10938397 (P(age, sex-adjusted)=3 × 10(-3); OR (95% CI): 1.34 (1.11, 1.63)) were significantly associated with persistent central obesity. GNPDA2 rs10938397 was also significantly associated with MetS (P(age, sex-adjusted)=0.011, OR (95% CI): 1.20 (1.04, 1.38)) in the case-control study. However, none of these SNPs showed an individual association with persistent MetS. In the combined genetic risk analyses for persistent central obesity and persistent MetS, the combined genetic risk score of the three SNPs showed an OR of 1.25 (95% CI: 1.10, 1.42; P(age, sex-adjusted)=4.92 × 10(-3)) and 1.19 (95% CI: 1.03, 1.38; P(age, sex-adjusted)=0.019) for each additional risk allele respectively. CONCLUSION: This study demonstrated that FTO and GNPDA2 variants predicted persistent central obesity in the Chinese population, further supporting their importance as obesity-susceptible genes.
OBJECTIVE: Central obesity predisposes to various cardiometabolic diseases and is a key component of the metabolic syndrome (MetS). We have previously demonstrated that three obesity-susceptible single nucleotide polymorphisms (SNPs), rs10938397 (GNPDA2), rs8050136 (FTO) and rs17782313 (MC4R), were associated with obesity and waist circumference in cross-sectional studies in the Chinese population. In this study, we investigate whether these SNPs could also predict the persistence of central obesity and MetS in subjects from the Hong Kong Cardiovascular Risk Factors Prevalence Study (CRISPS) cohort. DESIGN AND METHODS: We genotyped these SNPs in i) 354 subjects with and 994 subjects without central obesity at both baseline and a 12-year follow-up, ii) 2214 subjects (816 cases and 1398 controls) in an MetS cross-sectional case-control study and iii) 225 subjects with and 1221 subjects without MetS at both baseline and the 12-year follow-up. RESULTS: Both FTOrs8050136 (P(age, sex-adjusted)=0.019; odds ratio (OR) (95% confidence intervals (CI)): 1.35 (1.05, 1.73)) and GNPDA2rs10938397 (P(age, sex-adjusted)=3 × 10(-3); OR (95% CI): 1.34 (1.11, 1.63)) were significantly associated with persistent central obesity. GNPDA2rs10938397 was also significantly associated with MetS (P(age, sex-adjusted)=0.011, OR (95% CI): 1.20 (1.04, 1.38)) in the case-control study. However, none of these SNPs showed an individual association with persistent MetS. In the combined genetic risk analyses for persistent central obesity and persistent MetS, the combined genetic risk score of the three SNPs showed an OR of 1.25 (95% CI: 1.10, 1.42; P(age, sex-adjusted)=4.92 × 10(-3)) and 1.19 (95% CI: 1.03, 1.38; P(age, sex-adjusted)=0.019) for each additional risk allele respectively. CONCLUSION: This study demonstrated that FTO and GNPDA2 variants predicted persistent central obesity in the Chinese population, further supporting their importance as obesity-susceptible genes.
Authors: Jacquelyn Y Taylor; Aldi T Kraja; Lisa de Las Fuentes; Ansley Grimes Stanfill; Ashley Clark; Ann Cashion Journal: J Nurs Scholarsh Date: 2013-01-31 Impact factor: 3.176
Authors: Bo Xi; Hong Cheng; Yue Shen; Giriraj R Chandak; Xiaoyuan Zhao; Dongqing Hou; Lijun Wu; Xingyu Wang; Jie Mi Journal: PLoS One Date: 2013-02-12 Impact factor: 3.240