Association of Obesity-Related Genetic Variants with Android Fat Patterning and Cardiometabolic Risk in Women

肥胖相关基因变异与女性安卓型脂肪分布及心血管代谢风险的关联

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Abstract

Background/Objectives: The location and distribution of excess fat, rather than overall adiposity, are stronger predictors of cardiometabolic risk and are commonly assessed using the waist-to-hip ratio (WHR). Fat distribution in women has a heritable component, yet the genetic factors that influence it remain poorly understood. We aim to assess the association between obesity-related polymorphisms with WHR and cardiometabolic risk in overweight and obese women. Methods: A cohort study was conducted in 512 women (56.1 ± 6.4 years; body mass index (BMI) ≥ 25 kg/m(2)). WHR was calculated, and participants were classified into android (WHR > 0.85) or gynoid (WHR ≤ 0.85) obesity groups. We genotyped 15 SNPs previously associated with obesity using TaqMan real-time PCR. Different genetic models (dominant, recessive, and allelic) were analysed, and bivariate and multivariate analyses were performed to compare the fat distribution groups. Results: Of the 15 SNPs studied, only 3 presented a significant association with WHR > 0.85. PSRC1 rs599839 in a dominant model (AA + GA vs. GG) with OR = 3.18 (p = 0.041), SLC30A8 rs1326634 in a recessive model (CC vs. TC + TT) (OR = 2.38; p = 0.004), both showing increased susceptibility to central obesity. KIF6 rs20455 offers protection in a recessive model (CC vs. TC + TT) with an OR of 0.47 (p = 0.043). After adjusted multivariate analysis, only SLC30A8 and diabetes remained independently associated with an increased risk of android obesity (OR = 2.50; p = 0.003 and OR = 3.63; p = 0.004, respectively). Conclusions: The SLC30A8 variant was significantly associated with android fat distribution and high cardiometabolic risk in overweight/obese women. Identifying genetic factors that influence fat distribution may help specify targeted lifestyle changes or pharmacological interventions to reduce risk.

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