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Uric acid and obesity-related phenotypes in postmenopausal women.

ABSTRACT: The aim of this study was to find the genetic, metabolic, and nutritional risk factors, which can be associated with uric acid (UA) level. The risk factors related to uricemia were assessed among 271 postmenopausal women without cardiometabolic disorders and hypolipidemic/hypoglycemic treatment selected from a cohort of 1423 obese postmenopausal women. The bioimpedance analysis and biochemical and genetic analyses were performed in two groups characterized by serum UA ? 4 mg/dL (238 ?mol/L) and < 4 mg/dL. The TaqMan-based real-time PCR method was applied to assess the role of Pro12Ala of peroxisome proliferation-activated receptor (PPAR)gamma-2 and Trp64Arg of beta-3-adrenergic receptor (ADRB) polymorphisms. Women with UA level ? 4 mg/dL were characterized by larger body mass, triceps skinfold, waist circumference, body fat amount, and serum insulin, glucose, and triglyceride levels. There was no difference in dietary habits between the analyzed groups. Body mass, waist circumference, body fat amount, diastolic blood pressure, and serum insulin, glucose, high-density lipoprotein, and triglyceride levels, Homeostasis Model Assessment-Insulin Resistance, and energy from the dietary fat influence the UA level ? 4 mg/dL; however, the serum UA was not determined by Pro12Ala and Trp64Arg polymorphism analyses. The model of linear regression revealed that the group characterized by body mass index ? 25 kg/m2 and glucose ? 100 mg/dL has 4 times increased risk of UA level (p = 0.0009); after adding triglycerides ? 150 mg/dL, the risk of UA increased 7 times (p = 0.0216). Increasing the level of UA ? 4 mg/dL is associated with overweight, hyperglycemia, and hypertriglyceridemia in women without a history of cardiometabolic disorders. A better management of metabolic factors could help prevent further increase in UA levels.

SUBMITTER: Grygiel-Gorniak B

PROVIDER: S-EPMC5943388 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Uric acid and obesity-related phenotypes in postmenopausal women.

Grygiel-Górniak B B Mosor M M Marcinkowska J J Przysławski J J Nowak J J

Molecular and cellular biochemistry 20171026 1-2

The aim of this study was to find the genetic, metabolic, and nutritional risk factors, which can be associated with uric acid (UA) level. The risk factors related to uricemia were assessed among 271 postmenopausal women without cardiometabolic disorders and hypolipidemic/hypoglycemic treatment selected from a cohort of 1423 obese postmenopausal women. The bioimpedance analysis and biochemical and genetic analyses were performed in two groups characterized by serum UA ≥ 4 mg/dL (238 μmol/L) and ...[more]

PMID: 29075989

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Project description:Obesity is a risk factor for periodontal disease (PD). Initiation and progression of PD are modulated by complex interactions between oral dysbiosis and host responses. Although obesity is associated with increased susceptibility to bacterial infection, the detailed mechanisms that connect obesity and susceptibility to PD remain elusive. Using fecal microbiota transplantation and a ligature-induced PD model, we demonstrated that gut dysbiosis-associated metabolites from high-fat diet (HFD)-fed mice worsen alveolar bone destruction. Fecal metabolomics revealed elevated purine degradation pathway activity in HFD-fed mice, and recipient mice had elevated levels of serum uric acid upon PD induction. Furthermore, PD induction caused more severe bone destruction in hyperuricemic than normouricemic mice, and the worsened bone destruction was completely abrogated by allopurinol, a xanthine oxidase inhibitor. Thus, obesity increases the risk of PD by increasing production of uric acid mediated by gut dysbiosis. IMPORTANCE Obesity is an epidemic health issue with a rapid increase worldwide. It increases the risk of various diseases, including periodontal disease, an oral chronic infectious disease. Although obesity increases susceptibility to bacterial infection, the precise biological mechanisms that link obesity and susceptibility to periodontal disease remain elusive. Using fecal microbial transplantation, experimental periodontitis, and metabolomics, our study demonstrates uric acid as a causative substance for greater aggravation of alveolar bone destruction in obesity-related periodontal disease. Gut microbiota from obese mice upregulated the purine degradation pathway, and the resulting elevation of serum uric acid promoted alveolar bone destruction. The effect of uric acid was confirmed by administration of allopurinol, an inhibitor of xanthine oxidase. Overall, our study provides new insights into the pathogenic mechanisms of obesity-associated periodontal disease and the development of new therapeutic options for the disease.

Project description:OBJECTIVE:Body mass index (BMI) is a widely used indicator of obesity status in clinical settings and population health research. However, there are concerns about the validity of BMI as a measure of obesity in postmenopausal women. Unlike BMI, which is an indirect measure of obesity and does not distinguish lean from fat mass, dual-energy x-ray absorptiometry (DXA) provides a direct measure of body fat and is considered a gold standard of adiposity measurement. The goal of this study is to examine the validity of using BMI to identify obesity in postmenopausal women relative to total body fat percent measured by DXA scan. METHODS:Data from 1,329 postmenopausal women participating in the Buffalo OsteoPerio Study were used in this analysis. At baseline, women ranged in age from 53 to 85 years. Obesity was defined as BMI ??30?kg/m and body fat percent (BF%) greater than 35%, 38%, or 40%. We calculated sensitivity, specificity, positive predictive value, and negative predictive value to evaluate the validity of BMI-defined obesity relative BF%. We further explored the validity of BMI relative to BF% using graphical tools, such as scatterplots and receiver-operating characteristic curves. Youden's J index was used to determine the empirical optimal BMI cut-point for each level of BF% defined obesity. RESULTS:The sensitivity of BMI-defined obesity was 32.4% for 35% body fat, 44.6% for 38% body fat, and 55.2% for 40% body fat. Corresponding specificity values were 99.3%, 97.1%, and 94.6%, respectively. The empirical optimal BMI cut-point to define obesity is 24.9?kg/m for 35% BF, 26.49?kg/m for 38% BF, and 27.05?kg/m for 40% BF according to the Youden's index. CONCLUSIONS:Results demonstrate that a BMI cut-point of 30?kg/m does not appear to be an appropriate indicator of true obesity status in postmenopausal women. Empirical estimates of the validity of BMI from this study may be used by other investigators to account for BMI-related misclassification in older women.

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Uric acid and obesity-related phenotypes in postmenopausal women.

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Uric acid and obesity-related phenotypes in postmenopausal women.

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