Visceral fat mass: is it the link between uric acid and diabetes risk?

Seyedsadjadi, Neda; Berg, J.H.J. van den; Bilgin, Ayşe; Grant, Ross

doi:10.1186/s12944-017-0532-4

Cited by 32 publications

(24 citation statements)

References 46 publications

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“…Further, the levels of pantothenic acid and uric acid were lower in the BET+PDX group, as in the HF control group, in SAT. Interestingly, in obese nondiabetics, the amount of VAT, but not SAT, correlated with serum uric acid levels . Hyperuricemia is associated with components of MetS, and uric acid has also been suggested as a novel risk factor for diabetes .…”

Section: Discussionmentioning

confidence: 97%

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High‐Fat Diet, Betaine, and Polydextrose Induce Changes in Adipose Tissue Inflammation and Metabolism in C57BL/6J Mice

Airaksinen

Jokkala

Ahonen³

et al. 2018

Molecular Nutrition Food Res

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Scope High‐fat diets are a likely cause of low‐grade inflammation and obesity‐related pathologies. This study measures the effects of a high‐fat diet, in combination with two dietary supplements—betaine and polydextrose—on metabolism and inflammation in the adipose tissue of diet‐induced obese mice. Methods and Results Forty male C57BL/6J mice are fed a high‐fat diet for 8 weeks and compared with low‐fat‐diet‐fed control animals (n = 10). For the last 4 weeks, the high‐fat‐diet‐fed animals are supplemented with 1% betaine, 3.33% polydextrose, their combination, or plain water. Fat depots from subcutaneous and visceral adipose tissue are analyzed for inflammatory markers and nontargeted metabolomics by quantitative PCR and LC–QTOF‐MS. The high‐fat diet significantly increases adipose tissue inflammation in both fat depots. By metabolic profiling, clear differences are noted between low‐fat‐diet and high‐fat‐diet groups with regard to the levels of several metabolite species—primarily carnitines, lipids, and amino acids. Dietary betaine mitigates the high‐fat‐diet‐induced IL‐6 expression and significantly increases betaine and butyrobetaine levels in adipose tissue. Conclusions The high‐fat diet induces patent changes in carnitine and lipid metabolism in adipose tissue. Betaine supplementation elevates the levels of betaine and its derivatives and certain carnitine species, as reported in muscle and liver, and moderately reduces inflammation.

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Section: Discussionmentioning

confidence: 97%

“…Interestingly, in obese nondiabetics, the amount of VAT, but not SAT, correlated with serum uric acid levels. [38] Hyperuricemia is associated with components of MetS, and uric acid has also been suggested as a novel risk factor for diabetes. [38] The effect of BET on lipid species was nearly insignificant.…”

Section: Discussionmentioning

confidence: 99%

High‐Fat Diet, Betaine, and Polydextrose Induce Changes in Adipose Tissue Inflammation and Metabolism in C57BL/6J Mice

Airaksinen

Jokkala

Ahonen³

et al. 2018

Molecular Nutrition Food Res

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“…This implies that the risks for health are related to where body fat is stored. A higher level of android fat and/or its proportion in relation to gynoid fat, for instance, is linked to risk factors for developing diseases (25).…”

Section: Discussionmentioning

confidence: 99%

Cytokines and body adiposity in young female undergraduate students

Pereira¹,

Silva²,

Lopes³

et al. 2020

Nutr Hosp

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Objective: to identify cytokines and to associate them with several indexes of total and central adiposity in young female undergraduate students. 2 Methods: 58 young female sophomore students, aged 18 to 25 years, from a Brazilian public university were evaluated. Both anthropometric measures (weight, height, waist circumference and hip circumference) and body composition were assessed through DXA, and the values of android, gynoid and truncal fat mass were obtained. Cytokines (IL-8, IL-1β, IL-6, IL-10 e TNF-α) were analyzed, and Body Mass Index (BMI), Body Adiposity Index (BAI), Visceral Adiposity Index (VAI), Conicity Index (CCI), Waist-Hip Index (WHR), Waist-to-Height Ratio (WHtR), Fat Mass Distribution Index 1 (FMI 1) and Fat Mass Distribution Index 2 (FMI 2) were calculated. Eventually, a linear regression was carried out to determine the regression coefficient and confidence interval (CI), having the predictor variables (cytokines) adjusted according to age and family history of obesity. The statistical significance of α = 5% was applied. Results: a correlation between adiposity indexes and cytokines (CCI, WHR and IL-12; CCI, WHR, FMI 1 , FMI 2 and TNF-α) was identified. When it comes to the regression models, cytokines increase was related to CCI, WHR, FMI 1 and FMI 2 increase. Conclusion: pro-inflammatory cytokines were associated with an increase in adipose indexes. Therefore, these indexes became a feasible strategy for clinical practice in order to identify propensity to inflammatory disorders.

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“…Furthermore, Sun et al (Sun et al 2015) found that uric acid-associated genes have an impact on insulin secrction in a Chinese patients with T2DM. Finally, another study (Seyed-Sadjadi et al 2017) showed that the associations between SUA and diabetes risk factors are Manuscript to be reviewed…”

Section: Discussionmentioning

confidence: 99%

Peer Review #1 of "The relationship between serum uric acid within the normal range and β-cell function in Chinese patients with type 2 diabetes: differences by body mass index and gender (v0.1)"

2019

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Background: Elevated serum uric acid (SUA) has a positive correlation with insulin secretion and insulin resistance indexes. However, whether weight-and gender-specific differences regarding the relationship between SUA within the normal range and β-cell function and insulin resistance exist is unknown in T2DM patients. Methods: Three hundreds and eighty patients with type 2 diabetes were divided into two groups as overweight/obesity (n=268) and normal weight (n=112). Each group were again divided into low (LSUA) and high normal SUA (HSUA). The HbA1c, C-peptide, SUA, creatinine, and lipids profiles were measured. HOMA2IR and HOMA%2B were estimated using fasting glucose and C-peptide by homeostasis model assessment (HOMA). Pearson's correlations and multiple linear regression analyses were conducted to assess the associations between SUA levels and islet function indexes. Results: In overweight/obesity subgroup, the levels of BMI, FCP, P2HCP, FCPI, PPCPI, ΔC-peptide, HOMA2%B and HOMA2IR were higher in HSUA group than in LSUA group. In contrast, the HbA1c, FBS, and P2hBS were lower in HSUA than in LSUA. In normal weight subgroup, there were on differences between the HSUA than LSUA group in terms of clinical characteristics. Pearson's correlations indicated that there were no significant correlations between SUA and insulin secretory capacity in normal weight group, but in overweight/obesity group, SUA had positive significant correlations with P2hCP, FCPI, PPCPI, ΔC-peptide, and HOMA2%B. In female group, there were no significant correlations between SUA and insulin secretory capacity. However, in male group, SUA had positive significant correlations with insulin secretory capacity include P2hCP, FCPI, PPCPI, ΔC-peptide, and HOMA2%B. Multiple linear regression showed that SUA was significantly associated with HOMA2%B, but not with HOMA2IR in overweight/obesity and male group. Conclusions : Our study shows that SUA levels within normal range were associated with β-cell function in T2DM patients with overweight/obesity or male. This finding supports that the association between SUA within normal range and insulin secretion ability differs by weight and sex.

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Visceral fat mass: is it the link between uric acid and diabetes risk?

Cited by 32 publications

References 46 publications

High‐Fat Diet, Betaine, and Polydextrose Induce Changes in Adipose Tissue Inflammation and Metabolism in C57BL/6J Mice

High‐Fat Diet, Betaine, and Polydextrose Induce Changes in Adipose Tissue Inflammation and Metabolism in C57BL/6J Mice

Cytokines and body adiposity in young female undergraduate students

Peer Review #1 of "The relationship between serum uric acid within the normal range and β-cell function in Chinese patients with type 2 diabetes: differences by body mass index and gender (v0.1)"

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