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Repeated sense of hunger leads to the development of visceral obesity and metabolic syndrome in a mouse model.

ABSTRACT: Obesity-related disorders, especially metabolic syndrome, contribute to 2.8 million deaths each year worldwide, with significantly increasing morbidity. Eating at regular times and proper food quantity are crucial for maintaining a healthy status. However, many people in developed countries do not follow a regular eating schedule due to a busy lifestyle. Herein, we show that a repeated sense of hunger leads to a high risk of developing visceral obesity and metabolic syndrome in a mouse model (both 3-week and 6-week-old age, 10 mice in each group). The ad libitum (AL) group (normal eating pattern) and the food restriction (FR) group (alternate-day partially food restriction by given only 1/3 of average amount) were compared after 8-week experimental period. The total food consumption in the FR group was lower than in the AL group, however, the FR group showed a metabolic syndrome-like condition with significant fat accumulation in adipose tissues. Consequently, the repeated sense of hunger induced the typical characteristics of metabolic syndrome in an animal model; a distinct visceral obesity, hyperlipidemia, hyperglycemia and hepatic steatosis. Furthermore, we found that specifically leptin, a major metabolic hormone, played a major role in the development of these pathological disorders. Our study indicated the importance of regular eating habits besides controlling calorie intake.

SUBMITTER: Han JM

PROVIDER: S-EPMC4039491 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Repeated sense of hunger leads to the development of visceral obesity and metabolic syndrome in a mouse model.

Han Jong-Min JM Kim Hyeong-Geug HG Lee Jin-Seok JS Choi Min-Kyung MK Kim Young-Ae YA Son Chang-Gue CG

PloS one 20140530 5

Obesity-related disorders, especially metabolic syndrome, contribute to 2.8 million deaths each year worldwide, with significantly increasing morbidity. Eating at regular times and proper food quantity are crucial for maintaining a healthy status. However, many people in developed countries do not follow a regular eating schedule due to a busy lifestyle. Herein, we show that a repeated sense of hunger leads to a high risk of developing visceral obesity and metabolic syndrome in a mouse model (bo ...[more]

PMID: 24879081

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Project description:AimsMetabolic syndrome (MS) is a global health problem associated with an increased risk of diabetes mellitus (DM), cardiovascular disease (CVD), and cancer. Body composition parameters, including obesity, visceral adiposity, and sarcopenia contribute to the development of MS and CVD. Previous studies have investigated the association of individual body composition parameters with MS. Studies analyzing the association between multiple body composition parameters and MS have been rare. We aimed to investigate the association between MS and multiple body composition parameters, including obesity, visceral adiposity, and sarcopenia.MethodsA total of 13,620 subjects who underwent voluntary routine checkups at the Health Care Center of our institution between October 2014 and December 2019 were enrolled. Only data from the first examination of subjects who underwent repeated checkups were included. Clinical and laboratory data were collected. Skeletal muscle mass and visceral fat area (VFA) were measured using bioelectrical impedance analysis. Appendicular skeletal muscle mass (ASM) was divided by body weight (in kg) and expressed as a percentage (calculated as, ASM% = ASM × 100/Weight). Data were compared between the groups based on obesity, VFA, and ASM%. Logistic regression analysis was performed to determine the risk of MS in each group.ResultsBody mass index and VFA were significantly higher in subjects with MS than in those without MS. ASM% was significantly lower in subjects with MS than in those without MS. Subjects with obesity, visceral adiposity, or sarcopenia had a higher prevalence of MS than those without. As the number of metabolic components increased from 0 to 5, we identified a decreasing trend of ASM% and an increasing trend of VFA and BMI (P for trend < 0.001 for all). In the paired analyses, all the three body composition parameters showed additive effects in predicting MS. In the logistic regression analysis, the three parameters were associated with an increased risk of MS after adjustment for age, sex, hypertension, DM, dyslipidemia, smoking, alcohol intake, and C-reactive protein.ConclusionsObesity, visceral adiposity, and sarcopenia showed additive effects on MS prediction. Subjects with obesity, visceral adiposity, or sarcopenia were significantly associated with the increased risk of MS after adjustment for multiple confounders. Increasing skeletal muscle and reducing visceral fat may be strategies for the prevention or treatment of MS.

Project description:OBJECTIVE:Accumulating evidences suggests that obesity and metabolic syndrome (MetS) contribute towards lower urinary tract symptoms (LUTS) through alterations in the phenotype of bladder and prostate gland. Clinical studies indicate a link between MetS and LUTS. Nevertheless, there is lack of suitable animal model(s) which could illustrate an association linking obesity to LUTS. We examined the lower urinary tract function in an obesity-initiated MetS mouse model. METHODS:Male C57BL/6N wild-type and obese B6.V-Lepob/J maintained on regular diet for 28?weeks were subjected to the assessment of body weight (BW), body length (BL), waist circumference (WC), body mass index (BMI), blood glucose (BG), plasma insulin (INS), plasma leptin (LEP), total cholesterol (CHO), free fatty acid (FFA), and measurement of urinary functions. Whole animal peritoneal and subcutaneous adipose tissue measurements as well as prostate and bladder volumes were analyzed by MRI followed by histological evaluation. These parameters were used to draw correlations between MetS and LUTS. RESULTS:Obesity parameters such as BW, WC, and BMI were significantly higher in B6.V-Lepob/J mice compared to C57BL/6N mice (P?<?0.01). Higher levels of total CHO and FFA were noted in B6.V-Lepob/J mice than C57BL/6N mice (P?<?0.05). These results were concurrent with frequency, lower average urine volume and other urinary voiding dysfunctions in B6.V-Lepob/J mice. MRI assessments demonstrate marked increase in body fat and prostate volume in these mice. Compared to C57BL/6N mice, histological analysis of the prostate from B6.V-Lepob/J mice showed increased proliferation, gland crowding, and infiltration of immune cells in the stroma; whereas the bladder urothelium was slightly thicker and appears more proliferative in these mice. The regression and correlation analysis indicate that peritoneal fat (R?=?0.853; P?<?0.02), CHO (R?=?0.729; P?<?0.001), BG (R?=?0.712; P?<?0.001) and prostate volume (R?=?0.706; P?<?0.023) strongly correlate with LUTS whereas BMI, WC, INS, and FFA moderately correlate with the prevalence of bladder dysfunction. CONCLUSION:Our results suggest that LUTS may be attributable in part to obesity and MetS. Validation of an in vivo model may lead to understand the underlying pathophysiological mechanisms of obesity-related LUTS in humans. Prostate 76:964-976, 2016. © 2016 Wiley Periodicals, Inc.

Project description:BACKGROUND: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed among lifestyle, nutritional and metabolic predictors. Thirty-four predictors related to lifestyle, adiposity, body fat distribution, blood lipids and adipocyte sizes have been considered as potential correlates of visceral obesity in women. To properly address the difficulties in managing such interactions given our limited sample of 150 women, bootstrapped Bayesian networks were constructed based on novel constraint-based learning methods that appeared recently in the statistical learning community. Statistical significance of edge strengths was evaluated and the less reliable edges were pruned to increase the network robustness. To allow accessible interpretation and integrate biological knowledge into the final network, several undirected edges were afterwards directed with physiological expertise according to relevant literature. RESULTS: Extensive experiments on synthetic data sampled from a known Bayesian network show that the algorithm, called Recursive Hybrid Parents and Children (RHPC), outperforms state-of-the-art algorithms that appeared in the recent literature. Regarding biological plausibility, we found that the inference results obtained with the proposed method were in excellent agreement with biological knowledge. For example, these analyses indicated that visceral adipose tissue accumulation is strongly related to blood lipid alterations independent of overall obesity level. CONCLUSIONS: Bayesian Networks are a useful tool for investigating and summarizing evidence when complex relationships exist among predictors, in particular, as in the case of multifactorial conditions like visceral obesity, when there is a concurrent incidence for several variables, interacting in a complex manner. The source code and the data sets used for the empirical tests are available at http://www710.univ-lyon1.fr/~aaussem/Software.html.

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Repeated sense of hunger leads to the development of visceral obesity and metabolic syndrome in a mouse model.

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Repeated sense of hunger leads to the development of visceral obesity and metabolic syndrome in a mouse model.

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