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Query: UMLS:C0020505 (hyperphagia)
 6,116 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Epidemiologic studies consistently report associations between obesity and dietary fat but not total energy intake. We measured ad libitum food intake in a laboratory setting and evaluated its relation to body weight and composition, energy expenditure, and macronutrient utilization in 28 women of Pima-Papago heritage (aged 27 +/- 7 y, 85.3 +/- 19.0 kg, 44 +/- 6% body fat; means +/- SD). All women were studied during the follicular phase of the menstrual cycle. After a 4-d weight-maintenance period, the volunteers selected their food for 5 d from computerized vending machines offering a variety of familiar and preferred foods, ie, a "cafeteria diet". Twenty-four-hour energy expenditure and substrate oxidation were measured in a respiratory chamber on the 4th d o weight maintenance and the 5th d of ad libitum intake. Average ad libitum intake was 13,732 +/- 4238 kJ/d (11 +/- 1% protein, 40 +/- 1% fat, 49 +/- 4% carbohydrate), ie, moderate overeating by 27 +/- 37% above weight maintenance requirements (range: -27% to 124%). Percent body fat correlated with daily energy intake (r = 0.53, P < 0.01), the degree of overeating (r = 0.41, P < 0.05), and the selection of a diet higher in fat and lower in carbohydrate (r = 0.70 and r = -0.63, respectively, P < 0.001). Excess carbohydrate intake caused an increase in carbohydrate oxidation (r = 0.51, P < 0.01), whereas excess fat intake resulted in a decrease in fat oxidation (r = -0.53, P < 0.01) and thus a positive fat balance of 85 +/- 65 g/d. The positive relations among degrees of obesity, dietary fat intake and overeating, and the fact that dietary fat does not induce fat oxidation, support the hypothesis that dietary fat promotes obesity in women.
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PMID:Ad libitum food intake on a "cafeteria diet" in Native American women: relations with body composition and 24-h energy expenditure. 757 35

Studies, such as those on Pima Indians, have shown that metabolic factors are involved in the development of obesity and that being overweight is not simply a result of "sloth and gluttony." However, the environment also affects the development of obesity. Among individuals in a given environment, the variability in body size is influenced by genetically determined responses to that environment. People with a low metabolic rate (adjusted for body size and composition) are prone to weight gain, whereas those with a high level of spontaneous physical activity are less likely to become obese. Similarly, individuals with a high 24-hour respiratory quotient (RQ) are more likely to gain weight than those with a low RQ. Insulin sensitivity (not insulin resistance) is another metabolic predictor of obesity. Genetic linkage studies suggest a number of genes are linked to the development of obesity. By sibling-pair linkage analysis, tumor necrosis factor-alpha (TNF-alpha) was found to be linked to the percentage of body fat, and other studies have shown that fat cell production of TNF-alpha is greater in obese individuals.
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PMID:Metabolic differences and the development of obesity. 767 9

In the last years type 2 diabetes has reached almost epidemic proportions. More than 170 million individuals are affected worldwide, about 6 million in Germany. Manifestation of type 2 diabetes is determined by both environmental factors such as lack of physical exercise and overeating and a genetic predisposition. Despite enormous efforts in medical research to identify susceptibility loci and high risk alleles, the genetics of common type 2 diabetes (non-MODY) remain unknown. To date, only a few susceptibility genes have been identified (such as PPARG, KCNJ11, CAPN10). However, replication of initial studies is often difficult. This can be explained by both locus and allelic heterogeneity as well as ethnic differences between different populations. Studies in genetically isolated populations such as the Pima Indians are advantageous to identify susceptibility alleles. Despite some recent advances, it is not possible to predict an individual's risk of type 2 diabetes based on the presence of a certain disease-risk allele.
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PMID:[Genetics of type 2 diabetes]. 1591 30