Increased adiposity on normal diet, but decreased susceptibility to diet-induced obesity in μ-opioid receptor-deficient mice
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摘要
The mu-opioid receptor encoded by the Oprm1 gene plays a crucial role in the mediation of food reward and drug-induced positive reinforcement, but its genetic deletion has been shown to provide food intake-independent, partial protection from diet-induced obesity. We hypothesized that mu-opioid receptor-deficient mice would show an even greater, intake-dependent, resistance to high-fat diet-induced obesity if the diet comprises a sweet component. We generated an F2 population by crossing the heterozygous offspring of homozygous female Oprm1−/− mice (on a mixed C57BL/6 and BALB/c genetic background) with male inbred C57BL/6 mice. Groups of genotyped wild-type (WT) and homozygous mutant (KO) males and females were fed either control chow or a high caloric palatable diet consisting of sweet, liquid chocolate-flavored Ensure together with a solid high-fat diet. Food intake, body weight, and body composition was measured over a period of 16 weeks. Unexpectedly, male, and to a lesser extent female, KO mice fed chow for the entire period showed progressively increased body weight and adiposity while eating significantly more chow. In contrast, when exposed to the sweet plus high-fat diet, male, and to a lesser extent female, KO mice gained significantly less body weight and fat mass compared to WT mice when using chow fed counterparts for reference values. Male KO mice consumed 33%less of the sweet liquid diet but increased intake of high-fat pellets, so that total calorie intake was not different from WT animals. These results demonstrate a dissociation of the role of μ-opioid receptors in the control of adiposity for different diets and sex. On a bland diet, normal receptor function appears to confer a slightly catabolic predisposition, but on a highly palatable diet, it confers an anabolic metabolic profile, favoring fat accretion. Because of the complexity of μ-opioid gene regulation and tissue distribution, more selective and targeted approaches will be necessary to fully understand the underlying mechanisms.

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