Preference or fat? Revisiting opioid effects on food intake
Section snippets
Opioid signaling promotes food intake and alters food preferences
Signaling through central opioid receptors has potent effects on food intake. In sated animals, opioid administration can drive voracious feeding persisting for hours [1]. However, this hyperphagia is not indiscriminate. A fascinating aspect of opioid-induced consumption is its specificity, as opioid effects are typically most potent for highly palatable foods, particularly those that are sweet or fatty (or both) [2], [3], [4]. Studies of rodent models have shown that opioid agonists signaling
Role of opioids in macronutrients selection
Despite considerable progress in characterizing the mechanisms and neural pathways underlying opioid-induced food intake, the role of opioid signaling in determining macronutrient preference – an early area of study – remains unclear. Two principal arguments have been advanced: that opioid signaling increases consumption of preferred foods, independent of macronutrient content [2], [24] or that opioid signaling preferentially increases consumption of fat [25], [26] (More precisely, opioids have
Effects of opioid agonists on diet choice
Table 1 summarizes opioid agonist effects on diet choice. In most experiments, rats either self-selected macronutrient intake through consumption of freely available fat, carbohydrate, and protein rations, or chose between high and low fat food options. (For details of experimental paradigms, see table legend and footnotes). For each experiment, the carbohydrate and fat composition of pre-drug and post-drug intake, as well as the macronutrient composition of the drug-induced change in
Effects of opioid antagonists on diet choice
Opioid antagonist effects (Table 2) were more variable than those produced by agonists in the degree to which drug-induced changes in intake (in this case, decreases in consumption) were expressed through changes in fat intake. In contrast to agonist effects, antagonist-induced changes could rarely be attributed entirely to changes in fat consumption (only 6 of 37 studies for antagonists, compared to 17 of 40 for agonists, 16% vs. 43%). Nonetheless, the prevailing trend in the data was similar
Conclusions and caveats
Comparing data from Table 1, Table 2 suggests an overarching similarity between opioid agonist and antagonist effects. For both agonists and antagonists, fat-selective effects predominate across studies, providing the main evidence in favor of a preferential effect of these manipulations on fat intake. The apparent dose dependence of these effects, in which the drug concentration was directly correlated with specificity for agonists and inversely for antagonists, provides additional support.
Acknowledgements
I gratefully acknowledge Dr. Richard Bodnar and Dr. Rebecca Corwin for their valuable comments on this paper. This work was supported by the Office of the Vice-President for Research at the University of Utah; NARSAD; the March of Dimes; and by the National Institute of Mental Health.
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