A recent study published in Molecular Psychiatry suggests a new way to understand the relationship between body fat and the brain chemical dopamine. The findings indicate that individuals with higher adiposity may not have fewer dopamine receptors, as a long-standing theory proposed, but rather higher baseline levels of dopamine in a key reward region of the brain. This work could reframe scientific understanding of the neurobiology associated with body weight regulation.
Dopamine is a brain chemical that helps regulate motivation, reward, and learning. For decades, researchers have studied whether people with obesity have differences in dopamine signaling, particularly in the striatum, a key part of the brain’s reward system.
A landmark 2001 study using positron emission tomography, or PET, found that individuals with obesity appeared to have lower availability of dopamine D2 receptors in the brain. This was widely interpreted as evidence that people with obesity might be less responsive to rewards and might overeat to compensate.
This concept, often called the “reward deficiency” hypothesis, suggested that people with obesity might have a dampened dopamine system, similar in some ways to individuals with substance use disorders. This could theoretically drive them to overeat to compensate for a weaker reward signal.
However, the scientific literature has been filled with conflicting reports. Some human studies supported the original finding of a negative association, while others found a positive link, and still others reported no association at all. These discrepancies may be a result of variations in experimental design, such as whether participants were fasted or fed before brain scans, and the use of different chemical tracers for imaging.
To address this ambiguity, a team of researchers at the National Institutes of Health, led by senior author Kevin D. Hall, designed a highly controlled study. Hall, a leading researcher in nutrition and metabolism, has been involved in many prominent studies on diet and weight regulation. He and his collaborators designed the experiment to eliminate many of the confounding variables that may have affected earlier research.
Their primary goal was to measure dopamine receptor availability in the same individuals under standardized conditions using two different imaging tools. This approach was intended to help disentangle the factors that may have contributed to previous inconsistent findings.
The research team recruited 54 adults spanning a wide range of body mass indexes, from 20 to 44. Participants were admitted to an inpatient clinical center for several days, a step that allowed for precise control over their environment and diet. This inpatient setting allowed the scientists to ensure all participants consumed a standardized, weight-stabilizing diet for several days leading up to their brain scans, removing diet as a potential confounding variable.
On separate days, each participant underwent two positron emission tomography, or PET, scans. PET scans use radioactive tracers that bind to specific targets in the brain, allowing scientists to visualize and quantify them. The team used two different tracers that both bind to dopamine type-2 receptors, but they do so with different properties.
One tracer, [11C]raclopride, has a relatively low affinity for dopamine receptors, meaning it is more easily displaced by the brain’s own naturally occurring dopamine. Its signal is sensitive not only to the number of available receptors but also to the amount of ambient dopamine competing for those same binding sites. The other tracer, [18F]fallypride, binds more tightly, making its signal less influenced by ambient dopamine levels and more reflective of the sheer number of available receptors.
When using [11C]raclopride, the researchers observed a negative linear relationship between body mass index and receptor binding potential. In other words, as a person’s body fat increased, the amount of the tracer that could bind in the brain’s striatum decreased. This result was consistent with the original studies that gave rise to the reward deficiency hypothesis.
In the same participants, however, the scans using the higher-affinity [18F]fallypride tracer showed no significant relationship between body mass index and receptor binding potential. The quantity of available receptors did not appear to change systematically with body fat. The correlation coefficients from the two different scans were statistically different from one another.
The difference between the two scans provides a key insight into the underlying neurochemistry. Because the number of receptors seemed stable, as suggested by the [18F]fallypride results, the researchers inferred that the reduced binding of [11C]raclopride in individuals with higher body fat was likely caused by greater competition from their own dopamine. This suggests that adiposity is associated with higher baseline, or tonic, levels of dopamine.
To explore this further, the team created a statistical index to estimate this dopamine tone by comparing the results from the two tracers for each individual. This index showed a positive association with body mass index, lending support to their interpretation. The relationship was particularly evident in the dorsal striatum, a part of the reward circuit involved in habit formation.
These results suggest that people with more body fat tend to have greater dopamine tone in brain regions associated with reward. That finding could help explain some behaviors observed in obesity, such as increased motivation for food or other rewards.
Past theories often emphasized a dopamine deficit model, in which lower receptor availability made individuals less sensitive to rewards. The current study supports a different view. Higher dopamine tone might actually make reward-related stimuli more salient or harder to resist.
However, the study’s design is cross-sectional, which means it captures a single moment in time and cannot establish causality. It is not possible to determine whether increased adiposity leads to heightened dopamine tone or if elevated dopamine tone might contribute to weight gain over time. Additionally, the measurement of dopamine tone was an inference derived from the PET scan data, not a direct quantification of the chemical itself.
Future research could investigate the mechanisms behind this association and explore whether changes in diet or weight can alter dopamine tone over time. The findings open new avenues for understanding how the brain’s reward system interacts with metabolism and body weight regulation, potentially moving the field beyond the simple model of receptor deficiency.
While the study advances understanding of the brain’s role in obesity, it arrives at a time of concern for scientific independence. The study’s senior author, Kevin D. Hall, has taken early retirement from his position at the National Institutes of Health.
He stated his departure was driven by multiple instances where he felt his work was being censored by federal officials. Hall described an incident in which he was barred from speaking freely with reporters about a study whose results might have been seen as contradicting Health and Human Services Secretary Robert F. Kennedy Jr.’s stance on food addiction.
“We experienced what amounts to censorship and controlling of the reporting of our science,” Hall said in an interview. He also noted that routine approvals for his work were being elevated to political appointees, and he expressed concern that this oversight might eventually interfere with the design and execution of his studies. His departure has been called a significant setback for nutrition research by outside health experts.
The study, “Striatal dopamine tone is positively associated with adiposity in humans as determined by PET using dual dopamine type-2 receptor antagonist tracers,” was authored by Valerie L. Darcey, Juen Guo, Meible Chi, Stephanie T. Chung, Amber B. Courville, Isabelle Gallagher, Peter Herscovitch, Rebecca Howard, Melissa La Noire, Lauren Milley, Alex Schick, Michael Stagliano, Sara Turner, Nicholas Urbanski, Shanna Yang, Eunha Yim, Nan Zhai, Megan S. Zhou, and Kevin D. Hall.
