From Brain Waves to Behavior Change: Neuromarkers to Personalize Obesity Interventions

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Introduction

This summary outlines the research presented by Dr. Francesco Versace, a Professor in the Behavioral Science Department at MD Anderson Cancer Center. His work focuses on the psychophysiological underpinnings of smoking and obesity, two significant causes of preventable disease and disability in the United States.

Dr. Versace’s research aims to develop more effective and personalized treatments for these conditions by understanding the shared neurobiological mechanisms underlying reward-seeking behaviors like excessive eating and smoking.

Challenging the Common Premise in Obesity Research

A common assumption in obesity research is that individuals with obesity consistently exhibit high reactivity to food-related cues. This perspective suggests that intense brain responses to food cues trigger craving, leading to compulsive eating. This idea is supported by the Incentive Sensitization Theory, originally from addiction research and extended to obesity. This theory posits that stimuli promoting survival (e.g., food) hold "incentive salience," attracting attention and directing behavior. Through Pavlovian conditioning, cues associated with these rewards (e.g., banana leaves, fast-food logos) can also acquire incentive salience, becoming attractive enough to drive behavior even in the absence of the reward itself.

Measuring Brain Responses to Cues

Dr. Versace's laboratory uses electroencephalography (EEG) to measure cortical brain activity as participants view images. By analyzing Event-Related Potentials (ERPs), specifically the Late Positive Potential (LPP), researchers can assess the motivational relevance of stimuli. A higher LPP amplitude indicates greater stimulus relevance.

Initially, studies presenting food-related cues alongside neutral and emotional stimuli (pleasant, unpleasant, high and low arousal) revealed a surprising finding: food cues, on average, were processed as low-arousing stimuli, like moderately arousing emotional content, in both lean and obese individuals. This seemingly contradicted the premise of high cue reactivity in obesity and highlighted the need to investigate individual differences.

Individual Differences: Lessons from Animal Models (Sign Tracking vs. Goal Tracking)

Dr. Versace drew inspiration from animal models, which demonstrate significant individual differences in how incentive salience is attributed to cues that precede rewards. Studies with rats in Pavlovian conditioning paradigms identified two distinct behavioral profiles:

• Sign Trackers: These animals learn the association between a cue (e.g., a lever) and a reward (e.g., food) but then increasingly interact with the cue itself, as if the cue has become the primary attraction. Dopamine release studies show that sign trackers progressively lose their dopamine response to the food reward, instead increasing or maintaining their dopamine response to the cue, indicating the cue has acquired incentive salience.
• Goal Trackers: These animals also learn the cue-reward association but primarily focus on where the reward will be delivered, waiting for it on the other side of the cage. They do not attribute significant incentive salience to the cue itself.

Importantly, these differences predict vulnerability to cue-induced behaviors, including drug self-administration, where sign trackers show increased drug use when cues are present. This led Dr. Versace to hypothesize that similar individual differences might exist in humans and predict maladaptive eating behaviors.

Identifying Sign Trackers and Goal Trackers in Humans

To investigate this in humans, Dr. Versace developed an innovative "candy delivery machine" paradigm. Participants viewed images, and after one second of a food-related picture being presented, a candy was delivered. The LPP amplitude in response to the pictures was measured.

Key findings from this "candy task" included:

• When food cues predicted the delivery of a reward (candy), the LPP reactivity was on par with or even higher than the highest arousing emotional images.
• Conversely, food images that did not predict a reward were processed as low-arousing stimuli, like initial findings.

To identify individual differences, cluster analysis was employed, a data-driven approach that groups subjects based on common patterns of reactivity. This analysis revealed two distinct groups in humans, analogous to the animal sign and goal trackers:

• Human Sign Trackers: For these individuals, food-related cues are the most motivationally relevant stimuli shown, eliciting the highest LPP amplitudes.
• Human Goal Trackers: These individuals process the cues as only moderately arousing, showing significantly lower LPP amplitudes to the cues.

Crucially, these brain reactivity differences were linked to behavior: sign trackers consumed more than twice as many candies as goal trackers in the experiment.

Further re-analysis of previous data (where food cues did not predict a reward) also replicated these two groups. This re-analysis revealed a critical link to obesity: 70% of individuals identified as sign trackers had obesity, whereas goal trackers showed an equal distribution of lean and obese individuals. This suggests that the tendency to attribute incentive salience to food-related cues is a significant risk factor for developing obesity, as it increases vulnerability to compulsive cue-induced behaviors. These findings have also been replicated with a control condition (predicting a non-food bead) and extend to other domains, such as smoking cessation, where sign-tracking smokers relapsed significantly more often than goal-tracking smokers.

Clinical Implications and Future Directions

The ability to identify these individual differences through neuromarkers holds significant clinical promise for personalizing treatment for obesity and other reward-seeking disorders.

Current and future work includes:

• Developing Patient Classifiers: Researchers are working on Bayesian classifiers to identify a person as a sign tracker or goal tracker on an individual basis, allowing for real-time stratification into appropriate treatments. A classifier for smoking is already in use in a clinical trial, and one for food cues is under development.
• Targeting Brain Reactivity with Transcranial Magnetic Stimulation (TMS): TMS is a non-invasive neuromodulation technique already FDA-approved for conditions like depression, smoking, and obsessive-compulsive disorders. Dr. Versace's team is exploring two primary targets for TMS to address high cue reactivity in sign trackers:
  • Ventromedial Prefrontal Cortex: Stimulating this area with an inhibitory protocol (continuous theta burst stimulation - cTBS) aims to reduce the heightened reactivity to cues.
  • Dorsolateral Prefrontal Cortex: Stimulating this area with an excitatory protocol (intermittent theta burst stimulation - iTBS) aims to increase cognitive control over cravings.
  • A feasibility trial funded by the Houston Nutrition Obesity Research Center (HNORC) is currently collecting data on these TMS protocols.
• Predicting Weight Regain After Bariatric Surgery: In collaboration with Dr. Matar, a grant proposal is being developed to use these two neural profiles to predict vulnerability to weight regain in patients undergoing bariatric surgery. The hypothesis is that sign trackers are more likely to plateau early and regain weight, suggesting a need for early, targeted interventions like TMS to reduce their vulnerability to maladaptive eating. This also extends to considering the impact of GLP1 receptor agonist use and the variability in weight regain after cessation.
• Improving TMS Targeting: Collaboration with Dr. Bartis involves using intracranial recordings in patients to better identify the brain areas activated during the neurobehavioral task in sign and goal trackers, with the goal of improving the precision of TMS targeting.
• Genetic Association Studies: With a larger sample of smokers, Dr. Versace and Dr. Kiproaki are conducting genetic association studies, including calculating polygenic risk scores, with exciting preliminary results.

Important Considerations

• Appetite Control: While appetite is controlled for using visual analogue scales before sessions, a formal feeding study has not been conducted. The results, however, remain consistent when controlling for appetite.
• LPP Specificity: The LPP is a measure of motivational relevance and does not distinguish between positive and negative valence (pleasant vs. unpleasant).
• Robustness of Effect: The LPP differences between emotional and neutral stimuli, and between sign and goal trackers, remain robust even after hundreds of repetitions of the same pictures over multiple sessions.
• Frequency Analysis: Research is ongoing into differences in brain activity in the theta band of the EEG, which may represent another biomarker related to decision-making, though these findings require replication.

In conclusion, Dr. Versace’s research demonstrates that humans exhibit significant individual differences in how they attribute incentive salience to cues, a trait that predicts vulnerability to maladaptive cue-induced behaviors and is clinically relevant for obesity. These neuromarkers provide a basis for developing personalized and more effective treatments for challenging conditions like obesity and addiction.

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