Neuromolecular Risk Factors for Obesity (PROSPECT)

Diet, nutrition, and physical exercise are critical factors in the maintenance of good health through the entire life course. However, in most western countries the annual increase in the prevalence and the severity of obesity and physical inactivity is substantial. Early detection of individuals with high risk for obesity is important, because reversing the obese state is very difficult. To prevent and treat obesity, it is necessary to characterize neural mechanisms supporting altered incentive motivation and food intake, and to build a comprehensive model of the interactions between neural, physiological, and psychological factors contributing to development and maintenance of obesity. This obviously calls for novel data analysis techniques allowing fusion analysis of neurobiological, physiological, and behavioural data, as well as screening the critical combination of biomarkers for obesity.

A total of sixty males (30 normal-weight, 30 with risk for developing obesity) are recruited into this prospective study. The subjects will undergo physical examination, physical fitness tests, physical activity measures, body tissue composition measurement, structural and functional magnetic resonance imaging of the brain and body (MRI \& fMRI), and positron emission tomography (PET) with ligands \[18F\]-fluorodeoxyglucose (\[18F\]-FDG), \[18-F\]FMPEP, and \[11C\]carfentanil. Subjects' weight and physical condition will be followed up for 5 years.

In three interconnected work packages (WPs) we test three hypotheses derived from human and animal studies:

1. Altered reward and cognitive control functions in the brain predisposes some individuals to overeating and obesity.
2. Opioid system and reward circuit function provide feasible biomarkers for obesity risk.
3. Mobile tracking and behavioural paradigms tapping reward learning and inhibitory control can be used for unobtrusive and inexpensive detection of risk factors for obesity.

These studies will improve our understanding of the neural and psychological mechanisms of obesity and addictive disorders. This knowledge will translate into crucial knowledge for developing novel risk factor screening procedures, and novel pharmacological and psychological treatments for obesity.

• fMRI imaging (Diagnostic test): Using blood oxygenation level dependent (BOLD) echo-planar imaging, fMRI will be used for characterising individual differences in the brain circuits.
• [11C]carfentanil PET scan (Diagnostic test): \[11C\]carfentanil is used to measure μ-opioid receptor (MOR) availability in brain.
• [18F]FMPEP-d2 PET scan (Diagnostic test): \[18F\]FMPEP-d2 is used to measure cannabinoid receptor type 1 (CB1) availability in brain and body.
• [18F]-FDG PET scan (Diagnostic test): Brain and body insuin stimulated glucose uptake is measured with radioligand \[18F\]-FDG.
• Physical activity measures and fitness tests (Diagnostic test): Physical activity will be measured over one week following the screening check-up, before the PET measurement days. For the measurement, subjects will wear Polar M600 GPS Sports Watch for the measurement period. The fitness tests will be performed at the Paavo Nurmi Centre.
• Laboratory measurements (Diagnostic test): Weight, height, blood pressure, medical history, and current medication are determined. Body fat percentage will be assessed using BodPod plethysmograph.
• Questionnaires (Diagnostic test): All the participants will complete a self-administered questionnaire at baseline, and at 12 months, for assessment of leisure-time physical activity (LTPA). The following questionnaires will be completed: Behavioural inhibition / activation, Dutch Eating Behaviour Questionnaire, Yale Food Addiction Scale, PCL-Revised, Food craving State / Trait (FCS-FCST) questionnaires, Autism Spectrum Quotient, State-Trait Anxiety Questionnaire and Pain Sensitivity Questionnaire.
• Hyperinsulinemic euglycemic clamp (Diagnostic test): Low-dose hyperinsulinemic euglycemic clamp technique will be used to promote glucose uptake and measure insulin sensitivity of the subjects. In the clamp study subjects are administered intravenous insulin at a steady rate of 0.25 mU/kg/min and normoglycemia is maintained using a variable rate infusion of 20 % glucose based on plasma glucose measurements, which are performed every 5-10 min from arterialized venous blood.

Primary outcomes

• Neuromolecular risk score for weight gain [Within five study years]: Acquired with combining the measured BMI change in five years to measured alterations in brain function (see below).

Secondary outcomes

• Localization of on-going neural activity during various cognitive and affective tasks [Within one study day]: Acquired with fMRI imaging
• Brain and body glucose uptake [Within one study day]: Acquired with PET imaging
• Brain and body CB1 availability [Within one study day]: Acquired with PET imaging
• Brain MOR availability [Within one study day]: Acquired with PET imaging
• Genes regulating MOR (OPRM1) and D2R (DRD2) expression [Within one study week]: Acquired with whole blood sample and DNA/RNA analysis
• Genetic risk score from all known obesity-risk genes [Within one study week]: Acquired with whole blood sample and DNA/RNA analysis
• Behavioural patterns involving dysfunctional reward learning and inhibitory control [Within one study year]: Acquired with following questionnaires: assessment of leisure-time physical activity (LTPA), Behavioural inhibition / activation, Dutch Eating Behaviour Questionnaire, Yale Food Addiction Scale, PCL-Revised, Food craving State / Trait (FCS-FCST) questionnaires, Autism Spectrum Quotient, State-Trait Anxiety Questionnaire, Pain Sensitivity Questionnaire, DASS-21, PSS-10
• Physical activity level [Within one study week]: Acquired with Polar M600 GPS Sports Watch that study subjects wear for the measurement period
• Maximal physical performance [Within one study day]: The subjects will perform a maximal aerobic exercise test on a bicycle ergometer starting at the intensity of 50 W and followed by an increase of 30 W every 2 min until volitional exhaustion. Peak workload will be calculated as an average workload during the last 2 min of the test (weighted average will be used if the final stage is stopped prior the completion) and used as a measure of maximal performance of the subjects
• Physical strength [Within one study day]: Total physical strenght score is calculated from 1) countermovement jump test with a contact mat (flight time measured - jump height calculated), hand grip strength (measured in Newtons), sit-ups (number of repetitions in 30 s), and back extension (reps in 30 s)
• BMI change in five years [Within five study years]: Acquired with BMI of the study subjects measured in initial health check-up and once in every study year
• Body adiposity [Within one study day]: Acquired with BodPod device (Frisard, Greenway, \& DeLany, 2005)

Sex: Male, ages: 20 Years to 35 Years, accepts healthy volunteers

Inclusion Criteria:

Inclusion criteria for low-risk group:

* Male sex
* Age 20-35 years
* BMI 20-24 kg/m2
* Physical exercise > 4 hrs per week
* No maternal / paternal obesity OR maternal / paternal type 2 diabetes mellitus (T2DM)

Inclusion criteria for high-risk group:

* Male sex
* Age 20-35 years
* BMI 25 - 30 kg/m2
* Maternal / paternal obesity OR maternal / paternal T2DM
* Physical exercise < 4 hrs per week

Exclusion Criteria:

* Any chronic disease or medication that could affect glucose metabolism or neurotransmission
* History of anorexia nervosa, bulimia or other eating disorder (excl. common obesity)
* Smoking of tobacco, taking of snuffs, or use of narcotics
* Abusive use of alcohol
* Any other condition that in the opinion of the investigator could create a hazard to the subject safety, endanger the study procedures or interfere with the interpretation of study results

• Frisard MI, Greenway FL, Delany JP. Comparison of methods to assess body composition changes during a period of weight loss. Obes Res. 2005 May;13(5):845-54. doi: 10.1038/oby.2005.97. PMID 15919837

• Pirjo Nuutila, M.D., Ph.D., Principal investigator, Turku PET Centre (Turku University Hospital)