The goal of this project is to characterize the neural and psychological mechanisms that contribute to development of obesity in the early adulthood. We address the neuromolecular risk factors for obesity using multi-modal molecular (positron emission tomography with) and functional (functional magnetic resonance imaging) neuroimaging in a prospective design. Normal weight adolescents with high versus low familial, genetic and psychological risk factors for obesity will be studied and followed for five years.
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.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
60
Using blood oxygenation level dependent (BOLD) echo-planar imaging, fMRI will be used for characterising individual differences in the brain circuits.
\[11C\]carfentanil is used to measure μ-opioid receptor (MOR) availability in brain.
\[18F\]FMPEP-d2 is used to measure cannabinoid receptor type 1 (CB1) availability in brain and body.
Turku PET Centre (Turku University Hospital)
Turku, Finland
Neuromolecular risk score for weight gain
Acquired with combining the measured BMI change in five years to measured alterations in brain function (see below).
Time frame: Within five study years
Localization of on-going neural activity during various cognitive and affective tasks
Acquired with fMRI imaging
Time frame: Within one study day
Brain and body glucose uptake
Acquired with PET imaging
Time frame: Within one study day
Brain and body CB1 availability
Acquired with PET imaging
Time frame: Within one study day
Brain MOR availability
Acquired with PET imaging
Time frame: Within one study day
Genes regulating MOR (OPRM1) and D2R (DRD2) expression
Acquired with whole blood sample and DNA/RNA analysis
Time frame: Within one study week
Genetic risk score from all known obesity-risk genes
Acquired with whole blood sample and DNA/RNA analysis
Time frame: Within one study week
Behavioural patterns involving dysfunctional reward learning and inhibitory control
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
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.
Brain and body insuin stimulated glucose uptake is measured with radioligand \[18F\]-FDG.
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.
Weight, height, blood pressure, medical history, and current medication are determined. Body fat percentage will be assessed using BodPod plethysmograph.
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.
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.
Time frame: Within one study year
Physical activity level
Acquired with Polar M600 GPS Sports Watch that study subjects wear for the measurement period
Time frame: Within one study week
Maximal physical performance
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
Time frame: Within one study day
Physical strength
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)
Time frame: Within one study day
BMI change in five years
Acquired with BMI of the study subjects measured in initial health check-up and once in every study year
Time frame: Within five study years
Body adiposity
Acquired with BodPod device (Frisard, Greenway, \& DeLany, 2005)
Time frame: Within one study day