This study is a prospective, single-center, longitudinal cohort trial designed to unravel
the metabolic heterogeneity among morbidly obese individuals and to develop a clinically
feasible method for metabolic phenotyping. The aim is to identify distinct metabolic
responses to a controlled fasting period that may predict weight loss outcomes and guide
personalized obesity therapy.
Potential participants are morbidly obese patients (BMI >40 kg/m²) already enrolled in a
multimodal obesity therapy program at the University Hospital Schleswig-Holstein, Campus
Kiel. The screening process includes a thorough medical history, physical examination,
and laboratory testing to exclude confounding conditions that might affect energy
expenditure or the interpretation of metabolic measurements.
In the baseline phase, enrolled subjects undergo extensive assessments to characterize
their metabolic status. Body composition is evaluated using several complementary
techniques: bioimpedance analysis (BIA), quantitative magnetic resonance imaging (qMR),
and air displacement plethysmography (BodPod). These methods provide detailed insights
into fat mass, lean mass, and overall body composition. Resting metabolic rate (RMR) is
measured using indirect calorimetry, with subjects placed under a canopy
(haubenkalorimeter) that records oxygen consumption and carbon dioxide production to
yield precise energy expenditure data.
A critical component of the study is the evaluation of RMR before and after an extended
fasting period. Initially, RMR is measured following a 12-hour overnight fast.
Participants then complete a 24-hour fasting period, during which continuous
monitoring-via devices such as a continuous glucose monitor-ensures compliance with the
fasting protocol. A second RMR measurement is taken after the fasting period, and the
percentage change in RMR is calculated. Based on previous research, a significant RMR
reduction (≥5.7%) classifies a subject as having a "thrifty" metabolic phenotype, while a
minimal reduction or slight increase (≥+3.8%) indicates a "spendthrift" phenotype.
Subjects with intermediate changes are not categorized for the primary analysis.
Following the fasting assessments, participants undergo a low-protein meal test. They
consume a standardized chocolate beverage calibrated to provide 50% of their baseline RMR
in caloric content. Postprandial RMR is then measured at several intervals over a
three-hour period to assess the thermic effect of food and the energy cost associated
with digestion. This test helps to elucidate differences in nutrient oxidation and
metabolic flexibility between the two phenotypes.
After completing the baseline phase, subjects enter a 12-week very-low-calorie diet
(VLCD) phase. During this period, they consume approximately 800 kcal per day through
nutritionally complete formula meals that are designed to maintain a balanced
macronutrient profile despite severe caloric restriction. Weight, body composition, and
metabolic parameters are monitored on a weekly basis to capture the effects of the
dietary intervention. The hypothesis is that individuals with a "thrifty" metabolic
response may lose less weight compared to those with a "spendthrift" response, owing to
their reduced energy expenditure during fasting.
Following the VLCD phase, patients transition into a 12-week weight maintenance phase. In
this period, the focus shifts to sustaining weight loss and monitoring long-term
metabolic changes. RMR, body composition, and dietary intake continue to be assessed
periodically. Participants also use an activity tracker to document daily physical
activity, ensuring that variations in energy expenditure are accounted for in the
analysis.
An innovative aspect of this study is the incorporation of metabolomic analysis to
identify potential biomarkers linked to the metabolic phenotypes. Biological
samples-including blood, urine, and saliva-are collected at various time points
throughout the study. These samples undergo metabolomic profiling using advanced
techniques such as liquid chromatography-mass spectrometry (LC/MS) and nuclear magnetic
resonance (NMR) spectroscopy. The goal is to identify specific metabolites or
patterns-such as variations in leptin, fibroblast growth factor 21 (FGF21), and
catecholamines-that correlate with the magnitude of RMR change during fasting. This
analysis may reveal novel biomarkers that predict weight loss responsiveness and
metabolic health.
Data collection extends beyond metabolic measurements. Participants complete visual
analog scales (VAS) to assess subjective feelings of hunger and satiety, providing
insights into the behavioral dimensions of appetite regulation. In addition, continuous
glucose monitoring and measurements of beta-hydroxybutyrate levels are used to verify
fasting compliance and to ensure the accuracy of the metabolic assessments.
The study is managed by a multidisciplinary team led by Dr. Tim Hollstein, with
contributions from specialists in endocrinology, diabetology, clinical nutrition, and
metabolomics. Collaborations with experts from associated institutions enhance the
methodological rigor and analytical capacity of the trial. Statistical power
calculations, based on prior studies, indicate that approximately 20 subjects (10 per
extreme phenotype group) are required to detect significant differences in weight loss
outcomes. To accommodate variability and potential dropouts, an initial screening of
around 80 individuals is planned.
Safety and compliance are paramount. The protocol includes rigorous monitoring for
adverse events related to fasting, blood sampling, and the use of continuous monitoring
devices. Subjects who do not meet fasting criteria-confirmed via continuous glucose
readings or ketone measurements-are excluded from the primary analysis but continue to
receive standard obesity therapy.
Ultimately, the study seeks to bridge the gap between complex laboratory-based
measurements and practical clinical applications. By establishing a reliable and
straightforward method for metabolic phenotyping, it aims to enable personalized obesity
treatments that are tailored to an individual's unique metabolic profile. This approach
could revolutionize obesity management by providing clinicians with predictive tools to
optimize weight loss interventions and improve long-term metabolic outcomes.
