Metabolic Phenotyping for Personalized Obesity Therapy

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.