Characterisation of human metabolism in physiological and pathophysiological states
The aim of this thesis was to describe the relationships between energy expenditure and body composition in healthy adults and children and in patients with metabolic disorders. In a healthy population resting energy expenditure (REE) is highly influenced by body composition, specifically lean mass (LM). Prediction equations can therefore accurately predict REE from body composition in healthy individuals. However, application of these equations to clinical patients, in whom metabolism is disordered, risks miscalculation of energy metabolism due to their dissociation between body composition and energy expenditure. Therefore new prediction equations were derived based on precise body composition measurements in healthy adults and children. Then, in patients with metabolic disorders, differences between their measured and equation-predicted REE and LM were presented as standardised Z scores. REE in healthy adults was predicted by the coefficients: age, fat mass and fat-free mass. LM in healthy adults was predicted by the coefficients: bone mineral content and height2 in men; and by fat and height2 in women. In healthy children, REE was predicted using gender specific models: by fat and LM in boys; and by solely LM in girls. REE and LM were then measured in adult and paediatric patients with metabolic disorders (Lipodystrophy, Thyrotoxicosis and Resistance to Thyroid Hormone β or α), and Z scores were calculated to highlight their deviations from the healthy populations. In adults, thyrotoxicosis patients displayed the highest REE Z scores (5.8), followed by lipodystrophy (2.9) and RTHβ cases (1.8), with RTHα demonstrating the lowest REE Z scores (-2.3). For LM, lipodystrophy patients exhibited with the highest Z scores (4.2), followed by RTHα patients (2.1), with RTHβ patients showing normal LM Z scores (-0.2) and thyrotoxicosis patients presenting with the lowest LM Z scores (-1.2). In the paediatric patients, RTHβ patients demonstrated REE Z scores similar to healthy controls (males; -0.15, females; 0.15), but RTHα patients displayed lower REE Z scores (male; -0.82, female; -2.2) compared to RTHβ patients and healthy controls. These studies highlight the disassociation between REE and body composition in patients with metabolic disorders. The application of a prediction equation for REE to calculate Z scores between measured and predicted values allows quantification of the differences between patients with metabolic disorders and healthy populations, and is a new and important concept.
Resting energy expenditure, Body composition, Metabolic disease
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