Models use leptin and calculus to count calories

New insights in the mechanisms of weight-loss maintenance: Summary from a Pennington symposium

Obesity is a chronic disease that affects more than 650 million adults worldwide. Obesity not only is a significant health concern on its own, but predisposes to cardiometabolic comorbidities, including coronary heart disease, dyslipidemia, hypertension, type 2 diabetes, and some cancers. Lifestyle interventions effectively promote weight loss of 5% to 10%, and pharmacological and surgical interventions even more, with some novel approved drugs inducing up to an average of 25% weight loss. Yet, maintaining weight loss over the long-term remains extremely challenging, and subsequent weight gain is typical. The mechanisms underlying weight regain remain to be fully elucidated. The purpose of this Pennington Biomedical Scientific Symposium was to review and highlight the complex interplay between the physiological, behavioral, and environmental systems controlling energy intake and expenditure. Each of these contributions were further discussed in the context of weight-loss maintenance, and systems-level viewpoints were highlighted to interpret gaps in current approaches. The invited speakers built upon the science of obesity and weight loss to collectively propose future research directions that will aid in revealing the complicated mechanisms involved in the weight-reduced state.

Dynamic interplay among homeostatic, hedonic, and cognitive feedback circuits regulating body weight

Obesity is associated with a prolonged imbalance between energy intake and expenditure, both of which are regulated by multiple feedback processes within and across individuals. These processes constitute 3 hierarchical control systems-homeostatic, hedonic, and cognitive-with extensive interaction among them. Understanding complex eating behavior requires consideration of all 3 systems and their interactions. Existing models of these processes are widely scattered, with relatively few attempts to integrate across mechanisms. We briefly review available empirical evidence and dynamic models, discussing challenges and potential for better integration. We conclude that developing richer models of dynamic interplay among systems should be a priority in the future study of obesity and that systems science modeling offers the potential to aid in this goal.

Misconceptions in body weight regulation: implications for the obesity pandemic

Energy is a concept of universal importance. In applying it to body weight regulation, the focus has been on energy balance and how this balance is affected by intakes and expenditures. However, energy is an abstract concept without biological equivalent and applying it to explain body weight regulation has led to various misconceptions and created intellectual obstacles in understanding the obesity problem. When nutrient and substrate interactions are considered, instead, a number of important issues pertaining to body weight regulation and to the obesity epidemic can be much more pertinently addressed.

Metabolism of mice and men: mathematical modeling of body weight dynamics

PURPOSE OF REVIEW

Dynamic interrelationships between food intake, energy expenditure, energy partitioning, and metabolic fuel selection underlie changes in body weight and composition. A quantitative understanding of these interrelationships is becoming increasingly important given the rise of the worldwide obesity epidemic and the widespread interest in weight management. This review describes how mathematical models offer a quantitative framework for integrating dynamic physiological and behavioral data underlying body weight dynamics in both humans and mice.

RECENT FINDINGS

Mathematical models have provided important insights regarding the drivers of the obesity epidemic, how metabolism adapts to different diets, the predicted magnitude and variability of weight change, and why mouse models have obesity phenotypes. Because mathematical models are constrained by conservation laws, they can also be used to infer physiological variables that are difficult to measure directly.

SUMMARY

Mathematical models can help improve our understanding of the dynamic energy and macronutrient imbalances that give rise to changes in body weight and composition over time. The model development process can also highlight important knowledge gaps and model simulations can help design and predict the results of key new experiments to fill those gaps.

Predicting changes of body weight, body fat, energy expenditure and metabolic fuel selection in C57BL/6 mice

The mouse is an important model organism for investigating the molecular mechanisms of body weight regulation, but a quantitative understanding of mouse energy metabolism remains lacking. Therefore, we created a mathematical model of mouse energy metabolism to predict dynamic changes of body weight, body fat, energy expenditure, and metabolic fuel selection. Based on the principle of energy balance, we constructed ordinary differential equations representing the dynamics of body fat mass (FM) and fat-free mass (FFM) as a function of dietary intake and energy expenditure (EE). The EE model included the cost of tissue deposition, physical activity, diet-induced thermogenesis, and the influence of FM and FFM on metabolic rate. The model was calibrated using previously published data and validated by comparing its predictions to measurements in five groups of male C57/BL6 mice (N = 30) provided ad libitum access to either chow or high fat diets for varying time periods. The mathematical model accurately predicted the observed body weight and FM changes. Physical activity was predicted to decrease immediately upon switching from the chow to the high fat diet and the model coefficients relating EE to FM and FFM agreed with previous independent estimates. Metabolic fuel selection was predicted to depend on a complex interplay between diet composition, the degree of energy imbalance, and body composition. This is the first validated mathematical model of mouse energy metabolism and it provides a quantitative framework for investigating energy balance relationships in mouse models of obesity and diabetes.

Is there evidence for a set point that regulates human body weight?

There is evidence for the idea that there is biological (active) control of body weight at a given set point. Body weight is the product of genetic effects (DNA), epigenetic effects (heritable traits that do not involve changes in DNA), and the environment. Regulation of body weight is asymmetric, being more effective in response to weight loss than to weight gain. However, regulation may be lost or camouflaged by Western diets, suggesting that the failure of biological control is due mainly to external factors. In this situation, the body’s ‘set point’ (i.e., a constant ‘body-inherent’ weight regulated by a proportional feedback control system) is replaced by various ‘settling points’ that are influenced by energy and macronutrient intake in order for the body to achieve a zero energy balance. In a world of abundance, a prudent lifestyle and thus cognitive control are preconditions of effective biological control and a stable body weight. This idea also impacts future genetic research on body weight regulation. Searching for the genetic background of excess weight gain in a world of abundance is misleading since the possible biological control is widely overshadowed by the effect of the environment. In regard to clinical practice, dietary approaches to both weight loss and weight gain have to be reconsidered. In underweight patients (e.g., patients with anorexia nervosa), weight gain is supported by biological mechanisms that may or may not be suppressed by hyperalimentation. To overcome weight loss-induced counter-regulation in the overweight, biological signals have to be taken into account. Computational modeling of weight changes based on metabolic flux and its regulation will provide future strategies for clinical nutrition.

Genetic studies of common types of obesity: a critique of the current use of phenotypes

Recent research into the genetic basis of obesity has focused upon the study of candidate genes, both functional and positional, of genes underlying weight-related Mendelian disorders and of susceptibility loci identified in genome-wide association studies. Three large genome-wide association studies on obesity, together involving more than 150,000 individuals, were published in Nature Genetics last year. The results suggested the involvement of a large number of genetic variants in disease susceptibility. Most genetic effects upon body weight are likely to become obscured by the use of inappropriate phenotypes. In particular, clinical categories such as the body mass index and Metabolic Syndrome do not provide sufficient etiological information for them to be used sensibly in genetic studies on obesity or obesity-related disease. Alleviation of this situation will not come from new genomic research tools, sophisticated statistical algorithms or ever larger sample sizes. Instead, the above notions argue in favour of so-called 'deep phenotyping'.