Insects as a New Complex Model in Hormonal Basis of Obesity

Abstract

Nowadays, one of the biggest problems in healthcare is an obesity epidemic. Consumption of cheap and low-quality energy-rich diets, low physical activity, and sedentary work favor an increase in the number of obesity cases within many populations/nations. This is a burden on society, public health, and the economy with many deleterious consequences. Thus, studies concerning this disorder are extremely needed, including searching for new, effective, and fitting models. Obesity may be related, among other factors, to disrupting adipocytes activity, disturbance of metabolic homeostasis, dysregulation of hormonal balance, cardiovascular problems, or disorders in nutrition which may lead to death. Because of the high complexity of obesity, it is not easy to find an ideal model for its studies which will be suitable for genetic and physiological analysis including specification of different compounds’ (hormones, neuropeptides) functions, as well as for signaling pathways analysis. In recent times, in search of new models for human diseases there has been more and more attention paid to insects, especially in neuro-endocrine regulation. It seems that this group of animals might also be a new model for human obesity. There are many arguments that insects are a good, multidirectional, and complex model for this disease. For example, insect models can have similar conservative signaling pathways (e.g., JAK-STAT signaling pathway), the presence of similar hormonal axis (e.g., brain–gut axis), or occurrence of structural and functional homologues between neuropeptides (e.g., neuropeptide F and human neuropeptide Y, insulin-like peptides, and human insulin) compared to humans. Here we give a hint to use insects as a model for obesity that can be used in multiple ways: as a source of genetic and peptidomic data about etiology and development correlated with obesity occurrence as well as a model for novel hormonal-based drug activity and their impact on mechanism of disease occurrence.