**1. Introduction**

Obesity is a global epidemic and is on the rise at an alarming rate. It is estimated that 2.1 billion people worldwide are either obese or overweight, which is almost 30% of the world's population [1]. This increase in obesity also predisposes individuals to other comorbidities such as cardiovascular disease, type 2 diabetes and metabolic syndrome [2] and therefore is a major public health concern. Obesity has traditionally been thought of as a consequence of a "bad diet" (high energy intake) and/or a sedentary lifestyle (low energy expenditure) resulting in a positive energy balance that manifests itself in the form of energy storage within adipose tissue. While this is true, it is now apparent that this is a simplistic view, and there are many contributing factors that impact energy storage and utilisation. In recent years, signifi-

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

cant advances in the understanding of obesity and metabolism have been made using "omic" technologies. "Omic" techniques involve the detection and identification of molecules within a given biological sample, whether it is derived from cells, a tissue sample or indeed an entire organ or organism. Primarily, omics studies have aimed to identify the genes (genomics), messenger RNA (mRNA) (transcriptomics), proteins (proteomics) and metabolites (metabolomics that encompasses lipids (lipidomics)) of a sample or a group of samples and how they differ from another sample or group. Other omics platforms are also important in the regulation of these pathways including the effect of epigenetics (the epigenome/epigenomics) on the function of genes and the role of the gut microbiota within a host (the microbiome/microbiomics) on metabolite production and energy harvest from food. "Omic" platforms are being utilised by researchers around the world to identify mechanisms that contribute to the development and maintenance of obesity, the evolution of obesity to metabolic diseases such as type 2 diabetes and to try and identify possible therapeutic avenues to treat obesity (**Figure 1**). This chapter focuses on discussing obesity from the level of the genes associated with obesity and their regulation by the epigenome right through to the proteomic, lipidomic and metabolomic level in studies from both human cohorts as well as studies conducted in pre‐clinical models.

**Figure 1.** Flow chart representation of the various "omic" platforms used to study obesity. Further understanding of each of these stages will not only lead to a greater understanding of the pathogenesis of obesity and identification of therapeutic targets, but could potentially be used for prescription of personalized medicine (prevention and treatment). Data such as what is able to be obtained from lipidomic analysis may be utilized in the clinic to evaluate risk and monitor disease severity and provide prognostic information.
