The generic term “metabolism” is defined as the set of biochemical reactions that take place within the cell. It involves the synthesis and degradation of hundreds of intermediary metabolites by means of catalytic proteins known as enzymes. Metabolic networks are controlled at several levels, but three are very important: (1) energy charge, (2) redox state, and (3) cellular compartments (Liu and Zhang 1985). Energy charge refers to the proportion of adenine nucleotides within the internal milieu. The ratio ATP/AMP drives the regulation of key allosteric proteins to enhance or reduce metabolic fluxes in response to the cellular requirements to grow, differentiate, or adapt to energetic challenges (Atkinson 1968). Redox regulation concerns the regulated transit of electrons that enable the control of the oxidative–catabolic or the reductive–anabolic reactions. It is based on pairs of molecules (redox pairs) that are usually coenzymes: NAD⁺/NADH for degradative processes, NADP⁺/NADPH for synthetic pathways, and GSSG/GSH (oxidized and reduced glutathione) for modulating the redox state of protein-bound thiol groups (Veech 2006). Endomembranes make possible the formation of well-defined organelles such as mitochondria, peroxisomes, endoplasmic reticulum, and others. These intracellular compartments allow the creation of gradients of ions or metabolites that are one of the most important driving forces to control the directionality of the metabolic pathways as well as the state of membrane polarization (Elias 2010).

Most of the time, organisms reach equilibrium between the calories they ingest at mealtime and calories spent during their daily activities. The result is a regulated control of the body mass. However, under certain pathological circumstances this equilibrium is broken, with the concomitant consequence of under- or overweight. Obesity develops when energy intake exceeds energy expenditure. The health problem associated with obesity is not only the increase in fatty deposits in the subcutaneous white adipose tissue, but more importantly, the increases in visceral fat and the fat deposited “ectopically” in organs like the liver, pancreas, heart, or skeletal muscles that tend to cause a pro-inflammatory condition with negative health consequences (Item and Konrad 2012).

Obesity is an organic condition caused by multiple factors including genetic predisposition, altered endocrine signaling, and metabolic abnormalities; however, in order to be expressed, it requires an environmental influence, usually a change in the daily access to calories or performance of physical activity (Faith and Kral 2006).

To gain more understanding regarding the metabolic, physiological, and genetic mechanisms that underlie obesity, several experimental models and approaches have been implemented (reviewed in Kanasaki and Koya 2011). Experimental models of obesity in mice are divided into monogenic and polygenic. Among monogenic mice, the most popular are those with defects in leptin signaling, the ob/ob and db/db mice that lack the gene for leptin or its receptor, respectively. The altered aguti gene/protein (lethal yellow mutant) was the first obesity gene characterized at the molecular level more than 20 years ago. Although monogenic models provide important information about the biology of obesity, human obesity is most likely mediated by multiple genes. Therefore, polygenic models could be much more relevant to human obesity. The New Zealand obese mouse exhibits hyperphagia, reduced energy expenditure, and type 2 diabetes (only in males). The Tsumura Suzuki obese diabetic mouse shows marked hyperglycemia and hyperinsulinemia, and eventually displays lesions similar to diabetic nephropathy and neuropathy. M16 mice exhibit hyperphagia, hyperinsulinemia, and hyperleptinemia. Kuo Kond mice also show type 2 diabetes with a marked insulin resistance preceding the onset of obesity. Neotomodon alstoni is a Mexican mouse that spontaneously develops overweight and obesity when fed with a regular diet for laboratory rodents, especially the females. These mice show modified circadian rhythmicity and altered parameters related to the metabolic syndrome (Carmona-Alcocer et al. 2012).

Three types of rat have been used as experimental models for obesity: Zucker, Wistar fatty, and Otsuka Long Evans Tokushima fatty. All of them show abnormalities in glucose handling and are prone to the diabetogenic condition. Usually, the males are more likely than females to develop more severe anomalies.

Manipulating the dietary input of calories is also a very popular way to produce obese animals in biomedical laboratories. Depending on the rodent strain, a high-fat diet induces overweight and abnormalities similar to human metabolic syndrome. C57BL/6J mice show more severe irregularities than C57BL/KsJ, whereas C57BL/J6 mice, sand mice, and spiny mice exhibit a clear obese phenotype with type 2 diabetes characteristics (Collins et al. 2004). A diet supplemented with sucrose in the drinking water has also been used to produce overweight in rats and is accompanied by metabolic alterations similar to human pathologies (Larqué et al. 2011).

Cancer is defined as an undifferentiated cell population with abnormal metabolism and uncontrolled cell division. The role of onco-proteins and tumor suppressor proteins in proliferative signaling, cell cycle regulation, and altered adhesion is well established. Chemicals, viruses, and radiation are generally accepted as agents that commonly induce mutations in genes encoding these cancer-inducing proteins, thereby giving rise to cancer. More recent evidence indicates the importance of two additional key factors imposed on proliferating cells—hypoxia and/or lack of glucose. These two additional triggers can initiate and promote the process of malignant transformation, when a low percentage of cells escape cellular senescence. Unregulated cell proliferation leads to the formation of cellular masses that extend beyond the resting vasculature, causing oxygen and nutrient deprivation. The resulting hypoxia triggers a number of critical adaptations that enable cancer cell survival. The process of apoptosis is suppressed, and glucose metabolism is altered. Aerobic glycolysis or the Warburg effect links the high rate of glucose fermentation to cancer. Together with glutamine, glycolysis of glucose provides the carbon skeletons, NADPH, and ATP to build new cancer cells that persist in hypoxia, which in turn rewires metabolic pathways for cell growth and survival (Dang 2012). Recent investigations suggest that oxygen depletion stimulates mitochondria to compensate increased reactive oxygen species (ROS). Oxygen depletion activates signaling pathways, such as hypoxia-inducible factor 1, that promote cancer cell survival and tumor growth (Hahn et al. 1999).

There are several approaches to study the biology of cancer in experimental models (reviewed in Zhao et al. 2004): (1) use of established cell lines derived from cancerous organisms; (2) immortalization and transformation using chemical, physical, and viral agents; (3) immortalization and transformation using defined combinations of genetic elements such as oncogenes; (4) immortalization by upregulation of telomere reverse transcriptase, and (5) introduction of SV40 large T antigen with an oncogenic allele of RAS.

There are several examples of how metabolic networks interact with transcriptional programs to regulate circadian functions that have a direct impact on the handling of cellular energy and are affected during states of obesity and cancer (Fig. 14.2).

Obesity is currently a major health problem and is increasing worldwide; its prevalence is mainly a consequence of interactions among multiple genes, physiology, and lifestyle factors. Defined in humans as a body mass index (BMI, weight in kilograms divided by the square of the height in meters) above 30, obesity is currently associated with premature death through increased risk of many chronic diseases, including type 2 diabetes, cardiovascular disease, and cancer (Cheung and Mao 2012). For the past several years, various approaches have been used to identify the physiological and genetic bases of obesity; one of the strongest pieces of evidence involves mechanisms regulating food intake and mediated by hormones and neurotransmitters controlling the sensations of satiety in specific centers within the brain, resulting in chronic energy imbalance such that calories consumed exceed calories expended (Shin et al. 2009). This condition has also been linked to many environments that offer an abundance of calorie-rich foods and few opportunities for physical activities. Recent clinical and laboratory studies suggest that circadian biology also plays an important role in the pathogenesis of obesity, type 2 diabetes, and the metabolic syndrome (Maury et al. 2010).

Circadian rhythms are evolutionarily conserved and represent an adaptation of the organism to its environment; diurnal or nocturnal activity involves behaviors that include feeding–fasting cycles, which are also inputs to the circadian system. The circadian system in mammals is hierarchically organized the hypothalamic suprachiasmatic nucleus (SCN), identified as the dominant circadian pacemaker, imposes period and phase on peripheral oscillators, which are all cells in the body that express “clock genes.” However, internal entrainment requires a tight coordination between neural and humoral inputs, driven directly or indirectly by the SCN. These “peripheral clocks” differ in the manner in which they are reset as well as in the outputs under their control, suggesting that the system must be accurately synchronized (Mohawk et al. 2012; Menaker et al. 2013).

Studies on these peripheral clocks, especially as they affect metabolism, may give us a vision of circadian alignment for internal synchrony in normal physiology as well as in disease. The mechanisms, including this internal circadian synchrony, may include signaling at the transcriptional level, posttranscriptional, and posttranslational regulation of the proteins encoded by clock genes, and epigenetic influences of clock genes on chromatin modifications that affect gene regulation (Green et al. 2008; Bass and Takahashi 2010; Froy 2010; Bass 2012).

In normal conditions the SCN maintains temporal organization of activity, body temperature, and feeding, in such a way that local and systemic circadian signals present a particular alignment. However, when food is provided on a regular basis at a different time, out of the animal’s activity phase, anticipatory locomotor activity prior to the arrival of the meal indicates that the internal timing also depends on the coincidence of different zeitgebers, such as light and food cycles, and that a different alignment of peripheral oscillators occurs (Pezuk et al. 2012 ; Mistlberger 2011).

Unorganized activity–rest and feeding–fasting cycles in humans may cause circadian misalignment, and also may facilitate the occurrence of metabolic disorders (Scheer et al. 2009). In addition, disorders in the sleep–wake cycles are associated with irregular feeding schedules, and may be one of the multiple causes of metabolic disorders (Laposky et al. 2008).

Misalignment of the endogenous circadian phase can occur with forced or artificial non-circadian cycles that do not coincide with retinal light exposure, meal times, and the times of wakefulness/activity, work/school, exercise, and sleep; the main examples are shift work and jet lag (Bass 2012). Circadian disregulation and obesity have an initial behavioral reference; artificial bright-light exposure during the evening and hypercaloric diets consumed at night are signals that may work as “false” zeitgebers in conflict with the natural cycles. Together with reduced physical activity and sleep disorders, such behaviors favor an increase in body weight that, over a number of years, results in obesity and metabolic syndrome.

The link between obesity and clock mechanisms is just beginning to be understood. Studies performed in animal models offer unique and powerful experimental approaches and allow us to understand the underlying mechanisms of metabolic disorders and circadian disruption, as well as to develop therapeutic strategies (Arble et al. 2010). Circadian misalignment in rodents may be illustrated by experiments simulating jet lag, where some tissues are able to re-entrain to jet lag more quickly than others (Yamazaki et al. 2000). Mice with mutations in the circadian Clock gene develop obesity and metabolic syndrome (Turek et al. 2005), and genetic polymorphisms within the core clock genes Clock and Bmal1 are also associated with obesity, hypertension, and type 2 diabetes (Marcheva et al. 2010). On the other hand, just changing the feeding schedule facilitates overweight and obesity in mice. When food access occurs during the rest/fasting phase of the cycle (photophase in nocturnal rodents), a gradual increase of body weight is clearly noted in comparison with the animals that have access only during the night or ad libitum (Arble et al. 2009). In a rat model susceptible to the development of type 2 diabetes (HIP rats), disruption of circadian rhythms accelerates the loss of beta-cell function and the mass characteristic of this condition (Gale et al. 2011). Feeding time determines the targets and phases of rhythmic transcripts in liver. Thus, there is a synergistic interaction between clock and temporarily restricted feeding patterns in many important metabolic genes, including those involved in mitochondrial function. By using a Restricted Feeding protocol, it is possible to cause a completely new phase relationship between the light-entrained (SCN) and a food-entrainable oscillator (FEO). Mice and rats are naturally nocturnal feeders, and limiting food access to the light phase causes some behaviors, such as feeding-dependent hormonal rhythms and the expression of circadian clock genes and clock-controlled genes within metabolic tissues (e.g., the liver), to become entrained to the novel feeding time.

Clock gene expression in the liver is highly correlated with circadian feeding rhythms, while the SCN remains synchronized to light cues (Stokkan et al. 2001 ). This dissociation offers an exciting window through which new insights about the link between circadian disruption and metabolism can be explored. On the other hand, misalignment produced in mice by protocols resembling shift-work protocols may result in metabolic disturbances, such as the loss of glucose rhythmicity, inverted triglyceride rhythm, and an increase in body weight (Yoon et al. 2012).

Besides the timing of feeding, hyperlipidic diets also have an impact on the clock outputs, such as the free running period, amplitude of circadian clock protein oscillations, and phase-shift responses to light (Kohsaka et al. 2007; Mendoza et al. 2011). High-fat diets consumed ad libitum may affect the clock genes, reducing protein transcript levels, hormone receptors that regulate the clock, and clock-controlled genes involved in fuel utilization in the hypothalamus and peripheral tissues (Mendoza et al. 2008, 2011), also affecting the phase relationship between central and peripheral circadian oscillators (Pendergast et al. 2013).

Obese mice often show a less organized circadian activity, with bursts of locomotion more often observed during the rest phase of the cycle, more fragmented sleep, and a reduced amplitude of activity during the night (Laposky et al. 2009; Carmona-Alcocer et al. 2012; Fuentes-Granados et al. 2012). The way in which obesity affects circadian rhythms may also differ between sexes; obese female mice present more acute changes of circadian parameters than those observed in males, in an animal model where obesity occurs in an environment with free access to food but with limited space (Carmona-Alcocer et al. 2012).

The understanding of the mechanisms by which obesity is linked to the circadian clock is in its early stages. Different levels of organization in circadian regulation and metabolism can be observed. At the level of hypothalamic center that regulates feeding, the SCN projects axons to the arcuate nucleus, where the main integration of feeding–fasting cycles takes place (Green et al. 2008). Two main hormones, Ghrelin and Leptin, participate in feeding–fasting behavior through hypothalamic mediators. Ghrelin is an orexigenic hormone from the periphery (released mainly by the oxyntic cells within the stomach) that stimulates food intake and is elevated under conditions of physiological demand such as fasting (Schellekens et al. 2012). Leptin is mainly secreted by adipose tissue, and it is recognized as an endocrine signal related to the satiety process. It signals pro-opiomelanocortin (POMC) neurons in hypothalamus (De Jonghe et al. 2012). Both leptin and ghrelin also exert feedback on the SCN and are endocrine signals that are out of balance in conditions of obesity (Froy 2010).

At the cell level, chemical signals that couple internal clock function to nutrient state involve AMP kinase (AMPK). Stimulation of AMPK leads to degradation of CRY (Lamia et al. 2009), suggesting that AMPK is a key sensor and integrator of hormonal and nutritional signals with neurochemical and neurophysiological responses (Schneeberger and Claret 2012) that affect circadian transcriptional cycles. Glucocorticoids have also been shown to modulate the expression of lipogenic genes (Cho et al. 2012) and REV-ERB-α (Torra et al. 2000), a core clock gene involved together with PPARs in lipolytic metabolic pathways. NAD+ oscillation, redox flux, ATP availability, and mitochondrial function can also participate in tuning the clock by posttranslational modification of transcription factors (Bass 2012). NAD+/NADH+H oscillation regulates a protein deacetylase, Sirtuin 1, recently recognized as a key metabolic sensor in several tissues; it modulates a diversity of cellular processes, including glucose and lipid metabolism, fat mobilization, insulin secretion, sensing of nutrient availability in the hypothalamus, and the activity of the circadian clock in metabolic tissues (Li 2013).

Increasing research leads us to conclude that the relationships between circadian clock genes, central and peripheral oscillators as well as inputs and outputs to the SCN, represent a multifactorial system that must eventually be taken into consideration for treatments of obesity.

In humans, the meal timing as well as the food quality and quantity may be considered key factors contributing to metabolic impairment, seen as circadian disruption from consuming calories during the “wrong” circadian time. Circadian misalignment, such as occurs with jet lag or chronically with shift work, increases postprandial glucose, insulin, and mean arterial pressure, while it decreases leptin and sleep efficiency and completely inverts the cortisol profile across the behavioral cycle (Scheer et al. 2009).

Better planning and control of our environment (sleep cycles, time of eating and exercise, light exposure, etc.) will allow us to reduce the chances of circadian misalignment and may also help reduce the severity of various other diseases (Mikhail 2009).

Cancer is a group of diseases characterized by chronic proliferation of cells having many competetive advantages compared with normal cells. Two models have been proposed to explain the heterogeneous potential of tumor cells and the process of metastasis: (1) the stochastic model, in which a distinct population of cells acquires some somatic mutations and develops metastatic capability, and (2) the hierarchical model, in which primary tumors and metastatic cancer are initiated by occasional stem cells with cancerous properties (Reya et al. 2001; Li et al. 2007).

Hanahan and Weinberg in 2000 proposed to characterize the cancerous process by six hallmarks that constitute a logical framework for understanding the remarkable diversity of neoplasic diseases (Fig. 14.3).