Introduction
Circadian rhythms are cyclical endogenous processes that occur with a periodicity of approximately 24 h. They are found throughout the natural world, from simple unicellular organisms through to human beings( Reference Pittendrigh 1 ). Possession of such rhythms enables organisms to anticipate predictable changes in the environment and thus adapt their physiology accordingly. Temporal control over metabolic processes also allows cells and organisms to separate opposing biochemical pathways, for example, redox reactions and anabolism v. catabolism. Moreover, in model species, it has been demonstrated that possession of circadian rhythms that synchronise to environmental changes confers a selective advantage( Reference Ouyang, Andersson and Kondo 2 ).
A great deal of current research is being undertaken at the interface between the circadian timing system, metabolic physiology and nutritional science. Studying how these major biomedical areas inter-relate will not only increase our understanding of healthy metabolism, but may also guide the development of nutritional interventions for body-weight regulation, the management of obesity-related disease and the treatment of circadian disorders associated with shift work, jet-lag, abnormal sleep phase and blindness.
The mammalian circadian timing system
It was recognised over 40 years ago that a small brain region within the anterior hypothalamus, the suprachiasmatic nuclei (SCN), is important for the expression of circadian rhythms in mammals( Reference Moore and Eichler 3 , Reference Stephan and Zucker 4 ). When the SCN are isolated from surrounding brain tissue in vivo, or maintained as tissue explants in vitro, their neurones maintain robust rhythmicity( Reference Inouye and Kawamura 5 – Reference Groos and Hendriks 7 ). Furthermore, if SCN tissue from one animal is transplanted to another animal that has had its SCN lesioned, the resulting behavioural rhythms reflect that of the donor animal, not the host( Reference Ralph, Foster and Davis 8 ). It is therefore clear that the SCN play a key role in the generation of mammalian circadian rhythms.
Mammalian clocks outside the SCN, termed ‘peripheral clocks’, were first identified in tissues such as the retina, which exhibits rhythmic hormone secretion when maintained in culture( Reference Tosini and Menaker 9 ). Following the cloning of genetic components of the mammalian clock came the discovery of rhythmic clock gene expression in peripheral tissues( Reference Sakamoto, Nagase and Fukui 10 , Reference Zylka, Shearman and Weaver 11 ). Subsequent advances came from the use of transgenic animals in which reporter gene expression is driven by clock gene elements. Real-time imaging of tissue explants taken from these animals confirmed that many peripheral tissues possess an endogenous clock( Reference Yamazaki, Numano and Abe 12 , Reference Yoo, Yamazaki and Lowrey 13 ). Perhaps most surprisingly, circadian rhythms have also been identified in cultures of immortalised cells( Reference Balsalobre, Damiola and Schibler 14 – Reference Welsh, Yoo and Liu 16 ).
In animal models, rhythmic clock gene expression is known to occur in multiple tissues involved in metabolism and nutritional physiology, including the liver, pancreas, gastrointestinal tract, adipose tissue and skeletal muscle( Reference Albrecht 17 , Reference Cagampang and Bruce 18 ). For ethical and technical reasons, molecular analysis of human tissues is difficult and various strategies have been adopted to study human clock gene expression( Reference Johnston 19 ). However, clock gene rhythms have now successfully been observed in human leucocytes( Reference Boivin, James and Wu 20 , Reference Archer, Viola and Kyriakopoulou 21 ), fibroblasts( Reference Brown, Fleury-Olela and Nagoshi 22 , Reference Hasan, Santhi and Lazar 23 ) and adipose tissue( Reference Gomez-Santos, Gomez-Abellan and Madrid 24 , Reference Otway, Mantele and Bretschneider 25 ), with single time point analysis of clock gene expression in other tissues, including pancreatic islets( Reference Stamenkovic, Olsson and Nagorny 26 ).
The presence of rhythms throughout the body requires appropriate physiological mechanisms to keep tissues correctly synchronised to one another. The SCN receive photic information directly from the retina and are readily synchronised to the external light–dark cycle( Reference Schmidt, Do and Dacey 27 ). In normal circumstances, the clock in the SCN then synchronises rhythms elsewhere in the body through a variety of output pathways( Reference Dibner and Schibler 28 ). A commonly used analogy to describe this organisation refers to the SCN as a conductor of an orchestra, with the peripheral tissues representing individual musicians; each of the ‘musicians’ is capable of generating its own time but requires the central ‘conductor’ to ensure that they all maintain correct time relative to each other and thus optimal overall output.
There are many ways through which the SCN can synchronise peripheral tissues. These include endocrine and neuronal pathways, such as the secretion of glucocorticoids and the tone of the autonomic nervous system( Reference Dibner and Schibler 28 ). In addition, by influencing the timing of sleep–wake rhythms, the SCN also dictate the timing of certain behaviours, for example, feeding, which are thought to be critical to the rhythms in peripheral tissues as explained below.
Metabolic functions of circadian timing and specific roles of peripheral clocks
Since the identification of clocks in peripheral tissues, a critical challenge has been to identify their physiological role. An early indication that peripheral clocks had a strong influence on metabolism came from transcriptomic analyses. Depending on the analytical methods used, these studies estimated that up to 20 % of the transcriptome in peripheral tissues exhibits 24 h variation( Reference Akhtar, Reddy and Maywood 29 – Reference Zvonic, Ptitsyn and Conrad 33 ). Identification of the rhythmic transcripts revealed a large cluster of genes encoding proteins involved in metabolic pathways. Later proteomic analysis also suggested that up to 20 % of proteins in the mouse liver oscillate with a circadian rhythm, and many of these proteins are indeed involved in important metabolic functions( Reference Reddy, Karp and Maywood 34 ). Technical advances have since permitted direct analysis of the daily metabolome in different tissues. Similar to the transcriptomic and proteomic data, both mouse( Reference Minami, Kasukawa and Kakazu 35 – Reference Fustin, Doi and Yamada 37 ) and human( Reference Dallmann, Viola and Tarokh 38 – Reference Kasukawa, Sugimoto and Hida 40 ) studies estimate that up to 20 % of the metabolome is under 24 h regulation.
Genetic evidence for a role of circadian clocks in key metabolic processes is now substantial. As discussed previously( Reference Johnston, Frost and Otway 41 ), the precise nature of metabolic abnormality in transgenic animals depends upon their genetic background. Nonetheless the dysregulation of key metabolic processes, including glucose and lipid homeostasis, following disruption of key genes involved in circadian biology reveals fundamental links between circadian genetics and metabolism( Reference Raspe, Duez and Mansen 42 – Reference Cho, Zhao and Hatori 47 ). Consistent with these animal data, a number of groups have now reported correlations between aspects of human metabolism and clock gene polymorphisms( Reference Woon, Kaisaki and Braganca 48 – Reference Garaulet and Esteban Tardido 53 ).
One limitation of studies involving individuals with ‘whole body’ genetic changes is that they do not clearly indicate the contribution of individual tissue rhythms to whole-organism physiology. Using the Cre-Lox recombinase system to disrupt the Bmal1 (brain and muscle arnt-like protein-1) gene in a tissue-specific manner, circadian rhythms in the liver, pancreas and white adipose tissue have been selectively ‘knocked out’ allowing the in vivo role of their clocks to be investigated. Mice bearing a liver-specific clock disruption exhibit increased glucose clearance following acute challenge, fasting hypoglycaemia and other features suggesting that the hepatic clock regulates glucose export into the blood( Reference Lamia, Storch and Weitz 54 ). By contrast, disruption of the pancreatic clock results in hyperglycaemia, reduced glucose tolerance and impaired insulin secretion( Reference Marcheva, Ramsey and Buhr 55 , Reference Sadacca, Lamia and deLemos 56 ). Finally, knock-out of Bmal1 in white adipose tissue induces obesity; a contributory mechanism to this phenotype is the temporal modification of PUFA signalling from adipocytes to appetite-regulatory regions of the hypothalamus, leading to increased feeding during the resting phase of the day( Reference Paschos, Ibrahim and Song 57 ). Thus, circadian dysfunction in individual tissues can lead to major changes in whole-body energy metabolism.
Timed feeding as a synchroniser of peripheral clocks
The food-entrainable oscillator
Restriction of food availability to a narrow time window each day results in profound reorganisation of behaviour and physiology( Reference Stephan 58 , Reference Mistlberger 59 ). Such temporal restriction induces a bout of activity in advance of food availability, termed ‘food anticipatory activity’ (FAA). This phenomenon was originally observed in rats, but has since been reported in multiple vertebrate and invertebrate species. More detailed analysis in rodents reveals that this FAA is also accompanied by physiological changes including increased core body temperature and serum glucocorticoid concentration.
Interestingly, FAA exhibits properties that are consistent with it being controlled by endogenous circadian clock(s), rather than being merely a food-driven phenomenon. For example, if the temporal window of food availability is abruptly delayed, the onset of FAA takes multiple 24 h cycles to resynchronise to the new feeding time. Moreover, if an animal is completely food deprived, FAA persists at approximately the same time every 24 h for as long as the food deprivation can be maintained( Reference Stephan 58 , Reference Mistlberger 59 ).
The underlying circadian basis of FAA has led to the postulation that animals contain a food-entrainable oscillator (FEO). Although there are reported differences in FAA in mice lacking genetic components of the circadian clock( Reference Challet, Mendoza and Dardente 60 ), these mice do retain the ability to display FAA( Reference Storch and Weitz 61 ). It is therefore believed that the genetic control of the FEO differs from other circadian processes. In keeping with this idea, food anticipatory responses persist in SCN-lesioned animals( Reference Krieger, Hauser and Krey 62 , Reference Stephan 63 ), indicating that the FEO resides in tissue(s) outside of the SCN, the master circadian clock. Some studies have suggested that the FEO may be closely linked to the dorsomedial hypothalamic nuclei, a brain region known to be involved in the homeostatic regulation of feeding( Reference Mieda, Williams and Richardson 64 , Reference Fuller, Lu and Saper 65 ). Other work has highlighted the potential role of extra-hypothalamic brain regions in FAA( Reference Mendoza, Pevet and Felder-Schmittbuhl 66 ). The anatomical localisation of the FEO remains a controversial topic, however( Reference Mistlberger, Buijs and Challet 67 – Reference Landry, Kent and Patton 69 ). Indeed the FEO may lie outside of the brain or require the interplay between multiple tissues.
Regulation of rhythms in peripheral tissues
One potential mechanism underlying food-entrainable rhythmicity is the effect of feeding time on peripheral tissue clocks. In normal physiological conditions, the timing of behavioural rhythms, such as feeding, is driven by the SCN and thus represents a mechanism through which the SCN can synchronise rhythms in the periphery. The powerful nature of timed feeding as a circadian signal becomes apparent when food availability is divorced from SCN rhythms.
A typical protocol restricts food availability to nocturnal rodents, so that they can only eat during the light period of a light–dark cycle. This inverts the phase of clock gene rhythms in peripheral tissues, such as the liver, kidney, heart, pancreas, lung, gastrointestinal tract, and brown and white adipose tissue( Reference Zvonic, Ptitsyn and Conrad 33 , Reference Damiola, Le Minh and Preitner 70 – Reference Hoogerwerf, Hellmich and Cornelissen 72 ). Full entrainment of the liver rhythms appears to occur within 2–3 d, whereas the other peripheral tissues may require up to 1 week before they exhibit the maximal phase shift. A later mouse study involved removal of food access for the first 6 h of the dark period of a light–dark cycle, with mild energy restriction. After 4 d in this protocol, mice exhibited delayed rhythms of hepatic and plasma TAG concentration, together with delayed rhythms of lipogenic and clock gene expression in both liver and adipose tissue( Reference Yoshida, Shikata and Seki 73 ). When animals are able to eat ad libitum quantities of food during temporal restriction paradigms, SCN rhythms remain locked to the light–dark cycle( Reference Damiola, Le Minh and Preitner 70 , Reference Stokkan, Yamazaki and Tei 71 ). However, the combination of temporal food restriction and hypoenergetic food availability does induce reorganisation of rodent SCN rhythms( Reference Mendoza, Graff and Dardente 74 , Reference Mendoza, Gourmelen and Dumont 75 ). Indeed, hypoenergetic feeding of nocturnal rodents without restricting food availability to the light period alters the phase of SCN-driven rhythms( Reference Mendoza, Drevet and Pevet 76 ) as well as gene expression in peripheral tissues( Reference Kuroda, Tahara and Saito 77 ). Thus the overall effect of feeding on circadian organisation appears to involve an interaction between both the timing and the quantity of food intake (Fig. 1).
An important caveat when extrapolating the studies described above to human society is the relevance to standard human meal patterns. A common theme in human society is a feeding pattern of three meals per d. In contrast, most animal studies to date have utilised prolonged ad libitum feeding opportunities restricted to certain phases of the 24 h day. Some studies, however, have developed a ‘humanised’ meal protocol for rodents. When rats are only given their daily energy intake over ‘lunch’ and ‘dinner’ their gene expression rhythms in liver, heart and white adipose tissue are delayed compared with a group receiving the same total energy intake spread over three meals( Reference Wu, Sun and ZhuGe 78 ). Consistent with this finding, studies in mice using a range of mealtime combinations indicate that the first meal following a long fasting period provides an important synchronising signal to peripheral clocks( Reference Kuroda, Tahara and Saito 77 , Reference Hirao, Nagahama and Tsuboi 79 ). To date there are no comparable molecular data from human studies. One rare investigation of timed feeding on human circadian physiology is an experiment in which subjects were fed a single daily carbohydrate-rich meal for 3 d; morning consumption of this meal advanced core body temperature and heart rate, but not melatonin, rhythms compared with evening meal timing( Reference Krauchi, Cajochen and Werth 80 ). Furthermore, a delay in the timing of three daily meals within a fixed light–dark cycle is known to delay the phase of plasma leptin rhythms( Reference Schoeller, Cella and Sinha 81 ), which may be at least partially due to changes in adipose tissue clocks.
Although redundancy of signalling pathways providing input to the relevant tissues hinders elucidation of mechanistic insight into food entrainment, some progress has been made. At the nutritional level, phase shifting of the liver clock seems greater when the starch component of a mixed diet provides a large postprandial glucose concentration( Reference Itokawa, Hirao and Nagahama 82 ). Interestingly, however, ingestion of 100 % glucose, sucrose or maize starch is insufficient to alter the phase of liver rhythms, indicating that mixed macronutrient content may be necessary for food entrainment in the liver( Reference Hirao, Tahara and Kimura 83 ). At the physiological level, temporal food restriction more rapidly resynchronises peripheral clock gene rhythms in mice that have been adrenalectomised, compared with sham-operated controls( Reference Le Minh, Damiola and Tronche 84 ). This finding suggests that glucocorticoid signalling, which is believed to be an endocrine link between the SCN and peripheral clocks( Reference Balsalobre, Brown and Marcacci 85 ), may inhibit or delay the impact of temporal food availability. At the molecular level, it has been demonstrated that rhythmic phosphorylation of key transcription factors CREB and Akt (cAMP response element-binding protein and protein kinase B) in the mouse liver is driven by temporal feeding patterns( Reference Vollmers, Gill and DiTacchio 86 ). In keeping with this result, the expression of multiple genes targeted by molecular nutrient and stress sensors was similarly dependent on feeding time( Reference Vollmers, Gill and DiTacchio 86 ). Finally, mice deficient for the gene Parp1 (poly [ADP-ribose] polymerase 1) or the neurone-specific γ form of protein kinase C (PKCγ) exhibit impaired synchronisation to timed feeding( Reference Asher, Reinke and Altmeyer 87 , Reference Zhang, Abraham and Lin 88 ). Despite these advances, the mechanisms that mediate the effects of food on the circadian system are poorly understood and will doubtless be the subject of multiple further studies.
Human metabolic physiology and postprandial responses vary across the day
Diurnal changes
Diurnal rhythmicity refers to 24 h changes that occur in individuals kept in a varying environment, for example, a 24 h light–dark cycle. Although such rhythms are often relevant to a real-life scenario, there is the possibility that they are driven by environmental fluctuations rather than endogenous processes per se. As a result, they are not considered to be truly circadian.
Arguably the best-characterised daily metabolic rhythms in humans relate to changes in glucose homeostasis. Diurnal changes in glucose tolerance have been recognised in human subjects for many years( Reference Van Cauter, Polonsky and Scheen 89 ). Sensitivity to elevated glucose concentration is greatest in the early morning and then declines over the course of the day, leading to a phenomenon that has been termed ‘afternoon diabetes’. This daily change is not dependent upon changes in gastrointestinal function, but instead appears to be the result of altered glucose utilisation and insulin sensitivity, with maximal insulin sensitivity occurring in the early morning and decreasing throughout the day( Reference Van Cauter, Polonsky and Scheen 89 ).
In addition to glucose homeostasis, the regulation of plasma lipids is also subject to daily variation. Not only are basal concentrations of TAG elevated at night, but also there are diurnal changes in the postprandial TAG response. Ingestion of a meal at night results in increased plasma TAG that remains elevated for longer than the response to the same meal given during the day( Reference Sopowski, Hampton and Ribeiro 90 ). A study of postprandial responses to breakfast and lunch reported approximately 50 % less change in plasma TAG concentration following lunch than breakfast, despite the plasma TAG fraction showing no differences in concentration of [13C]palmitic acid that was included in each meal( Reference Burdge, Jones and Frye 91 ). The physiological basis for temporal differences in postprandial TAG response may therefore be independent of absorption or mobilisation of meal-derived lipids from the gut( Reference Burdge, Jones and Frye 91 ).
A number of groups have studied temporal variation of adipokines, which are adipose-derived hormones that regulate metabolic physiology in the brain and multiple peripheral tissues( Reference Trujillo and Scherer 92 , Reference Galic, Oakhill and Steinberg 93 ). Diurnal rhythms have been reported for many of these hormones, including leptin, adiponectin, chemerin, lipocalin and visfatin( Reference Sinha, Ohannesian and Heiman 94 – Reference Benedict, Shostak and Lange 98 ). Although the secretion of these hormones is likely to be governed by multiple factors such as feeding and sleep, detailed analyses of leptin secretion suggest that there is likely to be an underlying circadian component to adipokine rhythmicity( Reference Shea, Hilton and Orlova 99 , Reference Otway, Frost and Johnston 100 ). Furthermore, given the functional roles of adipokines, their rhythmic secretion may make important contributions towards the daily changes in glucose and lipid homeostasis described above.
Identification of endogenous circadian rhythms
In order to unmask truly endogenous circadian rhythms from temporal changes in the environment, a number of different laboratory protocols have been developed. The most widely used of these are the constant routine and forced desynchrony protocols( Reference Duffy and Dijk 101 , Reference Blatter and Cajochen 102 ). In a constant routine, subjects are kept awake in a supine posture in constant dim light, with identical regular (for example, hourly) snacks. Although this protocol effectively removes environmental rhythms, it does result in the development of sleep debt due to the necessity to keep subjects awake. One solution to this problem is to allow subjects to sleep during the dark phase of a light–dark cycle that is sufficiently different from 24 h to permit entrainment of subjects' circadian rhythms; this is the basis of a forced desynchrony protocol. For example, a commonly used variant of this protocol employs a 28 h light–dark cycle that therefore allows subjects to sleep every 28 h, while their circadian rhythms occur (‘free run’) with a frequency of approximately 24 h.
Various research groups have utilised the above protocols to investigate the contribution of the endogenous circadian system to daily rhythms of glucose and lipid metabolism. One study in which 4-hourly meals were administered over a constant routine revealed elevation of both postprandial glucose and TAG during the biological night, especially after high-fat meal intervention over the week preceding the constant routine( Reference Holmback, Forslund and Forslund 103 ). Consistent with this finding, analysis of postprandial responses during a forced desynchrony of 27-h days revealed effects of both circadian time and length of prior wakefulness on glucose and TAG concentration( Reference Morgan, Arendt and Owens 104 ). By contrast, postprandial insulin responses were regulated by circadian time, but not length of wakefulness. A more recent forced desynchrony protocol kept volunteers on 28-h days, each of which contained four meals: breakfast, lunch, dinner and a snack shortly before bedtime( Reference Scheer, Hilton and Mantzoros 105 ). It was found that the times during which subjects were awake and eating during their biological night resulted in multiple cardiometabolic changes, including decreased plasma leptin concentration and increased concentrations of both plasma glucose and insulin. In fact, the postprandial responses of some of these healthy subjects during the biological night were equivalent to the responses of a pre-diabetic individual( Reference Scheer, Hilton and Mantzoros 105 ). In a separate cross-over study using forced desynchrony, volunteers had daily metabolic profiles assessed after both three 21-h days and also three 27-h days. Although there were some differences in response to the 21-h v. 27-h days, both schedules disrupted glucose–insulin metabolism, increased carbohydrate oxidation and reduced protein oxidation, but had little or no effect on appetite or energy balance( Reference Gonnissen, Rutters and Mazuy 106 ). The human circadian system therefore exerts clear influence over key aspects of metabolic physiology.
Effects of body weight on circadian rhythms
The data discussed above describe the interaction between clocks and metabolism on a relatively short-term time frame. Of importance to health is the longer-term relationship between circadian rhythms, metabolic status and body weight. Indeed, many studies in the literature have reported altered daily rhythms in association with factors including altered body weight, presence of metabolic disease and long-term changes in nutrient intake.
Following the demonstration of daily rhythms of plasma leptin in human subjects, it was reported that the percentage amplitude of these rhythms declined in obese individuals( Reference Sinha, Ohannesian and Heiman 94 , Reference Matkovic, Ilich and Badenhop 107 , Reference Saad, Riad-Gabriel and Khan 108 ). However, not all studies have been able to replicate this finding( Reference Yildiz, Suchard and Wong 109 , Reference Mantele, Otway and Middleton 110 ). The reasons for discrepancies are not clear, but may include varied pre-laboratory controls, sex of subjects, extent of obesity (i.e. BMI of 30–35 v. 40+ kg/m2) and distribution of fat within the obese subjects recruited.
Another hormone that appears to demonstrate correlation between rhythm amplitude, body weight and metabolic health is melatonin. An early report that nocturnal melatonin concentration positively correlates with BMI in insulin-sensitive human subjects( Reference Arendt, Hampton and English 111 ) has been supported by recent data reporting elevated amplitude melatonin rhythms in obese non-diabetic men, although blunted melatonin rhythms are present in weight-matched men with type 2 diabetes( Reference Mantele, Otway and Middleton 110 ). In addition, nocturnal melatonin concentration correlates with aspects of the metabolic syndrome in women( Reference Corbalan-Tutau, Madrid and Nicolas 112 ). The functional relevance of these endocrine data is supported by molecular and genetic evidence for a role of melatonin signalling in metabolic physiology and type 2 diabetes mellitus. Common polymorphisms of the human MT2 melatonin receptor have been associated with impaired glucose homeostasis and type 2 diabetes in multiple populations( Reference Bouatia-Naji, Bonnefond and Cavalcanti-Proenca 113 – Reference Ronn, Wen and Yang 116 ). Although the calculated risk of developing type 2 diabetes is small for these polymorphisms, subsequent work identified additional rare MT2 variants that confer a much higher risk of diabetes and also disrupt melatonin signalling in cell culture experiments( Reference Bonnefond, Clement and Fawcett 117 ). Evidence from animal models further supports the existence of a physiological link between melatonin, insulin secretion( Reference Mulder, Nagorny and Lyssenko 118 ) and insulin sensitivity( Reference Contreras-Alcantara, Baba and Tosini 119 , Reference Nogueira, Lellis-Santos and Jesus 120 ). When comparing rodent and human data, it should be recognised that elevated melatonin secretion occurs at night in all species, irrespective of whether they are active at night or during the day; therefore direct translation of data relating melatonin to glucose homeostasis from rodents to humans is difficult. Despite this, there is now evidence to support linking low nocturnal melatonin levels in humans, estimated from morning urinary metabolite concentration, with the risk of developing type 2 diabetes( Reference McMullan, Schernhammer and Rimm 121 ) and also insulin resistance in non-diabetic subjects( Reference McMullan, Curhan and Schernhammer 122 ).
Comparison of molecular rhythms in lean and obese individuals has also been addressed by a number of research groups. Reduced amplitude rhythms have been reported in tissues such as adipose( Reference Ando, Yanagihara and Hayashi 123 , Reference Ando, Kumazaki and Motosugi 124 ), liver( Reference Ando, Kumazaki and Motosugi 124 , Reference Ando, Oshima and Yanagihara 125 ) and brain stem( Reference Kaneko, Yamada and Tsukita 126 ) of obese and diabetic mice. However, interpretation of these data is sometimes hampered by the use of different genetic strains in the lean and obese groups. We have recently compared daily profiles of clock gene expression in subcutaneous adipose biopsies taken from lean and obese human subjects and failed to observe any effects of body weight on these molecular rhythms( Reference Otway, Mantele and Bretschneider 25 ). Although it is possible that differences would have been observed if we had been able to serially sample other (for example, visceral) adipose depots, the data nonetheless indicate that obesity per se does not impair clock gene rhythms in all metabolically active tissues.
A small number of animal studies have compared lean and obese groups generated by manipulation of dietary intake, rather than examining the effects of altered body weight due to genetic differences. In most cases, dietary obesity results in clear changes in aspects of the circadian system, but the available results are not entirely consistent. In one study, 6 weeks of high-fat diet altered behavioural and endocrine rhythms, together with changes in gene expression profiles that included reduced amplitude clock gene rhythms in adipose and liver( Reference Kohsaka, Laposky and Ramsey 127 ). In another experiment, mice were fed for 7 weeks with either a high- or low-fat diet, fasted for 24 h and killed in constant darkness. Comparison of clock gene expression in the liver of these animals revealed a phase delay of approximately 3 h with no consistent reduction in rhythm amplitude in the animals fed on a high-fat diet( Reference Barnea, Madar and Froy 128 ). Analysis of two daytime time points in mice maintained on high- or low-fat diets for 11 months also revealed altered liver and kidney clock gene expression( Reference Hsieh, Yang and Tseng 129 ). In contrast to the above studies, which all used male mice, few significant differences were observed in liver and adipose clock gene rhythms from female mice fed high- or low-fat diets for 8 weeks( Reference Yanagihara, Ando and Hayashi 130 ).
The differences in type and magnitude of response observed in mice chronically fed a high-fat diet probably reflect details of experimental design such as sex of the animal, dietary composition and environmental conditions used during the protocol. Sex is an issue of note in regard to human physiology, where sex differences in circadian rhythms( Reference Duffy, Cain and Chang 131 ), adiposity( Reference Tchernof and Després 132 ) and nocturnal postprandial response (described below) have been reported. Furthermore, the extreme changes in dietary intake utilised in animal experiments may not accurately represent typical human diets. It is therefore clear that more research is required in this area before the translational consequences are fully understood.
Relevance to human lifestyle
As would be expected for an emerging research field, the available literature mostly derives from controlled laboratory experiments. However, the biological principles described have far-reaching implications for many people living in contemporary society.
Dietary regulation of body weight
Evidence is rapidly accumulating to support an important role of meal times in the long-term regulation of body weight. Proof-of-concept studies in animal models have utilised different timed feeding paradigms. Mice housed in a light–dark cycle and fed a high-fat diet gain more weight when the food is available only throughout the light phase, when they would usually be resting, than when it is provided throughout the dark phase( Reference Arble, Bass and Laposky 133 ). This body-weight effect becomes statistically significant within 2 weeks and despite trends towards increased energy intake and reduced activity in the light-fed animals, there were no statistically significant changes in these parameters. In a refinement of the protocol, mice were fed a high- or low-fat diet that was available either ad libitum throughout the day, or during a 4 h period in the middle of the light phase( Reference Sherman, Genzer and Cohen 134 ). Remarkably, temporal food restriction resulted in reduced body weight on both high- and low-fat diets, to the extent that mice on a restricted high-fat diet weighed less than those provided with a low-fat diet ad libitum. This occurred despite no difference in energy consumption (as expressed relative to body weight) between the restricted high-fat-diet group and the two low-fat-diet groups, although mice under restricted feeding did exhibit elevated total daily activity compared with ad libitum controls( Reference Sherman, Genzer and Cohen 134 ). Comparing these two studies, it seems that the duration of restricted food availability has profound effects on body-weight regulation, but the mechanisms underlying this phenomenon are not yet clear.
In humans, there is an increasing interest in the effects of meal timing per se on metabolism and body weight. Work in this area has understandably focused to a large degree on meals taken at the start and end of the day, for instance the study of breakfast consumption and individuals with night eating disorders. Evidence suggests a role for regular breakfast consumption in the maintenance of healthy body weight, although the issue has rarely been approached from a chronobiological perspective and questions remain about the causative mechanisms involved( Reference de la Hunty and Gibson 135 , Reference Casazza, Fontaine and Astrup 136 ). Night eating syndrome has recently been included in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). It is broadly characterised by recurrent episodes of nocturnal eating that cannot be better accounted for by other behavioural and psychiatric disorders, and is discussed in detail elsewhere( Reference Berner and Allison 137 ). The relationship between night eating syndrome and body weight is complex, with some variable findings reported in the literature. Despite this, the overall evidence provides compelling associations between night eating and obesity, with a consistent finding that night eating syndrome is more prevalent in overweight and obese groups( Reference Gallant, Lundgren and Drapeau 138 ). The importance of evening meals is further highlighted in studies of subjects without night eating disorder. For example, energy consumption after 20.00 hours has been associated with BMI independently of age, sleep timing and sleep duration( Reference Baron, Reid and Kern 139 ). This group later reported that protein intake within 4 h of sleep onset is associated with elevated BMI after controlling for age, sex, sleep timing and sleep duration( Reference Baron, Reid and Horn 140 ).
The link between food timing and body weight is also apparent in dietary weight-loss studies. A group of 420 individuals undergoing a 20-week weight-loss programme were categorised according to the time at which they ate lunch, which was their main daily meal. Those in the late group lost less weight and at a slower rate than the early group, with no difference in energy intake, energy expenditure, dietary composition or sleep duration( Reference Garaulet, Gomez-Abellan and Alburquerque-Bejar 141 ). In a separate experiment, obese/overweight women consumed energy-restricted diets that differed in the proportion of energy distributed between breakfast and dinner. The women eating more energy at breakfast than dinner not only lost more weight but also exhibited an improved metabolic profile in insulin sensitivity and TAG concentration( Reference Jakubowicz, Barnea and Wainstein 142 ). Together these data support the hypothesis that the timing of food intake is important for body-weight regulation.
Shift work and jet-lag
Since industrialisation, humans have gained the ability to regulate environmental conditions and subsequently alter temporal patterns of behaviour. Indeed the phrase ‘24/7 society’ is now in common usage to describe the constant presence of industrial and social activity. In order to cope with the demands of this modern aspect of society, varied work schedules are now commonplace, with approximately 20 % of the European workforce engaged in night shifts( Reference Costa 143 ). This clearly indicates that a large section of the population experiences regular misalignment of their behaviour with the solar day. A second common cause of abrupt circadian misalignment is jet-lag, the rapid travel across time zones. Although this experience is a rare and transient phenomenon for most people, it nonetheless affects a substantial number of individuals and in some cases (for example, airline crew) can be a regular event. A related phenomenon that is common in society is a weekly change between widely differing sleep times on work and free days. This has been termed ‘social jet-lag’( Reference Wittmann, Dinich and Merrow 144 ) and is associated with elevated BMI( Reference Roenneberg, Allebrandt and Merrow 145 ).
Multiple health problems are associated with shift work, including increased risk of cardiovascular and metabolic disease( Reference Tucker, Marquie and Folkard 146 ). Understanding the aetiology of shift work-related morbidity is complex due to diverse contributory factors such as sleep disturbance, altered social pressure and patterns of food intake( Reference Esquirol, Bongard and Mabile 147 , Reference Lowden, Moreno and Holmback 148 ). For example, although shift workers often report normal total energy intake, there is commonly an altered temporal distribution of feeding characterised by more irregular eating times, more snacking and fewer substantial meals( Reference Lowden, Moreno and Holmback 148 ). Alongside these lifestyle changes it is likely that disrupted circadian physiology is a major contributor to the pathophysiological consequences of shift work. Indeed it is generally recognised that many shift workers in temperate regions poorly adapt circadian rhythms to their work conditions( Reference Folkard 149 ). As a result, these individuals experience prolonged durations of misalignment between their circadian biology and behavioural patterns.
As described previously, postprandial profiles of glucose and TAG concentration vary over the day. Such studies clearly imply that shift workers eat a substantial proportion of their meals during the time of suboptimal glucose and lipid tolerance. This prediction is strengthened by studies of simulated shift work where subjects are subjected to an abrupt shift of typically 6–10 h in their daily routine. Interestingly, the postprandial response in such protocols is altered by the preceding diet. In comparable experiments, the exaggerated postprandial response following a test meal in shifted subjects was reduced for glucose and insulin but increased for TAG following a low-fat pre-meal( Reference Ribeiro, Hampton and Morgan 150 ) rather than a high-fat pre-meal( Reference Hampton, Morgan and Lawrence 151 ). Furthermore, there are reported sex differences in postprandial response, with a more pronounced elevation of TAG in the first night of a simulated night shift in men than in women( Reference Sopowski, Hampton and Ribeiro 90 ).
In real shift workers, there are also postprandial data describing the relative insulin resistance and lipid intolerance following abrupt shift changes( Reference Lund, Arendt and Hampton 152 ). Given the large number of individuals undertaking shift work in modern society, there is a clear need to improve circadian alignment in these individuals. One possible intervention is the manipulation of light, which is able to reset circadian rhythms and also directly improve alertness( Reference Vandewalle, Maquet and Dijk 153 ) even following short exposure times( Reference Chang, Santhi and St Hilaire 154 ). However, timed food may also be a powerful method for resetting rhythms to a new phase. Of particular interest is the ability of timed food to reset peripheral tissue rhythms.
Animal models support the idea that timed food intake could be a valuable intervention to minimise adverse effects of shift work. Mice subjected to an artificial shift work-like environmental schedule exhibit circadian desynchrony and metabolic disturbance( Reference Barclay, Husse and Bode 155 ). Similar findings have been reported in rats exposed to an artificial shift work protocol, although the body-weight increase and metabolic disturbances experienced were attenuated when food availability was restricted to the normal activity phase( Reference Salgado-Delgado, Angeles-Castellanos and Saderi 156 ). Further development of these animal models will permit detailed molecular analysis to complement human studies of shift work and its adverse effects.
Conclusion
A wealth of data from varied experimental approaches provides us with clear links between circadian, metabolic and nutritional biology. These findings provide a strong foundation upon which to model mechanisms underlying the temporal differences in response to food intake. One limitation of the field is that little translational research has yet been performed in human subjects. Understanding the circadian regulation of human metabolism will have profound implications for nutritional science and explain how time of day is important for postprandial physiology. Furthermore, it will also reveal how timed dietary intake can be used as a means to alleviate some of the deleterious effects of circadian misalignment that are experienced by large numbers of people within modern society.
Acknowledgements
The author thanks Dr S. M. Hampton for critically reading an earlier version of this paper.
The author's work cited in the present review was funded by the UK Biotechnology and Biosciences Research Council (BBSRC), Diabetes UK and Stockgrand Ltd. The funders had no role in the design, analysis or writing of this article.
The author has performed consultancy work for Kellogg Marketing and Sales Company (UK) Limited.