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Nutrition and the circadian system

Published online by Cambridge University Press:  25 May 2016

Gregory D. M. Potter*
Affiliation:
LIGHT Laboratories, Division of Epidemiology and Biostatistics, University of Leeds, LeedsLS2 9JT, UK
Janet E. Cade
Affiliation:
Nutritional Epidemiology Group, School of Food Science and Nutrition, University of Leeds, LeedsLS2 9JT, UK
Peter J. Grant
Affiliation:
LIGHT Laboratories, Division of Cardiovascular & Diabetes Research, University of Leeds, LeedsLS2 9JT, UK
Laura J. Hardie
Affiliation:
LIGHT Laboratories, Division of Epidemiology and Biostatistics, University of Leeds, LeedsLS2 9JT, UK
*
*Corresponding author: G. D. M. Potter, email umgdmp@leeds.ac.uk
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Abstract

The human circadian system anticipates and adapts to daily environmental changes to optimise behaviour according to time of day and temporally partitions incompatible physiological processes. At the helm of this system is a master clock in the suprachiasmatic nuclei (SCN) of the anterior hypothalamus. The SCN are primarily synchronised to the 24-h day by the light/dark cycle; however, feeding/fasting cycles are the primary time cues for clocks in peripheral tissues. Aligning feeding/fasting cycles with clock-regulated metabolic changes optimises metabolism, and studies of other animals suggest that feeding at inappropriate times disrupts circadian system organisation, and thereby contributes to adverse metabolic consequences and chronic disease development. ‘High-fat diets’ (HFD) produce particularly deleterious effects on circadian system organisation in rodents by blunting feeding/fasting cycles. Time-of-day-restricted feeding, where food availability is restricted to a period of several hours, offsets many adverse consequences of HFD in these animals; however, further evidence is required to assess whether the same is true in humans. Several nutritional compounds have robust effects on the circadian system. Caffeine, for example, can speed synchronisation to new time zones after jetlag. An appreciation of the circadian system has many implications for nutritional science and may ultimately help reduce the burden of chronic diseases.

Type
Full Papers
Copyright
Copyright © The Authors 2016 

Life is exposed to relatively predictable daily changes in the environment, the most conspicuous of which is the daily light/dark (LD) cycle. Endogenous circadian (approximately 24 h) timing systems have evolved in organisms in response to daily cycles of abiotic (such as temperature cycles) and biotic factors (such as food availability cycles) to generate circadian rhythms in behaviour and physiology to anticipate and adapt to these fluctuations and temporally compartmentalise incompatible biological processes, such as anabolism and catabolism( Reference Bass and Takahashi 1 ). The circadian system therefore primes organisms to feed at specific times, and restricting food access to times at which feeding is typically low in model organisms produces many deleterious health consequences. Fruit flies fed at the ‘wrong’ time, for example, produce fewer eggs( Reference Xu, DiAngelo and Hughes 2 ), and mice fed during the light period only – the rest period for these nocturnal rodents – are prone to diabetes, the metabolic syndrome, obesity, and even impaired cognitive function( Reference Loh, Jami and Flores 3 Reference Bray, Ratcliffe and Grenett 6 ).

The circadian system comprises networks of molecular clocks throughout body tissues. Although circadian rhythms are autonomous, self-sustaining and temperature compensated, the circadian system has remarkable plasticity, and feeding can modify circadian rhythms from the molecular to behavioural level( Reference Damiola, Le Minh and Preitner 7 , Reference Boulos, Rosenwasser and Terman 8 ). Indeed, peripheral tissue clocks such as the liver clock are particularly sensitive to the composition and timing of food consumed. Disorganisation of the circadian system and loss of timing relationships between circadian rhythms in particular are thought to contribute to the development of certain chronic diseases( Reference Mukherji, Kobiita and Damara 5 ). Hence, appropriate nutrition, where energy intake is aligned with energy expenditure and clear feeding/fasting cycles are synchronised with clock-regulated metabolic changes, helps maintain robust behavioural and physiological circadian rhythms and health( Reference Chaix, Zarrinpar and Miu 9 ).

Relatively recent environmental changes have predisposed many individuals to circadian system disruption. The advent of artificial lighting, jetlag induced by high-speed trans-meridian travel, shift work and around-the-clock access to energy-dense food are but a few factors that may conspire to disorganise the circadian system, and thereby adversely affect the health of people in modern societies( Reference Damiola, Le Minh and Preitner 7 , Reference Moreno, Vasconcelos and Marqueze 10 , Reference Sack, Auckley and Auger 11 ).

The purposes of this review were therefore to introduce the circadian system, highlight its influences on physiological responses to feeding, show how feeding in turn influences the circadian system and to provide implications for nutritionists and directions for future research.

The hierarchical circadian system

Central and peripheral clocks

The paired suprachiasmatic nuclei (SCN) in the anterior hypothalamus orchestrate circadian rhythms throughout body tissues using autonomic, behavioural and humoral mechanisms( Reference Ralph, Foster and Davis 12 , Reference Silver, LeSauter and Tresco 13 ). SCN cells contain cell-autonomous molecular clocks based on negative feedback loops that generate approximately 24-h rhythms in ‘clock’ gene transcription( Reference Welsh, Takahashi and Kay 14 ) (Fig. 1). As transcription factors, clock genes temporally segregate incompatible cellular processes by regulating the transcription of myriad clock-controlled genes, many of which are enriched for metabolic functions, and the same molecular clocks present in the SCN regulate rhythmic cellular processes in tissues throughout the body( Reference Partch, Green and Takahashi 15 ). That over half of protein-coding genes in mice have been shown to exhibit circadian transcription in certain conditions( Reference Patel, Ceglia and Zeller 16 ), and large proportions of proteins and metabolites follow suit( Reference Reddy, Karp and Maywood 17 , Reference Eckel-Mahan, Patel and Mohney 18 ), exemplifies the importance of clock control in metabolism. Post-transcriptional clock protein regulation confers another level of tissue-specific metabolic control( Reference Cardone, Hirayama and Giordano 19 Reference Hirayama, Sahar and Grimaldi 22 ). Recently discovered non-transcriptional rhythms in peroxiredoxins, redox-sensitive proteins, are ubiquitous among organisms of all kingdoms, but how these are integrated with clock gene feedback loops is little understood( Reference O’Neill, van Ooijen and Dixon 23 ).

Fig. 1 The mammalian circadian clock. The molecular clock consists of ‘clock’ genes that form negative-feedback loops. The transcription factors circadian locomotor output cycles kaput (CLOCK) and brain and muscle aryl hydrocarbon receptor nuclear translocator-like 1 (BMAL1) heterodimerise and activate clock-controlled genes (CCG). On activation by CLOCK-BMAL1, cryptochrome (CRY) 1–2 and period (PER) 1–3 proteins accumulate in the cytosol, multimerise and translocate into the nucleus and form inhibitory complexes, repressing CLOCK-BMAL1 and terminating CRY1–2 and PER1–3 transcription during the rest phase. As the rest phase progresses, PER-CRY complexes are degraded by F-box/LRR-repeat protein 3 (FBXL3), casein kinase 1 (CK1) ε and CK1δ. Inhibition of CLOCK-BMAL1 activity ends, completing the negative feedback loop. Auxiliary feedback loops are antiphasic to the core loop and regulate BMAL1 transcription. The nuclear receptors reverse-erythroblastosis (REV-ERB) α and β repress BMAL1 transcription, whereas RAR-related orphan receptor (ROR) α activates BMAL1 transcription. Auxiliary feedback loops add robustness, among other roles.

In the absence of time cues, the human circadian system has a period of approximately 24·2 h( Reference Czeisler, Duffy and Shanahan 24 ) and must therefore be re-set (entrained) daily to the 24-h day. The SCN are primarily entrained by light via a monosynaptic pathway from intrinsically photosensitive retinal ganglion cells in the inner retinae to the SCN( Reference Berson, Dunn and Takao 25 ). In turn, a multisynaptic pathway from the SCN to the pineal gland is a major route by which photoperiodic information is disseminated( Reference Moore 26 ). During darkness, the pineal gland synthesises melatonin, a hormone that increases sleep propensity and acts on its widely expressed receptors to provide photoperiodic information, and contributes to synchronisation of circadian rhythms in other tissues( Reference Zawilska, Skene and Arendt 27 ). Dim light melatonin onset (DLMO) can therefore be used as a proxy for the onset of the biological night in humans, with melatonin offset in the morning corresponding to the start of the biological day.

In addition to melatonin, the SCN help maintain appropriate phase relationships among peripheral clocks by regulation of other humoral factors – for example, the SCN produce their own secretions to support synchronisation of clocks in other tissues( Reference Kramer, Yang and Snodgrass 28 Reference Kraves and Weitz 30 ). Further SCN secretions also contribute to the rhythmic release of hormones such as glucocorticoids by other tissues( Reference Kalsbeek, van Heerikhuize and Wortel 31 ), and glucocorticoids are particularly important entraining agents for many peripheral clocks. The demonstration that glucocorticoid receptor activation restores approximately 60 % of rhythmic gene transcripts in the mouse liver exemplifies this( Reference Reddy, Maywood and Karp 32 ). Another mechanism by which the SCN synchronise clocks throughout tissues is by regulating the circadian body temperature rhythm, as molecular clocks can be entrained by circadian temperature fluctuations by way of the heat shock pathway( Reference Buhr, Yoo and Takahashi 33 ).

The circadian system readies for feeding during the active phase

As it does with physical activity, the circadian system readies the body for daytime feeding. Human gastric emptying and gastrointestinal motility rates peak in the morning( Reference Goo, Moore and Greenberg 34 , Reference Rao, Sadeghi and Beaty 35 ), and studies in rodents have shown that clock regulation of bile acids and nutrient transporters optimises digestion during the active phase( Reference Han, Zhang and Jain 36 , Reference Hussain and Pan 37 ). Furthermore, daily rhythms in the gut microbiota of mice and humans fulfil time-of-day-specific functions, enhancing energy metabolism during the active phase and favouring detoxification during the rest phase( Reference Thaiss, Zeevi and Levy 38 ). The microbiota and circadian system have a complex bidirectional relationship, as disruption of the molecular clock disorganises rhythmic changes in the gut microbiota( Reference Liang, Bushman and FitzGerald 39 ), and germ-free mice have altered clock gene expression( Reference Leone, Gibbons and Martinez 40 ). Related to such changes, there are circadian rhythms in blood concentrations of many nutrients, such as glucose and lipids( Reference Morgan, Arendt and Owens 41 ). An important implication of circadian regulation of the gastrointestinal system is the importance of considering timing of nutritional tests, as exemplified by the recent demonstration that food allergy test results are contingent on the time of day( Reference Tanabe, Kitagawa and Wada 42 ).

The circadian system promotes energy substrate storage in appropriate tissues during the day. Insulin sensitivity has a bimodal daily peak during the active phase( Reference Scheer, Hilton and Mantzoros 43 ), and appetite for most foods is clock-controlled and lowest in the morning, perhaps to allow consolidated sleep despite diminishing energy availability( Reference Scheer, Morris and Shea 44 ). Diet-induced thermogenesis too has a circadian rhythm that peaks in the morning( Reference Morris, Garcia and Myers 45 ). These changes may be of particular relevance to the obesity epidemic, as they suggest that delayed bedtimes increase time for food consumption when appetite is high, and that consuming a higher proportion of dietary energy in the morning might encourage a negative energy balance, the principle determinant of decreasing body mass.

Feeding entrainment of clocks

Although the SCN clocks are primarily entrained by light, time-of-day-restricted feeding (TRF) studies, where food availability is restricted to a period of several hours, have shown that peripheral clocks are predominantly responsive to feeding. Indeed, rest phase TRF inverts gene expression profiles in many peripheral tissues including the heart, kidney, liver, pancreas, adipose tissue and the gastrointestinal tract( Reference Damiola, Le Minh and Preitner 7 , Reference Stokkan, Yamazaki and Tei 46 Reference Hoogerwerf, Hellmich and Cornelissen 48 ). The time course of this entrainment varies depending on the organs in question, with the liver clock responding to feeding particularly rapidly. As a result, peripheral tissue rhythms can be uncoupled from SCN rhythms( Reference Damiola, Le Minh and Preitner 7 ). Interestingly, feeding shifts the liver clock more rapidly in SCN-lesioned mice, suggesting that the SCN counters internal desynchronisation – the loss of appropriate phase relationships between clocks that is thought to contribute to metabolic aberrations( Reference Saini, Liani and Curie 49 ). During ad libitum conditions, TRF does not appear to affect the phase of the SCN clock; however, the SCN clock phase may respond somewhat to TRF combined with energy restriction( Reference Mendoza, Graff and Dardente 50 ). Although few studies on the effects of TRF on the human circadian system have been published, circadian rhythms in core body temperature and heart rate were advanced after 3 d of morning v. evening TRF in healthy young men( Reference Krauchi, Cajochen and Werth 51 ).

Coupling between metabolism and clocks

Feeding entrainment of tissue clocks is predicated on reciprocal relationships between molecular clocks and metabolic sensors and regulators( Reference Eckel-Mahan and Sassone-Corsi 52 ). Feeding/fasting cycles produce changing nutrient availability, and hence periodic phosphorylation of energy sensors such as 5' AMP-activated protein kinase (AMPK), which promotes ATP production during reduced energy availability, and mechanistic target of rapamycin (mTOR), which promotes anabolic processes during increased energy availability. These regulators are coupled to molecular clock components, which in turn influence myriad metabolic processes integral to nutrient homoeostasis. AMPK, for example, phosphorylates and destabilises cryptochrome (CRY) 1 in peripheral cells( Reference Lamia, Sachdeva and DiTacchio 53 ) and interacts with SIRTUIN (SIRT) 1. In turn, SIRT1 modulates transcription factors including period (PER) 2( Reference Asher, Gatfield and Stratmann 54 ) as well as the ventromedial hypothalamic clock, a brain region that contributes to regulation of the circadian rhythm in feeding behaviour( Reference Orozco-Solis, Ramadori and Coppari 55 ). SIRT1 is one of a family of deacetylase enzymes that have many roles in metabolic regulation, and SIRT1 and SIRT6 appear to be particularly important to temporal partitioning of metabolism by controlling the transcription of distinct sets of genes with circadian expression profiles, with SIRT6 regulating the rhythmic transcription of genes involved in cholesterol and fatty acid (FA) metabolism( Reference Masri, Rigor and Cervantes 56 ).

Both tissue-specific and whole-body genetic disruption of the molecular clock produce diverse metabolic aberrations( Reference Paschos, Ibrahim and Song 57 , Reference Turek, Joshu and Kohsaka 58 ), and the molecular clock partly mediates beneficial effects of some nutritional interventions, such as the longevity-promoting effects of energy restriction( Reference Patel, Chaudhari and Gupta 59 ). These findings support recent observational studies that have associated SNP in clock genes with various facets of metabolic health. Regarding circadian locomotor output cycles kaput (CLOCK), for example, CLOCK SNP have been associated with non-alcoholic steatohepatitis, the metabolic syndrome, small dense LDL levels, obesity and diabetes( Reference Sookoian, Castano and Gemma 60 Reference Uemura, Katsuura-Kamano and Yamaguchi 64 ). Perhaps the most studied of these associations is that of obesity: to date, eight common CLOCK SNP have been linked to obesity and three have been associated with energy intakes( Reference Valladares, Obregon and Chaput 65 ). Results of such small, candidate-gene association studies need support from large, unbiased, genome-wide association studies, however.

Food anticipatory activity and food-entrainable oscillators

Coupling between nutrient availability and the circadian system is also evident at the behavioural level. TRF in animals such as rats produces food anticipatory activity (FAA) – food-seeking behaviour at times during which food procurement is most likely. FAA is goal-directed towards places where food is available, and may thus be an adaptive strategy to enhance foraging success( Reference Boulos, Rosenwasser and Terman 8 ). Indeed, FAA is accentuated during energy restriction. As FAA is entrainable and persists during several days of food deprivation, FAA appears to be a true circadian rhythm.

Interestingly, FAA persists both following SCN ablation( Reference Stephan, Swann and Sisk 66 ) and disruption of the positive and negative arms of the molecular clock( Reference Storch and Weitz 67 ); therefore, the food-entrainable oscillators thought to underlie FAA must reside elsewhere. Candidate oscillators comprise various brain structures (including the cerebellum, dorsomedial nuclei, and dorsal striatal and mesocorticolimbic circuits( Reference Mendoza, Pevet and Felder-Schmittbuhl 68 Reference Verwey and Amir 70 )), neurochemical pathways (including dopaminergic and melanocortinergic signalling( Reference Gallardo, Darvas and Oviatt 71 , Reference Sutton, Perez-Tilve and Nogueiras 72 )) and hormonal signals (including ghrelin and orexins( Reference LeSauter, Hoque and Weintraub 73 )).

Eating patterns: feeding/fasting matters

As metabolic rhythms are intertwined with nutrient availability, clear feeding/fasting cycles consolidate robust metabolic and behavioural rhythms. High-fat diets (HFD) blunt feeding/fasting cycles in mice, increasing the proportion of energy consumed during the rest phase, and hence dampen circadian rhythms in clock genes( Reference Kohsaka, Laposky and Ramsey 74 , Reference Hatori, Vollmers and Zarrinpar 75 ). Consistent with this, expression of adipose tissue clock genes such as PER2 is increased following weight loss in humans( Reference Pivovarova, Gogebakan and Sucher 76 ). Ad libitum access to HFD consistently and rapidly produces obesity in many animals, and endocrine rhythms are similarly blunted in obese humans( Reference Matkovic, Ilich and Badenhop 77 ). Whether obesity precedes dampened circadian rhythms has been contentious, but recent evidence indicates that HFD induce rapid re-organisation of gene transcription rhythms before overt increases in adiposity in mice( Reference Eckel-Mahan, Patel and de Mateo 78 ).

Compared with ad libitum feeding, TRF offsets HFD-induced blunted feeding rhythms in mice, and the result is superior metabolic health, including reduced adiposity, despite similar energy intakes( Reference Hatori, Vollmers and Zarrinpar 75 ). Comprehensive recent experiments have shown that, despite similar energy intakes and locomotor activity, various TRF schedules are beneficial during different nutritional ‘challenges’, such as HFD and high-fructose diets, and that beneficial metabolic effects of TRF are proportional to fasting duration( Reference Chaix, Zarrinpar and Miu 9 ). During HFD feeding, TRF produces nutrient sensor profiles (including AMPK and mTOR) that are more similar to mice fed normal chow( Reference Hatori, Vollmers and Zarrinpar 75 ). Furthermore, TRF counters HFD-induced reductions in cyclical changes in the gut microbiota, and stool metabolite analyses suggest that this effect of TRF contributes to metabolic health benefits of TRF( Reference Zarrinpar, Chaix and Yooseph 79 ). These studies used male C57/BL6 mice, animals with a particular susceptibility to diet-induced obesity. As such, it may be premature to extrapolate these findings to humans. Nevertheless, recent research found that eight obese adults with habitual eating periods exceeding 14 h experienced sustained weight loss and improved sleep when consumption of energy-containing foods and drinks was restricted to an 11-h period each day( Reference Gill and Panda 80 ). The latter study was clearly limited by its sample size, however.

In contrast to the beneficial effects of TRF during HFD feeding, TRF may not confer such striking metabolic advantages when mice are fed normal chow( Reference Hatori, Vollmers and Zarrinpar 75 ). The same may be true among lean humans consuming typical diets. Among fifteen healthy young adults, a cross-over trial found that evening TRF increased fasting glycaemia and impaired glucose tolerance v. an isoenergetic diet comprising three meals throughout the day( Reference Carlson, Martin and Stote 81 ). Another study of the same design associated TRF with increased hunger, blood pressure and cholesterol( Reference Stote, Baer and Spears 82 ). However, findings may have been confounded by circadian variations in these parameters, as measures were taken at different times of the day.

Although not described as TRF studies, breakfast skipping is conceptually akin to TRF. In a larger study of overweight and obese adults, breakfast skipping did not influence responses to weight-loss diets( Reference Dhurandhar, Dawson and Alcorn 83 ), and a careful study in lean young adults found that one of the only effects of 6 weeks of breakfast omission was increased afternoon glycaemic variability( Reference Betts, Richardson and Chowdhury 84 ). Subsequent research using the same protocol in obese adults also found few differences between groups, although insulin sensitivity was higher in breakfast eaters( Reference Chowdhury, Richardson and Holman 85 ). It is possible that breakfast omission altered the timing of peak insulin sensitivity, however. Therefore, it appears that TRF may not benefit metabolic health in all contexts. Certainly, further studies with larger sample sizes are needed. Important questions remain unanswered, such as what is the optimal TRF period and meal frequency, and under what circumstances?

Time-of-day-restricted feeding: meal timing matters

One factor that may be relevant to the efficacy of TRF is meal timing. Mice fed HFD during the rest phase tended to gain more fat mass than mice fed HFD during the active phase( Reference Arble, Bass and Laposky 4 ). Similarly, mice fed normal chow during the rest phase also gained more fat mass than mice fed during the active phase. Rest phase TRF also altered clock and metabolic gene expression profiles in peripheral tissues, blunted corticosterone rhythm amplitudes, reduced energy expenditure despite comparable locomotor activity and reduced lipid oxidation within 9 d( Reference Bray, Ratcliffe and Grenett 6 ). It is possible that deleterious metabolic effects of rest phase TRF are related to misalignment between energy intake and energy expenditure. Clock gene mutations alter circadian rhythm periods in organisms including humans( Reference Toh, Jones and He 86 ), and a transgenic hPER1 mutation in mice increases obesity risk by advancing peak feeding time relative to peak daily energy expenditure. Subsequently using TRF to synchronise feeding with peak energy expenditure mitigates obesity development in these animals( Reference Liu, Huang and Wu 87 ).

Ramadan confines eating to the rest phase and modifies circadian rhythms in hormone secretion – for example, the timing of the morning rise in cortisol and night-time melatonin peak are both delayed( Reference Bogdan, Bouchareb and Touitou 88 ). Some results of Ramadan studies appear to contradict rodent TRF study findings, however. Meta-analysis of thirty-five observational studies found a mean reduction in body mass of 1·24 kg during Ramadan, with differences between ethnicities and greater reductions in men. No effects on dietary macronutrient proportions were observed, and fasting duration was not associated with body mass changes( Reference Sadeghirad, Motaghipisheh and Kolahdooz 89 ). It was not possible to evaluate body composition, however, and carefully controlled human TRF experiments are needed to determine whether large differences in TRF timing produce similarly large metabolic changes to those seen in mice.

Time-of-day-restricted feeding: nutrient and energy distribution timing matters

We refer to nutrient intake timing as the timing of ingestion of specific nutrients and the distribution of energy assigned to eating occasions when the timing of eating occasions is otherwise similar. Studies of mice show that high-fat meal consumption at the end of the active phase increases adiposity, insulin, leptin, and triacylglycerolaemia v. consumption at the beginning of the active phase( Reference Bray, Tsai and Villegas-Montoya 90 ). Similarly, restricting fructose access to the rest phase increases adiposity and insulin resistance in comparison with restricting access to the active phase( Reference Morris, Araujo and Pohlman 91 ).

In overweight and obese women matched for energy intakes, those who consumed a larger proportion of daily energy early in the day lost more weight than those consuming more later in the day( Reference Jakubowicz, Barnea and Wainstein 92 ), consistent with other findings that earlier lunch consumption is associated with greater weight loss after 20 weeks( Reference Garaulet, Gomez-Abellan and Alburquerque-Bejar 93 ). Similar associations have since been reported in severely obese adults following bariatric surgery( Reference Ruiz-Lozano, Vidal and de Hollanda 94 ). As diet-induced thermogenesis peaks in the morning, and breakfast consumption is associated with higher subsequent non-exercise activity thermogenesis, and hence energy expenditure( Reference Betts, Richardson and Chowdhury 84 ), it is plausible that assigning more of daily energy expenditure to earlier meals may encourage a negative energy balance during hypoenergetic diets. Further studies on how meal composition and energy availability affect responses to TRF will be valuable.

Eating patterns: consistency matters

Finally, eating patterns are very inconsistent in some adults( Reference Gill and Panda 80 ), and this may be relevant to metabolic health. In mice, fixing TRF to a 12-h period during twice-weekly 6-h LD cycle advances might be expected to uncouple LD cycle-entrained SCN rhythms from feeding-entrained peripheral clock rhythms and produce corresponding metabolic disorder. In these conditions, however, TRF mitigated the obesogenic effects of LD cycle shifts observed in ad libitum-fed mice, despite similar energy intakes. Hence, meal regularity and not just its timing relative to activity may be important to metabolic benefits of TRF( Reference Oike, Sakurai and Ippoushi 95 ). The mechanisms by which regular feeding schedules offset obesity in this study are unclear, however, and similar studies in humans are necessary to determine whether these findings are applicable to populations such as shift workers. It will also be interesting to clarify whether TRF needs to be implemented daily to be beneficial; some evidence suggests otherwise( Reference Halberg, Henriksen and Soderhamn 96 ).

Together, it appears that TRF may be a promising way to improve metabolic health in overweight and obese individuals. Consistent meal patterns and consuming meals shortly after physical activity may help optimise metabolic health. Furthermore, allocating a higher proportion of energy intake to earlier meals may promote a lower energy balance when diets are matched for energy intake. Nevertheless, many questions remain. It is important to determine how effective different TRF schedules are compared to one another and what factors determine inter-individual variability in responses.

Nutrient composition modifies clocks

The compositions of foods have been shown to influence many different circadian rhythms in rodents, from gene expression profiles to behavioural rhythms. HFD have sometimes but not always been found to influence peripheral tissue clock gene expression profiles in mice studies( Reference Kohsaka, Laposky and Ramsey 74 , Reference Yanagihara, Ando and Hayashi 97 ), and these discrepancies may have resulted from factors including diet composition. In support of this contention, higher-protein, lower-carbohydrate chow advanced expression rhythms of multiple clock genes in the kidneys and livers of mice, and increased mean expressions of brain and muscle aryl hydrocarbon receptor nuclear translocator-like 1 (Bmal1) and Cry1 in comparison with standard chow( Reference Oishi, Uchida and Itoh 98 ). In humans, switching participants from higher-carbohydrate (55 %) and lower-fat (30 %) diets to isoenergetic lower-carbohydrate (40 %) and higher-fat (45 %) diets delayed and increased the amplitude of cortisol rhythms, changed inflammatory and metabolic gene expression profiles and altered PER gene expression rhythms in monocytes( Reference Pivovarova, Jurchott and Rudovich 99 ).

In addition to the proportions of dietary energy coming from the macronutrients influencing peripheral clocks, individual nutrients may influence the circadian system, even within certain types of nutrients. Using FA to exemplify this, palmitate, the most abundant SFA in animals, and DHA, a PUFA found plentifully in fish, differentially affected Bmal1 expression in a murine hypothalamic cell line( Reference Greco, Oosterman and Belsham 100 ). Moreover, manipulating dietary DHA and EPA content shifts liver clock gene expression profiles in mice in vivo ( Reference Furutani, Ikeda and Itokawa 101 ).

There are also several non-essential dietary compounds consistently shown to influence the circadian system. Alcohol is widely consumed in many societies and appears to be particularly disruptive to molecular, endocrine and behavioural circadian rhythms in humans and other animals( Reference Huang, Ho and Chen 102 Reference Brager, Ruby and Prosser 106 ). Caffeine, the most-used psychoactive compound worldwide, is present in many foods and beverages and influences the amplitudes and phases of peripheral tissue clock gene expression rhythms in mice( Reference Sherman, Gutman and Chapnik 107 ). Evening caffeine consumption delays the human circadian system in vivo and lengthens clock gene expression periods in vitro ( Reference Burke, Markwald and McHill 108 ). Hence, careful use of caffeine can expedite circadian rhythm entrainment following jetlag( Reference Pierard, Beaumont and Enslen 109 ). However, even if subjective sleepiness is unaffected by its ingestion, caffeine impairs sleep following jetlag( Reference Beaumont, Batejat and Pierard 110 ). Caffeine has also been studied for efficacy in entraining individuals with chronic circadian system dysfunction. In a small study of blind individuals with non-24-h sleep/wake rhythm disorder, a disorder where light fails to synchronise the circadian system with the 24-h d, 150 mg of morning caffeine was insufficient to entrain circadian rhythms( Reference St Hilaire and Lockley 111 ). Dietary polyphenols are another group of compounds consistently shown to influence both molecular and behavioural circadian rhythms in some animals( Reference Ribas-Latre, Baselga-Escudero and Casanova 112 , Reference Pifferi, Dal-Pan and Menaker 113 ), and other novel nutritional supplements such as dietary polyamines( Reference Zwighaft, Aviram and Shalev 114 ) phase-shift the circadian system in rodents. Further research is needed to see whether such compounds might be useful in humans, however; if they are, what are the best times to consume them to maximise their impact, and what are the dose–response and phase–response curves of these compounds?

Conclusions and directions for future research

Growing interest in nutrition and the circadian system has produced many insights into the reciprocal relationships between the two in recent years. Findings from these studies have many implications. When assessing nutritional status and the efficacy of nutritional interventions, for example, test timing is an important consideration. More specifically, physiological measures should be taken relative to internal time (DLMO, for example) where feasible. Related to this, chronotype classifies individuals into morning or evening types according to their preference for when to be active and when to sleep. Where laboratory measures of internal time are impractical, chronotype can be estimated by simple questionnaires such as the Morningness–Eveningness Questionnaire and the Munich Chronotype Questionnaire Test( Reference Horne and Ostberg 115 , Reference Roenneberg, Wirz-Justice and Merrow 116 ). As chronotype influences the times at which various physiological processes are optimised, consideration of chronotype will be important for personalised nutrition recommendations. Recent studies have also begun exploring how clock gene SNP may influence responses to dietary interventions( Reference Garcia-Rios, Gomez-Delgado and Garaulet 117 ), and ultimately knowledge of circadian system gene variants may also help inform personalised nutrition.

Pressing questions remain unanswered, and there is a glaring need for human studies addressing these. Regarding eating patterns, whether TRF can accelerate entrainment in populations experiencing circadian disruption is a question of relevance to many. With respect to specific foods and supplements, are there dietary interventions with consistently beneficial effects on sleep? It is known that the composition of human breast milk varies daily( Reference Illnerova, Buresova and Presl 118 ), and perhaps infant formulae should reflect this.

Continuing collaboration between chronobiologists and nutritionists will further clarify interactions between nutrition and the circadian system, and ultimately has the potential to reduce the prevalence and burden of chronic diseases.

Acknowledgements

G. D. M. P. is supported by a Medical Research Council Doctoral Training Grant. P. J. G. is supported by a EuRhythDia grant (number 278397). J. E. C. and L. J. H. are supported by a Medical Research Council grant (number G1100235/1).

G. D. M. P. wrote the manuscript; J. E. C., P. J. G. and L. J. H. provided constructive feedback at all stages of its preparation.

The authors declare that there are no conflicts of interest.

References

1. Bass, J & Takahashi, JS (2010) Circadian integration of metabolism and energetics. Science 330, 13491354.Google Scholar
2. Xu, K, DiAngelo, JR, Hughes, ME, et al. (2011) The circadian clock interacts with metabolic physiology to influence reproductive fitness. Cell Metab 13, 639654.Google Scholar
3. Loh, DH, Jami, SA, Flores, RE, et al. (2015) Misaligned feeding impairs memories. Elife 4, e09460.CrossRefGoogle ScholarPubMed
4. Arble, DM, Bass, J, Laposky, AD, et al. (2009) Circadian timing of food intake contributes to weight gain. Obesity (Silver Spring) 17, 21002102.CrossRefGoogle ScholarPubMed
5. Mukherji, A, Kobiita, A, Damara, M, et al. (2015) Shifting eating to the circadian rest phase misaligns the peripheral clocks with the master SCN clock and leads to a metabolic syndrome. Proc Natl Acad Sci U S A 112, E6691E6698.Google Scholar
6. Bray, MS, Ratcliffe, WF, Grenett, MH, et al. (2013) Quantitative analysis of light-phase restricted feeding reveals metabolic dyssynchrony in mice. Int J Obes (Lond) 37, 843852.CrossRefGoogle ScholarPubMed
7. Damiola, F, Le Minh, N, Preitner, N, et al. (2000) Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes Dev 14, 29502961.CrossRefGoogle ScholarPubMed
8. Boulos, Z, Rosenwasser, AM & Terman, M (1980) Feeding schedules and the circadian organization of behavior in the rat. Behav Brain Res 1, 3965.CrossRefGoogle ScholarPubMed
9. Chaix, A, Zarrinpar, A, Miu, P, et al. (2014) Time-restricted feeding is a preventative and therapeutic intervention against diverse nutritional challenges. Cell Metab 20, 9911005.CrossRefGoogle ScholarPubMed
10. Moreno, CR, Vasconcelos, S, Marqueze, EC, et al. (2015) Sleep patterns in Amazon rubber tappers with and without electric light at home. Sci Rep 5, 14074.CrossRefGoogle ScholarPubMed
11. Sack, RL, Auckley, D, Auger, RR, et al. (2007) Circadian rhythm sleep disorders: part I, basic principles, shift work and jet lag disorders. An American Academy of Sleep Medicine review. Sleep 30, 14601483.Google Scholar
12. Ralph, MR, Foster, RG, Davis, FC, et al. (1990) Transplanted suprachiasmatic nucleus determines circadian period. Science 247, 975978.CrossRefGoogle ScholarPubMed
13. Silver, R, LeSauter, J, Tresco, PA, et al. (1996) A diffusible coupling signal from the transplanted suprachiasmatic nucleus controlling circadian locomotor rhythms. Nature 382, 810813.Google Scholar
14. Welsh, DK, Takahashi, JS & Kay, SA (2010) Suprachiasmatic nucleus: cell autonomy and network properties. Annu Rev Physiol 72, 551577.Google Scholar
15. Partch, CL, Green, CB & Takahashi, JS (2014) Molecular architecture of the mammalian circadian clock. Trends Cell Biol 24, 9099.Google Scholar
16. Patel, VR, Ceglia, N, Zeller, M, et al. (2015) The pervasiveness and plasticity of circadian oscillations: the coupled circadian-oscillators framework. Bioinformatics 31, 31813188.CrossRefGoogle ScholarPubMed
17. Reddy, AB, Karp, NA, Maywood, ES, et al. (2006) Circadian orchestration of the hepatic proteome. Curr Biol 16, 11071115.Google Scholar
18. Eckel-Mahan, KL, Patel, VR, Mohney, RP, et al. (2012) Coordination of the transcriptome and metabolome by the circadian clock. Proc Natl Acad Sci U S A 109, 55415546.Google Scholar
19. Cardone, L, Hirayama, J, Giordano, F, et al. (2005) Circadian clock control by SUMOylation of BMAL1. Science 309, 13901394.Google Scholar
20. Zhang, R, Lahens, NF, Ballance, HI, et al. (2014) A circadian gene expression atlas in mammals: implications for biology and medicine. Proc Natl Acad Sci U S A 111, 1621916224.Google Scholar
21. Asher, G, Reinke, H, Altmeyer, M, et al. (2010) Poly(ADP-ribose) polymerase 1 participates in the phase entrainment of circadian clocks to feeding. Cell 142, 943953.CrossRefGoogle ScholarPubMed
22. Hirayama, J, Sahar, S, Grimaldi, B, et al. (2007) CLOCK-mediated acetylation of BMAL1 controls circadian function. Nature 450, 10861090.Google Scholar
23. O’Neill, JS, van Ooijen, G, Dixon, LE, et al. (2011) Circadian rhythms persist without transcription in a eukaryote. Nature 469, 554558.Google Scholar
24. Czeisler, CA, Duffy, JF, Shanahan, TL, et al. (1999) Stability, precision, and near-24-hour period of the human circadian pacemaker. Science 284, 21772181.CrossRefGoogle ScholarPubMed
25. Berson, DM, Dunn, FA & Takao, M (2002) Phototransduction by retinal ganglion cells that set the circadian clock. Science 295, 10701073.Google Scholar
26. Moore, RY (1996) Neural control of the pineal gland. Behav Brain Res 73, 125130.Google Scholar
27. Zawilska, JB, Skene, DJ & Arendt, J (2009) Physiology and pharmacology of melatonin in relation to biological rhythms. Pharmacol Rep 61, 383410.Google Scholar
28. Kramer, A, Yang, FC, Snodgrass, P, et al. (2003) Regulation of daily locomotor activity and sleep by hypothalamic EGF receptor signalling. Science 294, 25112515.Google Scholar
29. Cheng, MY, Bullock, CM, Li, C, et al. (2002) Prokineticin 2 transmits the behavioural circadian rhythm of the suprachiasmatic nucleus. Nature 417, 405410.Google Scholar
30. Kraves, S & Weitz, CJ (2006) A role for cardiotrophin-like cytokine in the circadian control of mammalian locomotor activity. Nat Neurosci 9, 212219.Google Scholar
31. Kalsbeek, A, van Heerikhuize, JJ, Wortel, J, et al. (1996) A diurnal rhythm of stimulatory input to the hypothalamo-pituitary-adrenal system as revealed by timed intrahypothalamic administration of the vasopressin V1 antagonist. J Neurosci 16, 55555565.Google Scholar
32. Reddy, AB, Maywood, ES, Karp, NA, et al. (2007) Glucocorticoid signaling synchronizes the liver circadian transcriptome. Hepatology 45, 14781488.Google Scholar
33. Buhr, ED, Yoo, SH & Takahashi, JS (2010) Temperature as a universal resetting cue for mammalian circadian oscillators. Science 330, 379385.Google Scholar
34. Goo, RH, Moore, JG, Greenberg, E, et al. (1987) Circadian variation in gastric emptying of meals in humans. Gastroenterology 93, 515518.Google Scholar
35. Rao, SS, Sadeghi, P, Beaty, J, et al. (2001) Ambulatory 24-h colonic manometry in healthy humans. Am J Physiol Gastrointest Liver Physiol 280, G629G639.Google Scholar
36. Han, SS, Zhang, R, Jain, R, et al. (2015) Circadian control of bile acid synthesis by a KLF15-Fgf15 axis. Nat Commun 6, 7231.Google Scholar
37. Hussain, MM & Pan, X (2015) Circadian regulation of macronutrient absorption. J Biol Rhythms 30, 459469.Google Scholar
38. Thaiss, CA, Zeevi, D, Levy, M, et al. (2014) Transkingdom control of microbiota diurnal oscillations promotes metabolic homeostasis. Cell 159, 514529.Google Scholar
39. Liang, X, Bushman, FD & FitzGerald, GA (2015) Rhythmicity of the intestinal microbiota is regulated by gender and the host circadian clock. Proc Natl Acad Sci U S A 112, 1047910484.Google Scholar
40. Leone, V, Gibbons, SM, Martinez, K, et al. (2015) Effects of diurnal variation of gut microbes and high-fat feeding on host circadian clock function and metabolism. Cell Host Microbe 17, 681689.Google Scholar
41. Morgan, L, Arendt, J, Owens, D, et al. (1998) Effects of the endogenous clock and sleep time on melatonin, insulin, glucose and lipid metabolism. J Endocrinol 157, 443451.CrossRefGoogle ScholarPubMed
42. Tanabe, K, Kitagawa, E, Wada, M, et al. (2015) Antigen exposure in the late light period induces severe symptoms of food allergy in an OVA-allergic mouse model. Sci Rep 5, 14424.Google Scholar
43. Scheer, FA, Hilton, MF, Mantzoros, CS, et al. (2009) Adverse metabolic and cardiovascular consequences of circadian misalignment. Proc Natl Acad Sci U S A 106, 44534458.Google Scholar
44. Scheer, FA, Morris, CJ & Shea, SA (2013) The internal circadian clock increases hunger and appetite in the evening independent of food intake and other behaviors. Obesity (Silver Spring) 21, 421423.Google Scholar
45. Morris, CJ, Garcia, JI, Myers, S, et al. (2015) The human circadian system has a dominating role in causing the morning/evening difference in diet-induced thermogenesis. Obesity (Silver Spring) 23, 20532058.Google Scholar
46. Stokkan, KA, Yamazaki, S, Tei, H, et al. (2001) Entrainment of the circadian clock in the liver by feeding. Science 291, 490493.Google Scholar
47. Zvonic, S, Ptitsyn, AA, Conrad, SA, et al. (2006) Characterization of peripheral circadian clocks in adipose tissues. Diabetes 55, 962970.CrossRefGoogle ScholarPubMed
48. Hoogerwerf, WA, Hellmich, HL, Cornelissen, G, et al. (2007) Clock gene expression in the murine gastrointestinal tract: endogenous rhythmicity and effects of a feeding regimen. Gastroenterology 133, 12501260.Google Scholar
49. Saini, C, Liani, A, Curie, T, et al. (2013) Real-time recording of circadian liver gene expression in freely moving mice reveals the phase-setting behavior of hepatocyte clocks. Genes Dev 27, 15261536.Google Scholar
50. Mendoza, J, Graff, C, Dardente, H, et al. (2005) Feeding cues alter clock gene oscillations and photic responses in the suprachiasmatic nuclei of mice exposed to a light/dark cycle. J Neurosci 25, 15141522.Google Scholar
51. Krauchi, K, Cajochen, C, Werth, E, et al. (2002) Alteration of internal circadian phase relationships after morning versus evening carbohydrate-rich meals in humans. J Biol Rhythms 17, 364376.Google Scholar
52. Eckel-Mahan, K & Sassone-Corsi, P. (2013) Metabolism and the circadian clock converge. Physiol Rev 93, 107135.CrossRefGoogle ScholarPubMed
53. Lamia, KA, Sachdeva, UM, DiTacchio, L, et al. (2009) AMPK regulates the circadian clock by cryptochrome phosphorylation and degradation. Science 326, 437440.CrossRefGoogle ScholarPubMed
54. Asher, G, Gatfield, D, Stratmann, M, et al. (2008) SIRT1 regulates circadian clock gene expression through PER2 deacetylation. Cell 134, 317328.Google Scholar
55. Orozco-Solis, R, Ramadori, G, Coppari, R, et al. (2015) SIRT1 relays nutritional inputs to the circadian clock through the sf1 neurons of the ventromedial hypothalamus. Endocrinology 156, 21742184.Google Scholar
56. Masri, S, Rigor, P, Cervantes, M, et al. (2014) Partitioning circadian transcription by SIRT6 leads to segregated control of cellular metabolism. Cell 158, 659672.Google Scholar
57. Paschos, GK, Ibrahim, S, Song, WL, et al. (2012) Obesity in mice with adipocyte-specific deletion of clock component Arntl. Nat Med 18, 17681777.Google Scholar
58. Turek, FW, Joshu, C, Kohsaka, A, et al. (2005) Obesity and metabolic syndrome in circadian clock mutant mice. Science 308, 10431045.Google Scholar
59. Patel, SA, Chaudhari, A, Gupta, R, et al. (2015) Circadian clocks govern calorie restriction-mediated life span extension through BMAL1- and IGF-1-dependent mechanisms. FASEB J 30, 16341642.CrossRefGoogle ScholarPubMed
60. Sookoian, S, Castano, G, Gemma, C, et al. (2007) Common genetic variations in clock transcription factor are associated with nonalcoholic fatty liver disease. World J Gastroenterol 13, 42424248.Google Scholar
61. Scott, EM, Carter, AM & Grant, PJ (2008) Association between polymorphisms in the clock gene, obesity and the metabolic syndrome in man. Int J Obes (Lond) 32, 658662.Google Scholar
62. Tsuzaki, K, Kotani, K, Sano, Y, et al. (2010) The association of the Clock 3111 T/C SNP with lipids and lipoproteins including small dense low-density lipoprotein: results from the Mima study. BMC Med Genet 11, 150.Google Scholar
63. Sookoian, S, Gemma, C, Gianotti, TF, et al. (2008) Genetic variants of clock transcription factor are associated with individual susceptibility to obesity. Am J Clin Nutr 87, 16061615.Google Scholar
64. Uemura, H, Katsuura-Kamano, S, Yamaguchi, M, et al. (2015) A variant of the CLOCK gene and related haplotypes are associated with the prevalence of type 2 diabetes in the Japanese population. J Diabetes (epublication ahead of print version 16 September 2015).Google Scholar
65. Valladares, M, Obregon, AM & Chaput, JP (2015) Association between genetic variants of the clock gene and obesity and sleep duration. J Physiol Biochem 71, 855860.Google Scholar
66. Stephan, FK, Swann, JM & Sisk, CL (1979) Anticipation of 24-hr feeding schedules in rats with lesions of the suprachiasmatic nucleus. Behav Neural Biol 25, 346363.Google Scholar
67. Storch, KF & Weitz, CJ (2009) Daily rhythms of food-anticipatory behavioral activity do not require the known circadian clock. Proc Natl Acad Sci U S A 106, 68086813.Google Scholar
68. Mendoza, J, Pevet, P, Felder-Schmittbuhl, MP, et al. (2010) The cerebellum harbors a circadian oscillator involved in food anticipation. J Neurosci 30, 18941904.Google Scholar
69. Landry, GJ, Kent, BA, Patton, DF, et al. (2011) Evidence for time-of-day dependent effect of neurotoxic dorsomedial hypothalamic lesions on food anticipatory circadian rhythms in rats. PLoS ONE 6, e24187.Google Scholar
70. Verwey, M & Amir, S (2009) Food-entrainable circadian oscillators in the brain. Eur J Neurosci 30, 16501657.Google Scholar
71. Gallardo, CM, Darvas, M, Oviatt, M, et al. (2014) Dopamine receptor 1 neurons in the dorsal striatum regulate food anticipatory circadian activity rhythms in mice. Elife 3, e03781.Google Scholar
72. Sutton, GM, Perez-Tilve, D, Nogueiras, R, et al. (2008) The melanocortin-3 receptor is required for entrainment to meal intake. J Neurosci 28, 1294612955.CrossRefGoogle ScholarPubMed
73. LeSauter, J, Hoque, N, Weintraub, M, et al. (2009) Stomach ghrelin-secreting cells as food-entrainable circadian clocks. Proc Natl Acad Sci U S A 106, 1358213587.Google Scholar
74. Kohsaka, A, Laposky, AD, Ramsey, KM, et al. (2007) High-fat diet disrupts behavioral and molecular circadian rhythms in mice. Cell Metab 6, 414421.Google Scholar
75. Hatori, M, Vollmers, C, Zarrinpar, A, et al. (2012) Time-restricted feeding without reducing caloric intake prevents metabolic diseases in mice fed a high-fat diet. Cell Metab 15, 848860.Google Scholar
76. Pivovarova, O, Gogebakan, O, Sucher, S, et al. (2016) Regulation of the clock genes expression in human adipose tissue by the weight loss. Int J Obes (Lond) (epublication ahead of print version 23 February 2016).Google Scholar
77. Matkovic, V, Ilich, JZ, Badenhop, NE, et al. (1997) Gain in body fat is inversely related to the nocturnal rise in serum leptin level in young females. J Clin Endocrinol Metab 82, 13681372.Google Scholar
78. Eckel-Mahan, KL, Patel, VR, de Mateo, S, et al. (2013) Reprogramming of the circadian clock by nutritional challenge. Cell 155, 14641478.Google Scholar
79. Zarrinpar, A, Chaix, A, Yooseph, S, et al. (2014) Diet and feeding pattern affect the diurnal dynamics of the gut microbiome. Cell Metab 20, 10061017.CrossRefGoogle ScholarPubMed
80. Gill, S & Panda, S. (2015) A smartphone app reveals erratic diurnal eating patterns in humans that can be modulated for health benefits. Cell Metab 22, 789798.Google Scholar
81. Carlson, O, Martin, B, Stote, KS, et al. (2007) Impact of reduced meal frequency without caloric restriction on glucose regulation in healthy, normal-weight middle-aged men and women. Metabolism 56, 17291734.Google Scholar
82. Stote, KS, Baer, DJ, Spears, K, et al. (2007) A controlled trial of reduced meal frequency without caloric restriction in healthy, normal-weight, middle-aged adults. Am J Clin Nutr 85, 981988.Google Scholar
83. Dhurandhar, EJ, Dawson, J, Alcorn, A, et al. (2014) The effectiveness of breakfast recommendations on weight loss: a randomized controlled trial. Am J Clin Nutr 100, 507513.Google Scholar
84. Betts, JA, Richardson, JD, Chowdhury, EA, et al. (2014) The causal role of breakfast in energy balance and health: a randomized controlled trial in lean adults. Am J Clin Nutr 100, 539547.Google Scholar
85. Chowdhury, EA, Richardson, JD, Holman, GD, et al. (2016) The causal role of breakfast in energy balance and health: a randomized controlled trial in obese adults. Am J Clin Nutr 103, 747756.Google Scholar
86. Toh, KL, Jones, CR, He, Y, et al. (2001) An hPer2 phosphorylation site mutation in familial advanced sleep phase syndrome. Science 291, 10401043.CrossRefGoogle ScholarPubMed
87. Liu, Z, Huang, M, Wu, X, et al. (2014) PER1 phosphorylation specifies feeding rhythm in mice. Cell Rep 7, 15091520.Google Scholar
88. Bogdan, A, Bouchareb, B & Touitou, Y (2001) Ramadan fasting alters endocrine and neuroendocrine circadian patterns. Meal-time as a synchronizer in humans? Life Sci 68, 16071615.Google Scholar
89. Sadeghirad, B, Motaghipisheh, S, Kolahdooz, F, et al. (2014) Islamic fasting and weight loss: a systematic review and meta-analysis. Public Health Nutr 17, 396406.Google Scholar
90. Bray, MS, Tsai, JY, Villegas-Montoya, C, et al. (2010) Time-of-day-dependent dietary fat consumption influences multiple cardiometabolic syndrome parameters in mice. Int J Obes (Lond) 34, 15891598.Google Scholar
91. Morris, M, Araujo, IC, Pohlman, RL, et al. (2012) Timing of fructose intake: an important regulator of adiposity. Clin Exp Pharmacol Physiol 39, 5762.Google Scholar
92. Jakubowicz, D, Barnea, M, Wainstein, J, et al. (2013) High caloric intake at breakfast vs. dinner differentially influences weight loss of overweight and obese women. Obesity (Silver Spring) 21, 25042512.CrossRefGoogle ScholarPubMed
93. Garaulet, M, Gomez-Abellan, P, Alburquerque-Bejar, JJ, et al. (2013) Timing of food intake predicts weight loss effectiveness. Int J Obes (Lond) 37, 604611.Google Scholar
94. Ruiz-Lozano, T, Vidal, J, de Hollanda, A, et al. (2016) Timing of food intake is associated with weight loss evolution in severe obese patients after bariatric surgery. Clin Nutr (epublication ahead of print version 16 February 2016).Google Scholar
95. Oike, H, Sakurai, M, Ippoushi, K, et al. (2015) Time-fixed feeding prevents obesity induced by chronic advances of light/dark cycles in mouse models of jet-lag/shift work. Biochem Biophys Res Commun 465, 556561.Google Scholar
96. Halberg, N, Henriksen, M, Soderhamn, N, et al. (2005) Effect of intermittent fasting and refeeding on insulin action in healthy men. J Appl Physiol (1985) 99, 21282136.Google Scholar
97. Yanagihara, H, Ando, H, Hayashi, Y, et al. (2006) High-fat feeding exerts minimal effects on rhythmic mRNA expression of clock genes in mouse peripheral tissues. Chronobiol Int 23, 905914.Google Scholar
98. Oishi, K, Uchida, D & Itoh, N (2012) Low-carbohydrate, high-protein diet affects rhythmic expression of gluconeogenic regulatory and circadian clock genes in mouse peripheral tissues. Chronobiol Int 29, 799809.Google Scholar
99. Pivovarova, O, Jurchott, K, Rudovich, N, et al. (2015) Changes of dietary fat and carbohydrate content alter central and peripheral clock in humans. J Clin Endocrinol Metab 100, 22912302.Google Scholar
100. Greco, JA, Oosterman, JE & Belsham, DD. (2014) Differential effects of omega-3 fatty acid docosahexaenoic acid and palmitate on the circadian transcriptional profile of clock genes in immortalized hypothalamic neurons. Am J Physiol Regul Integr Comp Physiol 307, R1049R1060.Google Scholar
101. Furutani, A, Ikeda, Y, Itokawa, M, et al. (2015) Fish oil accelerates diet-induced entrainment of the mouse peripheral clock via GPR120. PLOS ONE 10, e0132472.Google Scholar
102. Huang, MC, Ho, CW, Chen, CH, et al. (2010) Reduced expression of circadian clock genes in male alcoholic patients. Alcohol Clin Exp Res 34, 18991904.Google Scholar
103. Ando, H, Ushijima, K, Kumazaki, M, et al. (2010) Associations of metabolic parameters and ethanol consumption with messenger RNA expression of clock genes in healthy men. Chronobiol Int 27, 194203.Google Scholar
104. Filiano, AN, Millender-Swain, T, Johnson, R Jr., et al. (2013) Chronic ethanol consumption disrupts the core molecular clock and diurnal rhythms of metabolic genes in the liver without affecting the suprachiasmatic nucleus. PLOS ONE 8, e71684.CrossRefGoogle ScholarPubMed
105. Conroy, DA, Hairston, IS, Arnedt, JT, et al. (2012) Dim light melatonin onset in alcohol-dependent men and women compared with healthy controls. Chronobiol Int 29, 3542.Google Scholar
106. Brager, AJ, Ruby, CL, Prosser, RA, et al. (2010) Chronic ethanol disrupts circadian photic entrainment and daily locomotor activity in the mouse. Alcohol Clin Exp Res 34, 12661273.Google Scholar
107. Sherman, H, Gutman, R, Chapnik, N, et al. (2011) Caffeine alters circadian rhythms and expression of disease and metabolic markers. Int J Biochem Cell Biol 43, 829838.Google Scholar
108. Burke, TM, Markwald, RR, McHill, AW, et al. (2015) Effects of caffeine on the human circadian clock in vivo and in vitro . Sci Transl Med 7, 305ra146.Google Scholar
109. Pierard, C, Beaumont, M, Enslen, M, et al. (2001) Resynchronization of hormonal rhythms after an eastbound flight in humans: effects of slow-release caffeine and melatonin. Eur J Appl Physiol 85, 144150.Google Scholar
110. Beaumont, M, Batejat, D, Pierard, C, et al. (2004) Caffeine or melatonin effects on sleep and sleepiness after rapid eastward transmeridian travel. J Appl Physiol (1985) 96, 5058.Google Scholar
111. St Hilaire, MA & Lockley, SW (2015) Caffeine does not entrain the circadian clock but improves daytime alertness in blind patients with non-24-hour rhythms. Sleep Med 16, 800804.Google Scholar
112. Ribas-Latre, A, Baselga-Escudero, L, Casanova, E, et al. (2015) Dietary proanthocyanidins modulate BMAL1 acetylation, Nampt expression and NAD levels in rat liver. Sci Rep 5, 10954.Google Scholar
113. Pifferi, F, Dal-Pan, A, Menaker, M, et al. (2011) Resveratrol dietary supplementation shortens the free-running circadian period and decreases body temperature in a prosimian primate. J Biol Rhythms 26, 271275.Google Scholar
114. Zwighaft, Z, Aviram, R, Shalev, M, et al. (2015) Circadian clock control by polyamine levels through a mechanism that declines with age. Cell Metab 22, 874885.Google Scholar
115. Horne, JA & Ostberg, O (1976) A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int J Chronobiol 4, 97110.Google ScholarPubMed
116. Roenneberg, T, Wirz-Justice, A & Merrow, M (2003) Life between clocks: daily temporal patterns of human chronotypes. J Biol Rhythms 18, 8090.Google Scholar
117. Garcia-Rios, A, Gomez-Delgado, FJ, Garaulet, M, et al. (2014) Beneficial effect of CLOCK gene polymorphism rs1801260 in combination with low-fat diet on insulin metabolism in the patients with metabolic syndrome. Chronobiol Int 31, 401408.Google Scholar
118. Illnerova, H, Buresova, M & Presl, J (1993) Melatonin rhythm in human milk. J Clin Endocrinol Metab 77, 838841.Google Scholar
Figure 0

Fig. 1 The mammalian circadian clock. The molecular clock consists of ‘clock’ genes that form negative-feedback loops. The transcription factors circadian locomotor output cycles kaput (CLOCK) and brain and muscle aryl hydrocarbon receptor nuclear translocator-like 1 (BMAL1) heterodimerise and activate clock-controlled genes (CCG). On activation by CLOCK-BMAL1, cryptochrome (CRY) 1–2 and period (PER) 1–3 proteins accumulate in the cytosol, multimerise and translocate into the nucleus and form inhibitory complexes, repressing CLOCK-BMAL1 and terminating CRY1–2 and PER1–3 transcription during the rest phase. As the rest phase progresses, PER-CRY complexes are degraded by F-box/LRR-repeat protein 3 (FBXL3), casein kinase 1 (CK1) ε and CK1δ. Inhibition of CLOCK-BMAL1 activity ends, completing the negative feedback loop. Auxiliary feedback loops are antiphasic to the core loop and regulate BMAL1 transcription. The nuclear receptors reverse-erythroblastosis (REV-ERB) α and β repress BMAL1 transcription, whereas RAR-related orphan receptor (ROR) α activates BMAL1 transcription. Auxiliary feedback loops add robustness, among other roles.