Chrononutrition: Potential, Challenges, and Application in Managing Obesity

The mammalian circadian system is hierarchically organized, with the SCN functioning as the central “master clock” [1,3]. This master oscillator synchronizes molecular clocks in peripheral tissues, ensuring coordinated phase alignment throughout the body. Light acts as the dominant zeitgeber, maintaining the SCN’s ~24 h rhythm. Intrinsically, photosensitive retinal ganglion cells in the retina, which express melanopsin, detect environmental light and relay signals to the SCN via the retinohypothalamic tract (RHT) that facilitates adaptation to the external light–dark cycle.

The RHT plays a critical role in entraining the circadian system by transmitting photic signals directly to a subset of SCN neurons, particularly those located in the ventrolateral (core) region [18]. These neurons respond to glutamate and pituitary adenylate cyclase-activating polypeptide (PACAP), the primary neurotransmitters released by the RHT terminals. Upon light stimulation, these excitatory signals activate intracellular signaling cascades, including calcium influx and phosphorylation of CREB (cAMP response element-binding protein), which in turn modulates the expression of clock genes such as Per1 and Per2 [19,20]. This rapid gene induction enables the SCN to adjust its phase in response to changes in light exposure, forming the molecular basis of photic entrainment.

The timing and intensity of light input through the RHT are crucial, as they determine whether the clock is advanced or delayed [21,22]. For example, light exposure in the early subjective night typically delays the circadian phase, while light during the late night induces phase advances [23,24]. This bidirectional phase-shifting capacity allows the SCN to align internal rhythms with the external environment and maintain temporal homeostasis. Disruption in RHT signaling—whether due to retinal damage, altered light environments, or aging—can impair SCN entrainment and lead to downstream circadian misalignment in peripheral tissues [25,26,27,28]. By integrating environmental light cues through the RHT, the SCN is able to regulate the timing of behavioral and physiological processes, such as sleep–wake cycles, feeding, hormone secretion, and body temperature, thereby orchestrating systemic circadian harmony.

At the molecular level in the SCN, clock genes form the core of the transcriptional–translational feedback loop (TTFL) that operates the circadian oscillator [2]. The core loop is driven by the heterodimeric complex of CLOCK and BMAL1, which binds to E-box elements in the promoter regions of target genes, activating the transcription of core clock genes, such as Period (Per1, Per2, and Per3) and Cryptochrome (Cry1, and Cry2) [2]. The resulting PER and CRY proteins accumulate in the cytoplasm, undergo post-translational modifications (e.g., phosphorylation) and form complexes that translocate to the nucleus. Within the nucleus, these complexes inhibit CLOCK-BMAL1 activity, forming a negative feedback loop that reduces their own transcription. As PER and CRY proteins gradually degrade, repression is lifted, and a new cycle begins, completing the ~24 h oscillation. To add robustness to this system, an auxiliary loop regulates Bmal1 expression. Nuclear receptors REV-ERBα/β and RORα/γ compete for binding to ROR response elements (ROREs) in the Bmal1 promoter [1,2]. REV-ERBs act as transcriptional repressors, while RORs act as activators, creating a balance that fine tunes the oscillatory dynamics of Bmal1 and, thus, the activity of the core loop. Beyond these core and auxiliary loops, PAR-bZIP transcription factors DBP and the repressor NFIL3 play a crucial role in an additional feedback mechanism called the accessory loop. Through binding to D-boxes, both DBP and NFIL3 integrate circadian control with downstream physiological processes (Figure 1). This multi-tiered regulation of central clock genes not only ensures precision and robustness of circadian rhythms but also allows dynamic adaptability to external cues, such as light and feeding, while coordinating a wide array of physiological processes.

Beyond the master clock in the SCN, nearly all cells in the body host independent, self-sustaining clock regulatory systems as described in Figure 1 [1,2,3,7]. Through the modulation of core body temperature, autonomic nervous system signals, and endocrine signaling, including glucocorticoids and melatonin secretion, the SCN creates systemic rhythmic signals that reinforce the alignment of peripheral clocks [29,30,31]. Peripheral clocks, influenced by SCN-generated signals, regulate metabolic pathways and nutrient utilization, with oscillations in metabolites observed across tissues and blood plasma (Figure 2). Disruption of master and/or peripheral clock function abolishes the rhythmic patterns in activity and feeding behavior, resulting in a loss of metabolic rhythmicity and imbalance in energy expenditure, highlighting the essential interaction between central and peripheral clocks in maintaining metabolic equilibrium [30,32]. As tissue evolves to perform specialized functions, the importance of different environmental cues as zeitgebers adjust to match the specific demands of those functions, underscoring the tissue-specific roles of circadian rhythms in regulating metabolic and physiological functions, as exemplified by key peripheral systems such as adipose tissue, liver, skeletal muscle, and gut microbiota [1,3,7].

Adipose tissue was initially recognized as an energy storage tissue, but it is currently known to have an endocrine function by secreting various factors, referred to as adipokines, and a thermogenic function [33,34,35]. The expression of clock genes, such as Bmal1, Per1, Per2, Per3, Cry1, and Cry2, and clock-controlled downstream genes, such as Rev-erbα and Rev-erbβ, show 24 h rhythmicity in inguinal white adipose tissue (iWAT), epididymal white adipose tissue (eWAT), and brown adipose tissue (BAT). Furthermore, the rhythmicity of the clock genes or adipokines in perigonadal adipose tissue is attenuated in obese mice [36,37,38]. Alteration of the adipocyte clock function leads to shifts in the timing of plasma polyunsaturated fatty acid levels, which subsequently influence the expression of neurotransmitters involved in appetite regulation within hypothalamic feeding centers [37]. These effects arise independently of changes in the rhythmic activity of circadian clock genes, such as Bmal1, within the hypothalamus, indicating that the adipocyte circadian clock directly influences hypothalamic feeding centers, without involvement from the local hypothalamic clocks [39]. Another study demonstrated that leptin expression in the adipose tissue is regulated by BMAL1/CLOCK-modulated binding of C/EBPα to the leptin promoter, resulting in the rhythmic transcription of leptin in adipose tissue and the circulating system, independently of food intake [40]. Leptin is an adipose tissue signature adipokine, acting as a strong inhibitor of appetite in the hypothalamus, and leptin resistance is commonly developed in obese subjects [41,42].

Modulation of clock genes has been shown to have a causal role in regulating adipose tissue function [37]. A study by Nam et al. showed that deletion of BMAL1 induced brown adipocyte differentiation [43]. They demonstrated that aP2-Cre Bmal1^flox/flox mice showed reduced obesity-induced whitening of BAT and lost more weight during the 24 h cold tolerance test compared to their littermate controls. However, despite this, Bmal1-deficient mice exhibited increased food intake and developed obesity when fed a chow diet [24]. It was also reported that depletion of BMAL1 from the adipose tissue using Adipoq-Cre mice model resulted in a significant increase in adipocyte size in eWAT without inducing adipose tissue inflammation [44]. These findings indicate that the function of clock genes varies depending on the adipose tissue types.

Chronic inflammation within white adipose tissue, marked by a shift toward production of pro-inflammatory adipokines, is central in the progression of obesity-induced systemic metabolic dysfunction [45,46]. Clock genes are known to regulate immune cell responses. REV-ERBα was demonstrated to repress Ccl2 expression by directly binding the Ccl2 promoter region [45]. CCL2 expression is known to be upregulated in obese mice, responsible for the recruitment of other immune cells [46,47]. In addition, myeloid cell-specific deletion of Per1 and Per2 mice showed an increase in body weight and visceral adipose tissue weight, as well as worsening adipose tissue inflammation and insulin resistance [48]. These findings indicate that clock genes play a role in preserving the homeostasis of adipose tissue.

The liver is a key organ in systemic metabolism, responsible for storing glycogen, synthesizing proteins, secreting hormones, and detoxification [49,50]. In mammals, the liver’s transcriptome and proteome exhibit rhythmic regulation driven by direct circadian control, along with cyclic modulation of nuclear transport and post-translational modifications [51,52]. As a key regulator of metabolic functions, the liver clock is influenced by dietary composition. For instance, an obesogenic diet significantly disrupts the rhythmic expression of thousands of liver genes [53,54]. Moreover, ketogenic diets amplify BMAL1 binding to chromatin and enhance the rhythmic activity of PPARα signaling in the liver [55]. On the other hand, acute alcohol drinks induce the rhythmic and expression level of the SREBP1 pathway, whereas chronic alcohol drinks suppress it [56,57,58]. These findings highlight how dietary factors and substance intake can distinctly modulate circadian regulatory pathways in the liver.

The disruption of specific clock genes in the liver has profound effects on the regulation of metabolic pathways. Liver-specific Bmal1-knockout resulted in arrhythmic expression of glucose regulatory genes and exacerbated glucose clearance [59,60]. Another study demonstrated that liver-specific Bmal1-knockout led to elevated plasma levels of low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) cholesterol, attributed to disruptions in the proprotein convertase subtilisin/kexin type 9 (PSCK9) and LDL receptor regulatory pathway [61]. Furthermore, deleting BMAL1 in the liver reduced the rhythmic expression of retinol-binding protein-4, which has been linked to insulin resistance, followed by enhanced systemic insulin sensitivity [62,63]. In response to fasting conditions, CRY1 and CRY2 inhibit cAMP-responsive element-binding protein (CREB) signaling in the liver by modulating G protein-coupled receptors and the stimulatory G-protein α-subunit [64,65]. Furthermore, the nuclear receptor REV-ERBα regulates the liver’s daily activation of SREBP-1C, which subsequently controls the expression of genes involved in hepatic cholesterol and lipid metabolism [66].

Skeletal muscle constitutes approximately 40% of body mass, playing a crucial role in locomotion, maintaining posture, and serving as a key metabolic organ involved in basal metabolism, glucose utilization, and fatty acid oxidation [67]. Given its significant contribution to systemic energy homeostasis, skeletal muscle has emerged as a promising therapeutic target for the prevention and treatment of metabolic diseases. A DNA microarray study by McCarthy et al. revealed 215 circadian genes in mouse skeletal muscle, with nearly 40% showing peak expression during the middle of the active (dark) phase [68]. Separately, four weeks of forced treadmill exercise during the inactive (light) phase shifted the circadian phase of bioluminescence rhythms in the skeletal muscle of PER2-Luciferase knock-in mice by three hours, while the SCN’s timing remained unchanged [69], indicating that exercise is a zeitgeber cue for skeletal muscle clocks that is independent of the SCN.

Several studies have tried to uncover the importance of the molecular clock for maintaining skeletal muscle homeostasis. Bmal1-null and Clk/Clk mutant mice showed dysfunctional mitochondria, reduced muscle force, and disrupted myofilament [70]. Additionally, Bmal1-null mice develop severe sarcopenia at 40 weeks of age [71]. However, it remains possible that the changes observed in the skeletal muscle of Bmal1-null and Clk/Clk mutant mice were indirectly caused by clock gene disruptions in other organs, as the skeletal muscle phenotype is strongly shaped by systemic factors, including hormonal signals and metabolic conditions. By using Mlc1f-Cre Bmal1^flox/flox mice system, Dyar et al. showed that skeletal muscle-specific KO of Bmal1 mice gain more weight after ~30 weeks of age compared with their littermates, followed by the impairment of insulin-induced glucose uptake by muscle, without systemic glucose metabolic dysfunction [72]. To exclude the influence of Bmal1 deletion on skeletal muscle development and postnatal maturation, Dyar et al. developed a tamoxifen-inducible muscle-specific Bmal1 knockout (im-Bmal1 KO; HSA-Cre-ER Bmal1^flox/flox). They found no alteration in muscle weight and force between two littermates after 5 months (~20 weeks) of tamoxifen administration [72]. In a comparable im-Bmal1 KO model, Schroder et al. observed decreased specific tension and elevated muscle fibrosis following 58 weeks of tamoxifen treatment [73]. The discrepancies between these two studies might be caused by the differences in experimental design, such as the age differences when tamoxifen was injected into the mice and the age of mice when they were analyzed.

The gut microbiota, a diverse ecosystem of microorganisms, including bacteria, fungi, viruses, and archaea, functions as an integral part of the body, interacting closely with major systems, such as the immune, metabolic, and nervous systems. Disruptions in the balance of this microbial community can lead to significant health consequences, promoting the onset of chronic conditions, such as obesity, diabetes, metabolic syndromes, cancer, and autoimmune disorders [74,75,76]. A study by Thaiss et al. demonstrated that around 60% of the microbiota composition oscillates over a 24 h period [77]. Additionally, other studies revealed that, despite the absence of direct light exposure, gut microbes exhibit rhythmic fluctuations in both their population and functionality, driven by diurnal signals from the host [78,79,80]. For instance, Bmal1-null mice ablate the composition and abundance of bacteria in the feces [81]. Additionally, the whole-body knock-out of Per1/Per2 alters the diurnal fluctuation of the gut microbiome, contributing to obesity and glucose intolerance [78]. Simultaneously, gut microbiota may contribute to the alignment of the host’s circadian clock by emitting various natural signaling molecules. Studies have uncovered that in mice lacking gut microbes, antibiotic-treated mice, or germ-free mice, alterations in circadian gene expression and metabolic pathways have been observed, suggesting a possible regulatory role of the gut microbiota on host circadian rhythms [78,79,80]. The gut microbiota influences the host’s circadian clock system through the activity of numerous bacterial metabolites, such as short-chain fatty acids, that have been identified as key players, displaying diurnal fluctuations in their levels [79,80,81,82].

Beyond the molecular difference, the anatomical structure of organisms also plays a fundamental role in regulating biological rhythms, including those governing feeding behavior, metabolism, and energy homeostasis [98,99,100,101]. The differences in organ structure and function between mice and humans lead to variations in how circadian rhythms influence metabolism. Such structures include the digestive system, central clock (SCN and pineal gland), and metabolic organs (liver and adipose tissue) [60,101,102,103,104]. These subsequently determine the way circadian signals regulate nutrient absorption, energy storage, and metabolic rhythms. While the core circadian clock mechanisms are conserved across species, the anatomical differences between mice and humans lead to species-specific metabolic adaptations to meal timing and circadian regulation [101,102,103].

One of the primary anatomical differences affecting circadian metabolic regulation is the structure of the intestines, which influences how nutrients are absorbed and processed in alignment with biological rhythms [105]. In mice, the small intestine is relatively longer, and the cecum is larger, facilitating enhanced microbial fermentation of dietary components. This structure enables stronger rhythmic control of microbial activity. Such features allow the gut microbiome composition to oscillate in a more pronounced manner over the circadian cycle [106]. As a result, microbial metabolites, such as short-chain fatty acids (SCFAs), follow a strong circadian rhythm in mice, impacting systemic metabolic pathways [107].

In contrast, humans have a shorter cecum and a different gut microbiome composition, leading to less pronounced circadian oscillations in microbial activity [106,107]. Instead of relying on fermentation for energy regulation, humans depend more on hepatic metabolic rhythms for glucose and lipid homeostasis [107,108]. At the molecular level, circadian regulation of nutrient absorption in the intestine is controlled by rhythmic expression of genes, such as the sodium–glucose transporter (Sglt1) and peptide transporter (Pept1), which exhibit species-specific variations in circadian patterns [109,110,111]. In mice, glucose absorption peaks during their active (night) phase, whereas in humans, it is most efficient during the early daytime hours, reflecting differences in feeding behavior and metabolic demands. While mice display sharper oscillations in metabolic gene expression based on feeding–fasting cycles, humans integrate a more complex set of cues, including light exposure and social behaviors, to regulate metabolism [112,113].

These anatomical differences provide a foundation for understanding how circadian regulation of metabolism varies between mice and humans. To further critically examine these molecular differences, this section explores the SCN and pineal gland, liver, and adipose tissue, highlighting the species-specific mechanisms that govern circadian metabolic regulation (Table 1).

Despite the limitations of both nocturnal and diurnal animal models, murine studies remain central to preclinical chrononutrition research. These models have provided valuable mechanistic insights, particularly into how core clock genes regulate metabolic processes in response to feeding time. However, determining the translational relevance of these findings requires careful evaluation, as key physiological, behavioral, and environmental differences can significantly affect how these mechanisms manifest in humans (). Table 3

As one of the most widely studied chrononutrition strategies in animal models, TRF has consistently demonstrated strong metabolic benefits—even in the absence of caloric restriction [,,,]. Hatori et al. (2012) showed that TRF prevented obesity, hyperinsulinemia, and hepatic steatosis in high-fat-diet-fed mice, despite identical caloric intake to ad libitum controls []. Mechanistically, TRF in mice enhances BMAL1 and CLOCK binding to metabolic gene promoters, restores oscillatory expression ofandand improves mitochondrial function in liver and adipose tissue [,]. These results suggest direct entrainment of peripheral clocks by feeding time, driving rhythmic metabolic gene expression independently of calorie intake. ^{190 191 195 196 194 6 196} Rev-erbα Pparα,

In contrast, clinical trials in humans have yielded more modest, and often inconsistent, outcomes [,,]. For instance, Sutton et al. (2018) reported that early TRF (eating from 8 a.m. to 2 p.m.) improved insulin sensitivity, blood pressure, and oxidative stress markers in prediabetic men—even without weight loss []. Jamshed et al. (2019) also observed improvements in 24 h glucose profiles and circadian hormone markers following early TRF []. However, these effects are less robust than those seen in mice and are not consistently replicated across studies [,,,,,,,,,]. ^{192 197 198 14 13 6 13 14 191 192 193 195 196 197 198}

These discrepancies underscore a fundamental translation gap. Unlike mice housed under tightly controlled conditions—with uniform light/dark cycles, diet, and genetics—humans are exposed to highly variable environments that interact with circadian and metabolic systems. Human metabolism is further influenced by complex behavioral and hormonal dynamics, including sleep quality, stress, melatonin–cortisol rhythms, and social eating patterns, which are difficult to model in animals [,,]. Moreover, most human trials rely on indirect metabolic outcomes (e.g., glucose, lipid profiles) without assessing circadian gene expression directly [,,,,], making it challenging to verify whether metabolic improvements are truly circadian-driven or behaviorally mediated. ^{93 150 199 13 14 191 192 197}

Ultimately, while murine studies clarify the molecular basis of feeding–fasting rhythms, they oversimplify the context in which human metabolic health unfolds. Bridging this translational divide will require integrating mechanistic findings with human-specific variables through tools such as wearable circadian biomonitoring, tissue-specific metabolic profiling, and behavioral chronotype. Without these, the promise of chrononutrition risks being lost in the complexity of real-world application.

Current chrononutrition studies, mostly conducted in controlled settings, struggle with limitations in self-reported food intake methods, such as 24 h dietary recalls (24HRs), which suffer from memory bias, portion size estimation issues, and interviewer variability. Additionally, the lack of standardized tools for assessing behaviors leads to inconsistent findings, limiting research reliability and broader applicability [200,201,202]. Without universal methods, cultural and population-specific differences limit the generalizability of findings, while clinical applications and integration with emerging technologies remain constrained. This leaves chrononutrition as a field that remains fragmented, with limited impact on global health policies and practical interventions. Developing adaptable, validated tools is crucial to ensure their growth and relevance.

Another key challenge in chrononutrition research is accounting for individual chronotype differences, which profoundly influence their physiological processes, including metabolic activity [213,214,215,216]. Studies have demonstrated that early chronotypes tend to have better glucose tolerance in the morning, while late chronotypes often show delayed peaks in metabolic efficiency [150,203,204]. However, current research struggles to capture these variations comprehensively, as many studies apply uniform meal timing protocols without considering individual circadian preferences. This one-size-fits-all approach introduces significant variability in outcomes and limits the ability to draw generalized conclusions. Additionally, genetic and epigenetic factors, such as variations in circadian clock genes (Clock, Bmal1, Per, and Cry), influence individual responses to meal timing, but research in this area faces challenges due to gene–environmental interactions and limited population diversity. To improve chrononutrition interventions, integrating personalized approaches that consider chronotype, genetic background, and lifestyle factors is crucial for optimizing metabolic health outcomes.

Short-term chrononutrition studies show promising results, but their long-term feasibility is limited due to rigid, clock-based meal definitions that overlook cultural diversity and individual circadian rhythms [217,218,219]. This Western-centric approach reduces the applicability of findings, especially for populations with varied eating patterns, such as late-night dining in Mediterranean regions or dispersed meals in Asian cultures [128,129]. Practical constraints, including work schedules and social obligations, further challenge strict meal timing adherence, making flexible, personalized interventions essential for sustainable dietary strategies [220,221,222,223]. Additionally, while circadian realignment strategies, such as light exposure and melatonin supplementation, show potential, their success depends on adherence and addressing broader societal factors, such as shift work and urbanization, to ensure lasting health benefits [15,16,31,146,224,225].

While methodological inconsistencies, chronotype variability, and long-term feasibility have been widely recognized in chrononutrition research, these limitations often stem from a layer. Such a layer includes the socio-ecological context in which dietary behaviors occur [213,226,227,228,229]. Chrononutrition interventions do not operate in a vacuum; rather, they are shaped by a multilayered network of influences, ranging from individual traits to societal norms. At the individual level, metabolic responses to meal timing are modulated not only by chronotype but also by sleep quality, stress, and occupational demands, all of which are unequally distributed across populations [200,230,231,232,233,234]. At the interpersonal and community levels, cultural meal customs (e.g., evening feasting in Mediterranean cultures or late-night social eating in East Asia), religious fasting practices, and shared family eating routines may conflict with rigid TRF protocols [205,206,207]. At the societal level, structural determinants, such as socioeconomic status (SES), urbanization, and food insecurity, exert profound influence over individuals’ ability to adhere to time-based eating protocols [226,227,228]. Those in lower SES brackets are often subject to irregular work hours, limited food access, and financial constraints that favor calorie-dense, nutrient-poor foods [208,209,210,211]. These conditions not only compromise dietary quality but also lead to erratic meal timing, which directly conflicts with the structured patterns promoted in time-restricted feeding (TRF) interventions. In particular, food insecurity can result in unpredictable eating behaviors driven by availability rather than biological timing [235,236,237]. Thus, undermining circadian alignment and introducing stress-related metabolic disruptions. Likewise, urbanization and shift work promote 24 h lifestyles, increased exposure to artificial light at night, and inconsistent sleep and meal schedules [146,212]. These realities disproportionately affect marginalized populations and are rarely accounted for in clinical study designs, despite their significant impact on adherence and metabolic outcomes [238,239,240,241].

Adding another layer of complexity is the prevalence of Western-centric assumptions in chrononutrition research. Many current protocols are based on ideals of early dinner, consolidated daytime meals, and structured work–rest patterns [238,242,243]. These norms do not reflect the lived experiences of diverse global populations. In regions such as the Mediterranean, Middle East, and parts of Asia, culturally embedded practices often include late-evening meals, irregular eating occasions, or religious fasting patterns [207,244,245,246,247]. Applying rigid, one-size-fits-all TRF protocols in these contexts risks both poor adherence and limited clinical relevance. Moreover, few studies stratify outcomes by cultural background, SES, or occupational demands, making it difficult to generalize findings across populations [248,249,250]. Without explicit integration of behavioral, economic, and cultural contexts, even well-controlled interventions may fail to produce sustainable or equitable outcomes. To truly advance the field, chrononutrition research must adopt socio-ecologically informed frameworks that reflect the diversity of real-world lived experiences. This includes designing adaptable, culturally sensitive, and socioeconomically feasible strategies that can accommodate varying chronotypes, lifestyles, and resource availability. Only by addressing these contextual complexities can chrononutrition fulfill its promise as a globally relevant approach to metabolic health.