How Time-Restricted Eating Relates to the Body's Internal Clock

One of the key underlying elements of metabolic homeostasis is a proper transition between periods of nutrient availability and times of scarcity. In mammals, this balance is maintained by accumulating nutrients during feeding periods and releasing stored nutrients during fasting. Main metabolic tissues, including the liver, adipose, and muscle, play well-established roles in energy intake and utilization (Chadt and Al-Hasani, 2020). Furthermore, the gastrointestinal tract, which is initially impacted by ingested nutrients and, in turn, houses its system (the intestinal microbiome), receives special consideration likewise as an active actor in promoting metabolic balance by regulating nutrient metabolism, immune function, and the production of signaling metabolites (Cox et al., 2022). Disrupted homeostasis is shared in many metabolic diseases that generally converge in patients with obesity, diabetes, dyslipidemia, arterial hypertension, and cardiovascular disease. Obesity and its comorbidities have been progressively arising in the last century until reaching epidemic proportions (Saklayen, 2018). A multifactorial and subject-specific process encompassing several associated pathologies without a definitive cure makes the curve difficult to flatten (Guerra et al., 2021). Under this pessimistic paradigm, effective treatment and prevention are the desired weapons for many researchers and the hope for many current and future patients. The diet itself, in terms of quantity, quality, and, more recently, timing, can take part in both treatment and prevention. In recent years, more and more groups have been transitioning from investigating caloric restriction (CR) diets, characterized by a daily controlled reduction in calorie consumption, to the so-called intermittent fasting (IF) diets without a forced caloric restriction (except for the fasting hours/days). Both approaches provide comparable metabolic benefits. However, time-restricted eating (TRE), a specific type of intermittent fasting (IF), garners increased attention due to its practicality and potential to synchronize more effectively with the participant’s natural sleep–wake cycle. Despite pre-clinical studies demonstrating favorable outcomes, no research has aligned participants’ circadian rhythms with a specific TRE protocol.

Human circadian rhythms are influenced by I) the light/dark cycle, also referred to as the solar clock; II) the social clock, which encompasses all social inputs that entrain human sleep/wake cycles; and III) the biological clock, which is partially determined by genetics and explains individual preferences in the timing of sleep and wake, known as chronotypes (Roenneberg et al., 2003). Chronotypes are primarily assessed through questionnaires that categorize individuals based on their tendencies toward extreme, moderate, or slight levels of ‘morningness,’ ‘eveningness,’ or ‘intermediate’ (Horne and Ostberg, 1976; Roenneberg et al., 2003). However, more robust assessments, such as actigraphy, are necessary to validate these subjective categorizations.

Thus, the main focus of this review will weigh heavily on some of the most recent studies looking at TRE and its different types, as well as the basic knowledge behind steaming from both pre-clinical and clinical studies, which contemplate their biological clock as a critical factor to boost the TRE effectiveness. Furthermore, we will briefly discuss the existing relationships among the microbiota, circadian clock, and TRE, highlighting the microbiota as a factor that can be entrained by both TRE and the circadian clock and vice versa.

Nutrient restriction in the form of CR or IF can improve cardiometabolic outputs by reducing body weight (and fat), levels of LDL cholesterol, blood pressure, inflammation, and oxidative stress, in turn, improving the lean mass index and insulin sensitivity (i.e., lower HOMA-IR index) (James et al., 2024). Although CR aims for a sustainable reduction in caloric intake, IF encompasses a broad range of nutrient-restricted strategies. Among the IF diets, alternate-day fasting (ADF), the 5:2 weekly fasting regimen, and daily TRE are the most commonly utilized and studied approaches (Di Francesco et al., 2018) (Figure 1). The fasting state induced by these interventions induces alterations in lipid metabolism by stimulating lipolysis, increasing fatty acid oxidation, enhancing ketogenesis, suppressing lipogenic enzyme activity, and modifying lipid transport, thereby promoting the utilization of stored fats for energy. ADF is the most restrictive option where feasting and fasting days alternate, evoking a stronger feeling of hunger and, thus, a lower adherence (Trepanowski et al., 2017). In addition, 5:2 fasting can help on that avenue, where out of the 7 days of the week, two freely chosen days are reserved for fasting. Whether the fasting days have to be consecutive is not clear in terms of metabolic benefits, leaving the participant the freedom to choose to reach the maximum level of adherence, which, for this strategy, is indeed inferior to a CR diet (Pannen et al., 2021). For example, a study comparing consecutive 36 vs. 60 fasting hours per week within a 4-week intervention in overweight and obese adults showed a modest influence on the gut microbiome and the plasma metabolome, translating into no clinical differences between the groups (Mohr et al., 2022). However, adding one more week of intervention (5 weeks) showed more significant reductions in body weight and waist circumference with 2 consecutive days of fasting compared to 1 day in overweight adults (Arciero et al., 2022). Yet, understanding the systemic adaptions in humans subjected to extreme caloric restriction is very limited. A recent study employing a 7-day water-only fast has shed light on that. Aside from a remarkable weight loss, such an intervention induced systemic proteome reprogramming, which was already evident from the third day and well-conserved across the 12 participants enrolled in the study, with a signature strongly enriched beyond metabolic adaptions (Pietzner et al., 2024). Finally, TRE becomes the least restrictive option, where restriction of food is time-wise and determined across the day, comprising a wide range of restricted-eating windows (from 4 to 10 h) generally across the human active phase (8 a.m.–8 p.m. in average) (Soliman, 2022).

Interestingly, results from two recent meta-analyses comprising over 50 randomized controlled trials comparing the effect of CR and IF interventions for a median period of 2–3 months revealed similar effects in subjects with overweight and obesity in terms of body weight (and composition), plasmatic lipid profile, or insulin resistance improvements (Gu et al., 2022; Ezzati et al., 2023). Extending the period intervention over a year neither showed differences in body weight (Ostendorf et al., 2022) nor even in healthy weight subjects, and the lack of apparent differences was consistent except for a slight reduction in fat-free mass and waist circumference based on a recent meta-analysis composed by 28 trials (Schroor et al., 2024). Only minimal improvements (solely supported by few studies) for IF, when compared to CR, were observed in subjects with overweight and obesity, including a reduction in waist circumference (Gu et al., 2022) and body fat, an improvement in insulin sensitivity (Ezzati et al., 2023), as well as a decrease in inflammatory cytokines accompanied by a reduction in HOMA-IR (Castela et al., 2022). Broader differences have been reported only when both regimens differ in the daily protein intake. IF, accompanied by a 35% daily protein intake compared to CR with a 15% daily protein intake, resulted in reductions in desire to eat, body weight, and total and visceral fat mass accompanied by increments in fat-free mass percent (Arciero et al., 2023). Therefore, both diet interventions are beneficial when compared to a non-intervened group. Still, the preference for one or the other cannot be currently established based on metabolic outputs due to a lack of apparent differences. It has been postulated that the benefits observed under IF regimens are due to a reduction in energy intake, which is the main feature of a CR diet (Liu et al., 2022; Thomas et al., 2022). Thus, a combination of both interventions, subjected to the patient itself, could be the better option. However, evidence in this matter is relatively scarce. Three recent randomized trials in participants with obesity rigorously evaluated the comparative effects of a CR regimen and an identical CR protocol within the framework of TRE interventions, delineated by periods of 8 h/day (Liu et al., 2022), 10 h/day (Thomas et al., 2022), or 12 h/day (Pureza et al., 2020; de; Oliveira Maranhão Pureza et al., 2021). Notably, these investigations revealed no significant disparities in weight loss outcomes. Yet, Oliveira Maranhão Pureza et al. found a reduction in body fat composition and waist circumference in obese women (Pureza et al., 2020; de; Oliveira Maranhão Pureza et al., 2021).

Similarly, by doing 4-h eTRE (between 8 a.m. and 12 p.m.) followed by a 20-h fasting period on three non-consecutive days per week and ad libitum eating on other days (known as iTRE, which would be an intermediate paradigm between ADF and 5:2 IF) over 6 months, with an additional 12-month follow-up, glucose tolerance was improved compared with CR at month 6, concomitant to a reduction in fasting triglycerides (Teong et al., 2023). Nonetheless, the differences in glucose tolerance were lost at month 18, and no differences were observed in most of the variables studied (i.e., body weight, fat mass, waist circumference, cholesterol levels, etc.) (Teong et al., 2023). Whether another eating window following the participant’s chronotype can display different outcomes has not been addressed. Therefore, given that IF options are “at least” able to mimic CR diets in terms of their impact on metabolic health, the study and further exploitation of TRE, in particular, become more promising due to its greater feasibility and acceptance (Parr et al., 2020a; Kesztyüs et al., 2021) (including in adolescence population (Vidmar et al., 2021)), despite being less successful lowering body weight and mass index when compared to an ADF intervention (Chair et al., 2022). Recent studies have pointed to TRE as a preventive, in addition to an interventional tool for subjects with overweight and obesity (Kesztyüs et al., 2019; Schuppelius et al., 2021; Xie et al., 2022a), opening a dilemma on whether this intervention should rather be seen as a lifestyle implementation.

Although no trials directly comparing the effects of ADF, 5:2 fasting, and TRE together have still been performed, TRE possesses two intrinsic advantages compared to the others: i) better adherence due to the lack of forced CR and ii) closer to achieving personalized nutrition according to the inter-subject’s chronotype (Figure 2) (Roenneberg et al., 2003). Yet, at the practical level, TRE intervention is often prescribed without considering the subject’s chronotype, which could mask more beneficial effects. For example, in the “Nurses’ Health Study 2” following 64,615 from 2005 to 2011, evening preference among day workers was associated with a higher T2D risk (Vetter et al., 2015). It has been recently shown that individuals with obesity and a late chronotype present a significantly higher BMI, waist circumference, and hip circumference associated with non-alcoholic steatohepatitis index impairment when compared to individuals with obesity and an early chronotype (Vetrani et al., 2022). A lower adherence to a healthy diet associated with late chronotypes could explain the metabolic impairment observed in this population (Patterson et al., 2016; Bazzani et al., 2022). Yet, a key question remains. How could an early or delayed TRE affect morningness or eveningness chronotypes? Comparing early, late, and self-selected TRE strategies would be necessary to determine whether self-selecting the eating window, which could align with an individual’s chronotype, provides additional benefits for cardiometabolic health in adults with overweight/obesity/T2DM (OOT). The number of clinical trials in single-armed pilot trials, randomized crossover studies, or parallel-arm randomized clinical trials using different forms of TRE in adults with OOT is still not very high. Still, it has dramatically increased since 2018 (Table 1). Nonetheless, those are still in a preliminary phase, and information about diet composition, caloric intake, and other variables, including the inter-subject’s chronotype, is often not contemplated. Furthermore, emerging evidence suggests that sex differences in the effectiveness of these nutritional approaches exist and need to be further addressed (Rius-Bonet et al., 2024).

The caloric intake of the participants is controlled in 16 out of the 40 clinical trials shown in Table 1, and from those, seven are trials that compare a CR diet to the same CR diet but with the addition of the TRE intervention (Pureza et al., 2020; Jamshed et al., 2022; Liu et al., 2022; Thomas et al., 2022; Steger et al., 2023b; 2023a). In turn, chronotype assessment has been ignored in 36 out of the 40 trials (Table 1), and none of the four left trials (Parr et al., 2020b; 2020a; Prasad et al., 2021; Andriessen et al., 2022) have randomized different subjects’ chronotypes to different TRE windows. So far, this type of clinical trial studying the effect of a TRE window based on the participant’s chronotype does not exist. Yet, this is important considering that late sleepers who followed a 2-week early TRE (eTRE) significantly advanced their sleep timing (Blum et al., 2023), highlighting the power of the intervention in changing crucial behavioral characteristics like sleep.

Despite the lack of human trials employing TRE interventions according to the participant’s chronotype, animal models of obesity have shown metabolic improvements when time-restricted feeding (TRF), in this case, is implemented during the animal’s active phase (Chaix et al., 2014; 2019; Chung et al., 2016; de Goede et al., 2019; Smith et al., 2019; Hou et al., 2021). However, whether TRF at the optimal time provides superior health outcomes compared to ADF and 5:2 fasting in mice remains unclear due to a lack of comparative studies. Compared to the control mice on a high-fat diet (HFD) ad libitum, ADF, and TRF protocols, they resulted in weight loss, while TRF and 5:2 fasting reduced visceral adiposity (Habiby et al., 2024). In another similar study, utilizing different fat percentages in the HFD, ADF, and TRE interventions consistently led to reduced weight and fat mass gain, lower fasting glucose, insulin, and HOMA-IR, and improved glucose tolerance, particularly in the ADF group (Smith et al., 2019). Except for fasting glucose and glucose tolerance, no additional differences were observed among the IF (and the CR control) groups, suggesting that, similar to humans, there are no apparent differences between CR and IF (and among IF paradigms) in murine models (Smith et al., 2019). Behaviorally, CR impacts food intake patterns more severely than TRF, resulting in a drastic reduction in the duration of daily food intake and a shift in the temporal pattern of wheel running (Acosta-Rodríguez et al., 2017). This suggests that CR associated with IF diet is a major factor behind the metabolic improvements. Other studies in mouse models employing IF in ADF support this notion (Henderson et al., 2021), while other studies indicate an apparent independence (Zheng et al., 2024). Sex- and age-dependent effects of CR in murine models could account for such inconsistencies (Suchacki et al., 2023).

Although the fact of presenting metabolic disturbances have been associated with a disrupted circadian clock in human and animal models, the disruption of the circadian clock, in turn, has been associated with an increased risk of cardiometabolic disorders (Morris et al., 2015; Shimizu et al., 2016). Whether the disruption of the circadian clock is previous to the appearance of the metabolic disorder has not been demonstrated. Yet, animal models of circadian misalignment, including jet lag (Kettner et al., 2015) or genetic ablation of some specific clock gene (Turek et al., 2005; Paschos et al., 2012), clearly promote the beginning of the pathologic process. The circadian clock comprises peripheral clocks (spread throughout the body) and a central clock in the hypothalamic suprachiasmatic nucleus (SCN).

Given that every cell in the body possesses its clock, the latter functions as a cell-specific temporal sensor capable of organizing many aspects of the cellular metabolism in front of extracellular inputs. Although photic signals from the light–dark cycle mainly entrain the central clock, peripheral clocks can be influenced by other external cues, including diet and fasting/feeding cycles (Green et al., 2008). Thus, communication across the different clocks around the body is crucial in maintaining metabolic balance. Rodent models have suggested that restricted feeding at the wrong time (i.e., rest/light phase) (Damiola et al., 2000) or high-fat diet (HFD) given ad libitum can impair such communication (Kohsaka et al., 2007; Eckel-Mahan et al., 2013), while restricting HFD feeding during the rodent active phase for 12 weeks can re-establish this communication accompanied by an improvement in several metabolic markers including the body weight and composition among others (Hatori et al., 2012; Chaix et al., 2014; 2019). Thus, unlike human studies, animal models have shown the involvement of the clock as a mechanism to restore metabolic disturbances induced by obesity after a TRF intervention. In other words, TRF seems to boost the clock while promoting health. In this sense, the role of the clock has to be seen as the controller of the circadian pattern of wakefulness and sleep (i.e., feeding and fasting), while the TRF/E as a “clock agonist” that facilitates the alignment of those diurnal physiological events. TRF intervention can even restore the metabolism of diet-induced obesity mice lacking a clock core gene (via genetically modified mouse models) (Chaix et al., 2019). Although this finding suggested that TRF can restore obesity and metabolic-related disturbances independently of the clock, these different clockless models phenotypically display arrhythmicity in the food intake pattern, and the TRF can re-establish it (Chaix et al., 2019). Mechanistically, TRF exerts an epigenetic control of the pancreatic beta cell function, reverting, in turn, insulin resistance despite the circadian clock disruption (Brown et al., 2021). Thus, the metabolic reprogramming caused by the re-installment of the normal oscillatory food intake pattern, ultimately driven by the TRF, seems to compensate for the absence of a specific clock gene. More specific mechanisms that shed light on the interrelation between TRF/E and the clock system at the molecular level are warranted. Still, so far, insulin sensitization seems to be the strongest link. Several studies restoring insulin function in insulin resistance mouse models have shown a parallel re-setting of the clock (Yamajuku et al., 2012; Eckel-Mahan et al., 2013; Tseng et al., 2015; Ribas-Latre et al., 2019).

Because the link between TRE and the clock system seems to be the oscillatory pattern of food intake, a third variable within the equation strongly affected by food intake can connect both TRE and the clock system. Such a candidate meeting the criteria is the gut microbiota. The gut microbiota comprises a wide range of microorganisms, including bacteria, archaea, fungi, protists, and algae, required to preserve the host’s metabolic balance (Berg et al., 2020). Interestingly, the microbiota’s composition and (thereby) function exhibit daily oscillations intimately related to the oscillatory food intake pattern of the host (Thaiss et al., 2014; Tuganbaev et al., 2020). Not only food timing but also the quality and quantity of food finally translated into dietary components, either metabolized by the host or escaping from the host’s absorptive process (e.g., fiber), modulates the microbiota composition (Zarrinpar et al., 2014; Klingbeil and de La Serre, 2018; Nova et al., 2022). In turn, the microorganisms composing the microbiota generate metabolites or signaling molecules able to positively or negatively impact the host’s physiology, depending on the amount of microbe-related compounds generated (directly related to the microbial diversity, species abundance, or the phylum level) and the host susceptibility to uptake or defend from them (Krautkramer et al., 2021). The list of bioactive microbial metabolites includes (and is not limited to) short-chain fatty acids (e.g., acetate, propionate, butyrate, and colicin), carboxylic acid intermediates (e.g., lactate and succinate), secondary bile acids (e.g., lithocholic acid (LCA), and deoxycholic acid (DCA) and derivatives), pattern receptor recognition (PRR) ligands (e.g., lipopolysaccharide (LPS), peptidoglycan, lipoteichoic acid (LTA), polysaccharide A, bacterial DNA, and secreted microbial proteins), flavonoids (e.g., quercetin, apigenin, and naringenin), lipids and fatty acids (linoleic acid and arachidonic acid), vitamins (group B, K2, A, C, and D), protein–amino acid derivatives (e.g., trimethylamine oxide, taurine, branched-chain amino acids (BCAAs), tryptophan, lysine, and l-glutamine), or other classes including indole-3-propionic acid (I3PA), indole-3-aldehyde (IAId), indoxyl sulfate (IS), or tryptamine (Li et al., 2018; Spivak et al., 2022).

One general trend associated with improved host outcomes is its microbiota’s bacterial diversity (Lozupone et al., 2012). Germ-free mice colonized with microbes isolated from humans or rodents with cardiometabolic disorders, which present lower (and different) bacterial diversity within their microbiota, develop metabolic complications, including weight gain (Turnbaugh et al., 2006; Ridaura et al., 2013; Thaiss et al., 2016a), fatty liver (Murakami et al., 2016), hypertension (Shi et al., 2021), and impaired glycemic response (Suez et al., 2014; Gérard and Vidal, 2019). When inducing weight gain accompanied by adverse metabolic effects and gut microbiota dysbiosis characterized by lower microbial diversity (Liu et al., 2020), HFD feeding disrupts the host’s clock system (Kohsaka et al., 2007; Eckel-Mahan et al., 2013) concomitant with a dampened oscillation of the gut microbiota and gut-derived metabolic factors (Zarrinpar et al., 2014; Martchenko et al., 2020). For example, the circadian secretion of GLP-1 from L-cells is attenuated due to HFD feeding. However, by transferring fecal microbiota from a mouse-eating standard chow into a mouse-eating HFD, GLP-1 circadian secretion is restored (Martchenko et al., 2020). Additional models of circadian desynchrony (and metabolic imbalance), such as jet lag or core clock ablation, similarly display a dampened gut microbiota oscillation (Thaiss et al., 2014; 2016b; Zarrinpar et al., 2014; Heddes et al., 2022). In turn, microbial rhythms’ disruption (or absence) alters several murine tissues’ host rhythmic transcriptome, epigenome, and metabolome (Thaiss et al., 2016b; Kuang et al., 2019; Weger et al., 2019). Therefore, maintaining metabolic homeostasis implies a fine-tuned regulatory checkpoint composed of a dynamic and diverse healthy microbiota and a functional clock system. In this sense, TRE/F not only reinforces peripheral clock rhythmicity but also could expand microbiota diversity and heighten its diurnal oscillation depending on the specific intervention and the host’s microbiota state (Hu et al., 2018; Van Der Merwe et al., 2020; Ye et al., 2020; Ratiner et al., 2022).

Any TRE strategy could lead to different effects, as has been observed in the case of other IF paradigms addressed to people with overweight and obesity. ADF for 1 (ADF-1) or 2 (ADF-2) consecutive days of fasting in a 4-week intervention leads to different outputs. Although ADF-1 increases the abundance of Ruminococcaceae Incertae Sedis and Eubacterium fissicatena families, ADF-2 also increases the abundance of Ruminococcaceae Incertae Sedis and decreases the levels of the Eubacterium ventriosum group, translating at the metabolome level with increases in serine, trimethylamine oxide (TMAO), levulinic acid, 3-aminobutyric acid, citrate, isocitrate, and glucuronic acid compared to ADF-1 (Mohr et al., 2022). Along the same line, an every-other-day (ADF) IF regimen in obese mice results in a shift in the gut microbiota composition, leading to elevation of the fermentation products acetate and lactate, which translates into a selective stimulation of beige fat development within white adipose tissue and a consequent amelioration of obesity (Li et al., 2017). Confirmatory results in terms of browning have been recently observed using the same IF paradigm, with additional inhibitory lipid absorptive effects driven by Akkermansia muciniphila (Yang et al., 2023), while a consistent increase in the abundance of health-associated genera, including Lactobacillus, and an increase in the abundance of Firmicutes, accompanied by a decrease in the proportion of Bacteroidetes and Verrucomicrobia, have also been observed in a genetic model of obesity, specifically in the db/db mice (Beli et al., 2018).

Alternatively, a 3-week 5:2 fasting intervention in human volunteers with varying BMI levels resulted in a significant enrichment of Parabacteroides distasonis and Bacteroides thetaiotaomicron, which inversely correlated with parameters related to obesity and cardiovascular diseases (Hu et al., 2023). In contrast, an 8-week intervention in participants with metabolic syndrome increased the relative abundance of Ruminococcaceae at the family level and Roseburia at the genus level, belonging to Firmicutes. These alterations were significantly associated with cardiovascular risk factors and led to distinct genetic shifts in carbohydrate metabolism within the gut microbiome (Guo et al., 2021). By conducting a similar intervention in participants with overweight and obesity but with fasting on three non-consecutive days per week, an overall shift in the microbiota structure and diversity from baseline to 3 months was observed, with an increase in Akkermansia abundance, which all together correlated with a reduction in the waist circumference (Stanislawski et al., 2021).

In the case of a TRE, participants with obesity enrolled in a 12-week TRE regimen below 12 h/day showed a minimal effect in microbiota diversity and composition compared to a control group with more than 12 h/day eating. In this case, only an increase in the frequency of Lachnospiraceae, Parasutterella, and Romboutsia at the end of the study was observed, with uncertain clinical relevance (Ferrocino et al., 2022). Indeed, a recent systematic review focusing on the clinical effects of TRE in the gut microbiota concluded that only two human studies showed a beneficial correlation between microbiota changes driven by the TRE intervention and the host’s metabolic (HDL cholesterol) or anthropometric parameters (body mass index) (Pieczyńska-Zając et al., 2023). Yet, in this systematic review, only seven clinical trials between 2020 and 2022 were included (three out of the seven were observational studies using Ramadan as a TRE), highlighting the lack of knowledge in this field. Furthermore, several possible confounding factors, study-design limitations, the host’s lifestyle itself, and the microbiota’s great level of flexibility in front of any dietetic regimen, could be behind the weak causal relationship between IF and the improvement of gut microbiota-related outcomes (Paukkonen et al., 2024). Despite similar confounding factors, the impact of TRE in gut microbiota on the lean population seems to be more consistent and in a good direction when a similar TRE protocol is applied. Three studies employing a very late 8-h TRE during 25–26 days, similar to IF-Ramadan, generally revealed an increase in bacterial diversity together with an increase in Prevotellaceae, Bacteroideaceae, and Firmicutes, while pathogenic bacteria were decreased (Zeb et al., 2020a; 2020b; Khan et al., 2022). Similar outputs have been observed in murine models of diet-induced obesity. TRE for 6–8 h during the active phase in obese mice increases α-diversity microbiota (Van Der Merwe et al., 2020) and healthy micro-groups, including Firmicutes phylum, Clostridia class, Ruminococcaceae family, or Roseburia genus, while detrimental groups are inhibited (Hu et al., 2018). This is consistent with another study where restricting food consumption during the active phase was accompanied by a CR (Zhang et al., 2019). Interestingly, by switching from active-phase TRF-CR to ad libitum feeding, the gut microbiota returned to the state resembling that of mice fed standard chow ad libitum, but that of rest-phase TRF-CR mice was still significantly different from the other two groups, reinforcing the importance of the timing of feeding (Zhang et al., 2019).

Thus, the general notion across pre-clinical and clinical studies is that IF regimens (ADF, 5:2 fasting, or TRE) enhance the microbiota structure and diversity, translating into healthy outputs. Yet, the number of studies is still considerably low, and consistency and reproducibility regarding specific microbes being modulated by different IF strategies, particularly TRE interventions, are lacking. Therefore, this field needs to be further exploited, and conclusions regarding the impact of IF on microbiota are far from being reached.

Modern life with constant access to noise, artificial light, rigid schedules, processed food, etc., accompanied by sleep loss, late of eating, or lack of stable eating patterns with a tendency to skip meals (Gill and Panda, 2015), can lead to circadian misalignment, or in other words, chronic “Social Jet Lag” negatively impacting metabolism (Wittmann et al., 2006). An extreme example of that is the case of rotating shift workers, who exhibit an increased risk of developing metabolic disorders (Cheng et al., 2021; Yang et al., 2021; Bayon et al., 2022) and some types of cancer (Härmä et al., 2023). On the other hand, a rhythmic food intake pattern based on the rhythmic pattern of wakefulness and sleep is crucial to sustain the clock system and partially prevent metabolic derangements. One novel tool feasible for rotating shift workers (Manoogian et al., 2022) to promote and increase the robustness of the rhythmic food intake pattern and mitigate metabolic disturbances is TRE. So far, TRE is the only approach that contemplates time daily to maximize health. Aside from the quantity and the quality of food ingested, the timing of food consumption likewise matters. Studies have shown that in front of the same meal in terms of composition and caloric power, a different metabolic response is triggered when the time of eating is different. Studies in healthy adults have shown that evening vs morning eating results in higher postprandial glucose concentrations and GIP (Takahashi et al., 2018) and lower postprandial insulin secretion and GLP-1 responses (Jakubowicz et al., 2015).

Intriguingly, these effects can be mitigated by skipping the evening meal (Tsuchida et al., 2013; Nas et al., 2017) or manipulating the quantity of food administered at night. For example, by transferring 100 kcal of fat intake from night (20:30–05:00) to earlier periods, systemic low-density lipoprotein (LDL) cholesterol levels are reduced (Chen et al., 2019). Having dinner 3 hours earlier (6 p.m. vs. 9 p.m.) improves 24-h blood glucose levels and boosts lipid metabolism after breakfast the next day (Nakamura et al., 2021). Importantly, this effect seems independent of the type of food since the blood glucose levels caused by the consumption of high glycemic index foods are higher when food is offered at night, compared to light hours in healthy subjects (Gibbs et al., 2014). In contrast, shortening the time lapse between one meal and another by having lunch earlier increases glucose tolerance, accompanied by increased carbohydrate oxidation and fasting resting energy expenditure (Bandín et al., 2015). Similar observations have been shown in studies comprising subjects with T2D (Jakubowicz et al., 2015), overweight, and obesity (Garaulet et al., 2013). Mechanistically, a hormonal imbalance driven by evening eating could play a role. For example, the concurrence of high melatonin levels at night and high glucose levels after a late dinner impairs glucose tolerance, specifically in homozygous carriers of the MTNR1B risk allele (Lopez-Minguez et al., 2018), pointing to the melatonin receptor MTNR1B as an important factor. Similarly, the lower concentrations of epinephrine/norepinephrine and higher concentrations of acylated ghrelin after the evening dinner (at 20:00) could also explain such unfavorable effects at night since the balance between these hormones was shifted after a morning meal (at 8:00) (Bo et al., 2017).

Thus, eating earlier rather than later is a good strategy to improve metabolic health, which suggests that implementing TRE early in the morning could be a good approach. Based on what is known, TRE should respect breakfast time since skipping this early meal could impair rather than improve metabolic balance (Betts et al., 2014; Ballon et al., 2019). Therefore, better than reducing the number of meals per day, modulating the timing of those while keeping consistency confined in a shorter eating window (Fleischer et al., 2022) could be sufficient to improve self-metabolic responses to feeding. Whether the feasting time window needs to be necessarily earlier than later and which amount of fasting hours are required to obtain better metabolic outcomes need to be personalized, considering the person’s chronotype. A 12-week randomized (including 1-year follow-up) double-blind, parallel-group controlled trial studying the effectiveness of a hypocaloric diet in weight loss in people with overweight and obesity via the comparison of a hypocaloric dietary treatment to the same regimen but adjusted to the chronotype’s participants concluded that the chronotype-adjusted diet significantly reduced body weight, BMI, and waist circumference when compared to the other group (Galindo Muñoz et al., 2020). Indeed, despite the lack of studies randomizing participants in a TRE intervention according to their chronotype, several examples of the chronotype-driven benefits are observed at different levels. For example, executive function in pre-adolescents and academic performance in adolescents is improved when school timing is better aligned with their biological rhythms (students with early chronotypes perform better in the morning, and the opposite is true for students with late chronotypes) (Hahn et al., 2012; Lara et al., 2014; Goldin et al., 2020). In addition to cognitive performance, the chronotype should be considered when scheduling training sessions to promote a faster recovery in athletes. Morning-type young participants subjected to high-intensity interval training in the evening presented impairment in sleep quality accompanied by signs of pre-fatigue and wellness the following day (Vitale et al., 2017; Saidi et al., 2023). Likewise, exercise following the appropriate chronotype can mitigate the physiopathological condition for some illnesses. For instance, performing exercise in synchrony with the chronotype may be essential to decrease migraine load in chronic migraine (Malek et al., 2023), while an improvement in parameters such as HbA_1c, fasting blood glucose, HDL-LDL cholesterol, triglyceride, total cholesterol, functionality, and quality of life has been observed in individuals with T2D (Menek and Budak, 2022).

Furthermore, chronotherapy, taking into account the patient’s chronotype, could also be applied to treat several pathologies, including inflammatory bowel disease (Swanson et al., 2023), rheumatoid arthritis (To et al., 2011), hypertension, and cardiovascular disease (Festus et al., 2024) or asthma (Pincus et al., 1995) among others. A thousand cycling genes expressed across the body encode proteins that either transport or metabolize drugs or are themselves drug targets, highlighting the importance of considering circadian and behavioral rhythms when studying drug response (Ruben et al., 2018). Further studies will build up from this baseline to better understand the TRE consequences and improve its efficacy.