Simple Summary
Plant-based diets are often discussed in terms of nutrients that may be less available when foods of animal origin are reduced or excluded. However, the human body is not a passive recipient of dietary nutrients: it can adjust to sustained changes in food intake through natural processes that help maintain internal balance. This review examines how these adaptations may occur in people following plant-based diets, focusing on iron, compounds such as creatine and carnosine, protein metabolism, dietary fiber, and polyphenols. The available evidence suggests that long-term dietary changes can trigger increased iron absorption, a greater production of some compounds by the body, more efficient use and recycling of amino acids, changes in the gut bacteria that improve tolerance to fiber, and greater transformation of plant compounds into metabolites that can be used by the body. However, these adaptations have limits. Higher nutritional requirements, chronic inflammation, digestive disorders, severe dietary insufficiency, and other health conditions may reduce the ability of the body to compensate. Understanding these adaptations can improve how plant-based diets are evaluated, help distinguish short-term responses from long-term effects, and support more individualized dietary advice.
Keywords: plant-based diet, vegan diet, physiological adaptation, iron homeostasis, creatine, protein metabolism, gut microbiota, nutrient bioavailability
Abstract
Plant-based dietary patterns are typically discussed in terms of nutrients of concern—iron, creatine, indispensable amino acids, and rapidly fermented carbohydrates—based on the assumption that reduced dietary exposure necessarily translates into reduced physiological availability. This review examines physiological adaptation as an alternative framework, drawing on human intervention and observational evidence across five biological systems: iron homeostasis, endogenous biosynthesis of creatine and carnosine, protein metabolism, fermentation of dietary fiber by the gut microbiota, and the microbial biotransformation of plant polyphenols. Sustained changes in dietary exposure are accompanied by coordinated homeostatic responses, including increased intestinal iron absorption, upregulated endogenous synthesis, improved nitrogen economy, functional remodeling of the gut microbiota, and enhanced polyphenol biotransformation, which contribute to maintaining physiological function. However, adaptive capacity is not unlimited: pregnancy, chronic inflammation, malabsorptive disease, and severe or prolonged dietary insufficiency can exceed adaptive capacity and increase the physiological relevance of dietary intake, planning, or supplementation. Recognizing physiological adaptation as a distinct, measurable phenomenon reframes plant-based diets less as inherently deficient patterns requiring correction and more as a physiological model for understanding how the human body responds to sustained dietary change, with implications for interpreting acute versus long-term evidence and for nutritional counseling.
1. Introduction
The relationship between dietary intake and physiological function is commonly interpreted through an implicit linear paradigm in nutritional science, whereby changes in nutrient intake are expected to produce proportional changes in biological function. This assumption underlies nutrient reference values, dietary recommendations, nutritional epidemiology, and the interpretation of many randomized clinical trials [1,2]. Within this framework, reducing the intake of a nutrient or food component is generally expected to decrease its biological availability, and consequently, impair the physiological processes that depend upon it. Although this approach has been fundamental for understanding nutrient deficiencies and establishing dietary recommendations, it does not fully capture the dynamic physiological responses that occur following sustained changes in dietary exposure.
Physiological responses to dietary change are regulated by homeostatic mechanisms that maintain internal stability despite fluctuations in nutrient availability [3,4]. These mechanisms involve coordinated endocrine, metabolic, intestinal and cellular responses that modify the relationship between dietary exposure and physiological function. Well-established examples include the regulation of glucose, calcium, and iron homeostasis, in which physiological outcomes depend not only on nutrient intake, but also on endogenous mechanisms controlling nutrient absorption, metabolism, storage, and tissue distribution [5,6,7,8,9]. Consequently, dietary exposure alone does not necessarily predict physiological function [10].
Plant-based dietary patterns provide a particularly informative model for studying these adaptive responses because they simultaneously modify exposure to multiple nutrients and bioactive food components. Compared with omnivorous diets, they are characterized by lower exposure to heme iron, creatine, and in some contexts, highly digestible protein, together with higher intakes of dietary fiber, fermentable carbohydrates, and phytochemicals [11,12,13]. Consequently, much of the literature has focused on identifying nutrients of concern, evaluating dietary adequacy, and proposing strategies such as dietary planning, food fortification, or supplementation to ensure nutritional sufficiency [14,15]. Accordingly, discussions surrounding plant-based diets have traditionally emphasized nutritional adequacy and nutrients of concern rather than the physiological adaptations accompanying long-term dietary adherence. Viewing these dietary patterns through a physiological lens may therefore provide broader insights into how humans adapt to sustained alterations in dietary exposure while maintaining nutritional and metabolic homeostasis.
Rather than considering plant-based diets solely in terms of nutrient adequacy, this review examines them as a model of human physiological adaptation, discussing how coordinated homeostatic responses contribute to maintaining nutritional and metabolic function during long-term dietary adherence.
Relevant literature was identified through targeted searches of PubMed, Scopus, and Web of Science, complemented by examination of the reference lists of key publications. The initial search was conducted on 17 June 2026 using combinations of the following keywords: ‘plant-based diet’, ‘vegan diet’, ‘vegetarian diet*’, ‘physiological adaptation’, ‘metabolic adaptation’, ‘homeostasis’, ‘protein metabolism’, ‘iron metabolism’, ‘gut microbiota’, ‘polyphenol*’, ‘creatine’, and ‘carnosine’. The searches focused primarily on human studies examining physiological responses, metabolic adaptation, and long-term outcomes associated with plant-based dietary patterns. Additional studies were considered when they provided relevant mechanistic or physiological evidence to support the proposed framework.
2. Physiological Principles of Dietary Adaptation
Living organisms maintain internal stability despite continuous fluctuations in nutrient availability through a complex network of homeostatic regulatory mechanisms. Rather than responding passively to dietary exposure, physiological systems dynamically adjust nutrient absorption, endogenous synthesis, metabolic utilization, storage, and excretion in order to preserve biological function [16,17,18,19]. Consequently, the relationship between dietary intake and physiological outcomes is not static but is continuously modulated by adaptive responses that buffer changes in nutrient availability and contribute to maintaining metabolic homeostasis (Figure 1).
Figure 1.

Conceptual model of physiological adaptation to sustained dietary change.
2.1. Iron Homeostasis
Iron homeostasis represents one of the most illustrative examples of the complex relationship between dietary exposure and physiological function. Plant-based dietary patterns pose a distinctive nutritional challenge because they rely almost exclusively on non-heme iron, whereas omnivorous diets also provide heme iron, which is generally absorbed more efficiently. Furthermore, plant foods naturally contain compounds such as phytates and certain polyphenols that can reduce the acute bioavailability of non-heme iron by forming insoluble complexes within the intestinal lumen [16,17].
These characteristics have led iron to be regarded as one of the principal nutrients of concern in vegetarian and vegan diets, with discussions largely focusing on the lower bioavailability of dietary iron and the consequent risk of iron deficiency [18,19]. Accordingly, nutritional recommendations have primarily emphasized strategies aimed at increasing dietary iron availability, including higher recommended iron intakes, dietary planning to enhance iron absorption, food fortification, and supplementation in individuals at increased risk of deficiency [20,21]. However, these approaches are largely based on the assumption that lower dietary iron bioavailability necessarily translates into lower physiological iron availability. Whether this assumption adequately reflects iron homeostasis during long-term adherence to plant-based diets remains an important physiological question.
It is also worth distinguishing bioavailability from total intake: several dietary surveys report that mean total iron intake is as high as, or higher than, that of omnivores among vegetarians and vegans, since many staple plant foods—legumes, whole grains, leafy greens, and fortified cereals—are iron-dense. Lower fractional absorption of non-heme iron therefore does not necessarily translate into lower total iron delivered to the gut for absorption, which may partly explain why differences in iron status between dietary patterns are often smaller than differences in absorption efficiency alone would predict [22].
2.1.1. Homeostatic Adaptive Mechanisms
Iron homeostasis is maintained through a tightly coordinated network of endocrine and cellular mechanisms that continuously adjust intestinal iron absorption according to systemic iron requirements rather than dietary iron intake alone [17]. Unlike many nutrients, iron balance is achieved almost exclusively by regulating absorption, since physiological iron losses are minimal and cannot be actively increased. Consequently, alterations in dietary iron availability are primarily counteracted by changes in intestinal iron transport rather than by modifications in iron excretion [16,23].
The hepatic peptide hormone hepcidin acts as the master regulator of systemic iron homeostasis. Adaptive regulation of hepcidin constitutes the principal mechanism through which the organism adjusts intestinal iron absorption to sustained changes in iron availability. When iron availability is reduced or iron demand increases, circulating hepcidin concentrations decrease, allowing for greater expression of the iron exporter ferroportin on enterocytes and macrophages [16,24]. This promotes the release of absorbed and recycled iron into the circulation, thereby increasing systemic iron availability. Conversely, elevated hepcidin concentrations induce ferroportin internalization and degradation, limiting intestinal iron absorption and iron recycling [16,25].
At the intestinal level, iron absorption is further regulated through coordinated changes in the expression and activity of key transport proteins. Ferric iron is initially reduced to its ferrous form by duodenal cytochrome b (Dcytb) at the apical membrane of enterocytes, after which it is transported into the cell via the divalent metal transporter 1 (DMT1) [26]. Once inside the enterocyte, iron can either be stored as ferritin or exported across the basolateral membrane through ferroportin, the only known cellular iron exporter [23,27]. The expression and activity of these transporters are dynamically regulated according to systemic iron requirements, enabling the intestine to adjust iron uptake efficiency in response to sustained changes in dietary iron availability.
Collectively, these regulatory mechanisms provide the physiological basis by which the organism maintains iron homeostasis despite substantial differences in dietary iron bioavailability. Rather than functioning as a passive consequence of dietary composition, intestinal iron absorption is a highly adaptive process that continuously responds to the body’s iron requirements. The extent to which these mechanisms translate into physiological adaptation during long-term adherence to plant-based dietary patterns has been explored in a growing number of human studies.
2.1.2. Evidence for Long-Term Adaptation
The physiological mechanisms regulating iron absorption are well-established. A key question, however, is whether these regulatory responses translate into measurable adaptations during the long-term consumption of diets characterized by lower iron bioavailability. Over the past two decades, accumulating human evidence has progressively shown that intestinal iron absorption adapts according to habitual dietary exposure rather than remaining fixed.
The first experimental evidence was provided by Hunt and Roughead, who demonstrated that healthy adults consuming diets with lower iron bioavailability for several weeks exhibited significantly greater fractional non-heme iron absorption than those consuming diets with higher iron bioavailability, despite similar iron intakes [28]. These results challenged the assumption that acute estimates of iron bioavailability necessarily predict long-term iron absorption. This concept was subsequently reinforced by Armah et al., who reported that women consuming a high-phytate diet for eight weeks showed significantly greater fractional iron absorption than before the intervention, despite continued exposure to phytate [29]. These findings contrast with single meal studies in which phytate exposure can significantly impair iron absorption [30,31]. Therefore, these longer-term studies demonstrate that intestinal iron absorption is not a fixed physiological characteristic but a plastic process that responds to habitual dietary exposure, which we cannot infer from acute feeding studies.
Further support has come from observational studies. Ambroszkiewicz et al. found that vegetarian children exhibited lower circulating hepcidin concentrations than omnivorous children while maintaining normal iron status, consistent with enhanced physiological regulation of iron absorption in response to habitual dietary intake [32]. More recently, a controlled trial comparing long-term vegans and omnivores demonstrated a significantly greater postprandial absorption of non-heme iron in individuals habitually consuming a vegan diet following the ingestion of an identical standardized test meal. This enhanced absorptive response was accompanied by lower circulating hepcidin concentrations in the vegan group (13.6 ± 8.0 vs. 24.3 ± 9.0 ng/mL in omnivores; p = 0.02; probability of superiority [PS] = 0.58), together with a greater serum iron incremental area under the curve (iAUC; 1002.8 ± 143.9 vs. 853.9 ± 268.2 µmol/L/h; p = 0.04; effect size [ES] = 0.68). These findings provide physiological evidence consistent with the adaptive regulation of iron homeostasis in individuals habitually consuming a vegan diet. Although the standardized test-meal approach was appropriate for assessing differences in postprandial iron handling associated with habitual dietary exposure, further longitudinal studies and research in populations with specific physiological or clinical characteristics are needed to further characterize the extent and limits of this adaptive response [33].
These findings collectively challenge the widespread assumption that acute estimates of dietary iron bioavailability necessarily predict long-term iron status. Instead, they support a more dynamic model in which physiological adaptation actively modulates the relationship between dietary exposure and systemic iron homeostasis.
2.1.3. When Adaptation Becomes Insufficient
The available evidence indicates that in healthy individuals, adaptive regulation of iron absorption is generally sufficient to preserve normal erythropoiesis despite the lower bioavailability of dietary iron [34]. Consistent with this concept, comparative studies generally report no clinically meaningful differences in hemoglobin concentrations between vegetarians, vegans, and omnivores, suggesting that adaptive increases in iron absorption are often sufficient to preserve erythropoiesis under normal physiological conditions [35,36,37,38]. However, hemoglobin is a relatively late indicator of iron deficiency and does not necessarily reflect body iron stores. Accordingly, the maintenance of normal hemoglobin concentrations should not be interpreted as evidence that adaptive capacity is unlimited.
Rather, the capacity to increase intestinal iron absorption operates within physiological boundaries and may become insufficient when iron requirements exceed absorptive capacity or when additional factors disrupt iron homeostasis [23]. Physiological conditions associated with increased iron requirements represent the clearest examples of these limitations. During pregnancy, maternal iron demands increase substantially to support fetal growth, placental development, and expansion of maternal blood volume, while regular menstrual blood losses and periods of rapid growth, such as adolescence, also increase the iron requirements [39,40]. Under these circumstances, adaptive increases in intestinal iron absorption may be insufficient to fully compensate for increased physiological demands, particularly when dietary iron intake is suboptimal.
The effectiveness of adaptive mechanisms may also be impaired by pathological conditions that interfere with iron regulation or intestinal iron absorption. Chronic inflammation stimulates hepcidin production, thereby reducing ferroportin-mediated iron export and limiting intestinal iron absorption irrespective of dietary iron intake [41,42]. As a consequence, inflammation can also lead to elevated ferritin concentrations, which may partly explain the higher ferritin levels observed in omnivores than in vegans in some cohorts, without necessarily reflecting a better iron status [34]. Finally, gastrointestinal disorders that compromise intestinal integrity or nutrient absorption, including celiac disease, inflammatory bowel disease, and conditions following gastrointestinal surgery, may reduce the capacity to adapt to diets characterized by lower iron bioavailability [43,44].
These observations reinforce an important physiological concept: adaptation reduces, but does not eliminate, the nutritional challenges associated with lower dietary iron bioavailability. Consequently, dietary counseling, food fortification, or iron supplementation may still be required in individuals with increased physiological requirements, impaired iron regulation, or multiple concurrent risk factors for iron deficiency [40]. Rather than viewing lower dietary iron bioavailability as inevitably leading to iron deficiency, or physiological adaptation as providing complete protection, current evidence supports a more nuanced interpretation in which iron status reflects the balance between dietary exposure, homeostatic adaptation, and individual physiological requirements.
2.2. Endogenous Biosynthesis as a Physiological Adaptation
Unlike essential nutrients, several bioactive compounds found predominantly in animal-source foods—including creatine and carnosine—can also be synthesized endogenously from dietary amino acid precursors. Nevertheless, plant-based dietary patterns provide little or no preformed amounts of these compounds, resulting in substantially lower dietary exposure than omnivorous diets [45,46]. Consequently, individuals adhering to vegetarian and vegan dietary patterns have frequently been assumed to be at increased risk of functional insufficiency owing to the absence of preformed dietary sources, potentially contributing to impaired muscular, neurological, or metabolic function [47].
This interpretation, however, implicitly assumes that tissue concentrations depend primarily on dietary intake. In reality, circulating and tissue levels of these compounds reflect the balance between dietary exposure, endogenous biosynthesis, tissue uptake, metabolic utilization, and excretion. Therefore, reduced dietary intake does not necessarily imply proportional reductions in biological availability.
2.2.1. Homeostatic Adaptive Mechanisms
The principal adaptive response to reduced dietary exposure is the upregulation of endogenous biosynthesis. Creatine is synthesized primarily in the kidneys and liver through sequential reactions involving arginine:glycine amidinotransferase (AGAT) and guanidinoacetate methyltransferase (GAMT), with synthesis being tightly regulated according to tissue creatine availability [48,49]. Likewise, carnosine is synthesized endogenously from β-alanine and L-histidine, predominantly in skeletal muscle and nervous tissue, where it contributes to intracellular buffering and other physiological functions [50].
Beyond increased biosynthesis, homeostasis may also be maintained through adaptations affecting tissue transport, intracellular conservation, and metabolic utilization. Although these mechanisms have been less extensively investigated in humans than endogenous synthesis itself, they contribute to maintaining tissue availability despite prolonged reductions in dietary intake. Consequently, tissue concentrations are determined by the integrated regulation of synthesis, transport, utilization, and turnover rather than dietary exposure alone.
2.2.2. Evidence for Long-Term Adaptation
Human studies consistently demonstrate that individuals adhering to vegetarian and vegan dietary patterns consume negligible or substantially lower amounts of preformed creatine and carnosine than omnivores [51]. However, unlike essential nutrients, these compounds can be synthesized endogenously from amino acid precursors and are therefore not considered dietary essentials under normal physiological conditions [52]. Consequently, lower dietary exposure does not necessarily translate into inadequate biological availability but rather modifies the relative contribution of endogenous biosynthesis and dietary intake to tissue homeostasis.
Among these compounds, creatine provides the clearest evidence supporting this adaptive concept. Vegetarians generally exhibit lower intramuscular creatine concentrations than omnivores, reflecting the absence of dietary creatine intake rather than impaired creatine homeostasis [53,54,55]. Importantly, these lower baseline concentrations are typically compatible with normal physiological function, indicating that endogenous creatine synthesis is generally sufficient to meet habitual metabolic requirements in healthy individuals [52].
Evidence from supplementation studies provides further insight into this adaptive response. Compared with omnivores, vegetarians consistently exhibit greater increases in intramuscular total creatine and phosphocreatine concentrations following creatine supplementation, frequently accompanied by larger improvements in lean body mass and high-intensity exercise performance [54,55,56]. Rather than indicating a pre-existing physiological deficiency, this enhanced responsiveness is more plausibly explained by lower baseline tissue saturation resulting from chronically reduced dietary exposure [57]. From this perspective, these findings suggest that endogenous creatine synthesis is generally sufficient to preserve physiological function under habitual conditions, whereas exogenous creatine may confer additional physiological benefits when long-term dietary exposure has resulted in lower baseline tissue saturation.
Although considerably fewer human data are available for carnosine, circulating concentrations are generally maintained within physiological ranges in healthy vegetarians and vegans despite negligible dietary intake [58,59]. While further research is required to characterize tissue-specific adaptations, the available evidence suggests that endogenous biosynthesis similarly contributes to maintaining the homeostasis of these metabolites under conditions of chronically reduced dietary exposure [60].
2.2.3. When Adaptation Becomes Insufficient
As with other homeostatic systems, endogenous biosynthesis has physiological limits. Endogenous production appears to be regulated to preserve physiological homeostasis rather than to maximize tissue concentrations or functional reserve. Consequently, conditions associated with increased metabolic demands may exceed the capacity of endogenous synthesis alone and increase the physiological relevance of dietary intake or supplementation [49,61].
This concept is particularly relevant for creatine. Although endogenous synthesis appears sufficient to maintain normal physiological function in healthy individuals, accumulating evidence suggests that exogenous creatine supplementation may provide additional benefits in situations characterized by increased energetic demands, including high-intensity athletic performance, aging-associated sarcopenia, neurodegenerative disorders, and certain neuromuscular diseases [56,62]. Importantly, these observations should not be interpreted as evidence that endogenous synthesis is inadequate under normal conditions, but rather that physiological requirements may extend beyond those necessary to maintain basal homeostasis.
The adaptive capacity of endogenous biosynthesis may also be influenced by the availability of precursor amino acids and the integrity of the enzymatic pathways involved. Conditions affecting hepatic or renal function, inherited defects in creatine biosynthesis, severe protein-energy malnutrition, or disorders associated with altered sulfur amino acid metabolism may compromise the synthesis of creatine or carnosine, thereby increasing dependence on dietary intake or supplementation [49].
2.3. Protein
Protein metabolism differs fundamentally from that of many other nutrients because amino acids continuously participate in dynamic processes of protein synthesis, degradation, oxidation, and recycling rather than existing as static body stores [63,64]. Consequently, maintaining protein homeostasis depends not only on dietary protein intake, but also on the coordinated regulation of whole-body protein turnover and nitrogen metabolism [65].
Plant-based dietary patterns present a distinctive physiological challenge because although the total protein intake frequently meets the current recommendations established by the Institute of Medicine (IOM) and the European Food Safety Authority (EFSA) [66,67], the protein supplied generally exhibits lower digestibility, and depending on dietary composition, lower proportions of one or more indispensable amino acids than diets containing animal-source foods [68,69]. For this reason, plant-based diets have traditionally been regarded as potentially suboptimal for supporting muscle protein metabolism, particularly in populations with increased physiological requirements [70]. Accordingly, nutritional strategies have largely focused on increasing total protein intake, combining complementary plant protein sources, improving protein quality, or recommending protein supplementation to compensate for differences in digestibility and amino acid composition [71,72].
Collectively, these approaches are based on the implicit assumption that lower dietary protein quality and digestible indispensable amino acid supply translate directly into proportional reductions in physiological protein availability. Whether this assumption adequately reflects the regulation of protein homeostasis during long-term adherence to plant-based dietary patterns remains an important physiological question.
2.3.1. Homeostatic Adaptive Mechanisms
Protein homeostasis is maintained through several complementary adaptive mechanisms that improve the efficiency of amino acid utilization during sustained reductions in dietary protein availability, thereby preserving whole-body protein homeostasis across a broad range of physiologically adequate protein intakes [73,74]. One of the best-characterized adaptive responses is an improvement in nitrogen economy. Sustained reductions in habitual protein intake are accompanied by progressive decreases in amino acid oxidation and urea production, thereby conserving indispensable amino acids for protein synthesis rather than irreversible catabolism [75,76]. These metabolic adjustments increase the efficiency with which dietary amino acids are utilized and contribute to the maintenance of nitrogen balance despite lower protein availability [77]. Protein turnover is likewise adaptively regulated through coordinated adjustments in protein synthesis and degradation according to dietary protein availability, energy status, endocrine regulation, and physiological demand. By continuously remodeling these processes, the organism preserves essential protein functions while minimizing unnecessary amino acid losses during sustained dietary change [74,78].
A further component of this adaptive response is the efficient recycling of endogenous amino acids. Because most amino acids released during protein degradation are reutilized for subsequent rounds of protein synthesis, only a relatively small proportion is irreversibly oxidized or lost each day. This metabolic efficiency reduces the need for the continuous replacement of amino acids from the diet and contributes to maintaining protein homeostasis during sustained fluctuations in dietary protein availability [64,79].
Together, these mechanisms illustrate that physiological protein availability cannot be inferred solely from dietary protein quantity or quality. Instead, whole-body protein homeostasis emerges from the dynamic interaction between dietary amino acid supply and the adaptive regulation of protein metabolism.
2.3.2. Evidence for Long-Term Adaptation
Evidence from human studies indicates that well-planned plant-based dietary patterns providing adequate total protein intake generally preserve muscle mass and functional outcomes during long-term interventions [11,80]. Rather than supporting the assumption that lower dietary protein digestibility inevitably compromises physiological function, the available evidence suggests that whole-body protein homeostasis can be maintained despite differences in dietary protein quality, consistent with the adaptive mechanisms described above [68,69].
Initial concerns regarding plant-based proteins largely originated from acute metabolic studies evaluating postprandial muscle protein synthesis following the ingestion of isolated protein sources. Several early investigations reported lower anabolic responses after the ingestion of certain plant-derived proteins compared with rapidly digested animal proteins such as whey [81,82,83]. However, subsequent studies demonstrated that these differences become substantially attenuated, and in some experimental settings disappear altogether, when the total protein intake is sufficient, complementary protein sources are consumed, or adequate leucine intake is achieved [83,84,85,86,87]. Moreover, recent controlled feeding studies using integrated measurements of daily myofibrillar or mixed muscle protein synthesis have reported comparable rates between omnivorous and exclusively plant-based dietary patterns over 9–10 days [88,89]. In further support of these findings, a quasi-experimental study found that meals containing foods with an “incomplete” essential amino acid profile stimulated comparable 24-h muscle protein synthesis to meals with complete or complementary essential amino acid profiles [90]. These findings highlight the complexity of the relationship between protein intake and muscle protein synthesis [91].
Evidence from longer-term randomized controlled trials provides a more appropriate framework for determining whether differences observed at the level of protein intake and muscle protein synthesis translate into meaningful changes in physiological outcomes, because these studies capture the cumulative effects of sustained dietary exposure rather than isolated metabolic responses. Across these interventions, plant-based dietary patterns providing adequate protein intake consistently preserve lean body mass, skeletal muscle mass, and muscular strength to a similar extent as omnivorous diets [69]. Consistent with these findings, a recent systematic review and meta-analysis of randomized controlled trials found no significant differences between plant-based and omnivorous dietary patterns for upper-body strength, lower-body strength, or overall muscular strength [92]. Taken as a whole, these findings indicate that differences in dietary protein quality are not sufficient, by themselves, to predict long-term physiological function. Rather, the preservation of functional outcomes is consistent with the capacity of whole-body protein metabolism to adapt to differences in dietary protein characteristics, although these functional outcomes do not directly demonstrate the underlying adaptive mechanisms.
2.3.3. When Adaptation Becomes Insufficient
Although the adaptive regulation of protein metabolism is highly effective under normal physiological conditions, its capacity is not unlimited. Adaptive capacity ultimately depends on the interaction between three interrelated factors: substrate availability, metabolic demand, and the integrity of the regulatory systems responsible for maintaining protein homeostasis. Consequently, when dietary protein availability becomes insufficient, metabolic demand increases substantially, or the physiological mechanisms regulating protein metabolism are impaired, adaptive responses may no longer be sufficient to preserve protein homeostasis, increasing the physiological importance of dietary protein quantity and quality [74,76].
One important circumstance in which adaptive capacity may become insufficient is prolonged exposure to protein intakes below physiologically adequate levels. Although homeostatic mechanisms improve nitrogen economy and amino acid utilization, they cannot fully compensate when dietary protein availability falls below the minimum required to sustain tissue protein synthesis. Under these conditions, persistent negative nitrogen balance, progressive reductions in body cell mass, and impaired muscle function may ultimately develop despite ongoing metabolic adaptation [93]. This situation remains particularly relevant in populations experiencing chronic food insecurity or limited access to adequate protein-rich foods, where insufficient protein intake reflects constrained dietary availability rather than dietary choice [91].
Adaptive capacity may also be compromised in conditions characterized by profound disturbances of protein metabolism, including severe systemic inflammation, major trauma, extensive burns, advanced chronic disease, or gastrointestinal disorders associated with protein malabsorption [94,95,96]. Under these circumstances, accelerated protein turnover, increased amino acid oxidation, impaired nutrient absorption, or reduced anabolic responsiveness may overwhelm the capacity of homeostatic mechanisms to maintain protein balance, thereby increasing dependence on adequate dietary protein intake, and when appropriate, nutritional support.
2.4. Fermentable Carbohydrates
Unlike most nutrients absorbed in the small intestine, a substantial proportion of dietary fiber, resistant starch, galacto-oligosaccharides (GOSs), and other fermentable carbohydrates escape host digestion and reach the colon largely intact, where they become substrates for microbial fermentation rather than direct human metabolism [97,98]. Consequently, the physiological effects of these dietary components depend not only on their chemical structure or quantity, but also on the metabolic capacity of the gut microbiota to utilize them [99].
Plant-based dietary patterns are typically characterized by substantially greater intakes of dietary fiber and other fermentable substrates than omnivorous diets, including resistant starch, GOS, fructans, and diverse non-digestible polysaccharides [100,101]. This abrupt increase in substrate availability alters the ecological and metabolic environment of the colon, frequently resulting in increased microbial fermentation and transient elevations in hydrogen, carbon dioxide, methane, and short-chain fatty acid production [102,103,104,105]. During the early stages of dietary transition, these changes may be accompanied by gastrointestinal symptoms such as flatulence, bloating, or abdominal discomfort, which are commonly perceived as evidence of poor tolerance to plant-based foods.
Consequently, efforts to improve gastrointestinal tolerance have traditionally focused on strategies such as the gradual introduction of fiber-rich foods, food processing techniques that reduce the fermentable carbohydrate content of foods, enzyme supplementation, or, in susceptible individuals, the temporary restriction of specific fermentable carbohydrates [106,107,108]. Although these approaches may be appropriate for managing symptoms in selected clinical contexts, they place comparatively less emphasis on the capacity of the gut microbiota to adapt to sustained increases in fermentable substrate availability. Whether these early gastrointestinal responses reflect persistent intolerance or a transient phase preceding functional adaptation of the gut microbial ecosystem remains an important physiological question.
2.4.1. Homeostatic Adaptive Mechanisms
The adaptive response to sustained increases in fermentable substrate availability is primarily mediated through functional remodeling of the gut microbiota. Rather than representing a static microbial community, the intestinal microbiota continuously adjusts its composition and metabolic activity according to the availability of fermentable substrates reaching the colon [100,109]. One of the principal adaptive responses is the selective enrichment of microbial taxa capable of degrading complex carbohydrates. Increased exposure to dietary fiber, resistant starch, galacto-oligosaccharides, and other non-digestible carbohydrates promotes the expansion of saccharolytic microorganisms possessing carbohydrate-active enzymes (CAZymes), thereby increasing the efficiency with which these substrates are metabolized [110,111]. As microbial communities adapt to habitual substrate availability, their collective fermentative capacity progressively increases.
Microbial adaptation is further reinforced through metabolic cross-feeding, whereby fermentation products generated by primary degraders serve as substrates for secondary microbial species [112,113]. These cooperative metabolic interactions enhance ecosystem stability, increase substrate utilization efficiency, and promote the production of short-chain fatty acids (SCFAs), particularly acetate, propionate, and butyrate, which contribute to colonic epithelial health, intestinal barrier integrity, and host metabolic regulation [114,115].
2.4.2. Evidence for Long-Term Adaptation
Longitudinal human intervention studies provide the most appropriate framework for evaluating physiological adaptation to fermentable carbohydrates because they capture the cumulative effects of sustained dietary exposure rather than the transient responses observed immediately after dietary change. Across controlled dietary interventions involving legumes and other fermentable substrates, gastrointestinal symptoms such as flatulence, bloating, and abdominal discomfort generally decline over time despite continued dietary exposure [106,116,117,118]. Interestingly, improvements in gastrointestinal tolerance are not always accompanied by proportional reductions in intestinal gas production. Early controlled feeding studies demonstrated that repeated consumption of legumes progressively reduced the perception of flatulence and digestive discomfort despite relatively small changes in the total volume of intestinal gas produced [105,116]. More recent intervention studies have similarly reported that regular consumption of legumes or galacto-oligosaccharides is generally well-tolerated following an initial adaptation period, supporting the concept that clinical adaptation reflects more than a simple reduction in microbial gas production [104,117,118].
The reproducibility of these observations across different fermentable substrates, intervention protocols, and study populations supports the concept that gastrointestinal tolerance is a dynamic physiological characteristic that evolves with sustained dietary exposure rather than a fixed response determined by the initial digestive experience [104,106,118]. This raises an important unresolved question: whether the pre-existing state of the gut microbiota may influence the magnitude or trajectory of this adaptive response. Antibiotic exposure and dysbiosis can substantially perturb the gut microbial ecosystem, but whether such perturbations identify individuals with a reduced capacity to adapt to increased fermentable carbohydrate intake remains unknown [119,120]. Prospective studies integrating baseline microbiota characteristics with longitudinal measures of gastrointestinal tolerance and microbial function could help determine whether specific features of the pre-existing gut ecosystem predict individual differences in adaptation and could ultimately serve as clinically useful biomarkers.
Taken together, these findings indicate that the digestive symptoms frequently experienced during the transition to plant-based dietary patterns should be interpreted as part of a dynamic adaptive process. Acute physiological responses following dietary change do not necessarily predict the functional equilibrium achieved after long-term adaptation.
2.4.3. When Adaptation Becomes Insufficient
Adaptive capacity ultimately depends on three interrelated factors: sustained exposure to fermentable substrates, the resilience and functional diversity of the gut microbial community, and the integrity of the gastrointestinal environment [121]. Consequently, conditions that impair microbial diversity or disrupt host–microbiota interactions may reduce the capacity to adapt to increased intakes of fermentable carbohydrates [120,122,123].
Adaptive capacity may be compromised in gastrointestinal disorders characterized by altered microbial composition or impaired intestinal function, including irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and other conditions associated with intestinal dysbiosis [119,124]. In these individuals, increased fermentation of dietary fiber or other fermentable carbohydrates may provoke persistent gastrointestinal symptoms despite repeated exposure, and temporary dietary modifications, including low-FODMAP approaches, may be clinically appropriate during symptom management [125,126]. However, these interventions should not be interpreted as evidence that fermentable carbohydrates are intrinsically poorly tolerated, but rather that the adaptive capacity of the gut ecosystem may be impaired under specific pathological conditions.
Adaptive capacity may also be transiently impaired following major perturbations of the gut microbial ecosystem, including recent antibiotic exposure or gastrointestinal infections, which may delay the establishment of microbial adaptation [120,127]. Consequently, the physiological consequences of increasing fermentable carbohydrate intake depend not only on the amount of fermentable substrate reaching the colon, but also on the capacity of the gut microbial ecosystem to establish and maintain functional adaptation.
2.5. Plant Polyphenols
Plant-based dietary patterns are naturally rich in polyphenols, including hydroxybenzoic acids, hydroxycinnamic acids, flavonoids, lignans, and condensed tannins [128]. However, the biological effects of many dietary polyphenols depend not only on their dietary intake, but also on their transformation by the gut microbiota into smaller, more readily absorbable and biologically active metabolites. Many polyphenols occur in foods in complex or conjugated forms, limiting their direct absorption in the gastrointestinal tract. Consequently, the biological availability of dietary polyphenols cannot be inferred solely from their intake or their chemical abundance in foods [129]. Rather, it depends on the capacity of the gut microbial ecosystem to metabolize these compounds and on the host’s subsequent absorption and metabolism of the resulting products [130]. In this context, sustained exposure to a polyphenol-rich plant-based diet may influence gut microbial metabolism and the biotransformation of dietary polyphenols into bioactive metabolites.
2.5.1. Homeostatic Adaptive Mechanisms
The gut microbiota is a dynamic ecosystem capable of metabolizing a wide range of dietary polyphenols, with specific microbial taxa contributing to the conversion of these compounds into smaller metabolites. These include Faecalibacterium prausnitzii, Bifidobacterium longum, Bifidobacterium pseudocatenulatum, Oscillibacter, and Roseburia species [131,132,133]. Similarly, replacement of animal protein sources with legumes has been associated with increased abundance of Eubacterium rectale, Roseburia faecis, Roseburia hominis, and Bifidobacterium species [134]. These microorganisms have been implicated in the biotransformation of dietary polyphenols into smaller metabolites that can be absorbed and further metabolized by the host.
Specifically, Faecalibacterium prausnitzii is positively associated with fecal and urinary concentrations of enterolactone [135,136], a lignan-derived metabolite. This association appears to be strengthened by higher fiber intake, suggesting that the fiber-associated microbial environment may facilitate lignan biotransformation [135]. Consumption of whole grains, particularly oats, has also been associated with an increased abundance of F. prausnitzii and greater biotransformation of avenanthamides into dihydro-AVA metabolites [137]. Furthermore, F. prausnitzii, together with Eubacterium and Oscillibacter, is positively associated with hippuric acid concentrations, a metabolite derived largely from the microbial catabolism of catechins and chlorogenic acids present in plant foods [138,139]. Consistent with these observations, individuals following plant-based diets exhibit higher concentrations of several chlorogenic acid-derived metabolites, including hippuric acid [128,129,140].
Eubacterium and Oscillibacter are also positively associated with urinary equol concentrations, reflecting the microbial conversion of daidzein from soyfoods [141]. In the Health Study, individuals following vegan diets excreted 4.4-fold and 3-fold higher concentrations of urinary enterolactone and equol, respectively, than non-vegetarian individuals [142]. Similarly, Setchell et al. found that the proportion of equol producers was higher among vegetarians (59%) than among non-vegetarians, with vegetarians being 4.25 times more likely to be equol producers [143].
Specific plant foods provide further examples of microbiota-dependent polyphenol biotransformation. Bifidobacterium pseudocatenulatum and Bifidobacterium longum, owing to their myrosinase-like activity, can contribute to the conversion of glucoraphanin and glucotropaeolin from cruciferous vegetables into sulforaphane [144,145]. Similarly, the consumption of nuts, particularly walnuts, has been associated with an increased abundance of Gordonibacter, a genus involved in the biotransformation of ellagitannins into urolithin A [146].
Together, these examples illustrate the central role of the gut microbiota in determining the metabolic fate of plant-derived polyphenols and the resulting exposure to bioactive metabolites.
2.5.2. Evidence for Long-Term Adaptation
Evidence from intervention studies provides a stronger basis for considering whether sustained polyphenol exposure can modify the gut microbial metabolism. Controlled dietary interventions have shown that the regular consumption of polyphenol-rich foods can alter gut microbial composition. For example, a polyphenol-rich dietary intervention over 8 weeks increased fiber-fermenting and butyrate-producing bacteria, including members of the Ruminococcaceae family and the genus Faecalibacterium [147]. Similarly, a controlled intervention with red wine polyphenols increased several bacterial groups, including Bifidobacterium, Bacteroides, and Prevotella [148].
These intervention findings complement observational evidence linking habitual plant-based dietary patterns with differences in polyphenol-derived metabolites. Greater adherence to a healthy plant-based diet has been associated with higher plasma concentrations of polyphenol-derived metabolites, including trigonelline, O-methylcatechol sulfate, catechol sulfate, and hippuric acid [128,140]. Similarly, individuals following vegan diets exhibit higher plasma concentrations of benzoate-derived metabolites and higher urinary concentrations of enterolactone and equol than non-vegetarian individuals [142,143]. These findings indicate that sustained exposure to plant-based dietary patterns is associated with measurable differences in the systemic and urinary metabolite profiles derived from plant foods. However, whether these changes reflect functional adaptation of microbial polyphenol metabolism, rather than simply greater substrate availability, remains uncertain. Demonstrating functional adaptation would require evidence that sustained exposure alters the microbial capacity to biotransform polyphenols beyond the increase expected from greater substrate availability alone.
2.5.3. When Adaptation Becomes Insufficient
The capacity of the gut microbiota to biotransform dietary polyphenols is not uniform across individuals and may be influenced by microbial composition, habitual dietary exposure, gastrointestinal health, and other host-related factors. The marked interindividual variability in the production of metabolites such as equol illustrates that exposure to the same dietary substrate does not necessarily result in the same metabolic response [149,150]. Conditions that substantially disrupt the gut microbial ecosystem or impair intestinal function may therefore alter the capacity to generate bioactive metabolites from plant-derived compounds [151,152,153]. Consequently, dietary polyphenol exposure should not be interpreted solely from food intake, but in relation to the functional capacity of the gut microbiota and the host to metabolize these compounds.
3. Integrating Physiological Adaptation into Nutritional Science
The evidence reviewed throughout this article supports a broader conceptual framework for interpreting nutritional physiology. Across multiple biological systems—including iron homeostasis, endogenous biosynthesis, protein metabolism, and the gut microbial ecosystem—a common physiological principle emerges: the biological consequences of dietary exposure are determined not only by nutrient intake but also by the homeostatic adaptive mechanisms that regulate physiological function during sustained dietary exposure [28,53,74,105] (Table 1). Consequently, dietary composition should be viewed as the starting point of physiological regulation rather than its sole determinant.
Table 1.
From dietary exposure to physiological adaptation: common adaptive responses across biological systems.
| System | Dietary Exposure | Initial Perturbation | Adaptive Response | Adapted Physiological Outcome | Limits of Adaptation |
|---|---|---|---|---|---|
| Iron | ↓ bioavailable iron | ↓ absorbed iron | ↑ absorption | Iron balance maintained | Pregnancy, inflammation |
| Endogenous synthesis | ↓ dietary creatine/carnosine | ↓ exogenous supply | ↑ synthesis | Tissue availability maintained | Enzyme defects, high demand |
| Protein | ↓ digestible indispensable amino acids | ↓ anabolic stimulus | Nitrogen conservation, recycling | Muscle preserved | Protein insufficiency, catabolic disease |
| Fermentable carbohydrates | ↑ fiber/FODMAPs | ↑ fermentation symptoms | Microbial remodeling | Improved tolerance | IBS, dysbiosis |
| Plant polyphenols | ↑ polyphenol intake | Variable/limited direct absorption | Microbial biotransformation | ↑ bioactive metabolite production | Interindividual variability, dysbiosis |
FODMAPs, fermentable oligosaccharides, disaccharides, monosaccharides, and polyols; IBS, irritable bowel syndrome. Arrows indicate an increase (↑) or decrease (↓) relative to habitual or baseline conditions.
An important implication of this framework is the need to distinguish between acute physiological responses and the homeostatic equilibrium established after long-term adaptation. Although acute metabolic studies provide valuable mechanistic insights, they do not necessarily predict the functional state ultimately achieved following sustained dietary exposure [28,105,154]. Failure to distinguish between these temporal dimensions may lead to the overinterpretation of acute physiological responses while underestimating the capacity of adaptive mechanisms to maintain long-term homeostasis.
Recognizing physiological adaptation does not imply that nutrient composition is unimportant or that all dietary patterns are physiologically equivalent. Rather, it emphasizes that dietary recommendations should consider both nutrient exposure and the capacity of physiological regulatory systems to maintain homeostasis. This distinction becomes particularly relevant in situations where adaptive capacity may be exceeded because of increased physiological demands or pathological conditions, in which dietary interventions or supplementation remain essential.
Overall, incorporating physiological adaptation into nutritional science provides a more comprehensive framework for understanding how dietary patterns influence human health. Ultimately, nutrient intake represents the input to human physiology, whereas long-term physiological function reflects the integrated output of adaptive homeostatic regulation.
From a clinical and dietetic perspective, this framework has a direct practical implication: counseling around plant-based diets should extend beyond static nutrient-of-concern checklists to also consider adaptation timelines and individual adaptive capacity. Patients newly transitioning to a plant-based diet, or those in physiological states associated with reduced regulatory capacity—including pregnancy, active inflammatory or gastrointestinal disease, and recovery from disordered eating— may benefit from closer nutritional monitoring during the adaptation period, while patients with long, stable adherence and no complicating conditions may require less intensive intervention than nutrient-of-concern checklists alone would suggest.
4. Future Research Priorities
Despite growing evidence supporting physiological adaptation across multiple biological systems, several important questions remain unresolved. Addressing these knowledge gaps will be essential for improving our understanding of how adaptive processes influence the long-term physiological consequences of dietary patterns and for integrating this perspective into nutritional science.
One important area requiring further investigation concerns the temporal dynamics of physiological adaptation. Most dietary intervention studies evaluate outcomes after only a few weeks of dietary exposure, providing limited insight into when adaptive responses are initiated, how they evolve over time, or when a new homeostatic equilibrium is established. Longitudinal studies incorporating repeated measurements throughout the adaptation process, rather than relying solely on baseline and end-of-intervention assessments, would allow for the characterization of adaptation trajectories and provide a more comprehensive understanding of the transition from acute physiological responses to long-term homeostasis [155].
Another important challenge is the identification of biomarkers capable of distinguishing transient physiological responses from stable adaptive states. Current nutritional research relies predominantly on biomarkers that quantify nutrient status or metabolic function, yet relatively few indicators directly reflect the progression or completion of physiological adaptation. The development of such biomarkers could substantially improve the interpretation of dietary intervention studies by differentiating temporary metabolic responses from stable physiological regulation.
Future research should also seek to better understand the determinants of interindividual variability in adaptive capacity. The extent and rate of physiological adaptation are likely influenced by multiple factors, including age, genetic background, habitual dietary patterns, metabolic health, physical activity, and the composition and functional capacity of the gut microbiota [10,156]. Elucidating these sources of variability may contribute to more individualized nutritional recommendations and improve the identification of populations in whom adaptive mechanisms are either enhanced or compromised.
Chronic disease states that alter baseline regulatory capacity may be a particularly informative test case. For example, in a 12-week randomized controlled trial in adults with type 1 diabetes, a fiber-rich, plant-based dietary intervention was associated with reduced daily insulin requirements; a secondary analysis of this trial further found that higher dietary lignan intake—a marker of fiber and plant food intake—was associated with lower insulin requirements independent of change in body weight [157]. Whether this reflects an adaptive metabolic response of the kind described throughout this review or a distinct mechanism specific to impaired insulin-dependent glucose regulation remains to be clarified, but it illustrates how populations with altered baseline regulatory capacity could serve as a useful model for probing the limits of physiological adaptation to dietary change.
Finally, future nutritional research may benefit from adopting a more integrative physiological perspective. Rather than evaluating nutrients as isolated dietary exposures, intervention studies should increasingly characterize the coordinated adaptive responses that link dietary change with long-term physiological function. Such an approach would provide a more comprehensive understanding of how homeostatic regulation shapes the biological consequences of dietary exposure and may ultimately improve both the interpretation of nutritional evidence and the development of evidence-based dietary recommendations.
5. Conclusions
Plant-based dietary patterns provide a unique physiological model for understanding how the human organism adapts to sustained dietary change. As illustrated throughout this review, differences in nutrient composition, digestibility, or bioavailability do not necessarily translate into proportional differences in long-term physiological function because adaptive homeostatic mechanisms continuously regulate nutrient absorption, metabolism, synthesis, utilization, and microbial function. Recognizing these dynamic physiological responses provides a more comprehensive framework for interpreting the health effects of plant-based dietary patterns while acknowledging that adaptive capacity operates within defined biological limits and may be exceeded under specific physiological or pathological conditions.
More broadly, the concept of physiological adaptation extends beyond plant-based nutrition and has important implications for nutritional science as a whole. Rather than considering dietary intake as the sole determinant of physiological function, nutritional assessment should increasingly recognize that long-term biological outcomes emerge from the continuous interaction between dietary exposure and adaptive homeostatic regulation. Incorporating this perspective into nutritional research and dietary recommendations may improve the interpretation of dietary interventions and provide a more physiologically grounded framework for understanding the relationship between diet and human health.
Acknowledgments
Generative AI was used exclusively to improve grammar, spelling, and language clarity during manuscript preparation. ChatGPT (GPT-5.6 Luna) was also used to assist in the creation of the graphical illustrations based on concepts and content developed by the authors. No AI tools were used to generate scientific content, interpret results, perform analyses, or draw conclusions. The authors reviewed and approved all revisions and assume full responsibility for the final content of the manuscript.
Author Contributions
M.L.-M. conceived the article and wrote the first draft of the manuscript. All other authors critically reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
There were no human participants in this article, and informed consent was not required.
Data Availability Statement
Data sharing does not apply to this article as no datasets were generated or analyzed during the current study.
Conflicts of Interest
M.L.-M. reports having previously received remuneration from Danone and Foods For Tomorrow for advisory board participation and consulting activities. These activities were unrelated to the submitted work and are not ongoing. At present, he has no active financial relationships with these entities. M.N. has received grant funding from the Karuna Foundation for work unrelated to this manuscript and has received financial support as a writer and speaker for Soy Nutrition Institute Global. The other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.
Funding Statement
This research received no external funding.
Footnotes
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References
- 1.Willett W.C. Nutritional Epidemiology. Oxford Academic; Oxford, UK: 2012. Biochemical Indicators of Dietary Intake; pp. 1–90. [Google Scholar]
- 2.National Institutes of Health . Dietary Reference Intakes. National Academies Press; Washington, DC, USA: 2006. [Google Scholar]
- 3.Bich L., Menatti L. Homeostasis and Health: From Balance to Change. Biol. Theory. 2026;21:174–186. doi: 10.1007/S13752-025-00510-X. [DOI] [Google Scholar]
- 4.Kitano H. Biological Robustness. Nat. Rev. Genet. 2004;5:826–837. doi: 10.1038/nrg1471. [DOI] [PubMed] [Google Scholar]
- 5.Deluque A.L., Dimke H., Alexander R.T. Biology of Calcium Homeostasis Regulation in Intestine and Kidney. Nephrol. Dial. Transplant. 2025;40:435–445. doi: 10.1093/NDT/GFAE204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Matikainen N., Pekkarinen T., Ryhänen E.M., Schalin-Jäntti C. Physiology of Calcium Homeostasis: An Overview. Endocrinol. Metab. Clin. N. Am. 2021;50:575–590. doi: 10.1016/J.ECL.2021.07.005. [DOI] [PubMed] [Google Scholar]
- 7.MacDonald A.J., Yang Y.H.C., Cruz A.M., Beall C., Ellacott K.L.J. Brain-Body Control of Glucose Homeostasis-Insights From Model Organisms. Front. Endocrinol. 2021;12:662769. doi: 10.3389/FENDO.2021.662769. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Gallardo N., Artigas-Jerónimo S., Mazuecos L., Andrés A. Neuroendocrine Control of Glucose Homeostasis: Integrative Mechanisms from the Hypothalamus to the Brainstem. Front. Endocrinol. 2025;16:1731725. doi: 10.3389/FENDO.2025.1731725. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ganz T. Systemic Iron Homeostasis. Physiol. Rev. 2013;93:1721–1741. doi: 10.1152/PHYSREV.00008.2013. [DOI] [PubMed] [Google Scholar]
- 10.Berry S.E., Valdes A.M., Drew D.A., Asnicar F., Mazidi M., Wolf J., Capdevila J., Hadjigeorgiou G., Davies R., Al Khatib H., et al. Human Postprandial Responses to Food and Potential for Precision Nutrition. Nat. Med. 2020;26:964–973. doi: 10.1038/S41591-020-0934-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Melina V., Craig W., Levin S. Position of the Academy of Nutrition and Dietetics: Vegetarian Diets. J. Acad. Nutr. Diet. 2016;116:1970–1980. doi: 10.1016/j.jand.2016.09.025. [DOI] [PubMed] [Google Scholar]
- 12.Dinu M., Abbate R., Gensini G.F., Casini A., Sofi F. Vegetarian, Vegan Diets and Multiple Health Outcomes: A Systematic Review with Meta-Analysis of Observational Studies. Crit. Rev. Food Sci. Nutr. 2017;57:3640–3649. doi: 10.1080/10408398.2016.1138447. [DOI] [PubMed] [Google Scholar]
- 13.Raj S., Guest N.S., Landry M.J., Mangels A.R., Pawlak R., Rozga M. Vegetarian Dietary Patterns for Adults: A Position of the Academy of Nutrition and Dietetics. J. Acad. Nutr. Diet. 2025;125:831–846.E2. doi: 10.1016/J.JAND.2025.02.002. [DOI] [PubMed] [Google Scholar]
- 14.Bakaloudi D.R., Halloran A., Rippin H.L., Oikonomidou A.C., Dardavesis T.I., Williams J., Wickramasinghe K., Breda J., Chourdakis M. Intake and Adequacy of the Vegan Diet. A Systematic Review of the Evidence. Clin. Nutr. 2021;40:3503–3521. doi: 10.1016/J.CLNU.2020.11.035. [DOI] [PubMed] [Google Scholar]
- 15.Sanders T.A.B. The Nutritional Adequacy of Plant-Based Diets. Proc. Nutr. Soc. 1999;58:265–269. doi: 10.1017/S0029665199000361. [DOI] [PubMed] [Google Scholar]
- 16.Sangkhae V., Nemeth E. Regulation of the Iron Homeostatic Hormone Hepcidin. Adv. Nutr. 2017;8:126–136. doi: 10.3945/AN.116.013961. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Galy B., Conrad M., Muckenthaler M. Mechanisms Controlling Cellular and Systemic Iron Homeostasis. Nat. Rev. Mol. Cell Biol. 2024;25:133–155. doi: 10.1038/s41580-023-00648-1. [DOI] [PubMed] [Google Scholar]
- 18.van Wonderen D., Melse-Boonstra A., Gerdessen J.C. Iron Bioavailability Should Be Considered When Modeling Omnivorous, Vegetarian, and Vegan Diets. J. Nutr. 2023;153:2125–2132. doi: 10.1016/J.TJNUT.2023.05.011. [DOI] [PubMed] [Google Scholar]
- 19.Saunders A., Craig W., Baines S., Posen J. Iron and Vegetarian Diets. Med. J. Aust. 2013;199:S11–S16. doi: 10.5694/MJA11.11494. [DOI] [PubMed] [Google Scholar]
- 20.Bresson J.L., Burlingame B., Dean T., Fairweather-Tait S., Heinonen M., Hirsch-Ernst K.I., Mangelsdorf I., McArdle H., Naska A., Neuhäuser-Berthold M., et al. Scientific Opinion on Dietary Reference Values for Iron. EFSA J. 2015;13:4254. doi: 10.2903/J.EFSA.2015.4254. [DOI] [Google Scholar]
- 21.Institute of Medicine . Dietary Reference Intakes for Vitamin A, Vitamin K, Arsenic, Boron, Chromium, Copper, Iodine, Iron, Manganese, Molybdenum, Nickel, Silicon, Vanadium, and Zinc: A Report of the Panel on Micronutrient. National Academies Press; Washington, DC, USA: 2001. [PubMed] [Google Scholar]
- 22.Haider L.M., Schwingshackl L., Hoffmann G., Ekmekcioglu C. The Effect of Vegetarian Diets on Iron Status in Adults: A Systematic Review and Meta-Analysis. Crit. Rev. Food Sci. Nutr. 2018;58:1359–1374. doi: 10.1080/10408398.2016.1259210. [DOI] [PubMed] [Google Scholar]
- 23.Anderson G.J., Frazer D.M. Current Understanding of Iron Homeostasis. Am. J. Clin. Nutr. 2017;106:1559S–1566S. doi: 10.3945/AJCN.117.155804. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Chambers K., Ashraf M.A., Sharma S. StatPearls. StatPearls Publishing; Treasure Island, FL, USA: 2023. Physiology, Hepcidin. [PubMed] [Google Scholar]
- 25.Nemeth E., Ganz T. Hepcidin and Iron in Health and Disease. Annu. Rev. Med. 2022;74:261–277. doi: 10.1146/ANNUREV-MED-043021-032816. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Knutson M.D. Iron Transport Proteins: Gateways of Cellular and Systemic Iron Homeostasis. J. Biol. Chem. 2017;292:12735–12743. doi: 10.1074/jbc.R117.786632. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Pantopoulos K., Porwal S.K., Tartakoff A., Devireddy L. Mechanisms of Mammalian Iron Homeostasis. Biochemistry. 2012;51:5705–5724. doi: 10.1021/bi300752r. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hunt J.R., Roughead Z.K. Adaptation of Iron Absorption in Men Consuming Diets with High or Low Iron Bioavailability. Am. J. Clin. Nutr. 2000;71:94–102. doi: 10.1093/ajcn/71.1.94. [DOI] [PubMed] [Google Scholar]
- 29.Armah S.M., Boy E., Chen D., Candal P., Reddy M.B. Regular Consumption of a High-Phytate Diet Reduces the Inhibitory Effect of Phytate on Nonheme-Iron Absorption in Women with Suboptimal Iron Stores. J. Nutr. 2015;145:1735–1739. doi: 10.3945/jn.114.209957. [DOI] [PubMed] [Google Scholar]
- 30.Petroski W., Minich D.M. Is There Such a Thing as “Anti-Nutrients”? A Narrative Review of Perceived Problematic Plant Compounds. Nutrients. 2020;12:2929. doi: 10.3390/nu12102929. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.López-Moreno M., Garcés-Rimón M., Miguel M. Antinutrients: Lectins, Goitrogens, Phytates and Oxalates, Friends or Foe? J. Funct. Foods. 2022;89:104938. doi: 10.1016/j.jff.2022.104938. [DOI] [Google Scholar]
- 32.Ambroszkiewicz J., Klemarczyk W., Mazur J., Gajewska J., Rowicka G., Strucińska M., Chełchowska M. Serum Hepcidin and Soluble Transferrin Receptor in the Assessment of Iron Metabolism in Children on a Vegetarian Diet. Biol. Trace Elem. Res. 2017;180:182–190. doi: 10.1007/s12011-017-1003-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.López-Moreno M., Viña I., Marrero-Fernández P., Galiana C., Bertotti G., Roldán-Ruiz A., Garcés-Rimón M. Dietary Adaptation of Non-Heme Iron Absorption in Vegans: A Controlled Trial. Mol. Nutr. Food Res. 2025;69:e70096. doi: 10.1002/mnfr.70096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.López-Moreno M., Castillo-García A., Roldán-Ruiz A., Viña I., Bertotti G. Plant-Based Diet and Risk of Iron-Deficiency Anemia. A Review of the Current Evidence and Implications for Preventive Strategies. Curr. Nutr. Rep. 2025;14:81. doi: 10.1007/s13668-025-00671-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Abraham K., Trefflich I., Gauch F., Weikert C. Nutritional Intake and Biomarker Status in Strict Raw Food Eaters. Nutrients. 2022;14:1725. doi: 10.3390/nu14091725. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Bruns A., Nebl J., Jonas W., Hahn A., Schuchardt J.P. Nutritional Status of Flexitarians Compared to Vegans and Omnivores—A Cross-Sectional Pilot Study. BMC Nutr. 2023;9:140. doi: 10.1186/s40795-023-00799-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Storz M.A., Müller A., Niederreiter L., Zimmermann-Klemd A.M., Suarez-Alvarez M., Kowarschik S., Strittmatter M., Schlachter E., Pasluosta C., Huber R., et al. A Cross-Sectional Study of Nutritional Status in Healthy, Young, Physically-Active German Omnivores, Vegetarians and Vegans Reveals Adequate Vitamin B(12) Status in Supplemented Vegans. Ann. Med. 2023;55:2269969. doi: 10.1080/07853890.2023.2269969. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Weikert C., Trefflich I., Menzel J., Obeid R., Longree A., Dierkes J., Meyer K., Herter-Aeberli I., Mai K., Stangl G.I., et al. Vitamin and Mineral Status in a Vegan Diet. Dtsch. Arztebl. Int. 2020;117:575–582. doi: 10.3238/arztebl.2020.0575. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Organización Mundial de la Salud . WHO Guideline on Use of Ferritin Concentrations to Assess Iron Status in Populations. World Health Organization (WHO); Geneva, Switzerland: 2020. p. 1. [PubMed] [Google Scholar]
- 40.Luna F., Rossi E.V., Moreno M.L., Heim T., Arrieta E.M. Iron Deficiency in Vegetarian Athletes: A Narrative Review. Curr. Nutr. Rep. 2026;15:44. doi: 10.1007/S13668-026-00765-1. [DOI] [PubMed] [Google Scholar]
- 41.Wang C.Y., Babitt J.L. Hepcidin Regulation in the Anemia of Inflammation. Curr. Opin. Hematol. 2016;23:189–197. doi: 10.1097/MOH.0000000000000236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Lanser L., Fuchs D., Kurz K., Weiss G. Physiology and Inflammation Driven Pathophysiology of Iron Homeostasis—Mechanistic Insights into Anemia of Inflammation and Its Treatment. Nutrients. 2021;13:3732. doi: 10.3390/NU13113732. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Stein J., Connor S., Virgin G., Ong D.E.H., Pereyra L. Anemia and Iron Deficiency in Gastrointestinal and Liver Conditions. World J. Gastroenterol. 2016;22:7908–7925. doi: 10.3748/WJG.V22.I35.7908. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Bergamaschi G., Caprioli F., Lenti M.V., Elli L., Radaelli F., Rondonotti E., Mengoli C., Miceli E., Ricci C., Ardizzone S., et al. Pathophysiology and Therapeutic Management of Anemia in Gastrointestinal Disorders. Expert Rev. Gastroenterol. Hepatol. 2022;16:625–637. doi: 10.1080/17474124.2022.2089114. [DOI] [PubMed] [Google Scholar]
- 45.Brosnan M.E., Brosnan J.T. The Role of Dietary Creatine. Amino Acids. 2016;48:1785–1791. doi: 10.1007/S00726-016-2188-1. [DOI] [PubMed] [Google Scholar]
- 46.Rogerson D. Vegan Diets: Practical Advice for Athletes and Exercisers. J. Int. Soc. Sports Nutr. 2017;14:36. doi: 10.1186/s12970-017-0192-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Plotnikoff G.A., Dobberstein L., Raatz S. Nutritional Assessment of the Symptomatic Patient on a Plant-Based Diet: Seven Key Questions. Nutrients. 2023;15:1387. doi: 10.3390/NU15061387. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Wyss M., Kaddurah-Daouk R. Creatine and Creatinine Metabolism. Physiol. Rev. 2000;80:1107–1213. doi: 10.1152/PHYSREV.2000.80.3.1107. [DOI] [PubMed] [Google Scholar]
- 49.Brosnan J.T., Brosnan M.E. Creatine: Endogenous Metabolite, Dietary, and Therapeutic Supplement. Annu. Rev. Nutr. 2007;27:241–261. doi: 10.1146/ANNUREV.NUTR.27.061406.093621. [DOI] [PubMed] [Google Scholar]
- 50.Wu G. Important Roles of Dietary Taurine, Creatine, Carnosine, Anserine and 4-Hydroxyproline in Human Nutrition and Health. Amino Acids. 2020;52:329–360. doi: 10.1007/S00726-020-02823-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Delanghe J., De Slypere J.P., De Buyzere M., Robbrecht J., Wieme R., Vermeulen A. Normal Reference Values for Creatine, Creatinine, and Carnitine Are Lower in Vegetarians. Clin. Chem. 1989;35:1802–1803. doi: 10.1093/CLINCHEM/35.8.1802. [DOI] [PubMed] [Google Scholar]
- 52.Turck D., Bohn T., Cámara M., Castenmiller J., de Henauw S., Hirsch-Ernst K.I., Jos Á., Maciuk A., Mangelsdorf I., McNulty B., et al. Creatine and Improvement in Cognitive Function: Evaluation of a Health Claim Pursuant to Article 13(5) of Regulation (EC) No 1924/2006. EFSA J. 2024;22:e9100. doi: 10.2903/J.EFSA.2024.9100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Shomrat A., Weinstein Y., Katz A. Effect of Creatine Feeding on Maximal Exercise Performance in Vegetarians. Eur. J. Appl. Physiol. 2000;82:321–325. doi: 10.1007/S004210000222. [DOI] [PubMed] [Google Scholar]
- 54.Burke D.G., Chilibeck P.D., Parise G., Candow D.G., Mahoney D., Tarnopolsky M. Effect of Creatine and Weight Training on Muscle Creatine and Performance in Vegetarians. Med. Sci. Sports Exerc. 2003;35:1946–1955. doi: 10.1249/01.MSS.0000093614.17517.79. [DOI] [PubMed] [Google Scholar]
- 55.Maccormick V.M., Hill L.M., Macneil L., Burke D.G., Smith-Palmer T. Elevation of Creatine in Red Blood Cells in Vegetarians and Nonvegetarians After Creatine Supplementation. Can. J. Appl. Physiol. 2004;29:704–713. doi: 10.1139/h04-045. [DOI] [PubMed] [Google Scholar]
- 56.Gutiérrez-Hellín J., Del Coso J., Franco-Andrés A., Gamonales J.M., Espada M.C., González-García J., López-Moreno M., Varillas-Delgado D. Creatine Supplementation Beyond Athletics: Benefits of Different Types of Creatine for Women, Vegans, and Clinical Populations—A Narrative Review. Nutrients. 2025;17:95. doi: 10.3390/nu17010095. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.López-Moreno M., Muñoz A., Aguilar-Navarro M., Gutiérrez-Hellín J., Franco-Andrés A., López-López P., Crespo-Cañizares A., Marrero-Fernández P., Forbes S.C. Does Creatine Supplementation Improve Strength and Power in Physically Active Individuals on a Vegan Diet? A Randomized, Triple-Blind, Placebo-Controlled Trial. Eur. J. Appl. Physiol. 2026 doi: 10.1007/S00421-026-06323-5. Epub ahead of printing . [DOI] [PubMed] [Google Scholar]
- 58.Everaert I., Mooyaart A., Baguet A., Zutinic A., Baelde H., Achten E., Taes Y., De Heer E., Derave W. Vegetarianism, Female Gender and Increasing Age, but Not CNDP1 Genotype, Are Associated with Reduced Muscle Carnosine Levels in Humans. Amino Acids. 2011;40:1221–1229. doi: 10.1007/S00726-010-0749-2. [DOI] [PubMed] [Google Scholar]
- 59.Blancquaert L., Baguet A., Bex T., Volkaert A., Everaert I., Delanghe J., Petrovic M., Vervaet C., De Henauw S., Constantin-Teodosiu D., et al. Changing to a Vegetarian Diet Reduces the Body Creatine Pool in Omnivorous Women, but Appears Not to Affect Carnitine and Carnosine Homeostasis: A Randomised Trial. Br. J. Nutr. 2018;119:759–770. doi: 10.1017/S000711451800017X. [DOI] [PubMed] [Google Scholar]
- 60.Goldman D.M., Warbeck C.B., Barbaro R., Khambatta C., Nagra M. Assessing the Roles of Retinol, Vitamin K2, Carnitine, and Creatine in Plant-Based Diets: A Narrative Review of Nutritional Adequacy and Health Implications. Nutrients. 2025;17:525. doi: 10.3390/NU17030525. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Flanagan J.L., Simmons P.A., Vehige J., Willcox M.D., Garrett Q. Role of Carnitine in Disease. Nutr. Metab. 2010;7:30. doi: 10.1186/1743-7075-7-30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Wax B., Kerksick C.M., Jagim A.R., Mayo J.J., Lyons B.C., Kreider R.B. Creatine for Exercise and Sports Performance, with Recovery Considerations for Healthy Populations. Nutrients. 2021;13:1915. doi: 10.3390/NU13061915. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Knopf B.A., Lamming D.W. The Hallmarks of Protein and Amino Acid Restriction in Aging and Longevity. Cell Press Blue. 2026;1:100079. doi: 10.1016/J.CPBLUE.2026.100079. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Wolfe R.R. The Underappreciated Role of Muscle in Health and Disease. Am. J. Clin. Nutr. 2006;84:475–482. doi: 10.1093/AJCN/84.3.475. [DOI] [PubMed] [Google Scholar]
- 65.Liu Z., Barrett E.J. Human Protein Metabolism: Its Measurement and Regulation. Am. J. Physiol. Endocrinol. Metab. 2002;283:E1105–E1112. doi: 10.1152/AJPENDO.00337.2002. [DOI] [PubMed] [Google Scholar]
- 66.Agostoni C., Bresson J.-L., Fairweather-Tait S., Flynn A., Golly I., Korhonen H., Lagiou P., Løvik M., Marchelli R., Martin A., et al. Scientific Opinion on Dietary Reference Values for Protein. EFSA J. 2012;10:2557. doi: 10.2903/J.EFSA.2012.2557. [DOI] [Google Scholar]
- 67.Institute of Medicine . Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. National Academies Press; Washington, DC, USA: 2002. pp. 1–1331. [DOI] [Google Scholar]
- 68.Mariotti F., Gardner C.D. Dietary Protein and Amino Acids in Vegetarian Diets—A Review. Nutrients. 2019;11:2661. doi: 10.3390/NU11112661. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.López-Moreno M., Kraselnik A. The Impact of Plant-Based Proteins on Muscle Mass and Strength Performance: A Comprehensive Review. Curr. Nutr. Rep. 2025;14:147. doi: 10.1007/S13668-025-00628-1. [DOI] [PubMed] [Google Scholar]
- 70.Soh B.X.P., Smith N.W., Von Hurst P.R., McNabb W.C. Achieving High Protein Quality Is a Challenge in Vegan Diets: A Narrative Review. Nutr. Rev. 2024;83:e2063–e2081. doi: 10.1093/NUTRIT/NUAE176. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Pinckaers P.J.M., Trommelen J., Snijders T., van Loon L.J.C. The Anabolic Response to Plant-Based Protein Ingestion. Sports Med. 2021;51:59–74. doi: 10.1007/S40279-021-01540-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.van Vliet S., Burd N.A., van Loon L.J. The Skeletal Muscle Anabolic Response to Plant- versus Animal-Based Protein Consumption. J. Nutr. 2015;145:1981–1991. doi: 10.3945/jn.114.204305. [DOI] [PubMed] [Google Scholar]
- 73.Millward D.J. Metabolic Demands for Amino Acids and the Human Dietary Requirement: Millward and RRvers (1988) Revisited. J. Nutr. 1998;128:S2563–S2576. doi: 10.1093/JN/128.12.2563S. [DOI] [PubMed] [Google Scholar]
- 74.Millward D.J. An Adaptive Metabolic Demand Model for Protein and Amino Acid Requirements. Br. J. Nutr. 2003;90:249–260. doi: 10.1079/BJN2003924. [DOI] [PubMed] [Google Scholar]
- 75.Pacy P.J., Price G.M., Halliday D., Quevedo M.R., Millward D.J. Nitrogen Homeostasis in Man: The Diurnal Responses of Protein Synthesis and Degradation and Amino Acid Oxidation to Diets with Increasing Protein Intakes. Clin. Sci. 1994;86:103–118. doi: 10.1042/CS0860103. [DOI] [PubMed] [Google Scholar]
- 76.Price G.M., Halliday D., Pacy P.J., Quevedo M.R., Millward D.J. Nitrogen Homeostasis in Man: Influence of Protein Intake on the Amplitude of Diurnal Cycling of Body Nitrogen. Clin. Sci. 1994;86:91–102. doi: 10.1042/CS0860091. [DOI] [PubMed] [Google Scholar]
- 77.Gorissen S.H.M., Horstman A.M.H., Franssen R., Kouw I.W.K., Wall B.T., Burd N.A., De Groot L.C.P.G.M., Van Loon L.J.C. Habituation to Low or High Protein Intake Does Not Modulate Basal or Postprandial Muscle Protein Synthesis Rates: A Randomized Trial. Am. J. Clin. Nutr. 2017;105:332–342. doi: 10.3945/AJCN.115.129924. [DOI] [PubMed] [Google Scholar]
- 78.Rand W.M., Pellett P.L., Young V.R. Meta-Analysis of Nitrogen Balance Studies for Estimating Protein Requirements in Healthy Adults. Am. J. Clin. Nutr. 2003;77:109–127. doi: 10.1093/AJCN/77.1.109. [DOI] [PubMed] [Google Scholar]
- 79.Young V.R., Marchini J.S. Mechanisms and Nutritional Significance of Metabolic Responses to Altered Intakes of Protein and Amino Acids, with Reference to Nutritional Adaptation in Humans. Am. J. Clin. Nutr. 1990;51:270–289. doi: 10.1093/AJCN/51.2.270. [DOI] [PubMed] [Google Scholar]
- 80.Agnoli C., Baroni L., Bertini I., Ciappellano S., Fabbri A., Papa M., Pellegrini N., Sbarbati R., Scarino M.L., Siani V., et al. Position Paper on Vegetarian Diets from the Working Group of the Italian Society of Human Nutrition. Nutr. Metab. Cardiovasc. Dis. 2017;27:1037–1052. doi: 10.1016/J.NUMECD.2017.10.020. [DOI] [PubMed] [Google Scholar]
- 81.Wilkinson S.B., Tarnopolsky M.A., MacDonald M.J., MacDonald J.R., Armstrong D., Phillips S.M. Consumption of Fluid Skim Milk Promotes Greater Muscle Protein Accretion after Resistance Exercise than Does Consumption of an Isonitrogenous and Isoenergetic Soy-Protein Beverage. Am. J. Clin. Nutr. 2007;85:1031–1040. doi: 10.1093/AJCN/85.4.1031. [DOI] [PubMed] [Google Scholar]
- 82.Tang J.E., Moore D.R., Kujbida G.W., Tarnopolsky M.A., Phillips S.M. Ingestion of Whey Hydrolysate, Casein, or Soy Protein Isolate: Effects on Mixed Muscle Protein Synthesis at Rest and Following Resistance Exercise in Young Men. J. Appl. Physiol. 2009;107:987–992. doi: 10.1152/japplphysiol.00076.2009. [DOI] [PubMed] [Google Scholar]
- 83.Yang Y., Churchward-Venne T.A., Burd N.A., Breen L., Tarnopolsky M.A., Phillips S.M. Myofibrillar Protein Synthesis Following Ingestion of Soy Protein Isolate at Rest and after Resistance Exercise in Elderly Men. Nutr. Metab. 2012;9:57. doi: 10.1186/1743-7075-9-57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Monteyne A.J., Dunlop M.V., MacHin D.J., Coelho M.O.C., Pavis G.F., Porter C., Murton A.J., Abdelrahman D.R., DIrks M.L., Stephens F.B., et al. A Mycoprotein Based High-Protein Vegan Diet Supports Equivalent Daily Myofibrillar Protein Synthesis Rates Compared with an Isonitrogenous Omnivorous Diet in Older Adults: A Randomized Controlled Trial. Br. J. Nutr. 2020;126:674–684. doi: 10.1017/S0007114520004481. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 85.Martini G.L., Schemes M.B., Strey B., Schneider C.D., de Souza C.G., Pinto R.S. No Differences in Muscular Adaptations to Long-Term Resistance Training Between Young Strict Vegetarian and Non-Vegetarian Women. Scand. J. Med. Sci. Sports. 2026;36:e70224. doi: 10.1111/SMS.70224. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 86.Gorissen S.H.M., Horstman A.M.H., Franssen R., Crombag J.J.R., Langer H., Bierau J., Respondek F., van Loon L.J.C. Ingestion of Wheat Protein Increases In Vivo Muscle Protein Synthesis Rates in Healthy Older Men in a Randomized Trial. J. Nutr. 2016;146:1651–1659. doi: 10.3945/JN.116.231340. [DOI] [PubMed] [Google Scholar]
- 87.Monteyne A.J., Coelho M.O.C., Murton A.J., Abdelrahman D.R., Blackwell J.R., Koscien C.P., Knapp K.M., Fulford J., Finnigan T.J.A., Dirks M.L., et al. Vegan and Omnivorous High Protein Diets Support Comparable Daily Myofibrillar Protein Synthesis Rates and Skeletal Muscle Hypertrophy in Young Adults. J. Nutr. 2023;153:1680–1695. doi: 10.1016/j.tjnut.2023.02.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 88.Domić J., Pinckaers P.J., Grootswagers P., Siebelink E., Gerdessen J.C., van Loon L.J., de Groot L.C. A Well-Balanced Vegan Diet Does Not Compromise Daily Mixed Muscle Protein Synthesis Rates When Compared with an Omnivorous Diet in Active Older Adults: A Randomized Controlled Cross-Over Trial. J. Nutr. 2025;155:1141–1150. doi: 10.1016/J.TJNUT.2024.12.019. [DOI] [PubMed] [Google Scholar]
- 89.Askow A.T., Barnes T.M., Zupancic Z., Deutz M.T., Paulussen K.J.M., McKenna C.F., Salvador A.F., Ulanov A.V., Paluska S.A., Willard J.W., et al. Impact of Vegan Diets on Resistance Exercise-Mediated Myofibrillar Protein Synthesis in Healthy Young Males and Females: A Randomized Controlled Trial. Med. Sci. Sports Exerc. 2025;57:1923–1934. doi: 10.1249/MSS.0000000000003725. [DOI] [PubMed] [Google Scholar]
- 90.Arentson-Lantz E.J., Von Ruff Z., Connolly G., Albano F., Kilroe S.P., Wacher A., Campbell W.W., Paddon-Jones D. Meals Containing Equivalent Total Protein from Foods Providing Complete, Complementary, or Incomplete Essential Amino Acid Profiles Do Not Differentially Affect 24-h Skeletal Muscle Protein Synthesis in Healthy, Middle-Aged Women. J. Nutr. 2024;154:3626–3638. doi: 10.1016/j.tjnut.2024.10.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 91.FAO . The State of Food Security and Nutrition in the World 2024. Food and Agriculture Organization of the United Nations (FAO); Rome, Italy: 2024. [DOI] [Google Scholar]
- 92.López-Moreno M., Rossi E.V., López-Gil J.F., Marrero-Fernández P., Roldán-Ruiz A., Bertotti G. Are Plant-Based Diets Detrimental to Muscular Strength? A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Sports Med. Open. 2025;11:62. doi: 10.1186/s40798-025-00852-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 93.Castaneda C., Charnley J.M., Evans W.J., Crim M.C. Elderly Women Accommodate to a Low-Protein Diet with Losses of Body Cell Mass, Muscle Function, and Immune Response. Am. J. Clin. Nutr. 1995;62:30–39. doi: 10.1093/AJCN/62.1.30. [DOI] [PubMed] [Google Scholar]
- 94.Mehdi S.F., Qureshi M.H., Pervaiz S., Kumari K., Saji E., Shah M., Abdullah A., Zahoor K., Qadeer H.A., Katari D.K., et al. Endocrine and Metabolic Alterations in Response to Systemic Inflammation and Sepsis: A Review Article. Mol. Med. 2025;31:16. doi: 10.1186/S10020-025-01074-Z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 95.Boettcher E., Crowe S.E. Dietary Proteins and Functional Gastrointestinal Disorders. Am. J. Gastroenterol. 2013;108:728–736. doi: 10.1038/AJG.2013.97. [DOI] [PubMed] [Google Scholar]
- 96.Viteri F.E., Schneider R.E. Gastrointestinal Alterations in Protein-Calorie Malnutrition. Med. Clin. N. Am. 1974;58:1487–1505. doi: 10.1016/S0025-7125(16)32085-5. [DOI] [PubMed] [Google Scholar]
- 97.Flint H.J., Scott K.P., Duncan S.H., Louis P., Forano E. Microbial Degradation of Complex Carbohydrates in the Gut. Gut Microbes. 2012;3:289–306. doi: 10.4161/GMIC.19897. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 98.Rowland I., Gibson G., Heinken A., Scott K., Swann J., Thiele I., Tuohy K. Gut Microbiota Functions: Metabolism of Nutrients and Other Food Components. Eur. J. Nutr. 2018;57:1–24. doi: 10.1007/S00394-017-1445-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 99.Rinninella E., Tohumcu E., Raoul P., Fiorani M., Cintoni M., Mele M.C., Cammarota G., Gasbarrini A., Ianiro G. The Role of Diet in Shaping Human Gut Microbiota. Best Pract. Res. Clin. Gastroenterol. 2023;62–63:101828. doi: 10.1016/J.BPG.2023.101828. [DOI] [PubMed] [Google Scholar]
- 100.David L.A., Maurice C.F., Carmody R.N., Gootenberg D.B., Button J.E., Wolfe B.E., Ling A.V., Devlin A.S., Varma Y., Fischbach M.A., et al. Diet Rapidly and Reproducibly Alters the Human Gut Microbiome. Nature. 2014;505:559–563. doi: 10.1038/NATURE12820. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 101.Fan S., Tu Z., Zhang Z., Fu L., Shen N., Xiao X. Dietary Fibers as Drivers of Short-Chain Fatty Acids Homeostasis: A Review of Intestinal Production, Systemic Distribution, and Inter-Individual Variation. J. Agric. Food Chem. 2026;74:8948–8970. doi: 10.1021/ACS.JAFC.5C12022. [DOI] [PubMed] [Google Scholar]
- 102.Mutuyemungu E., Singh M., Liu S., Rose D.J. Intestinal Gas Production by the Gut Microbiota: A Review. J. Funct. Foods. 2023;100:105367. doi: 10.1016/J.JFF.2022.105367. [DOI] [Google Scholar]
- 103.Kalantar-Zadeh K., Berean K.J., Burgell R.E., Muir J.G., Gibson P.R. Intestinal Gases: Influence on Gut Disorders and the Role of Dietary Manipulations. Nat. Rev. Gastroenterol. Hepatol. 2019;16:733–747. doi: 10.1038/s41575-019-0193-z. [DOI] [PubMed] [Google Scholar]
- 104.Mego M., Accarino A., Tzortzis G., Vulevic J., Gibson G., Guarner F., Azpiroz F. Colonic Gas Homeostasis: Mechanisms of Adaptation Following HOST-G904 Galactooligosaccharide Use in Humans. Neurogastroenterol. Motil. 2017;29:e13080. doi: 10.1111/NMO.13080. [DOI] [PubMed] [Google Scholar]
- 105.Mego M., Manichanh C., Accarino A., Campos D., Pozuelo M., Varela E., Vulevic J., Tzortzis G., Gibson G., Guarner F., et al. Metabolic Adaptation of Colonic Microbiota to Galactooligosaccharides: A Proof-of-Concept-Study. Aliment. Pharmacol. Ther. 2017;45:670–680. doi: 10.1111/APT.13931. [DOI] [PubMed] [Google Scholar]
- 106.Winham D.M., Hutchins A.M. Perceptions of Flatulence from Bean Consumption among Adults in 3 Feeding Studies. Nutr. J. 2011;10:128. doi: 10.1186/1475-2891-10-128. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 107.Nowak K., Rohn S., Halagarda M. Impact of Cooking Techniques on the Dietary Fiber Profile in Selected Cruciferous Vegetables. Molecules. 2025;30:590. doi: 10.3390/MOLECULES30030590. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 108.Chen B., Zhang Y., Du L., Jin J., Dai N. Advances in the Mechanism of Low FODMAP Diet in the Treatment of Irritable Bowel Syndrome: A Review. Front. Nutr. 2026;13:1719048. doi: 10.3389/FNUT.2026.1719048. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 109.Flint H.J., Duncan S.H., Scott K.P., Louis P. Links between Diet, Gut Microbiota Composition and Gut Metabolism. Proc. Nutr. Soc. 2015;74:13–22. doi: 10.1017/S0029665114001463. [DOI] [PubMed] [Google Scholar]
- 110.El Kaoutari A., Armougom F., Gordon J.I., Raoult D., Henrissat B. The Abundance and Variety of Carbohydrate-Active Enzymes in the Human Gut Microbiota. Nat. Rev. Microbiol. 2013;11:497–504. doi: 10.1038/NRMICRO3050. [DOI] [PubMed] [Google Scholar]
- 111.Sonnenburg E.D., Sonnenburg J.L. The Ancestral and Industrialized Gut Microbiota and Implications for Human Health. Nat. Rev. Microbiol. 2019;17:383–390. doi: 10.1038/s41579-019-0191-8. [DOI] [PubMed] [Google Scholar]
- 112.Louis P., Flint H.J. Formation of Propionate and Butyrate by the Human Colonic Microbiota. Environ. Microbiol. 2017;19:29–41. doi: 10.1111/1462-2920.13589. [DOI] [PubMed] [Google Scholar]
- 113.Culp E.J., Goodman A.L. Cross-Feeding in the Gut Microbiome: Ecology and Mechanisms. Cell Host Microbe. 2023;31:485–499. doi: 10.1016/J.CHOM.2023.03.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 114.Koh A., De Vadder F., Kovatcheva-Datchary P., Bäckhed F. From Dietary Fiber to Host Physiology: Short-Chain Fatty Acids as Key Bacterial Metabolites. Cell. 2016;165:1332–1345. doi: 10.1016/J.CELL.2016.05.041. [DOI] [PubMed] [Google Scholar]
- 115.Meiners F., Ortega-Matienzo A., Fuellen G., Barrantes I. Gut Microbiome-Mediated Health Effects of Fiber and Polyphenol-Rich Dietary Interventions. Front. Nutr. 2025;12:1647740. doi: 10.3389/FNUT.2025.1647740. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 116.O’Donnell A.U., Fleming S.E. Influence of Frequent and Long-Term Consumption of Legume Seeds on Excretion of Intestinal Gases. Am. J. Clin. Nutr. 1984;40:48–57. doi: 10.1093/AJCN/40.1.48. [DOI] [PubMed] [Google Scholar]
- 117.Baldwin A., Zahradka P., Weighell W., Guzman R.P., Taylor C.G. Feasibility and Tolerability of Daily Pulse Consumption in Individuals with Peripheral Artery Disease. Can. J. Diet. Pract. Res. 2017;78:187–191. doi: 10.3148/CJDPR-2017-015. [DOI] [PubMed] [Google Scholar]
- 118.Wilson S.M.G., Peterson E.J., Gaston M.E., Kuo W.Y., Miles M.P. Eight Weeks of Lentil Consumption Attenuates Insulin Resistance Progression without Increased Gastrointestinal Symptom Severity: A Randomized Clinical Trial. Nutr. Res. 2022;106:12–23. doi: 10.1016/J.NUTRES.2022.08.002. [DOI] [PubMed] [Google Scholar]
- 119.Lozupone C.A., Stombaugh J.I., Gordon J.I., Jansson J.K., Knight R. Diversity, Stability and Resilience of the Human Gut Microbiota. Nature. 2012;489:220–230. doi: 10.1038/NATURE11550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 120.Daniel N., Lécuyer E., Chassaing B. Host/Microbiota Interactions in Health and Diseases—Time for Mucosal Microbiology! Mucosal Immunol. 2021;14:1006–1016. doi: 10.1038/S41385-021-00383-W. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 121.Safarchi A., Al-Qadami G., Tran C.D., Conlon M. Understanding Dysbiosis and Resilience in the Human Gut Microbiome: Biomarkers, Interventions, and Challenges. Front. Microbiol. 2025;16:1559521. doi: 10.3389/FMICB.2025.1559521. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 122.Dethlefsen L., Relman D.A. Incomplete Recovery and Individualized Responses of the Human Distal Gut Microbiota to Repeated Antibiotic Perturbation. Proc. Natl. Acad. Sci. USA. 2011;108:4554–4561. doi: 10.1073/PNAS.1000087107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 123.Napolitano M., Fasulo E., Ungaro F., Massimino L., Sinagra E., Danese S., Mandarino F.V. Gut Dysbiosis in Irritable Bowel Syndrome: A Narrative Review on Correlation with Disease Subtypes and Novel Therapeutic Implications. Microorganisms. 2023;11:2369. doi: 10.3390/MICROORGANISMS11102369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 124.Simreń M., Barbara G., Flint H.J., Spiegel B.M.R., Spiller R.C., Vanner S., Verdu E.F., Whorwell P.J., Zoetendal E.G. Intestinal Microbiota in Functional Bowel Disorders: A Rome Foundation Report. Gut. 2013;62:159–176. doi: 10.1136/GUTJNL-2012-302167. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 125.Halmos E.P., Gibson P.R. Controversies and Reality of the FODMAP Diet for Patients with Irritable Bowel Syndrome. J. Gastroenterol. Hepatol. 2019;34:1134–1142. doi: 10.1111/JGH.14650. [DOI] [PubMed] [Google Scholar]
- 126.Staudacher H.M., Whelan K. The Low FODMAP Diet: Recent Advances in Understanding Its Mechanisms and Efficacy in IBS. Gut. 2017;66:1517–1527. doi: 10.1136/GUTJNL-2017-313750. [DOI] [PubMed] [Google Scholar]
- 127.Pickard J.M., Zeng M.Y., Caruso R., Núñez G. Gut Microbiota: Role in Pathogen Colonization, Immune Responses, and Inflammatory Disease. Immunol. Rev. 2017;279:70–89. doi: 10.1111/IMR.12567. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 128.Wang F., Baden M.Y., Guasch-Ferré M., Wittenbecher C., Li J., Li Y., Wan Y., Bhupathiraju S.N., Tobias D.K., Clish C.B., et al. Plasma Metabolite Profiles Related to Plant-Based Diets and the Risk of Type 2 Diabetes. Diabetologia. 2022;65:1119–1132. doi: 10.1007/S00125-022-05692-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 129.Wu G.D., Compher C., Chen E.Z., Smith S.A., Shah R.D., Bittinger K., Chehoud C., Albenberg L.G., Nessel L., Gilroy E., et al. Comparative Metabolomics in Vegans and Omnivores Reveal Constraints on Diet-Dependent Gut Microbiota Metabolite Production. Gut. 2016;65:63–72. doi: 10.1136/GUTJNL-2014-308209. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 130.Tomás-Barberán F.A., Selma M.V., Espín J.C. Interactions of Gut Microbiota with Dietary Polyphenols and Consequences to Human Health. Curr. Opin. Clin. Nutr. Metab. Care. 2016;19:471–476. doi: 10.1097/MCO.0000000000000314. [DOI] [PubMed] [Google Scholar]
- 131.Kahleova H., Rembert E., Alwarith J., Yonas W.N., Tura A., Holubkov R., Agnello M., Chutkan R., Barnard N.D. Effects of a Low-Fat Vegan Diet on Gut Microbiota in Overweight Individuals and Relationships with Body Weight, Body Composition, and Insulin Sensitivity. A Randomized Clinical Trial. Nutrients. 2020;12:2917. doi: 10.3390/NU12102917. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 132.Asnicar F., Berry S.E., Valdes A.M., Nguyen L.H., Piccinno G., Drew D.A., Leeming E., Gibson R., Le Roy C., Al Khatib H., et al. Microbiome Connections with Host Metabolism and Habitual Diet from 1,098 Deeply Phenotyped Individuals. Nat. Med. 2021;27:321–332. doi: 10.1038/S41591-020-01183-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 133.Link V.M., Subramanian P., Cheung F., Han K.L., Stacy A., Chi L., Sellers B.A., Koroleva G., Courville A.B., Mistry S., et al. Differential Peripheral Immune Signatures Elicited by Vegan versus Ketogenic Diets in Humans. Nat. Med. 2024;30:560–572. doi: 10.1038/s41591-023-02761-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 134.Wu X., Tjahyo A.S., Volchanskaya V.S.B., Wong L.H., Lai X., Yong Y.N., Osman F., Tay S.L., Govindharajulu P., Ponnalagu S., et al. A Legume-Enriched Diet Improves Metabolic Health in Prediabetes Mediated through Gut Microbiome: A Randomized Controlled Trial. Nat. Commun. 2025;16:942. doi: 10.1038/s41467-025-56084-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 135.Hu Y., Li Y., Sampson L., Wang M., Manson J.A.E., Rimm E., Sun Q. Lignan Intake and Risk of Coronary Heart Disease. J. Am. Coll. Cardiol. 2021;78:666–678. doi: 10.1016/J.JACC.2021.05.049. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 136.TwinsUK Gut Explorer. [(accessed on 10 August 2026)]. Available online: https://twinsuk.ac.uk/%20publisheddata_gutexplorer/
- 137.Wang P., Zhang S., Yerke A., Ohland C.L., Gharaibeh R.Z., Fouladi F., Fodor A.A., Jobin C., Sang S. Avenanthramide Metabotype from Whole-Grain Oat Intake Is Influenced by Faecalibacterium Prausnitzii in Healthy Adults. J. Nutr. 2021;151:1426–1435. doi: 10.1093/JN/NXAB006. [DOI] [PubMed] [Google Scholar]
- 138.Pan Y., Yang Y., Peng Z., Wang W., Zhang J., Sun G., Wang F., Zhu Z., Cao H., Lyu Y., et al. Gut Microbiota May Modify the Association between Dietary Polyphenol Intake and Serum Concentrations of Hippuric Acid: Results from a 1-Year Longitudinal Study in China. Am. J. Clin. Nutr. 2025;121:654–662. doi: 10.1016/J.AJCNUT.2025.01.018. [DOI] [PubMed] [Google Scholar]
- 139.Pallister T., Jackson M.A., Martin T.C., Zierer J., Jennings A., Mohney R.P., MacGregor A., Steves C.J., Cassidy A., Spector T.D., et al. Hippurate as a Metabolomic Marker of Gut Microbiome Diversity: Modulation by Diet and Relationship to Metabolic Syndrome. Sci. Rep. 2017;7:13670. doi: 10.1038/s41598-017-13722-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 140.Kim H., Yu B., Li X., Wong K.E., Boerwinkle E., Seidelmann S.B., Levey A.S., Rhee E.P., Coresh J., Rebholz C.M. Serum Metabolomic Signatures of Plant-Based Diets and Incident Chronic Kidney Disease. Am. J. Clin. Nutr. 2022;116:151–164. doi: 10.1093/AJCN/NQAC054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 141.Liang S., Zhang H., Mo Y., Li Y., Zhang X., Cao H., Xie S., Wang D., Lv Y., Wu Y., et al. Urinary Equol and Equol-Predicting Microbial Species Are Favorably Associated With Cardiometabolic Risk Markers in Chinese Adults. J. Am. Heart Assoc. 2024;13:e034126. doi: 10.1161/JAHA.123.034126. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 142.Miles F.L., Lloren J.I.C., Haddad E., Jaceldo-Siegl K., Knutsen S., Sabate J., Fraser G.E. Plasma, Urine, and Adipose Tissue Biomarkers of Dietary Intake Differ Between Vegetarian and Non-Vegetarian Diet Groups in the Adventist Health Study-2. J. Nutr. 2019;149:667–675. doi: 10.1093/JN/NXY292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 143.Setchell K.D.R., Cole S.J. Method of Defining Equol-Producer Status and Its Frequency among Vegetarians. J. Nutr. 2006;136:2188–2193. doi: 10.1093/JN/136.8.2188. [DOI] [PubMed] [Google Scholar]
- 144.Wu J., Cui S., Tang X., Zhang Q., Jin Y., Zhao J., Mao B., Zhang H. Bifidobacterium Longum CCFM1206 Promotes the Biotransformation of Glucoraphanin to Sulforaphane Contributes to Amelioration of Dextran-Sulfate-Sodium-Induced in Mice. J. Agric. Food Chem. 2023;71:1100–1112. doi: 10.1021/ACS.JAFC.2C07090. [DOI] [PubMed] [Google Scholar]
- 145.Tian S., Liu X., Lei P., Zhang X., Shan Y. Microbiota: A Mediator to Transform Glucosinolate Precursors in Cruciferous Vegetables to the Active Isothiocyanates. J. Sci. Food Agric. 2018;98:1255–1260. doi: 10.1002/JSFA.8654. [DOI] [PubMed] [Google Scholar]
- 146.Liu H., Birk J.W., Provatas A.A., Vaziri H., Fan N., Rosenberg D.W., Gharaibeh R.Z., Jobin C. Correlation between Intestinal Microbiota and Urolithin Metabolism in a Human Walnut Dietary Intervention. BMC Microbiol. 2024;24:476. doi: 10.1186/S12866-024-03626-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 147.Del Bo’ C., Bernardi S., Cherubini A., Porrini M., Gargari G., Hidalgo-Liberona N., González-Domínguez R., Zamora-Ros R., Peron G., Marino M., et al. A polyphenol-rich dietary pattern improves intestinal permeability, evaluated as serum zonulin levels, in older subjects: The MaPLE randomised controlled trial. Clin. Nutr. 2021;40:3006–3018. doi: 10.1016/J.CLNU.2020.12.014. [DOI] [PubMed] [Google Scholar]
- 148.Queipo-Ortuño M.I., Boto-Ordóñez M., Murri M., Gomez-Zumaquero J.M., Clemente-Postigo M., Estruch R., Cardona Diaz F., Andrés-Lacueva C., Tinahones F.J. Influence of red wine polyphenols and ethanol on the gut microbiota ecology and biochemical biomarkers. Am. J. Clin. Nutr. 2012;95:1323–1334. doi: 10.3945/AJCN.111.027847. [DOI] [PubMed] [Google Scholar]
- 149.Setchell K.D.R., Brown N.M., Summer S., King E.C., Heubi J.E., Cole S., Guy T., Hokin B. Dietary Factors Influence Production of the Soy Isoflavone Metabolite S-(-)Equol in Healthy Adults. J. Nutr. 2013;143:1950–1958. doi: 10.3945/JN.113.179564. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 150.Gong Y., Lv J., Pang X., Zhang S., Zhang G., Liu L., Wang Y., Li C. Advances in the Metabolic Mechanism and Functional Characteristics of Equol. Foods. 2023;12:2334. doi: 10.3390/FOODS12122334. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 151.Di Vincenzo F., Del Gaudio A., Petito V., Lopetuso L.R., Scaldaferri F. Gut Microbiota, Intestinal Permeability, and Systemic Inflammation: A Narrative Review. Intern. Emerg. Med. 2023;19:275–293. doi: 10.1007/S11739-023-03374-W. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 152.Bozic J., Santic R., Zivkovic P.M., Kumric M. Diet, Gut Microbiome, and Microbial Metabolites in Inflammatory Bowel Disease: From Functional Dysbiosis to Precision Nutrition. Int. J. Mol. Sci. 2026;27:5262. doi: 10.3390/IJMS27125262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 153.Vargas A., Robinson B.L., Houston K., Sangay A.R.V., Saadeh M., D’Souza S., Johnson D.A. Gut Microbiota-Derived Metabolites and Chronic Inflammatory Diseases. Explor. Med. 2025;6:1001275. doi: 10.37349/EMED.2025.1001275. [DOI] [Google Scholar]
- 154.Staudacher H.M., Cox S.R. Editorial: Metabolic Adaptation of Colonic Microbiota to Galactooligosaccharides—Good News for Prebiotics in Irritable Bowel Syndrome? Aliment. Pharmacol. Ther. 2017;45:1005–1006. doi: 10.1111/APT.13976. [DOI] [PubMed] [Google Scholar]
- 155.Mozaffarian D., Rosenberg I., Uauy R. History of Modern Nutrition Science—Implications for Current Research, Dietary Guidelines, and Food Policy. BMJ. 2018;361:k2392. doi: 10.1136/BMJ.K2392. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 156.Ordovas J.M., Ferguson L.R., Tai E.S., Mathers J.C. Personalised Nutrition and Health. BMJ. 2018;361:bmj.k2173. doi: 10.1136/BMJ.K2173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 157.Kahleova H., Znayenko-Miller T., Smith K., Khambatta C., Barbaro R., Sutton M., Holtz D.N., Sklar M., Pineda D., Holubkov R., et al. Effect of a Dietary Intervention on Insulin Requirements and Glycemic Control in Type 1 Diabetes: A 12-Week Randomized Clinical Trial. Clin. Diabetes. 2024;42:419–427. doi: 10.2337/CD23-0086. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Data sharing does not apply to this article as no datasets were generated or analyzed during the current study.
