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Annual Review of Nutrition
Protein-Restricted Diets and
Their Impact on Metabolic
Health and Aging
Sora Q. Kim,1 Redin A. Spann,1 Cristal M. Hill,2
Claire E. Berryman,1 Hans-Rudolf Berthoud,1
David H. McDougal,1 Yanlin He,1 Heike Münzberg,1
Sangho Yu,1 and Christopher D. Morrison1
1
Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA;
email: christopher.morrison@pbrc.edu
2
Leonard Davis School of Gerontology, University of Southern California, Los Angeles,
California, USA
Annu. Rev. Nutr. 2025. 45:13.1–13.29
Keywords
The Annual Review of Nutrition is online at
nutr.annualreviews.org
protein restriction, longevity, FGF21, health span, LPHC, low-protein,
high-carbohydrate diet
https://doi.org/10.1146/annurev-nutr-121624114918
Copyright © 2025 by the author(s).
All rights reserved
Abstract
Recent improvements in human longevity have highlighted the challenge
of maintaining health throughout extended lifespans. This review examines
how organisms regulate nutrient intake and metabolism, focusing on dietary protein’s unique role in health and longevity. While caloric restriction
enhances longevity, adherence to a low-calorie diet is challenging. Protein
restriction represents an alternate nutritional intervention that improves
longevity and health in model organisms and may be easier to translate to
humans. However, its impacts are complex, and its mechanisms are poorly
understood. The beneficial effects of protein restriction on metabolism and
longevity may come at a cost to lean mass and physical resilience. Conversely, while public health recommendations often emphasize high protein
intake, human epidemiological data and work on model organisms suggest
that excessive protein consumption correlates with increased mortality. Understanding this paradox is crucial for developing evidence-based protein
intake recommendations that balance longevity with physical performance.
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Contents
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1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.2
2. DIETARY PROTEIN AS A UNIQUE, ESSENTIAL MACRONUTRIENT . . . . 13.4
2.1. Role of Protein in Body Functions and Metabolism . . . . . . . . . . . . . . . . . . . . . . . . 13.4
2.2. Evidence That Protein Intake Is Defended by the Body . . . . . . . . . . . . . . . . . . . . 13.4
3. DIETARY RECOMMENDATIONS FOR PROTEIN . . . . . . . . . . . . . . . . . . . . . . . . . 13.5
3.1. Current Dietary Protein Guidelines and Current Intake Level . . . . . . . . . . . . . . 13.6
3.2. Arguments for Higher Protein Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . 13.6
4. PROTEIN RESTRICTION EXTENDS LIFESPAN AND IMPROVES
METABOLIC HEALTH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.8
4.1. Protein Restriction Versus Calorie Restriction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.8
4.2. Effects of Protein Restriction on Lifespan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.10
4.3. Effects of Protein Restriction on Metabolic Health and Prevention
of Age-Related Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.13
4.4. Balancing the Positive and Negative Aspects of Protein Restriction . . . . . . . . . .13.14
5. MECHANISMS DRIVING THE EFFECTS OF DIETARY
PROTEIN RESTRICTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.15
5.1. Physiological Changes: Energy Intake and Expenditure . . . . . . . . . . . . . . . . . . . . .13.15
5.2. Cell-Autonomous, Intracellular Mediators of Protein Restriction . . . . . . . . . . . 13.16
5.3. Endocrine Systems That Mediate the Response to Protein Restriction . . . . . . 13.17
6. CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.18
1. INTRODUCTION
Significant advancements in nutrition, health care, and living conditions have led to an increase in
human lifespan. Mean life expectancy is projected to continue increasing (95), although the rate
of improvement in life expectancy has slowed (140). However, ensuring that these additional years
are characterized by sustained physical and cognitive function rather than prolonged morbidity
presents a challenge, especially in the modern era of rising obesity rates and associated metabolic
complications. Alongside the challenges, substantial evidence indicates that reduced calorie or
nutrient intake prolongs well-being and extends lifespan (153). These critical effects of diet raise a
fundamental question: How do animals, including humans, navigate a complex food environment,
and what mechanisms are in place to manage food intake for optimal health?
The ability to identify and procure food is one of the most essential phenomena in biology.
Free-feeding animals navigate a complex nutritional environment in which food availability
and quality can be unreliable and highly variable. Yet, survival depends on consuming a variety
of macro and micronutrients. Thus, it is unsurprising that multiple brain neurocircuitries and
physiological systems exist to adaptively alter feeding behavior, nutrient absorption, and cellular
metabolism in the face of variable food intake. Importantly, an abundant literature suggests
that animals “detect” their internal nutritional state and adaptively alter both food intake and
metabolism to compensate for variations in nutritional status, a remarkable feat of biological adaptation. These adaptive mechanisms are powerfully demonstrated in settings of energy restriction,
which increases the motivation to procure and consume food while decreasing satiety signaling,
leading animals to more readily seek out food and eat larger meals when food is available (14).
These behavioral changes accompany changes in a host of metabolic processes that cumulatively
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Defense mechanism
Weakest
Strongest
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Fat
Carbohydrate
Salt/water
Protein
Vitamins
Micronutrients
O2
Energy
Figure 1
Relative strengths of defense mechanisms for various nutrients and total energy, according to empirical
evidence showing motivation to obtain the nutrient when depleted. Protein is essential for life, and just as
animals detect insufficient intake of oxygen, sodium, water, or energy, they also detect and adaptively
respond to insufficient protein intake. Intake of essential fatty acids as well as vitamins and other
micronutrients is also important for long-time survival, but there is little empirical evidence for the detection
of insufficient intake and adaptive responses. Finally, carbohydrate and fat can be synthesized through
conversion from the other macronutrients, and there are only very weak defense mechanisms.
lead to reductions in energy-intensive processes (growth, reproduction, basal energy expenditure)
and changes in cellular signaling that preserve existing energy stores. Via mechanisms still under
study, these adaptive responses to energy restriction, or calorie restriction, generally improve
metabolic health and extend lifespan (177). Thus, caloric intake exerts marked effects on health,
with very low caloric intake (deprivation/starvation) being unhealthy, moderate caloric restriction
extending health and lifespan, and high caloric intake (obesity) also being unhealthy. Finally,
while modest reductions in caloric intake improve health and extend lifespan, no model organism
and very few humans voluntarily reduce their caloric intake to a level that maximizes these end
points.
Although energy intake is often at the forefront of nutritional research due to its relevance to
obesity, ingestive behavior is influenced by more than just the need for energy. The putative hierarchy of nutrient prioritization and intake defense is outlined in Figure 1. For instance, sodium
intake is essential for survival, and sodium depletion triggers unique behavioral adaptations that
drive sodium intake (sodium appetite), along with metabolic adaptations that promote sodium
retention (53). Water restriction similarly triggers behavioral and metabolic adaptations that increase thirst and conserve water (7). These responses vary in strength depending on the specific
nutrient, with sodium and water eliciting particularly strong adaptive responses, while others, such
as certain vitamins and minerals, evoke weaker reactions (188).
Among macronutrients, it has long been known that animals actively defend their protein
intake to ensure adequate protein status, as protein provides essential amino acids (EAAs) and
serves as the sole nitrogen source. Protein is unique since our body does not readily store protein for future use, making sufficient dietary protein crucial to offset daily losses. Many species
avoid protein deficiency via behavioral flexibility, that is, by seeking or selecting protein-rich foods.
Beyond changes in feeding behavior, protein restriction is detected by the body and brain, triggering whole-body metabolic adaptations. In certain model organisms, these adaptations can extend
lifespan, highlighting the potential benefits of low protein intake. These beneficial effects of low
protein intake are contrasted with evidence that high protein intake may promote satiety, growth,
and physical performance while preventing sarcopenia. As such, this review does not advocate for
protein restriction as inherently beneficial or suggest that humans should reduce protein intake.
Instead, this review argues that the mechanisms underlying the response to protein restriction may
be unique from those triggered by calorie restriction, and understanding these unique mechanisms
will offer an opportunity to uncover novel pathways that regulate feeding behavior, metabolic
health, and lifespan.
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Feedback
Circulating
and stored
Intake
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Fat
Fat
Lipogenesis
Energy
Metabolism
Body weight
Fat mass
Carbohydrate
Carbohydrate
GNG
Protein
Protein
Growth
and repair
Lean mass
Feedback
Figure 2
Simplified diagram showing intake, conversion, utilization, and hypothesized feedback control mechanisms
of the three macronutrients: fat, carbohydrate, and protein. Energy metabolism is predominantly fueled by
fat and carbohydrate, with only a minor contribution of protein under normal conditions. Therefore,
homeostatic regulation of energy balance is accomplished by feedback signals affecting mainly fat and
carbohydrate intake. In contrast, structural growth and repair is critically dependent on available protein,
suggesting the existence of separate feedback signals specifically affecting protein intake. Line thickness
approximates the strength of the relationship. Abbreviation: GNG, gluconeogenesis.
2. DIETARY PROTEIN AS A UNIQUE, ESSENTIAL MACRONUTRIENT
2.1. Role of Protein in Body Functions and Metabolism
Food is primarily composed of three dietary macronutrients: protein, fat, and carbohydrate
(Figure 2). Of these, carbohydrate intake almost exclusively serves as a source of energy (glucose),
while fat primarily provides energy as well as essential (omega-3 and -6) fatty acids. Humans and
animals can survive relatively well on carbohydrate-free (ketogenic) diets due to the body’s ability
to generate glucose and ketone bodies. Short-term exposure to very low-fat diets also does not
produce adverse outcomes, although humans require some fat intake over longer-term periods,
especially when body fat content is high. Conversely, adequate dietary protein consumption is essential for survival, and the absence of protein intake can induce changes in metabolism and growth
over relatively short periods. By providing EAAs, dietary protein represents a distinct nutritional
niche and is required for the synthesis of body proteins and the maintenance of muscle mass. Importantly, amino acids can also be metabolized for energy, while a subset also serves as substrates
for gluconeogenesis. Amino acids also play key roles in diverse metabolic pathways, for instance,
via various amino acid shuttles and cycles (e.g., malate-aspartate, alanine-glucose, glutamineglutamate cycles) and function as neurotransmitters or serve as precursors to neurotransmitters
(e.g., glutamate, gamma-aminobutyric acid, glycine, serotonin, dopamine, norepinephrine, and
epinephrine). Thus, dietary protein broadly supports biological processes that extend beyond lean
tissue growth.
2.2. Evidence That Protein Intake Is Defended by the Body
The manipulation of dietary protein quality and quantity in laboratory and agricultural models
dates back more than 100 years. These data suggest that animals detect variations in dietary protein
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intake in two key ways: protein quantity (total protein intake) and protein quality (amino acid
composition/balance).
In terms of protein quantity, there is ample evidence in both human and animal models that
high-protein diets suppress food intake over the short term (5, 115, 199). Protein is widely regarded as the most satiating macronutrient per calorie, with high-protein preloads reducing both
perceived hunger and subsequent food intake to a greater extent than low-protein preloads (11,
191). Over the longer term, the effects of high-protein diets on food intake and body weight are
more complex. Clinical studies in humans show that high-protein diets promote weight and fat
loss, likely through reduced food intake, preservation of fat-free mass, and increased energy expenditure (41, 197, 199). Similar evidence exists in rodents, with rats rapidly reducing intake in
response to a high-protein diet (11, 99). However, other studies describe an initial suppression of
food intake followed by a recovery of intake over time, likely due to adaptive increases in amino
acid degradation and metabolism (83, 150). Interestingly, when given a choice, animals will also
readily abandon the high-protein source in favor of a control diet (149).
In contrast, low-protein diets tend to increase food intake (38, 78, 101) except in cases of extremely low-protein or protein-free diets, which reduce food intake (38, 150). As such, low-protein
diets have a biphasic effect on food intake, with moderate reductions increasing intake and severe reductions reducing it. Similarly, restricting a single EAA can increase food intake (45, 63,
70, 112, 114, 195, 210). For instance, limiting branched-chain amino acids (BCAAs), particularly
isoleucine, increases food intake and replicates many metabolic benefits of general protein restriction (63, 210). Additionally, the restriction of threonine alone has been shown to confer systemic
metabolic benefits similar to dietary protein dilution (205).
These findings primarily focus on single-diet responses, but many species, including insects,
fish, rodents, and pigs, exhibit self-selection behavior, balancing their intake between high- and
low-protein diets (3, 98, 110, 135, 149). These behavioral responses are consistent with the protein
leverage hypothesis, which posits that dietary protein intake is prioritized over fat or carbohydrate (58, 157, 173). Studies using the Nutritional Geometry Framework further demonstrate
that species from insects to primates regulate their protein intake to maintain a specific ratio of protein to nonprotein energy, underscoring the adaptive control of protein consumption
(42, 130).
The above body of evidence highlights that dietary protein content does more than alter food
intake. It positions dietary protein intake as a defended variable. Animals detect protein quantity
and quality in diets, just as animals detect insufficient intake of oxygen, sodium, water, or energy,
and adaptively respond to insufficient protein intake. How do animals perceive an internal need
state for protein? Does protein restriction trigger adaptive mechanisms that enhance health or
longevity? What are the mediators of protein restriction’s effects? These topics are addressed in
the remaining sections of this review.
3. DIETARY RECOMMENDATIONS FOR PROTEIN
Before we discuss the health benefits of protein restriction, it is important to consider the current dietary recommendations for protein intake. While this section primarily focuses on adult
humans in the United States, similar recommendations from organizations such as the Joint
FAO/WHO (Food and Agriculture Organization/World Health Organization) Committee and
from other developed nations align closely with US guidelines. These recommendations are based
on the minimum protein intake required to prevent negative nitrogen balance and maintain basic
physiological functions. However, as this review later discusses, the amount of protein needed to
support optimal growth in young animals or humans may not necessarily align with the levels that
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promote long-term metabolic health or extend lifespan. This distinction highlights the complexity
of determining protein requirements for different life stages and health outcomes.
3.1. Current Dietary Protein Guidelines and Current Intake Level
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The most recent edition of the Dietary Reference Intakes (DRIs) for protein and EAAs, set by
the Institute of Medicine in 2005, applies uniformly to individuals aged 19 and older, regardless of
age or sex. These recommendations are based on maintaining nitrogen balance and do not differ
between younger (19–52 years) and older (53+ years) adults (81, 156). Although this conclusion
conflicts with some primary research (22, 132), a large meta-analysis also concluded that age does
not affect nitrogen balance (156).
Protein requirements are defined as the minimal continuous intake level that will maintain a
specific nutriture in an individual on the basis of an adequacy indicator, typically nitrogen balance.
It is calculated by subtracting nitrogen losses (i.e., urine, feces, skin, and miscellaneous) from nitrogen intake and thus indicates whether intake meets bodily needs (81). The Estimated Average
Requirement (EAR) is set at 0.66 g protein/kg body weight for adults and represents the average
daily intake sufficient to meet the needs of 50% of healthy individuals in a particular life stage
and gender group (81). The Recommended Dietary Allowance (RDA), derived from the EAR,
is 0.80 g protein/kg body weight and aims to meet the needs of nearly all (97–98%) healthy individuals (81). Thus, the EAR and RDA are based on nitrogen balance and are population-level
recommendations, with the RDA in particular guiding individual dietary intake goals.
The 2005 DRI report also outlines the Acceptable Macronutrient Distribution Range
(AMDR), a range intended to prevent deficiency while accommodating different macronutrient
needs. The AMDR for protein is 10–35% of total energy intake, with the lower range set to prevent
deficiency and the upper range set to complement the AMDR for the other two macronutrients.
Notably, when the RDA is converted to percent protein and compared with AMDR, RDA falls
well below the upper range of 35% of energy as protein and, in some cases, below 10% depending
on individuals’ variable caloric intake and body weights (201), allowing flexibility as to how much
protein should be eaten in the context of a complete diet. In developed countries, most of the
adult population exceeds dietary protein recommendations, and these proteins are mainly derived
from animal sources (13, 168). Recent studies using data from the National Health and Nutrition
Examination Survey indicate that most Americans are meeting or exceeding the DRIs for protein
and EAAs, with protein intake averaging 16% of total energy intake (12, 13). These values exceed
the RDA but are within the AMDR.
3.2. Arguments for Higher Protein Recommendations
Evidence suggests that protein intake significantly above the RDA provides benefits in select settings. This emphasis extends from two primary research areas, the first being food intake/obesity
research and the second being muscle mass and physical performance research.
As noted previously, dietary protein is the most satiating macronutrient per calorie, with protein preloads promoting fullness and at times reducing intake at a subsequent meal (5, 11, 115,
191, 199). This satiety-inducing effect also translates to long-term studies, where high-protein
diets generally reduce food intake (197). However, the use of high-protein diets in weight loss has
primarily focused on increasing protein intake while simultaneously decreasing total food/energy
intake (115), as high-protein diets promote satiety and produce a positive nitrogen balance that
diminishes the breakdown of endogenous protein (nitrogen) (92, 107, 109, 147, 203). This resulting weight loss is also associated with increased energy expenditure and improvements in
various metabolic and/or cardiovascular end points (199). Thus, there is a broad consensus that
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high-protein diets generally exert positive effects on body weight and metabolic health, and
these benefits are particularly apparent when energy intake is restricted while protein intake is
maintained at or above dietary requirements.
The other research area in which high protein intake is linked to positive outcomes is muscle
mass accretion and improvement in physical performance. Simply put, abundant anecdotal evidence suggests that elevating protein intake is necessary for substantial increases in muscle mass
during resistance training. However, the 2005 DRI report states that resistance training does not
increase the protein requirement to maintain nitrogen balance, while an intake of 0.8 g protein/kg
body weight/day with energy balance spared body nitrogen during physical activity (187). These
conclusions seemingly contradict evidence supporting a positive effect of protein supplementation
on lean body mass and muscle protein synthesis (26, 151, 182), with some studies also showing
increases in muscle mass (26, 134). These contradictions are partly due to the fact that protein
supplementation alone has a relatively small effect on muscle mass in comparison to the large
effect produced by resistance training. While the minimum requirement for protein does not increase with resistance training, increased protein intake in combination with resistance exercise
does increase muscle protein synthesis and, in some cases, lean mass accrual (69). These positive
effects of protein intake on muscle protein synthesis, in combination with an anabolic stimulus
(i.e., resistance exercise), are likely the driving force behind the food and nutrition industry’s promotion of high-protein diets, foods, and supplements. Nonetheless, there is limited evidence that
these findings translate to improved physical performance (185, 200). The position of the Academy
of Nutrition and Dietetics, Dietitians of Canada, and the American College of Sports Medicine
reflects this weak relationship, stating that “although protein intake may support glycogen resynthesis and, when consumed in close proximity to strength and endurance exercise, enhances muscle
protein synthesis, there is a lack of evidence from well-controlled studies that protein supplementation directly improves athletic performance” (186, p. 517). In summary, while some minimal level
of protein intake is necessary for muscle growth, and protein supplementation tends to positively
support muscle growth when combined with resistance exercise, protein supplementation in the
absence of resistance training produces relatively marginal effects on strength and performance.
Another related area in which protein intake is emphasized is age-related sarcopenia. Loss of
muscle mass during aging is unavoidable, as older individuals require more protein to stimulate
muscle protein synthesis due to age-related anabolic resistance (133). This muscle loss is linked
to poor quality of life, physical disability, and frailty (91, 152), and, therefore, interventions that
prevent muscle loss with age are highly valuable. Considering the beneficial effects of protein
intake on muscle mass and the reduced efficiency of muscle protein synthesis that occurs with
age, there has been a significant focus on whether daily protein intake should be increased in
older adults. Overall, it seems clear that low protein intake (below the RDA) can lead to negative
nitrogen balance and decreased lean mass and muscle strength in older adults (24, 25). However,
it is less clear whether protein supplementation beyond the RDA affords a substantial benefit,
as multiple trials suggest only a limited benefit of additional supplementation on lean mass or
muscle mass (15, 126) and even poorer effects on strength or performance (185). Therefore, while
maintaining or exceeding the RDA for protein intake in older adults is frequently recommended
(21), it remains unclear whether a high protein intake alone is sufficient to increase strength or
functional performance in aging adults. Similar to younger individuals, protein intake above the
RDA may only illicit lean mass accrual in combination with resistance training (21).
The above discussion suggests two key conclusions related to protein intake and its health benefits. First, protein intake below RDA levels can lead to increased caloric intake (due to protein
leveraging) and a loss of lean body mass. Conversely, protein intake at or above the RDA in healthy
adults is beneficial when deliberately combined with calorie reduction or resistance training, as
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protein generally supports healthy body weight management and preserves or increases lean mass.
Second and alternatively, it is unclear whether protein intake beyond the RDA alone elicits significant benefits. Most research on high-protein diets and protein supplements involves short-term
interventions or observational studies. In addition, most focus either on high-protein, low-calorie
diets as a means for weight loss in overweight or obese individuals or on the effect of protein supplementation in the context of exercise. Increased protein intake may offer modest enhancements
in these contexts, but high- protein intake by itself is unlikely to yield meaningful improvements.
In other words, a sedentary person likely receives no meaningful benefit by overconsuming a highprotein diet. Therefore, broadly applying these findings requires caution, as they may not extend
to the general population without context-specific adjustments. This discussion underscores the
point that an optimal level of protein intake should be flexible and tailored to targeted individual
health goals.
4. PROTEIN RESTRICTION EXTENDS LIFESPAN AND IMPROVES
METABOLIC HEALTH
While maintaining or potentially supplementing protein intake is linked to improvements in
weight maintenance and muscle mass, a separate body of work suggests that reductions in protein
intake positively impact both metabolism and longevity. These conclusions are driven by human
epidemiological data as well as studies in model organisms.
4.1. Protein Restriction Versus Calorie Restriction
More than a century ago, Osborne et al. (145) showed that a reduction in caloric intake increased
lifespan in rats. Approximately 15 years later, a more refined study conducted by McCay et al.
(131) expanded this discovery, demonstrating that calorie restriction soon after weaning increased
lifespan in rats. Since then, calorie restriction has been consistently shown to increase mean and
maximum lifespan across various organisms (111), establishing it as the gold standard for delaying
age-related phenotypes and promoting longevity. An early study by Yu et al. (209) suggested that
the life-extending effect of calorie restriction is primarily due to the restriction of specific nutrients, particularly proteins and certain amino acids, but subsequent research demonstrated that
calorie restriction without protein restriction also extends lifespan, indicating that the effects of
calorie restriction are not entirely attributable to protein reduction (127, 178). Further analyses
suggest that calorie restriction and protein restriction exert their effects through both overlapping
and distinct mechanisms, contributing independently to improved health span and lifespan (178).
Calorie restriction is generally defined as a 30–50% reduction in energy intake compared with
ad libitum chow-diet-fed control animals. In humans, however, the term is often used more loosely,
encompassing any reduction in caloric intake, including among overweight or obese individuals.
However, in the context of aging and longevity research, calorie restriction may be better understood when it refers to an energy intake level sufficient to maintain a low-normal body weight
(body mass index < 21) without inducing malnutrition (141). On the other hand, protein restriction in animal and human studies typically involves ad libitum consumption of a diet providing
protein at 3–9% of total energy, as compared with control diets providing 15–25% of energy as
protein (17, 74, 138). This level of protein intake aligns with findings that a reduced protein-tocarbohydrate ratio (with 5% energy from protein) is associated with increased median lifespan in
mice (173). Overall, the term protein restriction is often applied to low-protein, high-carbohydrate
diets, but the optimal balance between protein and carbohydrate intake is not set and varies across
species. In epidemiological studies, protein restriction can be assessed by stratifying intake into
quartiles or deciles or using a scoring system for low-carbohydrate, high-protein (LCHP) content.
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Calorie and protein restriction share similarities in their physiological effects on whole-body
metabolism, metabolic health, and lifespan. Both are defended when intake is low and profoundly
impact whole-body metabolism, feeding behavior, health span, and lifespan when restricted.
Accordingly, the molecular mechanisms triggered by these two dietary interventions overlap
significantly, with some distinctions. For instance, fibroblast growth factor 21 (FGF21) is robustly elevated in response to protein restriction but not to calorie restriction (101). Sirtuin1 is
highly activated by calorie restriction due to increased nicotinamide adenine dinucleotide (NAD+ )
level, leading to metabolic and longevity benefits, but the relationship with protein restriction
remains inconclusive and context-dependent. For instance, 8-week methionine restriction increased sirtuin1 expression when the diet was initiated at 12 months old but not at 2 months old
(113).
Additionally, energy intake and expenditure also differ markedly between the two interventions,
underscoring that calorie restriction and protein restriction act through independent mechanisms
(Table 1). One of the reasons why protein restriction can be considered more sustainable than
calorie restriction for translation into humans is that it captures many of the health benefits of
calorie restriction without requiring reduced food intake. For instance, an 8-week ad libitum
low-protein, high-carbohydrate diet improved glucose and lipid metabolism similarly to those
Table 1 Summary of comparisons of general traits between calorie restriction and protein
restriction
Calorie restriction
30–50% reduction in energy intake
without essential nutrient deficiency
Definition
Protein restriction
Low-protein,
high-carbohydrate diet
Molecular mechanisms
mTOR signaling
↓a
↓
AMPK signaling
↑b
↑
Autophagy
↑
↑
IGF1
↓
↓
FGF21
↔
↑
Sirtuin1
↑
?c
Energy intake
↓
↑
Energy expenditure
↓
↑
Macronutrient
preference
Carbohydrate (sugar)
Protein
Lean mass
↓
↓
Fat mass
↓
↓/↔d
Physiological change
Cardiometabolic markers
Fasting glucose
↓
↓
Fasting triglycerides
↓
↓
Fasting insulin
↓
↓
Inflammation
↓
↓
↓: Decrease.
↑: Increase.
c
Relationship unknown.
d
Mixed results published.
Abbreviations: AMPK, AMP-activated protein kinase; FGF21, fibroblast growth factor 21; IGF, insulin-like growth factor;
mTOR, mammalian target of rapamycin.
a
b
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Table 2 Rodent protein/AA restriction studies on lifespan
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Organism
Lifespan in
low-protein/AA group
Strain
Intervention
Rat
Long-Evans
Fischer 344
Long-Evans
Tryptophan-deficient diet
Protein restriction
Tryptophan restriction
↑a
↑
↑ (late-life)b
1976
1988
1988
Year
166
79
142
Reference
Mouse
C57Bl/6
A/J, C57Bl/6, hybrid
Swiss albino
C57Bl/6
C57Bl/6
Protein restriction (casein based)
Protein restriction (casein based)
Tryptophan restriction
25 diets varying in macronutrients
25 diets varying in macronutrients
1976
1978
1986
2014
2015
116
56
36
173
175
C57Bl/6
2019
172
C57Bl/6
200%, 100%, 50%, 20% BCAA
compared with AIN-93G diet
BCAA restriction
2021
158
C57Bl/6
C57Bl/6
HET3
Protein restriction (casein based)
Histidine restriction
Isoleucine restriction
↑
↑
↑
LPHC ↑
P:C ratio of 1:13 in males
and 1:11 in females ↑
20% BCAA ↔,
200% BCAA ↓c
↑ in WT males,
↔ in WT females,
↑ in LmnaG609G/G096G
miced
↑
↔
↑
2022
2023
2023
74
45
63
↑: Increased lifespan.
Juvenile mortality was higher while late-life mortality was lower in low-tryptophan-fed rats.
c
↓: Decreased lifespan.
d
LmnaG609G/G096G is an aging model characterized by accelerated aging.
Abbreviations: AA, amino acid; BCAA, branched chain amino acid; C, carbohydrate; LPHC, low-protein, high-carbohydrate diet; P, protein; WT,
wild-type.
a
b
observed in mice exposed to a 40% calorie restriction (174). Interestingly, due to protein leveraging, energy intake often increases during protein restriction, making it a less restrictive and
potentially more sustainable intervention.
4.2. Effects of Protein Restriction on Lifespan
The primary evidence supporting a beneficial effect of protein restriction on lifespan comes from
a wide range of research in invertebrate and vertebrate animal models, including flies (19, 60,
123), crickets (124), and rodents (56, 74, 79, 116, 173) (Table 2). As an alternative to total protein
restriction, the restriction of select amino acids also extends lifespan (18), including methionine
restriction (143, 215), threonine and/or tryptophan restriction (36, 142, 166, 205), and BCAA restriction (63, 158, 172). Thus, this expanding body of literature provides compelling support for
the conclusion that reductions in protein intake, whether total or amino acid-specific, are not detrimental but instead drive positive molecular, cellular, and physiological changes that collectively
increase longevity.
While protein restriction has been extensively tested in rodents, studies in rhesus monkeys
remain limited compared with those on calorie restriction. Existing protein restriction studies in
rhesus monkeys primarily focus on pregnancy, fetal development, and offspring health outcomes,
leaving the potential lifespan-extending effects of protein restriction largely unexplored. However,
we can learn some insights about the relationship between protein intake and lifespan from the
existing rhesus monkey calorie-restriction studies.
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Two calorie-restriction studies in rhesus monkeys have yielded contrasting results. One conducted by the National Institute on Aging (NIA) found no effect of calorie restriction on lifespan
extension (129), while the study conducted by the University of Wisconsin (UW) showed that
calorie restriction extended lifespan (32). When comparing these two studies in parallel, several differences in diet composition can be observed. The NIA diet contained 17.3% protein by
weight, sourced from soybean and fish meal, whereas the UW diet contained 13.13% protein by
weight with lactalbumin, an animal-based protein, as the primary source. Additionally, the NIA
diet was higher in protein, lower in fat, and higher in fiber compared with the UW diet. Both diets were approximately 60% carbohydrates by weight, but sucrose made up less than 7% of total
carbohydrates in the NIA diet compared with 45% in the UW diet. At NIA, calorie-restricted
monkeys received 30% less food than height-, age-, and sex-matched control monkeys, while at
UW, calorie restriction was tailored to individual monkeys. In summary, the monkeys in the UW
study, who were provided with a slightly less “healthy” diet, demonstrated lifespan extension under
calorie restriction, whereas the NIA monkeys, who consumed a higher-protein, plant-based diet,
did not exhibit significant lifespan differences between the calorie restriction and control groups
(128). These observations, while speculative, raise the possibility that differences in both protein
quantity and quality may modulate the effects of calorie restriction on lifespan and suggest that
protein intake, in terms of both amount and source, plays a role in shaping the outcomes of dietary
interventions on longevity.
The effect of protein restriction on longevity in humans remains inconclusive, as long-term
survival trials are impractical, and several observational studies showed mixed or nonsignificant
findings on the association between protein intake and mortality (Table 3). A key limitation of
these studies is that they are observational in nature and, thus, susceptible to confounding factors such as physical activity, socioeconomic status, and preexisting health conditions. When the
association between LCHP scores and mortality outcomes was analyzed, higher LCHP scores
were not significantly associated with all-cause mortality in most studies (103, 139, 190), but the
Nurses’ Health Study and Health Professionals’ Follow-up Study found an increased risk with
high LCHP score (50). When the association between protein intake and mortality outcome was
examined, the Rotterdam Study reported higher all-cause mortality in the highest quartile of protein intake (28). Other studies, such as the Kawasaki Aging and Wellbeing Project and studies on
older adults in Spain and Sweden, found lower mortality associated with higher protein intake
(23, 96). Another limitation is that the low-protein group in observational studies often does not
reflect an experimental level of protein restriction, as this group may still derive a significant proportion of energy from protein. This discrepancy complicates identifying correlations specifically
linked to protein restriction in epidemiological data. Finally, diet quality significantly influences
protein intake. High-protein consumption is often accompanied by increased meat and saturated
fat intake and reduced fiber intake, which could collectively contribute to adverse health outcomes.
Despite these limitations, important insights can still be drawn from the existing data. One
consistent finding is that the source of protein appears to be critical as a determinant of health
benefit. The follow-ups from the Nurses’ Health Study and the Health Professionals’ Follow-up
Study found that diets high in animal proteins and fats with low carbohydrate intake were associated with higher overall mortality, while plant-based low-carbohydrate diets appear protective,
reducing overall and cardiovascular mortality (50). Additionally, several prospective cohort studies
noted that different types of protein (animal versus plant-based) yield varying mortality outcomes
(28, 117, 176, 181). A recent systematic review also found that higher total protein intake, particularly from animal sources, was linked to increased all-cause mortality, whereas higher plant protein
intake was associated with reduced mortality risk (136). Mechanistically, these findings align with
studies suggesting that animal protein is richer in BCAAs, which can elevate insulin resistance
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42,192 adults
102,521 women
833 adults
8,543 adults
Korean cohort
Women’s Health Initiative Study
Kawasaki Aging and Wellbeing
Project
Study on Cardiovascular Health;
Nutrition and Frailty in Older
Adults in Spain 1 and 2;
Swedish National Study on
Aging and Care in
Kungsholmen
P intake
P intake (quartiles)
Animal and plant P
intake (quintiles)
NS for high animal P;
↓ for high plant P
NA
NA
NS for high animal P;
↓ for high plant P
↓ in Q4
↓
NA
NA
NA
NS
NA
NS
↑ in Q4 animal P
↑ in Q4
NS
NA
↑ for high animal P;
↓ for high plant P
NS for high animal P;
↓ for high plant P
23
96
181
97
28
176
117
139
b
↑: Increased risk or association.
↓: Decreased risk or association.
Abbreviations: C, carbohydrate; CHD, coronary heart disease; CVD, cardiovascular disease; E, energy; F, fat; LCHP, low-carbohydrate, high-protein; NA, not available; NS, not significant;
P, protein; Q, quartile.
a
P intake (quartiles)
7,786 adults
Rotterdam Study
P intake
%E for animal and
plant P
NS
↓ in low P (<65 years);
↑ in low P (66+ years)
↓ in low P (<65 years);
↑ in low P (66+
years)
P intake (high >20%
E, low <10% E)
6,381 adults
US cohort
NS
NS
NS
LCHP score (from
deciles of C and P
intake)
77,319 adults
May 5, 2025
Nurses’ Health Study; Health
85,013 women,
Professionals’ Follow-up Study
46,329 men
Reference
103
(50)
Cancer mortality
↑ in high LCHP score, ↑ in high LCHP score ↑ in high LCHP score
↑ in high LCHP
based on animal P,
based on animal P
score based on
↓ in LCHP score
animal P, ↓b in
based on
LCHP score based on
vegetable P
vegetable P
NA
190
↑a in high LCHP
score
CVD/ CHD
mortality
↑ in high LCHP score ↑ in high LCHP score
NS
Swedish cohort
LCHP score (from
deciles of C and P
intake)
NS
All-cause mortality
LC score (from
deciles of %E from
C, P, and F)
22,944 adults
European Prospective
Investigation into Cancer and
Nutrition (EPIC) Study
LCHP score (from
deciles of C and P
intake)
Assessment
ARjats.cls
Nurses’ Health Study; Health
85,168 women,
Professionals’ Follow-up Study
44,548 men
42,237 women
Number of
participants
Swedish Women’s Lifestyle and
Health Cohort
Study
Table 3 Prospective studies on protein intake and mortality in humans
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and insulin-like growth factor 1 (IGF1) levels and contribute to age-related diseases (137, 163). In
contrast, plant proteins have lower EAA content (e.g., leucine, lysine, methionine) and are rich in
fiber, phytochemicals, and micronutrients, which may offer metabolic and cardiovascular benefits
(57).
Another important factor is the age-dependent effect of protein intake. Levine et al. (117) examined the relationship between protein intake and mortality in a US cohort of 6,381 individuals
aged 50 and older. They found that high protein intake (≥20% of calories) increased all-cause and
cancer-related mortality risk compared with low protein intake (<10% of calories) among individuals aged 50–65, while high protein intake reduced all-cause and cancer mortality risk compared
with low protein intake in individuals aged 66 and older (117). Given the result from a mouse study
showing that increasing protein relative to carbohydrates in later life could minimize age-specific
mortality and optimize lifespan (167), adjusting protein intake in an age-specific manner may
be crucial for maximizing longevity. Further stratification of age groups may help better capture
age-dependent effects in mortality analysis.
Finally, cultural dietary patterns must be considered when interpreting epidemiological findings. Traditional Asian diets tend to be higher in carbohydrates and lower in fat and animal-based
protein, whereas Western diets typically include higher fat and animal protein intake, with 60–
80% of protein coming from animal sources (192). These differences in dietary composition and
lifestyle factors could influence mortality outcomes and complicate cross-population comparisons.
Future studies should aim to account for dietary diversity and consider confounding factors to
better understand the nuanced effects of protein restriction on human health and lifespan.
In summary, the effect of protein restriction on lifespan and longevity is well-supported
across multiple species, where reductions in total protein intake or restriction of specific amino
acids consistently extend lifespan. These effects suggest the presence of evolutionarily conserved
mechanisms through which protein restriction modulates aging that are potentially applicable
to humans. However, observational studies in humans have yielded mixed results, likely due to
variations in study design and confounding factors. Future studies should account for these variations and integrate mechanistic findings from animal models to better understand how protein
restriction influences human aging and longevity.
4.3. Effects of Protein Restriction on Metabolic Health and Prevention
of Age-Related Diseases
Protein restriction profoundly affects metabolic health, with the most noticeable outcome being
a reduction of excess weight in animals and in humans (9, 17, 44, 47, 74, 77, 100, 122, 174). For
instance, protein-restricted diets with 7–9% of energy from protein decreased body weight in
persons with obesity (44, 47). Furthermore, in healthy volunteers with a body mass index between
19 and 30, hypercaloric diets with 5% energy from protein reduced weight gain compared to diets
with higher protein content (17).
Beyond body weight, protein restriction enhances metabolic flexibility by improving glucose
and lipid metabolism (9, 74, 77, 100, 122, 174). Conversely, prospective cohort studies found that
total and animal protein intake increases the risk of type 2 diabetes (169, 206). Interestingly, similar
benefits are observed with selective amino acid restriction, particularly methionine (70, 180, 211),
BCAAs (35, 47, 172, 189), leucine (66, 195, 204), isoleucine (63, 210), histidine (45), threonine, and
tryptophan (205). However, high protein intake, particularly through BCAA-enriched diets, has
been linked to insulin resistance and metabolic dysfunction (137). Notably, the beneficial effects
of low-protein or amino acid–restricted diets on metabolic health are evident in both aging and
diet-induced obesity models, as protein restriction not only improves health when initiated in aged
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animals but also prevents high-fat-diet-induced weight gain and impaired glucose homeostasis (74,
207). These data suggest that protein restriction not only prevents metabolic diseases but also can
reverse some metabolic impairments.
Along with improvements in metabolic health, the beneficial effects of protein restriction also
extend to other age-related diseases, including cancer and neurodegenerative disease. Rapidly dividing cancer cells are particularly sensitive to nutrient restriction, and the restriction of various
amino acids impairs the growth of cancer cells in culture while also enhancing the efficacy of
chemotherapeutic agents (148, 194). Several in vivo studies indicate that reduced protein or amino
acid intake produces anticancer changes in metabolic and cellular end points, reducing the occurrence of spontaneous tumors with age and inhibiting tumor growth in xenograft models (46, 121).
Epidemiological data further indicate that high protein intake is associated with increased cancer
risk, although this effect varies depending on the protein source (e.g., animal versus plant protein),
as mentioned above (117). Finally, a recent finding suggests that low-protein diets improve brain
health and cognitive function in aging models (9). However, conflicting findings exist, highlighting the need for further investigation into the long-term neurological effects of protein restriction
(165, 208).
Overall, protein restriction enhances metabolic health and shows potential for preventing and
mitigating age-related diseases, including cancer and neurodegeneration, in both in vitro and in
vivo models. Observational studies further suggest that high protein intake, particularly from animal sources, is associated with an increased risk of type 2 diabetes and cancer. Although it is
premature to draw a definitive conclusion, current evidence from animal models and cellular studies suggests that dietary protein modulation is a promising strategy for promoting metabolic health
and slowing age-related diseases. Further research is needed to elucidate precise mechanisms and
establish more concrete evidence from human studies.
4.4. Balancing the Positive and Negative Aspects of Protein Restriction
The above discussion highlights the beneficial effects of protein restriction on longevity, metabolic
health, cancer incidence, and brain health, while also highlighting the negative impacts of protein
restriction on growth, muscle mass, and resilience. How do we balance such competing effects?
It is essential to recognize that protein restriction is not a single intervention but rather a spectrum ranging from mild restriction to severe deprivation. While it is well established that severe
protein restriction/deprivation produces adverse effects, the effects of moderate protein restriction
are less clear. For instance, dietary protein restriction variably impacts immune function, depending on the severity of restriction and the specific immune response (cellular versus humoral) (55,
118). While severe protein restriction produces uniformly adverse effects, modest restriction may
exert beneficial effects in some circumstances, particularly cellular immunity (43, 144). Wound
healing is another end point influenced by protein status. Again, evidence strongly indicates that
severe protein restriction impairs wound healing (146), yet more moderate restriction has been
linked to beneficial effects (73). These data highlight that protein deprivation/malnutrition negatively impacts various physiological processes, yet a modest, controlled restriction may avoid these
negative effects or even produce positive outcomes in some situations.
The impact of protein restriction must also be considered in the context of the individual’s environment and physiology. While protein restriction extends lifespan in model organisms, nearly all
these studies are conducted in a highly controlled environment. Considering the impact of protein
restriction on immune function and wound healing, the benefit of protein restriction might be less
apparent in more naturalistic contexts where the individual is exposed to pathogens, injury, tissue
repair, or extensive physical exertion. Physiological state is also an important consideration, with
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pregnancy and early development as clear examples. Protein restriction is a standard experimental
model of intrauterine growth retardation and can produce negative impacts on the developing
fetus as well as effects on metabolism and immune function that persist into adulthood (72, 216).
Advanced age is another state in which protein restriction may not be desirable, as relatively recent work in both mice and humans suggests that protein restriction produced protective effects
in middle age but increased mortality at advanced ages (117). Taken together, these observations
highlight that both the positive and negative impacts of protein restriction can vary depending on
the severity of restriction and the state of the individual.
Targeted interventions might be useful in mitigating the adverse effects of protein restriction.
As noted above, protein restriction has a clear dose effect, such that careful titration or reduction
in the level of restriction may trigger beneficial metabolic or immunological effects without substantial impacts on lean mass. Resistance exercise may also offset adverse effects on muscle mass
and strength during protein restriction and should be recommended in any setting of potential
muscle/functional loss (e.g., advancing age). Strategic supplementation with specific EAAs may
also help stimulate muscle protein synthesis, although recent work indicates that BCAA restriction benefits metabolism and lifespan ((158). Ultimately, the level of protein restriction should be
tailored to individual circumstances, as there is no one-size-fits-all approach. The goal is to maximize metabolic benefits while using targeted exercise and supplementation to mitigate adverse
effects on lean mass, resilience, and immune function.
5. MECHANISMS DRIVING THE EFFECTS OF DIETARY
PROTEIN RESTRICTION
Dietary protein restriction exerts broad effects on multiple physiological end points, including
food intake, body weight, lean body mass, longevity, and metabolism. How does it produce these
effects? Here we discuss the effects on overall physiological processes and then focus on underlying
endocrine and cellular mechanisms.
5.1. Physiological Changes: Energy Intake and Expenditure
We previously discussed that low-protein diets tend to increase food intake because protein intake is defended. While a key physiological effect of protein restriction is an increase in food
intake, another common observation is an increase in energy expenditure that was first described
in rodents more than 40 years ago (160, 161). The low-protein-induced increase in energy expenditure and reduction in feed efficiency is associated with increased uncoupling protein 1 (Ucp1)
gene expression in both brown adipose tissue (BAT) and white adipose tissues (WAT) (159), suggesting that protein restriction drives UCP1-dependent thermogenesis. More recent work has
broadly supported this effect, as multiple studies indicate that protein restriction increases energy
expenditure, activates BAT, and remodels (browns) WAT (70, 78, 101, 205, 212). This increase in
energy expenditure depends on UCP1, occurs at both room temperature and thermoneutrality,
and is not dependent on hyperphagia (77). As discussed below, our work suggests that increased
energy expenditure requires FGF21 action in the brain, and it is speculated that the increased
energy expenditure is an adaptive mechanism that allows the animal to overeat low-protein diets
to gain additional protein (170).
In line with rodent studies, a recent human study also supports the effects of protein restriction
on energy balance. When healthy, lean male volunteers consumed a protein-restricted diet with
∼9% of energy from protein for 5 weeks, they required a progressive increase in energy intake
to maintain body weight (138). When participants returned to an equicaloric higher protein diet,
their energy intake requirement was progressively reduced after 6–8 days to baseline levels to
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prevent weight gain, emphasizing the important role of dietary protein intake on energy requirement. Additional analysis of the inguinal WAT proteome showed that UCP1 was not increased
but that proteins of the mitochondrial electron transport chain were altered under protein
restriction in wild-type mice and in humans, which was not observed in FGF21-knockout mice.
These data suggest that uncoupling or a leak within the electron transport chain in WAT, potentially induced by FGF21, contributes to increased energy expenditure under protein restriction
(138). Collectively, the increase in energy expenditure appears to be a core physiological response
to protein restriction, and the broad remodeling/reprogramming of adipose tissue and other
metabolic end points may contribute to effects on glucose homeostasis, metabolic health, and
potentially longevity.
5.2. Cell-Autonomous, Intracellular Mediators of Protein Restriction
Cells adapt to plasma amino acid levels by regulating metabolic functions accordingly. Amino
acids in the plasma are transported into cells through amino acid transporters, primarily solute
carrier proteins. Once inside the cell, these amino acids activate nutrient sensors such as Sestrin2,
S-adenosylmethionine sensor upstream of mTORC1 (SAMTOR), or cellular arginine sensor for
mTORC1 (CASTOR1), which in turn stimulate mechanistic target of rapamycin 1 (mTORC1)
signaling. In contrast, amino acid deprivation triggers the activation of general control nonderepressible 2 (GCN2) kinase. Beyond mTORC1 and GCN2, other nutrient-sensing pathways also
contribute to the cellular response to dietary protein restriction. These include AMPK, PI3K,
Akt, and other signaling systems (34, 61, 84). As depicted in Figure 3, these pathways are highly
interconnected and interact with one another (8, 67). As a result, manipulating a single signaling
pathway often affects others, highlighting the complexity of nutrient-sensing mechanisms.
5.2.1. mTORC1 and autophagy. mTOR is a critical mediator of the cellular effects of amino
acids (87, 104). mTORC1, a subunit of mTOR, plays a key role in linking cellular growth and
metabolism to nutrient availability. Amino acids, particularly leucine, arginine, and methionine,
activate mTOR activity both in vivo and in vitro (16, 27, 51, 54, 64, 119, 164), while the inhibition of mTOR signaling via either pharmacological (rapamycin) or genetic means produces robust
effects on lifespan in many species (61). The effects of protein restriction on a variety of stressor injury-related end points are blunted by mTOR inhibition (68) and so are the effects of protein restriction on tumor growth (105). Conversely, the evidence also suggests that the activation
of mTOR contributes to the induction of insulin resistance in response to high-protein diets in
settings of obesity (88, 106). Amino acids also regulate autophagy through mTORC1 activity.
Autophagy removes protein aggregates or damaged organelles to maintain intracellular homeostasis, and protein restriction impacts metabolic end points at least in part by inducing autophagy
(71, 94). These data collectively suggest that the mTORC1 pathway and autophagy contribute
to adaptive responses to protein restriction, although definitive evidence indicating that they are
critical for the longevity effects of protein restriction is lacking.
5.2.2. GCN2. Another important intracellular sensor of amino acids is GCN2. As a component
of the integrated stress response, GCN2 phosphorylates eukaryotic initiation factor 2 (eIF2α)
in response to the depletion of cellular amino acids (198), leading to the inhibition of general
protein synthesis while increasing the translation of specific transcription factors, such as activating
transcription factor 4 (ATF4), which coordinate adaptive responses to nutritional stress. GCN2dependent phosphorylation of eIF2α and resultant activation of ATF4 links amino acid availability
to metabolism, particularly in the liver (6, 40, 66, 204, 213). In addition to contributing to amino
acid sensing at the cellular level, GCN2 is also critical for the longevity effects of both nutrient
restriction and TOR inhibition in worms (162). In rodents, GCN2 and downstream mediators
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Low protein/AA
IGF1
Uncharged tRNA
GATOR complex
GCN2
GCN2
Inactive
Active
eIF2α
Selective
translations
ATF4
Dimerization
partner
ATF4
PI3K
AKT
FOXO
↑ Metabolic
health
Activation
Repression
Transcription
mTORC1
↓ Protein
synthesis
↑ Autophagy
AMPK
FGF21
↑ Energy expenditure
↑ Protein appetite
↑ Metabolic health
↑ Cell survival
↑ Antioxidant defense
↑ Metabolic enzymes
↑ Unfolded protein response
↓ Cell senescence
Aging
Figure 3
Multiple pathways activated/inhibited by protein restriction. Protein restriction activates GCN2 in response
to uncharged tRNAs, leading to phosphorylation of eIF2α and selective translation of specific mRNAs,
including ATF4. ATF4 drives the expression of genes, such as FGF21, which enhance energy expenditure,
protein appetite, and metabolic health, as well as other adaptive genes that overall promote cell survival.
Simultaneously, protein restriction suppresses mTORC1 activity through reduced signaling via the
IGF1-PI3K-AKT pathway and activation of AMPK. mTORC1 inhibition leads to decreased protein
synthesis and enhanced autophagy, contributing to improved metabolic health. The GATOR complex also
integrates signals from upstream nutrient sensors to regulate mTORC1 activity. Reduced mTORC1 and
enhanced AMPK activity also activate FOXO transcription factors, further supporting metabolic adaptation
under protein restriction. These pathways collectively contribute to extension of health span through
coordinated regulation of whole-body metabolism. Abbreviations: AA, amino acid; AMPK, AMP-activated
protein kinase; ATF4, activating transcription factor 4; eIF2α, eukaryotic initiation factor 2; FGF21,
fibroblast growth factor 21; FOXO, forkhead box O; GATOR, GTPase-activating protein toward Rags;
GCN2, general control nonderepressible 2; IGF1, insulin-like growth factor 1; mRNA, messenger RNA;
mTORC1, mammalian target of rapamycin complex 1; PI3K, phosphoinositide 3-kinase; tRNA, transfer
RNA.
such as ATF4 have been linked to responses to dietary protein or amino acid restriction (85),
as well as the cancer therapeutic asparaginase (2, 20). Our work indicates that GCN2 deletion
also blocks adaptive changes in food intake and energy expenditure in response to dietary protein
restriction, although this GCN2 dependency is transient, such that mice begin exhibiting typical
responses to the low-protein diet after 2 weeks (100). GCN2 appears to be completely unnecessary
for metabolic responses to methionine restriction (196), although ATF4 contributes to some but
not all effects of sulfur amino acid restriction (84).
5.3. Endocrine Systems That Mediate the Response to Protein Restriction
While multiple nutrient-sensitive intracellular signaling pathways are responsive to changes in
amino acid availability, this cellular sensing model is based on the hypothesis that each cell individually detects reduced amino acid availability (cell-autonomously) and responds in a largely
uncoordinated manner. These mechanisms are clearly engaged in cultured cells, and genetic or
pharmacological manipulation of these signaling molecules impacts metabolic and/or longevity
end points in vivo. However, whether these cell-autonomous molecules coordinate the adaptive
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response to reduced dietary protein intake in a more physiological context is unclear. For instance, low-protein diets generally produce only modest reductions in circulating amino acids
due to adaptive changes in liver metabolism (47). Additionally, our work suggests that changes
in circulating amino acids are not responsible for the changes in food intake observed with lowprotein diets (102). Therefore, key endocrine signaling molecules may be critical in coordinating
adaptive responses to protein restriction.
5.3.1. Insulin-like growth factor 1. The growth hormone/insulin-like growth factor 1
(GH/IGF1) system plays a critical role in growth and cellular function, including coordinating
organismal growth with nutrient availability. Deletion of GH produces a robust lifespan extension
(1, 86) and protects against the metabolic effects of high-fat diets (76). Humans with GH receptor
mutations that lead to deficiencies in serum IGF1 and insulin levels show protection from cancer
and diabetes (65, 179). A key factor of GH signaling is the stimulation of IGF1 production from
the liver, and while global IGF1 deletion is lethal, multiple studies indicate that lowering IGF1
extends lifespan (33, 184). Importantly, IGF1 levels are closely linked to nutritional intake, and
protein restriction reduces plasma IGF1 in rodents (4, 39) and humans (48, 117). Interestingly,
a recent meta-analysis of 19 prospective cohort studies showed a U-shaped association between
IGF1 level and mortality in humans, where both low and high IGF1 levels are linked to increased
mortality risk (154). Together, these data strongly suggest that reductions in circulating IGF1 levels are likely to contribute to the effects of dietary protein restriction on metabolic health and
longevity.
5.3.2. FGF21. FGF21 is a member of the endocrine family of fibroblast growth factors. FGF21
is expressed in multiple tissues, including the adipose tissue and liver, but current evidence suggests
that circulating FGF21 is primarily derived from the liver (125). Circulating FGF21 is increased
by fasting in rodents (10, 80) but not in humans (31, 52). More recent work indicates that FGF21
is primarily increased by dietary macronutrient imbalance, particularly reduced protein but increased carbohydrate intake (37, 59, 101, 122, 155, 171, 192). Most importantly, FGF21 is required
for mice to adaptively respond to protein restriction, as the deletion of FGF21 blocks the effects
of protein restriction on food intake, growth, energy expenditure, adipose tissue browning, and
glucose homeostasis (77, 78, 100, 101, 122, 205). These effects also impact longevity, as transgenic overexpression of FGF21 promotes longevity (214), while deletion of FGF21 blocks the
lifespan-extending effects of protein restriction FGF21 in male mice (74).
In addition to its effects on metabolism and longevity, FGF21 also plays a critical role in regulating macronutrient preference. Protein restriction produces a selective increase in the preference
and motivation to consume protein (e.g., a protein appetite), but these physiological shifts in protein preference and motivation do not occur in FGF21-knockout mice nor in mice lacking FGF21
signaling in the brain (78, 90). Conversely, FGF21 treatment increases protein intake and reduces
the consumption of sugar and alcohol (108, 170, 183, 193, 202). These data collectively suggest
that protein restriction triggers FGF21 secretion from the liver, with FGF21 then acting in the
brain to adaptively alter food preference/motivation, energy expenditure, metabolism, and growth
in a manner that induces beneficial effects on health and lifespan (75, 89, 93).
6. CONCLUSION
Dietary interventions remain one of the most practical and cost-effective strategies for maintaining metabolic health and addressing age-related diseases (153). Numerous studies highlight the
potential benefits of moderate protein restriction in these areas. This review aims to explore and
clarify the current understanding of protein intake, acknowledging that it is a vast and complex
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topic that cannot be comprehensively addressed in a single review. However, we emphasize several
conclusions and points of future research.
First, recommending a specific level of protein intake to the general population is challenging,
and this review does not take a particular stance on optimal protein levels. Animal studies indicate
that protein restriction positively affects metabolism and longevity, yet protein restriction may
produce adverse outcomes depending on age and physiological state. Conversely, high protein
may support lean mass when combined with resistance training or during weight loss; however,
high protein without exercise or reduced caloric intake probably provides little benefit and is
linked with increased mortality.
Second, while various regulatory mechanisms act to coordinate cellular and physiological responses to low or high protein intake, the mechanisms that primarily drive the beneficial effects
of protein restriction remain unclear. It is also unclear whether any individual mechanism alone
can be targeted to promote human longevity. For instance, signaling molecules such as mTOR
are clearly impacted by amino acid availability, and inhibition of mTOR is well-established to
promote longevity in model organisms. Similarly, FGF21 mediates many of protein restriction’s
behavioral and metabolic effects, including lifespan extension. However, FGF21’s contribution
may vary according to sex and genetic background (62), and FGF21 contributes to the effects
of amino acid restriction in some but not all cases (45, 49). Therefore, while FGF21 contributes
to the response to protein restriction, it seems unlikely that any single molecule will mediate its
broad effects overall.
Third, would applying protein restriction at a specific age avoid the negative effects on growth
while eliciting beneficial effects on lifespan and health span? For instance, few people would advocate for significant protein restriction in young, rapidly developing children, during pregnancy,
or at advanced ages. Could significant benefits be observed if protein restriction were applied only
during critical target periods (e.g., middle age)?
Fourth, to what extent does the protein source impact outcomes? Many epidemiological studies
show that animal-derived proteins contribute to age-related mortality and diseases. Early work in
rats indicated that changing the protein source from casein to soy, while keeping the caloric content the same, conferred an increase in the lifespan of rats (82). Conversely, recent work comparing
animal- versus plant-based diets indicates that total protein intake is the critical factor, not protein
source (120).
Collectively, these observations highlight the relative paucity of human clinical trials involving protein restriction, particularly as compared with overall food or fat/sugar restriction. It is
currently problematic to recommend a specific level of protein restriction, and additional work is
necessary to test whether a low-protein diet can effectively balance the positive versus negative
effects of protein restriction. Such studies must also account for age and physiological state and
assess whether specific interventions, such as resistance exercise, can offset any detrimental effects.
Adherence to protein-restricted diets is also an open question, as rodents clearly detect a state of
protein restriction and adapt by increasing protein motivation and consumption (29, 30, 90). Finally, additional opportunities exist for outlining the biological mechanism of protein restriction,
including the contribution and mechanism of FGF21 action, the contribution of other amino acid
signaling pathways (mTOR, GCN2, etc.), whether restriction of select amino acids activates similar or distinct mechanisms, and the extent to which known mechanisms in rodents translate to
humans.
In summary, dietary protein plays a key role in feeding behavior, metabolism, growth, and
longevity. Multiple endocrine and cell signaling mechanisms exist to detect protein availability,
while reductions in protein intake trigger adaptive changes in nutrient preference, growth, energy
expenditure, and cellular signaling. Public nutritional literature frequently emphasizes consuming
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adequate or excess dietary protein, on the basis of evidence that protein promotes satiety and
maintains lean mass. However, research in model organisms shows that reduced protein intake
promotes metabolic health and longevity, while high protein intake correlates with increased
mortality in humans. Therefore, broad recommendations for excess protein intake should be
approached with caution, particularly for sedentary individuals not actively pursuing weight loss.
Conversely, while protein restriction shows promise in animal models, additional research is
needed to determine whether these benefits translate to humans.
DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings that
might be perceived as affecting the objectivity of this review.
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