Role of ingested amino acids/protein in the promotion of resistance exercise-training adaptations in aging: analysis of meta-analyses

Abbreviations

1Introduction

Human aging is characterized by the gradual loss of muscle mass and strength [1, 2], accelerated in periods of inactivity and illness [3, 4]. As these decrements compound, they contribute to loss of vital lean mass and functional strength, resulting in limitations of functional independence, development of disability, [5] and a greater susceptibility to poor health. These emerging concerns present a mounting health care burden. Thus, strategies to maintain musculoskeletal health, delay entry into the disability threshold, and prolong quality of life are of prime importance for the booming aging population. Readily available, inexpensive, and modifiable lifestyle modifications such as exercise and nutrition are commonly thought to be effective strategies in this regard. In particular, resistance exercise, when performed over a period of time, clearly yields many systemic health benefits, in particular, increased muscle mass, strength, and functional independence [6]. Many recent reports have promoted the combined effectiveness of resistance exercise and protein and/or amino acid supplementation (PRO/AA) compared to these interventions in isolation (resistance exercise or protein nutrition) to maximize these health outcomes and help mitigate the cost of the looming health care crisis. Over two decades ago the estimated economic burden of sarcopenia was ∼$20 billion [7]. The costs have increased as persons with sarcopenia are more expensive to care for [8] and more likely to be hospitalized and readmitted [9] There have been less systematic reviews or meta-analyses that describe the phenotypic result or even the clinical relevance of PRO supplementation during RET in older adults - until the past decade. Unfortunately, the consensus from these meta-analyses have been contradictory and unclear, making interpretation and application for the healthcare professional challenging. Therefore, our goal in this review is to critically assess the collection of meta-analytic evidence to provide clarity regarding the differences between meta-analyses examining the combined effectiveness of chronic exposure to PRO/AA supplementation and resistance exercise to enhance the adaptive response.

2Methods

We have set out to provide a critical examination of the meta-analytic evidence characterizing the physiological and phenotypic response of human muscle adaptation and to determine whether giving PRO/AA in close proximity to resistance exercise enhances this effect. The evidence was collected by database searches of reviews and hand-searching author lists on the topic. Population: analysis of older adults (> 40y) as a main analysis, or a subgroup analysis. Intervention: Resistance exercise training and protein and/or amino acid nutrition with and without other nutrients. Resistance exercise training is defined as non-continuous dynamic exercise with defined sets and repetitions to contract against a posing force to generate external resistance with intent to increase muscle size and strength. Comparison: A comparison of the above intervention vs. resistance exercise training plus placebo or resistance exercise alone. All comparisons must include resistance exercise training (> 4 weeks in duration). Outcomes: Include a measure of body composition, muscle mass/size, strength, physical function testing. Physical function testing included, but was not limited to short physical performance battery (SPPB), gait speed, timed up and go (TUG), walk capacity and/or chair rise testing. Type of study design: Meta-analyses studies of Randomized Clinical Controlled Trials (RCTs). Search methods for identification of studies: We searched MEDLINE (including in-process and other non-indexed citations), Biomedical Reference Collection: Pubmed, CINAHL, Web of Science, SPORTDiscus, and reference lists of articles (in June 2021). Several studies were not retrieved via standard methods. The most fruitful method of discovering studies were 1) manually searching for articles published by researchers who are well-known to work in the area of muscle protein metabolism/exercise training, 2) using the reference lists of all retrieved articles to identify potentially missing sources, and 3) using key papers on the topic to select PubMed’s “similar” and “cited by” search options combined with the “meta-analysis” filter. As such, we comprehensively and critically assessed all the RCTs (see tables), to our knowledge, regarding the meta-analytic assessment of chronic exposure to RET and PRO/AA supplementation in older adults.

3Results and discussion

Thirteen meta-analyses were discovered that met our criteria. Eight other studies were excluded because they could not address our research question concerning older adults described in the methods. Hudson et al. [10], Bergia et al. [11], Valenzuela et al. [12], and Messina et al. [13] did not have a subgroup analysis for older adults alone, restricted to our topic and question. Hita-Contreras et al. 2018 [14] did not have a comparison of resistance exercise versus resistance exercise plus supplementation. Cheng et al. [15] and Liao et al. [16] were too broad with their exercise type by including aerobic exercise and rehabilitation from injury. Since Colonetti et al. [17] included only one study and Thomas et al. [18] were excluded for having too few studies (<2) included in the qualitative analysis.

The titles, main outcomes examined, and the number of participants per outcome from these meta-analyses on the topic are summarized in Table 1 and the descriptive characteristics of these meta-analyses are in Table 2. Table 1 also shows the number of participants per meta-analysis for the pooled estimate of each outcome they examined. The number of subjects pooled for analysis has not linearly increased over the years, suggesting these analyses were more distinct than what most of their titles would suggest. All but two studies examined fat-free/lean mass [27, 33] for this indirect estimation of muscle mass. All but two meta-analyses [19, 20] examined a measure of muscle strength. Physical function was examined in six studies [20–25]. Direct measures of muscle mass and size were only examined in three meta-analyses [22, 24, 26]. Myofiber size changes, for older adults only, were only reported in one meta-analysis [27]. The titles of these studies suggest very similar goals upon first glance, but examination of the methods and characteristics of included studies for these meta-analytic studies reveals several distinctions. The standout areas include differences in inclusion and exclusion criteria, participant population, and analytical approach, specifically heterogeneity of pooled outcomes and approach to estimate incomplete data.

Unfortunately, an area of confusion is that these meta-analyses have different results but very similar titles. Mostly all these meta-analyses provide the general title of “effects of protein supplementation on…etc., yet a few distinctly specify whey protein [19, 28], milk protein only [29], “multi-ingredient protein” [30] or more generally, “nutrient” [25] in their titles. Those studies not restricted to whey or milk proteins took a few different and somewhat unclear approaches as described below. A few studies were entitled “protein supplementation” and actually defined criteria in their excluding protein supplementation with other “potentially hypertrophic agents” or “supplements known to induce muscle hypertrophy” [21, 26, 27, 31]. This very broad classification was normally a very short list with one to three items mentioned. The only consistent item mentioned was creatine, which was mentioned six times [21, 26–28, 30, 31] - what other items authors chose to exclude under that umbrella term remain unknown. Another study was more strict and even mentioned exclusion of added carbohydrates and fat, yet it included egg and milk-based supplementation/diet, which includes those macronutrients [26]. A protein-containing multi-ingredient meta-analysis accepted all forms of supplementation that contained protein, but specifically excluded androgenic agents [30]. One study excluded “other hypertrophic” (creatine and β-HMB) and androgenic agents [31]. Some studies marketing “protein supplementation” in the title could have been more specific to reflect their use of any protein-enriched supplement, whether it was multi-nutrient or not [22–24]. One study with “nutritional supplementation” in the title was less broad in actuality as it only examined “protein-containing nutritional supplementation” [25].

4Effect on fat-free mass/ lean mass

A statistically significant effect of PRO/AA during RET in older adults on total fat-free/lean mass was found in eight meta-analyses (17,21–23,26,27,29,30) with mean difference (MD) effects of 0.23–0.81 kg or about 0.23 to 5.78 as standardized mean difference (SMD) (Fig. 1 and Table 2). Whereas three meta-analyses did not find an effect on fat-free mass (FFM) [24, 28, 31] a few meta-analyses did not examine this metric [19, 20]. A few studies collected data on regional lean mass (appendicular, arm, leg), and a significant effect (0.39 kg MD; 0.3–0.4 SMD) was found in two studies [21, 22] with borderline insignificance in a third [23]. However, these latter studies were primarily enriched with sarcopenic and frail participants.

Fig. 1

Meta-analysis-calculated effects of protein supplementation and resistance exercise training compared to resistance exercise training with or without placebo in older adults for the outcomes of tissue composition, strength and physical function. Panels A, C and E show the mean difference (MD) of Protein vs Placebo for tissue composition (A), Strength (C) and physical function (C). Panels B, D and F show the standardized mean difference (MD) of Protein vs Placebo for tissue composition (B), Strength (D) and physical function (F). Data are MD or SMD with 95% CI as extracted from each meta-analysis. Effect favoring protein is to the right and the effect favoring placebo is to the left on the x-axis.

5Effect on fat mass

A statistically significant effect of PRO/AA during RET in older adults on total fat-free/lean mass was only found in two [21, 22] but not four [25, 27–29] other meta-analyses The MD effect magnitude ranged from –0.19 to 0.62 kg and SMD from –0.61 to –2.5.

6Effect on strength

There was a wide variety of strength measures utilized in the RCTs, so the meta-analyses often categorized them as upper or lower body exercises and which required use the SMD metric as the pooled estimate. Six of the 12 meta-analyses that examined muscle strength found statistically significant effects of PRO/AA during RET in older adults on at least one of the strength outcomes they assessed [21–23, 25, 27, 30], whereas the remaining found no effects in any strength outcomes [19, 20, 24, 26, 28, 31]. These studies demonstrating some effect were focused on multi-nutrient protein containing supplements [22, 23, 25, 30] or contained an enrichment of sarcopenic/frail participants [21–23, 25] with most of the effects found in the leg [21–23, 25, 27], but one of four studies revealed an effect in the upper body [30]. Type of strength assessment and frequency of use by chosen RCTs is another potential reason for divergence in results. For example: Cermak et al. [27] used leg press muscle strength from three studies, Finger et al. [26] used knee extension 1RM from ten studies. Other studies conducted multiple analyses for each individual exercise test [19, 21, 25, 26], sub-classified them as all leg/lower limb [20–24, 27, 30) or upper limb 20, 22, 24, 30], or pooled them all together [28].

7Effect on muscle mass and myofiber size

A statistically significant effect of PRO/AA during RET in older adults on muscle mass/volume/size was found in one (SMD: 1.23) [22] but not the others (SMD: 0.09–0.14) [24, 26] meta-analyses. The likely reason for this difference is that those analyses that found an effect included a high enrichment of sarcopenic participants [22, 25]. Additionally, further analysis of one study [25] revealed that its pooled estimate of “muscle mass” was only a bioelectrical impedance derived estimate and not a direct measure of muscle mass. Few studies have reported direct assessments of muscle mass/size like the expensive gold standard MRI [32]. It should be noted that Finger et al. included both myofiber CSA and whole muscle size measures into their pooled estimate of muscle size [26]. Only one meta-analysis investigated the effect of PRO/AA during RET in older adults specifically on myofiber cross-sectional area [27], and it demonstrated no effect in either slow or fast twitch myofibers.

8Effect on physical function

Three meta-analyses found no effect on any physical function outcome [20, 20, 24]. The remaining meta-analyses had several physical function outcomes yet only one statistically significant effect of PRO/AA during RET in older adults of those outcome of physical function [22, 23, 25]. Thus, many physical function outcomes in those studies were not significant, even though they were enriched with sarcopenic and frail patients who would arguably demonstrate the greatest improvement as they would have the most to gain. Liao et al. 2017 only found a significant effect with the short physical performance battery (SPPB), but not gait speed, physical activity, timed up and go (TUG), or chair rise protocols [22]. Luo et al. 2017 only investigated usual walk speed 0.57 (0.19, 0.95) [25] and Liao et al. 2019 only found a significant effect with walk capacity, but not chair rise tests [23].

9Relevance of these pooled estimates

These meta-analyses have collectively demonstrated that the effects of protein supplementation on enhancing the adaptations of resistance exercise training in older adults are not easily apparent, and it is more difficult to observe significance for outcomes of physical function, strength, muscle mass, and fat mass compared to fat-free mass. Although protein supplementation in older adults does not often improve strength or physical function beyond the improvements seen with resistance exercise training alone, some increase in lean body mass may occur. Enhancement could provide potential for fatigue resistance [33], a greater postabsorptive glucose disposal, or the presence of a greater amino acid reservoir acting as a buffer against the acute periods of sickness, injury, or disuse common with aging [34].

One could argue that most studies showing no effect for PRO were underpowered for their outcome of interest. Although some RCTs do report how they determine sample size goals, most calculations are centered on whole body FFM as the primary outcome. Future studies are advised to describe this and to be clearer in reporting variability and mean of the change values of their outcomes such that effect size/sample size estimations can be calculated for more specific outcomes. To determine whether studies are appropriately powered to show a chronic effect of PRO/AA supplementation during RET, we extracted the mean effects and standard deviations to calculate the sample size needed to determine a significant effect of PRO/AA supplementation during RET (Supplemental Table 1) in these meta-analyses. These effect sizes are very small, and the sample sizes needed to determine an effect of PRO/AA are very large. As suggested by others [31], this further cements the understanding that the vast majority of the benefits on strength and other outcomes come from the resistance exercise training modality itself, with very little contribution from the protein supplementation. The absence of effects and the low effect sizes could be attributable to the heterogeneity of individual responses to RE such as body type [35] and other factors [36–38].

10Selection of randomized control’s trials and their overlap in meta-analyses

Within the past decade, many new studies have contributed to the literature. We extracted all of the current randomized control trials used in these meta-analytic reviews to examine presence or absence of overlap for use. As the years progressed, one would assume that the same studies would be included year after year with the addition of newly published studies, but that was not the clear case. The Supplemental Connectivity Map and Supplemental Table 2 highlight a prominent reason for the discrepancy of results between meta-analyses in that each meta-analysis had a diverse selection of studies. We discovered many studies not included in any of these meta-analyses. A few RCTs were consistently included [39–43], but sparsely, as they were typically in less than 50% of the meta-analyses. Each particular RCT was utilized in a meta-analysis on average 2.7 times. 25 RCT’s were used once, 9 RCT’s were used twice, 11 RCT’s were used three times, 2 RCTs were used five times, 3 RCTs were used six times, and 4 RCTs were used seven times. 23 RCT’s were also cited by meta-analyses, but not used in quantitative analysis in some meta-analyses. In reality, only 7 studies [39–45] demonstrated a consistent pattern (used in about half the studies) for inclusion in meta-analyses and as such, they have a more consistent weight across the literature in influencing the results of these meta-analyses.

An online interactive connectivity map was also made to help visualize the connection of each RCT to each meta-analysis by outcome (fat-free mass, fat mass, muscle mass, strength, and physical function (Supplemental online material). Supplemental Table 3 also highlights that these meta-analyses also only cited less than 50% of previous meta-analyses, again indicating a lack of cohesion in the literature or divergence in topics not readily apparent from initial inspection of the article titles and abstracts. However, this may be a result of insufficient space for citations and or publishing lag.

We examined if study quality (Fig. 2 and Table 3) was a potential determining factor on study exclusion into these meta-analyses as it often should be. Typical RCT methodological quality metrics assess items like random allocation, concealed allocation, similarity at baseline, subject blinding, therapist blinding, assessor blinding, follow up for at least one key outcome, intention-to-treat analysis, between-group statistical comparisons, and point and variability measures for at least one key outcome. Each meta-analysis, except two [21, 27], reported a methodology quality metric and score for each individual RCT it used in its meta-analysis. Although most meta-analyses utilized the PEDro scale (0–10) to assess study quality, not all did. We converted those on a different scale to a 10-point scale for comparison purposes so that methodological quality approaches could be better assessed, to a degree, across and within meta-analyses (Table 3 and Fig. 2). As with the PEDro approach, methodological quality was considered high, ≥7 points; medium, 4–6 points; low, ≤3 points. Therefore, we report a summary of the RCT methodology quality scores provided by each meta-analysis.

Fig.2

Average quality score from the randomized controlled trials included in the meta-analyses. Data are mean with 95% confidence intervals.

We averaged the RCT study quality scores from each meta-analysis with lower and upper 95% confidence intervals (Fig. 2). These scores reflect the quality of the RCTs and/or the nature of the approach (conservative or not) taken by the respective authors of the meta-analyses when making these assessments. All but two studies scored a high (≥7 points) methodological quality in their collected RCTs. One was borderline medium/high at 7.69 (5.49–9.88 95% CI) [26] while another was noticeably composed of medium quality RCTs or was more conservative with its assessment at 5.42 (4.43–6.41 95% CI) [25]. One meta-analysis conducted subgroup analysis demonstrating that those RCTs with a PEDro score less than or greater than 7 tended to show different outcome responses [23] suggesting that study quality is a relevant variable.

All the 134 RCT’s used in these analyses resulted in an average quality score of 7.80 (7.54–8.06 95% CI) to be considered high quality. Studies that were used only once scored 6.72 (5.69–7.76 95% CI), which was slightly less than those utilized more than once in a meta-analysis at 7.84 (7.46–8.22 95% CI), but not significantly so. Those multi-use studies had a variation coefficient of 15.3% (12.4–18.2 95% CI) when comparing scores across meta-analyses. This suggests that although methodological quality may have been used as a criterion for exclusion from some meta analyses, it was a minor one, and there are likely other more prominent reasons for the infrequent use of many of these RCTs across these meta analyses.

11Inclusion and exclusion criteria

Differences between these meta-analyses’ RCT selections are likely due to the inclusion and exclusion criteria for included RCTs (Table 2 and Supplemental Table 4). Age was one criterion with selection cut points of >40 to >65 years of age, with the majority of meta-analyses picking 50–60y as the cutpoint, but as low as 40y in some cases. Length of resistance training was also a selection criterion, with cutoff points of 4+ to 12+ weeks. Weekly frequency of RET sessions was normally limited to RCT’s with two or more sessions per week, with one study allowing a minimum of 1 session per week [21].

11.1Differences in population

The selection of RCTs and their inherent participant populations found in the selected RCT’s is a likely strong contributor to the divergent conclusions in the literature. When examining the meta-analyses that included an enrichment of greater than 25% frail and sarcopenic older adults, seven of eight meta-analyses demonstrated a positive effect on at least one outcome with protein supplementation during resistance training (Table 4). Indeed, as the enrichment of frail and sarcopenic adults increases (moving from left to right in Table 4), a trend for more significant effects are found in these meta-analyses, specifically for hospitalized or institutionalized older adults [23, 25]. The increasing number or reports that RET + AA/Pro supplementation actually have a greater impact advanced age/frailty presents an interesting juxtaposition between with the concept that anabolic resistance increases with age. We know the concept of anabolic resistance is more complex than just increasing anabolic resistance with every year of aging [46]. The frail older adult has the greatest need as they are likely the most nutrient/protein deficient and physically inactive. Although speculative it is common knowledge that those who benefit most with any nutritional supplementation are those who are deficient in that nutrient and those who have the least physical activity reap the most rapid health benefits by engaging in physical exercise. So, within the aging population, they may have the most to gain when they start RET. Indeed, meta-analyses with data pooled from younger and older adults has shown an attenuation of the effect of protein supplementation with age [28, 31] To examine this age and anabolic resistance relationship, within the older adult age group further a large collection of RCTs with a heterogenous population of older adults across age with varied health conditions would be needed for a meta-regression. Unfortunately, most meta-analyses that did look at age as a continuous covariable had a homogenous population of older adults [31] and those that did have a varied population of older adults did not conduct a meta-regression age as a continuous covariable.

Table 4

Outcomes effective for lean mass, muscle strength, and physical function and percent of each participant category in each meta-analysis

Conversely, meta-analyses with a greater enrichment of overweight and obese participants appear to demonstrate no effect [19, 24, 28, 31]. This would be reflective of anabolic resistance with excess weight [47], which can be common to older adults. However, Liao et al. 2019 presented conflicting findings with its subgroup analysis of older adults greater than or less than a BMI of 30. They reported an equivalent lean mass gain, body mass and body fat loss, and lower body strength and no changes in upper body strength [22]. These minor improvements in obese participants in Liao et al. 2017 may be more reflective of the presence of a cocktail of other nutrients and anabolic agents (creatine) included in the supplementation other than protein and or inclusion of an energy restriction trials [48]. As recently suggested by O’Bryan et al., in 2020, a protein-containing multi-nutrient intervention with RET may be slightly more effective (but not statistically so) than just protein alone with RET in older adults [30]. Regardless, when examining the pattern across these meta-analyses it becomes apparent that the effect of protein supplementation to enhance the adaptations to RET are attenuated in overweight and obese older adults who are less likely to be deficient in protein and more physically inactive.

Most meta-analyses had an equal proportion of men and women with about 48–60% male (Table 5). Although one meta-analysis was 76% male participants [20], another was 34% male participants [27] they both demonstrated positive effects on their chosen outcomes. This is reflective of other meta-analysis subgroup examinations showing minimal sex-differences [22, 23, 29], with the single exception of lean mass in one early study [22]. Thus, there appears to be a similar response (or lack thereof) in both males and females.

11.2Differences by length of intervention

Longer RCT RET duration may [49–51] or may not [52] impact strength and muscle mass gain [50]. Muscle cross sectional area increases of ∼15% seem to plateau at about 3 months of training in the general population [53], but specific long term >3 months’ time course of muscle hypertrophy in older adults specifically is unclear. Therefore, we looked to see if length of intervention had any patterns with positive outcomes on whether or not a meta-analysis was effective in increasing fat-free mass, muscle strength, and/or function. The intervention lengths of studies within the meta-analyses lasted anywhere from 3 to 104 weeks with most lasting from 12 to 72 weeks (Fig. 3A). There was no clear pattern, from examination at the level of these meta-analyses, to suggest that length of intervention may impact effectiveness of resistance training and protein supplementation for older adults. Because the majority of studies are ∼12 to 16 weeks in length, there is little spread in this data, making it difficult to assess the relationship of study duration on these outcomes as shown in previous meta-regressions [28]. As longer RCTs (>20 weeks) are included future meta-regression may be able to provide more insight in this regard.

Fig.3

Volcano plot of intervention length (A) and daily protein dose (B) in meta-analyses examining the effects of protein supplementation and resistance exercise training compared to resistance exercise training with or without placebo in older adults for the outcomes of tissue composition, strength and physical function. Data are individual RCTs included in each meta-analysis. The suggested optimal dose of protein is highlighted as a dotted line on the x-axis in panel B.

Previous studies have conducted subgroup analyses to determine if length of the RET intervention may optimize the effect of protein supplementation. One study found no difference between RCTs < or >12 weeks in duration with a direct statistical assessment [29]. One study [22] defined short a <12 weeks, medium as 12–24 weeks and long as >24 weeks and suggested greater enhancement of LM and physical function with medium and long interventions vs short interventions. The issue is that they defined sub-groups to examine the effect of protein supplementation and demonstrate statistical effects within, but not between short, medium or long sub-groups although their conclusions would suggest otherwise. Further meta-analyses are encouraged to design hypotheses with appropriate analyses to test for the ideal training duration to evaluate a protein and exercise interaction.

12Differences in analytical approach

Other distinctions between meta-analyses are much less apparent and “hidden” in the methodological approaches. These factors are only apparent to the statistician and/or those who regularly conduct meta-analytic research, thus a small proportion of the population. Yet, these factors have a tremendous impact on the outcomes and results so they should be better appreciated by those in the field.

13Summary and conclusion

Several reports have demonstrated that when contraction and sufficient protein are acutely combined, the age-related anabolic resistance diminishes. Thus, it would seem intuitive that supplementing protein during RET would be a more effective strategy to enhance muscle size, strength, and physical function. Several meta-analyses sought to answer this question and although they shared remarkably similar titles, they had pronounced differences in 1) results, 2) type of protein-focused nutritional intervention, 3) data extraction approach, and 4) RCT study selection/participants used. However, the compiled evidence from these meta-analyses clearly indicates that the phenotypic response to RET and protein-focused nutrition is very similar to that of resistance training alone, suggesting that chronic application diminishes this beneficial effect of combined resistance exercise and protein-focused nutrition. The lack of an effect is most apparent and difficult to discern with muscle strength, muscle mass, fat mass and physical function, but somewhat more common, although still minimal with fat-free mass. When considering the other factors in these meta-analyses such as: participant population, quality score, sample size, differences in protein intake with supplementation or between supplement groups, diet quality, protein dosing, or distribution of protein at each meal, the current findings are no surprise. The lack of an effect is clearly noticeable in analyses containing enrichment of overweight and obese participants. However, in sarcopenic and frail older adults (or those on a poor diet), optimizing the total amount, and quality protein throughout the day may be useful in enhancing muscle growth and function in response to RET. Further, RCTs need to be conducted to fill the gaps in the literature and to provide complete data sets in the correct format for meta-analyses such that the field is able to progress.

Authors’ contributions

P.T.R. formulated the review topic; P.T.R., A.K.D., J.M.M., A.M.B., C.N.K. and C.E.P conducted the literature review, data extraction, and formatting; P.T.R., A.K.D., J.M.M., A.M.B., and C.N.K. reviewed the manuscript; P.T.R., A.K.D. and J.M.M. wrote the manuscript and had primary responsibility for the final content. All authors read and approved the final manuscript.