Effects of High-Volume Versus High-Load Resistance Training on Skeletal Muscle Growth and Molecular Adaptations

The effect of the ketogenic diet on resistance training load management: a repeated-measures clinical trial in trained participants

BACKGROUND

The effect of low-carbohydrate high-fat dietary manipulation, such as the ketogenic diet (KD), on muscle strength assessment in resistance-training (RT) participants has focused on the one-repetition maximum test (1-RM). However, a pre-specified 1-RM value during an exercise training program disregards several confounding factors (i.e. sleep, diet, and training-induced fatigue) that affect the exerciser's "true" load and daily preparedness. We aimed to evaluate the effect of a 6-week RT program on load control-related variables in trained subjects following a KD intervention.

METHODS

Fourteen resistance-trained individuals (3F, 11 M; 30.1 [6.2] years; 174.2 [7.6] cm; 75.7 [10.8] kg; BMI 24.8 [2.1] kg·m-2) completed this single-arm repeated-measures clinical trial. Load management variables included volume load, number of repetitions, perceived exertion (RPE), movement velocity loss, and exertion index. These primary outcomes were assessed weekly before, during, and at the end of a 6-week RT program that included traditional RT exercises (bench press, femoral lying down, lat pulldown, leg extension, and back squat).

RESULTS

There was a significant difference in RPE between weeks (p = 0.015, W = 0.19) with a slight trend in decreasing RPE. We found differences in the volume load per week (p < 0.001; W = 0.73 and p < 0.001, W = 0.81, respectively), with an increase in the last weeks. In the control of the load based on movement velocity, we did not find significant differences between weeks (p = 0.591, W = 0.06), although significant differences were found in the effort index (p = 0.026, W = 0.17).

CONCLUSIONS

A KD diet in recreational strength participants does not appear to lead to performance losses during a RT program aimed at improving body composition. However, the lack of adherence and familiarity with the ketogenic diet must be considered specially during first weeks.

Peripheral quantitative computed tomography is a valid imaging technique for tracking changes in skeletal muscle cross-sectional area

Peripheral quantitative computed tomography (pQCT) has recently expanded to quantifying skeletal muscle, however its validity to determine muscle cross-sectional area (mCSA) compared to magnetic resonance imaging (MRI) is unknown. Eleven male participants (age: 22 ± 3 y) underwent pQCT and MRI dual-leg mid-thigh imaging before (PRE) and after (POST) 6 weeks of resistance training for quantification of mid-thigh mCSA and change in mCSA. mCSA agreement at both time points and absolute change in mCSA across time was assessed using Bland-Altman plots for mean bias and 95% limits of agreement (LOA), as well as Lin's concordance correlation coefficients (CCC). Both pQCT and MRI mCSA increased following 6 weeks of resistance training (∆mCSApQCT: 6.7 ± 5.4 cm2, p < 0.001; ∆mCSAMRI: 6.0 ± 6.4 cm2, p < 0.001). Importantly, the change in mCSA was not different between methods (p = 0.39). Bland-Altman analysis revealed a small mean bias (1.10 cm2, LOA: -6.09, 8.29 cm2) where pQCT tended to overestimate mCSA relative to MRI when comparing images at a single time point. Concordance between pQCT and MRI mCSA at PRE and POST was excellent yielding a CCC of 0.982. For detecting changes in mCSA, Bland-Altman analysis revealed excellent agreement between pQCT and MRI (mean bias: -0.73 cm2, LOA: -8.37, 6.91 cm2). Finally, there was excellent concordance between pQCT and MRI mCSA change scores (CCC = 0.779). Relative to MRI, pQCT imaging is a valid technique for measuring both mid-thigh mCSA at a single time point and mCSA changes following a resistance training intervention.

Effects of low-load resistance training with blood flow restriction on muscle fiber myofibrillar and extracellular area

Blood flow restriction applied during low-load resistance training (LL-BFR) induces a similar increase in the cross-sectional area of muscle fibers (fCSA) compared to traditional high-load resistance training (HL-RT). However, it is unclear whether LL-BFR leads to differential changes in myofibrillar spacing in muscle fibers and/or extracellular area compared to HL-RT. Therefore, this study aimed to investigate whether the hypertrophy of type I and II fibers induced by LL-BFR or HL-RT is accompanied by differential changes in myofibrillar and non-myofibrillar areas. In addition, we examined if extracellular spacing was differentially affected between these two training protocols. Twenty recreationally active participants were assigned to LL-BFR or HL-RT groups and underwent a 6-week training program. Muscle biopsies were taken before and after the training period. The fCSA of type I and II fibers, the area occupied by myofibrillar and non-myofibrillar components, and extracellular spacing were analyzed using immunohistochemistry techniques. Despite the significant increase in type II and mean (type I + II) fCSA (p < 0.05), there were no significant changes in the proportionality of the myofibrillar and non-myofibrillar areas [∼86% and ∼14%, respectively (p > 0.05)], indicating that initial adaptations to LL-BFR are primarily characterized by conventional hypertrophy rather than disproportionate non-myofibrillar expansion. Additionally, extracellular spacing was not significantly altered between protocols. In summary, our study reveals that LL-BFR, like HL-RT, induces skeletal muscle hypertrophy with proportional changes in the areas occupied by myofibrillar, non-myofibrillar, and extracellular components.

Proteolytic markers associated with a gain and loss of leg muscle mass with resistance training followed by high-intensity interval training

We recently reported that vastus lateralis (VL) cross-sectional area (CSA) increases after 7 weeks of resistance training (RT, 2 days/week), with declines occurring following 7 weeks of subsequent treadmill high-intensity interval training (HIIT) (3 days/week). Herein, we examined the effects of this training paradigm on skeletal muscle proteolytic markers. VL biopsies were obtained from 11 untrained college-aged males at baseline (PRE), after 7 weeks of RT (MID), and after 7 weeks of HIIT (POST). Tissues were analysed for proteolysis markers, and in vitro experiments were performed to provide additional insights. Atrogene mRNAs (TRIM63, FBXO32, FOXO3A) were upregulated at POST versus both PRE and MID (P < 0.05). 20S proteasome core protein abundance increased at POST versus PRE (P = 0.031) and MID (P = 0.049). 20S proteasome activity, and protein levels for calpain-2 and Beclin-1 increased at MID and POST versus PRE (P < 0.05). Ubiquitinated proteins showed model significance (P = 0.019) with non-significant increases at MID and POST (P > 0.05). in vitro experiments recapitulated the training phenotype when stimulated with a hypertrophic stimulus (insulin-like growth factor 1; IGF1) followed by a subsequent AMP-activated protein kinase activator (5-aminoimidazole-4-carboxamide ribonucleotide; AICAR), as demonstrated by larger myotube diameter in IGF1-treated cells versus IGF1 followed by AICAR treatments (I+A; P = 0.017). Muscle protein synthesis (MPS) levels were also greater in IGF1-treated versus I+A myotubes (P < 0.001). In summary, the loss in RT-induced VL CSA with HIIT coincided with increases in several proteolytic markers, and sustained proteolysis may have driven this response. Moreover, while not measured in humans, we interpret our in vitro data to suggest that (unlike RT) HIIT does not stimulate MPS. NEW FINDINGS: What is the central question of this study? Determining if HIIT-induced reductions in muscle hypertrophy following a period of resistance training coincided with increases in proteolytic markers. What is the main finding and its importance? Several proteolytic markers were elevated during the HIIT training period implying that increases in muscle proteolysis may have played a role in HIIT-induced reductions in muscle hypertrophy.

Resistance training in humans and mechanical overload in rodents do not elevate muscle protein lactylation

Although several reports have hypothesized that exercise may increase skeletal muscle protein lactylation, empirical evidence in humans is lacking. Thus, we adopted a multi-faceted approach to examine if acute and subchronic resistance training (RT) altered skeletal muscle protein lactylation levels. In mice, we also sought to examine if surgical ablation-induced plantaris hypertrophy coincided with increases in muscle protein lactylation. To examine acute responses, participants' blood lactate concentrations were assessed before, during, and after eight sets of an exhaustive lower body RT bout (n = 10 trained college-aged men). Vastus lateralis biopsies were also taken before, 3-h post, and 6-h post-exercise to assess muscle protein lactylation. To identify training responses, another cohort of trained college-aged men (n = 14) partook in 6 weeks of lower-body RT (3x/week) and biopsies were obtained before and following the intervention. Five-month-old C57BL/6 mice were subjected to 10 days of plantaris overload (OV, n = 8) or served as age-matched sham surgery controls (Sham, n = 8). Although acute resistance training significantly increased blood lactate responses ∼7.2-fold (p < 0.001), cytoplasmic and nuclear protein lactylation levels were not significantly altered at the post-exercise time points, and no putative lactylation-dependent mRNA was altered following exercise. Six weeks of RT did not alter cytoplasmic protein lactylation (p = 0.800) despite significantly increasing VL muscle size (+3.5%, p = 0.037), and again, no putative lactylation-dependent mRNA was significantly affected by training. Plantaris muscles were larger in OV versus Sham mice (+43.7%, p < 0.001). However, cytoplasmic protein lactylation was similar between groups (p = 0.369), and nuclear protein lactylation was significantly lower in OV versus Sham mice (p < 0.001). The current null findings, along with other recent null findings in the literature, challenge the thesis that lactate has an appreciable role in promoting skeletal muscle hypertrophy.

Different Resistance Exercise Loading Paradigms Similarly Affect Skeletal Muscle Gene Expression Patterns of Myostatin-Related Targets and mTORC1 Signaling Markers

Although transcriptome profiling has been used in several resistance training studies, the associated analytical approaches seldom provide in-depth information on individual genes linked to skeletal muscle hypertrophy. Therefore, a secondary analysis was performed herein on a muscle transcriptomic dataset we previously published involving trained college-aged men (n = 11) performing two resistance exercise bouts in a randomized and crossover fashion. The lower-load bout (30 Fail) consisted of 8 sets of lower body exercises to volitional fatigue using 30% one-repetition maximum (1 RM) loads, whereas the higher-load bout (80 Fail) consisted of the same exercises using 80% 1 RM loads. Vastus lateralis muscle biopsies were collected prior to (PRE), 3 h, and 6 h after each exercise bout, and 58 genes associated with skeletal muscle hypertrophy were manually interrogated from our prior microarray data. Select targets were further interrogated for associated protein expression and phosphorylation induced-signaling events. Although none of the 58 gene targets demonstrated significant bout x time interactions, ~57% (32 genes) showed a significant main effect of time from PRE to 3 h (15↑ and 17↓, p < 0.01), and ~26% (17 genes) showed a significant main effect of time from PRE to 6 h (8↑ and 9↓, p < 0.01). Notably, genes associated with the myostatin (9 genes) and mammalian target of rapamycin complex 1 (mTORC1) (9 genes) signaling pathways were most represented. Compared to mTORC1 signaling mRNAs, more MSTN signaling-related mRNAs (7 of 9) were altered post-exercise, regardless of the bout, and RHEB was the only mTORC1-associated mRNA that was upregulated following exercise. Phosphorylated (phospho-) p70S6K (Thr389) (p = 0.001; PRE to 3 h) and follistatin protein levels (p = 0.021; PRE to 6 h) increased post-exercise, regardless of the bout, whereas phospho-AKT (Thr389), phospho-mTOR (Ser2448), and myostatin protein levels remained unaltered. These data continue to suggest that performing resistance exercise to volitional fatigue, regardless of load selection, elicits similar transient mRNA and signaling responses in skeletal muscle. Moreover, these data provide further evidence that the transcriptional regulation of myostatin signaling is an involved mechanism in response to resistance exercise.

Molecular predictors of resistance training outcomes in young untrained female adults

We sought to determine if the myofibrillar protein synthetic (MyoPS) response to a naïve resistance exercise (RE) bout, or chronic changes in satellite cell number and muscle ribosome content, were associated with hypertrophic outcomes in females or differed in those who classified as higher (HR) or lower (LR) responders to resistance training (RT). Thirty-four untrained college-aged females (23.4 ± 3.4 kg/m2) completed a 10-wk RT protocol (twice weekly). Body composition and leg imaging assessments, a right leg vastus lateralis biopsy, and strength testing occurred before and following the intervention. A composite score, which included changes in whole body lean/soft tissue mass (LSTM), vastus lateralis (VL) muscle cross-sectional area (mCSA), midthigh mCSA, and deadlift strength, was used to delineate upper and lower HR (n = 8) and LR (n = 8) quartiles. In all participants, training significantly (P < 0.05) increased LSTM, VL mCSA, midthigh mCSA, deadlift strength, mean muscle fiber cross-sectional area, satellite cell abundance, and myonuclear number. Increases in LSTM (P < 0.001), VL mCSA (P < 0.001), midthigh mCSA (P < 0.001), and deadlift strength (P = 0.001) were greater in HR vs. LR. The first-bout 24-hour MyoPS response was similar between HR and LR (P = 0.367). While no significant responder × time interaction existed for muscle total RNA concentrations (i.e., ribosome content) (P = 0.888), satellite cell abundance increased in HR (P = 0.026) but not LR (P = 0.628). Pretraining LSTM (P = 0.010), VL mCSA (P = 0.028), and midthigh mCSA (P < 0.001) were also greater in HR vs. LR. Female participants with an enhanced satellite cell response to RT, and more muscle mass before RT, exhibited favorable resistance training adaptations.NEW & NOTEWORTHY This study continues to delineate muscle biology differences between lower and higher responders to resistance training and is unique in that a female population was interrogated. As has been reported in prior studies, increases in satellite cell numbers are related to positive responses to resistance training. Satellite cell responsivity, rather than changes in muscle ribosome content per milligrams of tissue, may be a more important factor in delineating resistance-training responses in women.

Skeletal Muscle DNA Methylation and mRNA Responses to a Bout of Higher versus Lower Load Resistance Exercise in Previously Trained Men

We sought to determine the skeletal muscle genome-wide DNA methylation and mRNA responses to one bout of lower load (LL) versus higher load (HL) resistance exercise. Trained college-aged males (n = 11, 23 ± 4 years old, 4 ± 3 years self-reported training) performed LL or HL bouts to failure separated by one week. The HL bout (i.e., 80 Fail) consisted of four sets of back squats and four sets of leg extensions to failure using 80% of participants estimated one-repetition maximum (i.e., est. 1-RM). The LL bout (i.e., 30 Fail) implemented the same paradigm with 30% of est. 1-RM. Vastus lateralis muscle biopsies were collected before, 3 h, and 6 h after each bout. Muscle DNA and RNA were batch-isolated and analyzed using the 850k Illumina MethylationEPIC array and Clariom S mRNA microarray, respectively. Performed repetitions were significantly greater during the 30 Fail versus 80 Fail (p < 0.001), although total training volume (sets × reps × load) was not significantly different between bouts (p = 0.571). Regardless of bout, more CpG site methylation changes were observed at 3 h versus 6 h post exercise (239,951 versus 12,419, respectively; p < 0.01), and nuclear global ten-eleven translocation (TET) activity, but not global DNA methyltransferase activity, increased 3 h and 6 h following exercise regardless of bout. The percentage of genes significantly altered at the mRNA level that demonstrated opposite DNA methylation patterns was greater 3 h versus 6 h following exercise (~75% versus ~15%, respectively). Moreover, high percentages of genes that were up- or downregulated 6 h following exercise also demonstrated significantly inversed DNA methylation patterns across one or more CpG sites 3 h following exercise (65% and 82%, respectively). While 30 Fail decreased DNA methylation across various promoter regions versus 80 Fail, transcriptome-wide mRNA and bioinformatics indicated that gene expression signatures were largely similar between bouts. Bioinformatics overlay of DNA methylation and mRNA expression data indicated that genes related to "Focal adhesion," "MAPK signaling," and "PI3K-Akt signaling" were significantly affected at the 3 h and 6 h time points, and again this was regardless of bout. In conclusion, extensive molecular profiling suggests that post-exercise alterations in the skeletal muscle DNA methylome and mRNA transcriptome elicited by LL and HL training bouts to failure are largely similar, and this could be related to equal volumes performed between bouts.