Natural exercise ability is linked to muscle body clock genes and growth signals in older rats with low and high running endurance

Female low- and high-capacity runner rats (LCR and HCR) from the 44th generation were used in the present study. All animals were 23–24 months of age at the time of experimentation. A total of 19 rats were included (HCR, n = 10; LCR, n = 9). Rats were housed under controlled environmental conditions (12:12-h light–dark cycle, temperature 22 ± 2 °C, relative humidity approximately 55 ± 10%) with ad libitum access to standard laboratory chow and water. All experimental procedures were conducted in accordance with the European Directive 2010/63/EU for animal experiments and were approved by the National Animal Research Ethical Committee of Hungary (approval no. PE/EA/62-2/2021).

Maximal oxygen uptake (VO₂max) was assessed using a motor-driven treadmill system in a closed metabolic chamber customized for rats (Columbus Instruments, USA), following the same methodology as in previous studies of the LCR/HCR model. Briefly, all rats were acclimated to treadmill running prior to VO₂max measurements. Animals rested on the running belt for 5 min, after which running speed was gently increased. Acclimatization runs were performed for 5–10 min at speeds ranging from 5 to 25 m/min on two consecutive days. For VO₂max testing, rats began running at 5 m/min following a 5-min rest period, and treadmill speed was increased by 5 m/min every 2 min until exhaustion. VO₂max was determined for each animal when at least one of the following criteria was met:

VO₂max values were recorded when any of the predefined exhaustion criteria were reached. All VO₂max measurements were conducted during the light phase under controlled environmental conditions (22 ± 2 °C, relative humidity approximately 55 ± 10%). Measurements were performed between approximately ZT1 and ZT7 for both HCR and LCR rats. Although testing was conducted across a relatively broad time window, measurement timing and experimental conditions were coordinated between groups to minimize potential circadian-related variability.

Skeletal muscle tissues (plantaris and soleus) were collected at least 48 hours after completion of the VO₂max measurements under deep anesthesia, rapidly excised, cleared of visible connective tissue, snap-frozen in liquid nitrogen, and stored at −80 °C until analysis. All dissections were performed during the light phase, with Zeitgeber time defined relative to lights on (ZT0), corresponding approximately to ZT2–ZT3; sampling times showed substantial overlap between HCR and LCR rats and were restricted to a narrow time window to limit potential circadian influences on clock gene expression.

Total RNA was extracted from plantaris and soleus muscles using the RNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Reverse transcription was performed using the Maxima First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, Waltham, MA, USA), using standardized amounts of total RNA (0.5–1 μg) for each sample to minimize variability in cDNA synthesis efficiency. Quantitative real-time PCR (qRT-PCR) was performed using the LightCycler 480 SYBR Green I Master mix (Roche, Basel, Switzerland). Each reaction was carried out in a total volume of 20 μL containing 10 μL of 2× SYBR Green master mix, 1 μL of cDNA template, gene-specific primers (final concentration 0.3 μM each), and nuclease-free water. Amplification was performed using the QuantStudio 3/5 Real-Time PCR System (Thermo Fisher Scientific). All samples were analyzed in technical triplicates. Melting curve analysis was performed to confirm amplification specificity. Mean Ct values were used for subsequent analysis. Relative gene expression levels were calculated using the 2^−ΔΔCt method, with ribosomal protein L13 (RPL13) serving as the housekeeping gene. Expression levels were normalized to RPL13 and expressed relative to the HCR group.

Protein extraction and immunoblotting were performed as described previously (Zhou et al., 2025). Briefly, skeletal muscle samples were homogenized in ice-cold lysis buffer supplemented with protease and phosphatase inhibitors. Protein concentrations were determined using the BCA assay. Equal amounts of protein were separated by SDS–PAGE and transferred onto PVDF membranes. Membranes were incubated with the following primary antibodies: total STAT5A/B Proteinteich, Cat. No. 12071-1-AP]), phospho-STAT5A/B (Tyr694/699; AbboMax : 500-9334]), total JAK2 (Cell Signaling Technology: (D2E12) #3230), phospho-JAK2 (Tyr1007/Tyr1008): bs-2485R]), and PPARδ ([Proteintech: Cat No. 60193-1-Ig]).

For phosphorylated proteins, membranes were first probed with antibodies against the phosphorylated form, then stripped and reprobed for the corresponding total protein. Band intensities were quantified by densitometry using ImageJ. Total protein loading was assessed by Coomassie Brilliant Blue (CBB) staining of the PVDF membrane. Phosphorylated STAT5A/B and phosphorylated JAK2 signals were normalized to their corresponding total protein levels (STAT5A/B and JAK2, respectively) for calculation of phosphorylation ratios. Total protein loading and transfer efficiency were additionally verified by Coomassie Brilliant Blue (CBB) staining of PVDF membranes. Representative immunoblots and quantitative analyses are shown in Figure 1.

All data are presented as mean ± standard deviation (SD), with individual data points shown where appropriate. Normality of data distribution was assessed using the Shapiro–Wilk test. As all variables met the assumption of normality, comparisons between high-capacity runner (HCR) and low-capacity runner (LCR) rats were performed using unpaired two-tailed Student’s t-tests. Associations between intrinsic aerobic capacity (VO₂max) and skeletal muscle molecular markers (Igf1, Igf1Ec, Cry1, and Bmal1) were evaluated separately for plantaris and soleus muscles using Pearson correlation coefficients. Correlation results are presented as heat maps depicting correlation coefficients and corresponding significance levels. All statistical analyses were conducted using IBM SPSS Statistics for Mac (version 28.0; IBM Corp., Armonk, NY, USA). A two-tailed P value < 0.05 was considered statistically significant.

Body weight was significantly higher in LCR rats than in HCR rats (p = 0.041; Supplementary Figure 1). Intrinsic aerobic exercise capacity, assessed by maximal oxygen consumption (VO₂max), was significantly higher in HCR rats than in LCR rats (Figures 2A, B). This difference was evident when VO₂max was expressed both as an absolute value (ml/min, p = 0.002; Figure 2A) and when normalized to body mass (ml/g/min, p = 0.008; Figure 2B), confirming a robust separation of intrinsic aerobic capacity between the two phenotypes.

Quantitative PCR analyses revealed distinct skeletal muscle gene expression patterns between HCR and LCR rats in both the plantaris and soleus muscles (Figure 3). Among clock genes, Cry1 mRNA expression was significantly higher in LCR rats than in HCR rats in the plantaris muscle (p = 0.027; Figure 3A), with a similar tendency observed in the soleus muscle (p = 0.073; Figure 3A). Bmal1 expression was significantly elevated in LCR rats in both the plantaris (p = 0.021) and soleus muscles (p = 0.030; Figure 3C), whereas Cry2 expression did not differ significantly between phenotypes in either muscle (Figure 3B). Expression of the muscle atrophy–related genes MuRF-1 and Atrogin-1 did not differ significantly between phenotypes (Figures 3D, E). Genes related to metabolic regulation showed muscle-specific responses. Pdk4 expression did not differ significantly between HCR and LCR rats (Figure 3F), while Ucp3 expression exhibited a trend toward lower expression in the soleus muscle of LCR rats (p = 0.075; Figure 3G). In contrast, components of the IGF-1 pathway were consistently altered. Igf1 mRNA expression was significantly higher in LCR rats in both the plantaris (p = 0.017) and soleus muscles (p = 0.005; Figure 3H), with a more pronounced difference in the soleus muscle. Similarly, Igf1Ec expression was significantly higher in LCR rats than in HCR rats in both muscles (plantaris: p = 0.011; soleus: p = 0.016; Figure 3I).

Western blot analyses demonstrated phenotype-dependent differences in IGF-1–related signaling pathways in skeletal muscle (Figure 1). Phosphorylated STAT5A/B levels, total STAT5A/B protein abundance, and the ratio of phosphorylated to total STAT5A/B did not differ significantly between HCR and LCR rats in either muscle (Figures 1A, B, F). In contrast, total JAK2 protein abundance was higher in the soleus muscle of LCR rats than in HCR rats (Figure 1G, p = 0.014). Nevertheless, the ratio of phosphorylated JAK2 to total JAK2 was significantly lower in LCR rats compared with HCR rats in both plantaris (p = 004; Figure 1D) and soleus muscles (p = 0.014; Figure 1D), indicating altered JAK2-related signaling balance. Total PPARδ protein expression did not differ significantly between phenotypes in either muscle (Figure 1E).

Correlation analyses revealed significant associations between intrinsic aerobic capacity and skeletal muscle molecular markers (Figure 4). In the plantaris muscle, VO₂max was negatively correlated with Igf1, Igf1Ec, Cry1, and Bmal1 expression, whereas Igf1 and Igf1Ec were strongly positively correlated with Bmal1 expression. Cry1 expression also showed moderate positive correlations with IGF-1–related markers (Figure 4A). In the soleus muscle, VO₂max exhibited stronger negative correlations with Igf1 and Igf1Ec expression, while positive correlations were observed between Igf1/Igf1Ec and Bmal1 expression. Associations between Cry1 and IGF-1–related markers were weaker in the soleus compared with the plantaris muscle (Figure 4B).

One important finding of the present study is that skeletal muscle clock gene signaling was associated with intrinsic exercise capacity, independent of exercise training. Circadian clock genes are known for regulating circadian rhythms, but they have also been shown to play a fundamental role in determining baseline metabolic and functional capacity (Dyar et al., 2014). In skeletal muscle, clock components such as Cry1/2 and Bmal1 influence mitochondrial function, substrate utilization, and oxidative metabolism, processes that are closely linked to endurance performance (Andrews et al., 2010). In the present study, we observed differences in clock gene-related signaling between low- and high-running capacity phenotypes, indicating that intrinsic aerobic capacity is linked to the circadian clock-regulating network in skeletal muscle. Given that cryptochromes have been reported to repress PPARδ-related metabolic activity and downstream signaling pathways (Jordan et al., 2017), altered Cry1/2 expression may be associated with modified metabolic regulation rather than altered total PPARδ protein abundance. This interpretation is consistent with prior studies demonstrating that suppression of PPARδ signaling can limit oxidative capacity and endurance performance (Wang et al., 2004; Narkar et al., 2008). These findings broaden our understanding of clock gene function, suggesting that circadian rhythmic control mechanisms contribute to a molecular framework related to intrinsic exercise capacity and metabolic control. However, the present data are correlative, and more research is needed to understand how circadian rhythmic signaling interacts with the genetic background to influence aerobic capacity and metabolic health.

This study demonstrated an association between intrinsic exercise capacity and skeletal muscle IGF-1-related signaling. The IGF-1 system plays important roles in growth, metabolism, and tissue maintenance (Rommel et al., 2001; Glass, 2005). However, precise regulation of this system is required, as both insufficient and excessive signaling can be harmful (Richardson et al., 2004; Junnila et al., 2013). In skeletal muscle, IGF-1 influences protein synthesis, regeneration, and metabolic function, establishing it as a central pathway linking physical performance to long-term health outcomes (Barclay et al., 2019). The present findings suggest that low and high intrinsic exercise capacity are accompanied by distinct patterns of IGF-1–JAK2–STAT5B signaling in skeletal muscle (Chaudhari et al., 2017), potentially contributing to divergent aging trajectories. Dysregulation of this pathway has been associated with insulin resistance, sarcopenia, and metabolic diseases, while proper regulation has been linked to the maintenance of muscle function and an extended lifespan (Friedrich et al., 2012; Junnila et al., 2013; Ascenzi et al., 2019; Barclay et al., 2019). Therefore, altered IGF-1-related signaling in low exercise capacity phenotypes may be a molecular pathway through which reduced exercise capacity leads to increased disease risk. Emerging evidence suggests that clock genes interact with the IGF-1 signaling pathway (Chaudhari et al., 2017; Jordan et al., 2017), which indicates the existence of a coordinated regulatory network rather than independent mechanisms. Thus, these findings suggest potential associations between selected clock gene transcript expression and IGF-1–related signaling markers in skeletal muscle that may be relevant to intrinsic exercise capacity and aging-related phenotypes.

Interestingly, expression of the muscle atrophy–related genes MuRF-1 and Atrogin-1 did not differ significantly between HCR and LCR rats despite substantial differences in intrinsic aerobic capacity. This observation may suggest that reduced exercise capacity in aged LCR rats is not primarily driven by overt activation of canonical muscle atrophy pathways. Instead, the observed phenotype differences may be more closely associated with alterations in metabolic regulation, anabolic signaling balance, or skeletal muscle functional quality rather than increased expression of ubiquitin–proteasome–related atrophy markers. These findings are consistent with the concept that aging-related declines in muscle function and aerobic performance can occur independently of pronounced activation of classical atrophy signaling pathways (Joseph et al., 2012; Cruz-Jentoft et al., 2019).

The identification of clock gene and IGF-1–related pathways as molecular correlates of intrinsic exercise capacity may have implications for exercise physiology and aging research. Skeletal muscle represents a physiologically relevant tissue in which genetic background, circadian regulation, and metabolic signaling converge (Pedersen and Febbraio, 2008; Hawley et al., 2014). A better understanding of these molecular features may contribute to refining strategies aimed at optimizing exercise interventions across different levels of aerobic capacity. In addition, the present findings raise the possibility that circadian and growth-related pathways participate in the regulatory landscape associated with intrinsic exercise capacity. Although the current study does not establish therapeutic targets, these pathways may warrant further investigation in the context of aging and metabolic health. Such exploration could be particularly relevant for populations with reduced exercise tolerance, including older individuals or those with metabolic disorders.

Several limitations should be acknowledged. First, the cross-sectional nature of the present study precludes causal inference regarding the relationships among skeletal muscle clock gene expression, IGF-1–related signaling, and intrinsic exercise capacity. In addition, the present study focused specifically on skeletal muscle, despite the well-established contributions of other metabolically active tissues, including liver, adipose tissue, and central regulatory systems, to systemic exercise capacity and metabolic regulation. Therefore, the present findings should be interpreted as skeletal muscle–associated molecular signatures rather than evidence of integrated systemic regulation. Second, the present study focused primarily on molecular markers and did not directly assess functional outcomes such as mitochondrial respiration, muscle contractile performance, or broader endocrine and metabolic responses. In addition, downstream anabolic signaling pathways, including PI3K-AKT-mTOR signaling, as well as skeletal muscle–derived secretory factors and myokines, were not evaluated. These analyses may provide additional mechanistic insight into the relationship between intrinsic exercise capacity, skeletal muscle signaling, and systemic metabolic regulation. Third, clock gene expression was assessed at a single circadian time point (ZT2–ZT3), which limits interpretation regarding circadian rhythmicity, phase shifts, or amplitude-dependent regulation. Therefore, the observed differences in Cry1 and Bmal1 transcript expression may reflect altered circadian alignment rather than baseline expression differences. Fourth, the present study was observational in nature and did not employ pharmacological inhibitors or genetic models targeting JAK2- or IGF-1–related signaling pathways. Accordingly, the present findings do not establish causal mechanistic relationships between altered signaling balance and intrinsic exercise capacity. Finally, only aged female rats were included in the present study, which may limit generalizability to males and younger populations. Future studies incorporating longitudinal designs, multiple circadian sampling time points, multi-tissue analyses, mechanistic interventions, and sex-specific comparisons will be important for further clarifying the molecular mechanisms linking intrinsic exercise capacity, skeletal muscle regulation, aging, and metabolic health.

The original contributions presented in the study are included in the article/. Further inquiries can be directed to the corresponding author. 1