Research ArticleAgingMuscle biology Open Access | 10.1172/JCI172890

Haiming L. Kerr,1,2 Kora Krumm,1,2 Barbara Anderson,1,2 Anthony Christiani,1,2 Lena Strait,1,2 Theresa Li,1,2 Brynn Irwin,1,2 Siyi Jiang,1,2 Artur Rybachok,1,2 Amanda Chen,1,2 Elizabeth Dacek,1,2 Lucas Caeiro,1,2 Gennifer E. Merrihew,3 James W. MacDonald,4 Theo K. Bammler,4 Michael J. MacCoss,3 and Jose M. Garcia1,2

1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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1Geriatric Research, Education and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington, USA.

2Division of Gerontology and Geriatric Medicine, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.

3Department of Genome Sciences, and

4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.

Address correspondence to: Jose M. Garcia, Geriatric Research, Education and Clinical Center, VA Puget Sound Health Care System, University of Washington, 1660 South Columbian Way (S-182-GRECC), Seattle, Washington 98108-1597, USA. Phone: 206.764.2984; Email: jose.garcia@va.gov.

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Published August 15, 2024 - More info

Published in Volume 134, Issue 16 on August 15, 2024
J Clin Invest. 2024;134(16):e172890. https://doi.org/10.1172/JCI172890.
© 2024 Kerr et al. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Published August 15, 2024 - Version history
Received: July 5, 2023; Accepted: June 4, 2024 View PDF Related article:

Abstract

There remains a critical need to define molecular pathways underlying sarcopenia to identify putative therapeutic targets. Research in the mechanisms of aging and sarcopenia relies heavily on preclinical rodent models. In this issue of the JCI, Kerr et al. implemented a clinically-relevant sarcopenia classification system of aged C57BL/6J mice, capturing sarcopenia prevalence across both sexes. The authors performed detailed physiological, molecular, and energetic analyses and demonstrated that mitochondrial biogenesis, oxidative capacity, and AMPK-autophagy signaling decreased as sarcopenia progressed in male mice. Sarcopenia was less prevalent in female mice with fewer alterations compared with the male-affected processes. The findings highlight factors beyond age as necessary for classifying the sarcopenic phenotype in rodent models, reveal sexual dimorphism across the trajectory of age-related declines in muscle mass and function in a commonly used rodent model, and provide insight into sex-dependent molecular alterations associated with sarcopenia progression.

Authors

Allison M. Owen, Christopher S. Fry

× Related video: Sex- and age-specific differences revealed by mouse sarcopenia models

In this episode, Jose Garcia and Haiming Kerr describe how their study characterizes sarcopenia in aged mice using a clinically relevant definition, elucidating age-related changes in muscle mass and function, and the underlying molecular mechanisms in male and female mice.

Abstract

Our study was to characterize sarcopenia in C57BL/6J mice using a clinically relevant definition to investigate the underlying molecular mechanisms. Aged male (23–32 months old) and female (27–28 months old) C57BL/6J mice were classified as non-, probable-, or sarcopenic based on assessments of grip strength, muscle mass, and treadmill running time, using 2 SDs below the mean of their young counterparts as cutoff points. A 9%–22% prevalence of sarcopenia was identified in 23–26 month-old male mice, with more severe age-related declines in muscle function than mass. Females aged 27–28 months showed fewer sarcopenic but more probable cases compared with the males. As sarcopenia progressed, a decrease in muscle contractility and a trend toward lower type IIB fiber size were observed in males. Mitochondrial biogenesis, oxidative capacity, and AMPK-autophagy signaling decreased as sarcopenia progressed in males, with pathways linked to mitochondrial metabolism positively correlated with muscle mass. No age- or sarcopenia-related changes were observed in mitochondrial biogenesis, OXPHOS complexes, AMPK signaling, mitophagy, or atrogenes in females. Our results highlight the different trajectories of age-related declines in muscle mass and function, providing insights into sex-dependent molecular changes associated with sarcopenia progression, which may inform the future development of novel therapeutic interventions.

Graphical Abstract Introduction

Sarcopenia, the loss of muscle mass and function due to aging, affects 25%–45% of older adults in the United States (1) and is associated with increased incidence of falls and injuries, cardiac disease, respiratory disease, and cognitive impairment, and is closely linked to frailty, poor quality of life, and increased mortality (2, 3). Currently, exercise is the only recognized treatment for sarcopenia (4, 5), while nutritional supplementation (6, 7) and off-label pharmacological interventions (8, 9) have shown limited efficacy in improving muscle strength and physical function (10). Therefore, sarcopenia remains an unmet clinical need. Several cellular and molecular mechanisms have been proposed as important regulators of muscle mass during aging, including fiber type transformation (11, 12), imbalance in protein homeostasis (13, 14), and mitochondrial dysfunction (15). However, alterations in these mechanisms are not consistent across studies, and their relative contribution to muscle function loss is still unclear.

Preclinical studies are essential tools to understand the molecular drivers and potential therapeutic targets of sarcopenia. Mice are excellent models because of their shorter lifespan, suitability for genetic modification, and physiological similarity to humans. Natural aging is still the most suitable model for studying sarcopenia in rodents as it can resemble the human aging process more closely than genetically modified or senescence-accelerated models (16). However, in natural aging rodent models, sarcopenia is usually categorized by age regardless of sarcopenic status or based only on muscle mass loss. To date, animal studies investigating sarcopenia limit their subject selection to 1 “old” group aged 18–24 months, which is equivalent to humans aged 56–69 years. Given that the life expectancy in the US is approximately 76.1 years old (17), it is crucial to study mice at an equivalent age (24–30 months old in the C57BL/6J strain).

In 2010, sarcopenia in patients was defined as low muscle mass plus low muscle function (muscle strength or physical performance) by the European Working Group on Sarcopenia in Older People (EWGSOP) (18). In 2018, the same group revised this consensus definition for clinical diagnosis (known as EWGSOP2), prioritizing muscle function over muscle mass as the primary parameter for sarcopenia (19). This change was made because muscle strength better predicts adverse outcomes (20–22) and muscle mass is not considered a clinically meaningful outcome, per se, by the Food and Drug Administration and the European Medicines Agency (23). According to this updated sarcopenia definition (19), probable sarcopenia in patients is defined as low muscle strength only (such as hand grip strength); sarcopenia is defined as low muscle strength plus low muscle mass; and severe sarcopenia is defined as the above-mentioned deficits plus low physical performance (such as low walking speed). This definition also supports the need for interventional studies emphasizing the importance of improving muscle function in addition to muscle mass. Despite these recent advances, there is no consensus on the definition of sarcopenia in rodents, which hinders the identification of molecular targets of clinical relevance.

The goals of this study are: (a) to define sarcopenia in C57BL/6J mice of a clinically relevant age range utilizing the new definition of sarcopenia in humans as a model; (b) to understand the relationship between functional loss and muscle mass loss during the progression of sarcopenia; and (c) to elucidate selected molecular mechanisms underlying the progression of sarcopenia. We evaluated the age-related changes in muscle mass and function in young (4–9 months old) and old (23–32 months old) C57BL/6J male mice. We assessed forelimb grip strength, treadmill running time (time to exhaustion), and hindlimb muscle mass (upon termination) to identify sarcopenia in old mice and established normative parameters to define these outcomes. Subsequently, we analyzed muscle physiology and morphological characteristics in these mice and relevant molecular markers to understand their contribution to the progression of sarcopenia. We also performed proteomic analysis in young and old muscles to elucidate the associations between molecular pathways and each measurement of sarcopenia. A group of young (6–7 month-old) and old (27–28 month-old) female mice were also studied for sarcopenia identification and molecular markers to address sex-specific differences in these characteristics.

Results

Defining sarcopenia in male and female mice using clinically relevant criteria. The EWGSOP2 clinical sarcopenia definition identifies muscle strength as the primary criterion for diagnosing sarcopenia, confirmed by low muscle quality and/or quantity. Severe sarcopenia is diagnosed when low muscle strength, low muscle quantity/quality, and low physical performance are all present (19). To develop a concordant definition in mice, we measured grip strength, total hindlimb muscle mass (milligrams), and treadmill running time (time to exhaustion in seconds) to assess muscle strength, mass, and physical performance, respectively, in young and old male mice. In 23–24 month-old male mice, grip strength and treadmill running time decreased by 21% and 20%, respectively, compared with the young mice, whereas muscle mass decreased by 15%. In mice older than 30 months, the age-related declines were 34% in grip strength, 51% in treadmill running time, and 30% in muscle mass. The decline in treadmill running time from 23 months to over 30 months was more pronounced compared with the other 2 measurements (31% in treadmill versus 13% in grip strength and 15% in muscle mass, Figure 1, A–C). Absolute values of grip strength (g), muscle mass (g), and treadmill running time (s) in male mice at different age brackets are also available in Supplemental Figure 1, A–C; supplemental material available online with this article; https://doi.org/10.1172/JCI172890DS1 Male mice aged 23–26 months showed higher body weight compared with young mice, but differences did not reach significance beyond 26 months (Supplemental Figure 1D). Lean body mass (LBM, which includes skeletal muscle and other organs) increased in old male mice compared with young male mice (Supplemental Figure 1E), and fat mass was 40% higher in male mice aged 23–24 months compared with young male mice but it declined after that. At the age of 29 months or older, fat mass was lower than in young male mice (Supplemental Figure 1F). When grip strength was normalized to body weight (grip strength/body weight, g/g), all old male mice exhibited lower relative grip strength compared with young mice, though no significant age-related difference was observed within the old group (Supplemental Figure 1G). The decrease in grip strength relative to hindlimb muscle mass was more pronounced in male mice aged 23–26 months compared with young male mice. However, in 27–30 month-old male mice, the normalized grip strength was not significantly different from that of the young group (Supplemental Figure 1H). In female mice, at the age of 27–28 months, grip strength, muscle mass, and treadmill running time individually decreased by 13% compared with young mice (Supplemental Figure 2, A–C). In addition, in these old female mice, normalized grip strength (grip strength/BW) decreased by 36% compared with the younger mice (Supplemental Figure 2H), and there was no significant difference after normalizing grip strength to muscle mass (Supplemental Figure 2I). In contrast, body weight, LBM, and fat mass increased by 37%, 19%, and 106%, respectively, in these old female mice compared with their younger peers (Supplemental Figure 2, E–G).

Figure 1

Muscle mass and strength and physical function in young and old C57BL/6J male mice. (A) Forelimb grip strength, (B) Muscle mass, and (C) Treadmill time to exhaustion, by age group, as a percent of the young group’s mean. (A–C) Red horizontal lines at 2 SDs below the young group’s mean define cutoff points for impairments. 1-way ANOVA with LSD post hoc tests (ANOVA P < 0.05) shows significant differences, denoted by different letters (a, b, c, d). (D) The percentage of animals in each age group is identified by their sarcopenia status as nonsarcopenic (NonS; 0 deficit), probably sarcopenic (PS, 1 deficit), or sarcopenic (S, 2–3 deficits) based on the numbers of deficits in grip strength, muscle mass, and treadmill running time. (E–G) Differences in grip strength, muscle mass, and treadmill running time among sarcopenia groups (n = 27, 47, 37 for grip strength and muscle mass; n = 23, 37, 30 for treadmill). 1-way ANOVA followed by LSD post hoc tests (ANOVA P < 0.05) were performed to detect differences among groups (*P < 0.05 and ***P < 0.001 indicate differences in pairwise comparisons). (H–J) Correlations between grip strength, muscle mass, and treadmill running time in old mice. Correlations were assessed with the Spearman correlation coefficient test (ρ). **P < 0.01.

To identify sarcopenia in mice older than 23 months, 3 criteria were used: low muscle strength, muscle mass, and physical performance. Cutoff points were set at 2 SDs below the mean of young mice of the same sex, and a measurement below the cutoff indicated meeting the criterion. This method parallels those used in clinical studies (19, 24). For male mice, the cutoffs were 131 g for muscle strength, 708 mg for muscle mass, and 514 seconds for physical performance (Figure 1, A–C). For female mice, the cutoffs were 126 g, 621 mg, and 576 seconds, respectively (Supplemental Figure 2, A–C). Old mice that did not meet any of the criteria were classified as nonsarcopenic (NonS). Animals that met one criterion were classified as having probable sarcopenia (PS), while animals that met 2 or 3 criteria were classified as having sarcopenia (S). Table 1 shows the percentage of animals exhibiting any of the criteria or a combination of criteria within the same age range. In male mice, the percentage of NonS mice began to decrease at the age of 27–28 months, while the percentage of S mice increased gradually with age (Figure 1D and Table 1). Among old male mice, 25.9% of mice were identified as NonS; 39.2% were identified as PS, with 30.3% exhibiting low grip strength (G), 4.2% with low muscle mass (M), and 4.7% with impaired physical performance (T). Additionally, 34.9% of mice were identified as S, with 14.3% exhibiting both declines in grip strength and muscle mass (GM), 3.6% exhibiting both decreased grip strength and physical performance (GT), and 17% exhibiting declines in all measurements (GMT, Table 1). Significant declines were seen in all 3 measurements among PS or S male mice compared with NonS, except treadmill running time between NonS and PS (Figure 1, E–G). These measurements were positively correlated (Figure 1, H–J). In female mice, the percentages of NonS, PS, and S in old mice were 33.3%, 45.5%, and 21.2%, respectively. Among the female mice with PS, 21.2% had low grip strength (G), 21.2% had low muscle mass (M), and 3% had impaired physical performance (T). Among the female mice with S, 12.1% had both low grip strength and low muscle mass (GM), and 9.1% had all 3 deficits (GMT, Supplemental Figure 2D and Table 1).

Table 1

Prevalence of sarcopenia status in old mice of different age groups

Muscle contractile properties decline as sarcopenia progresses in male mice. To determine if the changes in muscle contractile function worsen with the progression of sarcopenia, we tested in situ muscle contractility in tibialis anterior (TA) muscles in young and old male mice identified as NonS, PS, and S. Mice with S showed significantly lower tetanic force than young mice and old PS mice (Figure 2A). Muscle contractility was conducted by direct stimulation at the TA muscle at gradually increased frequencies every minute. Mice with PS showed declines in force generation starting at 100 Hz, while mice with S showed this decline at 75 Hz (Figure 2B). Consistently, mice with PS and S had a significantly lower peak force compared with the young mice(Figure 2C). An age-related decline was observed in TA muscle mass (Figure 2D), though no difference was found among old mice with different sarcopenia status. Also, mice with S showed numerically lower specific force compared with the young mice, but the difference was not statistically significant (peak force/physiological cross-sectional area, Po/pCSA, Figure 2E).

Figure 2

Contractile properties of TA muscles in young and old nonsarcopenic (NonS), probable-sarcopenic (PS), and sarcopenic (S) male mice. (A) Tetanic force (mN). (B) Contractile force (mN) in response to stimulation at various frequencies (Hz). (C) Peak force (Po, mN) was recorded as the highest force production during force-frequency regimen. (D) Muscle mass (g). (E) Specific force of TA muscle was calculated as peak force divided by physiological cross-sectional area (mN/mm2). Data are shown as mean ± SE (n = 11, 3, 9, 4). 1-way ANOVA was used to identify differences across groups followed by Dunnett’s (for force/frequency) or LSD post hoc test (ANOVA P < 0.05). Tukey HSD post hoc test was conducted when ANOVA was not significant (Specific force, ANOVA P = 0.205). *P < 0.05, **P < 0.01, ***P < 0.001 indicate significant differences compared with young in panel B and significant differences between groups for other panels.

Muscle morphological changes in sarcopenia in male mice. Fiber number and size CSA in plantaris (PL) muscles were analyzed based on myosin heavy chain (MHC) fiber types (Figure 3, A–D) in male mice. Our results did not show significant differences in total fiber number or fiber numbers based on their MHC fiber types, with the exception of type IIA fibers (Figure 3, A and B. IIA fiber number: ANOVA P = 0.087, trend). The number of type IIA fibers tended to be higher in old mice without S compared with young mice (P = 0.067); whereas old mice with S showed a lower number of type IIA fibers than nonS or PS old mice (S versus PS: P = 0.068, trend). Further, the CSA of IIB fibers tended to be smaller in mice with S compared with young mice (1-way ANOVA: P = 0.103, Tukey’s Honestly Significant Difference (Tukey HSD) post hoc test: P = 0.09), whereas the CSA of type IIA and IIX fibers remained unchanged regardless of age or sarcopenia status (Figure 3C).

Figure 3

IHC of myosin heavy chain type IIA, IIB, and IIX fibers in PL muscles from young and old NonS, PS, and S male mice (n= 9, 6, 3, 4). (A) Total fiber number in PL muscles. (B) Fiber number in PL muscles by myosin heavy chain (MHC) type (IIA, IIB, IIX, IIA/X, and IIB/X). (C) CSA of fibers by MHC type in PL muscles (n = 7, 6, 4, 4). (D) Representative images of IHC MHC staining for IIA (green), IIB (red), and IIX (no stain, blank) in PL, with membranes stained for dystrophin (magenta). Data are shown as mean ± SE. 1-way ANOVA was used to identify differences across groups followed by LSD post hoc test (IIA fiber number: ANOVA P = 0.087, trend difference). Tukey HSD post hoc test was conducted when ANOVA was not significant (other fiber number and CSA, ANOVA P > 0.1). *P < 0.05 indicate differences in pairwise comparisons. Trends (0.05 < P < 0.1) were marked in the figure with their P values. Scale bars: 100 μm.

Impaired mitochondrial function in male sarcopenic mice but unaffected mitochondrial markers in female sarcopenic mice. Mitochondrial function is central to maintaining muscle quality during aging (25, 26). We assessed mitochondrial respiration by examining isolated mitochondria in the PL muscles. Maximum mitochondrial respiration, including ADP-stimulated (oxygen consumption rate, OCR-ADP) and uncoupled maximum respiration (OCR-FCCP), was reduced in old mice, regardless of their sarcopenic status (Figure 4, A and B). The total protein content of isolated mitochondria from PL muscles was significantly lower in the S group compared with the other groups (Figure 4C). Compared with the young group, the content of oxidative phosphorylation (OXPHOS) complexes III and I showed a significant decrease in old mice, regardless of their sarcopenic status. The content of complex IV followed the same pattern in which old mice showed lower content than young mice, with the difference between the young and PS groups only approaching significance (P = 0.06). Complexes V and II contents showed similar patterns to other complexes, but there were no significant differences. There was no difference in any of the OXPHOS complexes among the old mice regardless of their sarcopenic status (Figure 4D). To further identify oxidative capacity changes during sarcopenia, we analyzed the succinate dehydrogenase (SDH) positive area in PL muscles, a marker of complex II–regulated oxidative capacity (Figure 5, A and B). With a trend in 1-way ANOVA (P = 0.095), the SDH-positive area was lower in PS and S mice compared with the young mice, whereas mice with NonS were not different from any of the groups (Figure 5, A and B). At the whole muscle level, the protein content of peroxisome proliferator–activated receptor (PPAR) γ coactivator 1α (PGC-1α), a marker of mitochondrial biogenesis, decreased in S mice compared with NonS and young mice, and an age-related decrease in this protein was also observed in PS mice (Figure 5C). We found positive correlations between PGC-1α levels and grip, treadmill, muscle mass, and IIB CSA (trend only) in old mice (Figure 5D). In female mice, the protein levels of PGC-1α in gastrocnemius (GAS) muscles and total protein levels of isolated mitochondria from PL muscles showed no differences across different groups (Supplemental Figure 3, A and B). Similar results were observed for OXPHOS complexes levels in isolated mitochondria (Supplemental Figure 3C).

Figure 4

Mitochondrial respiration and OXPHOS complex content in isolated mitochondria from PL muscles of young and old NonS, PS, and S male mice. (A) Maximum mitochondrial respiration measured as ADP-stimulated oxygen consumption rate (OCR-ADP, pmol/min, n = 16, 5, 7, 6). (B) Uncoupled maximum respiration measured as FCCP-stimulated oxygen consumption rate (OCR-FCCP, pmol/min, n = 16, 5, 7, 6). (C) Total protein in isolated mitochondria (μg) measured by BCA (n = 16, 10, 10, 10). (D) Protein levels of oxidative phosphorylation (OXPHOS) complexes measured using Western blotting (n = 7/group). Western blots were quantified by densitometry and normalized to Ponceau red signal. Representative Western blots and Ponceau red staining are on the right. The line on the blot indicates that lanes are not continuous but from the same blot. Data are shown as mean ± SE. 1-way ANOVA was used to identify differences across groups followed by LSD post hoc test (ANOVA P < 0.05). Tukey HSD post hoc test was conducted when ANOVA was not significant (Complex V and II, ANOVA P > 0.1). ADP-stimulated oxygen consumption rate was analyzed by Kruskal-Wallis tests as the data was not normally distributed (P < 0.05). * P < 0.05, ** P < 0.01, and *** P < 0.001 indicate differences in pairwise comparisons. Trends (0.05 < P < 0.1) were marked in the figure with their P values.

Figure 5

Oxidative capacity and mitochondria biogenesis markers in PL muscles of young and old NonS, PS, and S male mice. (A) Percentage of SDH-positive area in PL muscles (n = 6, 4, 3, 3). (B) Representative images of SDH-stained PL muscles. Scale bars: 100 μm. (C) Relative protein content of PGC-1α in GAS/PL muscles (n = 8, 5, 8, 5), measured by Western blotting, quantified by densitometry, and normalized to Ponceau red signal. Representative Western blots and Ponceau red staining are shown on the right. The line on the blot indicates that lanes are not continuous but from the same blot. Data are shown as mean ± SE. (A and C) 1-way ANOVA was used to identify differences across groups followed by LSD post hoc test (ANOVA P < 0.05 for PGC-1α; ANOVA P = 0.095 for SDH, trend difference). *P < 0.05, **P < 0.01, and ***P < 0.001 indicate differences in pairwise comparisons. Trends (0.05 < P < 0.1) are marked in the figure with the P value. (D) Correlations between PGC1-α protein content and grip strength, muscle mass, treadmill running time, or MHC IIB fiber cross-sectional area. Correlations were assessed with the Spearman correlation coefficient test (ρ). *P < 0.05, **P < 0.01.

Autophagy and AMPK signaling in sarcopenia in male and female mice. Autophagy serves as a quality control mechanism that breaks down damaged organelles, including mitochond