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6.2: Age Related Changes to the Skeletal Muscle System - Biology

6.2: Age Related Changes to the Skeletal Muscle System - Biology


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As one ages the mass of skeletal muscle decreases throughout the body. Proper nutrition and exercise can slow the loss muscle cells, but heredity also seems to be a factor.

Along with the loss of skeletal muscle mass comes the loss of skeletal muscle strength. For most individuals there is only a ten to twenty percent reduction in strength up to the age of seventy. After the age of seventy the reduction in strength may increase to fifty percent.


Muscle Echogenicity and Changes Related to Age and Body Mass Index

Introduction: Muscle fibers are lost and replaced by fat- and fibrous-tissue infiltration during aging. This process decreases muscle quality and influences tissue appearance on ultrasound images over time. Increased muscle "echogenicity" represents changes caused by fat- and fibrous-tissue infiltration and can be quantified with recently developed software.

Objective: To investigate skeletal muscle quality through echogenicity, estimates according to participant's body mass index (BMI) and age were taken.

Methods: This was a cross-sectional study performed at the Pennington Biomedical Research Center, Baton Rouge, Louisiana with 117 participants (57 men and 60 women), with mean age (±SD) 38.9 ± 17.0 years and BMI 28.6 ± 6.2 kg/m². All participants were examined by ultrasound (LOGIQ GE Healthcare), using a 5.0-MHz linear transducer. Participants had muscle thickness measured by ultrasound at 4 anatomic locations (biceps and triceps brachial, femoral quadriceps, and calf triceps). Echogenicity was analyzed with specific software (Pixel Health) that evaluated the image in gray scale.

Results: According to BMI, 41% of participants were obese. There was a positive correlation between age and thigh-muscle echogenicity (rp = 0.534, P < .0001) and a negative correlation between thigh-muscle echogenicity and thickness (rp = -0.395, P <.0001). There was high muscle echogenicity in participants with overweight and obesity aged 50 years or older (P < .05).

Conclusion: Older age and higher BMI were associated with stronger echogenicity signals and smaller muscle thickness. People with overweight, obesity, and/or older than 50 years old have reduced muscle quality with smaller muscle thickness, as observed with ultrasound.

Keywords: body composition echogenicity elderly muscle obesity ultrasound.


Abstract

Aging is associated with decreased bone mass and accumulation of bone marrow adipocytes. Both bone forming osteoblastic cells and bone marrow adipocytes are derived from a stem cell population within the bone marrow stroma called bone marrow stromal (skeletal or mesenchymal) stem cells (BMSC). In the present review, we provide an overview, based on the current literature, regarding the physiological aging processes that cause changes in BMSC lineage allocation, enhancement of adipocyte and defective osteoblast differentiation, leading to gradual exhaustion of stem cell regenerative potential and defects in bone tissue homeostasis and metabolism. We discuss strategies to preserve the “youthful” state of BMSC, to reduce bone marrow age-associated adiposity, and to counteract the overall negative effects of aging on bone tissues with the aim of decreasing bone fragility and risk of fractures.


Effects of Aging on the Musculoskeletal System

From about age 30, the density of bones begins to diminish in men and women. This loss of bone density accelerates in women after menopause. As a result, bones become more fragile and are more likely to break (see Osteoporosis), especially in old age.

As people age, their joints are affected by changes in cartilage and in connective tissue. The cartilage inside a joint becomes thinner, and components of the cartilage (the proteoglycans—substances that help provide the cartilage's resilience) become altered, which may make the joint less resilient and more susceptible to damage. Thus, in some people, the surfaces of the joint do not slide as well over each other as they used to. This process may lead to osteoarthritis. Additionally, joints become stiffer because the connective tissue within ligaments and tendons becomes more rigid and brittle. This change also limits the range of motion of joints.

Loss of muscle (sarcopenia) is a process that starts around age 30 and progresses throughout life. In this process, the amount of muscle tissue and the number and size of muscle fibers gradually decrease. The result of sarcopenia is a gradual loss of muscle mass and muscle strength. This mild loss of muscle strength places increased stress on certain joints (such as the knees) and may predispose a person to arthritis or falling. Fortunately, the loss in muscle mass and strength can partially be overcome or at least significantly delayed by a program of regular exercise.

The types of muscle fibers are affected by aging as well. The numbers of muscle fibers that contract faster decrease much more than the numbers of muscle fibers that contract slower. Thus, muscles are not able to contract as quickly in old age.


CAUSES OF SARCOPENIA

The cause of sarcopenia is generally thought to be multifactorial, with environmental causes, disease triggers, inflammatory pathway activation, mitochondrial abnormalities, loss of neuromuscular junctions, reduced satellite cell numbers, and hormonal changes all thought to contribute ( Fig. 1 ). In addition to these causes, recent progress in the understanding of molecular pathways that contribute to skeletal muscle maintenance has helped to further highlight Tissue growth factor (TGF)-β signaling, apoptosis activation, and declines in mitochondrial function as potentially important in triggering sarcopenia as described in more detail below.

Multifactorial cause of sarcopenia. The ovals represent domains known to influence the maintenance of skeletal muscle strength and mass in aging organisms.

Environmental causes are usually divided between declines in activity and declines in nutritional intake. Older adults are less active, in part because of the increased chronic disease burden that leads to pain and fatigue [20]. In addition, declines in adequate protein and calorie intake, as well as overnutrition that results in sarcopenic obesity and accelerated loss of muscle mass and function, are important contributors to sarcopenia in older adults [14▪,21]. Taken together, these environmental influences are superimposed on a multifactorial, age-related change in biology that pushes toward declines in skeletal muscle mass and strength as described below.

First, declines in the number of neuromuscular junctions, with resulting drop out of fast-twitch or type-II muscle fibers is thought to be play an important role in age-related muscle decline [22]. Recent studies in older female mice have demonstrated striking increases in the percentage of fully denervated neuromuscle junctions, especially in the fast-twitch muscle fibers such as in the extensor digitorum longus [23▪]. Interestingly, the number of motor neurons in the spinal cord that innervate this area is not decreased, suggesting that this may be an axonal decline rather than a nerve body change per se. Because of the potential importance of this loss to the development of sarcopenia in humans, a potentially important new diagnostic screening measurement, the C-terminal agrin fragment, has been identified as a marker of neuromuscular junction decline in older men [24]. Second, declines in hormones that are important in muscle mass maintenance, including insulin-like growth factor-1, Dehydroepiandrosterone sulfate, testosterone, and estrogen, all likely contribute to sarcopenia [25,26]. These pathways also offer important potential opportunities for interventions [27]. Third, inflammatory pathway activation, likely due to a variety of disease and aging causes, is known to be an important contributor to sarcopenia [28]. A study [29] of serum levels of the inflammatory cytokine interleukin-6 and its relationship to muscle strength in older women demonstrated a steeper decline in walking ability, a higher risk of developing physical disability, explained in part by a parallel decline in skeletal muscle strength. This may be in part due to the important influence of chronic inflammatory cytokine exposure on satellite cells in muscle fibers. The contribution of inflammation in older adults can come from multiple sources. Certainly, chronic disease states are among the most common triggers of inflammatory pathway activation. Many inflammatory rheumatological conditions such as systemic lupus erythematosus and RA are associated with muscle loss that is thought to be related to the chronic activation of inflammatory pathways that in turn negatively influence muscle regeneration [30▪]. Many other chronic conditions, including renal failure and congestive heart failure, likely accelerate the development of sarcopenia via the increase of inflammatory mediators [31].

Finally, the aging-related loss of ability to replenish and replace skeletal muscle is increasingly evident. Skeletal muscle stem cells, crucial to the regeneration of skeletal muscle in older and younger adults, appear to be compromised in older adults in that they migrate at much slower speeds than younger cells, and their motility is hampered perhaps in part because of low levels of integrin expression [32▪▪].

Newer molecular findings related to sarcopenia

Underlying the more physiological causes outlined above are a host of age-related and disease-related biological changes that increase the vulnerability of older adults to the development of sarcopenia [16▪]. Some important new studies have helped to shed light on aging-related molecular triggers for sarcopenia. Mitochondrial function and mitochondrial biogenesis appear to be altered in skeletal muscles of older adults, which in turn may contribute to altered skeletal muscle mass and function [33▪▪]. Aging-related changes in the angiotensin system were recently identified to play a crucial role in skeletal muscle healing and in disuse atrophy of skeletal muscle [34▪▪]. Importantly, in this same study, the angiotensin type-1 receptor blocking agent losartan was found to help accelerate skeletal muscle healing and prevent disuse atrophy in treated older mice, likely in response to downregulation of the TGF-β pathways. Losartan was also demonstrated to increase the number of angiotensin type-2 receptors in the mitochondria of older mice, which in turn explains some of the improved skeletal muscle healing that was observed in older mice treated with losartan [35▪]. Apoptosis, or programmed cell death may also play an important role in sarcopenia development. Preliminary studies of proteins associated with apoptosis showed an upregulation in those older adults with lower thigh muscle volume and slower gait speed, suggesting that apoptosis may contribute to this muscle decline. The apoptosis-inducing factor, usually located in the intermitochondrial membrane space, was recently found to protect skeletal muscle precursors, or satellite cells, from apoptosis so long as it was not released into the cytoplasm of cells [36]. Finally, newer evidence suggests that altered transcriptional regulation of mRNA and translation of proteins negatively impact proteins important in myogenesis, including Pax 7, myogenin, and MyoD [37].

Interventions for sarcopenia

Although substantial progress has been made in the understanding of the multifactorial causes of sarcopenia, most interventions have focused on improving the environmental causes of sarcopenia, namely through increasing activity and providing adequate nutrition. Given the high prevalence of sarcopenia, and close relationship to fatigue, functional decline, and chronic illness, the development of interventions has been touted by drug companies and investigators as a crucially important target for intervention in older adults [38]. Although a large-scale clinical trial that targets the prevention or treatment of sarcopenia per se has not been attempted, many studies have indirectly targeted sarcopenia by using age-related declines in physical function as an outcome. Results of clinical intervention studies in even the oldest and frailest nursing home residents have demonstrated significant functional improvement through a combination of nutrition and resistance exercise [39]. Recent clinical studies continue to show this with significant increases in muscle protein synthesis in older adults who receive physical activity and nutrition [40▪]. Other groups continue to refine the best exercise modality to treat or prevent sarcopenia [10,16▪,41]. These interventions appear to positively impact satellite cell dysfunction, neuromuscular junction decline, and mitochondrial biogenesis. Although endocrine interventions targeting muscle function and strength have been developed previously, few, if any, have shown efficacy [26]. Future pharmaceutical interventions for sarcopenia will also likely target very specific molecular pathways such as the angiotensin system, apoptosis, and mitochondrial function.

In order to develop the next generation of studies targeting sarcopenia per se, it will be important to develop a consensus definition that can be utilized across a number of studies and populations in order to determine safety and efficacy for sarcopenia. The International Working Group on Sarcopenia has developed recommendations on the design of phase IIB clinical trials and cautions that appropriate muscle mass measurements and physical function measurements, along with sufficient periods of time, are necessary to adequately test any proposed pharmaceutical intervention [42]. EWGSOP also strongly recommends that measures of muscle mass, muscle strength, and/or functional performance be utilized in any clinical definition [19], which will help to facilitate the operationalization and validation of a sarcopenia diagnostic screening methodology that can be reproduced across many populations, used in clinical trials, and integrated into the practice of geriatric medicine.


Methods

Animals, housing and study design

Male Dunkin Hartley guinea pigs (N =�) were sourced from Charles Rivers, UK, at 6 weeks of age. Animals were group-housed in large pens (4 m x 8 m) with free access to standard guinea pig chow (Purina, UK) and water. At 2, 3, 5 and 7 months of age, six animals were selected based upon their proximity to the median weight of the cohort and euthanized as described below. All animal procedures underwent ethical approval by the University of Nottingham and were conducted in full compliance with the Animals (Scientific Procedures) Act, 1986.

Termination and histopathology

Animals were euthanized by intra-peritoneal injection of pentobarbital sodium and death was confirmed by cervical dislocation. Knee joints were obtained for histopathological analysis by making a full thickness cut 2਌m above and below the patella. The joints were formalin fixed and decalcified in 10% formic acid prior to processing by routine vacuum assisted wax infiltration. Toluidine blue stained step coronal sections were prepared at 300 μm intervals and evaluated using a histological scoring system optimised and validated for guinea pig specimens [35]. Pathological features at each condyle were combined to calculate a femoral, tibial and combined OA score. The observer was blinded to both the animal number and age in all cases.

Biospecimens

Whole bilateral quadriceps muscle samples, inclusive of the rectus femoris, were dissected, weighed and immediately snap frozen in isopentane cooled with liquid nitrogen. Care was taken to avoid inclusion of any adipose tissue or additional muscle, most importantly the tensor fasciae latae and sartorius, which are located within the dissected area. Whole blood was drawn via cardiac puncture into clot-activator tubes (Sarstedt) and serum was obtained by centrifugation. All serum was kept at �ଌ prior to analysis.

Extraction of total RNA

Total RNA was extracted from 100 mg of sample using TRIzol regent (Invitrogen) according to standard procedure. Contaminating genomic DNA was removed by RQ RNase-Free DNase I digestion (Promega) as specified by the manufacturer’s standard instructions. The resulting total RNA was re-suspended in molecular biology grade water (Promega). All RNA was stored at �ଌ prior to use.

Reverse transcription

First strand complementary DNA (cDNA) was reverse transcribed from 1 μg total RNA using random hexamers and Moloney murine leukemia virus reverse transcriptase (MMLV) in a final volume of 25-μL as described by the manufacturer (Promega).

Primer design

Previously published oligonucleotide primers [36] were sourced from MWG Eurofins Operon (Table  1 ).

Quantitative PCR

Quantitative PCR reactions were performed in triplicate on 5 μL cDNA in SYBR 1 Master mix (Roche), 0.25 mM forward and reverse primers in a final volume of 15 μL. Cycling parameters were 95ଌ for 5 minutes prior to 35਌ycles of 10 seconds at 95ଌ, 10 seconds at 55ଌ and 30 seconds at 72ଌ. Single signal acquisition was set to read at 72ଌ. All reactions were run on a 384-well microplate on a LightCycler LC480 (Roche) configured for SYBR green determination as specified by the manufacturers. Melt curve analysis was performed at the end of each completed analysis run to ensure only the specific product was amplified. All quantitative PCR data was normalised to the total first strand cDNA concentration following reverse transcription using OliGreen (Invitrogen).

Serum CTX II assessment

Serum CTX II concentration was determined by a validated enzyme linked immunosorbent assay incorporating a monoclonal antibody specific for the neo-epitope formed when collagen type II is degraded to form CTX II (Serum Cartilaps, IDS, USA). Samples were processed according to the manufacturer’s instructions using 25 μL of guinea pig serum against standards produced from rat CTX II of known concentrations (0�.6 pg/mL). All samples were analysed in duplicate and a coefficient of variation υ% was deemed acceptable.

Skeletal muscle metabolic potential

Isocitrate dehydrogenase (ICDH) and lactate dehydrogenase (LDH) enzyme activities were measured as an index of oxidative (aerobic) metabolism and glycolytic (anaerobic) metabolism, respectively. Both enzyme activities were measured in accordance with the original method of Brandstetter, 1998 [56].

Serum regulated upon activation, normal T-cell expressed and secreted (RANTES) assessment

Serum RANTES expression was determined by fluorescent enzyme-linked immunosorbent assay (ELISA) (BioRad). Serum samples from all guinea pigs were analysed as recommended by the manufacturer against a range of rat cytokine standards (0𠄳,200 pg/mL) and a sample dilution of 1:3, utilising a total of 30 μL of sera. All samples were analysed (Bio-Plex 200) in triplicate, with a coefficient of variation υ% deemed as acceptable.

Statistical analysis

All data are reported as mean ± standard error of the mean (SEM) unless otherwise specified. Comparisons between multiple groups were performed by analysis of variance (ANOVA) using GraphPad software V5.0 (Prism) with Dunnett’s post hoc test (comparing all experimental groups to the 2 month group) performed where P π.05.


Some Recent Findings

  • CT evaluation of timing for ossification of the medial clavicular epiphysisΐ] "The clavicle is the first bone to ossify in the developing embryo and the last to complete epiphyseal union. It is the latter sustained period of growth that has attracted the interest of skeletal biologists and forensic practitioners alike, who collectively recognize the important opportunity this bone affords to estimate skeletal age across the prenatal to early adult lifespan. Current research is largely directed towards evaluating the applicability of assessing fusion in the medial epiphysis, specifically for determining age of majority in the living. . Transition analysis is used to calculate age ranges and determine the mean age for transition between an unfused, fusing and fused status. The maximum likelihood estimates (in years) for transition from unfused to fusing is 20.60 (male) and 19.19 (female) transition from fusing to complete fusion is 21.92 (male) and 21.47 (female)."
  • Ossification of the vertebral column in human foetuses: histological and computed tomography studiesΑ] "There is no agreement in the literature as to the time of the onset and progress of the vertebral column ossification. The aim of the present study was to determine the precise sequence of ossification of the neural arches and vertebral centra.Histological and radiographic studies were performed on 27 human foetuses aged from 9 to 21 weeks. It was found that the ossification of vertebrae commences in foetuses aged 10 and 11 weeks. Ossification centres appear first for neuralarches in the cervical and upper thoracic vertebrae and by the end of 11th week they are present in all thoracic and lumbar neural arches. In the vertebral centrain foetus of 10 weeks ossification was found in the lower 7 thoracic and first lumbar vertebrae. By the end of 11th week ossification is present in the lower 4 cervical, all thoracic, all lumbar and 4 sacral vertebral centra." Computed Tomography
  • An image-based skeletal tissue model for the ICRP reference newbornΒ] "Active marrow distributions were found to be in reasonable agreement with those given previously by the ICRP. However, significant differences were seen in total skeletal and site-specific masses of trabecular and cortical bone between the current and ICRP newborn skeletal tissue models. The latter utilizes an age-independent ratio of 80%/20% cortical and trabecular bone for the reference newborn. In the current study, a ratio closer to 40%/60% is used based upon newborn CT and micro-CT skeletal image analyses. These changes in mineral bone composition may have significant dosimetric implications when considering localized marrow dosimetry for radionuclides that target mineral bone in the newborn child."

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Methods

Subjects

Thirty-eight non-obese subjects (8 men and 10 women who were between 25 and 45 y old and 10 men and 10 women who were between 65 and 85 y old) participated in this study. Data from 8 young men and 8 young women have previously been reported [11]. None of the subjects engaged in regular physical activities (i.e., they exercised 𢙁.5 h·wk -1 ) or took medications (including hormonal contraceptives or hormone replacement therapy), and none reported excessive alcohol intake or consumed tobacco products. All subjects were considered to be in good health after completing a comprehensive medical evaluation, which included a history and physical examination, standard blood tests, and an oral glucose (75 g) tolerance test (Table ​ (Table1). 1 ). Written informed consent was obtained from all subjects before their participation in the study, which was approved by the Human Research Protection Office at Washington University School of Medicine in St. Louis, MO.

Table 1

Subjects’ anthropometric and basic metabolic characteristics at the time of screening

 MENWOMENANOVA
YoungOldYoungOldSexAgeInteraction
Age (years) 40 ±𠂒 69 ±𠂑 37 ±𠂒 73 ±𠂒 0.84 π.001 0.10
Body mass (kg) 81 ±𠂔 81 ±𠂓 69 ±𠂒 61 ±𠂔 π.001 0.22 0.25
Body mass index (kg/m 2 ) 26.5 ±𠂑.0 25.9 ±𠂐.8 25.0 ±𠂐.8 24.0 ±𠂑.3 0.09 0.44 0.84
Fat mass (kg) 18 ±𠂒 21 ±𠂒 22 ±𠂑 23 ±𠂓 0.16 0.34 0.61
Fat mass (% body mass) 21 ±𠂒 25 ±𠂒 32 ±𠂑 36 ±𠂒 π.001 0.055 0.97
Fat free mass (kg) 63 ±𠂒 60 ±𠂒 47 ±𠂒 38 ±𠂑 π.001 0.002 0.17
Fat free mass (% body mass) 79 ±𠂒 75 ±𠂒 68 ±𠂑 64 ±𠂒 π.001 0.055 0.97
Appendicular muscle mass (kg) 27.5 ±𠂑.1 24.9 ±𠂐.7 18.0 ±𠂐.9 14.1 ±𠂐.5 π.001 π.001 0.46
Appendicular muscle mass index (kg/m 2 ) 9.0 ±𠂐.2 8.0 ±𠂐.2 6.5 ±𠂐.2 5.5 ±𠂐.2 π.001 π.001 0.99
Fasting plasma glucose (mg/dl) 93 ±𠂑 95 ±𠂓 87 ±𠂑 90 ±𠂑 0.005 0.18 0.54
2 h post OGTT plasma glucose (mg/dl) 94 ±𠂗 111 ±𠂘 93 ±𠂔 106 ±𠂗 0.66 0.03 0.77
HOMA-IR 1.46 ±𠂐.32 1.59 ±𠂐.27 1.08 ±𠂐.22 1.16 ±𠂐.23 0.13 0.69 0.91
Systolic blood pressure (mm Hg) 109 ±𠂓 119 ±𠂕 105 ±𠂓 126 ±𠂖 0.69 π.001 0.21
Diastolic blood pressure (mm Hg) 69 ±𠂒 74 ±𠂓 65 ±𠂓 68 ±𠂔 0.14 0.21 0.70
Plasma triglycerides (mg/dl) 88 ±� 102 ±� 66 ±𠂘 72 ±� 0.04 0.43 0.75
Total plasma cholesterol (mg/dl) 170 ±� 193 ±𠂗 172 ±𠂘 197 ±𠂘 0.74 0.01 0.89
LDL-cholesterol (mg/dl) 106 ±𠂙 125 ±𠂖 97 ±𠂗 109 ±𠂘 0.09 0.03 0.61
HDL-cholesterol (mg/dl) 47 ±𠂔 49 ±𠂓 62 ±𠂔 73 ±𠂔 π.001 0.09 0.25
Testosterone (ng/ml) 4.8 ±𠂐.5 5.7 ±𠂐.5 0.9 ±𠂐.1 0.8 ±𠂐.1 π.001 0.26 0.18
Estradiol (pg/ml) 25 ±𠂒 18 ±𠂒 62 ±𠂙 a 8 ±𠂓 b 0.01 π.001 π.001
Progesterone (ng/ml)0.24 ±𠂐.100.28 ±𠂐.085.08 ±𠂑.53 a 0.23 ±𠂐.07π.01π.01π.01

Values are means ± SEM. HOMA-IR: Homeostasis model assessment of insulin resistance. OGTT: oral glucose tolerance test.

a Value significantly different from values in men and old women (P <𠂐.01). b Value significantly different from values in men (P <𠂐.05).

Experimental protocol

Approximately two weeks before the protein metabolism study, subjects' total body mass, fat mass, fat-free mass (FFM) and appendicular muscle mass (Table ​ (Table1) 1 ) were measured by using dual-energy X-ray absorptiometry (Delphi-W densitometer, Hologic, Waltham, MA) [29]. The appendicular muscle mass index, a measure of muscle mass adjusted for individual differences in height was calculated by dividing total appendicular muscle mass (kg) by height squared (m 2 ) [30]. Subjects were instructed to adhere to their usual diet and to refrain from vigorous physical activities for three days before the protein metabolism study. We did not control for menstrual cycle phase in our young women because Miller et al. [31] demonstrated that the rate of muscle protein synthesis is not different during the follicular and luteal phases of the menstrual cycle and we [11] have found that there is no relationship between plasma estradiol or progesterone concentrations and the muscle protein FSR in young women. The evening before the study, subjects were admitted to the Clinical Research Unit at Washington University School of Medicine. At 2000 h, they consumed a standard meal providing 50.2 kJ per kg body weight (15% as protein, 55% as carbohydrates and 30% as fat). Subjects then rested in bed and fasted (except for water) until completion of the study the next day. At

0600 h on the following morning, a cannula was inserted into a vein in the forearm or the antecubital fossa of one arm for the infusion of stable isotope labeled tracers, insulin, glucose, and amino acids another cannula was inserted into a vein of the contralateral hand (which was warmed to 55ଌ) to obtain arterialized blood samples. At

0800 h, primed, constant infusions of [ring- 2  H5phenylalanine (priming dose: 2.8 μmol·kg FFM -1 , infusion rate: 0.08 μmol·kg FFM -1 ·min -1 ) and [6,6- 2  H2glucose (priming dose: 18 μmol·kg body wt -1 , infusion rate: 0.22 μmol·kg body wt -1 ·min -1 ), both purchased from Cambridge Isotope Laboratories Inc. (Andover, MA), were started and maintained for seven hours. Four hours after the start of the tracer infusions, a hyperinsulinemic-hyperaminoacidemic-euglycemic clamp was started and maintained for three hours. Human insulin (Novolin R, Novo Nordisk, Princeton, NJ) was infused at a rate of 20 mU·m -2 body surface area (BSA)·min -1 (initiated with priming doses of 80 mU·m -2 BSA·min -1 for the initial 5 minutes and 40 mU·m -2 BSA·min -1 for an additional 5 minutes). Plasma amino acid availability was increased by providing an intravenous amino acid mixture (Travasol 10%, Baxter, Deerfield, IL) infused at a rate of 105 mg amino acids·kg FFM -1 ·h -1 (priming dose: 35 mg amino acids·kg FFM -1 ). During the insulin infusion, euglycemia at a blood glucose concentration of

5.5 mM was maintained by variable rate infusion of 20% dextrose solution (Baxter, Deerfield, IL) which was enriched (2.5%) with [6,6- 2  H2glucose. To adjust for the increased plasma amino acid availability and reduced hepatic glucose production during the clamp procedure, the [ring- 2  H5phenylalanine and [6,6- 2  H2glucose infusion rates were increased to 0.12 μmol·kg FFM -1 ·min -1 (phenylalanine) and decreased to 0.11 μmol·kg body wt -1 min -1 (glucose), respectively.

3 ml each) were obtained before beginning the tracer infusion and at 60, 90, 180, 210, 220, 230, 240, 270, 300, 330, 360, 390, 400, 410, and 420 min to determine phenylalanine and glucose tracer-to-tracee ratios (TTR) in plasma and plasma concentrations of insulin, glucose, myostatin, follistatin, phenylalanine, and leucine (thought to be a major regulator of muscle protein synthesis [32]). Additional blood samples (

1 ml each) were obtained every 10 minutes during the clamp procedure to monitor plasma glucose concentration. Muscle tissue (

50-100 mg) was obtained under local anesthesia (lidocaine, 2%) from the quadriceps femoris by using a Tilley-Henkel forceps [33] at 1 h, 4 h and 7 h after starting the tracer infusion to determine the muscle protein fractional synthesis rate (FSR) during basal conditions (1 h – 4 h) and during the hyperinsulinemic-hyperaminoacidemic-euglycemic clamp (4 h – 7 h) and the mRNA expressions (initial biopsy at 1 h only) of myostatin, myoD, and follistatin.

Sample processing and analyses

To determine plasma glucose concentration, blood was collected in pre-chilled tubes containing heparin, plasma was separated immediately by centrifugation and glucose concentration was measured immediately. All other blood samples were collected in pre-chilled tubes containing EDTA, plasma was separated by centrifugation within 30 min of collection and then stored at �ଌ until final analyses. Muscle samples were rinsed in ice-cold saline immediately after collection, cleared of visible fat and connective tissue, frozen in liquid nitrogen and stored at �ଌ until final analyses were performed.

Plasma glucose concentration was measured on an automated glucose analyzer (Yellow Spring Instruments, Yellow Springs, OH). Plasma insulin concentration was determined by radioimmunoassay (Linco Research, St. Louis, MO). Commercially available ELISA kits were used to determine the concentrations of testosterone, estradiol, progesterone (all IBL America, Minneapolis, MN), myostatin (ALPCO Diagnostics, Salem, NH) and follistatin (Rɭ Systems, Minneapolis, MN) in plasma.

To determine the labeling of plasma glucose, plasma proteins were precipitated with ice-cold acetone, and lipids were extracted with hexane. The aqueous phase, containing glucose, was dried by speed-vac centrifugation (Savant Instruments, Farmingdale, NY), glucose was derivatized with heptafluorobutyric acid and the TTR was determined by using gas-chromatography/mass-spectrometry (GC-MS, Hewlett-Packard MSD 5973 system with capillary column) as previously described [34].

To determine plasma concentrations of leucine and phenylalanine and the labeling of plasma phenylalanine, known amounts of nor-leucine and [1- 13 𠂜]phenylalanine were added to an aliquot of each plasma sample, plasma proteins were precipitated, and the supernatant, containing free amino acids, was collected to prepare the t-butyldimethylsilyl (t-BDMS) derivative of leucine and phenylalanine to determine their TTRs by GC-MS (MSD 5973 System, Hewlett-Packard) [35,36]. To determine phenylalanine labeling in muscle proteins and in tissue fluid, samples (

20 mg) were homogenized in 1 ml trichloroacetic acid solution (3% w/v), proteins were precipitated by centrifugation, and the supernatant, containing free amino acids, was collected. The pellet containing muscle proteins was washed and then hydrolyzed in 6 N HCl at 110ଌ for 24 h. Amino acids in the protein hydrolysate and supernatant samples were purified on cation-exchange columns (Dowex 50 W-X8-200, Bio-Rad Laboratories, Richmond, CA), and the t-BDMS derivative of phenylalanine prepared to determine its TTR by GC-MS (MSD 5973 System, Hewlett-Packard) analysis [35,36]. The extent of phenylalanine labeling in plasma (from arterialized blood samples), muscle tissue fluid, and muscle protein were calculated based on the simultaneously measured TTR of standards of known isotope labeling.

Muscle myostatin, myoD and follistatin gene expression was evaluated by using RT-PCR. RNA was isolated in RNA-Bee reagent (Tel-Test, Inc, Friendswood, TX), quantified spectrophotometrically (NanoDrop 1000, Thermo Scientific, Waltham, MA) and reverse transcribed (Taqman Reverse Transcription Kit, Applied Biosystems, Foster City, CA) by using the SYBR Green Master Mix (Applied Biosystems, Carlsbad, CA) on an ABI 7500 real-time PCR system (Applied Biosystems, Carlsbad, CA) using the following primer sequences (all 5' to 3'). Myostatin forward: ACC TGT TTA TGC TGA TTG TTG CT, reverse: GAG CTG TTT CCA GAC GAA GTT TA. MyoD forward: CGC CAT CCG CTA TAT CGA GG, reverse: CTG TAG TCC ATC ATG CCG TCG. Follistatin forward: GTA ATC GGA TTT GCC CAG AGC, reverse: GCA GGC AGG TAG CCT TTC T. Results were normalized to the 36B4 housekeeping gene.

Calculations

The muscle protein FSR was calculated from the rate of [ring- 2  H5phenylalanine incorporation into muscle protein, using a standard precursor-product model as follows: FSR = 㥎p/Eic ×𠂑/t ×� where 㥎p is the change between two consecutive biopsies in extent of labeling (TTR) of protein-bound phenylalanine. Eic is the mean labeling over time of the precursor for protein synthesis and t is the time between biopsies. The free phenylalanine labeling in muscle tissue fluid was chosen to represent the immediate precursor for muscle protein synthesis (i.e., aminoacyl-t-RNA) [37].

Glucose rates of appearance (Ra) in plasma during basal conditions and during the clamp procedure were calculated by dividing the glucose tracer infusion rate by the average plasma (from arterialized blood samples) glucose TTR during the last 30 min of the basal period and the last 30 min of the clamp, respectively. Glucose Ra during basal conditions represents endogenous glucose Ra and thus an index of hepatic glucose production rate. During the clamp procedure, glucose Ra represents the sum of endogenous glucose Ra and the rate of infused glucose. Endogenous glucose Ra during the clamp was therefore calculated by subtracting the glucose infusion rate from glucose Ra glucose rate of disappearance (Rd) was assumed to be equal to glucose Ra plus the tracer infusion rate. The homeostasis model assessment of insulin resistance (HOMA-IR) score was calculated by dividing the product of basal glucose and insulin concentrations (expressed in mM and mIU/l, respectively) by 22.5 [38].

Statistical analysis

All data sets were normally distributed. Two-way analysis of variance (ANOVA with age and study condition, i.e., basal vs. clamp as factors) was used to compare the muscle protein FSR, and substrate and hormone concentrations in young and old men and in young and old women, respectively. In addition, 2-way ANOVA with age and sex as factors was used to compare the basal muscle protein FSR, the anabolic response to increased amino acid and insulin availability, plasma substrate, hormone and myogenic regulatory factor concentrations, and muscle gene expression amongst all four groups (young men, old men, young women, and old women). When significant interactions were found, Tukey’s post-hoc procedure was used to locate the differences. A P-value of 𢙀.05 was considered statistically significant. Data are presented as means ± SEM unless otherwise noted (i.e., Figure ​ Figure1). 1 ). Statistical analyses were carried out by using the PASW statistical software package 18 (IBM, Armonk, NY).

Skeletal muscle protein fractional synthesis rate (FSR) during basal, post-absorptive conditions (top) and the increase in muscle protein FSR in response to the hyperinsulinemic-hyperaminoacidemic-euglycemic clamp procedure (bottom) in young and old men and young and old women. Data are median (central horizontal line), inter-quartile range (box), and minimum and maximum values (vertical lines). Bars not sharing the same letter are significantly different from each other (P <𠂐.05).


MATERIALS AND METHODS

Study population. InCHIANTI is an epidemiological study of risk factors for mobility disability in old age. The InCHIANTI study population is a representative sample of the population living in Greve in Chianti and Bagno a Ripoli, two small towns located in the Chianti countryside of Tuscany, Italy. The study design and data collection have been previously described (11). Of the initial 1,453 subjects who received an in-home interview, 277 were excluded from the analyses because information on muscle function and calf muscle cross-sectional area for these participants was not available, either because they refused to come to the clinic for an examination or were too sick to be evaluated. To avoid the possible interference of neurological impairments in the measure of muscle function, participants with a diagnosis of stroke (n = 55), Parkinson's disease (n = 9), peripheral neuropathy (n = 4), and cognitive impairment (Mini Mental State Examination Score ≤ 21 n = 78) were also excluded. The final study population thus included 1,030 persons, 469 men and 561 women, dispersed over a wide age range of 20–102 yr. The study protocol was examined and approved by the Italian National Institute of Research and Care on Aging ethics committee. All participants were informed of the study procedure, purposes, and known risks, and all gave their informed consent.

Measures. After the home interview, participants received a full standardized medical and functional evaluation by, respectively, a geriatrician and an experienced physical therapist, both of whom had received special training on the assessment tools used in this study. The objective assessment of physical function was performed within 4 wk after the interview in a dedicated laboratory.

In particular, isometric muscle strength was assessed on eight muscle groups of the lower extremity by a hand-held dynamometer, by using a standard protocol (2). We measured strength with isometric dynamometry because this method could be used both in the InCHIANTI study clinic and in the participants' homes for those who could not come to the study clinic. All measures of lower extremity muscle strength were highly correlated (Pearson's correlation coefficients ranging from 0.87 to 0.92). Therefore, in the analyses presented here, we used only knee-extension torque to indicate lower extremity muscle strength.

Measures of upper extremity muscle strength were isometric shoulder adduction and handgrip. Between them, we selected the handgrip for the present analysis because the assessment of handgrip is easy, reliable, and inexpensive. Furthermore, there is strong evidence in the literature that handgrip is a strong predictor of disability and mortality (27, 28). We decided to include both measures of lower and upper extremity muscle strength because previous studies suggested that the rate of age-associated decline in muscle strength is quite different in these two anatomic regions (13). In fact, the correlation between handgrip and isometric strength of the lower extremity muscle groups was moderately high, ranging from 0.70 to 0.72. In previous studies, the intraclass correlation coefficients for duplicate measures of knee-extension isometric strength and handgrip strength were, respectively, 0.81 and 0.85 for interrater reliability and 0.79 and 0.98 for test-retest reliability (2, 25). Lower extremity muscle power was measured in a single leg extension movement, according to the method described by Bassey and Short (4). The value of the best performance obtained over eight repetitions on the right side and eight repetitions on the left side was used in the analysis. Using this method, Bassey and Short (4) reported that the coefficient of variation for retests obtained after 1 wk was 9.4%.

Crude values of muscle power were divided by individual body weights, and the resulting values were multiplied by the gender-specific average body weight for the study population. These weight-adjusted values of muscle power are expressed in a scale that is comparable with the values directly obtained from the power rig. In exploratory analyses, we also obtained a weight-adjusted measure of muscle power using a regression approach. However, because the correlation between the measures obtained with the two different types of adjustment was 0.98 in men and 0.94 in women, only the simpler measure that does not require a regression model was used in the analysis.

A lower leg peripheral quantitative computerized tomography (pQCT) was performed in all participants by means of a recent generation device (XCT 2000, Stratec, Pforzheim, Germany) to evaluate calf muscle cross-sectional area. Data presented here were derived from standard 2.5-mm-thick transverse scans obtained at 66% of the tibia length, proximal to the anatomic marker. Previous studies demonstrated that this is the region with the largest outer calf diameter, with little variability across individuals (29). The total dose of radiation administered to the participants was <1 mrem.

The cross-sectional images obtained from the pQCT were analyzed by using the BonAlyse software (BonAlyse, Jyvaskyla, Finland http://www.bonalyse.com). Different tissues in the analysis were separated according to different density thresholds: a density value of 35 mg/mm 3 was used to separate fat from muscle tissue, and 180 mg/mm 3 to separate muscle from bone tissue.

To assess walking ability, we collected both subjective and objective information. The subjective evaluation consisted of asking participants to estimate the maximum distance they could walk without difficulty. The interviewer provided examples of distances taken from real life. For instance, for the participants living in Greve in Chianti, 1 km was exemplified as the distance between the municipal building and the local hospital. Based on responses, we categorized participants into able or unable to walk 1 km without stopping, feeling fatigued, or developing symptoms.

To measure walking speed, two photocells connected to a recording chronometer were placed at the beginning and the end of a 4-m course established at the site clinic. Participants were instructed to stand with both feet touching the starting line and to begin walking at their usual pace after a verbal command. The time between the activation of the first and the second photocell was recorded. The average of two walks was used to compute a measure of walking speed. The coefficient of variation between duplicate trials was 5.2%, and only in 3.7% of the participants did the second measure differ by >20% from the first one. Use of aids (canes or walkers) was allowed for this test. The 4-m walk test has been used extensively in previous studies, and its concurrent and predictive validity and its sensitivity to change have been confirmed in large epidemiological studies (17, 18, 23, 24). For the purpose of this analysis, low walking speed was defined as walking slower than 0.8 m/s. After exclusion of those who where unable to walk, this value approximately identified the lowest quintile of the speed distribution in our population.

Statistical analysis. All analyses were performed separately in men and women. Continuous variables are reported as means ± SD and categorical values as a percentage. Anthropometric characteristics were compared between age groups by using ANOVA. By analogy with the standard criteria for the diagnosis of osteoporosis and in accordance with Baumgartner et al. (5) and Melton et al. (21), the definition of sarcopenia was based on the comparison between individual muscle parameters and average values calculated in healthy, young adults. For example, in men 20–29 yr old, knee extension torque was 802.0 ± 202.6 N/dm. Therefore, all male participants with knee extension torque <396.8 N/dm (802.0 - 2 ± 202.6) were considered to be affected by sarcopenia. Using an analogous method, we also identified participants who could be defined as sarcopenic based on their values of handgrip, lower extremity muscle power, and calf muscle cross-sectional area. Then we calculated the prevalence of sarcopenia for each one of these four possible definitions. To study the relationship between muscle parameters and performance in mobility tasks, we computed the percentage of participants walking slower than 0.8 m/s and of those unable to walk 1 km without difficulty. Percentages were compared by using age-adjusted tests for trend obtained by logistic regression models. Furthermore, we obtained receiver operator characteristic (ROC) curves for each muscle parameter using, for reference, the two above-mentioned definitions of poor mobility. In a ROC analysis, the area under the curve (AUC) estimated for each muscle parameter yields a discriminative value in the identification of a participant walking slower than 0.8 m/s and unable to walk for 1 km without difficulty. AUCs for the four muscle parameters were compared by using the De Long method implemented in the statistical software ACCUROC for Windows, version 2.5 (8, 19). From the ROC curves, we identified optimal diagnostic cut points as those yielding the best compromise between sensitivity and specificity in the identification of each of the two mobility outcomes. Finally, using logistic regression models, we obtained crude and age-adjusted odd ratios estimating the probability of poor mobility associated with having a specific muscle parameter below vs. above the optimal cutoff threshold.


Dietary Advice [ edit | edit source ]

The Society for Sarcopenia, Cachexia, and Wasting convened an expert panel to develop nutritional recommendations for sarcopenia prevention and management.This panel concluded that for preventing and treating this condition key components are

The greatest effects are observed when resistance training and high protein diets are combined and appear to act synergistically.

  • Specifically, consuming 20-35 grams of protein per meal is advised, as such amounts provide sufficient amino acid content to maximize MPS, thus minimizing age-related muscle loss. eg Chicken Breast: 23.1 g Protein Per 100 g, Canned Tuna: 23.6 g Protein Per 100 g, Cocoa: 20 g Protein Per 100 g, Cheddar Cheese: 24.9 g Protein Per 100 g.Beef Jerky: 33.2 g Protein Per 100 g. [35]
  • Additionally, patients with sarcopenia are recommended to consume 1.0 - 1.2 g/kg (body weight)/day

Is there a role for supplements? [ edit | edit source ]

There is some evidence suggesting that additional supplementation with the amino acid Leucine (or its metabolite HMB) could potentially increase the effects of resistance training to combat sarcopenia [36] [37] . A randomised double-blind study has found that supplementation with l-leucine can be used in the treatment of sarcopenia in older individuals [38] .


Watch the video: Muscle Fibers Explained - Muscle Contraction and Muscle Fiber Anatomy (June 2022).


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