McArdle disease (or glycogen storage disease Type V) is an inherited metabolic disorder caused by deficiency of myophosphorylase, the enzyme that catalyzes the first step of glycogen breakdown in muscle tissue (1). The disorder is arguably the paradigm of exercise intolerance (2) and manifests functionally as acute “crises” of fatigue, myalgia, and muscle contractures (especially during the first minutes of exercise) that are often accompanied by myoglobinuria (dark urine) resulting from skeletal muscle damage, with the latter typically reflected in elevated serum levels of creatine kinase (CK). For these reasons, physical activity (PA) has long been contraindicated in these patients. That said, an inactive lifestyle further exacerbates the exercise intolerance of patients with McArdle disease (3) and could potentially increase the risk of other comorbidities associated with physical inactivity. Accordingly, an effective intervention for alleviating exercise intolerance is regular, light-moderate “aerobic” exercise (e.g., cycling or brisk walking) (4–7) and also supervised muscle resistance (“strength”) training, with carbohydrate ingestion before each session (8).
Because PA and muscular developments are major determinants of bone mass (BM) acquisition (9), we thought that it would be worthwhile to assess the lean mass (LM) and the BM of McArdle patients, and to ascertain to what extent these two important variables are associated with PA levels. To the best of our knowledge, aside from our previous preliminary, low sample-sized study reporting LM in McArdle disease (8), no study has assessed LM and BM objectively using dual-energy x-ray absorptiometry (DXA). The present study was therefore designed 1) to determine LM and BM in McArdle patients and compare the results with those of healthy subjects stratified by age and sex, and 2) to examine whether an active lifestyle contributes to increase LM and thus improve bone health in these patients. Our hypothesis was that LM and BM would be lower in patients with McArdle disease than in healthy individuals, and an active lifestyle could contribute to reverse these features.
MATERIALS AND METHODS
Subjects and Procedure
We followed a case–control, cross-sectional design. The study protocol was approved by the ethics committee of the Research Institute of the Hospital 12 de Octubre (Madrid, Spain; reference no. 16/081) and adhered to the tenets of the Declaration of Helsinki 1961 (fifth revision, Edinburgh, 2000). All participants were informed of the aims and procedures of the study, as well as the possible risks and benefits. Patients were recruited for the study if they met the following criteria: (i) genetic diagnosis of McArdle disease, that is, identification of the two mutant alleles in the PYGM gene encoding myophosphorylase (or, in those in whom only one mutant allele has been identified to date, biopsy diagnosis or alternatively laboratory confirmation of the “pathognomonic” second wind phenomenon) (1); (ii) age 16–55 yr; and (iii) having no condition contraindicating DXA (e.g., pregnancy). A total of 36 patients with McArdle disease (17 men and 19 women) who met all inclusion criteria and provided informed consent were evaluated during the period June 2015–October 2016 (see flow diagram, Fig. 1).
Age- and sex-matched healthy subjects with previous DXA data collected by us using the same instrument (see hereinafter) during the period 2012–2016, such as to meet a patient–control ratio as close as possible to ~1:3 (i.e., n = 103 individuals (49 men and 54 women)), were contacted and agreed to serve as controls for the current study. Written informed consent was obtained from each participant.
Sample size was determined from pilot data by an a priori power analysis for ANCOVA (α = 0.05, 1 − β = 0.90, fz = 0.80, 2 groups and 3 covariates) on the basis of expected differences in bone mineral density (BMD) between McArdle patients and controls. Thus, a minimum of 12 subjects per group was needed to detect significant differences in the contrast of the null hypothesis H 0: μ1 = μ2.
The following measurements were also obtained during the same week of DXA assessment: anthropometric (patients and controls), serum CK (patients), and PA levels (patients).
Mutant PYGM alleles were identified in muscle or blood samples using SNaPShot mini-sequencing (ThermoFisher) or polymerase chain reaction and restriction fragment length polymorphism methods (10), followed by Sanger sequencing of the entire coding region and intron/exon boundaries of the myophosphorylase PYGM gene (11). Alternatively, we used a next-generation sequencing-customized gene panel on a PGM-IonTorrent platform (ThermoFisher), consisting of 35 genes (including PYGM) associated with metabolic myopathies. In some cases, analysis of muscle or blood mRNA/cDNA was needed to demonstrate the molecular pathogenicity of a presumed mutant allele, particularly when an alteration of the splicing mechanism was suspected (12,13).
Anthropometric measurements were obtained from each subject immediately before DXA assessment. Height was measured in the upright position, in underwear, and barefoot on a stadiometer with a precision of 1 mm (Seca 711, Hamburg, Germany). Body mass was determined with the same requirements using a balance with a 100-g precision (Seca 711). Body mass index (BMI) was calculated as body mass divided by height squared (kg·m−2).
Body Composition: LM and BM
Total and regional body composition and BM were assessed in all the study participants using the same DXA instrument (Hologic QDR Discovery, Bedford, MA) in the Sports Science Department of the Universidad de Castilla-La Mancha (Toledo, Spain). The instrument was calibrated using a lumbar spine phantom following the Hologic guidelines. All scans were analyzed using Physician’s Viewer, APEX System Software version 3.1.2. (Bedford, MA). LM (kg), bone mineral content (BMC, g), and BMD (g·cm−2) were calculated from total and regional analysis of the whole-body scan. Whole-body scans were submitted to a regional analysis to determine the composition of the arm, leg, and trunk regions. The arm region included the hand, forearm, and arm and was separated from the trunk by an inclined line crossing the scapulohumeral joint, such that the humeral head was located in the arm region. The leg region included the foot, the lower leg, and the upper leg. It was separated from the trunk by an inclined line passing just below the pelvis, which crossed the neck of the femur. The trunk region included the rest of the body excluding the arms, legs, and head regions. The head region comprised all skeletal parts of the skull and cervical vertebra above a horizontal line passing just below the jawbone. BMC and BMD were also reported for the lumbar spine (L1–L4) and proximal region of the femur (total hip, greater trochanter, intertrochanter, Ward triangle, and femoral neck). Scans were made with subjects in the supine position, wearing light clothing with no metal and no shoes or jewelry.
PA was assessed using the Spanish version of the International Physical Activity Questionnaire (IPAQ; long version) (14). The methods used to score the long IPAQ can be found at the IPAQ Web site (www.ipaq.ki.se). The IPAQ has been validated against accelerometry and is widely used to evaluate PA patterns (15,16). It has been shown to have satisfactory psychometric properties (15,17) and is suitable for patient populations (15) because it is divided in specific parts, with each addressing the types of PA that patients with chronic diseases are most likely to perform (18).
The IPAQ was used to categorize patients into two subgroups according to their leisure time PA levels in the previous 7 d. Accordingly, participants were categorized as “active” (n = 23) if they completed ≥600 metabolic equivalents MET-minutes per week (where 1 MET is the resting energy expenditure, equivalent to ~3.5 mL O2·kg−1·min−1, and 600 MET·min·wk−1 reflects the minimum of 150 min·wk−1 of moderate-vigorous PA recommended by the World Health Organization for all adults (19). Participants were considered “inactive” (n = 13) if their PA was below this threshold (20,21). The IPAQ was also used to report the frequency, intensity, and duration of occupational, transport, home, and leisure/sport PA that the patients had performed in the previous 7 d.
Statistical analyses were performed using the IBM SPSS Statistics package version 24 (SPSS, Inc., Chicago, IL). Differences in DXA-derived variables between groups and also between active and inactive patient subgroups in LM, BM, and PA were determined using Student t-test. An ANCOVA was used to test for differences in LM and BM between patients and controls using body mass, height, age, age at symptoms onset, and number of episodes of rhabdomyolysis in the previous year (as reported by number of episodes of myoglobinuria) as covariates, with Bonferroni post hoc tests. Differences between men and women related to the percentage of body fat were also studied; nevertheless, both were categorized in the overweight range (22) (i.e., 24.5% ± 9.3% body fat for men and 32.8% ± 6.0% for women). Given that both had the same categorization, the influence of fat mass on BM or LM would be very similar, and as such, fat mass was not included in the analyses. Statistical size and power were reported using Cohen d test for comparisons of equal sample size and Hedge g test for comparisons of unequal sample size. In addition, bivariate analysis was applied to identify the association between LM and BM. The level of statistical significance was set at P ≤ 0.05. Unless otherwise stated, results are reported as mean ± SEM.
All patients had previously described pathogenic mutations (that are known to cause McArdle disease) in both alleles of the PYGM gene, except for one case in which only one mutant allele was identified (see Table, Supplemental Digital Content 1, PYGM mutations identified in the study patients, http://links.lww.com/MSS/B25). However, this patient showed the pathognomonic “second wind” phenomenon in our laboratory. Table 1 summarizes anthropometric and descriptive data for the patient and control groups. Whereas both groups had similar age, body mass, and BMI, the control group had a lower percentage of body fat compared with the patient group (P < 0.05).
Table 2 summarizes total and regional LM values after controlling for the effect of body mass, height, age, age at symptoms onset, and number of episodes of rhabdomyolysis in the previous year. Whole-body and appendicular LM was significantly greater in patients than in controls (from 5.2% to 9.9%; except for leg LM, all P < 0.05). Effect sizes of these differences were large for the trunk (Hedge g = 1.18) and medium for the whole body and arms (0.70 and 0.67, respectively). The comparison between controls and nonactive patients revealed a similar trend, with large effect sizes for the whole body, trunk, and arms (Hedge g = 1.10–1.62; 9.4%–17.9% of difference; P < 0.05) and a small effect size and difference for the legs (Hedge g = 0.26% and 2.9%; P > 0.05). By contrast, significant differences between controls and active patients were found only for the trunk LM (Hedge g = 0.89% and 6.9%; P < 0.05), with small effect sizes in the whole body, arms, and legs (Hedge g = 0.16–0.43). Finally, the comparison between active and nonactive patients revealed significant differences in the whole-body and trunk LM (Cohen d = 0.87 and 0.89; 6.2% of difference; P < 0.05), and medium effect sizes for LM of the arms and legs (0.72 and 0.51; 6.7% and −1.8% of difference, respectively).
Table 3 and Figure 2 show BMC and BMD values after controlling for the effect of body mass, height, age, age at symptoms onset, and number of episodes of rhabdomyolysis in the previous year. Significant differences were found between patients and controls in all the bone-related variables, with large effect sizes in the BMC of the pelvis and legs (Hedge g = 1.11 and 1.10; 24.0% and 12.2%, respectively) and in the BMD of the whole body, pelvis, and legs (Hedge g = 0.84–1.29; 7.5%–9.7%). However, when comparing BMD between controls and active patients, these differences only remained significant in the whole body, arms, and legs (Hedge g = 0.95, 0.53, and 0.99; 7.7%, 6.3%, and 8.1%, respectively) and were not observed in the pelvis, Ward triangle, intertrochanteric zone, trochanter, femoral neck, and lumbar spine. BMD values were on average 7.6% higher in controls (Hedge g = 0.26–1.07; 5.6%–9.7%) than in patients, and these differences were even greater (Hedge g = 0.23–1.51; mean difference of 10.1%; range, 5.8%–12.8%) when controls were compared with active patients. These differences were significant for all BMD variables except for Ward triangle, femoral neck, and lumbar spine. BMC variables showed a similar trend with, on average, 13% greater values in controls than in patients (Hedge g = 0.13–0.68; range, 3.9%–24%), with a 17.1% mean difference between controls and nonactive patients (Hedge g = 0.16–1.42; range, 5.2%–29.2%) and smaller differences in BMC values between controls and active patients (Hedge g = 0.11–1.05; range, 3.3%–20.9%; mean difference of 11.2%). A representative image of a DXA scan comparing the different groups is shown in Supplemental Digital Content 2 (see Figure, Supplemental Digital Content 2, Representative DXA image comparison between the different groups, http://links.lww.com/MSS/B26). No significant correlations were found between BMC, BMD, and LM with age at symptoms onset or frequency of rhabdomyolysis.
Association between whole-body LM and BM
In the patient group, the strongest associations were found between whole-body LM and either whole-body BMD (r = 0.45, P < 0.01; Fig. 3A) or leg BMD (r = 0.74, P < 0.001; Fig. 3B). These associations remained in the control group (r = 0.78 (P < 0.001) and r = 0.54 (P < 0.001), respectively).
The following significant differences were found between active (n = 23) and nonactive patients (n = 13), with greater values in the former (all P < 0.01): “walk” category (1948 ± 468 vs 482 ± 115 MET·min·wk−1), moderate-vigorous PA (4290 ± 903 vs 1578 ± 389 MET·min·wk−1), “leisure time” PA (2031 ± 422 vs 212 ± 65 MET·min·wk−1), and “total time” PA (5465 ± 1536 vs 2492 ± 769 MET·min·wk−1).
Sex comparisons within the patient group are included as Table, Supplemental Digital Content 3, soft tissue composition from the total and regional body in McArdle patients by sex, http://links.lww.com/MSS/B27, and Table, Supplemental Digital Content 4, BMC and BMD, from the whole-body, femoral, and lumbar scans in the McArdle patients by sex, http://links.lww.com/MSS/B28. Men had greater LM values than did women after controlling for the effect of body mass, height, and age. Likewise, men had significantly higher BMC and BMD than did women at all sites except for the proximal femur (BMD, P = 0.08).
This study examined the effects of McArdle disease on LM and BM, in particular in relation to patients’ lifestyle (active vs inactive). Our main novel finding is that LM and BM were significantly lower in McArdle patients than in age- and sex-matched control subjects. However, active patients could mitigate the losses in LM and BM associated with an inactive lifestyle through the maintenance of their LM component, which remained similar to that of healthy controls.
An inactive lifestyle may attenuate the accrual of BM during growth, leading to a lower peak BM. The latter is usually attained in early adulthood both in men and in women, and a high peak BM is crucial to prevent osteoporotic fractures later in life (23). In our study, whole-body, spine, and femoral neck BMC values in McArdle patients were 12%, 4%, and 12% lower and BMD values were 9%, 7% and 6% lower, respectively, than in age- and sex-matched healthy peers. This indicates that, on average, the BMC and BMD of McArdle patients are low from a young adult age (mean age of the patients was 33 ± 15 yr). Indeed, when we compare our patients’ data with those of an elderly Spanish population (≥65 yr) assessed by us using the same instrument (unpublished data), we find that patients’ BMD values are only 4% and 5% higher for the whole body and spine, respectively. Thus, BMC and BMD values from young adult McArdle patients are clearly below the established reference values for their age (24), indicating that they are at high risk for bone diseases such as osteoporosis or osteopenia later in life. In this regard, a low BMD and a high incidence of fractures have been observed in other myopathies (25). Adult patients with Pompe disease or glycogenosis Type II also seem to have lower-than-normal BMD values, especially for the femoral neck (26). Furthermore, the McArdle patients in the present study had BMD values 5%, 17%, and 4% lower in the whole-body, spine, and femoral neck areas, respectively, when compared with the values previously reported in adult Pompe patients (27). The whole-body BMD values of our patients were similar to those previously reported in other adult patients with glycogenosis Type I and Type III (28).
There is a dearth of knowledge about the effects that regular PA may have on bone content and density in McArdle patients, a group that has been traditionally advised by physicians to refrain from exercise. Notwithstanding that BMC and BMD levels were significantly lower in our McArdle patients than in healthy subjects in many of the whole-body areas, an active lifestyle had a positive effect in the femoral regions. Thus, active patients had similar proximal femur, trochanter, and intertrochanteric BMD values to their healthy peers, whereas nonactive patients showed significantly lower values in these areas.
Although this positive exercise effect does not seem to be present in the spine, some studies have found similar results in other glycogenoses, showing that muscle strength and weight bearing positively affect BMD, which is supported by the greater involvement of the femoral neck over the lumbar spine (26). Whereas trabecular bone (e.g., lumbar spine) is mainly influenced by general systemic factors such as hormone status (29), cortical bone (at the femur) is more subject to regional, mechanical influences, such as gravity, LM, and muscle strength (29). For these reasons, PA is essential to increase BMD not only in healthy individuals but also in individuals with various pathological conditions (30).
Regular PA has an important osteogenic effect (31,32), and land-based weight-bearing activities increase BM more than do non–weight-bearing activities (e.g., swimming) in weight-loaded skeletal regions (33,34). Although weight-supported land-based activities associated with relatively low-magnitude ground-reaction forces such as brisk walking do not always have a substantial osteogenic effect (35), McArdle patients can safely perform this type of exercise and obtain, at least partially, indirect benefits for their bone health through the increase of muscle mass.
Since skeletal muscle is the primary component of LM, participation in sport and PA could have not only a direct osteogenic effect but also an indirect effect by increasing muscle mass and hence the tensions generated on bones during prepubertal years (36). The muscle–bone relationship is presumably explained by the mechanostat theory, which proposes that bone strength is regulated by modeling and remodeling processes depending on the forces acting on the bones (37,38); bigger muscles exert higher tensile forces on the bones they attach to. Moreover, a close relationship between whole-body LM and whole-body and leg BM was found in McArdle patients, suggesting that a higher whole-body LM will likely result in a higher osteogenic effect. Interestingly, a recent preliminary report from our laboratory indicated the feasibility and safety of an 8-wk supervised, moderate-intensity resistance (weight lifting) training program in McArdle patients (8). This is an encouraging finding given the greater potential of this exercise modality to increase muscle mass and subsequently BM (39). Indeed, despite its short duration, the resistance program resulted in a total LM gain of nearly 1 kg in the studied McArdle patients.
Our McArdle patient group had 5% lower whole-body LM than did the control group. However, the subgroup of active patients presented similar values of whole-body LM to the control group, and higher values than their sedentary patient peers. The low values of whole-body LM of the nonactive McArdle patients were similar to those previously found in Pompe patients (40). Thus, in contrast to Pompe or nonactive McArdle patients, active McArdle patients can reach normal values of total LM.
Our study is not without limitations. We did not report dietary information, although several diet factors, especially calcium and vitamin D intake, have a potentially important effect on BM acquisition. It would have also been useful to analyze blood variables that are known to be associated with BM (e.g., levels of parathyroid hormone or vitamin D). Furthermore, the self-reported nature of the PA questionnaires makes these tools less accurate than more objective methods for PA assessment, notably triaxial accelerometry. Nonetheless, a main strength of our study stems from the fact that it is the first to objectively assess a crucial health phenotype, body composition, in a relatively large cohort of McArdle patients using the gold-standard DXA method. Moreover, when considering that McArdle disease is a rare disease (a prevalence of ∼1/167,000 people (1), our study was well powered, with the sample size of the patient group sufficiently large to detect significant changes in bone variables, which allows for extrapolation of our data to other patients with the same disease.
In conclusion, we have identified poor BM starting in early adulthood as a previously undescribed condition associated with McArdle disease. Although both active and nonactive McArdle patients have compromised bone health, there seems to be a consistent association between higher PA levels and a healthier body composition phenotype (i.e., higher LM and BM) among young adult patients with McArdle disease, with active patients showing higher LM than their sedentary patient peers. Because there will likely be no genetic cure for McArdle disease in the foreseeable future, our study provides an additional rationale to support implementation of PA intervention in these patients. Future research might explore whether specific dietary interventions (e.g., calcium supplement intake) could maximize the benefits of PA on the bone health of McArdle patients and what type of safe, feasible PA modality is most suitable to enhance the muscle and BM of these patients.
This study was funded by the Cátedra Real Madrid–Universidad Europea de Madrid (P2016/RM25), Fondo de Investigaciones Sanitarias (A. L., PI15/00558; G. N. G., PI15/01756 and CP14/00032, J. A., PI14/00903), the Biomedical Research Networking Centre on Frailty and Healthy Aging (CIBERFES), and FEDER funds from the European Union (CB16/10/00477). Irene Rodríguez Gómez received a PhD grant from the Universidad de Castilla–La Mancha “Contratos predoctorales para la formación de personal investigador en el marco del Plan Propio de I + D + i, cofinanciados por el Fondo Social Europeo” (2014/10340).
The authors report no conflict of interest and they affirm that the results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The results of the present study do not constitute endorsement by the American College of Sports Medicine.
1. Lucia A, Ruiz JR, Santalla A, et al. Genotypic and phenotypic features of McArdle disease: insights from the Spanish national registry. J Neurol Neurosurg Psychiatry
2. Di Mauro S. Muscle glycogenoses: an overview. Acta Myol
3. Lucia A, Quinlivan R, Wakelin A, Martin MA, Andreu AL. The ‘McArdle paradox’: exercise
is a good advice for the exercise
intolerant. Br J Sports Med
4. Maté-Munoz JL, Moran M, Pérez M, et al. Favorable responses to acute and chronic exercise
in McArdle patients. Clin J Sport Med
5. Haller RG, Wyrick P, Taivassalo T, Vissing J. Aerobic conditioning: an effective therapy in McArdle’s disease. Ann Neurol
6. Perez M, Foster C, Gonzalez-Freire M, Arenas J, Lucia A. One-year follow-up in a child with McArdle disease: exercise
is medicine. Pediatr Neurol
7. Quinlivan R, Vissing J, Hilton-Jones D, Buckley J. Physical training for McArdle disease. Cochrane Database Syst Rev
8. Santalla A, Munguía-Izquierdo D, Brea-Alejo L, et al. Feasibility of resistance training in adult McArdle patients: clinical outcomes and muscle strength and mass benefits. Front Aging Neurosci
9. Vicente-Rodriguez G, Ara I, Pérez-Gómez J, Dorado C, Calbet JA. Muscular development and physical activity
as major determinants of femoral bone mass acquisition during growth. Br J Sports Med
10. Rubio JC, Garcia-Consuegra I, Nogales-Gadea G, et al. A proposed molecular diagnostic flowchart for myophosphorylase deficiency (McArdle disease) in blood samples from Spanish patients. Hum Mutat
11. Kubisch C, Wicklein EM, Jentsch TJ. Molecular diagnosis of McArdle disease: revised genomic structure of the myophosphorylase gene and identification of a novel mutation. Hum Mutat
12. García-Consuegra I, Rubio JC, Nogales-Gadea G, et al. Novel mutations in patients with McArdle disease by analysis of skeletal muscle mRNA. J Med Genet
13. Ballester-Lopez A, Blazquez A, Rubio JC, et al. Taking advantage of an old concept, “illegitimate transcription,” for a proposed novel method of genetic diagnosis of McArdle disease. Neuromuscul Disord
14. Martinez SM, Ainsworth BE, Elder JP. A review of physical activity
measures used among US Latinos: guidelines for developing culturally appropriate measures. Ann Behav Med
15. Craig CL, Marshall AL, Sjostrom M, et al. International Physical Activity
Questionnaire: 12-country reliability and validity. Med Sci Sports Exerc
16. Intitute K. IPAQ: International Physical Activity
Questionnaire 2010. [cited 2017 April 17]. Available at: http://www.ipaq.ki.se/
17. van Poppel MN, Chinapaw MJ, Mokkink LB, Van Mechelen W, Terwee CB. Physical activity
questionnaires for adults: a systematic review of measurement properties. Sports Med
18. Metsios GS, Stavropoulos-Kalinoglou A, Treharne GJ, et al. Disease activity and low physical activity
associate with number of hospital admissions and length of hospitalisation in patients with rheumatoid arthritis. Arthritis Res Ther
19. World Health Organization. Global Recommendations on Physical Activity for Health
. Geneva: WHO; 2010.
20. Brown WJ, Bauman AE. Comparison of estimates of population levels of physical activity
using two measures. Aust N Z J Public Health
21. Munguia-Izquierdo D, Santalla A, Lucia A. Cardiorespiratory fitness, physical activity
, and quality of life in patients with McArdle disease. Med Sci Sports Exerc
22. Lohman TG. Advances in Body Composition Assessment
. Champaign (IL): Human Kinetics Publishers; 1992.
23. Rizzoli R, Bianchi ML, Garabédian M, McKay HA, Moreno LA. Maximizing bone mineral mass gain during growth for the prevention of fractures in the adolescents and the elderly. Bone
24. Yang S, Shen X. Association and relative importance of multiple obesity measures with bone mineral density: the National Health and Nutrition Examination Survey 2005–2006. Arch Osteoporos
25. Bertoldo F, Zappini F, Brigo M, et al. Prevalence of asymptomatic vertebral fractures in late-onset Pompe disease. J Clin Endocrinol Metab
26. van den Berg LE, Zandbergen AA, van Capelle CI, et al. Low bone mass in Pompe disease: muscular strength as a predictor of bone mineral density. Bone
27. Papadimas GK, Terzis G, Methenitis S, et al. Body composition analysis in late-onset Pompe disease. Mol Genet Metab
28. Melis D, Rossi A, Pivonello R, et al. Reduced bone mineral density in glycogen storage disease type III: evidence for a possible connection between metabolic imbalance and bone homeostasis. Bone
29. Snow-Harter C, Bouxsein M, Lewis B, Charette S, Weinstein P, Marcus R. Muscle strength as a predictor of bone mineral density in young women. J Bone Miner Res
30. Bianchi ML. Osteoporosis in children and adolescents. Bone
31. Nickols-Richardson SM, Modlesky CM, O’Connor PJ, Lewis RD. Premenarcheal gymnasts possess higher bone mineral density than controls. Med Sci Sports Exerc
32. Vicente-Rodriguez G, Jimenez-Ramirez J, Ara I, Serrano-Sanchez J, Dorado C, Calbet J. Enhanced bone mass and physical fitness in prepubescent footballers. Bone
33. Calbet JA, Dorado C, Diaz-Herrera P, Rodriguez-Rodriguez L. High femoral bone mineral content and density in male football (soccer) players. Med Sci Sports Exerc
34. Nordström P, Pettersson U, Lorentzon R. Type of physical activity
, muscle strength, and pubertal stage as determinants of bone mineral density and bone area in adolescent boys. J Bone Miner Res
35. Dorado C, Moysi JS, Vicente G, Serrano J, Rodriguez L, Calbet J. Bone mass, bone mineral density and muscle mass in professional golfers. J Sports Sci
36. Vicente-Rodríguez G. How does exercise
affect bone development during growth? Sports Med
37. Rauch F, Bailey DA, Baxter-Jones A, Mirwald R, Faulkner R. The ‘muscle-bone unit’ during the pubertal growth spurt. Bone
38. Schoenau E, Frost H. The “muscle–bone unit” in children and adolescents. Calcif Tissue Int
39. Castrogiovanni P, Trovato FM, Szychlinska MA, Nsir H, Imbesi R, Musumeci G. The importance of physical activity
in osteoporosis. From the molecular pathways to the clinical evidence. Histol Histopathol
40. Umpleby AM, Wiles CM, Trend P, et al. Protein turnover in acid maltase deficiency before and after treatment with a high protein diet. J Neurol Neurosurg Psychiatry
DXA; BONE–MUSCLE INTERACTIONS; EXERCISE; PHYSICAL ACTIVITY
Supplemental Digital Content
© 2018 American College of Sports Medicine