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Improved strength prediction combining clinically available measures of skeletal muscle mass and quality.

ABSTRACT: BACKGROUND:Measures of skeletal muscle function decline at a faster rate with ageing than do indices of skeletal muscle mass. These observations have been attributed to age-related changes in muscle quality, another functional determinant separate from skeletal muscle mass. This study tested the hypothesis that improved predictions of skeletal muscle strength can be accomplished by combining clinically available measures of skeletal muscle mass and quality. METHODS:The participants included 146 healthy adult (age ? 18 years, range 18-77 years; X ± SD 47 ± 17 years and body mass index 16.5-51.8 kg/m2 ; 27.7 ± 6.2 kg/m2 ) men (n = 60) and women (n = 86) in whom skeletal muscle mass was estimated as appendicular lean soft tissue (LST) measured by dual-energy X-ray absorptiometry and skeletal muscle quality as bioimpedance analysis-derived phase angle and B-mode-evaluated echogenicity of mid-thigh skeletal muscle. Strength of the right leg and both arms was quantified as knee isokinetic extension and handgrip strength using dynamometers. The statistical significance of adding phase angle or echogenicity to strength prediction multiple regression models that included extremity-specific LST and other covariates (e.g. age and sex) was evaluated to test the study hypothesis. RESULTS:Right leg LST mass alone was significantly (P < 0.0001) correlated with isokinetic right leg strength (R2 = 0.57). The addition of segmental phase angle measured in the right leg at 50 kHz increased the R2 of this model to 0.66 (P < 0.0001); other phase angle frequencies (5 and 250 kHz) did not contribute significantly to these models. Results were similar for both right and left arm handgrip strength prediction models. Adding age and sex as model covariates increased the R2 values of these models further (e.g. right leg strength model R2 increased to 0.71), but phase angle continued to remain a significant (all P < 0.01) predictor of extremity strength. Similarly, when predicting isokinetic right leg strength, mid-thigh skeletal muscle echogenicity added significantly (P < 0.0001) to right leg LST, increasing R2 from 0.57 to 0.64; age was a significant (P < 0.0001) covariate in this model, increasing R2 further to 0.68. CONCLUSIONS:The hypothesis of the current study was confirmed, strongly supporting and extending earlier reports by quantifying the combined independent effects of skeletal muscle mass and quality on lower-body and upper-body measures of strength. These observations provide a clinically available method for future research aimed at optimizing sarcopenia and frailty risk prediction models.

SUBMITTER: Bourgeois B

PROVIDER: S-EPMC6438415 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Improved strength prediction combining clinically available measures of skeletal muscle mass and quality.

Bourgeois Brianna B Fan Bo B Johannsen Neil N Gonzalez Maria Cristina MC Ng Bennett K BK Sommer Markus J MJ Shepherd John A JA Heymsfield Steven B SB

Journal of cachexia, sarcopenia and muscle 20181029 1

<h4>Background</h4>Measures of skeletal muscle function decline at a faster rate with ageing than do indices of skeletal muscle mass. These observations have been attributed to age-related changes in muscle quality, another functional determinant separate from skeletal muscle mass. This study tested the hypothesis that improved predictions of skeletal muscle strength can be accomplished by combining clinically available measures of skeletal muscle mass and quality.<h4>Methods</h4>The participant ...[more]

PMID: 30371008

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Project description:BackgroundSkeletal muscle is a large and clinically relevant body component that has been difficult and impractical to quantify outside of specialized facilities. Advances in smartphone technology now provide the opportunity to quantify multiple body surface dimensions such as circumferences, lengths, surface areas, and volumes.ObjectivesThis study aimed to test the hypothesis that anthropometric body measurements acquired with a smartphone application can be used to accurately estimate an adult's level of muscularity.MethodsAppendicular lean mass (ALM) measured by DXA served as the reference for muscularity in a sample of 322 adults. Participants also had digital anthropometric dimensions (circumferences, lengths, and regional and total body surface areas and volumes) quantified with a 20-camera 3D imaging system. Least absolute shrinkage and selection operator (LASSO) regression procedures were used to develop the ALM prediction equations in a portion of the sample, and these models were tested in the remainder of the sample. Then, the accuracy of the prediction models was cross-validated in a second independent sample of 53 adults who underwent ALM estimation by DXA and the same digital anthropometric estimates acquired with a smartphone application.ResultsLASSO models included multiple significant demographic and 3D digital anthropometric predictor variables. Evaluation of the models in the testing sample indicated respective RMSEs in women and men of 1.56 kg and 1.53 kg and R2's of 0.74 and 0.90, respectively. Cross-validation of the LASSO models in the smartphone application group yielded RMSEs in women and men of 1.78 kg and 1.50 kg and R2's of 0.79 and 0.95; no significant differences or bias between measured and predicted ALM values were observed.ConclusionsSmartphone image capture capabilities combined with device software applications can now provide accurate renditions of the adult muscularity phenotype outside of specialized laboratory facilities. Am J Clin Nutr 2023;x:xx. This trial was registered at clinicaltrials.gov as NCT03637855 (https://clinicaltrials.gov/ct2/show/NCT03637855), NCT05217524 (https://clinicaltrials.gov/ct2/show/NCT05217524), and NCT03771417 (https://clinicaltrials.gov/ct2/show/NCT03771417).

Project description:BackgroundGrowth differentiation factor 11 (GDF11) is a member of the transforming growth factor β superfamily. The GDF11 propeptide, which is derived from the GDF11 precursor protein, blocks the activity of GDF11 and its homolog, myostatin, which are both potent inhibitors of muscle growth. Thus, treatment with GDF11 propeptide may be a potential therapeutic strategy for diseases associated with muscle atrophy like sarcopenia and the muscular dystrophies. Here, we evaluate the impact of GDF11 propeptide-Fc (GDF11PRO-Fc) gene delivery on skeletal muscle in normal and dystrophic adult mice.MethodsA pull-down assay was used to obtain physical confirmation of a protein-protein interaction between GDF11PRO-Fc and GDF11 or myostatin. Next, differentiated C2C12 myotubes were treated with AAV6-GDF11PRO-Fc and challenged with GDF11 or myostatin to determine if GDF11PRO-Fc could block GDF11/myostatin-induced myotube atrophy. Localized expression of GDF11PRO-Fc was evaluated via a unilateral intramuscular injection of AAV9-GDF11PRO-Fc into the hindlimb of C57BL/6J mice. In mdx mice, intravenous injection of AAV9-GDF11PRO-Fc was used to achieve systemic expression. The impact of GDF11PRO-Fc on muscle mass, function, and pathological features were assessed.ResultsGDF11PRO-Fc was observed to bind both GDF11 and myostatin. In C2C12 myotubes, expression of GDF11PRO-Fc was able to mitigate GDF11/myostatin-induced atrophy. Following intramuscular injection in C57BL/6J mice, increased grip strength and localized muscle hypertrophy were observed in the injected hindlimb after 10 weeks. In mdx mice, systemic expression of GDF11PRO-Fc resulted in skeletal muscle hypertrophy without a significant change in cardiac mass after 12 weeks. In addition, grip strength and rotarod latency time were improved. Intramuscular fibrosis was also reduced in treated mdx mice; however, there was no change seen in central nucleation, membrane permeability to serum IgG or serum creatine kinase levels.ConclusionsGDF11PRO-Fc induces skeletal muscle hypertrophy and improvements in muscle strength via inhibition of GDF11/myostatin signaling. However, GDF11PRO-Fc does not significantly improve the dystrophic pathology in mdx mice.

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Improved strength prediction combining clinically available measures of skeletal muscle mass and quality.

Publications

Improved strength prediction combining clinically available measures of skeletal muscle mass and quality.

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