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Altered Satellite Cell Responsiveness and Denervation Implicated in Progression of Rotator-Cuff Injury

View Article: PubMed Central - PubMed

ABSTRACT

Background: Rotator-cuff injury (RCI) is common and painful; even after surgery, joint stability and function may not recover. Relative contributions to atrophy from disuse, fibrosis, denervation, and satellite-cell responsiveness to activating stimuli are not known.

Methods and findings: Potential contributions of denervation and disrupted satellite cell responses to growth signals were examined in supraspinatus (SS) and control (ipsilateral deltoid) muscles biopsied from participants with RCI (N = 27). Biopsies were prepared for explant culture (to study satellite cell activity), immunostained to localize Pax7, BrdU, and Semaphorin 3A in satellite cells, sectioning to study blood vessel density, and western blotting to measure the fetal (γ) subunit of acetylcholine receptor (γ-AchR). Principal component analysis (PCA) for 35 parameters extracted components identified variables that contributed most to variability in the dataset. γ-AchR was higher in SS than control, indicating denervation. Satellite cells in SS had a low baseline level of activity (Pax7+ cells labelled in S-phase) versus control; only satellite cells in SS showed increased proliferative activity after nitric oxide-donor treatment. Interestingly, satellite cell localization of Semaphorin 3A, a neuro-chemorepellent, was greater in SS (consistent with fiber denervation) than control muscle at baseline. PCAs extracted components including fiber atrophy, satellite cell activity, fibrosis, atrogin-1, smoking status, vascular density, γAchR, and the time between symptoms and surgery. Use of deltoid as a control for SS was supported by PCA findings since “muscle” was not extracted as a variable in the first two principal components. SS muscle in RCI is therefore atrophic, denervated, and fibrotic, and has satellite cells that respond to activating stimuli.

Conclusions: Since SS satellite cells can be activated in culture, a NO-donor drug combined with stretching could promote muscle growth and improve functional outcome after RCI. PCAs suggest indices including satellite cell responsiveness, atrogin-1, atrophy, and innervation may predict surgical outcome.

No MeSH data available.


Related in: MedlinePlus

Principal component analysis (PCA) biplots.Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for each of the variables (for 27 participants) included in the particular PCA. Vectors project onto the 3 axes (dimensions) of the principal components (PCs) 1 (x-axis), 2 (y-axis), and 3 (z-axis, positive is upward, perpendicular to the page). A. PCA-1, on the full dataset (N = 23 variables). B. PCA-2, Supraspinatus variables only (N = 16). C. PCA-3, variables of interest from previous comparisons, including “muscle” as a variable (N = 15 variables). Variables that loaded onto PC3 (as shown in Tables 1–3) are indicated with an asterisk (*) to emphasize that the correlation vector projects upward, perpendicular to PC1 and PC2 axes. Variable labels on the vectors are abbreviated as follows: C (control muscle), SS (Supraspinatus muscle), BMI (body mass index), Sx-to-Surg (weeks from symptom onset to surgery), diam (fiber diameter), SS:C diam (ratio of fiber diameter in SS/C), SC-base (baseline SC activation in explant cultures), SC-ISDN (SC activation in explants cultured with ISDN), dystr (expression of dystrophin protein relative to β-actin), mmp9 (level of matrix metalloproteinase 9 protein relative to β-actin), logRed (log-transformation of average maximum Sirius Red staining), γ:ε (γ:ε ratio of AchR subunits), γ (expression of the γ-subunit of AchR protein relative to β-actin), and BvD (vascular density).
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pone.0162494.g004: Principal component analysis (PCA) biplots.Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for each of the variables (for 27 participants) included in the particular PCA. Vectors project onto the 3 axes (dimensions) of the principal components (PCs) 1 (x-axis), 2 (y-axis), and 3 (z-axis, positive is upward, perpendicular to the page). A. PCA-1, on the full dataset (N = 23 variables). B. PCA-2, Supraspinatus variables only (N = 16). C. PCA-3, variables of interest from previous comparisons, including “muscle” as a variable (N = 15 variables). Variables that loaded onto PC3 (as shown in Tables 1–3) are indicated with an asterisk (*) to emphasize that the correlation vector projects upward, perpendicular to PC1 and PC2 axes. Variable labels on the vectors are abbreviated as follows: C (control muscle), SS (Supraspinatus muscle), BMI (body mass index), Sx-to-Surg (weeks from symptom onset to surgery), diam (fiber diameter), SS:C diam (ratio of fiber diameter in SS/C), SC-base (baseline SC activation in explant cultures), SC-ISDN (SC activation in explants cultured with ISDN), dystr (expression of dystrophin protein relative to β-actin), mmp9 (level of matrix metalloproteinase 9 protein relative to β-actin), logRed (log-transformation of average maximum Sirius Red staining), γ:ε (γ:ε ratio of AchR subunits), γ (expression of the γ-subunit of AchR protein relative to β-actin), and BvD (vascular density).

Mentions: PCA was used to reduce the dimensionality of the multivariate dataset for the current study, in which a total of 35 parameters were assessed (whether or not individual statistical analyses, above, were significant). The large dataset was reduced to data in three dimensions (principal components, PCs) which helps visualize statistical findings from an analysis of many variables together. Use of PCA can therefore be preferable to examining many variables using multiple pair-wise correlations. Fig 4 shows plots of the results of PCAs that were run on the data in the current RCI study, following standard protocol [43]. Interpretation of these plots considers the vectors (direction and length) as representing the coefficients of each of the variables with the PC axes, and the numbers are located at points representing the loading (or correlation) scores of individual observations (participants or muscles) on the PCs in the plot. To be considered important in defining the PC, the absolute value of a loading coefficient for variable was set at ≥ 0.3 (PCA-1) or ≥ 0.35 (PCA-2, PCA-3).


Altered Satellite Cell Responsiveness and Denervation Implicated in Progression of Rotator-Cuff Injury
Principal component analysis (PCA) biplots.Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for each of the variables (for 27 participants) included in the particular PCA. Vectors project onto the 3 axes (dimensions) of the principal components (PCs) 1 (x-axis), 2 (y-axis), and 3 (z-axis, positive is upward, perpendicular to the page). A. PCA-1, on the full dataset (N = 23 variables). B. PCA-2, Supraspinatus variables only (N = 16). C. PCA-3, variables of interest from previous comparisons, including “muscle” as a variable (N = 15 variables). Variables that loaded onto PC3 (as shown in Tables 1–3) are indicated with an asterisk (*) to emphasize that the correlation vector projects upward, perpendicular to PC1 and PC2 axes. Variable labels on the vectors are abbreviated as follows: C (control muscle), SS (Supraspinatus muscle), BMI (body mass index), Sx-to-Surg (weeks from symptom onset to surgery), diam (fiber diameter), SS:C diam (ratio of fiber diameter in SS/C), SC-base (baseline SC activation in explant cultures), SC-ISDN (SC activation in explants cultured with ISDN), dystr (expression of dystrophin protein relative to β-actin), mmp9 (level of matrix metalloproteinase 9 protein relative to β-actin), logRed (log-transformation of average maximum Sirius Red staining), γ:ε (γ:ε ratio of AchR subunits), γ (expression of the γ-subunit of AchR protein relative to β-actin), and BvD (vascular density).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC5036792&req=5

pone.0162494.g004: Principal component analysis (PCA) biplots.Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for each of the variables (for 27 participants) included in the particular PCA. Vectors project onto the 3 axes (dimensions) of the principal components (PCs) 1 (x-axis), 2 (y-axis), and 3 (z-axis, positive is upward, perpendicular to the page). A. PCA-1, on the full dataset (N = 23 variables). B. PCA-2, Supraspinatus variables only (N = 16). C. PCA-3, variables of interest from previous comparisons, including “muscle” as a variable (N = 15 variables). Variables that loaded onto PC3 (as shown in Tables 1–3) are indicated with an asterisk (*) to emphasize that the correlation vector projects upward, perpendicular to PC1 and PC2 axes. Variable labels on the vectors are abbreviated as follows: C (control muscle), SS (Supraspinatus muscle), BMI (body mass index), Sx-to-Surg (weeks from symptom onset to surgery), diam (fiber diameter), SS:C diam (ratio of fiber diameter in SS/C), SC-base (baseline SC activation in explant cultures), SC-ISDN (SC activation in explants cultured with ISDN), dystr (expression of dystrophin protein relative to β-actin), mmp9 (level of matrix metalloproteinase 9 protein relative to β-actin), logRed (log-transformation of average maximum Sirius Red staining), γ:ε (γ:ε ratio of AchR subunits), γ (expression of the γ-subunit of AchR protein relative to β-actin), and BvD (vascular density).
Mentions: PCA was used to reduce the dimensionality of the multivariate dataset for the current study, in which a total of 35 parameters were assessed (whether or not individual statistical analyses, above, were significant). The large dataset was reduced to data in three dimensions (principal components, PCs) which helps visualize statistical findings from an analysis of many variables together. Use of PCA can therefore be preferable to examining many variables using multiple pair-wise correlations. Fig 4 shows plots of the results of PCAs that were run on the data in the current RCI study, following standard protocol [43]. Interpretation of these plots considers the vectors (direction and length) as representing the coefficients of each of the variables with the PC axes, and the numbers are located at points representing the loading (or correlation) scores of individual observations (participants or muscles) on the PCs in the plot. To be considered important in defining the PC, the absolute value of a loading coefficient for variable was set at ≥ 0.3 (PCA-1) or ≥ 0.35 (PCA-2, PCA-3).

View Article: PubMed Central - PubMed

ABSTRACT

Background: Rotator-cuff injury (RCI) is common and painful; even after surgery, joint stability and function may not recover. Relative contributions to atrophy from disuse, fibrosis, denervation, and satellite-cell responsiveness to activating stimuli are not known.

Methods and findings: Potential contributions of denervation and disrupted satellite cell responses to growth signals were examined in supraspinatus (SS) and control (ipsilateral deltoid) muscles biopsied from participants with RCI (N = 27). Biopsies were prepared for explant culture (to study satellite cell activity), immunostained to localize Pax7, BrdU, and Semaphorin 3A in satellite cells, sectioning to study blood vessel density, and western blotting to measure the fetal (γ) subunit of acetylcholine receptor (γ-AchR). Principal component analysis (PCA) for 35 parameters extracted components identified variables that contributed most to variability in the dataset. γ-AchR was higher in SS than control, indicating denervation. Satellite cells in SS had a low baseline level of activity (Pax7+ cells labelled in S-phase) versus control; only satellite cells in SS showed increased proliferative activity after nitric oxide-donor treatment. Interestingly, satellite cell localization of Semaphorin 3A, a neuro-chemorepellent, was greater in SS (consistent with fiber denervation) than control muscle at baseline. PCAs extracted components including fiber atrophy, satellite cell activity, fibrosis, atrogin-1, smoking status, vascular density, γAchR, and the time between symptoms and surgery. Use of deltoid as a control for SS was supported by PCA findings since “muscle” was not extracted as a variable in the first two principal components. SS muscle in RCI is therefore atrophic, denervated, and fibrotic, and has satellite cells that respond to activating stimuli.

Conclusions: Since SS satellite cells can be activated in culture, a NO-donor drug combined with stretching could promote muscle growth and improve functional outcome after RCI. PCAs suggest indices including satellite cell responsiveness, atrogin-1, atrophy, and innervation may predict surgical outcome.

No MeSH data available.


Related in: MedlinePlus