Abstract
Changes in skeletal muscle are an important aspect of overall health. The collection of human muscle to study cellular and molecular processes for research requires a needle biopsy procedure which, in itself, can induce changes in the tissue. To investigate the effect of repeat tissue sampling, we collected skeletal muscle biopsy samples from vastus lateralis separated by 7 days. Cellular infiltrate, central nucleation, enlarged extracellular matrix, and rounding of muscle fibers were used as indices to define muscle damage, and we found that 16/26 samples (61.5%) revealed at least two of these symptoms in the secondary biopsy. The presence of damage influenced outcome measures usually obtained in human biopsies. Damaged muscle showed an increase in the number of small fibers even though average fiber and fiber type-specific cross-sectional area (CSA) were not different. This included higher numbers of embryonic myosin heavy chain-positive fibers (P = 0.001) as well as elevated satellite cell number (P = 0.02) in the damaged areas and higher variability in satellite cell count in the total area (P = 0.04). Collagen content was higher in damaged (P = 0.0003) as well as nondamaged areas (P = 0.05) of the muscle sections of the damaged compared with the nondamaged group. Myofibrillar protein and ribonucleic acid (RNA) fractional synthesis rates were not significantly different between the damaged compared with the nondamaged group. Results indicate that common outcomes as well as outcome variability in human muscle tissue are affected by previous biopsies. Therefore, the extent of potential damage should be assessed when performing repeated biopsies.NEW & NOTEWORTHY Indices of damage can be found in repeated biopsy samples of nonintervened control legs. Variables, directly and not directly related to muscle damage or regeneration, were compromised in second biopsy. There is a need to determine potential damage within muscle tissue when repeated muscle sampling is part of the study design. Muscle biopsy sampling may be a source of increased heterogeneity in human muscle data.
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