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Aging and microRNA expression in human skeletal muscle: a microarray and bioinformatics analysis

Aging and microRNA expression in human skeletal muscle: a microarray and bioinformatics analysis

Physiological Genomics 43(10): 595-603

A common characteristic of aging is loss of skeletal muscle (sarcopenia), which can lead to falls and fractures. MicroRNAs (miRNAs) are novel posttranscriptional modulators of gene expression with potential roles as regulators of skeletal muscle mass and function. The purpose of this study was to profile miRNA expression patterns in aging human skeletal muscle with a miRNA array followed by in-depth functional and network analysis. Muscle biopsy samples from 36 men [young: 31 ± 2 (n = 19); older: 73 ± 3 (n = 17)] were 1) analyzed for expression of miRNAs with a miRNA array, 2) validated with TaqMan quantitative real-time PCR assays, and 3) identified (and later validated) for potential gene targets with the bioinformatics knowledge base software Ingenuity Pathways Analysis. Eighteen miRNAs were differentially expressed in older humans (P < 0.05 and >500 expression level). Let-7 family members Let-7b and Let-7e were significantly elevated and further validated in older subjects (P < 0.05). Functional and network analysis from Ingenuity determined that gene targets of the Let-7s were associated with molecular networks involved in cell cycle control such as cellular proliferation and differentiation. We confirmed with real-time PCR that mRNA expression of cell cycle regulators CDK6, CDC25A, and CDC34 were downregulated in older compared with young subjects (P < 0.05). In addition, PAX7 mRNA expression was lower in older subjects (P < 0.05). These data suggest that aging is characterized by a higher expression of Let-7 family members that may downregulate genes related to cellular proliferation. We propose that higher Let-7 expression may be an indicator of impaired cell cycle function possibly contributing to reduced muscle cell renewal and regeneration in older human muscle.

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Accession: 036103455

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PMID: 20876843

DOI: 10.1152/physiolgenomics.00148.2010

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