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THE IMPACT OF AGING ON THE TRANSCRIPTIONAL PROFILE OF HUMAN SKELETAL MUSCLE

Abstract

J.J. Dickinson1, L.J. D’Acquisto1, M. Naymik2, A.C. D’Lugos3, J.M. Dickinson1, FACSM

1Central Washington University, Ellensburg, WA

2Translational Genomics Research Institute, Phoenix, AZ

3University of Florida, Gainesville, FL

It is well known that advancing age is associated with deleterious changes in the size and function of skeletal muscle that contribute to reduced ability to perform daily activities and increased risk for injury. However, the precise molecular factors that contribute to declines in skeletal muscle size and function with advancing age are not completely understood. PURPOSE: To identify age-related differences in the transcriptional profile of human skeletal muscle. METHODS: Skeletal muscle biopsy samples (vastus lateralis) were analyzed from otherwise healthy younger (27±3yr; 8M, 1F; BMI: 24.5±2.0 kg•m-2; VO2max: 37.1±4.0 ml•kg-1•min-1) and older adults (68±5yr; 6M, 3F; BMI: 25.9±4.7 kg•m-2; VO2max: 33.6±9.6 ml•kg-1•min-1). All muscle biopsies were obtained after an overnight fast under resting conditions controlling for previous physical activity and caffeine and alcohol consumption. Total RNA was isolated and whole transcriptome next-generation sequencing (HISeq2500, Illumina) was performed on cDNA. Sequencing data were analyzed using HTSeq and differential gene expression between young and old was identified using DESeq2 (with young as reference). Genes with an adjusted p-value of <0.1 were considered differentially expressed. RESULTS: Of the 20,810 genes that were identified, 1,515 genes were considered to be differentially expressed in older adults compared to young. Among these genes, 729 were up-regulated while 786 were down-regulated in older adults compared to young. Many of the differentially expressed genes up-regulated in older adults were associated with energy metabolism, while many of the differentially expressed genes down-regulated in older adults were associated with cell membrane formation. CONCLUSION: These data highlight differences in the transcriptional profile of aging human skeletal muscle that may be related to age-related changes in skeletal muscle. Further research is needed to identify to what extent these unique transcriptional profiles may provide insight on therapeutic targets for aging skeletal muscle.

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