Research Paper Volume 14, Issue 1 pp 143—160

Different phases of aging in mouse old skeletal muscle

Yong-Kook Kang1,2, , Byungkuk Min1, , Jaemin Eom1,2, , Jung Sun Park1, ,

  • 1 Development and Differentiation Research Center, Korea Research Institute of Bioscience Biotechnology (KRIBB), Yuseong-Gu, Daejeon 34141, South Korea
  • 2 Department of Functional Genomics, Korea University of Science and Technology (UST), Yuseong-Gu, Daejeon 34113, South Korea

Received: June 23, 2021       Accepted: December 3, 2021       Published: January 11, 2022
How to Cite

Copyright: © 2022 Kang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


With a graying population and increasing longevity, it is essential to identify life transition in later years and discern heterogeneity among older people. Subclassifying the elderly population to inspect the subdivisions for pathophysiological differences is particularly important for the investigation of age-related illnesses. For this purpose, using 24- and 28-month-old mice to represent the “young-old” and “old-old”, respectively, we compared their skeletal muscle transcriptomes and found each in a distinct stage: early/gradual (E-aging) and late/accelerated aging phase (L-aging). Principal component analysis showed that the old-old transcriptomes were largely disengaged from the forward transcriptomic trajectory generated in the younger-aged group, indicating a substantial change in gene expression profiles during L-aging. By calculating the transcriptomic distance, it was found that the 28-month group was closer to the two-month group than to the 24-month group. The divergence rate per month for the transcriptomes was the highest in L-aging, twice as fast as the rate in E-aging. Indeed, many of the L-aging genes were significantly altered in transcription, although the changes did not seem random but rather coordinated in a variety of functional gene sets. Of 2,707 genes transcriptionally altered during E-aging, two-thirds were also significantly changed during L-aging, to either downturning or upturning way. The downturn genes were related to mitochondrial function and translational gene sets, while the upturn genes were linked to inflammation-associated gene sets. Our results provide a transcriptomic muscle signature that distinguishes old-old mice from young-old mice. This can help to methodically examine muscle disorders in the elderly.


E-/L-aging: early and late phase of aging; 2m to 28m: two months to 28 months of age; DEG: differentially expressed genes; PCA: principal component analysis; (f)GSEA: (fast pre-ranked) gene set enrichment analysis; ssGSEA: single-sample GSEA; ES: enrichment score; GSVA: gene set variation analysis; PBMC: peripheral blood mononuclear cell; GO: gene ontology.