Transcriptional profiling of aging in human muscle reveals a common aging signature
2006

Aging in Human Muscle: A Common Signature

Sample size: 81 publication 10 minutes Evidence: high

Author Information

Author(s): Jacob M. Zahn, Rebecca Sonu, Hannes Vogel, Emily Crane, Krystyna Mazan-Mamczarz, Ralph Rabkin, Ronald W. Davis, Kevin G. Becker, Art B. Owen, Stuart K. Kim

Primary Institution: Stanford University Medical Center

Hypothesis

Can gene expression profiles in human muscle reveal a common signature of aging across different tissues?

Conclusion

The study identified a common aging signature in human muscle that correlates with physiological age and is shared with other tissues like the kidney and brain.

Supporting Evidence

  • The study identified 250 age-regulated genes in human muscle.
  • Gene expression profiles reflected both chronological and physiological age.
  • A common aging signature was found across muscle, kidney, and brain tissues.
  • Six genetic pathways were identified as part of the aging signature.
  • Decreased expression of the electron transport chain was observed in humans, mice, and flies.
  • Age-regulated genes were enriched for those predicting muscle function.
  • Statistical tests confirmed the significance of the findings.
  • Findings suggest that aging affects gene expression in a coordinated manner across tissues.

Takeaway

As people get older, their muscle shows changes in gene activity that can tell us how well their muscles are working, not just how old they are.

Methodology

The study used Affymetrix DNA arrays to analyze gene expression in muscle samples from individuals aged 16 to 89.

Potential Biases

Potential bias from the selection of muscle samples based on medical conditions.

Limitations

The study may not account for all confounding factors affecting gene expression, such as specific medical conditions.

Participant Demographics

Participants ranged in age from 16 to 89 years, with samples from various anatomical locations.

Statistical Information

P-Value

p<0.001

Statistical Significance

p<0.001

Digital Object Identifier (DOI)

10.1371/journal.pgen.0020115

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