AgeMeta: Quantitative Gene Expression Database of Mammalian Aging

Area of Science:

• Genomics
• Aging Research
• Bioinformatics

Background:

• Mammalian aging involves complex transcriptomic alterations across various tissues.
• Existing data on aging-associated gene expression is fragmented across numerous studies.
• A unified, quantitative resource is needed to systematically analyze these changes.

Approach:

• Developed AgeMeta, a database integrating 122 gene expression datasets from 26 studies.
• Performed a meta-analysis to describe systemic and quantitative transcriptomic changes with age in humans, mice, and rats.
• Created an intuitive visual interface for exploring gene expression data and facilitating cross-species comparisons.

Key Points:

• AgeMeta quantifies aging-associated transcriptomics at individual gene and functional group levels.
• The database enables comparisons of aging patterns across different species and tissues.
• All data is downloadable for independent analysis, fostering further research.

Conclusions:

• AgeMeta provides a valuable resource for understanding the biological processes underlying mammalian aging.
• This database supports future research and advancements in aging biology.
• The freely available resource promotes broader scientific engagement with aging transcriptomics.