Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks.
Ze ZhangSamuel R ReynoldsHannah G StolrowJi-Qing ChenBrock C ChristensenLucas A SalasPublished in: Aging cell (2023)
Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.
Keyphrases
- dna methylation
- gene expression
- genome wide
- endothelial cells
- rheumatoid arthritis
- electronic health record
- stem cells
- machine learning
- mesenchymal stem cells
- physical activity
- big data
- peripheral blood
- skeletal muscle
- circulating tumor
- pluripotent stem cells
- climate change
- insulin resistance
- mass spectrometry
- artificial intelligence
- high resolution
- high density
- health information
- ankylosing spondylitis
- circulating tumor cells
- atomic force microscopy