
School of Medicine Publications and Presentations
Document Type
Article
Publication Date
10-22-2015
Abstract
Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.
Recommended Citation
Peters, M. J., Joehanes, R., Pilling, L. C., Schurmann, C., Conneely, K. N., Powell, J., ... & Johnson, A. D. (2015). The transcriptional landscape of age in human peripheral blood. Nature communications, 6(1), 8570. https://doi.org/10.1038/ncomms9570
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
Nature Communications
DOI
10.1038/ncomms9570
Academic Level
faculty
Mentor/PI Department
Office of Human Genetics
Comments
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