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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.
