The transcriptional landscape of age in human peripheral blood

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.

Age‐associated microRNA expression in human peripheral blood is associated with all‐cause mortality and age‐related traits

“…For the 127 age‐associated miRNAs, the coexpression analysis identified 4682 mRNAs that were highly coexpressed with the 123 age‐related miRNAs at FDR < 0.05, including 24 310 miRNA–mRNA coexpression pairs. Of the 4682 mRNAs that were coexpressed with age‐associated miRNAs, 551 mRNAs were previously reported to be age‐associated (Peters et al ., 2015); the total number of reported age‐associated mRNAs in that study was 1497. Comparison of the two ratios (4682/17 318 measured mRNAs and 551/1497) yielded P  <   1 × 10 −16 (by the hypergeometric test), suggesting that age‐associated differences in miRNA expression are indicative of age‐associated changes in their coexpressed mRNAs.…”

“…In our previous studies, we used mRNA expression and DNA methylation data to predict age ( i.e ., mRNA age and DNAm age) in FHS Offspring participants (Marioni et al ., 2015; Peters et al ., 2015). In order to compare miRNA age with mRNA age and DNAm age, we used miRNA age calculated only in the FHS Offspring cohort.…”

“…Recent studies have revealed that human aging can be characterized by changing patterns of DNA methylation (Hannum et al ., 2013; Horvath, 2013) and expression of protein‐coding genes (Peters et al ., 2015). A growing body of research suggests that aging is associated with changes in DNA methylation both genome‐wide and at specific C‐G dinucleotide (CpG) loci.…”

“…At the mRNA level, a recent meta‐analysis of whole‐blood gene expression in ~15 000 individuals identified 1497 mRNAs that are differentially expressed in relation to age (Peters et al ., 2015). An age predictor based on mRNA expression ( i.e ., mRNA age) highlighted genes involved in mitochondrial, metabolic, and immune function‐related pathways as key components of aging processes.…”

“…An age predictor based on mRNA expression ( i.e ., mRNA age) highlighted genes involved in mitochondrial, metabolic, and immune function‐related pathways as key components of aging processes. The difference between mRNA age and chronological age ( i.e ., mRNA Δage) correlated with many metabolic risk factors including blood pressure, total cholesterol levels, fasting glucose, and body mass index (BMI) (Peters et al ., 2015). …”