Transcriptomic profiles of aging in purified human immune cells

Abstract

Background: Transcriptomic studies hold great potential towards understanding the human aging process. Previous transcriptomic studies have identified many genes with age-associated expression levels; however, small samples sizes and mixed cell types often make these results difficult to interpret.

Results: Using transcriptomic profiles in CD14+ monocytes from 1,264 participants of the Multi-Ethnic Study of Atherosclerosis (aged 55-94 years), we identified 2,704 genes differentially expressed with chronological age (false discovery rate, FDR ≤ 0.001). We further identified six networks of co-expressed genes that included prominent genes from three pathways: protein synthesis (particularly mitochondrial ribosomal genes), oxidative phosphorylation, and autophagy, with expression patterns suggesting these pathways decline with age. Expression of several chromatin remodeler and transcriptional modifier genes strongly correlated with expression of oxidative phosphorylation and ribosomal protein synthesis genes. 17% of genes with age-associated expression harbored CpG sites whose degree of methylation significantly mediated the relationship between age and gene expression (p < 0.05). Lastly, 15 genes with age-associated expression were also associated (FDR ≤ 0.01) with pulse pressure independent of chronological age. Comparing transcriptomic profiles of CD14+ monocytes to CD4+ T cells from a subset (n = 423) of the population, we identified 30 age-associated (FDR < 0.01) genes in common, while larger sets of differentially expressed genes were unique to either T cells (188 genes) or monocytes (383 genes). At the pathway level, a decline in ribosomal protein synthesis machinery gene expression with age was detectable in both cell types.

Conclusions: An overall decline in expression of ribosomal protein synthesis genes with age was detected in CD14+ monocytes and CD4+ T cells, demonstrating that some patterns of aging are likely shared between different cell types. Our findings also support cell-specific effects of age on gene expression, illustrating the importance of using purified cell samples for future transcriptomic studies. Longitudinal work is required to establish the relationship between identified age-associated genes/pathways and aging-related diseases.

Figure 1

Study design and results summary. A) CD14+ monocytes were purified from 1,264 peripheral blood samples by magnetic bead selection, and gene expression levels were measured using microarray. Age-associated expression (FDR ≤ 0.01) was detected for 4,502 genes, which were further analyzed using the indicated in silico approaches to identify and investigate potential age-related pathways. Results support a potential transcriptomic decline in ribosomal protein synthesis machinery, as well as declines in oxidative phosphorylation and autophagy gene expression with age. Measures of DNA methylation and pulse pressure were incorporated to investigate DNA methylation as a potential mediator for the effect of age on gene expression, and to prioritize age-associated gene expression for potential relevance to vascular age. B) CD4+ T cells were purified in a subset of the peripheral blood samples by magnetic bead selection, and gene expression levels were measured using microarray. Age-associated genes (FDR < 0.01) were identified, revealing 30 genes with expression significantly associated with age in both monocytes and T cells from the same individuals. No pathways were significantly (FDR < 0.05) enriched among age-associated genes in T cells; however, suggestive evidence was observed for the ribonucleoprotein complex and immune response pathways.

Figure 2

Co-expression network modules associated with chronological age. Six mutually exclusive gene network modules with coordinate gene expression profiles associated with chronological age were identified in 1,264 monocyte samples (using WGCNA), ranging in size from 3 to 1,466 genes. For each module (x-axis), the partial correlation between age and the module eigengene is shown (y-axis); covariates included race, sex, site of data collection, and residual sample contamination with non-targeted cells. Below each module is the number of genes assigned to the module, and the direction of expression association with age; network modules discussed in further detail include the ‘black’ module (containing three genes: MCL1, TSC22D3, and CEBPD), and the ‘blue’ and ‘turquoise’ modules (which were significantly enriched with age-related pathways shown in Table 1). The significance of the module eigengene association with age is denoted as: * p < 0.008 (Bonferroni adjusted significance threshold for testing six modules, alpha = 0.05), and ** p ≤ 1x10⁻⁶.

Figure 3

Age-associated expression pattern for the Bcl-2 family and other key autophagy genes suggest autophagy declines with age. The ‘black’ co-expression network module gene - MCL1 (circle), and other key genes (diamonds) encoding autophagy machinery and autophagy inhibitors/activators (related to the Bcl-2 family and the PI3K/AKT signaling pathway) are shown, with edges representing previously characterized protein-protein interactions (STRING v9.05). Color denotes the direction and significance resulting from the association of age and gene expression in 1,264 CD14+ human monocyte samples, adjusting for race, sex, study site, and residual cell contamination with other cell types.

Figure 4

Protein functions and interactions between co-expressed genes assigned to the ‘blue’ network module. In 1,264 monocyte samples, older age was associated with lower expression of 217 co-expressed genes assigned to the ‘blue’ network module, 77 of which (shown as diamonds) have experimental evidence for interaction with other ‘blue’ module genes (interactions shown as edges, from STRING v9.1). Color denotes gene membership to Gene Ontology (GO) pathways enriched in the ‘blue’ module relative to all monocyte expressed genes (FDR < 0.05), including the electron transport chain/oxidative phosphorylation pathway (blue) and ribonucleoprotein complex pathway (green, purple, and yellow) – comprised of protein synthesis machinery genes from the mitochondrial ribosome (green), the ribosome (purple), and RNA processing genes (yellow). Genes relating to other cellular processes (white) include mitochondrial protein import genes (TOMM20, TOMM22) and DNA damage response genes (NSMCE2, SUMO2, SUMO1, TDP2); ‘blue’ module genes without reported protein-protein interactions are not shown (140 genes).

Figure 5

Comparison of the effect of age on gene expression in T cells and monocyte samples. The correlation between age and gene expression is shown in T cells (y-axis), compared to monocytes (x-axis) from 423 individuals, including all 10,322 genes expressed in both T cells and monocytes. Color indicates genes with expression significantly associated with age (FDR < 0.01) in T cells (green, 188 genes) or monocytes (red, 383 genes), both T cells and monocytes (blue, 30 genes), or neither T cells nor monocytes (grey); association analyses were adjusted for race, sex, study site, and residual cell contamination with non-target cells.