To identify cell-subtype-specific gene signatures associated with aging, we performed an integrated comparative analysis of differentially expressed genes (DEGs) from blood immune cells in the YA and AA groups. We found that blood immune cells showed heterogeneous transcriptional changes affected by aging based on the number of DEGs. Strikingly, BC was the cell type most affected by aging, followed by TC and MC (Figs. 3A, S6A; Table S4A–E). Specifically, we found a set of 60 genes whose expression was increased in all kinds of immune cells, indicative of general oxidative stress (e.g., DDIT4, CASP4, TSPO) and an inflammatory state (e.g., DUSP2, S100A10, COX5A, PSMB6) across cell populations (Fig. 3A). Conversely, genes with decreased expression shared across all cell populations included DDX17, RBM39, and SCAF11, which are involved in RNA splicing (Fig. S6A and S6B). Consistent with our understanding of the main immune cell lineages, we found that the myeloid and lymphocyte cell lineages were characterized by unique gene expression spectra, whereas TCs showed the highest heterogeneity in DEGs. To explore the biological implications of our data in the context of aging, we used Gene Ontology (GO) and pathway analysis for each immune cell population. Common aging-upregulated biological pathways included TNF signaling, IL-1 signaling, the apoptotic signaling pathway, and the adaptive immune response (Fig. 3B). We found that these pathways were especially enhanced in TCs. In addition, aging-upregulated biological pathways in MCs were enriched for interferon-gamma (IFN-γ) signaling and cell aging (Fig. 3B). To assess the impact of aging on circulating immune cells, we selected the top 20 genes of the 60 total genes that were upregulated in all immune cells (Fig. 3A) and calculated aging scores across all immune cell types. We found that MCs and DCs had the highest scores, suggesting that senescent cells are most likely present in these cell populations (Fig. 3C). Moreover, when calculating the scores of individual samples, we found that individuals in the AA group had consistently higher scores than individuals in the YA group (Fig. 3D), suggesting that aging-score assessments are suitable for studying aging-related immune dysfunction.
Figure 3 Changes in transcriptional profiles during aging. (A) UpSet Plot showing the integrated comparative analysis of upregulated DEGs in major immune cell lineages between YA and AA groups. Upregulated DEGs: upregulated in AA, downregulated in YA group. (B) Representative GO terms and pathways enriched in upregulated DEGs based on functional enrichment analysis in major immune cell populations. P value was derived by a hypergeometric test. (C) Distribution and comparison of the aging score in immune cell populations. (D) Distribution and comparison of the aging score in all cells of each sample. (E) UpSet plot showing the integrated comparative analysis of upregulated DEGs in CD4+ T cells between YA and AA groups. Upregulated DEGs: upregulated in AA, downregulated in YA. The count showing the number of DEGs. (F) Representative GO terms and pathways enriched in upregulated DEGs based on functional enrichment analysis in CD4+ T cells. P value was derived by a hypergeometric test. (G) Venn diagram showing integrated comparative analysis of upregulated DEGs in monocytes between YA and AA groups. Upregulated DEGs: upregulated in AA, downregulated in YA. The count showing the number of DEGs. (H) Representative GO terms and pathways enriched in upregulated DEGs based on functional enrichment analysis in monocytes. P value was derived by a hypergeometric test. (I) Violin plots showing the distribution of normalized expression levels of selected aging-associated genes in all DC cluster between YA and AA groups. (J) t-SNE plots segregated on the basis of DC subsets. (K) Representative GO terms and pathways enriched in biased DEGs of cDC2-A and cDC2-B clusters. P value was derived by a hypergeometric test. (L) CLEC12A expression in cDC2 is shown as flow cytometry histogram. (M) Percentage of CLEC12A+ cells in cDC2. P value are based on two-tailed Mann-Whitney-Wilcoxon tests between YA and AA groups (n = 3/group)