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. 2023 Jan 10:13:1081889.
doi: 10.3389/fimmu.2022.1081889. eCollection 2022.

Single-cell RNA sequencing reveals the molecular features of peripheral blood immune cells in children, adults and centenarians

Jinjie Zhong  1   2   3 , Rong Ding  4 , Huimin Jiang  1   2   3 , LongFei Li  4 , Junli Wan  1   2 , Xiaoqian Feng  1   2   3 , Miaomiao Chen  1   2 , Liping Peng  1   2   3 , Xiaoqin Li  1   2 , Jing Lin  1   2 , Haiping Yang  1   2   3 , Mo Wang  1   2   3 , Qiu Li  1   2   3 , Qilin Chen  1   2   3
Affiliations

Single-cell RNA sequencing reveals the molecular features of peripheral blood immune cells in children, adults and centenarians

Jinjie Zhong et al. Front Immunol. .

Abstract

Peripheral blood immune cells have different molecular characteristics at different stages of the whole lifespan. Knowledge of circulating immune cell types and states from children to centenarians remains incomplete. We profiled peripheral blood mononuclear cells (PBMCs) of multiple age groups with single-cell RNA sequencing (scRNA-seq), involving the age ranges of 1-12 (G1), 20-30(G2), 30-60(G3), 60-80(G4), and >110 years (G5). The proportion and states of myeloid cells change significantly from G1 to G2. We identified a novel CD8+CCR7+GZMB+ cytotoxic T cell subtype specific in G1, expressing naive and cytotoxic genes, and validated by flow cytometry. CD8+ T cells showed significant changes in the early stage (G1 to G2), while CD4+ T cells changed in the late stage (G4 to G5). Moreover, the intercellular crosstalk among PBMCs in G1 is very dynamic. Susceptibility genes for a variety of autoimmune diseases (AIDs) have different cell-specific expression localization, and the expression of susceptibility genes for AIDs changes with age. Notably, the CD3+ undefined T cells clearly expressed susceptibility genes for multiple AIDs, especially in G3. ETS1 and FLI1, susceptibility genes associated with systemic lupus erythematosus, were differentially expressed in CD4+ and CD8+ effector cells in G1 and G3. These results provided a valuable basis for future research on the unique immune system of the whole lifespan and AIDs.

Keywords: CD8+ cytotoxic T cells; autoimmune diseases; peripheral blood mononuclear cells; single-cell RNA sequencing (scRNAseq); whole lifespan.

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Conflict of interest statement

Authors RD and LL were employed by Nanjing Jiangbei New Area Biopharmaceutical Public Service Platform. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Single-cell transcriptome profiling of the PBMCs of healthy children and multiple other age groups. (A) Schematic representation of the cell profile of blood immune cells in multiple age groups. (B) Two-dimensional UMAP visualization of PBMCs for multiple age groups. Different colors represent 43 clusters (cell types). (C) Expression of marker genes for 7 main cell types; cell positions are from the UMAP plot in (B).
Figure 2
Figure 2
Changes in cellular proportion and molecular characteristics with age. (A) Composition of the main cell types in the 5 age groups. (B) Smoothed line plot displaying the number of specific and common DEGs of different cell types for pairwise comparisons with a G1 reference. Positive (negative) values represent upregulated (downregulated) genes. (C) UpSet plot showing the integrated comparative analysis of upregulated DEGs in the main cell types between G1 and the other groups. Upregulated DEGs: upregulated in G1, downregulated in other groups. (D) UpSet plot showing the integrated comparative analysis of downregulated DEGs in the main cell types between G1 and the other groups. Downregulated DEGs: downregulated in G1, upregulated in other groups. (E) Violin plots showing the expression distribution of selected canonical cell markers in the 7 subtypes of myeloid cells. (F) Boxplots of the percentage of 4 CD14+ monocyte subtypes in PBMCs. All differences with P < 0.01 are indicated. NS, not statistically significant; *P < 0.01; **P < 0.001.
Figure 3
Figure 3
A distinct subtype of CD8+ cytotoxic T cells in childhood. (A) Violin plots showing the expression distribution of selected canonical cell markers in the 8 subtypes of CD8+ T cells. (B) Composition of CD8+ T cells in the 5 age groups. (C) Boxplots of the percentage of CD8+ cytotoxic T5 subtype in PBMCs. All differences with P < 0.01 are indicated. **P < 0.001; ***P < 0.0001. (D) The gating strategy of CD8+CCR7+GZMB+ T cells analyzed by flow cytometry. (E) The scatter plot showed the proportion of CD8+CCR7+GZMB+ T cells in PBMCs of healthy children and healthy adults (P=0.03). Differences with P < 0.05 are indicated. (F, G) Results of GO enrichment analysis (F) and KEGG pathway enrichment analysis (G) of the top50 marker genes of CD8+ cytotoxic T5. (H) Pseudotime trajectory of CD8+ T cells in G1 estimated using Monocle 3. (I) Pseudotime trajectory of CD8+ T cells in each group estimated using Monocle 3. (J) Transcription factors unique to the CD8+ cytotoxic T5 subtype.
Figure 4
Figure 4
Molecular characterization of B cells and CD4+ T cells in multiple age groups. (A) Violin plots showing the expression distribution of selected canonical cell markers in the 5 subtypes of B cells. (B) Boxplots of the percentage of naive B1 subtype in PBMCs. All differences with P < 0.01 are indicated. NS, not statistically significant; **P < 0.001; ***P < 0.0001. (C) Smoothed line plot displaying the number of specific and common DEGs of different B cell subtypes for pairwise comparisons with a G1 reference. Positive (negative) values represent upregulated (downregulated) genes. (D) Expression levels of 3 GO biological process terms in naive B1 and memory B subtypes across the 5 age groups. All differences with P < 0.01 are indicated. **P < 0.001; ***P < 0.0001. (E) Violin plots showing the expression distribution of selected canonical cell markers in the 8 subtypes of CD4+ T cells. (F) Composition of CD4+ T cells in the 5 age groups. (G) Pseudotime trajectory of CD4+ T cells estimated using Monocle 3. (H) Pseudotime trajectory of CD4+ T cells in each group estimated using Monocle 3.
Figure 5
Figure 5
Active intercellular crosstalk of PBMCs in childhood. (A, B) Naive state, cytotoxicity and exhaustion scores of different CD4+ T cells (A) and CD8+ T cells across 5 groups. All differences with P < 0.01 are indicated. NS, not statistically significant; **P < 0.001; ***P < 0.0001. (C) The intercellular crosstalk number of each main cell type estimated using Cellphone DB, including myeloid cells, B cells, CD8+ T cells, CD4+ T cells, NK cells and other T cells.
Figure 6
Figure 6
Combined analysis of genes associated with immune-related disease risk. (A) Heatmap of susceptibility genes for AIDs in G1 and G3. (B) Susceptibility genes with significantly different expression between G1 and G3.
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This research was funded by National Natural Science Foundation of China (82170720) and Chongqing Municipal Education Commission (KJZD-M201900401).