Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2008 Jul 25:5:6.
doi: 10.1186/1742-4933-5-6.

Multiparameter flow cytometric analysis of CD4 and CD8 T cell subsets in young and old people

Affiliations

Multiparameter flow cytometric analysis of CD4 and CD8 T cell subsets in young and old people

Sven Koch et al. Immun Ageing. .

Abstract

Background: T cell-mediated immunity in elderly people is compromised in ways reflected in the composition of the peripheral T cell pool. The advent of polychromatic flow cytometry has made analysis of cell subsets feasible in unprecedented detail.

Results: Here we document shifts in subset distribution within naïve (N), central memory (CM) and effector memory (EM) cells defined by CD45RA and CCR7 expression in the elderly, additionally using the costimulatory receptors CD27 and CD28, as well as the coinhibitory receptors CD57 and KLRG-1, to further dissect these. Although differences between young and old were more marked in CD8 than in CD4 cells, a similar overall pattern prevailed in both. Thus, the use of all these markers together, and inclusion of assays of proliferation and cytokine secretion, may enable the construction of a differentiation scheme applicable to CD4 as well as CD8 cells, with the model (based on Romero et al.) suggesting the progression N-->CM-->EM1-->EM2-->pE1-->pE2-->EM4-->EM3-->E end-stage non-proliferative effector cells.

Conclusion: Overall, the results suggest that both differences in subset distribution and differences between subsets are responsible for age-related changes in CD8 cells but that differences within rather than between subsets are more prominent for CD4 cells.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Schematic model of the T cell differentiation subsets using the markers CCR7 and CD45RA and the co-stimulatory molecules CD27 and CD28. With protein tyrosine phosphatase isoform CD45RA and the chemokine receptor CCR7, T cells can be subdivided into CD45RA+CCR7+ naïve (N), CD45RA-CCR7+ central memory (CM), CD45RA-CCR7- effector memory (EM) and CD45RA+CCR7- terminally differentiated effector memory (TEMRA) cells. The main subsets can be further subdivided by their expression of the co-stimulatory molecules TNF-family receptor CD27 and B7-family receptor CD28. Here, N and CM cells were defined as CD27+CD28+, whereas in EM and TEMRA further populations can be distinguished, which within EM cells are CD27+CD28+ (EM1), CD27+CD28- (EM2), CD27-CD28- (EM 3) and CD27-CD28+ (EM4), and within TEMRA are CD27+CD28+ (pE1,) CD27+CD28- (pE2), CD27-CD28- (E).
Figure 2
Figure 2
Main T cells subsets identified in young and old by CD45RA and CCR7. Frequencies of CD45RA+CCR7+ Naive, CD45RA-CCR7+ CM, CD45-CCR7- EM and CD45RA+CCR7- TEMRA CD8+ (open symbols) and CD4+ (filled symbols) at different ages in linear regression analysis.
Figure 3
Figure 3
Expression of co-stimulatory molecules CD27 and CD28. The main T cell subsets were subdivided according to expression of the co-stimulatory molecules CD27 and CD28. Frequencies of CD27-CD28+, CD27+CD28+, CD27-CD28- and CD27+CD28- in N, CM, EM and TEMRA in (A) CD8+ and (B) CD4 T cells in young (filled symbols) and the elderly (open symbols) are shown. The naïve and CM cells were defined as CD27+CD28+, whereas the EM and TEMRA were divided into further subsets according to the model in Figure 1. Significant differences are indicated by asterisks, as in Figure 2.
Figure 4
Figure 4
Distribution of CD57 and KLRG1 in naive and CM T cells. The CD27+CD28+ N and CD28+CD27+ CM (A and C) CD8+ and (B and D) CD4+ T cells in young (filled symbols) and the elderly (open symbols) were analysed for CD57 and KLRG1. Significant differences are indicated by asterisks, as in Figure 2.
Figure 5
Figure 5
Distribution of CD57 and KLRG1 in different EM T cell subsets. According to the subset model depicted in Figure 1, the EM CD8+ (A) and CD4+ (B) were subdivided into CD27+CD28+ EM1, CD27+CD28- EM2, CD27-CD28- EM 3 and CD27-CD28+ EM4 T cells in young (filled symbols) and the elderly (open symbols) and analyzed for the expression CD57 and KLRG1. Significant differences are indicated by asterisks, as in Figure 2.
Figure 6
Figure 6
Distribution of CD57 and KLRG1 in different TEMRA T cell subsets. According to the subset model depicted in Figure 1, the EM CD8+ (A) and CD4+ (B) were subdivided into CD27+CD28+ pE1, CD27+CD28- pE2, CD27-CD28- E T cells in young (filled symbols) and the elderly (open symbols) and analyzed for the expression CD57 and KLRG1. Significant differences are indicated by asterisks, as in Figure 2.
Figure 7
Figure 7
Gating strategy for CD8+ T cells. (A) Viable Lymphocytes were gated and then selected for either CD8+ or CD4+ T cells. (B) The CD8+ T cells were subdivided into the main T cell subsets using CD45RA and CCR7. (C) The CD45RA+CCR7+ N, CD45RA-CCR7+ CM, CD45-CCR7- EM and CD45RA+ CCR7- TEMRA CD8+ T cells were plotted against CD27 and CD28. According to the subset model (Figure 1) the different CD27 and CD28 dependent subpopulations (D) CM, (E) N, (F) EM and (G) TEMRA subsets were analyzed for CD57 and KLRG1.
Figure 8
Figure 8
Gating strategy for CD4+ T cells. (A) Viable Lymphocytes were gated and then selected for either CD8+ or CD4+ T cells. (B) The CD4+ T cells were subdivided into the main T cell subsets using CD45RA and CCR7. (C) The CD45RA+CCR7+ N, CD45RA-CCR7+ CM, CD45-CCR7- EM and CD45RA+ CCR7- TEMRA CD4+ T cells were plotted against CD27 and CD28. According to the subset model (Figure 1) the different CD27 and CD28 dependent subpopulations (D) CM, (E) N, (F) EM and (G) TEMRA subsets were analyzed for CD57 and KLRG1.

Similar articles

Cited by

References

    1. Kovaiou RD, Herndler-Brandstetter D, Grubeck-Loebenstein B. Age-related changes in immunity: implications for vaccination in the elderly. Expert Rev Mol Med. 2007;9:1–17. doi: 10.1017/S1462399407000221. - DOI - PubMed
    1. Haynes L, Swain SL. Why aging T cells fail: implications for vaccination. Immunity. 2006;24:663–666. doi: 10.1016/j.immuni.2006.06.003. - DOI - PMC - PubMed
    1. Weng NP. Aging of the immune system: how much can the adaptive immune system adapt? Immunity. 2006;24:495–499. doi: 10.1016/j.immuni.2006.05.001. - DOI - PMC - PubMed
    1. Fulop T, Larbi A, Hirokawa K, Mocchegiani E, Lesourds B, Castle S, Wikby A, Franceschi C, Pawelec G. Immunosupportive therapies in aging. Clin Interv Aging. 2007;2:33–54. doi: 10.2147/ciia.2007.2.1.33. - DOI - PMC - PubMed
    1. Pawelec G, Hirokawa K, Fulop T. Altered T cell signalling in ageing. Mech Ageing Dev. 2001;122:1613–1637. doi: 10.1016/S0047-6374(01)00290-1. - DOI - PubMed