Immunosenescence Study of T Cells: A Systematic Review

Abstract

Background: Aging is accompanied by alterations in immune response which leads to increased susceptibility to infectious diseases, cancer, autoimmunity, and inflammatory disorders. This decline in immune function is termed as immunosenescence; however, the mechanisms are not fully elucidated. Experimental approaches of adaptive immunity, particularly for T cells, have been the main focus of immunosenescence research. This systematic review evaluates and discusses T cell markers implicated in immunosenescence.

Objective: To determine the best flow cytometry markers of circulating T cells associated with immunosenescence.

Methods: We systematically queried PubMed, MEDLINE, EBSCO, and BVS databases for original articles focused on two age groups of healthy humans: 18-44 (young adults) and >60 (older adults) years. In accordance with the Cochrane methodology, we synthesized data through qualitative descriptions and quantitative random effects meta-analysis due to extensive heterogeneity.

Results: A total of 36 studies conducted in the last 20 years were included for the qualitative analysis and four out of these studies were used to perform the meta-analysis. A significant decrease in naïve T cell subset was observed in older adults compared to young adults. Primary markers used to identify senescent cells were loss of CD28 and increased expression of CD57 and KLRG1 in terminally-differentiated memory T cell subset in older adults. Moreover, we observed an increase in proinflammatory cytokines and decrease in telomere length in old adult T cells. It was not possible to perform quantitative synthesis on cell markers, cytokines, and telomere length because of the significant variations between the groups, which is attributed to differences in protocols and unreported measurements, thus generating a high risk of bias.

Conclusions: Heterogeneity among studies in terms of data report, measurement techniques and high risk of bias were major impediments for performing a robust statistical analysis that could aid the identification of eligible flow cytometry markers of immunosenescence phenotype in T cells.

Keywords: T cells; cytokines; flow cytometry; immunosenescence; immunosenescence markers.

Figure 1

Study flow diagram. The search strategy performed in this article led to the initial selection of 418 potential papers. 303 were retrieved from PUBMED/MEDLINE, 115 from EBSCO and 0 from BVS in the identification phase. After duplicates were removed, a total of 263 papers were identified. From these, 157 articles were excluded based on title and abstract. Further investigation of the remaining 106 full text articles led to the exclusion of 70 articles and the inclusion of 36 studies for the qualitative synthesis among which 4 studies allowed us to perform a meta-analysis.

Figure 2

Risk of bias summary. Shows the bias results of all papers reviewed.

Figure 3

Risk of bias summary for paper. Review authors’s judgments about each risk of bias item for each included study.

Figure 4

Influence of age on naive CD8+ T cell frequency. Forest plot for the different outcomes regarding cell frequency between old and young groups. The forest plot displays the SMD (squares) and 95% confidence interval of the individual studies. The diamond in each plot indicates the overall estimate and 95% confidence interval.

Figure 5

Influence of age on naive CD4+ T cell frequency. Forest plot for the different outcomes regarding cell frequency. (A) Changes in the frequency of CD4+ naive T cells between old and young groups and (B) Changes in the frequency of CD4+ naive T cells between super old and young groups.

Figure 6

Qualitative analysis of frequency in CD4+ T cell subsets. CD4+ T cell subset and citation percent across studies comparing young and old populations. N, naive; CM, Central Memory; EM, Effector Memory; TE, Terminally Effector; NS, No Significant change; NM, Non measured; NC, not compared.