The immune system in the aging human

Rymkiewicz, Paulina; Heng, Yi Xiong; Vasudev, Anusha; Larbi, Anis

doi:10.1007/s12026-012-8289-3

Cited by 42 publications

(35 citation statements)

References 109 publications

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“…From the Old template, five clusters appeared to be memory CD4 T cells (CD3+CD4+CD8−CD45−), three expressed monocytic markers (CD3−CD14+CD11B+), and four expressed both T cell and monocyte markers and showed high FSC‐W values, consistent with T cell/monocyte conjugates. The T cell results fit well with previous studies that showed a shift in frequency from naïve to memory CD8 T cells on aging 18, 19, 20, 21, consistent with the accumulation of memory cells with continued antigen stimulation, and oligoclonal expansion of specific memory CD8 T cell populations 22, 23. Similarly, a decrease in gamma‐delta T cells has been reported previously 24, 25.…”

Section: Resultssupporting

confidence: 90%

Competitive SWIFT cluster templates enhance detection of aging changes

Rebhahn

Roumanes

et al. 2015

Cytometry Pt A

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Clustering‐based algorithms for automated analysis of flow cytometry datasets have achieved more efficient and objective analysis than manual processing. Clustering organizes flow cytometry data into subpopulations with substantially homogenous characteristics but does not directly address the important problem of identifying the salient differences in subpopulations between subjects and groups. Here, we address this problem by augmenting SWIFT—a mixture model based clustering algorithm reported previously. First, we show that SWIFT clustering using a “template” mixture model, in which all subpopulations are represented, identifies small differences in cell numbers per subpopulation between samples. Second, we demonstrate that resolution of inter‐sample differences is increased by “competition” wherein a joint model is formed by combining the mixture model templates obtained from different groups. In the joint model, clusters from individual groups compete for the assignment of cells, sharpening differences between samples, particularly differences representing subpopulation shifts that are masked under clustering with a single template model. The benefit of competition was demonstrated first with a semisynthetic dataset obtained by deliberately shifting a known subpopulation within an actual flow cytometry sample. Single templates correctly identified changes in the number of cells in the subpopulation, but only the competition method detected small changes in median fluorescence. In further validation studies, competition identified a larger number of significantly altered subpopulations between young and elderly subjects. This enrichment was specific, because competition between templates from consensus male and female samples did not improve the detection of age‐related differences. Several changes between the young and elderly identified by SWIFT template competition were consistent with known alterations in the elderly, and additional altered subpopulations were also identified. Alternative algorithms detected far fewer significantly altered clusters. Thus SWIFT template competition is a powerful approach to sharpen comparisons between selected groups in flow cytometry datasets. © 2015 The Authors. Published Wiley Periodicals Inc.

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Section: Resultssupporting

confidence: 90%

Competitive SWIFT cluster templates enhance detection of aging changes

Rebhahn

Roumanes

et al. 2015

Cytometry Pt A

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“…Overall, our results showed a lower number of total CD3 + lymphocytes (both CD4 + and CD8 + T cells) among individuals aged more than 50 years. Such a decrease has been reported previously and has been associated with increased immunosenescence, particularly among individuals aged > 65 years, and may be related to thymic involution [22,23,55,56]. Despite these differences, similar percentages of TNF-α + T lymphocytes and levels of secreted TNF-α, IL-2 and IL-4 were found in the two age groups after short-term in each TCR-Vβ family among individuals younger and older than 50 years of age.…”

Section: Discussionsupporting

confidence: 78%

“…In contrast, the higher levels of TNF-α, IFN-γ and IL-6 found among individuals aged more than 50 years is a new observation related to EBV responses; these results suggest that individuals aged more than 50 years have an EBVcompetent immune response alongside low-grade inflammation that may emerge with age (e.g. naturally) [22]. CD4 + and CD8 + T lymphocytes capable of producing at least one cytokine and TNF-α [12,45,47].…”

Section: Immune Response To Ebv In Healthy Individualsmentioning

confidence: 82%

Age-associated Epstein–Barr virus-specific T cell responses in seropositive healthy adults

Cárdenas

Colmenares

Matos

et al. 2014

Clinical and Experimental Immunology

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SummaryEpstein-Barr virus (EBV) is present in 95% of the world's adult population. The immune response participates in immune vigilance and persistent infection control, and this condition is maintained by both a good quality (functionality) and quantity of specific T cells throughout life. In the present study, we evaluated EBV-specific CD4 + and CD8 + T lymphocyte responses in seropositive healthy individuals younger and older than 50 years of age. The assessment comprised the frequency, phenotype, functionality and clonotypic distribution of T lymphocytes. We found that in both age groups a similar EBV-specific T cell response was found, with overlapping numbers of tumour necrosis factor (TNF)-α + T lymphocytes (CD4 + and CD8 + ) within the memory and effector cell compartments, in addition to monofunctional and multi-functional T cells producing interleukin (IL)-2 and/or interferon (IFN)-γ. However, individuals aged more than 50 years showed significantly higher frequencies of IL-2-producing CD4 + T lymphocytes in association with greater production of soluble IFN-γ, TNF-α and IL-6 than subjects younger than 50 years. A polyclonal T cell receptor (TCR)-variable beta region (Vβ) repertoire exists in both age groups under basal conditions and in response to EBV; the major TCR families found in TNF-α + /CD4 + T lymphocytes were Vβ1, Vβ2, Vβ17 and Vβ22 in both age groups, and the major TCR family in TNF-α + /CD8 + T cells was Vβ13·1 for individuals younger than 50 years and Vβ9 for individuals aged more than 50 years. Our findings suggest that the EBV-specific T cell response (using a polyclonal stimulation model) is distributed throughout several T cell differentiation compartments in an age-independent manner and includes both monofunctional and multi-functional T lymphocytes.

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“…Indeed, the deregulation of this well-balanced system may lead to the emergence of diseases but has also been associated with human aging [12]. It is of note that the extensive role of an adequate immune system may be correctly appreciated only in these cases.…”

Section: The Immune System a System Among Othersmentioning

confidence: 99%

On the Immunological Theory of Aging

Fülöp

Witkowski

Pawelec

et al. 2014

Interdisciplinary Topics in Gerontology and Geriatrics

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110

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Aging is a complex phenomenon the cause of which is not fully understood, despite the plethora of theories proposed to explain it. As we age, changes in essentially all physiological functions, including immunity, are apparent. Immune responses decrease with aging, contributing to the increased incidence of different chronic diseases with an inflammatory component (sometimes referred to as 'inflamm-aging'). It is clear from many studies that human longevity may be influenced by these changes in the immune system, but how they proceed is not clearly determined. In this chapter, we will review the age-related changes in the immune response and assess the validity of the immune theory of aging (i.e. that these changes in immune response are the primary cause of aging). Many data in humans support the notion that age-associated immune dysfunction may at least in part explain the aging process. Explanatory power may be enhanced by combination with other theories such as the free radical theory. More longitudinal studies are needed to corroborate the immune theory of aging.

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The immune system in the aging human

Cited by 42 publications

References 109 publications

Competitive SWIFT cluster templates enhance detection of aging changes

Competitive SWIFT cluster templates enhance detection of aging changes

Age-associated Epstein–Barr virus-specific T cell responses in seropositive healthy adults

On the Immunological Theory of Aging

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