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. 2018 Mar 1;77(3):337-344.
doi: 10.1097/QAI.0000000000001595.

HIV and Age Do Not Synergistically Affect Age-Related T-Cell Markers

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HIV and Age Do Not Synergistically Affect Age-Related T-Cell Markers

Shelli Farhadian et al. J Acquir Immune Defic Syndr. .
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Introduction: Despite major progress in controlling HIV disease through antiretroviral therapy, changes in immune phenotype and function persist in individuals with chronic HIV, raising questions about accelerated aging of the immune system.

Methods: We conducted a cross-sectional study (2005-2007) of HIV-infected (n = 111) and uninfected (n = 114) men from the Veterans Aging Cohort Study. All HIV-infected subjects were on antiretroviral therapy with VL <400 copies/mL for at least 3 years. T-cell markers were examined using flow cytometry. We evaluated the impact of HIV serostatus and age on T-cell phenotypes (expressed as percentages of the total CD4 and CD8 T-cell population) using multivariate linear regression, adjusted for smoking, alcohol, and race/ethnicity. We tested for interactions between HIV and age by including interaction terms.

Results: Among both HIV-infected and uninfected subjects, increasing age was associated with a decreased proportion of naive CD4 T cells (P = 0.014) and CD8 T cells (P < 0.0001). Both HIV infection and increasing age were associated with higher proportions of effector memory CD4 T cells (P < 0.0001 for HIV; P = 0.04 for age) and CD8 T cells (P = 0.0001 for HIV; P = 0.0004 for age). HIV infection, but not age, was associated with a higher proportion of activated CD8 T cells (P < 0.0001). For all T-cell subsets tested, there were no significant interactions between HIV infection and age.

Conclusions: Age and HIV status independently altered the immune system, but we found no conclusive evidence that HIV infection and advancing age synergistically result in accelerated changes in age-associated T-cell markers among virally suppressed individuals.


Figure 1
Figure 1. Gating of T cell populations
PBMCs were stained and captured by LSRII and analyzed using FlowJo software. Lymphocytes were identified by use of singlets and scatter gating. Dead/dying cells were excluded from further analysis using a viability dye. T cells were further defined by CD3 expression, and subsequently as CD4+ or CD8+ T cells. The CD4+ and CD8+ T-cell populations were each divided into subpopulations based on their expression of CD45RA, CD27, and CD28 with individual subsets identified using Boolean gating.
Figure 2
Figure 2. Modeled relationship between age and T-cell phenotypes, by HIV status
Black = HIV-infected, Red = uninfected. The impact of HIV and age on T cell phenotypes was assessed using multivariate linear regression models, adjusted for smoking, alcohol, and race/ethnicity. To maintain normality, outcomes with skewed distributions were log transformed. Y-axis units are percentages. Dots and lines represent modeled point estimates. Shaded gray areas represent 95% confidence bands for HIV-infected; shaded blue areas represent 95% confidence bands for uninfected. “p” indicates the p-value for interaction between HIV and age.

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