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. 2022 Jan 3;19(1):4.
doi: 10.1186/s12979-021-00260-x.

The effect of age on CD4+ T-cell recovery in HIV-suppressed adult participants: a sub-study from AIDS Clinical Trial Group (ACTG) A5321 and the Bone Loss and Immune Reconstitution (BLIR) study

Jingxian Chen  1   2 , Kehmia Titanji  3 , Anandi N Sheth  4 , Rajesh Gandhi  5 , Deborah McMahon  6 , Ighovwerha Ofotokun  4 , M Neale Weitzmann  3   7 , Kristina De Paris  8 , Julie B Dumond  9   10
Affiliations

The effect of age on CD4+ T-cell recovery in HIV-suppressed adult participants: a sub-study from AIDS Clinical Trial Group (ACTG) A5321 and the Bone Loss and Immune Reconstitution (BLIR) study

Jingxian Chen et al. Immun Ageing. .

Abstract

Older age could be a risk factor for suboptimal CD4+ T-cell recovery in HIV-infected patients despite successful viral suppression. However, evaluation of this effect could be confounded by age-related immune processes such as decreased thymus output, increased immune activation and exhaustion. Here, we established a semi-mechanistic population model simultaneously describing naïve and memory CD4+ T-cell trajectories in 122 participants. Covariate analysis accounting for immune activation showed that older age was significantly associated with faster apparent elimination rate of the naïve T-cells. In addition, female sex predicted slower apparent elimination rate of memory T-cells. Simulations showed that the median maximal CD4+ T-cell count on ART treatment was 593 cells/μL (IQR 442-794) in patients aged 50 years or above and 738 cells/μL (IQR 548-1002) in patients aged 18-35 years. The differences in the percentage of subjects achieving sufficient immune reconstitution (CD4+ T-cell count> 500 cells/μL) between the two age groups were 15, 21 and 26% at year 1, 4 years and steady state, respectively, suggesting that advanced age may have a greater impact on long-term CD4+ T-cell recovery.

Keywords: Aging; HIV; Immune recovery; Nonlinear mixed effects modeling; Pharmacodynamic modeling.

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Conflict of interest statement

JC is a current employee of Merck. RTG has served on scientific advisory boards for Merck and 460 Gilead. The other authors do not declare any competing interests.

Figures

Fig. 1
Fig. 1
Different Modeling of T-cell Dynamics. a Simple exponential model of total CD4+ T-cells. T: total T-cell measurement, int: initial CD4 + T-cell measurement, asy: asymptotic or long-term CD4+ T-cell measurement on treatment, c: cell elimination rate constant, ln(2)/c: time to achieve half asymptotic CD4+ T-cell measurement. b Joint viral and T-cell dynamic model in HIV infection. TUI: uninfected T-cells, T*: infected Tcells, V: infectious HIV virons, λ: production rate of uninfected T-cells, d: death rate constant of uninfected T-cells, k: viral infection rate constant, δ: death rate constant of infected T-cells, ρ: new viron production rate constant, cl: viron clearance rate constant. c and d Mechanistic models of T-cell homeostasis. R: resting T-cells, A: activated T-cells, a: activation rate constant, r: rate constant of reversion to resting state, π: resting cells proliferation rate constant, d: death rate constant, p: proliferation rate constant, N: naïve T-cells, M: memory T-cells, σ: naïve T-cell production rate
Fig. 2
Fig. 2
Structural Model Schematic. σ: production rate of naïve T-cells, α: activation rate constant of naïve T-cells that acquire a memory phenotype, dN: naïve T-cell death rate constant, dM: memory T-cell death rate constant, N: naïve T-cell number, M: memory T-cell number
Fig. 3
Fig. 3
Simulated CD4+ T-Cell Recovery after Antiretroviral Therapy by Age Group. CD4+ T-cell count at 5th, 25th, 50th, 75th and 95th of the simulations (represented by the whiskers and horizontal lines of the boxplots) of each age group at time after treatment are presented. The median CD4+ T-cell counts are indicated for each group. Dotted line at 500 cells/μL is chosen as the index for CD4+ T-cell count recovery. The percentages of the simulated subjects achieving immune recovery are indicated for each group on the top of the figure
Fig. 4
Fig. 4
Post Hoc Analysis of CD4+ T-Cell Dynamic Parameters. σ: production rate of naïve T-cells, α: activation rate constant of naïve T-cells that acquire a memory phenotype, dN: naïve T-cell death rate constant, dM: memory T-cell death rate constant. %CD31 on naïve CD4+ T-cells defines thymus output of naïve CD4+ T-cells, %PD-1/TIM-3 coexpression defines immune exhaustion. P values from the linear regression for each relation are indicated
Fig. 5
Fig. 5
Cartoon Illustration of the Establishment of the CD4+ T-Cell Pool. N: naïve T-cell pool size, M: memory T-cell pool size, σ: Thymus production of naïve T-cells, α: activation of naïve T-cells that acquire a memory phenotype, dN: naïve T-cell death, dM: memory T-cell death, pN: naïve T-cell proliferation, p0N: maximum proliferation of naïve T-cells, p0M: maximum proliferation of memory T-cells, h: pool size at half maximum proliferation; r: clonal size resulting from activation of a single naive T cell
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