In the late 1980s, the expression of CD38 on CD8+ T cells was described as a useful marker in determining progression to AIDS (e.g., [1,2]). Since then, the utility of activation markers as indicative of improvement or disease progression has been studied extensively. With the advent of highly active antiretroviral therapy (HAART), focus has shifted to determining whether activation markers and in particular CD38 on CD8+ T cells could augment our ability to determine whether therapy has had an optimal impact on CD4 recovery. Numerous studies looked at the correlation of viral load and expression of activation parameters finding that as viral load decreases so does cell activation [3,4]. For individuals on long-term suppressive HAART, CD38 expression on CD8+ T cells alone does not seem to correlate with CD4 T-cell recovery [5–7]. Although these and other studies have evaluated recovery of the memory population as a function of CD4 cell count and activation, they have not separated out whether specific changes in the central memory subset are correlated with CD8 activation in long-term virally suppressed patients.
The importance of the CD4 central memory population in terms of the maintenance of T-cell homeostasis has become an area of increasing focus for researchers studying HIV. Recent data have demonstrated in SIV-infected macaques that the ultimate loss of CD4 effector memory is in large part driven by lack of replenishment of this compartment by CD4 central memory cells . Other data have demonstrated that vaccinated macaques survive longer when they have preserved CD4 central memory cells  and that HIV-1 viral controllers tend to preserve CD4 central memory  further strengthening the contention for a pivotal role for central memory in preservation and reconstitution of host immunity.
The fact that recovery and stabilization of memory and naive cell populations occurs after continued antiviral suppression (e.g., ) suggests that evaluation of activation of CD8 cells may be more coupled to particular memory/naive cell subsets rather than the CD4 population as a whole. As such, in this study CD38 expression was evaluated on CD8+ T cells in a cohort of persistently virally suppressed patients as a function of memory and naive subsets.
Materials and methods
Participants and study
HIV-1-infected patients followed in the adult HIV outpatient clinics at the Jackson Memorial Hospital (JMH)/University of Miami Medical campus were considered for participation in the study if they had stable, plateau CD4 cell counts (<50 cells/μl increase) and a non-detectable viral load (<50 copies/ml) for a period of 1 year or more. Patients were included if they were on a non-nucleoside reverse transcriptase inhibitor (NNRTI) or protease inhibitor containing HAART regimen. Patients gave informed consent (approved by the Human Institutional Review Board of the University of Miami) to participate. Medical records were used to extract information on CD4 cell count, viral load, and medical history. All patients were hepatitis C negative.
CD4 cell count and viral load measurements
In general, absolute CD4 cell counts and viral load measurements (Roche Amplicor Assay, Mannheim, Germany) were performed at the JMH/University Diagnostic Pathology Laboratories. The sensitivity of the ultrasensitive assay is 50 copies/ml. For individuals with a previously measurable viral load, the laboratory uses a standard assay (<200 copies/ml) to report the viral load.
Fluorescent antibodies, phycoerythrin-anti-CD4, phycoerythrin-anti-CD8, fluorescein isothiocyanate (FITC)-antihuman leukocyte antigen DR-1 (HLADR), APC-anti-CD38, PerCP-anti-CD3, AlexaFluor-anti-CCR7, FITC-CD45RA, and isotypic controls were obtained from BD PharMingen (San Diego, California, USA). FACS lysing solution was obtained from Becton-Dickinson (San Jose, California, USA).
Whole blood was collected in EDTA-containing tubes. Freshly isolated blood was used to determine cell activation.
Phenotypic determination of activation and memory subsets by flow cytometry
After collection, 50 μl of whole blood was aliquoted into 6 ml FACS tubes and fluorescent antibodies added as a cocktail as determined by experiment for activation (CD3:CD8/4:CD38:HLADR) or memory cell subsets as defined phenotypically (see ; CD3:CD4/8:CCR7:CD45RA) along with isotypic controls. After vortexing, the tubes were incubated for 10 min on ice with the antibodies. This incubation was followed by addition 450 μl of the 1 × lysing solution. Following the manufacturers' protocol, cells were kept at room temperature for 10 min and then refrigerated (4°C) until ready to run on the FACS within 24 h. Cells were removed from the lysis buffer by centrifugation and fixed with 4% paraformaldehyde in buffered phosphate buffered saline for 15 min at 4°C. After fixing, the cells were washed twice with FACS buffer before flow cytometric analysis. In general, 30 000–40 000 events were collected in the lymphocyte gate by forward scatter (FSC) and side scatter (SSC). CD3 and CD8/4 gating subsequently defined the specific T-cell populations that were further analyzed in terms of activation markers. The percentage of cells positive for various markers was determined by those with fluorescence above the isotypic control.
Prism 4 Statistical package (GraphPad Software, Inc., San Diego, California, USA) was used to determine linear regression curves.
Table 1 gives the general demographic and immunologic information for the patients. Of the 13 patients studied, 12 were on an NNRTI-containing regimen and one on a ritonavir-boosted protease inhibitor-containing HAART regimen. Nine patients were men. There were five African–American, one Haitian and seven Hispanic patients. The median age was 51 years. All patients had durable viral load suppression with a median time of suppression of 5 years (Table 1). Information on CD4 cell counts at the time of western blots was available on 11 of 13 individuals. The median CD4 cell count at time of HIV diagnosis for the 11 patients was 28 cells/μl.
CD4 cell count and dependence on memory/naïve phenotype
Figure 1a shows the absolute number of memory/naive cells as a function of their absolute CD4 cell count. The number of effector memory CD4+ T-cells (CD4EM = CCR7−CD45RA−CD4+CD3+) is independent of the absolute CD4 T-cell count (r = 0.095, P = 0.759) whereas both CD4CM (CD4CM = CCR7+CD45RA−CD4+CD3+; r = 0.87, P = 0.0001) and CD4N (CD4N = CCR7+CD45RA+CD4+CD3+; r = 0.85, P = 0.0002) are significantly correlated with the absolute CD4 T-cell count (Fig. 1a). From these data, it is apparent that as the CD4 T-cell count increases the proportion of both the naive and central memory populations increase with a proportional decrease in the percentage of effector memory.
CD4 T-cell memory/naïve phenotypes and CD38+CD8 T-cells
When the percentage of positive CD8 T-cells with activation parameters CD38, HLADR, or both was plotted as a function of absolute CD4 T-cell number, there were no specific correlations found (data not shown). However, when the percentage of CD8+CD38+ T cells is viewed in terms of CD4 memory subsets, a significant negative correlation was found between the percentage of CD38+CD8 T-cells and the percentage of CD4CM T-cells (Fig. 1b; r = −0.85, P = 0.0003). The percentage of CD8+CD38+ T cells also correlated with the absolute number of CD4CM T-cells (Fig. 1c; r = −0.78, P = 0.0016) but not the absolute number of CD4N or CDEM populations (P = 0.354 and 0.874, respectively). When other activation subsets were evaluated, the percentage of CD8+HLADR+ T cells correlated positively with CD4CM (r = 0.61, P = 0.027) but not CD4N (P = 0.93) or CDEM (P = 0.79). As such, when all three subsets are combined into the absolute CD4 T-cell count, there was a trend toward significance with the percentage of CD8+CD38+ T cells (r = 0.55, P = 0.054). The CD4 T-cell nadir (available for 11 patients) did not correlate with either percentage of CD4CM or that of CD8+CD38+ T cells (P = 0.176 and 0.216, respectively).
The present study is the first to demonstrate a strong negative correlation between the percentage of CD4 central memory and percentage of CD8+CD38+ T cells in patients with viral load suppression for greater than 1 year. This finding is important because in both adult and pediatric populations, the percentage of CD8+CD38+ T cells or the level of CD38 expression on CD8 cells is not predictive of the level of CD4 T-cell reconstitution after sustained viral load suppression [5–7]. Although this finding is borne out in our study, the importance of evaluating activation in regards to specific memory/naive subset populations and not the total CD4 T-cell count is substantiated by the strong correlation between CD4 central memory and CD8 activation.
The correlation between CD38 on CD8 T cells and CD4 central memory suggests factors impacting on activation are coupled to those responsible for the recovery of central memory. In individuals with low CD4 cell counts, homeostatic cytokines such as interleukin-7, for example (e.g. ), may drive enhanced replication in the central memory population. For those with high CD4 cell counts, replication may be lower in the central memory cell pool in part because of less cell turnover that results in lower activation [14,15].
Over the last few years, a number of studies have implicated CD4 central memory as an important determinative for loss/preservation of CD4 T-cells during HIV or SIV infection [8–10]. In SIV-infected Rhesus Macaques, the inability to maintain CD4 central memory results in loss of CD4 effector memory resulting in eventual disease progression . In SIV-infected macaques that were vaccinated, survival was coupled to persistence of CD4 central memory . On the contrary, in sooty mangabeys, CD4 central memory cells were found to be relatively resistant to anergy that may, in part, be responsible for their resistance to SIV disease . In humans, a recent study  has shown that CD4 central memory is elevated in HIV controllers compared with infected individuals with viral loads, or on HAART. These data suggest that the preservation of CD4CM is important in disease progression but do not address its role in CD4 T-cell recovery while on HAART.
The data provided in the current work suggest that ultimate recovery of CD4 T-cell counts is dependent on both the naive and central memory populations. Multiple groups have described recovery of the naive CD4 population while on HAART (e.g. [17,18]) and to the central memory compartment . Evidence for the importance of the CD4N population in supporting recovery of CD4CM from low CD4 T-cell nadirs in HIV can be inferred from a number of studies that have looked at immune responsiveness as a function of low CD4 T-cell nadir [20,21]. In general, the response to recall antigen is blunted in patients who have recovered their CD4 cell counts from a low CD4 T-cell nadir  and may be due to failure of the CD4CM to respond to recall antigen . Additional data demonstrating the importance of these subsets come from work showing that immune responsiveness to vaccination was correlated with the CD4+CD28+ T cells  that contain both CD4CM and CD4N populations. The researchers demonstrated that though prevaccination responsiveness to recall antigen may be low, consistent with the aforementioned studies, vaccination improved cell-mediated responsiveness for numerous antigens . Together, these studies suggest that the recovery of CD4 population from a low CD4 T-cell nadir is due to both CD4CM and CD4N as described here.
As such these data show that CD8 cell activation may be important in CD4 T-cell reconstitution coupled through the central memory subset for patients with a low CD4 T-cell nadir. The role of homeostatic cytokines in this process and their participation in CD4 T-cell recovery, as determined by subset stratification, should be evaluated further.
The author would like to thank Ms. Maria Saenz for technical assistance.
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