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Highly Active Antiretroviral Therapy Restores CD4+ Vβ T-Cell Repertoire in Patients With Primary Acute HIV Infection But Not in Treatment-Naive HIV+ Patients With Severe Chronic Infection

Cossarizza, Andrea MD, PhD*; Poccia, Fabrizio PhD; Agrati, Chiara PhD; D'Offizi, Gianpiero MD; Bugarini, Roberto DrStat*; Pinti, Marcello PhD*; Borghi, Vanni MD; Mussini, Cristina MD; Esposito, Roberto MD; Ippolito, Giuseppe MD; Narciso, Pasquale MD

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JAIDS Journal of Acquired Immune Deficiency Syndromes: March 1, 2004 - Volume 35 - Issue 3 - p 213-222
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In patients infected with HIV, potent highly active antiretroviral therapy (HAART) can limit the extent of viral replication and block the progressive loss of CD4+ T cells. HAART also increases the number of peripheral CD4+ T cells, following a biphasic course. The first phase is characterized by the onset of memory cells derived from the redistribution of CD4+ T cells that migrate from lymphoid tissues to blood. In the second phase, newly formed virgin T cells arise, which may originate from within the thymus. As a result, CD4+ T cells increase to levels that are capable of protecting hosts from various HIV-related pathologies.

To achieve increased CD4+ T cells, it is crucial that their reconstitution is homogeneous and functionally efficient. An effective immune reconstitution is possible only if new naive T cells with a wide repertoire are generated. Previous studies have been designed to assess the impact of HAART on the immune system. With some notable exceptions, HIV-induced impairment of immune functions is relatively stable. 1,2 With respect to CD8+ T cells, independent investigators have indeed analyzed the T-cell repertoire in chronically infected patients. Martinon et al 3 found that in 16 patients who were not naive for antiretrovirals (previously treated with zidovudine and lamivudine), CD8+ cell repertoire alterations were profound after 1 year of HAART, whereas CD4+ cell alterations were moderate. The dynamics of CD8 T-cell expansions during HAART have been studied by Kostense et al. 4 They analyzed complementary determining region 3 (CDR3) spectratyping and single-strand conformation polymorphism, in combination with sequencing, to assess clonality of the expanded subsets. In 4 patients treated with ritonavir, zidovudine, and lamivudine who fully responded to the therapy, they found that HAART induces changes in CD8 T-cell receptor (TCR) diversity, eventually resulting in improvement of the repertoire. Before therapy, a few clonal expansions were observed in lymph nodes that were present in peripheral blood after therapy, suggesting that recirculation of CD4 and CD8 T cells from lymph nodes contributes to the early T-cell repopulation. Moreover, decreased immune activation and naive T-cell regeneration could decrease clonal expansions and perturbations in the CD8 TCR repertoire. King and Larsson Sciard 5 performed a longitudinal analysis of the CD8+ TCR Vβ repertoire in HAART-treated and untreated HIV patients. They found that HAART did not prevent perturbations within the CD8+ Vβ repertoire in both groups as defined by CDR3 spectratyping.

With respect to the CD4+ T-cell repertoire, Kostense et al 6 found an increased perturbation of CDR3 patterns in CD4+ T-cell subsets during the first period of therapy in a few patients treated with HAART, suggesting an early oligoclonal repopulation. At later time points, CDR3 size diversity increased when T-cell counts did not substantially decrease. In contrast, in 20 patients with chronic HIV infection who were naive for protease inhibitors, Giovannetti et al 7 found that T-cell repertoire perturbations were not restored after 12 months of successful antiretroviral treatment.

All these studies suggest 2 areas of investigation. First, understanding details and characterizing the immune reconstitution are of crucial importance for the relevant fundamental immunologic questions related to the role of the thymus in adult patients. 8 Second, there are practical clinical queries regarding the necessity for continuing prophylaxis against opportunistic infections. These answered, of course, would reveal the time when HAART can be stopped in patients experiencing acute primary infection.

We therefore investigated the capacity of HAART to restore the T-cell repertoire in 2 groups of HIV+ patients who were naive for antiretroviral therapy. The first was composed of individuals who came to clinical observation because they developed acute HIV infection. The second consisted of patients who had HIV infection for many years but never took protease inhibitors or other antiretrovirals. Using molecular and cellular techniques, we followed the changes in Vβ T-cell repertoire with time and found that HAART restored the CD4+ T-cell repertoire in patients with acute but not chronic infection.


Patient Characteristics and Blood Collection

We studied a total of 24 patients with chronic infection and 18 with primary acute infection. Acute infection was diagnosed according to the well-established criteria 9 used in our previous studies. 10–14 Mean age was 36 years (range: 30–47 years) in the group of chronic HIV+ patients and 30 years (range: 18–45 years) in the group of patients with acute HIV infection, median plasma viral load value was 60,440 copies/mL (range: 400–500,000 copies/mL) in the first group and 81,350 (range: 1200–1,475,000 copies/mL) in the second, and median CD4 count was 165 cells/μL (range: 10–1204 cells/μL) in the first group and 341 (range: 52–1307 cells/μL) in the second. Twenty-one of the 24 patients with chronic infection were studied during the first visit for HIV infection (ie, when they were found positive and were taking no drug). Three patients already knew themselves to be HIV-positive but had refused any clinical control and any antiretroviral drug, including protease inhibitors, in the previous 3 to 4 years and thus were considered naive. Similarly, of the other 21 patients, 2 of them came back to our attention because of relevant clinical signs and were enrolled in this study.

As controls, we analyzed 10 seronegative donors of the same age as the HIV+ individuals, randomly chosen among medical students and personnel. Their mean age was 33 years (range: 21–44 years). All individuals gave informed consent for the studies reported in this article.

Harvesting Peripheral Blood

Peripheral blood (10–20 mL) was collected at the time of the first observation and then after 1, 3, 6, and 12 months during follow-up of routine clinical, hematologic, and virologic controls. Control subjects donated blood on the same time schedule. In a few cases, lymphocytes were separated using standard methods and immediately stored in liquid nitrogen; in most cases, cells were immediately stained and analyzed. The process of freezing and thawing peripheral blood mononuclear cells (PBMCs) did not provoke any alteration in cytometric analysis as already described. 15

Flow Cytometry and Analysis of Vβ T-Cell Repertoire

Flow cytometric analysis was performed following staining of either whole blood or thawed PBMCs with fluorochrome-labeled monoclonal antibodies (mAbs) according to standard methods largely used by our group in the past years. 16 Peripheral blood lymphocytes (PBLs) were then identified on the basis of their physical characteristics (forward scatter [FSC] and side scatter [SSC], respectively). The percentage of monocytes present in the lymphocyte gate was calculated taking into account the expression of CD14 and was always negligible (not shown). Anti-CD14 mAbs were from Pharmingen (San Diego, CA).

The T-cell repertoire was studied by 3-color flow cytometry using fluorescein isothiocyanate (FITC), phycoerythrin (PE), or FITC plus a panel of PE-labeled mAbs (Io Beta test; Immunotech, Marseilles, France) recognizing different TCR Vβ families (anti-Vβ1, clone BL37.2; anti-Vβ2, clone MPB2D5; anti-Vβ3, clone CH92; anti-Vβ5, clone 3D11 recognizing Vβ5.3; anti-Vβ5.1, clone IMMU 157; anti-Vβ8, clone 56C5.2; anti-Vβ9, clone FIN9; anti-Vβ11, clone C21; anti-Vβ12, clone VER2.32.1; anti-Vβ13.1, clone IMMU 222; anti-Vβ13.6, clone JU74.3; anti-Vβ14, clone CAS1.1.3; anti-Vβ16, clone TAMAYA1.2; anti-Vβ17, clone E17.5F3.15.13; anti-Vβ18, clone BA62.6; anti-Vβ20, clone ELL1.4; anti-Vβ21.3, clone IG125; anti-Vβ22, clone IMMU 546; and anti-Vβ23, clone AF23) and anti-CD4 or anti-CD8 mAbs conjugated with Quantum Red. Parallel samples were prepared with anti-CD8 and anti-CD3 mAbs to be sure that all the CD8+bright cells were T lymphocytes. For the analysis of Vβ expression among CD4+ or CD8+bright T cells, an electronic gate was set on these cells and at least 5000 events per sample were collected. Three-color cytofluorimetric analysis was performed using a CyFlow ML flow cytometer (Partec GmbH, Münster, Germany) or a FACSCan or FACSCalibur flow cytometer (both from Becton Dickinson, San Jose, CA) as previously described. 17 Cases with values greater than 1.5 box length from the upper edge of the box were considered expansions (the box length represents the interquartile range [IQ]).

In 6 representative individuals from each group, we obtained about 30 mL of blood; thus, we could analyze the clonality of the repertoire by measuring the length of the CDR3 in CD4+ or CD8+ T cells separated with magnetic beads (MACS; Miltenyi, Germany) as previously described. 7 A perturbation in a given family was defined as the lack of expression or the increased expression of a given CDR3 length (ie, when a peak had more than 40% of the total area 18); the distribution of CDR3 lengths was considered normal when a pseudo-Gaussian distribution was present. 3,19

Isolation of Lymphocytes and Stimulation With Superantigens

Lymphocytes were isolated from freshly collected peripheral blood according to standard methods, cultured in complete medium (RMPI 1640 with 10% fetal calf serum, 2 mM of l-glutamine, 100 IU/mL of penicillin, and 100 μg/mL of streptomycin), and kept at 37°C in humidified atmosphere (5% co2 in air) for 72 hours in the presence of different superantigens (SAgs). 16 The following molecules derived from Staphylococcus aureus were used: staphylococcal enterotoxin (SE)-A, SE-C1, SE-C2, SE-D, SE-E, exfoliative toxin A (EXFT), and toxic shock syndrome toxin-1 (TSST-1). All were from Toxin Technology (Sarasota, FL) and were stored and used at a final concentration of 50 ng/mL according to the manufacturer's instructions. At the end of the incubation period, cells were pulsed with 0.5 μCi per well (Amersham; Aylesbury, UK) for 6 hours. Cultures were harvested (Skatron Instuments, Lier, Norway), and the radioactivity was measured using a β-counter (Gamma 5500; Packard, Downer Grove, IL) as described previously. 20 The stimulation index of each individual was calculated as counts per minute (cpm) of SAg-stimulated cultures divided by cpm of control unstimulated cultures.

Plasma Viral Load

Quantifications of plasma viral load were performed in all patients first by using branched DNA (bDNA) assay (Chiron, Emeryville, CA; 500 copies/mL limit of detection) and then by the ultrasensitive bDNA assay (Chiron; 50 copies/mL limit of detection) according to the manufacturer's instructions. In some patients with acute syndrome, plasma viremia was detected by nucleic acid sequence-based amplification (NASBA) (Organon Teknika, Boxtel, The Netherlands; 80 copies/mL limit of detection).

Statistical Analysis

Changes in CD4+ and CD8+ T-cell count and in plasma viral load and differences in repertoire among the 3 groups were analyzed.

Changes in CD4+ and CD8+ T-cell count and in plasma viral load over time were analyzed by analysis of variance for repeated measures, taking into account all the time points investigated. The same assay was employed to analyze changes in the response to SAgs. To analyze the T-cell repertoire, we developed an original approach. The differences between each of the 3 groups of individuals (acute and chronic patients and healthy controls) before treatment (time 0) were evaluated in 2 ways. First, the percentage of CD4 and CD8 cells in each family was considered as the response variable in an analysis of variance for repeated measures, with each patient as a block. The same comparisons were made using the absolute values of CD4 and CD8 cells per family, adjusting for the total number of CD4 and CD8 cells. In this case, analysis of covariance for repeated measures was used, because analysis of variance does not allow the entrance of continuous covariates in the model. Box and whisker plots were used to represent the distribution graphically at time 0 of CD4 and CD8 cells by family for each group (see below).

Evaluation of differences among the 3 groups over time was done using mixed models for repeated measures. The response variables were the percentage of CD4/CD8 cells per family and the absolute number of CD4/CD8 in each family, adjusted for the total number of CD4 and CD8 cells to mitigate the bias arising from small sample size and/or the nonrandomized enrollment of patients. In addition to the response variables for CD4 and CD8, the following variables were included in each model: patient group (acute, chronic, and control), Vβ family (1–22), time of measurement (in months after time 0), and terms for possible interactions (time-family, time-group, and group-family). An autoregressive autocorrelation structure of the first order was used within each nesting level, but the analyses were also evaluated with more robust correlation structures. Given the complexity of the study design, the interaction time-family (slope) and baseline levels of CD4 and CD8 cells (intercept) were considered as random effects.

Statistical Software

All the analyses were done using the “Proc. Mixed” procedure of the statistical software SAS, version 8.0 (SAS Institute, Cary, NC); the algorithm we wrote for this purpose is available for those interested. This software also generated the box and whiskers graphics: the boxes extend from the 25th percentile (x[25]) to the 75th percentile (x[75]) (IQ); lines inside boxes represent median values. 21 Lines emerging from boxes (whiskers) extend to the upper and lower adjacent values. The upper adjacent value is defined as the largest data point ≤x[75] + 1.5 × IQ, and the lower adjacent value is defined as the smallest data point ≥x[25] − 1.5 × IQ. Black circles represent outliers (ie, values >1.5 × IQ).


Clinical and Immunovirologic Characteristics

Clinical and immunovirologic characteristics of patients and their antiretroviral therapy at the beginning of the observation period are shown in Table 1. Even if the mean age of the 2 groups of HIV+ patients was statistically different (P < 0.05 by Student t test), we suggest that such a difference (6 years) can be considered substantially negligible with respect to age and the immune response. As shown in Figure 1, HAART was efficient in both acute and chronic patients. Indeed, in both groups, we observed a significant decrease in plasma viral load and an increase in CD4+ T cells (P < 0.01), which was much more marked in acute patients, however.

Characteristics of the Patients
Changes in the percentage and absolute number of CD4+ and CD8+ T lymphocytes and in plasma viremia in patients with acute (Ac) or chronic (Chr) HIV infection. * P < 0.01 by variance analysis (considering all times).

Analysis of the T-Cell Repertoire Among CD4+ and CD8+ T Lymphocytes in Patients With Acute or Chronic Infection and in Controls

Using a large panel of mAbs, we analyzed the T-cell repertoire among CD4+ and CD8+ T lymphocytes in the 3 groups. Figure 2 shows a representative example of 3-color fluorescence cytofluorimetric analysis of the Vβ TCR repertoire in CD4+ T cells from a patient with chronic infection. First, T helper lymphocytes were identified on the basis of their physical characteristics (low side scatter) and high CD4 expression (see Fig. 2, upper left panel). Second, an electronic gate was set on these cells to detect the fluorescence signal from the anti-Vβ mAbs conjugated with FITC, PE, or both (see Fig. 2, upper right and lower panels) and thus to calculate the percentage of cells with a given Vβ TCR among the population of CD4+ lymphocytes.

Representative example of cytofluorometric analysis of the T-cell repertoire in CD4+ T cells. Upper left panel, an electronic gate was set on the basis of physical parameters (side scatter) and CD4 expression (detected in fluorescence channel 3) to identify T helper lymphocytes. Upper right and lower panels, the positivity of such cells to different anti-Vβ monoclonal antibodies (mAbs) (namely, the presence of a different Vβ T-cell receptor [TCR]) was then detected in 2 other fluorescence channels, taking advantage of the possibility to use mAbs labeled with fluorescein isothiocyanate, with phycoerythrin, or with both fluorochromes. Numbers in the quadrants indicate the percentage of cells expressing a given Vβ TCR.

Figure 3 shows the distribution of the Vβ T-cell repertoire on CD4+ (left column) and CD8+ (right column) lymphocytes in the 3 groups at time 0 (ie, before the beginning of therapy). Data are expressed as percentage of CD4+ (or CD8+) T cells with a given Vβ TCR. It is noteworthy that a consistent number of expansions were present among either CD4+ or CD8+ T lymphocytes from all HIV+ patients and that at least 1 expansion, evenly distributed among the Vβ subsets, was found in the majority of subjects (not shown). Table 2 shows the number of expansions present among CD4+ or CD8+ T cells at the beginning of the study and after 12 months. The values and percentages reported in Table 2 are referred to the total number of cytofluorometric determinations performed in each group at each time.

Expansions Present Among CD4+ and CD8+ T Cells at the Beginning of the Study and After 12 Months in Control Donors and in HAART-Treated HIV+ Patients
Distribution of the different T-cell receptor Vβ families among CD4+ (left panels) and CD8+ (right panels) T lymphocytes from healthy controls (CTR, upper panels) and patients with acute (Ac, middle panels) or chronic (Chr, lower panels) HIV infection at the beginning of the study. The boxes extend from the 25th to the 75th percentile (ie, the interquartile range [IQ]); lines inside boxes represent median values. The whiskers extend to the upper and lower adjacent values; black circles represent outliers (ie, those with values greater than 1.5 × IQ, which were considered expansions).

Several Expansions Characterize the Repertoire of Untreated Patients With Acute or Chronic Infection

Statistical analysis of the aforementioned cytofluorimetric data (ie, relative to changes of T-cell repertoire over time) is reported in Tables 3 and 4. It is noteworthy that at the beginning of therapy, patients with either acute or chronic infection had a repertoire characterized by the presence of several expansions (see Fig. 3) and significantly different from that of healthy controls (as revealed by the analysis shown in Table 3). In contrast to acute patients, those with chronic infection had a CD4+ T-cell repertoire that remained significantly different from that of healthy controls after therapy (see Table 3).

Differences in T-Cell Repertoire Among Patients During Primary Acute Infection, Patients With Chronic Infection, and Healthy Controls
Effects of the Antiretroviral Treatment (or of the Time in the Case of Healthy Controls) on T-Cell Repertoire

The effect of the treatment and time (or time only in the case of healthy controls) within each group is shown in Table 4. In patients with acute infection, highly significant changes were present among CD4+ and CD8+ T cells. Patients with chronic infection had a modification in the CD8+ cell repertoire only; such a change is largely due to the reduction of the expansions observed during the entire period of therapy (not shown).

Presence of Perturbations Within Each Vβ Family Revealed by Measuring CDR3 Length

In a representative number of patients and controls, we analyzed the presence of perturbations within each Vβ family by measuring the distribution of the CDR3 length. Figure 4 (upper panel) reports a representative example of a patient with acute infection in whom, at the time of the first observation, an alteration was present among the Vβ2 (left column) but not the Vβ5.1 (right column) family of CD8+ T cells. This alteration disappeared after 3 months of therapy. Also in Figure 4 (lower panels), we indicate the number of perturbed families present in these patients and controls over time. It is noteworthy that the perturbed families were more frequently represented among CD4+ lymphocytes in patients with chronic infection and among CD8+ T cells in patients with acute infection.

Analysis of the perturbations of Vβ families in 6 subjects for each group. Upper panels, a representative example in magnetically isolated CD4+ lymphocytes from a patient with acute infection regarding the spectratype of 2 Vβ families, which was detected by measuring the length of the T-cell receptor third complementary region. This subject presented a perturbation among Vβ2 but not Vβ5.1 CD4+ T cells at the beginning of the study (ie, at time 0; such perturbation is revealed by the presence of a non-Gaussian distribution of the peaks); after 6 months, this perturbation was no longer present. Lower panels, the number of perturbed families present in the 3 groups and their changes with time. Open squares, acute HIV patients; closed triangles, chronic HIV patients; closed circles, healthy controls. A statistically significant decrease in the number of perturbed families (P < 0.05 by variance analysis) was observed only in patients with acute infection.

Functional Analyses of Vβ T-Cell Repertoire Using a Large Panel of Superantigens

In PBLs from patients with acute infection, we performed functional studies on the Vβ T-cell repertoire using a large panel of SAgs (Fig. 5). These molecules bind different Vβ families with different capacity and are able to stimulate T-cell proliferation. 10,16 In all cases, therapy provoked a consistent and significant increase in the capability to respond to SAgs (P < 0.05 after 6 months of therapy and P < 0.01 after 12 months), suggesting that the functional defects in Vβ-specific T-cell proliferation present during primary infection can be restored in parallel with the improvement of the TCR repertoire.

Functional analysis of different Vβ families. Lymphocytes from patients with acute HIV infection were stimulated with different Staphylococcus aureus enterotoxins cultured for 72 hours and pulsed with tritiated thymidine; data indicate the simulation index (mean ± standard deviation). A statistically significant increase in the response to all superantigens was observed after 6 and 12 months of therapy (P < 0.05 and P < 0.01, respectively, by variance analysis).


Analysis of the TCR repertoire can be useful to understand and evaluate the immunologic effects of HAART, which provoke a significant decline in the frequency and magnitude of perturbations in the CD8+ T-cell subset. 1,2 Indeed, the expansions of cytotoxic T lymphocytes (CTL) that are frequently observed, especially during primary infection, 22 can disappear for 2 reasons: because the expanded clones have exhausted their activity and undergo apoptosis or because of clonal deletion induced by high levels of viral antigens. 23 In contrast, HAART has variable effects on the normalization of the CD4+ T-cell repertoire, reflecting individual differences in the rate of regeneration and redistribution of CD4+ T cells from the central and peripheral lymphocyte pools. 24,25 Such studies are extended by our analysis, which was performed with a sophisticated methodologic approach that allows the acquisition of other substantial information. Several techniques have been employed to investigate the T-cell repertoire, 26–37 but flow cytometry can be considered the “gold standard” technique for these studies. The interpretation of data still represents 2 main problems: analyses of results often do not consider the repertoire in its complexity and extensiveness, and analyses are performed by simplistic statistical tests.

We have developed a novel integrated view to analyze T-cell repertoire based on an original statistical approach that makes use of the mixed models. Such an approach provides unbiased information not only on single effects, such as percentage variation(s) in individual families over time and average changes in individual patients, but allows for the evaluation of the effect of treatment in the groups independently of time and the composition of individual subfamilies. This approach was chosen because it not only allows a nested design of the analysis of the Vβ families within each patient but avoids bias due to the possible different number of measurements per patient, utilizing an autocorrelation structure. In addition, this method controls for the influence that a change in a given Vβ family has on the other families. Indeed, the model automatically adjusts for the fact that a large increase in 1 family necessarily results in a reduction in the relative value of other families. Finally, the model gives a unique value (expressed as P) that is extremely easy to understand and can describe not only the differences in the entire repertoire between 2 groups of individuals but its changes with time.

Data obtained by flow cytometry were fully corroborated by CDR3 spectratyping, which we could perform in some representative subjects per group. Indeed, we found a consistent number of perturbations among CD8+ T cells in acute patients at the beginning of therapy and an even higher number among CD4+ T cells from chronic patients. Therapy could restore the former but not the latter perturbations.

We have examined the HAART-related changes in the T-cell repertoire in 2 groups of patients naive for antiretrovirals (ie, some individuals who were recruited during acute primary infection and some subjects who came to our attention only in an advanced stage of the disease). The main finding is that HAART was capable of fully restoring the T-cell repertoire only in patients who have been treated during the acute phase of primary infection. In patients who received therapy in an advanced stage, a significant change occurred only among CD8+ T cells, whereas CD4+ T lymphocytes continued to show consistent alterations. We followed some of these patients for 24 months of therapy and found no difference from the previous time points (not shown).

The observations we report here introduce different problems, the first of which is related to the length of treatment after primary infection. Initiation of antiretroviral therapy during this phase of the infection induces a rapid stabilization of the T-cell repertoire and reduces the levels of oligoclonality, 38 with such an effect being especially evident on CD8+ T cells. 39 Our data confirm this observation and show that from a functional point of view, these patients could restore the capability to respond well to SAg stimuli.

A second problem is related to the fact that even if HAART-related reconstitution of the T-cell repertoire was not optimal in chronic patients, no opportunistic infections occurred in the patients we studied, even if they suspended secondary prophylaxis when the peripheral CD4+ level was higher than 200 cells/μL. 40 This suggests that even a relatively skewed T-cell repertoire could be functionally sufficient to cope with different pathogens.

Third, changes in T-cell repertoire can be viewed as a normal result of a generalized T-cell recruitment and expansion process associated with the necessity of developing a primary antiviral cell-mediated immunity. This has been shown for several viral diseases besides HIV, including simian immunodeficiency virus (SIV) infection, measles, and infectious mononucleosis. 41,42 Thus, it is possible that the perturbations we observed were the result of other clinical or subclinical situations and were caused by the emergence of primary antiviral cell-mediated immunity against agents other than HIV.

In conclusion, our data suggest that in naive patients with advanced infection, HAART is capable of restoring perturbations of the repertoire only among CD8+ T cells. In patients treated immediately after primary infection, HAART induces a full recovery of the T-cell repertoire; thus, our observations further stress the role of treatment of primary infection, even if the optimal treatment of this condition and its length are still a matter of debate. 43 Transplant studies reveal that CD4+ reconstitution is less rapid than that of CD8+ T cells 44,45; thus, it may take much longer than 1 year in chronic patients. The follow-up of the persons described in this study will allow further investigation of this aspect of the problem.


We acknowledge Antje Necker (Immunotech, Marseilles, France) for providing anti-Vβ mAb and Professor Edwin L. Cooper (University of California at Los Angeles, Los Angeles, CA) for helpful discussions and critical reading of the manuscript.


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HIV; AIDS; T-cell repertoire; Vβ; HAART; protease inhibitors

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