Regulatory T cells in human immunodeficiency virus-infected patients are elevated and independent of immunological and virological status, as well as initiation of highly active anti-retroviral therapy

Abstract

Infection with human immunodeficiency virus (HIV) causes a dysregulation of the immune system. This is caused by HIV-specific as well as non-specific mechanisms and has not been explained fully. In particular, knowledge is lacking about the potential role of host-mediated immunosuppressive mechanisms. During recent years it has become evident that a subpopulation of T cells [T regulatory (T_regs)] play a major role in sustaining tolerance to self-antigens. To investigate the influence of initiation of highly active anti-retroviral therapy (HAART) on the T_reg level in HIV-infected patients we have conducted a prospective study enrolling treatment-naive HIV-infected patients just prior to starting treatment with HAART, measuring levels of T_regs by flow cytometry and mRNA expression of forkhead box P3 (FoxP3) at weeks 0, 4, 12 and 24 of treatment. In this prospective study neither the percentage of CD4⁺CD25^high+ nor the expression of FoxP3 changed significantly during 24 weeks of HAART. Furthermore, HIV patients have higher T_regs measured as percentages of CD4⁺CD25^high+ cells paralleled by higher levels of FoxP3 compared with healthy controls. The elevated level of T_regs was found to be independent of both immunological and virological status, indicating that initiation of HAART has minor effects on the T_reg level in HIV-infected patients.

Introduction

Infection with human immunodeficiency virus (HIV) is characterized by progressive immunodeficiency [1], immune activation and depletion of CD4⁺ cells [2]. Chronic immune activation in HIV infection is a strong prognostic marker for the decline in CD4⁺ cells and disease progression [1]. Disease progression in HIV-infected patients can be delayed by treatment with highly active anti-retroviral therapy (HAART). HAART results in diminished viral replication and increased number of CD4⁺ cells [3].

The dysregulation of the immune system in HIV infection has not been explained fully. Knowledge is lacking about the potential role of host-mediated immunosuppressive mechanisms. During recent years it has become evident that a subpopulation of T cells called regulatory T cells (T_regs) play a crucial role in sustaining tolerance to self-antigens [4,5]. T_regs suppress T cell activation resulting in down-regulation of immune activation, including reduction in anti-tumour immunity, graft rejection and graft-versus-host disease [6]. Finally, T_regs are believed to play a role in the regulation of chronic viral infections, including HIV. Thus T_regs are believed to be able to down-regulate the chronic immune activation seen in HIV infection, making T_regs a key element in the understanding of the interaction between the host immune system and HIV [7,8]. However, T_regs might be beneficial as down-regulators of the unbeneficial immune activation or, in contrast, they might have a harmful effect if they down-regulate HIV-specific responses [9]. So far, no studies have been able to conclude whether T_regs hasten or delay HIV infection. T_regs express CD4 and CD25 and can be identified by flow cytometry. Furthermore, the expression of the gene forkhead box P3 (FoxP3) is proposed as an accurate measurement for T_regs[10].

The present study was designed to examine associations between immunodeficiency, immune activation and levels of T_regs in HIV-infected patients. A prospective study enrolling treatment-naive HIV-infected patients just prior to starting treatment with HAART was conducted. T_regs levels were measured by flow cytometry and mRNA expression of FoxP3 at weeks 0, 4, 12 and 24 of treatment. Comparisons between HIV-infected patients with CD4 counts above and below 200 cells/µl and comparisons of HIV-infected patients to healthy controls were conducted.

Patients and methods

Twenty-six HIV-infected patients and 11 healthy controls were included from the Departments of Infectious Diseases, Copenhagen University Hospital, Hvidovre or Rigshospitalet from January 2006 to August 2006. Patients were enrolled just before starting HAART and were all naive to any anti-retroviral treatment. They were followed for 24 weeks with blood samples at weeks 0, 4, 12 and 24. Stratification of patients into two groups with CD4 counts </≥ 200 cells/µl was performed to investigate the relation between T_regs and status of the immune system. One patient was excluded from the study due to treatment interruption. HIV-negative controls were recruited from hospital personnel and were age- and sex-matched. The clinical characteristics of HIV-infected patients and controls are presented in Table 1. The study was approved by the local ethics committee and informed consent was obtained from all participants. Ethylenediamine tetraacetic acid blood was used to obtain a full blood count and for flow cytometry. Viral load was determined using COBAS AmpliPrep/COBAS TaqMan with a threshold of 40 copies/ml. Peripheral blood mononuclear cells (PBMC) were isolated from heparin blood by means of density gradient centrifugation (Histopaque, Sigma, St. Louis, MO, USA), 518 g for 25 min, were washed twice in RMPI-1640 (Gibco, Carlsbat, CA, USA) and used for enrichment of CD4⁺ cells. RNA was extracted from the CD4⁺ cells, and the expression of mRNA FoxP3 was determined by real-time quantitative polymerase chain reaction (PCR).

Table 1.

Clinical characteristics of the 26 human immunodeficiency virus (HIV)-infected patients and the 11 controls.

	Sex	Age (years)	CD4 count (cells/µl) week 0	CD4 count (cells/µl) week 24	HIV-RNA (copies/ml) week 0	HIV-RNA (copies/ml) week 24	HIV-related illness	HAART
Patient no.
1	m	44	44	246	221 000	40	PCP, Karposi's sarcoma	TDF, FTC, LPV, RTV
2	m	44	270	360	472	40		ABV, 3TC, AZV, RTV
3	m	52	74	345	1 000 000	40		ABV, 3TC, AZV, RTV
4	f	26	32	ND	106 000	ND	PCP, TB	TDF, FTC, LPV, RTV
5	m	45	51	191	40 900	40		3TC, AZT, D4T
6	m	47	217	325	433 000	40		ABV, 3TC, AZV, RTV
7	m	43	368	280	999 000	51		ABV, 3TC, D4T
8	m	43	220	455	269 000	40		TDF, FTC, LPV, RTV
9	f	31	263	655	74 500	40		3TC, AZT, LPV, RTV
10	m	35	253	429	46 300	40		ABV, 3TC, D4T
11	m	34	261	602	323 000	67	Karposi's sarcoma	ABV, 3TC, D4T
12	f	38	23	218	84 100	40		3TC, DDI, LPV, RTV
13	m	25	210	430	40 568	39		TDF, FTC, D4T
14	m	69	194	329	262 000	40		ABV, 3TC, D4T
15	m	40	55	275	747 000	40	PCP	ABV, 3TC, D4T
16	m	47	190	630	484 795	83		3TC, AZT, LPV, RTV
17	m	37	224	321	214 000	40		TDF, FTC, D4T
18	m	31	271	486	45 700	40		ABV, 3TC, D4T
19	m	27	204	321	97 600	40		ABV, 3TC, D4T
20	m	27	220	530	118 670	40		TDF, FTC, D4T
21	m	61	280	330	8 637	39		ABV, 3TC D4T
22	f	25	180	295	30 700	40		3TC, AZT, LPV, RTV
23	m	48	206	422	65 800	40		TDF, FTC, LPV, RTV
24	m	31	231	308	14 700	44		ABV, 3TC, AZV, RTV
25	m	50	143	201	1 000 000	40		ABV, 3TC, AZV, RTV
26	m	39	160	241	44 300	40		TDF, FTC, LPV, RTV
Median		40	208	329	101 800	40
Control no.
1	m	47	731
2	m	36	ND
3	f	39	698
4	m	47	1088
5	m	27	721
6	m	34	781
7	m	68	910
8	m	25	529
9	m	33	509
10	m	52	691
11	m	41	703
Median		38	712

m, male; f, female; n.d., not determined; TDF, Tenofovir; FTC, emtricitabin; LPV, lopinavir; RTV, ritonavir; ABV, abacavir; 3TC, lamivudin; AZV, atazanavir; AZT, zidovudin; D4T, efavirenz; DDI, didanosin; PCP, Pneumocystis carinii pneumonia; TB, tuberculosis; HAART, highly active anti-retroviral therapy.

Antibodies and flow cytometry

Determination of lymphocyte subsets and preparation of cells for flow cytometry were performed as described [11]. CD4⁺ cells with T_reg phenotype were determined as CD4⁺ CD25^high+ cells. The gate on CD4⁺CD25^high+ was set on the very brightest cells in the same way every time by the same observer (Fig. 1). CD4⁺CD25^high+cells were analysed in three different samples and the mean value was calculated. The number of CD4⁺CD25⁺ and CD4⁺CD25^high+ cells positive for CD45RO, CD62L, cytotoxic T lymphocyte antigen (CTLA)-4, glucocorticoid-induced tumour necrosis factor receptor family-related gene (GITR), human leucocyte antigen D-related (HLA-DR) and CD38 was determined. The number of activated CD4⁺ cells was determined as CD4⁺CD38⁺HLA-DR⁺ cells. The following monoclonal antibodies used were isotype control γ₁-fluorescein isothiocyanate (FITC)/γ₁-phycoerythrin (PE)/γ₁-peridinin chlorophyll (PerCP)/γ₁-allophycocyanin (APC), CD4-PerCP (clone SK3), CD4-APC (clone SK3), CD25-PE (clone M-A251), CD25-FITC (clone M-A251), HLA-DR-PE (clone TU36), CD38-APC (clone HIT2), CD45RO-FITC (clone UCHL1), CD62L-APC (clone D_reg 56), CTLA-4-PE (clone BNI3) and GITR-PerCP (clone DTA-1), all purchased from Becton Dickinson (Erembodegem, Belgium). All samples were analysed by four-colour flow cytometry using a fluorescence activated cell sorter (FACS)Calibur (Becton Dickinson) equipped with a 488 nm argon-ion laser and a 635 nm red diode laser. Data were processed using CellQuest Pro software (Becton Dickinson). The fluorescence of 50 000 cells was measured. To obtain the absolute number of a lymphocyte population, the percentage of cells in a lymphocyte gate expressing lymphocyte markers was multiplied by the lymphocyte count. Lymphocyte counts were performed at the Department of Clinical Biochemistry at Copenhagen University Hospital, Hvidovre.

Fig. 1.

Flow cytometric panels showing the gating strategy. (a) Side scatter and CD4. The gate is set around the population of CD4⁺ cells used for further gating of CD4⁺CD25^high+ cells shown in Fig. 1b. PerCP: peridinin chlorophyll. (b) CD4 and CD25. The gate is set around the population of CD4⁺CD25^high+ cells. PE, phycoerythrin.

Enrichment of CD4⁺ cells

CD4⁺ cells were enriched from freshly collected PBMC using a magnetic activated cell separator (MACS; Miltenyi Biotec, Bergisch Gladbach, Germany), as described previously [11]. The purity of sorted populations was determined by flow cytometry and was always > 90%. Enriched CD4⁺ cells were used for reverse transcribed (RT)–PCR.

The FoxP3 by RT–PCR

Measurement of Foxp3 mRNA, CD4 mRNA, CD8 mRNA and CD14 mRNA in separated CD4⁺ cells was performed by RT–PCR (Taqman) assay. Preparation of mRNA was performed using an automated procedure (KingFisher, Waltham, MA, USA) based on magnetic beads coated with oligo-dT. The eluted mRNA was reverse transcribed using random hexamer priming and the Taqman assay was performed using intron-spanning primer probe sets. The FoxP3 signal was then expressed relative to the CD4 signal by the delta Ct method; that is, the CD4 was used as an internal reference instead of a household gene; the CD8 and CD14 were included for contamination control. All measurements were double-determined. FoxP3 mRNA was expressed as FoxP3/CD4 delta Ct values. These were converted into relative units (RU).

Statistical analysis

Data are given as medians (minimum, maximum). Descriptive analysis was performed for all efficacy measures overall and stratified by time of measurement (weeks 0, 4, 12, 24) and patient (yes, no). Correlations between efficacy measures were calculated using Spearman's correlation coefficient for patients and controls, separately. Pearson's correlation coefficient was calculated using the original observations. The test (H0: no association) was performed using a t-distribution. Spearman's correlation coefficient was calculated using the rank transformation of the original observations [12]. Differences in development of the efficacy measures (percentages and absolute counts variable) for the patients across time were evaluated using a repeated-measurements analysis of variance. The correlation between measurements for the same individual was taken into account by including a correlation structure in the analysis. Due to a non-normal distribution of the efficacy measures, a rank-transformation of the efficacy measures was used. The assumptions for using an analysis of variance were evaluated using the Shapiro–Wilks test for normality and visual inspection of residual plots for evaluating equal variances. Comparison between patients and controls were made using Wilcoxon's two-sample test.

Results

CD4 counts and viral loads before and after initiation of HAART

To examine immune recovery upon starting treatment with HAART CD4 counts and HIV-RNA viral load were measured in all 26 HIV-infected patients at weeks 0, 4, 12 and 24. For comparison, measurements of CD4 counts were performed in controls. In patients CD4 counts increased upon initiation of HAART (median 208 cells/µl (23–368 cells/µl) at week 0, median 329 cells/µl (191–655 cells/µl) at week 24; P < 0·0001. Similarly, viral loads decreased (median 101 800 HIV-RNA copies/ml (472–> 1 000 000 copies/ml) at week 0, to median < 40 HIV-RNA copies/ml (< 40–87 copies/ml) at week 24; P < 0·0001. In controls median CD4 counts were significantly higher than in patients [712 cells/µl (509–1088 cells/µl)] both compared with week 0 (P < 0·0001) and week 24 (P < 0·0001) values.

The T_reg determination by flow cytometry and FOXP3 mRNA levels

To determine T_reg levels in HIV-infected patients upon initiation of HAART CD4⁺CD25^high+ cells as percentages of CD4⁺ cells and absolute counts were measured at weeks 0, 4, 12 and 24 and in all 11 controls.

At baseline, median percentage of T_regs in HIV-infected patients was 2·2% of CD4⁺ cells (0·4–8·5%) and remained unchanged upon initiation of HAART [2·1% (1·0–5·6%), 2·5% (0·9–4·4%) and 2·3% (1·3–4·1%) at weeks 4, 12 and 24 respectively; P = 0·524]. In controls median T_reg percentages were significantly lower than in patients [1·55% (1·4–2·0%)] compared with week 0 (P = 0·034) and week 24 (P < 0·05) values (Fig. 2a).

Fig. 2.

All data are given as medians (range). (a) Percentages of T regulatory cells (T_regs) measured by flow cytometry as CD4⁺CD25^high+ cells were significantly higher in the 26 human immunodeficiency virus (HIV)-infected patients compared with controls both when comparing week 0 (P = 0·034) and week 24 (P < 0·05) values. Percentages of CD4⁺CD25^high+ percentages did not change during treatment with highly active anti-retroviral therapy (HAART) (P = 0·524). (b) Absolute numbers of CD4⁺CD25^high+ cells in the 26 HIV-infected patients increased significantly during HAART (P < 0·0001). In controls median absolute counts of CD4⁺CD25^high+ cells were significantly higher than in patients both when comparing control values to week 0 (P < 0·05) and 24 (P < 0·05) values. (c) Levels of T_regs measured as forkhead box P3 (FoxP3) mRNA expression and expressed as relative units (RU) did not change significantly during HAART in the 26 HIV-infected patients (P = 0·2859). In controls FoxP3 mRNA levels were significantly lower than in HIV-infected patients both when comparing control values to week 0 (P < 0·0001) and week 24 (P = 0·0013) values.

Absolute counts of CD4⁺CD25^high+ cells increased significantly during HAART [4·4 cells/µl (0·4–10·1 cells/µl), 5·7 cells/µl (1·2–11·3 cells/µl), 7·4 cells/µl (2·7–13·3 cells/µl) and 8·0 cells/µl (4·0–20·2 cells/µl) at weeks 0, 4, 12, 24 respectively; P < 0·0001]. In controls median T_reg absolute counts were significantly higher than in patients [10·6 cells/µl (6·7–13·9 cells/µl)] compared with week 0 (P < 0·001) and 24 (P < 0·02) values (Fig. 2b).

The FoxP3 mRNA levels were measured in all 26 HIV-infected patients at weeks 0, 4, 12 and 24 and in 11 controls. Median FoxP3 mRNA RU did not change significantly during HAART. [At weeks 0, 4, 12 and 24 median RU values in HIV-infected patients were 0·26 (0·08–0·63), 0·26 (0·06–1·01), 0·24 (0·07–0·73) and 0·19 (0·08–0·56) respectively; P = 0·2859]. In controls median mRNA level RU was 0·11 (0·05–0·21), which was significantly lower than patients compared with week 0 (P < 0·0001) and week 24 (P = 0·0013) values (Fig. 2c).

There was no significant correlation between time of seroconversion and levels of T_regs.

Association between T_reg levels and immune status

To investigate whether levels of T_regs are influenced by immunological status in HIV-infected patients, the association between T_regs and CD4 counts or viral loads was analysed. Significant correlations were not found between FoxP3 and viral loads at any time of follow-up. Furthermore, we investigated the relation between CD4 counts and T_regs by separating patients into two groups (CD4 counts </≥ 200 cells/µl at the time of initiation of HAART).

No correlation was found during follow-up between CD4 counts and percentages of CD4⁺CD25^high+ or FoxP3 levels. No significant changes over time were found between the two groups with CD4 counts of </≥ 200 cells/µl.

Immune activation upon initiation of HAART

To determine immune activation, CD4⁺ cells co-expressing CD38 and HLA-DR were measured in patients at weeks 0, 4, 12, 24 and in controls. In patients, median percentages of CD4⁺CD38⁺HLA-DR⁺ decreased after initiation of HAART. [Week 0 median 8·4% (3·3–53·3%), week 4 9·4% (2·2–39·5%), week 12 6·3% (1·6–29·2%), week 24 4·9% (1·3–13·8%); P = 0·0003]. In controls, immune activation was lower [median 1·4% of CD4⁺ cells (0·8–3·8%) compared with both weeks 0 and 24 (P < 0·0001). Significant correlation between percentages of CD4⁺CD38⁺HLA-DR⁺ and FoxP3 levels was not found.

Surface markers of T_regs

To determine the distribution of the surface markers CD45RO, CD62L, CTLA-4, GITR, HLA-DR and CD38 as T_reg markers, these markers were measured in the CD4⁺CD25⁺ and in the CD4⁺CD25^high+ cell populations (Table 2). None of the examined surface markers showed stronger correlations to FoxP3 than CD25 alone.

Table 2.

Percentages (%) of CD4⁺CD25⁺ and CD4⁺CD25^high+ cell subpopulations in patients at weeks 0 and 24 and controls.

Surface markers	Week 0 (%)	Week 24 (%)	Controls (%)
CD4+CD25+	26·9†	34·2†	42·3
CD4+CD25+CD45RO+	31·7	32·7	35·6
CD4+CD25+62L+	27·8	31·6	28·6
CD4+CD25+CTLA-4+	13·2	17·8	19·5
CD4+CD25+GITR+	5·9	10·8‡	9·6
CD4+CD25CD38+	18·9	16·8‡	15·4
CD4+CD25+HLA-DR+	4·6†	2·8†	1·2
CD4+CD25high+	2·2†	2·3†	1·6
CD4+CD25high+CD45RO+	2·2†	2·5†	1·5
CD4+CD25high+62L+	2·1†	2·1†	1·5
CD4+CD25high+CTLA-4+	0·7	1·1	0·5
CD4+CD25high+GITR+	0·3	0·4†	0·2
CD4+CD25high+CD38+	1·9†	1·2†,‡	0·7
CD4+CD25high+HLA-DR+	0·9†	0·9†,‡	0·3

All values are given as median values in percentages of CD4⁺ cells.

^†Indicates a significant difference from controls.

^‡Indicates a significant change from week 0 to week 24. CTLA: cytotoxic T lymphocyte antigen;GITR: glucocorticoid-induced tumour necrosis factor receptor family-related gene; HLA-DR: human leucocyte antigen D-related.

Discussion

The present study was designed to examine associations between immunodeficiency, immune activation and levels of T_regs in HIV-infected patient by quantifying levels of T_regs in treatment-naive HIV-infected patients prior to and during the first 24 weeks of HAART. The study showed higher percentages of CD4⁺CD25^high+ cells paralleled by higher levels of FoxP3 in HIV-infected patients compared with healthy controls. In patients neither the percentage of CD4⁺CD25^high+ nor the expression of FoxP3 changed significantly during 24 weeks of HAART. In contrast, CD4 counts increased and viral loads decreased. Thus, the elevated level of T_regs was found to be independent of both immunological and virological status in HIV-infected patients.

Determination of T_regs is possible both on surface marker and gene levels. T_regs identified via surface markers, primarily CD25, using flow cytometry has been used for years [4,13]. T_regs express CD25 in a higher manner (CD25^high+) than activated cells [10]. Identifying CD25^high+, however, is difficult and subjective. Also, it has been debated if the population of CD4⁺CD25^high+ cells is really covering the whole population of T_regs[14]. Other surface markers such as CD45RO, CD62L, CTLA-4, GITR, HLA-DR and CD38 have been suggested as markers of T_regs. However, they all have in common that they do not represent the whole T_reg population [14]. Also, the gene FoxP3 was believed previously to be expressed only by T_regs[10]. However, FoxP3 mRNA levels by RT–PCR is considered the gold standard for identification of T_regs[10,15]. In order to comply with the different methods of identifying T_regs, we chose to determine T_regs both by measuring FoxP3 levels and determining CD4⁺CD25^high+ cells. Also, the study intended to clarify the proportion of T_regs expressing the surface markers CD45RO, CD62L, CTLA-4, GITR, HLA-DR and CD38. The presence of these surface markers on T_regs is well established [2,4,16,17], while the proportion of T_regs positive for these surface markers is controversial [4,14]. We found elevated levels of CD4⁺CD25^high+ cells co-expressing these markers in patients compared with controls both before and after HAART. A better correlation to FoxP3 was not found by adding any of these surface markers. These findings indicate that replacing CD25 with any of these other T_reg markers are likely to underestimate the level of T_regs.

The relation between T_regs and HIV is controversial. Persistent antigen exposure is believed to induce normal CD4⁺ cells to obtain T_reg phenotype and function [18]. However, T_regs are CD4 and CCR5 positive and thereby susceptible to HIV [9]. Therefore, the absolute number of CD4⁺CD25^high+ cells is expected to decline with HIV progression. Thus, lower absolute numbers of CD4⁺CD25^high+ cells in HIV-infected patients compared with controls are reported in other studies [2,8], which our results support. We demonstrate significantly lower absolute numbers of CD4⁺CD25^high+ cells before initiation of HAART as well as after 24 weeks of treatment. Absolute numbers of CD4⁺CD25^high+ cells, however, might be less interesting than percentages of CD4⁺CD25^high+ cells; these percentages tell us if T_regs expand during HIV-infection or have a slower decline with different kinetics than CD4⁺ cells in general. Our data show that T_regs measured as percentages of CD4⁺CD25^high+ cells in treatment-naive patients are significantly higher than those in healthy controls. This suggests an expansion of T_regs as disease progresses. Higher percentages of CD4⁺CD25^high+ cells compared with controls are also consistent with the findings of other studies [2,6–8,19,20], including a large cross-sectional study of 81 patients [2]. Our data show elevated levels of FoxP3 as well as higher percentages of CD4⁺CD25^high+ cells in untreated patients compared with controls, which is in full agreement with a recently published study [20], thus supporting the hypothesis concerning expansion of T_regs in disease progression. Lower levels of FoxP3 mRNA have been reported only once [15].

Immune activation is meant to eliminate pathogens from the body. However, sometimes activation becomes unspecific, switching something supposedly useful into damage. This double-edged sword seems especially important concerning HIV, as immune activation has been proved to be associated with disease progression [1,21] and might be part of the causal and not well-understood relationship between CD4⁺ cell loss, HIV viraemia and immune activation. In this regard, T_regs are believed to play an important role; the immune activation might, as part of advanced disease, in turn cause the T_reg population to expand as an attempt to slow down disease progression. Alternatively, high frequencies of T_regs are down-regulating beneficial HIV-specific responses, thereby causing progression of the infection. We found no association between immune activation and T_regs. Interestingly, our data show clearly that T_regs did not change after initiation of HAART despite a highly significant decrease in immune activation, indicating that immune activation itself may not drive the expansion of T_regs. Alternatively, we are measuring levels of T_regs too soon after initiation of HAART as CD4 counts and immune activation are only near-normalized. However, in a study of 15 patients treated with HAART for more than 5 years full normalization of immune activation and CD4 counts was found, and even in that setting T_reg levels in HIV-infected patients were elevated (L. Kolte et al., submitted).

Few studies have examined the impact of HAART on the T_reg population. Our study of a prospective cohort provides unique knowledge and shows clearly that HAART has no influence on the T_reg level as percentages of CD4⁺CD25^high+ cells as well as FoxP3 mRNA levels remain significantly higher in HIV-infected patients than in controls. This is in excellent agreement with a recent prospective study [20], and is questioned only by one study that reports decreased FoxP3 expression in untreated HIV-patients, with normalization after treatment with HAART [15]. A relation between the virus itself and T_regs has been suggested as one of the contributors to possible changes in T_reg levels during HIV infection. However, we found no association between T_regs and HIV-RNA, which is supported by earlier findings [6,9], and questioned by only one study [20]. These findings support the lack of effect of HAART on T_regs.

In conclusion, HAART have minor effects on the T_reg level measured as CD4⁺CD25^high+ cells and FoxP3 mRNA levels. However, it brings us only slightly closer to answering the overall question as to whether or not T_regs are beneficial in HIV infection. Indeed, it highlights the need for knowledge about T_reg levels in large well-defined patient populations as well as in fast and slow/non-progressors.

The present study examined associations between immunodeficiency, immune activation and levels of T_regs inHIV-infected patients by investigating the influence of HAART on T_regs in a prospective study. We found elevated T_reg levels in HIV-infected patients, and initiation of HAART did not normalize or even lower the percentages of CD4⁺CD25^high+cells or FoxP3 mRNA levels after 24 weeks of treatment, despite patients at this point having fully suppressed viral loads, increasing CD4 counts and reduced immune activation, indicating that the presence of HIV is not the only factor influencing the T_reg level. Thus, treatment with HAART might not be sufficient to limit or repair the harmfull effects of HIV on the immune system.