HIV controllers (HICs) are rare, HIV-1-infected patients who display long-term spontaneous control of viremia [1–3]. The mechanisms of viral control are incompletely understood. Most HICs are infected with replication-competent viruses . The patient's genetic background probably influences the control of the virus, since the human leucocyte antigen (HLA)-B57 and B27 alleles are over-represented in HICs [2,5]. Controllers exhibit strong antiviral immune responses, which are mediated by polyfunctional CD8+ T cells [6–9]. However, HIV-specific CD8+ and CD4+ T-cell responses are not detected in all HICs [3,10,11]. Some HICs exhibit a decline in their CD4+ T-cell count or loss of the ability to control HIV, which may be subtended by excessive immune activation [12–14]. Indeed, HICs have higher proportions of activated HLA-DR+/CD38+ CD8+ T cells than healthy donors or patients on antiretroviral therapy (ART) do . This could be related to the persistence of extremely low levels of HIV replication that can be detected using ultrasensitive techniques , excessive microbial translocation  or other as-yet unknown mechanisms.
Immune activation and the associated systemic inflammation are hallmarks of the HIV disease process . Given that detailed flow cytometry analyses of HIV-infected patients are not performed on a routine basis, researchers have sought to define blood biomarker levels that define an individual's activation profile. Abnormally high levels of inflammatory and coagulation biomarkers [such as high-sensitivity C-reactive protein (hsCRP), interleukin (IL)6 and D-dimers] are associated with immunological failure, clinical morbidity and AIDS and non-AIDS-related mortality [18,19]. Levels of interferon gamma-induced protein 10 (IP10), soluble CD14 (sCD14), tumor necrosis factor (TNF)α, IL10 and monocyte chemoattractant protein-1 (MCP1) have been variously linked to a low CD4+ T-cell count [20–23], viral replication [23–25], atherosclerosis , cognitive impairment  and mortality .
The few studies to have focused on the role of circulating cytokines and chemokines in HICs have yielded contrasting results. Hsue et al. found higher levels of hsCRP in 33 HICs than in healthy donors, and Pereyra et al. found high sCD163, sCD14 and IP10 levels in 10 elite controller patients. Both studies reported an increased risk of atherosclerosis in HICs. However, a recent study found that IP10 and MCP1 levels in 18 HICs were similar to those seen in 13 healthy donors .
Here, we assayed plasma biomarkers in 70 patients from the Agence Nationale de Recherche sur le SIDA et les hépatites virales (ANRS) HIC cohort and for whom at least two consecutive samples (at enrollment and 1 year later) were available. This constitutes the largest group of HICs in whom soluble biomarkers have been quantified to date. The HICs were compared with treatment-naive viremic noncontrollers, aviremic ART-treated patients and healthy donors. We particularly studied changes over time in the cytokine and chemokine levels of the HICs and the latter's relationships with CD4+ T-cell counts.
Patients and study design
The study population comprised of 70 HICs from the ANRS CO21 COhorte Des EXtrêmes (CODEX) cohort. These ART-naive patients had been diagnosed at least 5 years previously and had displayed viral loads below 400 copies/ml in the last five consecutive measurements. Individuals whose viral loads had never exceeded 50 RNA copies/ml were referred to as elite controllers (n = 22) . All patients gave their informed consent to participation in the study. The study protocol was approved by the regional investigational review board (Comité de Protection des Personnes Ile-de-France VII, Paris, France; approval reference: 05–22) and performed in compliance with the tenets of the Declaration of Helsinki. Patients are followed every 12 months with plasma samples collected at each study visit and stored at −80°C.
The control groups consisted of 33 viremic (viral load >10 000 copies/ml), treatment-naive patients (viremic patients); 30 ART-treated patients with no detectable viral load (<40 copies/ml) for at least 2 years (ART-treated patients); and 40 healthy donors for whom blood samples were available for research purposes (stored at the Etablissement Français du Sang, Paris, France).
The data collected from the 70 HICs at enrollment (day 0) were then compared with the samples obtained 12 months later. In 40 HICs, a sample obtained at 24 months was also available.
Cytokine and chemokine measurements
The eight assayed soluble proteins were chosen for their inflammatory properties (TNFα, IL6, hsCRP, IP10), anti-inflammatory properties (IL10) or relationship with monocyte activation (MCP1, sCD14, sCD163) during HIV infection [14–25].
Levels of TNFα, IL6, IP10, MCP1 and IL10 were measured in a FlowCytomix bead-based multiplex immunoassay (eBioscience Inc., San Diego, California, USA), according to the manufacturer's instructions. Given that the IL6 level in over half the samples was below the assay's limit of detection, this interleukin was assayed with a specific ELISA (Human IL6 Platinum ELISA; eBioscience). We also used ELISAs to measure levels of hsCRP (CRP Gen.3 kit; Roche Diagnostics, Indianapolis, Indiana, USA), soluble CD14 and soluble CD163 (R&D Systems, Minneapolis, Minnesota, USA).
Flow cytometry analysis
Surface expression of T-lymphocyte activation markers (HLA-DR and CD38+) was analyzed by flow cytometry of the HIC whole blood samples, as described elsewhere .
Human leukocyte antigen typing and the HIV-specific CD8+ T-cell response
Human leukocyte antigen typing was based on the complement-dependent microlymphocytotoxic technique (InGen Biosciences, France). Interferon-gamma (IFN-γ) ELISpot assays were used to measure specific responses to peptides corresponding to optimal HIV-cytotoxic T lymphocytes epitopes (National Institutes of Health HIV Molecular Immunology Database: http://www.hiv.lanl.gov/content/immunology/tables/optimal_ctl_summary.html) according to the patients’ HLA type. Optimal peptides were used at 2 μg/ml in pools according to the HLA allele and to the HIV protein and were tested in duplicate. Data were expressed as spot-forming cells (SFCs) per 106 peripheral blood mononuclear cells (PBMCs). Results were considered positive if more than 50 SFCs/106 PBMCs after subtraction of the mean background were obtained with cells alone.
Data are expressed as the median (1st–3rd quartile) for continuous variables, and n (%) for categorical variables. Given their distribution, the cytokine/chemokine levels in the different groups were compared across the groups by using a nonparametric Kruskal–Wallis test. In order to take into account the risk of false discovery due to multiple comparisons, Dunn's test correction was used for the comparisons between the different groups. A chi-square test was used to compare categorical data. In HICs, changes over time in cytokine levels [from M0 to month 12 (M12) and month 24 (M24)] were analyzed in a Wilcoxon rank-sum test for matched pairs. Spearman's coefficient was used for correlation analyses after log10-normalization of non-normally distributed datasets. The threshold for statistical significance was set to P less than 0.05 for all analyses. Data were stored and analyzed using PRISM software (version 5; GraphPad Software, La Jolla, California, USA).
Characteristics of the study population
The characteristics of the four study groups are summarized in Table 1. The 70 HICs were monitored over a median (1st–3rd quartile) period of 12 (8–15) years after HIV diagnosis. The 22 HICs (32.4%) classified as elite controllers were monitored over a median [interquartile range (IQR)] period of 11 (7.5–15) years after HIV diagnosis. The elite controllers differed significantly from the other HICs in terms of ultrasensitive HIV RNA viral load at enrollment [4 (4–12) vs. 76 (25–285) copies/ml, respectively; P < 0.0001], but not for cellular HIV DNA copy number [24 (11.8–50.3) vs. 33.5 (19.0–128.5) copies/106 PBMCs, respectively; P = 0.17]. The elite controllers had a less profound CD4+ T-cell nadir (lowest CD4+ T-cell count reported) than the nonelite controllers did [median (IQR) counts: 462.5 (427.3–672.8) vs. 384.5 (299–504.3), respectively; P = 0.02], in accordance with previous studies . The HLA B57 allele was present in 34.4% of the HIC population as a whole (with 41 vs. 31% in elite and nonelite controllers, respectively; P = 0.43).
Biomarker levels in HIV controllers
We first compared elite controllers and nonelite HICs with healthy donors. Elite controllers had higher levels of IP10 and TNFα (P < 0.01 for both) than healthy donors, and nonelite HICs had higher levels of IP10 (P < 0.001), TNFα (P < 0.001) and sCD14 (P < 0.01) than healthy donors (Fig. 1).
Next, we compared elite controllers and nonelite HICs with viremic patients. Levels of IP10, IL6 and the anti-inflammatory cytokine IL10 were lower in both controller groups than in viremic patients. Furthermore, MCP1 levels were lower in elite controllers than in viremic patients. Neither group of HICs differed significantly from viremic patients in terms of sCD163 levels (Fig. 1). Given that the five study groups did not differ significantly (according to a Kruskal–Wallis test) in terms of hsCRP levels (low in all groups), this parameter was not analyzed further.
Interestingly, the levels of TNFα and sCD14 were similar in elite controllers, nonelite HICs and viremic patients (i.e. despite marked differences in the respective viral loads).
Finally, we focused our attention on similarities and disparities between elite controllers and ART-treated patients, as both groups do not experience detectable viral loads on long-term periods. Interestingly, elite controllers had similar levels of the vast majority of the biomarkers tested (IP10, MCP1, TNFα, sCD14, and sCD163) than ART-treated patients. Only IL6 and IL10 levels were lower in elite controllers than in ART-treated patients. Similar results were observed when comparing nonelite HICs with ART-treated patients, and there were no differences between elite controllers and nonelite controllers in terms of any of the cytokines.
In summary, these observations attest to the presence of inflammation in HICs, in the absence of marked viremia. Relative to healthy volunteers, IP10 and TNFα levels remained abnormally high in elite controllers (despite the absence of detectable viremic episodes in the latter).
Analysis of determinants of inflammatory biomarker levels in HIV controllers
No associations between biomarker levels on one hand and age, sex or hepatitis C status on the other were observed in any of the four study groups.
We then looked at whether prior immunologic damage might be associated with ongoing inflammation in HICs. The CD4+ T-cell nadir was significantly and negatively correlated with levels of IP10 (r = −0.439, P = 0.0002), sCD14 (r = −0.243, P = 0.049) and sCD163 (r = −0.270, P = 0.027) (Fig. 2a).
Furthermore, the CD4+ T-cell count at enrollment was negatively correlated with IP10 (r = −0.387, P = 0.001) and sCD163 (r = −0.279, P = 0.019), but not with sCD14 (Fig. 2b) or any of the other cytokines. Similar correlations were seen for the CD4+/CD8+ ratio at enrollment (IP10: r = −0.410, P = 0.0007; sCD163: r = −0.280, P = 0.024; sCD14: r = −0.306, P = 0.014), but not for the CD8+ T-cell count.
Given that the CD4+ T-cell count at enrollment was negatively correlated with the ultrasensitive RNA viral load (r = −0.389, P = 0.002), we then looked at whether the persistence of extremely low viral replication levels might influence biomarker levels. Interestingly, there were no associations between any of the cytokine levels (including IP10) and the viral load (whether measured as the ultrasensitive HIV RNA viral load or the cellular HIV DNA copy number), neither in HICs taken as a whole nor in elite controllers analyzed separately.
In summary, we found that systemic inflammation was associated with the CD4+ T-cell nadir and the CD4+ T-cell count at enrollment, but not with the ultrasensitive HIV RNA viral load.
Relationships with T-cell immune activation
Our data suggest that a very low viral load did not entirely account for cytokine/chemokine production. Therefore, we sought to analyze the relationships between biomarker levels and other immunologic parameters in HICs.
As shown in Fig. 3a and b, IP10, sCD163, IL6 and MCP1 levels were positively correlated with the proportion of HLA-DR+CD38+ activated CD8+ and CD4+ T cells in the group of HICs. No relationships between activated T-cell counts and the levels of sCD14, TNFα and IL10 were observed. In the subgroup of elite controllers, the proportion of activated CD8+ T cells was correlated with levels of IP10 (r = 0.453, P = 0.045), sCD163 (r = 0.640, P = 0.002) and MCP1 (r = 0.457, P = 0.037) (data not shown). There was a nonsignificant trend towards a correlation with IL6 levels (r = 0.398, P = 0.082). However, in elite controllers, there was no association with the proportion of HLA-DR+CD38+ CD4+ T cells.
There was no correlation between biomarker levels on one hand and the HIV-specific CD8+ T-cell frequency or the CD8+ cell ability to block viral replication on the other .
Lastly, we observed a positive correlation between IP10 and MCP1 levels (Spearman's r = 0.269, P = 0.02), between IP10 and sCD163 levels (r = 0.307, P = 0.0099) and between sCD14 and sCD163 levels (r = 0.385, P = 0.001) (Supplemental Figure 1, http://links.lww.com/QAD/A463); these correlations suggest the existence of links between the interferon pathway (IP10 and MCP1) and monocyte activation (sCD163 and sCD14) in HICs.
In summary, we found that the CD4+ and CD8+ T-cell activation levels were associated with systemic inflammation.
Evidence of persistent inflammation in HIV controllers
As described above, IP10 was the only biomarker associated with the following features: the CD4+ T-cell nadir, the CD4+ T-cell count at enrollment and T-lymphocyte activation. We therefore assessed the change over time in levels of this biomarker. The absence of any significant changes in IP10 levels from day 0 to M12 and M24 attested to the persistence of stable, chronic inflammation in HICs (Supplemental Figure 2, http://links.lww.com/QAD/A463).
We next investigated the interplay between IP10 levels on one hand and the dynamics of CD4+ T-cell counts at M12 and M24 on the other. At enrollment, higher IP10 levels correlated with a lower CD4+ T-cell count at M12 (r = −0.41, P = 0.0009) and at M24 (r = −0.38, P = 0.019) (Fig. 4).
Our results show that despite low levels of viral replication, IP10 levels remain abnormally high in HICs over time and are negatively correlated with the CD4+ T-cell count.
In the present study, we analyzed levels of inflammatory chemokines (IP10, MCP1) and cytokines (TNFα, IL6), monocyte activation markers (sCD14, sCD163) and an anti-inflammatory cytokine (IL10) in a large cohort of HICs. The HICs had low-grade but detectable inflammation, with significantly higher levels of IP10, sCD14 and TNFα than in healthy donors. For IP10 and TNFα, we validated these data in elite controllers who had controlled viral replication without any blips for a median (IQR) duration of 11 (7.5–15) years. Levels of several biomarkers (IP10, MCP1, IL6 and IL10) were lower in both elite controllers and nonelite HICs, when compared with viremic patients. Moreover, biomarker levels were similar in the two groups of patients with undetectable viral loads (i.e. elite controllers and ART-treated patients), except that IL6 and IL10 levels were higher in ART-treated patients than in elite controllers. On this basis, we suggest that IP10 may have value as a surrogate marker of immune activation.
IP10 was the most discriminant inflammatory chemokine because its levels differed significantly when comparing HICs with both viremic patients and healthy donors. This observation raises questions about the factors that might contribute to production of this chemokine. Viral proteins such as gp120  and Tat  might be trapped by follicular dendritic cells or macrophages in the lymph nodes, which would induce IP10 production by these cell types . Low levels of viral replication could take place in lymphoid organs rather than in the peripheral blood . Release of IFNγ and pro-inflammatory factors such as TNFα  might also constitute stimuli for IP10 production; indeed, levels of TNFα were consistently elevated in the HICs studied here. IFNα can also participate in IP10 production [36,37]. In line with this hypothesis, we previously reported that HICs have fully functional plasmacytoid dendritic cells capable of producing large amounts of IFNα . In summary, IP10 levels in HICs might depend (at least in part) on the history of viral control, enhanced inflammation (mediated by monocyte activation) and the IFNα/γ pathways.
The inflammation observed in HICs might conceivably be related to the persistence of extremely low levels of viral replication [15,39]. A true low-grade viral replication is supported by some studies which have shown evidence for HIV evolution [4,40–42]. However, some of our present observations weaken this hypothesis. Firstly, neither the ultrasensitive viral load nor the cellular HIV DNA levels correlated with biomarker levels. Secondly, we observed that TNFα and IP10 levels were persistently elevated in elite controllers (i.e. HICs who had kept their viral load below 50 copies/ml throughout the follow-up period). There were no significant differences between elite controllers and nonelite HICs in this respect.
Hence, factors other than residual viral replication are probably also involved. Here, we observed that IL6 and IL10 levels were higher in ART-treated patients than in both elite controllers and nonelite HICs. These differences might indirectly reflect more severe gut mucosa damage in ART-treated patients, who have a history of higher viral replication and lower CD4+ cell counts than HICs. Indeed, it has been reported that levels of circulating lipopolysaccharide (LPS) are higher in HICs and ART-treated patients than in healthy donors [14,16]. However, endotoxin-core antibody titers are higher in HICs than in ART-treated patients and are similarly low in ART-treated and viremic patients . These observations suggest that neutralization of LPS’ immunostimulatory effects might be more effective in HICs and might result in lower levels of inflammation in these patients. The higher IL10 levels in ART-treated patients might reflect their higher regulatory T-cell count (relative to HICs) .
Persistent monocyte activation might be also responsible for the elevated levels of IP10, TNFα and sCD14 observed in HICs . In a study of a small number of elite controllers (n = 10), Pereyra et al. suggested that monocyte-induced inflammation occurred in these individuals. Here, we observed positive correlations (between IP10 levels on one hand and MCP1 and sCD163 levels on the other) that also reflect monocyte activation. Furthermore, recent studies suggest that in the setting of HIV infection, TNFα may be produced by activated CD14++CD16+ and CD14+CD16++ monocytes . The intensity and duration of previous viral replication – rather than ongoing viral production – might account for this monocyte activation in HICs. In line with this, Ciccone et al. reported that long-term non-progressors/elite controllers did not have evidence of gut mucosal depletion and had normal sCD14 levels relative to 9 healthy donors, whereas it was significantly higher in ART-controlled patients. Here, we also observed that elite controllers have similar sCD14 levels than healthy donors. However, as compared with healthy donors, sCD14 levels were higher in the 48 nonelite HICs and 30 ART-treated patients tested. Altogether, these findings suggest that previous history of blips in nonelite HICs might also partially account for monocyte activation and inflammation in some HICs, in a similar manner to pre-ART elevated viral loads observed in treated patients.
Low T-cell activation has been described in both ART-treated patients and HICs . Here, we observed a link between immune activation in HICs (as measured by the proportion of HLA-DR+CD38+ CD8+ and CD4+ T cells) and their levels of IP10, sCD163, IL6 and MCP1. IP10, sCD14 and sCD163 levels were negatively associated with the nadir of the CD4+ T-cell count and high IP10 and sCD163 levels were associated with a low CD4+ T-cell count at enrollment. These findings extend previous observations whereby prolonged immune activation in HICs correlates with a decline in the CD4+ T-cell count . In our study, IP10 and sCD163 were significantly correlated with both immune activation and a low CD4+ T-cell count. Interestingly, Liovat et al. recently reported that elevated IP10 levels during primary infection were predictive of rapid CD4+ T-cell decline at M6. Moreover, the levels of the monocyte activation marker sCD163 are elevated in early-stage and chronic HIV infections and have been linked to immune activation and variations in the CD4+ T-lymphocyte count in non-HICs .
Here, we showed that in HICs, IP10 levels remained abnormally high over 12 and 24 months and were associated with low CD4+ T-cell counts at M12 and M24. This may have long-term immunological consequences. However, a direct link between the intensity of this inflammation and the time course of the CD4+ T-cell count in HICs remains to be confirmed. A multivariate analysis would have helped to determine the independent effect of IP10 in disease progression in HICs, taking into account nadir CD4+ cell count. However, only eight of the 70 patients displayed a clinically relevant CD4+ T-cell decline (i.e. changing from >500/μl at enrollment to <500 /μl) after 1 year of follow-up. This is in line with previous publications showing that HICs have a slow rate of disease progression . In such patients, a longer follow-up is needed to disentangle this important issue.
In addition to chronic inflammation and T-lymphocyte activation, several additional factors determine the change over time in CD4+ T-cell counts in HICs. Persistent, low-grade viral replication and a history of viral load blips are involved, as reported previously . Hence, elite controllers have significantly lower ultrasensitive HIV viral loads and higher CD4+ T-cell counts than nonelite controllers do . Depressed lymphopoieisis may also contribute to changes of CD4+ T-cell counts in some HICs . Lastly, microbial translocation may also have a role in HICs. We observed a negative correlation between the levels of circulating bacterial 16S rDNA and the CD4+ T-cell count in the 70 HICs studied here (data not shown). However, the absence of correlations between microbial translocation on one hand, and neither the biomarkers nor the HIV viral load measurements on the other, suggests that other unidentified pathways are involved.
Lastly, the persistent, low-grade inflammation seen in HICs may also have long-term clinical consequences, such as coronary artery disease or cognitive impairment. Subclinical atherosclerosis has already been documented in a small number of HICs [29,30] and IP10 has been linked to atherogenesis . hsCRP has been associated with cardiovascular events, but we did not find any difference in hsCRP levels when comparing the various patient groups and healthy donors. This apparent difference with the findings of the Strategies for Management of Antiretroviral Therapy (SMART) and Flexible Initial Retrovirus Suppressive Therapies (FIRST) studies [18,19] might be due to the number of patients included in our study and in these trials. Furthermore, such results regarding hsCRP have already been reported (i.e. no difference between infected patients and healthy donors in  and no difference between viremic patients, HICs and healthy donors in ).
In conclusion, we performed the largest study of inflammation biomarker levels in HICs. We found that HICs have elevated levels of IP10, TNFα and sCD14. This chronic inflammation might result from abnormal monocyte activation (TNFα and sCD14) and dysregulation of the IFNα/γ pathways (IP10). Of the various biomarkers studied here, IP10 seems to be the most discriminant biomarker in HICs (relative to both healthy donors and viremic noncontrollers), and its high levels may be related to low CD4+ T-cell counts. Monitoring of CD4+ T-cell count, the ultrasensitive viral load and IP10 levels might enable the detection of HICs at risk of disease progression and/or non-AIDS-related events.
The authors thank Stéphane Hua, Isabelle Girault and Dr Jean-Philippe Lavigne for technical support and helpful comments; Marc Conti (Service de Biochimie, CHU Henri Mondor, APHP, Créteil, France) for hsCRP assays; David Fraser for language editing; all patients for their cooperation and all physicians who cared for patients in the ANRS HIV controller cohort.
The steering committee of the ANRS CO21 study group: Henri Agut, Brigitte Autran, Faroudy Boufassa, Dominique Costagliola, Olivier Lambotte, Laurence Meyer, Gianfranco Pancino, Christine Rouzioux, Ioannis Theodorou, Alain Venet.
Funding statement: N.N. received a PhD fellowship from the Fondation pour la Recherche Médicale (FRM). This work was funded by the Agence pour la Recherche Contre le SIDA (ANRS), INSERM and Paris-Sud University.
Conflicts of interest
There are no conflicts of interest.
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