The majority of HIV type-1–infected patients with viral suppression during antiretroviral therapy (ART) experience a significant rise in the number of CD4+ T cells in peripheral blood.1 Patients who achieve a CD4 T-cell count exceeding 500 cells per microliter approach the mortality rates of the general population, indicating a more general reconstitution of the immune system.2 Some patients, however, do not normalize their CD4 T-cell count, even after several years of effective ART (ie, undetectable plasma HIV RNA). The incidence of these immunological nonresponders (INR) varies between studies depending on the definition of INR; CD4 T-cell counts <200–350 cells per microliter, an increase from baseline of <20%, or an increase <50–100 cells per microliter after various durations of ART have frequently been used.3,4 Importantly, INR patients face an increased risk not only of AIDS-related pathology, but also in particular of non–AIDS-related morbidity and mortality.5–10 The latter includes cardiovascular disease11 and non–AIDS-defining malignancies,12 suggesting a more general immune dysregulation including persisting detrimental immune activation. Efforts have therefore been made to better understand the pathogenic factors leading to INR, to search for biomarkers that can better identify these patients early, and to explore possible therapeutic strategies.
Many studies of immune reconstitution in HIV-infected patients on ART have observed patients only a few years after initiation of treatment. Although some studies report a plateau in CD4 T-cell counts already after 3–5 years of ART,13–16 others have observed a continuous increase in CD4 T-cell counts even after 10 years of viral suppression.17–20 A number of factors have been associated with impaired immune reconstitution in patients on ART. These include old age,10,13,15 hepatitis C coinfection,21,22 and a low nadir CD4 T-cell count,10,17,19 of which the latter seems to be the strongest predictor. However, these clinical factors do not fully explain the underlying immune mechanisms causing INR. Several mediators may be involved and differentially promote the development of INR in individual patients.
The aim of this study was to identify early prognostic biomarkers associated with the development of INR. An asymptomatic HIV-seropositive cohort was followed for up to 11 years after initiation of effective ART, from which a subgroup of INR patients was identified. In samples obtained before treatment initiation and during the first 3 years of ART, we performed a serial analysis of selected cytokines, including interleukins (ILs), chemokines, and growth factors with relevance for immune function and inflammation.
MATERIALS AND METHODS
HIV-positive patients (n = 112) were selected from the HIV patient database of the Department of Infectious Diseases at Oslo University Hospital, according to the following inclusion criteria: (1) initiated ART between January 2000 and May 2007; (2) viral suppression to HIV RNA <50 copies per milliliter within 6 months of ART initiation; (3) undetectable HIV RNA (<50 copies/mL) throughout the study period only allowing for single blips (<400 copies/mL); and (4) no AIDS-defining disease before or during the study period. The study was approved by the Norwegian South-Eastern Regional Committee for Medical and Health Research Ethics. Written informed consent was obtained from all participants.
Cryopreserved EDTA plasma samples, stored at −20°C, were selected from 5 time points: baseline (before ART, n = 112), 6 months (interquartile range, IQR: 5.4–6.8 months, n = 108), 1 year (IQR: 11.2–13.0 months, n = 103), 2 years (IQR: 23.1–25.3 months, n = 81), and 3 years (IQR: 35.1–37.5 months, n = 57) after ART initiation. Clinical biochemistry parameters, CD4 and CD8 T-cell counts, and HIV RNA obtained at the same time points as the plasma samples were recorded. In addition, the last available CD4 and CD8 T-cell counts and HIV RNA level (final sample, n = 112) were registered. Twenty-six samples (7.5%) from patients on ART had quantifiable HIV RNA >50 copies per milliliter (median 90 copies/mL, IQR: 70–100 copies/mL).
To assess the stability of the analytes in cryopreserved plasma samples stored at −20°C, we also analyzed EDTA plasma samples from a separate, HIV-positive ART-naive comparator cohort (n = 27) and HIV-negative blood donors (n = 20). These samples were snap-frozen and stored at −70°C for up to 3 years. The HIV-positive comparator cohort was characterized by higher CD4 counts and lower HIV RNA levels than the main study cohort at baseline (see Table, Supplemental Digital Content 1, http://links.lww.com/QAI/A664).
Multiplex Assay for Cytokine Analysis
Plasma samples were analyzed using a multiplex cytokine assay (Bio-Plex human cytokine 27-plex panel; Bio-Rad Laboratories Inc., Hercules, CA) containing assays for IL-1β, IL-1 receptor antagonist (IL1-ra), IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 (p70), IL-13, IL-15, IL-17, basic fibroblast growth factor (bFGF), granulocyte colony-stimulating factor, granulocyte-macrophage colony-stimulating factor, interferon gamma (IFN-γ), eotaxin/CCL11, IFN-γ-inducible protein 10 (IP-10)/CXCL10, macrophage chemoattractant protein 1/CCL2, macrophage inflammatory protein 1 alpha (MIP-1α)/CCL3, MIP-1β/CCL4, regulated on activation, normal T-cell expressed and secreted (RANTES)/CCL5, tumor necrosis factor (TNF), platelet-derived growth factor, and vascular endothelial growth factor. The samples were analyzed on a multiplex analyzer using Bio-Plex Manager 6.0 (Bio-Rad Laboratories) according to instructions from the manufacturer. Samples were run in single copies. Intra- and inter-assay coefficients of variation were <12% for all analytes.
Enzyme Immunoassays for Other Inflammatory Markers
Plasma levels of CXCL16, pentraxin 3, soluble TNF receptor 2 (sTNFRII), Fas Ligand (FasL), thymus and activation-regulated chemokine/CCL17, hepatocyte growth factor, osteoprotegerin, activated leukocyte cell adhesion molecule, and C-reactive protein were measured by enzyme immunoassays (R&D Systems, Stillwater, MN). Samples were run in duplicate. Intra- and inter-assay coefficients of variation were <10% for all except FasL (<15%).
Undetectable and Degraded Markers
Thirteen (IL-1β, IL-2, IL4, IL-5, IL-7, IL-8, IL-10, IL-12 (p70), IL-13, IL-17, bFGF, granulocyte colony-stimulating factor, and MIP-1α) of the 27 soluble markers measured by the multiplex assay were excluded from further statistical analysis because of low plasma levels [>80% below the lower detection level (LDL) of the assay]. In addition, 6 biomarkers (IL1-ra, IL-6, IFN-γ, TNF, pentraxin 3, and osteoprotegerin) were excluded because of suspected degradation in storage, that is, if levels in snap-frozen plasma from the HIV-positive comparator cohort but not in samples from the study cohort were significantly higher than in HIV-seronegative controls (see Table, Supplemental Digital Content 2, http://links.lww.com/QAI/A664).
For the remaining 17 markers, the occasional values (<20%) below the LDL were replaced by a common value below the LDL which allowed for statistical analysis. Similarly, occasional values above the upper detection level were replaced by a value just above the corresponding upper detection level value.
All statistical methods used were nonparametric. Comparisons between groups were assessed by Mann–Whitney U tests. Correlations between parameters were assessed by Spearman rank-sum correlation tests. Longitudinal data were assessed by Wilcoxon matched-pair tests. Differences between groups in categorical variables such as the frequency of HIV RNA viral blips and gender were assessed by χ2 tests. The effect of multiple variables on immunological nonresponse was assessed by binary logistic regression. Analyses were performed in Statistica v. 7.0 (Statsoft, Inc., Tulsa, OK) and SPSS v. 21 (IBM Corp., Armonk, NY). P values below 0.05 were considered statistically significant. Because frequent covariation between markers was observed, no correction for multiple comparisons was made.
Patient Study Cohort
A total of 112 HIV patients with a median age of 37.2 years (IQR 30.5–43.0 years) were included (77 males, 35 females). At baseline (pre-ART), the median CD4 T-cell count was 160 cells per microliter (IQR 100–215), CD8 T-cell count was 1070 cells per microliter (IQR 660–1620), and HIV RNA was 140,000 copies per milliliter (IQR 49,500–440,000). Eighty-six patients (77%) were treated with protease inhibitor–based ART regimens, whereas no patients used integrase inhibitors.
Immunological Responder Groups During ART
INR was defined as a final CD4 T-cell count <350 cells per microliter, after 8.4 years (median, IQR 7.0–10.7 years) of effective ART. Fifteen patients (13.4%) failed to exceed this threshold and were classified as long-term INR (LT-INR). All patients in this group had baseline CD4 T-cell counts <200 cells per microliter. Thus, they were compared with patients with baseline CD4 T-cell counts <200 cells per microliter but final CD4 T-cell counts >350 cells per microliter (n = 63, 56.3%), termed as low CD4 immunological responders (LowCD4-IR). The 2 groups had similar CD4 T-cell counts and HIV RNA at pre-ART baseline (Table 1). The remaining 34 patients (30.4%) all had baseline and final CD4 T-cell counts >200 and >350 cells per microliter, respectively and were defined as High CD4 immunological responders (HighCD4-IR). The HighCD4-IR patients had lower baseline HIV RNA levels than the 2 other patient groups. However, all 3 subgroups had comparable age and gender distribution (Table 1), as well as similar numbers of viral load “blips” (ie, HIV RNA between 50 and 400 copies/mL). Furthermore, there was no difference in the proportion of patients with protease inhibitor–based ART regimens or HBV/HCV coinfection between the subgroups (Table 1).
Although CD4 T-cell counts in the LowCD4-IR and HighCD4-IR subgroups rose throughout the study period, the increase in CD4 T-cell counts reached a plateau after 2 years in the LT-INR group (Fig. 1). As could be expected, pre-ART CD4 counts influenced later CD4 T-cell count recovery. In a binary logistic regression analysis including the entire cohort and adjusted for age, gender, and baseline HIV RNA, baseline CD4 T-cell count significantly predicted subsequent LT-INR [odds ratio (OR) 1.10; 95% confidence interval (CI): 1.01 to 1.19; pr. 10 cells/μL reduction in CD4 T-cell count, P = 0.030]. However, for the 2 patient groups with baseline CD4 T-cell counts <200 cells per microliter, CD4 T-cell counts were similar and therefore not predictive for INR (median CD4 T-cell count, 130 cells/μL for both LT-INR and LowCD4-IR, P = 0.550 (Table 1, Fig. 2). Moreover, there was no significant correlation between baseline CD4 T-cell counts and the increase in CD4 T-cell counts during the whole observation period (r = −0.02, P = 0.83). Notably, HIV RNA levels at baseline were not predictive for LT-INR (Table 1). Despite a negative correlation to baseline CD4 T-cell counts (r = −0.37, P < 0.05), baseline HIV RNA did not correlate to CD4 T-cell counts at any subsequent time point.
Overall Dynamics in Plasma Soluble Markers After ART
Plasma levels of a wide range of cytokines, including chemokines, growth factors, and markers of inflammation, were longitudinally analyzed in the whole study cohort and compared with plasma levels in HIV-seronegative controls. Seventeen markers were validated for further analysis (described in Methods section). Plasma levels of sTNFR2, FasL, activated leukocyte cell adhesion molecule, and IP-10 significantly decreased after 6 months of ART (Fig. 3). The decline in IP-10 correlated with the decline in sTNFR2 in the same period (r = 0.52, P < 0.001), whereas the correlations between the decline in FasL and IP-10 (r = 0.27, P = 0.01) and sTNFR2 (r = 0.30, P = 0.004), respectively were weaker. However, although IP-10 remained elevated in the study cohort even after 3 years of ART, levels of FasL and sTNFR2 were comparable with levels in HIV-seronegative controls after 6 months and 3 years of ART, respectively (Fig. 3).
Conversely, plasma levels of granulocyte-macrophage colony-stimulating factor, MIP-1β, RANTES, thymus and activation-regulated chemokine, and hepatocyte growth factor significantly increased in the cohort after 6 months of ART. RANTES levels were subnormal at baseline but normalized after 6 months of ART, an increase which correlated inversely with the concurrent fall in sTNFR2 (r = −0.23, P = 0.03). As for the other analyzed markers, no significant changes from baseline values were observed during the study period (see Figure, Supplemental Digital Content 3, http://links.lww.com/QAI/A664).
Plasma MIP-1β Predicts Long-Term Immunological Nonresponse to ART
MIP-1β was the only analyzed marker to consistently separate long-term immunological responders from nonresponders. At baseline, the LT-INR group had significantly higher MIP-1β levels than both the LowCD4-IR patients with comparable baseline CD4 T-cell counts (P = 0.02) and HIV-seronegative controls (P = 0.009) (Fig. 4). MIP-1β levels stayed elevated in the LT-INR group throughout the 3 years of observation, with significantly higher levels than the LowCD4-IR group after 2 years of effective ART and significantly higher levels than both the HighCD4-IR group and HIV-seronegative controls at all time points after the initiation of ART (Fig. 4). The LowCD4-IR and HighCD4-IR groups had similarly low levels of MIP-1β throughout the study period. In a binary logistic regression analysis restricted to patients with baseline CD4 T-cell counts <200 cells per microliter (ie, the LT-INR and LowCD4-IR groups), baseline MIP-1β significantly predicted LT-INR [OR 1.23 (95% CI: 1.02 to 1.47) per 10 pg/mL increase in MIP-1β, P = 0.029], after adjusting for baseline CD4 T-cell count, age, gender, and baseline HIV RNA.
Of note, plasma MIP-1β levels inversely correlated with CD8 T-cell counts at baseline and after 6 months of ART (r = −0.28, P = 0.003 and r = −0.20, P = 0.04, respectively). No association was found between MIP-1β and concurrent CD4 T-cell counts or HIV RNA.
Predictors of Early Immunological Nonresponse
Finally, we evaluated early immunological nonresponse 2 years after initiation of ART. This time point has frequently been evaluated in relation to INR and may be relevant for inclusion into therapeutic trials targeting INR. At this time, 45 patients (40%) had failed to reach a CD4 T-cell count >350 cells per microliter. Of these, only 15 (13.4%) ended up in the LT-INR group. The only parameter to predict INR this early was the baseline CD4 T-cell count [OR 1.16 (95% CI: 1.09 to 1.25) pr. 10 cells/μL reduction in CD4 T-cell count, P < 0.001], adjusted for age, gender, and baseline HIV RNA. MIP-1β levels did not predict early INR.
The aim of this study was to identify soluble factors in plasma that may serve as predictive biomarkers for long-term immunological nonresponse to suppressive ART. In a group of INR patients, defined by CD4 T-cell counts <350 cells per microliter after a median 8.4 years of effective ART, we found elevated pre-ART levels of the CC chemokine MIP-1β. Notably, all LT-INR cases had CD4 T-cell counts <200 cells per microliter before initiating ART, and the pre-ART CD4 T-cell count was an overall predictor of INR, in keeping with other studies.13,14,19,23,24 However, only plasma MIP-1β distinguished LT-INR patients from immunological responders with comparable low CD4 T-cell counts before initiating therapy. This difference in MIP-1β level between the groups was still detectable after 2 years of ART, indicating that MIP-1β may also contribute to identify patients with long-term immunodiscordant responses during ongoing ART.
Reports on INR have frequently followed patients for only a few years, although some long-term studies have observed continuous CD4 T-cell gains until a decade after treatment initiation.17,18,20 Our study corroborates these findings, showing a considerably lower proportion of LT-INR (13.4%) after a median overall observation time of 8.4 years, compared with 40% after only 2 years. A possible explanation for this high proportion of early INR could be that our study cohort had relatively low median CD4 T-cell counts (ie, 160 cells/μL) at baseline, probably influenced by HIV treatment guidelines at the time.25 Since then, there has been an ongoing trend toward earlier therapy in HIV infection at a higher CD4 cell count.26,27
On a cohort level, initiation of ART induced changes in the plasma levels of several inflammatory markers, including an expected decrease in sTNFR2 and IP-10, reflecting reduced systemic inflammation. However, after patients were stratified according to their immune response to ART, only baseline levels of MIP-1β identified LT-INR, also after adjusting for pre-ART CD4 T-cell counts, age, gender, and HIV RNA. The CC chemokine receptor 5 (CCR5) ligand MIP-1β has been shown to protect CD4+ T cells from HIV infection, both in vitro and in vivo.28,29 MIP-1β seems to be an important component of polyfunctional CD8 T-cell responses associated with HIV control,30,31 and MIP-1β secretion by CD8+ T cells has been associated with the inhibition of HIV replication.32 The capacity of HIV-specific T cells to secrete large amounts of MIP-1β in vitro is a characteristic of controlled HIV infection, in elite controllers, long-term nonprogressors, or effectively ART-treated patients.33,34
Observations of potential antiviral effects of MIP-1β may seem to contradict the findings in this study. However, although the antiviral effects of MIP-1β have been attributed to CD8 T-cell–derived MIP-1β, we found an inverse correlation between CD8 T-cell counts and plasma levels of MIP-1β at baseline. This suggests that other cellular subsets could contribute to the high MIP-1β levels in these patients. Moreover, in addition to the antiviral effects of MIP-1β, high levels could promote potent inflammatory responses in T cells, NK cells, and monocytes through interaction with its receptors CCR5 and CCR1.35–37 Enhanced MIP-1β activation has been implicated in the pathogenesis of various inflammatory disorders, including multiple sclerosis38 and psoriasis.39,40 Similar mechanisms in HIV infection could contribute to an inappropriate and persistent low-grade inflammation and immune dysregulation in these patients. Thus, it is tempting to hypothesize that although MIP-1β possesses some antiviral effects, persistently high levels could hamper immune reconstitution in HIV-infected patients during suppressive ART. Interestingly, MIP-1β has also been linked to development of atherosclerosis41,42 and may potentially contribute to the increased risk of cardiovascular disease in HIV-infected individuals in general and INR patients in particular.
Of the available ART drugs, the CCR5-antagonist maraviroc is the only agent to target a host protein. As well as blocking entry into cells by CCR5-dependent (R5-tropic) HIV, maraviroc inhibits CCR5-mediated signalling by CC chemokines, including MIP-1β.43 Thus, maraviroc may have immunomodulatory and anti-inflammatory properties, although the net effect on immune activation and immune reconstitution is debated. Addition of maraviroc to ART regimens has led to additional CD4 gains in some trials,44–47 but not in others.48,49 Based on our data, it is tempting to suggest that CCR5 inhibition should be explored as a therapeutic option, that is, in selected patients starting ART with CD4 T-cell counts <200 cells per microliter and with high plasma levels of MIP-1β. However, because the effects of MIP-1β are mediated through CCR1 in addition to CCR5,35–37 the effect of blocking only one of these receptors is not clear and should be explored in a clinical trial setting.
The main strength of this study is the long-term follow-up data in addition to a well-defined patient population. However, the number of patients with INR was limited, hampering the statistical power of some analyses. We also recognize that the suboptimal cryopreservation of samples at −20°C reduced the levels of some plasma markers during storage. Snap-frozen samples stored at lower temperatures are clearly preferable in the study of these plasma biomarkers. Nevertheless, storage and assay conditions were similar for all patient subgroups in our cohort, and the analyzed markers were validated by comparing snap-frozen samples, stored at −70°C, from HIV-positive and HIV-negative controls. This approach revealed significant degradation of certain cytokines and soluble cytokine receptors, including central pro-inflammatory cytokines IFN-γ and TNF, in accordance with previous studies.50,51
In conclusion, elevated pre-ART levels of MIP-1β significantly identified LT-INR in patients who started ART at CD4 T-cell counts <200. These patients were characterized by persistently high levels of MIP-1β during effective ART, in contrast to immunological responder patients with similarly low pre-ART CD4 T-cell counts. This chemokine may therefore be of use for the early identification of LT-INR patients who may benefit from immunomodulatory therapy in addition to ART. Such therapy could potentially include modulation of MIP-1β itself.
The authors thank Mette Sannes for excellent assistance.
1. Gulick RM, Mellors JW, Havlir D, et al.. Treatment with indinavir, zidovudine, and lamivudine in adults with human immunodeficiency virus infection and prior antiretroviral therapy
. N Engl J Med. 1997;337:734–739.
2. Lewden C, Chene G, Morlat P, et al.. HIV
-infected adults with a CD4 cell count greater than 500 cells/mm3 on long-term combination antiretroviral therapy
reach same mortality rates as the general population. J Acquir Immune Defic Syndr. 2007;46:72–77.
3. Corbeau P, Reynes J. Immune reconstitution under antiretroviral therapy
: the new challenge in HIV
-1 infection. Blood. 2011;117:5582–5590.
4. Gaardbo JC, Hartling HJ, Gerstoft J, et al.. Incomplete immune recovery in HIV
infection: mechanisms, relevance for clinical care, and possible solutions. Clin Dev Immunol. 2012;2012:17.
5. Baker JV, Peng G, Rapkin J, et al.. CD4+ count and risk of non-AIDS diseases following initial treatment for HIV
infection. AIDS. 2008;22:841–848.
6. Piketty C, Weiss L, Thomas F, et al.. Long-term clinical outcome of human immunodeficiency virus–infected patients with discordant immunologic and virologic responses to a protease inhibitor–containing regimen. J Infect Dis. 2001;183:1328–1335.
7. Opportunistic Infections Project Team of the Collaboration of Observational HIVERiEiE, Young J, Psichogiou M, et al.. CD4 cell count and the risk of AIDS or death in HIV
-infected adults on combination antiretroviral therapy
with a suppressed viral load: a longitudinal cohort study from COHERE. PLoS Med. 2012;9:e1001194.
8. Antiretroviral Therapy
Cohort Collaboration. Life expectancy of individuals on combination antiretroviral therapy
in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008;372:293–299.
9. Lapadula G, Cozzi-Lepri A, Marchetti G, et al.. Risk of clinical progression among patients with immunological nonresponse despite virological suppression after combination antiretroviral treatment. AIDS. 2013;27:769–779.
10. van Lelyveld SF, Gras L, Kesselring A, et al.. Long-term complications in patients with poor immunological recovery despite virological successful HAART in Dutch ATHENA cohort. AIDS. 2012;26:465–474.
11. Lichtenstein KA, Armon C, Buchacz K, et al.. Low CD4+ T cell
count is a risk factor for cardiovascular disease events in the HIV
outpatient study. Clin Infect Dis. 2010;51:435–447.
12. Guiguet M, Boue F, Cadranel J, et al.. Effect of immunodeficiency, HIV
viral load, and antiretroviral therapy
on the risk of individual malignancies (FHDH-ANRS CO4): a prospective cohort study. Lancet Oncol. 2009;10:1152–1159.
13. Moore RD, Keruly JC. CD4+ cell count 6 years after commencement of highly active antiretroviral therapy
in persons with sustained virologic suppression. Clin Infect Dis. 2007;44:441–446.
14. Le Moing V, Thiebaut R, Chene G, et al.. Long-term evolution of CD4 count in patients with a plasma HIV
RNA persistently <500 copies/mL during treatment with antiretroviral drugs. HIV
15. Kaufmann GR, Perrin L, Pantaleo G, et al.. CD4 T-lymphocyte recovery in individuals with advanced HIV
-1 infection receiving potent antiretroviral therapy
for 4 years: the Swiss HIV
Cohort Study. Arch Intern Med. 2003;163:2187–2195.
16. Garcia F, de Lazzari E, Plana M, et al.. Long-term CD4+ T-cell response to highly active antiretroviral therapy
according to baseline CD4+ T-cell count. J Acquir Immune Defic Syndr. 2004;36:702–713.
17. Lok JJ, Bosch RJ, Benson CA, et al.. Long-term increase in CD4+ T-cell counts during combination antiretroviral therapy
-1 infection. AIDS. 2010;24:1867–1876.
18. Gras L, Kesselring AM, Griffin JT, et al.. CD4 cell counts of 800 cells/mm3 or greater after 7 years of highly active antiretroviral therapy
are feasible in most patients starting with 350 cells/mm3 or greater. J Acquir Immune Defic Syndr. 2007;45:183–192.
19. D'Amico R, Yang Y, Mildvan D, et al.. Lower CD4+ T lymphocyte nadirs may indicate limited immune reconstitution in HIV
-1 infected individuals on potent antiretroviral therapy
: analysis of immunophenotypic marker results of AACTG 5067. J Clin Immunol. 2005;25:106–115.
20. Guihot A, Tubiana R, Breton G, et al.. Immune and virological benefits of 10 years of permanent viral control with antiretroviral therapy
. AIDS. 2010;24:614–617.
21. Potter M, Odueyungbo A, Yang H, et al.. Impact of hepatitis C viral replication on CD4+ T-lymphocyte progression in HIV
-HCV coinfection before and after antiretroviral therapy
. AIDS. 2010;24:1857–1865.
22. Miller MF, Haley C, Koziel MJ, et al.. Impact of hepatitis C virus on immune restoration in HIV
-infected patients who start highly active antiretroviral therapy
: a meta-analysis. Clin Infect Dis. 2005;41:713–720.
23. Kaufmann GR, Furrer H, Ledergerber B, et al.. Characteristics, determinants, and clinical relevance of CD4 T cell
recovery to <500 cells/microL in HIV
type 1-infected individuals receiving potent antiretroviral therapy
. Clin Infect Dis. 2005;41:361–372.
24. Robbins GK, Spritzler JG, Chan ES, et al.. Incomplete reconstitution of T cell
subsets on combination antiretroviral therapy
in the AIDS Clinical Trials Group protocol 384. Clin Infect Dis. 2009;48:350–361.
25. Dybul M, Fauci AS, Bartlett JG, et al.. Guidelines for using antiretroviral agents among HIV
-infected adults and adolescents. Recommendations of the panel on clinical practices for treatment of HIV
. MMWR Recomm Rep. 2002;51:1–55.
26. Thompson MA, Aberg JA, Hoy JF, et al.. Antiretroviral treatment of adult HIV
infection: 2012 recommendations of the International Antiviral Society–USA panel. JAMA. 2012;308:387–402.
27. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the Use of Antiretroviral Agents in HIV
-1-Infected Adults and Adolescents. Department of Health and Human Services; 2014. Available at: http://aidsinfo.nih.gov/contentfiles/lvguidelines/AdultandAdolescentGL.pdf
. Accessed June 13, 2014.
28. Cocchi F, DeVico AL, Garzino-Demo A, et al.. Identification of RANTES, MIP-1α, and MIP-1β
as the major HIV
-suppressive factors produced by CD8+ T cells. Science. 1995;270:1811–1815.
29. Casazza JP, Brenchley JM, Hill BJ, et al.. Autocrine production of β-chemokines protects CMV-Specific CD4 T cells from HIV
infection. PLoS Pathog. 2009;5:e1000646.
30. Eller MA, Eller LA, Ratto-Kim S, et al.. Single-cell level response of HIV
-specific and cytomegalovirus-specific CD4 T cells correlate with viral control in chronic HIV
-1 subtype A infection. J Acquir Immune Defic Syndr. 2012;61:9–18.
31. Brandt L, Benfield T, Kronborg G, et al.. HIV
-1-infected individuals in antiretroviral therapy
react specifically with polyfunctional T-cell responses to Gag p24. J Acquir Immune Defic Syndr. 2013;63:418–427.
32. Saunders KO, Ward-Caviness C, Schutte RJ, et al.. Secretion of MIP-1β
and MIP-1α by CD8(+) T-lymphocytes correlates with HIV
-1 inhibition independent of coreceptor usage. Cell Immunol. 2011;266:154–164.
33. Whittall T, Peters B, Rahman D, et al.. Immunogenic and tolerogenic signatures in human immunodeficiency virus (HIV
)-infected controllers compared with progressors and a conversion strategy of virus control. Clin Exp Immunol. 2011;166:208–217.
34. Brito A, Almeida A, Gonsalez CR, et al.. Successful HAART is associated with high B-chemokine levels in chronic HIV
type 1-infected patients. AIDS Res Hum Retroviruses. 2007;23:906–912.
35. Berahovich RD, Lai NL, Wei Z, et al.. Evidence for NK cell subsets based on chemokine receptor expression. J Immunol. 2006;177:7833–7840.
36. Kaufmann A, Salentin R, Gemsa D, et al.. Increase of CCR1 and CCR5 expression and enhanced functional response to MIP-1α during differentiation of human monocytes to macrophages. J Leukoc Biol. 2001;69:248–252.
37. Guan E, Wang J, Roderiquez G, et al.. Natural truncation of the chemokine MIP-1β
/CCL4 affects receptor specificity but not anti-HIV
-1 activity. J Biol Chem. 2002;277:32348–32352.
38. Boven LA, Montagne L, Nottet HS, et al.. Macrophage inflammatory protein-1α (MIP-1α), MIP-1β
, and RANTES mRNA semiquantification and protein expression in active demyelinating multiple sclerosis (MS) lesions. Clin Exp Immunol. 2000;122:257–263.
39. Szodoray P, Alex P, Chappell-Woodward CM, et al.. Circulating cytokines
in Norwegian patients with psoriatic arthritis determined by a multiplex cytokine array system. Rheumatology (Oxford). 2007;46:417–425.
40. Pedrosa E, Carretero-Iglesia L, Boada A, et al.. CCL4L polymorphisms and CCL4/CCL4L serum levels are associated with psoriasis severity. J Invest Dermatol. 2011;131:1830–1837.
41. Lutgens E, Faber B, Schapira K, et al.. Gene profiling in atherosclerosis reveals a key role for small inducible cytokines
: validation using a novel monocyte chemoattractant protein monoclonal antibody. Circulation. 2005;111:3443–3452.
42. Tatara Y, Ohishi M, Yamamoto K, et al.. Macrophage inflammatory protein-1β induced cell adhesion with increased intracellular reactive oxygen species. J Mol Cell Cardiol. 2009;47:104–111.
43. Nakata H, Kruhlak M, Kamata W, et al.. Effects of CC chemokine receptor 5 (CCR5) inhibitors on the dynamics of CCR5 and CC-chemokine-CCR5 interactions. Antivir Ther. 2010;15:321–331.
44. Wilkin TJ, Ribaudo HR, Tenorio AR, et al.. The relationship of CCR5 antagonists to CD4+ T-cell gain: a meta-regression of recent clinical trials in treatment-experienced HIV
-infected patients. HIV
Clin Trials. 2010;11:351–358.
45. Asmuth DM, Goodrich J, Cooper DA, et al.. CD4+ T-cell restoration after 48 weeks in the maraviroc treatment-experienced trials MOTIVATE 1 and 2. J Acquir Immune Defic Syndr. 2010;54:394–397.
46. Cuzin L, Trabelsi S, Delobel P, et al.. Maraviroc intensification of stable antiviral therapy in HIV
-1-infected patients with poor immune restoration: MARIMUNO-ANRS 145 study. J Acquir Immune Defic Syndr. 2012;61:557–564.
47. Gulick RM, Lalezari J, Goodrich J, et al.. Maraviroc for previously treated patients with R5 HIV
-1 infection. N Engl J Med. 2008;359:1429–1441.
48. Wilkin TJ, Lalama CM, McKinnon J, et al.. A pilot trial of adding maraviroc to suppressive antiretroviral therapy
for suboptimal CD4 (+) T-cell recovery despite sustained virologic suppression: ACTG A5256. J Infect Dis. 2012;206:534–542.
49. Gutierrez C, Diaz L, Vallejo A, et al.. Intensification of antiretroviral therapy
with a CCR5 antagonist in patients with chronic HIV
-1 infection: effect on T cells latently infected. PLoS One. 2011;6:e27864.
50. Exley AR, Cohen J. Optimal collection of blood samples for the measurement of tumor necrosis factor alpha. Cytokine. 1990;2:353–356.
51. Thavasu PW, Longhurst S, Joel SP, et al.. Measuring cytokine levels in blood. Importance of anticoagulants, processing, and storage conditions. J Immunol Methods. 1992;153:115–124.