Share this article on:

Immunological Recovery After 24 Weeks of Antiretroviral Therapy in Patients With X4 Virus During Primary HIV Infection

Nozza, Silvia MD*; Pignataro, Angela R. MSc; Galli, Laura MSc*; Ripa, Marco MD; Boeri, Enzo MD; Chiappetta, Stefania MD*,†; Galli, Andrea MSc*; Canducci, Filippo MD; Sampaolo, Michela MSc; Clementi, Massimo MD; Lazzarin, Adriano MD*,†; Tambussi, Giuseppe MD*

JAIDS Journal of Acquired Immune Deficiency Syndromes: January 1st, 2014 - Volume 65 - Issue 1 - p e27–e29
doi: 10.1097/QAI.0b013e3182a03ed2
Letters to the Editor

*Department of Infectious Diseases, San Raffaele Scientific Institute, Milan, Italy

University Vita-Salute, San Raffaele Scientific Institute, Milan, Italy

The authors have no funding or conflicts of interest to disclose.

To the Editors:

Back to Top | Article Outline


CXCR4 coreceptor usage has been associated with faster infection progression.1 The proportion of antiretroviral-naïve patients harboring CXCR4 viruses varies between 10% and 38%.2–4 Recent studies estimated the prevalence of CXCR4-using virus in primary HIV infection (PHI) at 6%–19%.5–8 This variability may be influenced by differences in methodology for coreceptor determination based on phenotypic determination or genotypic assays, recently applied in clinical practice: sequence of HIV-1 gp120 V3 loop region is used to infer coreceptor usage by algorithms as geno2pheno10%,9,10 position-specific scoring matrices (PSSMx4r5),11 and distant segments Kernel [(ds)Kernel].12 Aims of this study were to determine the proportion of CXCR4 tropism during PHI according to 3 genotypic assays and to evaluate if predicted coreceptor usage is associated with immunovirological response to antiretroviral therapy (ART).

Back to Top | Article Outline


The study included 66 patients with PHI followed at the Department of Infectious Diseases of the San Raffaele Scientific Institute. PHI was defined on the basis of a positive plasma HIV RNA and a negative/indeterminate Western Blot assay. Genotypic tropism test was performed using stored plasma and peripheral blood mononuclear cells (PBMCs) samples. Demographic and clinical characteristics used in the analysis were as follows: age, gender, HIV risk factor, Centers for Disease Control and Prevention stage of HIV infection, HCV status, year of HIV infection, CD4+ and CD8+–cell count, HIV RNA at the date of sample collection. The date of ART initiation was considered as baseline. Immunovirological parameters were determined at baseline and at week 24. HIV-1 coreceptor usage was determined on first available plasma sample using the following 3 different genotypic tools: the clonal version of genotypic algorithm geno2pheno adopting a false-positive rate (FPR) of 10% in plasma and 20% in PBMCs according to current European guidelines; PSSMx4r5 (position-scoring specific matrices); and (ds)Kernel (distant segment Kernel). In twenty subjects GP120 V3 loop sequences were obtained also from PBMC HIV DNA at baseline (T0), at the time of achievement of a plasma viral load <50 copies per milliliter (T1), and at week 48 (T2).

Back to Top | Article Outline

Statistical Analysis

Demographic and clinical characteristics were described as median (interquartile range) or frequency (%) as appropriate. McNemar's test of symmetry, for paired data, was used to test the equality of the off-diagonal frequencies obtained when comparing 2 different methods for assessing the presence of CXCR4 virus (determined by a false-positive rate ≤10%). Agreement between different methods for coreceptor usage prediction was assessed by the estimate of the Cohen Kappa (K) statistic (and their corresponding 95% confidence interval). The K values >0.75 suggest excellent agreement beyond that determined by chance; values >0.4 and <0.75 indicate fair to good agreement; and values <0.4 indicate poor agreement.

Characteristics of patients with CXCR4 or CCR5 virus were compared by the Mann–Whitney U test, χ2, or Fisher's exact test, as appropriate. Changes between baseline and week 24 were evaluated by the Wilcoxon sign test. Linear correlation was determined by the Spearman rank coefficient. The generalized linear model was used at multivariate analysis to evaluate predictive factors of immunological recovery after 24 weeks of ART; 3 models were calculated, including baseline CD4+ and CD8+–cell count, plasma HIV RNA, age, risk factor, virus subtype, and coreceptor usage predictions alternatively determined by geno2pheno10%, PSSMx4r5 and (ds)Kernel. A 2-sided P value less then 0.05 was used to indicate statistical significance. Statistical analyses were performed using the software SAS (SAS Institute, release 9.2).

Back to Top | Article Outline


Sixty-six patients followed since January 2001 through March 2012 were diagnosed with PHI. Baseline characteristics are shown in Table 1. At diagnosis, coreceptor usage was determined on plasma samples collected 21 (10–31) days after diagnosis. Proportion of CXCR4 viruses by geno2pheno10% was not influenced by the calendar year of HIV infection [2001–2004: 5/24 (20.8%); 2005–2008: 4/21 (19.1%); 2009–2012: 6/21 (28.6%); P = 0.734].



Fifteen (22.7%), 2 (3.0%), and 5 (7.6%) patients were classified as harboring CXCR4-using virus using geno2pheno10%, PSSMx4r5, and (ds)Kernel algorithms, respectively. Geno2pheno10% and PSSMx4r5 were concordant for 53 (80%) patients, although geno2pheno10% and (ds)Kernel predicted the same coreceptor usage in 52 (79%) patients. Agreement between geno2pheno10% and PSSMx4r5 was small (k = 0.192, P = 0.003), and between geno2pheno10% and (ds)Kernel (k = 0.210, P = 0.008). No significant differences between CCR5 and non-CCR5 tropism were found regardless of algorithm choice.

Twenty PBMCs samples were analyzed for proviral DNA tropism evaluation; coreceptor usage prediction by geno2pheno10% on viral RNA and proviral DNA agreed in 17 (85%) patients (k = 0.667, P = 0.250). There was no significant variation between FPR obtained for the baseline genotypes of HIV RNA and HIV DNA (P = 0.074); and in 2 of the 3 discordant cases, we found the same genotype and FPR on viral RNA and proviral DNA, although the remaining patient had FPR between 10% and 20% on both HIV RNA and HIV DNA. Samples from RNA had also a higher number of polymorphisms in the sequenced V3 when compared with the sequences from DNA. There were no significant variations between FPR values at baseline obtained from HIV RNA and subsequent FPR values inferred from proviral DNA (T1: P = 0.066; T2: P = 0.139).

All patients started ART after a median (interquartile range) of 7 (0–454) days since sample collection as follows: 40 (61%) patients started a protease inhibitor–based therapy, 10 (15%) patients started a nonnucleoside reverse transcriptase inhibitor–based treatment, and 16 (24%) patients started a regimen including maraviroc or raltegravir. By week 24, 14 (21%) subjects changed the type of antiretroviral regimen or discontinued ART [5 (8%) patients]. No association was found between regimens at baseline (P = 0.453) and the proportion of CXCR4-predicted viruses by geno2pheno10%. Moreover, change or discontinuation of antiretroviral regimen were not associated with the frequency of CXCR4-using viruses by geno2pheno10% (P = 0.069). Achievement of HIV RNA <50 copies per milliliter at week 24 was obtained in 40 (61%) patients and was not associated with viral tropism assessed by geno2pheno10% (P = 0.877). Greater CD4+-cell increase was observed in patients harboring CXCR4-using virus based on geno2pheno10% [X4 vs R5: 265 (180–370) vs 196 (88–280) cells/μL, P = 0.032]; PSSMx4r5 [X4 vs R5: 383 (296–470) vs 203 (107–302) cells/μL, P = 0.109]; or (ds)Kernel [X4 vs R5: 370 (296–470) vs 199 (92–280) cells/μL, P = 0.015]. The correlation between CD4+-cell recovery and the HIV RNA decrease was differently influenced by coreceptor usage prediction by geno2pheno10% [X4: r = 0.192, P = 0.529; R5: r = 0.389, P = 0.005].

At multivariate analysis, coreceptor usage prediction was a significant predictive factor of immunological response together with HIV RNA load and viral subtype [(R5-predicted tropism: Geno2pheno10%: β=−95.8, P = 0.045; PSSMx4r5: β = −219.1, P = 0.046; (ds)Kernel: β=−173.5, P = 0.014); (HIV-RNA per log10copies/ml: Geno2pheno10%: β = 44.5, P = 0.041; PSSMx4r5: β = 49.8, P = 0.023; (ds)Kernel: β = 42.3, P = 0.048); (virus subtype B: Geno2pheno10%: β = −133.7, P = 0.048; PSSMx4r5: β = −141.0, P = 0.039; (ds)Kernel: β = −153.2, P = 0.023)].

Back to Top | Article Outline


Twenty-three percent of the patients with PHI were defined as harboring CXCR4-using viruses using the geno2pheno10% algorithm, whereas PSSMx4r5 and (ds)Kernel identified a smaller proportion. Previous studies reported a lower percentage,5–8 about 10%, based on phenotypic assay. CCR5-tropic variants still represent the majority of strains found during PHI, probably due to a lower transmission rate of CXCR4 viruses.13,14

The association between higher viral load and coreceptor use is controversial,2,4 and we did not observe a higher prevalence of CXCR4 viruses in patients with viral load more than 100.000 copies per milliliter.

Concordance between PSSMx4r5 and (ds)Kernel with geno2pheno10% was shown to be 79% and 80%, respectively: the differences in coreceptor usage prediction were due to a lower frequency of CXCR4-using virus identified by PSSMx4r5 and (ds)Kernel.

HIV-1–predicted tropism in paired plasma and PBMC was similar; this is consistent with the observation that the virus population is more homogenous during PHI than in advanced disease.13–16

In V3 loop sequences obtained from DNA, we found a lower number of polymorphisms; this observation is interesting, assuming that the DNA should be more representative of the infecting quasispecies. There was no significant variation between value of FPR and predicted tropism in different time points.

One Association between CXCR4 use and low CD4 count is known in chronic infected patients,1–4 but not during PHI. Chronic HIV-infected patients with CXCR4-using viruses are described as having faster disease progression compared with patients with CCR5-tropic strains. Our analysis did not support this relation, and we found a greater CD4+-cell increase after initiation of ART in patients harboring CXCR4-using virus, regardless of algorithm choice. Patients with CXCR4-tropic viruses have a greater CD4-cell decrease without ART,4 and in chronic patients HIV tropism has no impact on immunovirological response.2 CXCR4-tropic viruses replication is lower than that of CCR5 variants in GALT, and CCR5 viruses are also more prone to infect macrophages especially during PHI.17 Starting ART during PHI in patients with CXCR4 viruses could help in increasing plasma CD4+ cells by targeting viral replication in peripheral blood, whereas ART has a limited effect on GALT CD4+-cell depletion which occurs mainly due to CCR5 variants.18 This may explain our findings of a better immunological recovery as measured by plasma CD4+-cell increase. The influence of predicted coreceptor usage on GALT CD4-cell depletion remains unclear.

All of the patients had antiretroviral syndrome, and no data are available regarding the association between symptoms and coreceptor usage: this could represent a selection of more pathogenic viruses, usually CXCR4 using.2 Further studies with phenotypic assays are needed to better evaluate the feasibility of genotypic methods to predict coreceptor usage in the setting of PHI. In conclusion our study remarks an immunological recovery in patients treated during PHI, even if harboring CXCR4-tropic virus; these results encourage treatment during this phase of infection.

Back to Top | Article Outline


The authors are grateful to Liviana Della Torre for clinical assistance. They are also grateful to the patients who participated in this study.

Back to Top | Article Outline


1. Koot M, van Leeuwen R, de Goede RE, et al.. Conversion rate towards a syncytium-inducing (SI) phenotype during different stages of human immunodeficiency virus type 1 infection and prognostic value of SI phenotype for survival after AIDS diagnosis. J Infect Dis. 1999;179:254–258.
2. Waters L, Mandalia S, Randell P, et al.. The impact of HIV tropism on decreases in CD4 cell count, clinical progression, and subsequent response to a first antiretroviral therapy regimen. Clin Infect Dis. 2008;46:1617–1623.
3. Simon B, Grabmeier-Pfistershammer K, Rieger A, et al.. HIV coreceptor tropism in antiretroviral treatment-naive patients newly diagnosed at a late stage of HIV infection. AIDS. 2010;24:2051–2058.
4. Nozza S, Canducci F, Galli L, et al.. Viral tropism by geno2pheno as a tool for predicting CD4 decrease in HIV-1-infected naive patients with high CD4 counts. J Antimicrob Chemother. 2012;67:1224–1227.
5. Frange P, Chaix ML, Raymond S, et al.. Low frequency of CXCR4-using viruses in patients at the time of primary non-subtype-B HIV-1 infection. J Clin Microbiol. 2010;48:3487–3491.
6. Raymond S, Delobel P, Mavigner M, et al.. CXCR4-using viruses in plasma and peripheral blood mononuclear cells during primary HIV-1 infection and impact on disease progression. AIDS. 2010;24:2305–2312.
7. Raymond S, Saliou A, Nicot F, et al.. Frequency of CXCR4-using viruses in primary HIV-1 infections using ultra-deep pyrosequencing. AIDS. 2011;25:1668–1670.
8. Hamlyn E, Hickling S, Porter K, et al.. Increased levels of CD4 T-cell activation in individuals with CXCR4 using viruses in primary HIV-1 infection. AIDS. 2012;26:887–890.
9. McGovern RA, Thielen A, Mo T, et al.. Population-based V3 genotypic tropism assay: a retrospective analysis using screening samples from the A4001029 and MOTIVATE studies. AIDS. 2010;24:2517–2525.
10. Vandekerckhove LPR, Wensing AM, Kaiser R, et al.. European guidelines on the clinical management of HIV-1 tropism testing. Lancet Infect Dis. 2011;11:394–407.
11. Jensen MA, Li F, Van ’t Wout AB, et al.. Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences. J Virol. 2003;77:13376–13388.
12. Boisvert S, Marchand M, Laviolette F, et al.. HIV-1 coreceptor usage prediction without multiple alignments: an application of string kernels. Retrovirology. 2008;5:110.
13. Grivel JC, Shattock RJ, Margolis LB. Selective transmission of R5 HIV-1 variants: where is the gatekeeper? J Transl Med. 2011;9(suppl 1):S6.
14. Parisi SG, Andreoni C, Sarmati L, et al.. HIV coreceptor tropism in paired plasma, peripheral blood mononuclear cell, and cerebrospinal fluid isolates from antiretroviral-naïve subjects. J Clin Microbiol. 2011;49:1441–1445.
15. Verhofstede C, Vandekerckhove L, Eygen VV, et al.. CXCR4-using HIV type 1 variants are more commonly found in peripheral blood mononuclear cell DNA than in plasma RNA. J Acquir Immune Defic Syndr. 2009;50:126–136.
16. Swenson LC, Dong WWY, Mo T, et al.. Use of cellular HIV DNA to predict virologic response to maraviroc: performance of population-based and deep sequencing. Clin Infect Dis. 2013:1–8.
17. Gorry PR, Ancuta P. Coreceptors and HIV-1 pathogenesis. Curr HIV/AIDS Rep. 2011;8:45–53.
18. Mehandru S, Poles MA, Tenner-Racz K, et al.. Lack of mucosal immune reconstitution during prolonged treatment of acute and early HIV-1 infection. PLoS Med. 2006;3:e484.
© 2014 by Lippincott Williams & Wilkins