DOI: 10.1111/hiv.12108 HIV Medicine (2014), 15, 269–275
© 2013 British HIV Association
ORIGINAL RESEARCH
Coreceptor tropism determined by genotypic assay in HIV-1 circulating in Thailand, where CRF01_AE predominates* A Phuphuakrat,1 S Phawattanakul,1 E Pasomsub,2 S Kiertiburanakul,1 W Chantratita2 and S Sungkanuparph1 Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand and 2 Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
1
Objectives
Chemokine (C-C motif) receptor 5 (CCR5) inhibitors are a novel class of antiretroviral agents that are promising for treatment of patients who harbour the HIV-1 R5 strain. Data on coreceptor tropism in non-B HIV-1 subtypes are limited. We studied coreceptor tropism in HIV-1 circulating in Thailand, where CRF01_AE predominates, using a genotypic assay. Methods
We compiled V3 sequences of HIV-1 strains circulating in Thailand during 2010–2012. Coreceptor tropism was predicted based on V3 sequences using GENO2PHENO version 2.5 (http://coreceptor.bioinf.mpi-inf.mpg.de). Results
One hundred and fifty-five HIV-1-infected patients were enrolled in this study. Ninety-nine patients (63.9%) were antiretroviral-naïve, and the remainder had virological failure. The median (interquartile range) CD4 cell count and HIV-1 RNA were 220 (74–379) cells/μL and 75 374 (14 127–226 686) HIV-1 RNA copies/mL, respectively. Of the sequences obtained from these patients, 119 (76.8%) were CRF01_AE and 22 (14.2%) were subtype B. At a false positive rate of < 5%, 61 (39.4%) HIV-1-infected individuals were predicted to harbour the X4 phenotype. X4 viruses were detected more frequently in the treatment-failure group compared with the treatment-naïve group (30.3 vs. 55.4%, respectively; P = 0.002). Those with CRF01_AE had a higher proportion of X4 viruses compared with non-AE subtypes (47.9 vs. 11.1%, respectively; P < 0.001). By multivariate logistic regression, CRF01_AE and treatment failure were independently associated with predicted X4 phenotype [odds ratio (OR) 7.93; 95% confidence interval (CI) 2.57–24.50; P < 0.001, and OR 3.10; 95% CI 1.50–6.42; P = 0.002, respectively]. Conclusions
CRF01_AE and treatment failure are associated with the predicted X4 phenotype. In regions where CRF01_AE predominates, use of CCR5 inhibitors must be considered with caution. The phenotypic assay and its correlation with genotypes should be further investigated in CRF01_AE. Keywords: CCR5, coreceptor, CXCR4, genotypic testing, HIV-1, Thailand, tropism Accepted 26 September 2013
Introduction
Correspondence: Professor Somnuek Sungkanuparph, Division of Infectious Diseases, Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand. Tel: 2 2011581; fax: 2 2012232; e-mail:
[email protected]
HIV-1 infection requires entry into the target cells as a first step to establish infection. The chemokine receptors chemokine (C-C motif) receptor 5 (CCR5) and chemokine (C-X-C motif) receptor 4 (CXCR4) are usually the main
*Some parts of this study were presented in an oral abstract session at IDWeek 2012, San Diego, CA, 17–21 October 2012 (Abstract 658).
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coreceptors used by HIV-1, together with CD4, to enter target cells [1]. HIV-1 isolates that use CCR5 and CXCR4 are called R5 and X4 strains, respectively. Dual tropic R5X4 strains can use both CCR5 and CXCR4 as coreceptors. R5 strains play an important role in transmission and can be detected in the vast majority of acute and recent infections [2]. X4 strains emerge later and are associated with accelerated disease progression [3]. CCR5 inhibitors are a novel class of antiretroviral agents that are promising for treatment of patients who harbour the R5 strain of HIV-1. Maraviroc (MVC) is the first antiretroviral agent in this group that has been approved for use in both treatment-naïve and treatment-experienced patients in whom only CCR5-tropic virus is detected. The high central nervous system penetration of MVC [4] and R5-dominant neurological strain [5] makes MVC appealing as an intensification regimen in HIV-associated neurocognitive disorder. Also, the safety and tolerability of the drug [6] make it attractive for use as a switch drug in nucleoside reverse transcriptase inhibitor (NRTI)-sparing regimens. Salvage therapy with MVC in combination with other antiretroviral agents in patients who had multi-drugclass resistance demonstrated sustained reductions in plasma viral load [7]. Coreceptor tropism testing should be performed prior to initiation of therapy with CCR5 inhibitors. HIV-1 tropism can be assessed with either phenotypic or genotypic methods. The Trofile assay (Monogram Biosciences, South San Francisco, CA) generates pseudovirions from the patient-derived envelope (env) gene [8]. These virions are used to infect human cell lines expressing either CCR5 or CXCR4. The enhanced sensitivity Trofile assay (ESTA) can detect X4 clones with 100% sensitivity when these clones make up 0.3% of the population. However, its use is limited by its restricted availability and long turnaround time. Genotypic testing of coreceptor usage is based on sequencing of the V3-encoding region of the HIV-1 env gene [9]. Various algorithms and programs are available to predict coreceptor usage from the sequence. Their accessibility, low cost and rapid turnaround time make genotypic assays a more feasible alternative to phenotypic assays [9] . The majority of HIV-1 strains circulating in Thailand are CRF01_AE, followed by subtype B [10,11]. However, the prevalences of R5 and X4 strains are not known. Data on coreceptor usage of HIV-1 CRF01_AE are also limited. Characterization of tropism of HIV-1 circulating in Thailand is crucial for formulating treatment regimens, especially CCR5 inhibitor-containing regimens, for treatment of HIV-1 CRF01_AE infection. We studied CCR5 inhibitor susceptibility in HIV-1 circulating in Thailand using a genotypic assay.
© 2013 British HIV Association
Methods Study population We conducted a cross-sectional study of HIV-1 tropism in HIV-1-infected individuals in Thailand. Plasma samples from treatment-naïve and treatment-experienced HIV-1infected individuals, age ≥ 15 years with viral HIV RNA levels of > 1000 HIV-1 RNA copies/ml, were consecutively collected at a medical school hospital in Bangkok, Thailand from April 2010 to August 2012. Patients whose history of antiretroviral exposure could not be determined were excluded from the study. Subjects in the treatment-naïve group had never been exposed to any antiretroviral agents prior to specimen collection. Patients in the treatmentfailure group had evidence of genotypic resistance to nonnucleoside reverse transcriptase inhibitor (NNRTI)-based or protease inhibitor (PI)-based regimens corresponding to the current antiretroviral regimen used. Documented resistance in reverse transcriptase (RT) and protease (PR) regions was obtained in the treatment-failure group during routine resistance monitoring using TRUGENE™ (Siemens, Erlangen, Germany). The minimum duration of receipt of antiretroviral therapy (ART) was 6 months. All patients were initiated on ART according to the 2008 Thai national guidelines [12]. None of the patients were MVC exposed. The study was approved by the Institutional Review Board of Ramathibodi Hospital.
Genotypic study and data analysis Ethylenediaminetetraacetic acid (EDTA) plasma samples were used for RNA extraction using the NucliSENS easyMAG platform (bioMérieux, Marcy l’Etoile, France) according to the manufacturer’s protocol. The extracted RNA was then subjected to a two-step reverse transcriptase− polymerase chain reaction (RT-PCR) with two sets of primers: forward primer, 5' GAG CCA ATT CCC ATA CAT TAT TGT and reverse primer, 5' GCC CAT AGT GCT TCC TGC TGC TCC CAA GAA CC for RT-PCR and forward primer, 5' TGT GCC CCA GCT GGT TTT GCG AT and reverse primer, 5' TAT AAT TCA CTT CTC CAA TTG TCC for nested PCR. The sequencing primers were 5' AAT GTC AGY ACA GTA CAA TGT ACA C (forward) and 5' GAA AAA TTC CCT TCC ACA ATT AAA (reverse). The sequencing reaction was performed in triplicate using Big-Dye® Terminator v1.1 with the ABI PRISM 3100 genetic analyser (Applied Biosystems, Foster City, CA). The V3 sequences were analysed using SEQSCAPE® v2.7 (Applied Biosystems). Viral tropism was predicted using the genotypic tool GENO2PHENO version 2.5 [13] (http://coreceptor.bioinf.mpi -inf.mpg.de). The lowest false positive rate (FPR) for the
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HIV-1 coreceptor tropism in Thailand 271
replicates was used to determine the overall tropism of the patient’s virus. Based on German guidelines, tropisms were divided into three groups according to the FPR (the likelihood of incorrectly identifying an R5 virus as X4). The cut-offs were set at 5 and 15%. An FPR of ≤ 5% predicts the virus to be X4, and thus CCR5 inhibitors are not likely to be effective. An FPR of > 15% predicts the virus to be R5, and hence CCR5 inhibitors are likely to be effective. An FPR between 5 and 15% predicts that the drug may be useful. Virus subtypes were determined based on V3 nucleotide sequences using the GENO2PHENO webpage. Subtype analysis based on RT was performed using the COMET tool (available at http://comet.retrovirology.lu). The V3 consensus sequence and characteristics of each subtype or circulating recombinant form (CRF) were obtained using WEBLOGO3 (available at http://weblogo.threeplusone.com/create.cgi).
Statistical analysis Mean and standard deviation (SD), median and interquartile range (IQR), and frequencies (%) were used to describe patients’ characteristics. The χ2 test and independent t-test or Mann−Whitney U-test were used to compare categorical variables and continuous variables between the two groups, respectively. Univariate logistic regression was used to determine the factors associated with reduced CCR5 inhibitor susceptibility. Variables that presented P < 0.10 were considered in a multivariate logistic regression model after assessment of multicollinearity of variance inflation factors. The selected variables were included in a multiple logistic regression model with forward selection and those that attained significance (P < 0.05) were retained in the model. The odds ratio (OR) and its 95% confidence interval (CI) were estimated. A P-value < 0.05 was considered statistically significant. All statistical analyses were
performed using the SPSS statistical software version 18 (SPSS Inc., Chicago, IL).
Results For this study, 155 HIV-1-infected individuals were recruited. Sixty-six (42.6%) of the individuals were female, and their mean (SD) age was 37.1 ± 11.2 years. The median (IQR) CD4 cell count and HIV-1 RNA viral load were 220 (74–379) cells/μL and 75 374 (14 127–226 686) HIV-1 RNA copies/mL, respectively. Of the sequences obtained from these patients, 119 (76.8%) were CRF01_AE, 22 (14.2%) were subtype B, and 14 (9.0%) were subtype A. Ninety-nine patients (63.9%) were antiretroviral-naïve, and the remainder had experienced virological failure of NNRTI- or PI-based antiretroviral regimens. Age, HIV-1 subtype and CD4 cell count were not different between the treatmentnaïve and treatment-failure groups. However, gender and viral load and were different between the groups. The characteristics of individuals recruited for this study are shown in Table 1. Greater than 80% agreement between subtyping based on the V3 loop and subtyping based on RT was found. The sequence characteristics of the HIV-1 V3 loop of each subtype in this study were examined (Fig. 1). Comparing CRF01_AE with subtype B, there were amino acid differences in the consensus sequence at the following positions: 5, N in subtype B but S in CRF01_AE; 10, K in subtype B but T in CRF01_AE; 13, H in subtype B but T in CRF01_AE; 18, R in subtype B but Q in CRF01_AE; 19, A in subtype B but V in CRF01_AE; 22, A in subtype B but R in CRF01_AE; 32, Q in subtype B but K in CRF01_AE; and 34, H in subtype B but Y in CRF01_AE. A basic amino acid at position 11 and/or 25 is associated with the X4 phenotype [14]. Of note, 10.1 and 1.3% of CRF01_AE sequences harboured R at position 11 and K at position 25, respectively.
Table 1 Characteristics of HIV-1-infected patients Treatment naïve
Characteristics Male gender [n (%)] Age (years) [median (IQR)] CD4 count (cells/μL) [median (IQR)] HIV-1 RNA (copies/ml) [median (IQR)] Subtype [n (%)] A B CRF01_AE
Treatment failure
CD4 ≥ 350 cells/μL (n = 31)
CD4 < 350 cells/μL (n = 68)
Before ART initiation (n = 56)
At tropism testing (n = 56)
19 (61.3) 34.5 (29.0–44.6) 491 (443–648) 19,580 (7,748–116,950)
45 (66.2) 36.6 (29.7–45.4) 107 (41–252) 162,494 (64,566–314,303)
25 (44.6) 36.6 (30.1–44.6) 155 (78–301) 43,200 (11,773–135,208)
25 (44.6) 36.9 (30.8–44.5) 188 (69–297) 29,050 (7,326–109,621)
3 (9.7) 4 (12.9) 24 (77.4)
9 (13.2) 8 (11.8) 51 (75.0)
2 (3.6) 10 (17.9) 44 (78.6)
ART, antiretroviral therapy; IQR, interquartile range.
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Subtype A
Subtype B
CRF01_AE
Fig. 1 Sequence logos of V3 residue sequences in this study. The size of each logo represents the proportion of patients with the amino acid at a specific site.
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