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Molecular and Clinical Epidemiology of CXCR4-Using HIV-1 in a Large Population of Antiretroviral-Naive Individuals

  1. Zabrina L. Brumme1,2,
  2. James Goodrich3,
  3. Howard B. Mayer3,
  4. Chanson J. Brumme1,
  5. Bethany M. Henrick1,
  6. Brian Wynhoven1,
  7. Jerome J. Asselin1,
  8. Peter K. Cheung1,
  9. Robert S. Hogg1,
  10. Julio S. G. Montaner1,2 and
  11. P. Richard Harrigan1,2
  1. 1BC Centre for Excellence in HIV/AIDS, St. Paul’s Hospital, and
  2. 2Faculty of Medicine, University of British Columbia, Canada;
  3. 3Pfizer, Inc., New London, Connecticut
  1. Reprints or correspondence: Dr. P. Richard Harrigan, BC Centre for Excellence in HIV/AIDS, 603-1081 Burrard St., Vancouver, BC, Canada V6Z 1Y6 (richard{at}hivnet.ubc.ca)
 
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Abstract

ObjectiveWe wished to characterize the epidemiological and clinical correlates of CXCR4-using human immunodeficiency virus type 1 (HIV-1) (“X4 variants”) in a cross-sectional analysis of a large population of antiretroviral-naive individuals

MethodsHIV-1 coreceptor use was determined in the last pretherapy plasma sample for 1191 individuals initiating triple-combination therapy in British Columbia, Canada. Baseline variables investigated included sociodemographic characteristics, plasma viral load (pVL), CD4 cell count, AIDS diagnosis, HIV-1 V3 loop sequence, and human CCR5 Δ32 genotype

ResultsIndividuals harboring X4 variants (n=178 of 979 phenotyped samples; 18.2%) displayed a poorer baseline clinical profile than individuals harboring exclusively CCR5-using HIV-1 (“R5 variants”) (median pVL, 175,000 vs. 120,000 copies of HIV-1 RNA/mL [P=.0006]; median CD4 cell count, 110 vs. 290 cells/mm3 [P<.0001]). Individuals heterozygous for the CCR5 Δ32 deletion (n=128 of 967; 13.2%) were at 2.5 times higher risk of harboring X4 variants, compared with those without the deletion (multivariate P=.0005). The presence of basic amino acids at codon 11 and/or codon 25 of HIV-1 V3 (n=109 of 955; 11.4%) was associated with a 9.1 times higher risk of harboring X4 variants (multivariate P<.0001), regardless of CCR5 Δ32 genotype. In multivariate analyses adjusting for baseline parameters, HIV-1 coreceptor use was not found to be a significant predictor of survival or treatment response

ConclusionBaseline CD4 cell count, pVL, HIV-1 V3 sequence, and CCR5 Δ32 genotype were the strongest determinants of CXCR4-using HIV-1 in this population. After adjustment for baseline parameters, the presence of X4 variants before initiation of highly active antiretroviral therapy was not independently associated with a poorer outcome of therapy

HIV-1 uses host cell membrane chemokine receptors in combination with CD4 to gain entry into host cells [1 –3]. The most important coreceptors in HIV-1 pathogenesis are the chemokine receptors CCR5 [1, 2, 4] and CXCR4 [5], although, in rare cases, other coreceptors have also been shown to mediate entry of HIV-1 into target cells, at least in vitro [6 –8]. In general, most HIV-1 variants isolated from newly infected individuals utilize CCR5 in combination with CD4 to gain entry to host cells. These “R5 variants” predominantly infect activated CD4 cells, as well as macrophages. While R5 variants are generally detectable over the entire course of HIV-1 infection [9], variants able to utilize CXCR4 emerge in ∼40%–50% of infected persons over the course of disease [10]. These “X4 variants” predominantly target naive and resting CD4 cells and display biological properties that differ from those of their R5 counterparts, including increased replication rate, pathogenicity, and syncytium-inducing (SI) capacity in immortalized CD4 cell lines [9, 11]. In addition, dual-tropic variants capable of using both CXCR4 and CCR5 may also arise over the course of disease [12]

The factors mediating the R5-to-X4 phenotype “switch” over the natural course of HIV-1 infection remain incompletely understood. The emergence of CXCR4-using variants is associated with a rapid decline in CD4 cell counts, accelerated disease progression, and reduced survival time in untreated individuals [13 –16], as well as poorer response to treatment in the pre–highly active antiretroviral therapy (HAART) era [17 –21]. However, it is not known whether X4 variants are inherently more pathogenic and are directly responsible for more-rapid disease progression or whether CXCR4-using HIV-1 variants may emerge as a consequence of progressive immune dysfunction [22]. Regardless of the direction of causation, the association of X4 HIV-1 with poorer prognosis and inferior therapy response remains an important issue in clinical practice, and it is important that the prognostic implications of HIV-1 coreceptor use be re-evaluated in the HAART era

At present, the epidemiology of R5 and X4 HIV-1 is also of particular relevance, because of the development of HIV-1 coreceptor inhibitors. This new class of antiretroviral agents is designed to specifically inhibit HIV-1 binding to CCR5 and/or CXCR4, thereby preventing HIV-1 entry into target cells. Although coreceptor inhibitors currently show promising effects in early clinical trials [22, 23], it is not known on a population basis what proportion of HIV-1–infected individuals may potentially benefit most from antiretroviral agents targeting CCR5 and/or CXCR4

Using the newly developed ViroLogic PhenoSense HIV entry assay, we investigated the epidemiology of HIV-1 coreceptor use in the HAART Observational Medical Evaluation and Research (HOMER) Cohort in British Columbia, Canada, consisting of 1191 antiretroviral-naive individuals initiating their first triple-combination therapy between August 1996 and September 1999 [24, 25]. In this cross-sectional study, we wished to characterize the prevalence of X4 HIV-1 at therapy initiation and to identify sociodemographic, clinical, and genetic risk factors associated with phenotypic CXCR4 use. Finally, using longitudinal clinical data collected over the course of study follow-up, we wished to establish the impact of CXCR4 coreceptor use on clinical and virological outcomes after initiation of first triple-combination therapy

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Subjects and Methods

The BC Centre for Excellence in HIV/AIDS Drug Treatment Program In the province of British Columbia, Canada, antiretrovirals are distributed free of charge to HIV-1–infected individuals, through a centralized drug treatment program based at the BC Centre for Excellence in HIV/AIDS. Antiretrovirals are prescribed according to specific guidelines set by the BC Therapeutic Guidelines Committee, which are revised regularly and are in accordance with international guidelines [24]. Patients who enroll in the program may provide informed consent and participate in a survey that collects sociodemographic data. Routine clinical monitoring of patients takes place at ∼3-month intervals, at which time plasma viral load (pVL) testing (Roche Amplicor Monitor Assay) and CD4 cell counts are performed. These data are stored in the Centre’s Drug Treatment Program database. Ethical approval for this study was obtained from the ethics board of Providence Health Care/University of British Columbia

The HOMER Cohort The HOMER Cohort includes all HIV-positive, antiretroviral-naive adults who started triple-combination therapy (consisting of 2 nucleoside reverse-transcriptase inhibitors and either a protease inhibitor [PI] or a nonnucleoside reverse-transcriptase inhibitor [NNRTI]) through the BC Drug Treatment Program between August 1996 and September 1999 (n=1191). This cohort has been the focus of a number of population-based studies and has been described in detail elsewhere [24, 25]. Subjects were followed for a median of 4.7 years (56 months) after initiation of antiretroviral therapy

Determination of baseline HIV-1 coreceptor phenotype and envelope V3 genotype For each study subject, a single pretherapy (baseline) plasma sample collected ⩽6 months before initiation of therapy was assayed using the ViroLogic PhenoSense HIV entry assay, to determine HIV-1 coreceptor use. Viral RNA was extracted using oligo(dT) columns, and HIV-1 env–specific primers were used to amplify a 2.5-kb reverse-transcription (RT) polymerase chain reaction (PCR) product that spanned the entire gp160 open reading frame. RT-PCR products were digested, purified, and ligated into an E. coli expression vector, and gene libraries were constructed. A replication-defective retroviral vector (pHIVluc) containing a luciferase expression cassette inserted within the env gene was used to cotransfect human embryonic kidney cell cultures with the sample plasmid DNA. Recombinant viruses were harvested after 48 h and were assessed for their ability to infect cells expressing CCR5 or CXCR4. The PhenoSense assay classifies isolates as R5, X4, or R5/X4 (indicating dual and/or mixed-tropic virus)

The same baseline plasma samples were used to determine HIV-1 V3 envelope sequence, as described elsewhere [25]. Isolates displaying positively charged amino acids at codon 11 and/or codon 25 of HIV-1 V3 [26], associated with an HIV-1 SI phenotype [26], were classified as having an “11/25 genotype” [25]

Determination of CCR5 Δ32 genotype Blood (n=796; 66.8%) or plasma (n=395; 33.2%) samples were available from all 1191 study subjects. DNA was extracted from blood or plasma by use of the Qiagen DNA kit adapted for use on the Qiagen Biorobot 9604. Extracted DNA was amplified in a single round of PCR using primers flanking the CCR5 Δ32 region. PCR products were visualized by electrophoresis on a 2% agarose gel and confirmed by automated DNA sequencing in both 5′ and 3′ directions on an ABI 3700 DNA sequencer (Applied Biosystems)

Statistical methods Associations between baseline HIV-1 coreceptor use and dichotomous baseline parameters, including sex, AIDS diagnosis, history of injection drug use, human CCR5 genotype (CCR5 wild-type [wt]/Δ32 or CCR5 wt/wt) and HIV-1 V3 11/25 genotype (present or absent) [25] were determined using the χ2 test. Associations between baseline HIV-1 coreceptor use and continuous variables, including age, pVL, and CD4 cell count, were determined using the Wilcoxon&amp;rank-sum test. Baseline predictors of CXCR4 use and associated odds ratios (ORs) were calculated using univariate and multivariate logistic regression

The primary end point investigated in the outcome analyses was time to nonaccidental death, defined as the time from therapy initiation to nonaccidental death (occurring on or before 30 June 2003, the date of latest linkage with mortality statistics from the British Columbia Vital Statistics Agency). Deaths were classified in accordance with International Classification of Diseases, Tenth Revision coding. Accidental deaths were not considered to be events, and subjects who died accidental deaths were censored at the date of death. Additional clinical outcomes included time to suppression of pVL (time from therapy initiation to first of 2 consecutive pVLs <500 copies of HIV-1 RNA/mL), time to pVL rebound (subsequent time to the first of 2 consecutive pVLs >500 copies of HIV-1 RNA/mL), and time to CD4 cell count decline (time to first decline of CD4 cell count below baseline). For the clinical outcome analyses, event-free subjects were censored at the collection date of the last tested sample up to and including 30 June 2003

The influence of HIV-1 coreceptor use on clinical outcomes was assessed by Kaplan-Meier methods. Cox proportional hazards regression was used to calculate univariate and multivariate hazard ratios (HRs) and 95% confidence intervals (CIs). Baseline variables included in the model were sex (male vs. female [reference group]), age (per 10-year increment), AIDS diagnosis (yes vs. no), pVL (per log10 increment), CD4 cell count (per 100-cell/mm3 decrement), proportion of total time spent receiving antiretroviral therapy during the first year of follow-up (per 10% increment) [27], type of therapy at initiation (PI vs. NNRTI containing), history of injection drug use (yes vs. no), CCR5 genotype (CCR5 wt/Δ32 vs. CCR5 wt/wt) and HIV-1 V3 11/25 genotype (present vs. absent) [25]

In both the logistic regression and Cox proportional hazards regression analyses, all factors significant in univariate analyses were included in multivariate analyses. All tests of significance were 2-sided, with P<.05 indicating statistical significance

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Results

Results of HIV-1 coreceptor phenotyping The prevalence and determinants of HIV-1 coreceptor use were investigated in the HOMER Cohort [24, 25] of 1191 antiretroviral-naive individuals initiating therapy. HIV-1 coreceptor use data were obtained for 979 of 1191 subjects (82.2%). Phenotype data were more likely to be available for male subjects (P=.043) and for subjects with higher pVLs (P<.0001), lower CD4 cell counts (P = .007), and the CCR5 wt/wt genotype (P = .007) (table 1). Of the 979 phenotyped subjects, 801 (81.8%) harbored R5 variants, 177 (18.1%) harbored R5/X4 variants, and only 1 (0.1%) harbored exclusively X4 variants. For the remainder of the analyses, this subject was included in the R5/X4 group

Figure 1
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Figure 1

Influence of HIV-1 coreceptor use on survival and clinical outcomes after initiation of first triple-combination antiretroviral therapy. Shown are Kaplan-Meier analyses of the influence of baseline HIV-1 coreceptor use (R5 vs. R5/X4 virus) on time to nonaccidental death (A) time to CD4 cell count decline below baseline (B) and time to plasma viral load (pVL) rebound to >500 copies/mL (C) after initiation of first triple-combination antiretroviral therapy, over a median follow-up time of 56 months. Individuals with R5 HIV-1 are represented by circles (○), and individuals with R5/X4 HIV-1 are indicated by plus signs (+). D Kaplan-Meier analysis of the influence of combined human CCR5 Δ32 genotype and HIV-1 coreceptor use on time to nonaccidental death after initiation of therapy. Categories are as follows: CCR5 wt/Δ32 genotype, R5 HIV-1 (plus signs [+]); CCR5 wt/wt genotype, R5 HIV-1 (stars [*]); CCR5 wt/Δ32 genotype, R5/X4 HIV-1 (circles [○]); and CCR5 wt/wt genotype, R5/X4 HIV-1 (triangles [Δ])

Table 1
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Table 1

Patient characteristics at baseline, stratified by HIV-1 coreceptor use

Baseline characteristics stratified by HIV-1 coreceptor use in an antiretroviral-naive population Comparison of baseline parameters in subjects harboring R5/X4 variants with those in subjects harboring exclusively R5 variants revealed several important differences in clinical characteristics (table 1). Subjects with R5/X4 variants had significantly higher pVLs (P=.0006) and lower CD4 cell counts (P<.0001) and were significantly more likely to have an AIDS-defining illness before therapy initiation (P<.0001). The distribution of HIV-1 coreceptor use at clinically useful CD4 cell count strata highlights the strong association between the detection of X4 variants and absolute CD4 cell count at baseline, ranging from <10%, for counts >200 cells/mm3, to >50%, for counts <25 cells/mm3 (table 2)

Table 2
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Table 2

Distribution of R5/X4 HIV-1, stratified by baseline CD4 cell count

As expected, subjects with basic amino acids at codon 11 and/or codon 25 of HIV-1 V3 (an 11/25 genotype [25, 26]), were significantly more likely to harbor R5/X4 HIV-1 variants (P<.0001) (table 1) than were subjects with neutral or negatively charged residues at these sites. The 11/25 genotype, in this case evaluated using direct PCR and population-based sequencing of patient-derived isolates, displayed a specificity of 93.1% but a sensitivity of only 32.7% for predicting the presence of X4 variants. In addition, subjects heterozygous for the CCR5 Δ32 deletion (CCR5 wt/Δ32) were also significantly more likely to harbor R5/X4 HIV-1 variants than were subjects with the CCR5 wt/wt genotype (P=.0085) (table 1)

Baseline characteristics stratified by combined CCR5 genotype and HIV-1 phenotype data To further investigate the association between CCR5 Δ32 genotype and R5/X4 HIV-1, we combined the human CCR5 genotype and HIV-1 coreceptor use data. Combined HIV-1 phenotype and human CCR5 genotype data were available for 967 subjects (table 3). The 4 categories (CCR5 wt/wt R5 phenotype [n=697]); CCR5 wt/wt R5/X4 phenotype [n=142]; CCR5 wt/Δ32 R5 phenotype [n=94]; and CCR5 wt/Δ32 R5/X4 phenotype [n=34]) were compared with respect to baseline sociodemographic and clinical characteristics. Subjects heterozygous for the CCR5 Δ32 deletion who harbored exclusively R5 HIV-1 displayed the most favorable clinical profile; of the 4 groups, these subjects had the lowest pVLs and the highest CD4 cell counts at baseline (table 3). In contrast, subjects with R5/X4 HIV-1, regardless ofCCR5 genotype had the poorest clinical profile; these subjects had the highest pVLs and the lowest CD4 cell counts and were more likely to have an AIDS-defining illness before therapy initiation than were subjects harboring only R5 HIV-1 (table 3)

Table 3
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Table 3

Patient characteristics at baseline, stratified by HIV-1 coreceptor use and human CCR5 Δ32 genotype

In addition, we wished to investigate whether R5/X4 HIV-1 variants from individuals with the CCR5 wt/wt or CCR5 wt/Δ32 genotype might differ in their predominant HIV-1 V3 amino acid sequence. Although, as mentioned previously, R5/X4 HIV-1 was significantly associated with the 11/25 genotype [25] (P<.0001) (table 3), we observed no significant difference in the ability of the 11/25 genotype to predict HIV-1 coreceptor use in subjects with either the CCR5 wt/wt or the CCR5 wt/Δ32 genotype (sensitivity, 30.1% vs. 39.4%, respectively; P=.3 [data not shown])

Predictors of R5/X4 HIV-1 in an antiretroviral-naive pop ulation Univariate and multivariate logistic regression were used to identify significant baseline predictors of R5/X4 HIV-1 and to calculate univariate and multivariate ORs associated with these parameters (table 4). In multivariate analyses, the strongest predictors of R5/X4 HIV-1 were low CD4 cell count (OR, 1.53 per 100-cell/mm3 decrement; P<.0001) and the HIV-1 V3 11/25 genotype (OR, 9.11; P<.0001). Additional predictors of R5/X4 HIV-1 were high baseline pVL (OR, 1.46 per log10 increment; P=.040) and the heterozygous CCR5 wt/Δ32 genotype (OR, 2.48; P=.0005) (table 4)

Table 4
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Table 4

Univariate and multivariate predictors of the presence of CXCR4-using HIV-1 variants at baseline

Association of baseline R5/X4 HIV-1 with mortality and other clinical outcomes In univariate analyses, the presence of R5/X4 HIV-1 at baseline was significantly associated with decreased survival after initiation of therapy (univariate P=.05) (figure 1 and table 5). However, after adjusting for baseline factors, including CD4 cell count, age, and pVL, this association was no longer significant (multivariate P=.45) (table 5)

Table 5
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Table 5

Influence of baseline risk factors on time to nonaccidental death, time to CD4 cell count decline to below baseline, and time to plasma viral load (pVL) rebound to >500 copies/mL (after initial suppression to <500 copies/mL)

In univariate analyses, we observed no significant associations between baseline HIV-1 coreceptor use and either CD4 cell response after initiation of therapy (P=.074) (figure 1B and table 5) or the time to achieve suppression of pVL to <500 copies/mL (HR, 1.00; P=.98) (data not shown). In univariate analyses, subjects harboring R5/X4 HIV-1 appeared to be less likely to experience pVL rebound (HR, 0.72; P=.012) after initial suppression (figure 1C and table 5). However, in multivariate analyses adjusting for baseline parameters, HIV-1 coreceptor use was not significantly associated with either virologic or immunologic response after initiation of HAART (P > .1) (table 5)

Analysis of combined CCR5 genotype and HIV-1 coreceptor phenotype to predict therapy outcome Combining data on both CCR5 genotype and HIV-1 coreceptor phenotype further clarified the association between these parameters and survival after therapy initiation (figure 1D ). In these analyses, the reference group was defined as subjects with the CCR5 wt/wt genotype harboring exclusively R5 HIV-1. In univariate analyses, subjects with the CCR5 wt/Δ32 genotype harboring exclusively R5 HIV-1 were at decreased risk of death (HR, 0.54; P=.09), compared with the reference group. In contrast, subjects with the CCR5 wt/wt genotype harboring R5/X4 HIV-1 were at significantly higher risk of death (HR, 1.54; P=.04), compared with the reference group. Subjects with the CCR5 wt/Δ32 genotype harboring R5/X4 HIV-1 were at comparable risk of mortality (HR, 1.09; P=.8) with respect to the reference group. However, in multivariate analyses adjusting for baseline parameters, including age, pVL, and CD4 cell count, these associations were not significant (P>.1 [data not shown])

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Discussion

We investigated the prevalence and clinical correlates of X4 HIV-1 in a large population of antiretroviral-naive individuals initiating first triple-combination therapy. Consistent with results from other cross-sectional studies [28 –31], there was a strong correlation between the presence of CXCR4-using HIV-1 and clinical parameters, including pVL, diagnosis of AIDS-defining illness, and, most strikingly, CD4 cell count. In the present study, CD4 cell counts in subjects harboring X4 variants were, on average, 3 times lower than those in subjects harboring exclusively R5 variants

Genotypic (sequence-based) and phenotypic HIV-1 coreceptor use assays as predictors of therapy response We previously undertook a study of the same cohort, in which we identified the HIV-1 V3 sequence as a significant predictor of survival and CD4 cell response after initiation of antiretroviral therapy [25]. As expected, we observed a significant correlation between positively charged amino acids at key residues of the HIV-1 V3 loop (the 11/25 genotype) and the presence of X4 HIV-1 at baseline [25, 26]. In the present study, the HIV-1 V3 11/25 genotype predicted the presence of CXCR4-using virus with a specificity of 93% and a sensitivity of 33%. These values appear to be considerably lower than those in other studies employing HIV-1 V3 sequence–based interpretation methods [32, 33]; however, this difference may be explained by the fact that our HIV-1 V3 genotypes were obtained using bulk PCR and by sequencing of nucleic material isolated directly from clinical isolates rather than by analysis of cloned PCR products. Since population-based sequencing methods detect only the predominant circulating species, the prevalence of X4 variants may be underestimated if they are present as minority variants. HIV-1 genotype-phenotype correlations will be examined in detail in a future study

However, somewhat in contrast to the previous study linking baseline HIV-1 V3 sequence to therapy outcome [25], the present study suggests that HIV-1 coreceptor use, although strongly associated with baseline clinical parameters, is not independently associated with response to treatment. HIV-1 coreceptor use at baseline was not a predictor of therapy response and did not remain an independent predictor of survival after associations with baseline clinical parameters, including CD4 cell count and pVL, were accounted for

Association between CCR5 Δ32 genotype and HIV-1 co recep tor use One hypothetical but potentially important consequence of the administration of CCR5 antagonists is the selection of CXCR4-using HIV-1 variants [34]. The naturally occurring CCR5 Δ32 deletion, which is associated with improved prognosis and slower HIV-1 disease progression [35, 36], may provide useful insights into this issue. Individuals with the CCR5 wt/Δ32 genotype have only 1 functional CCR5 allele and express CCR5 at much reduced levels [37]; therefore, if reduced cell-surface CCR5 availability indeed selects for CXCR4-using variants, one would expect to observe an increased prevalence of X4 HIV-1 in these individuals [38]. Indeed, our data indicate that, after other baseline parameters are accounted for, individuals with the CCR5 wt/Δ32 genotype are nearly twice as likely to harbor R5/X4 HIV-1 than are CCR5 wt/wt individuals, although other studies have reported no correlation [39]. Although our results suggest that limited cell-surface CCR5 may lead to selective pressure favoring CXCR4-using variants, one must be cautious in drawing conclusions from cross-sectional data. In addition, we must acknowledge the potential bias resulting from the possibility that individuals with the CCR5 wt/Δ32 genotype harboring CXCR4-using variants may be overrepresented in our cohort, as a result of poor survival of X4 HIV-1 carriers with the CCR5 wt/wt genotype. Whether this observation may be relevant to the administration of CCR5 coreceptor antagonists remains to be determined

When previous data linking the CCR5 Δ32 deletion with slower HIV-1 disease progression [35, 36] and the HIV-1 X4 phenotype with faster disease progression [13 –16] are taken into consideration, the observation that individuals with the CCR5 Δ32 genotype are more likely to harbor X4 HIV-1 appears contradictory. However, an analysis of the combined CCR5 genotype and HIV-1 coreceptor phenotype data indicate that the association between CCR5 wt/Δ32 genotype and both improved baseline clinical profile and survival after initiation of therapy is observed only when the predominant circulating virus at baseline is exclusively R5 (table 3). The protective effects of the CCR5 Δ32 deletion appear to be largely lost when X4 variants are present at baseline, which is consistent with results of previous studies [39, 40]. However, it is interesting to note that individuals with a CCR5 wt/Δ32 genotype who harbor R5/X4 variants have a higher baseline viral load than do individuals with a CCR5 wt/wt genotype who harbor R5/X4 variants (table 3), but they have slightly better survival after initiation of therapy (figure 1D ). A potential explanation is that the CCR5 wt/Δ32 genotype may still confer a slight survival advantage in the presence of X4-containing variants; however, we must caution that the CCR5 wt/Δ32 R5/X4 group is relatively small and, again, the potential biases resulting from the use of cross-sectional data and potential underrepresentation of X4 carriers with a CCR5 wt/wt genotype in this cohort must be acknowledged

Limitations of the present study include the fact that associations between HIV-1 coreceptor use and clinical parameters are based on cross-sectional data from a population of antiretroviral-naive individuals initiating their first antiretroviral therapy. Since the contemporary guidelines for when to initiate therapy are predominantly based on CD4 cell count and pVL thresholds and the presence of AIDS-defining illness, our study population may not be representative of the HIV-1–infected, antiretroviral-naive population in general. In addition, because of the cross-sectional nature of this study, we are unable to comment on the incidence of X4 variants, the length of time these variants have been present, or the evolution of HIV-1 coreceptor use over the natural history of infection. Similarly, since seroconversion dates are not known and historical plasma samples are not generally available, we also are unable to investigate what proportion of our study group may have acquired X4 variants at transmission. Finally, because population-based genotyping and phenotyping approaches were utilized, we are unable to distinguish whether subjects with R5/X4 HIV-1 harbor dual-tropic variants, a mixture of R5 and X4 variants, or both. Despite these limitations, our study is one of the first to characterize the epidemiology and clinical predictors of HIV-1 coreceptor use in a large antiretroviral-naive population and present longitudinal clinical outcome data after initiation of therapy. In addition, it is one of the largest studies evaluating associations between HIV-1 V3 genotype, coreceptor phenotype, human CCR5 Δ32 genotype, and other clinical parameters. Strong associations between R5/X4 HIV-1 and clinical markers of HIV-1 disease progression, including higher pVL and significantly lower CD4 cell counts, confirm the well-characterized link between X4 HIV-1 and poorer prognosis [13 –16], although the direction of causation remains unclear. Despite the association of X4 HIV-1 with poorer pretherapy prognosis, however, the presence of CXCR4-using HIV-1 at baseline did not remain an independent predictor of survival or clinical response to HAART after adjustment for baseline parameters, including CD4 cell count and pVL

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Footnotes

  • ↵Presented in part: 12th Conference on Retroviruses and Opportunistic Infections, Boston, 22–25 February 2005 (abstract 361)

    Financial support: Canadian Institutes for Health Research (Rx&D research grant; doctoral research award to Z.L.B.); Pfizer, Inc.; Michael Smith Foundation for Health Research (doctoral research award to Z.L.B.; Senior Scholar Award to R.S.H.)

    Potential conflicts of interest: J.G. and H.B.M. are employed by Pfizer, Inc

  • Received November 24, 2004.
  • Accepted March 3, 2005.
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  1. J Infect Dis. (2005) 192 (3): 466-474. doi: 10.1086/431519
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