Research ArticleHIV

Integrin α4β7 expression on peripheral blood CD4+ T cells predicts HIV acquisition and disease progression outcomes

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Science Translational Medicine  24 Jan 2018:
Vol. 10, Issue 425, eaam6354
DOI: 10.1126/scitranslmed.aam6354

Indicative integrins in HIV

The gut is thought to be a major viral reservoir in HIV infection, and studies in nonhuman primates suggest that targeting the α4β7 integrin on T cells may be a viable therapy. Sivro et al. now extend these findings to humans by examining HIV acquisition in multiple African cohorts. Higher frequencies of α4β7+ circulating CD4+ T cells before infection were associated with increased HIV acquisition, viral load at set point, and more rapid CD4+ T cell decline. These exciting data confirm that integrin targeting could help reduce the spread of HIV.

Abstract

The gastrointestinal (GI) mucosa is central to HIV pathogenesis, and the integrin α4β7 promotes the homing of immune cells to this site, including those that serve as viral targets. Data from simian immunodeficiency virus (SIV) animal models suggest that α4β7 blockade provides prophylactic and therapeutic benefits. We show that pre-HIV infection frequencies of α4β7+ peripheral blood CD4+ T cells, independent of other T cell phenotypes and genital inflammation, were associated with increased rates of HIV acquisition in South African women. A similar acquisition effect was observed in a Kenyan cohort and in nonhuman primates (NHPs) after intravaginal SIV challenge. This association was stronger when infection was caused by HIV strains containing V2 envelope motifs with a preference for α4β7 binding. In addition, pre-HIV α4β7+ CD4+ T cells predicted a higher set-point viral load and a greater than twofold increased rate of CD4+ T cell decline. These results were confirmed in SIV-infected NHPs. Increased frequencies of pre-HIV α4β7+ CD4+ T cells were also associated with higher postinfection expression of lipopolysaccharide binding protein, a microbial translocation marker, suggestive of more extensive gut damage. CD4+ T cells expressing α4β7 were rapidly depleted very early in HIV infection, particularly from the GI mucosa, and were not restored by early antiretroviral therapy. This study provides a link between α4β7 expression and HIV clinical outcomes in humans, in line with observations made in NHPs. Given the availability of a clinically approved anti-α4β7 monoclonal antibody for treatment of inflammatory bowel disease, these data support further evaluation of targeting α4β7 integrin as a clinical intervention during HIV infection.

INTRODUCTION

Several lines of evidence suggest that the gastrointestinal (GI) mucosa and the associated lymphoid tissue play a critical role in HIV pathogenesis. Infections by HIV and simian immunodeficiency virus (SIV) rapidly deplete CD4+ T cells from this site during the first weeks of infection (13), and the resulting extensive damage to the homeostasis of gut tissue persists into chronic HIV infection. One consequence of the extensive gut damage is the translocation of gut-resident bacterial products into the blood, which has been proposed to be a major source of chronic immune activation that drives HIV pathogenesis (4).

The homing of immune cells to the inductive and effector sites of the large and small intestine is facilitated by the expression of the integrin α4β7 on these cells and its preferred ligand MAdCAM-1, which is constitutively expressed on the high endothelial venules of all GI tissues (5). Several studies suggest that α4β7-expressing CD4+ T cells are important in HIV pathogenesis. These include direct binding of α4β7 to some HIV strains (69), not as an HIV entry co-receptor per se, but rather as a molecule that may facilitate attachment of the virus to its optimal target cells (1012). This role for α4β7 in facilitating localization and attachment of virus to cells may be particularly important during HIV transmission, when availability of target cells is a rate-limiting step for the virus. Many laboratories have shown that CD4+ T cells expressing α4β7 are preferentially infected both in vitro and ex vivo (6, 8, 1214), including during acute SIV infection and in experiments using HIV clade C viruses (15), the predominant clade in South Africa. We have previously shown that α4β7 expression on HIV target cells in the female reproductive tract (FRT) was associated with other markers of optimal HIV target cells, including CCR5 expression (16).

The in vivo implications of modulating α4β7 have been highlighted by studies that have used a primatized anti-α4β7 monoclonal antibody (mAb), with heterodimer specificity in nonhuman primates (NHPs). When administered just before and during acute intravenous SIVmac239 infection, anti-α4β7 mAb mediated moderate reductions in plasma viral load (VL) but substantial reductions in gut proviral DNA (17). More striking results were obtained when anti-α4β7 mAb was administered before low-dose repeated vaginal challenge with SIVmac251; a significant delay in SIV acquisition was observed (18). Animals that eventually acquired SIV showed markedly reduced damage to gut-associated lymphoid tissue (GALT), in addition to other lymphoid and mucosal tissues. When given in combination with antiretroviral therapy (ART), anti-α4β7 promoted potent therapeutic effects, leading to posttreatment virological control in eight of eight treated animals compared to zero of seven controls (19). These findings suggest that α4β7-expressing cells play a central role in SIV transmission and pathogenesis.

One important gap in the literature is the role of α4β7 at the time of HIV exposure in humans. Here, we report evidence that frequencies of α4β7-expressing CD4+ T cells predict both increased risk of HIV acquisition and more rapid disease progression in a cohort of high-risk women from KwaZulu-Natal, South Africa. Data from other cohorts and NHPs further support that α4β7-expressing CD4+ T cells are important HIV targets. With a number of anti-α4β7 blockers in various stages of clinical development, these findings inform the potential translation of these drugs in the treatment of HIV disease.

RESULTS

Study participants

We compared α4β7 integrin expression on CD4+ T cells in blood samples from individuals who later acquired HIV to controls that remained HIV-uninfected for the duration of the CAPRISA 004 study. Cases were sampled at the last available pre-HIV infection visit, with a sampling median of 110 days [interquartile range (IQR), 65 to 182] before HIV infection. Controls (n = 106) were matched to cases (n = 59) at a 2:1 ratio based on study arm, age (5-year window), and month of enrollment. No major differences between cases and controls were observed for a number of demographic, clinical, and behavioral variables (Table 1). Additional analyses were conducted in study cohorts from Kenya, Uganda and the RV254/SEARCH 010 cohort in Thailand (tables S1 to S3). Further data from SIV-challenged NHPs were included to determine consistency between primate species.

Table 1 Characteristics of the CAPRISA 004 study population.

IQR, interquartile range.

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Pre-HIV infection frequencies of β7Hi CD4+ T cells and HIV acquisition

Previous studies have demonstrated that β7Hi cells in the blood are >99% α4β7+ (6, 20); therefore, β7Hi CD45RA gating was used to quantify α4β7 expression on CD4+ T cells. We identified three populations of CD4+ T cells based on the relative density of the integrin β7 and CD45RA expression that were consistently measured across the study population: β7Hi CD45RA, β7Int CD45RA+, and β7Neg CD45RA (Fig. 1A). Because it is difficult to sample cases immediately before HIV infection, we investigated the stability of β7Hi frequencies in blood samples over multiple HIV-uninfected visits in a subset of participants (range, two to five visits; Fig. 1B). The median coefficient of variation (CV) was 15% (IQR, 11 to 36), indicating relatively stable expression in most individuals before HIV infection. We then determined whether any association between HIV infection and higher frequencies of β7Hi CD4+ T cells might be explained by sampling carried out closer to the estimated time of HIV infection (Fig. 1C). Our analysis indicates that this was not the case; the frequencies of β7Hi CD4+ T cells were consistent among cases and controls regardless of sample timing, congruent with the stability data presented in Fig. 1B.

Fig. 1 Effect of preinfection β7Hi CD45RACD4+ T cell frequency on HIV acquisition risk in CAPRISA 004 study.

(A) Parent gating strategy for the analysis of frozen PBMCs from the CAPRISA 004 study. The staining profile of PBMCs from a representative HIV-uninfected participant is shown. β7 gating is shown for one representative control and one case sample obtained at an HIV-uninfected time point. (B) Samples from 10 patients (x axis) were assayed from three to five HIV-uninfected visits (colored bars) depending on sample availability. Median coefficient of variation (CV) between HIV-uninfected time points for every individual was calculated. Individual CVs are indicated in boldface and in parentheses in the graph. (C) Sampling time points for the pre-HIV flow cytometry measurements. The number of days before HIV infection that the sample was obtained (x axis) is plotted against β7Hi frequency (y axis). The dashed line represents the median integrin β7Hi expression by CD4+ T cells. (D) Frequency of β7Hi CD45RACD4+ T cells in cases (n = 59) and controls (n = 106). Conditional logistic regression analysis was used to measure the effect of preinfection β7Hi frequency on HIV acquisition. (E) Spearman correlation between α4β7Hi CD4+ T cell frequency between the cervix and blood in the Nairobi/Uganda study (n = 54) (F) Infecting viral V2 motifs and pre-HIV frequencies of β7Hi CD4+ T cells. (G) Pre-HIV frequencies of β7Hi CD4+ T cells in cases infected by viruses with V2 loops containing the P/SDI/V and LDI/V motifs (n = 32). Differences between groups were analyzed using unpaired t test.

In our primary end point analysis, the frequency of β7Hi cells was higher in samples from cases (median, 9.7%; IQR, 8.1 to 12.3%) than controls (median, 8.7%; IQR, 6.5 to 10.7%). In conditional logistic regression analyses, each percent of pre-HIV infection β7Hi CD4+ T cells correlated with 17% increased risk of HIV acquisition [odds ratio (OR), 1.17; 95% confidence interval (CI), 1.05 to 1.32; P = 0.007; Fig. 1D]. In contrast, no significant associations were observed for either β7Int or β7Neg populations and HIV acquisition (P = 0.242 and 0.882, respectively; fig. S1).

We next carried out multivariable modeling to adjust for variables that may confound the HIV acquisition analysis. Integrin β7Hi cell frequency remained associated with HIV acquisition with a similar effect estimate after adjusting for study site, herpes simplex virus type-2 (HSV-2) serostatus, abnormal vaginal discharge, number of sexual partners and sex acts per month, condom, and depomedroxyprogesterone acetate (DMPA) usage [adjusted OR (aOR), 1.16; 95% CI, 1.03 to 1.32; P = 0.016; Table 2]. We also adjusted the analysis for genital inflammation [defined as ≥5 of 9 proinflammatory cytokines in the upper quartile (21)] and found that frequencies of β7Hi cells remained a predictor of HIV outcome in a model that included all of the other covariates listed above (aOR, 1.15; 95% CI, 1.02 to 1.30; P = 0.028). In addition, frequencies of β7Hi cells remained a predictor of HIV outcome in a model that included both CD4+ T cell activation (aOR, 1.18; 95% CI, 1.05 to 1.33; P = 0.005) and CD8+ T cell activation (aOR, 1.18; 95% CI, 1.05 to 1.32; P = 0.007) defined by HLA-DR and CD38 coexpression. We carried out further phenotypic profiling to compare abundance of CCR5, Ki67, CD38, and HLA-DR expression between the three main β7 subsets (fig. S2). β7Hi cells were comparable to at least one of the other β7-associated subsets with respect to phenotypic markers that have been associated with HIV pathogenesis, further indicating that the observed effect is specific to β7Hi expression.

Table 2 Multivariable analysis of HIV acquisition and integrin β7Hi CD4+ T cells using conditional logistic regression.
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The HIV acquisition results were examined in an additional 41 participants (11 cases and 30 controls) from an independent cohort of female sex workers (FSW) from Nairobi (table S3), with a very similar OR for HIV acquisition risk observed as in CAPRISA 004 (OR, 1.19; 95% CI, 0.94 to 1.52; P = 0.148; table S4). Combining the data from the two cohorts (n = 206), we found that each percent increase in β7Hi expression correlated with an 18% increase in HIV risk (OR, 1.18; 95% CI, 1.06 to 1.31; P = 0.002). These data demonstrate that α4β7 is a consistent predictor of HIV acquisition risk in two independent human cohorts.

We further analyzed preinfection α4β7 expression on blood CD4+ T cells as a predictor of SIV acquisition in NHPs exposed to weekly intravaginal challenges with SIVmac251. These animals were rhesus macaques (RMs) that were in the control arm [irrelevant immunoglobulin G (IgG)] of a published study (18). After adjusting for age, parity, and menses, RMs with higher α4β7 frequency acquired SIV more rapidly than RMs with lower α4β7 frequencies, although this did not reach statistical significance [adjusted HR (aHR), 1.20/% α4β7; 95% CI, 0.99 to 1.44; P = 0.057; fig. S3]. These results are congruent with the previous NHP observations (14, 22) and our human cohort data, suggesting that α4β7 expression on CD4+ T cells is associated with both HIV and SIV infection risk.

Expression of α4β7 integrin by CD4+ T cells in corresponding blood and cervical samples

We next explored whether the frequency of α4β7+ CD4+ T cells in the blood reflected frequencies of these cells in the FRT, the main site of HIV exposure during heterosexual transmission. Although cervical specimens were not available in CAPRISA 004, we evaluated whether α4+β7Hi cells in the blood correlated with α4+β7Hi cells from endocervical cytobrushes in women from Uganda and Kenya (Fig. 1E). Positive correlations were observed consistently between cohorts (combined r = 0.65; P < 0.0001; n = 57). These data suggest that assessing systemic β7Hi cells is likely reflective of α4+β7Hi abundance in the FRT.

Pre-HIV infection frequencies of β7Hi CD4+ T cells and early HIV env sequences

Several reports have suggested that α4β7 can bind to the gp120 second variable loop (V2) of some strains of HIV envelope (Env) directly (7, 9, 23, 24). Specifically, the P/SDI/V V2 motif has been associated with increased α4β7-dependent in vitro replication and is overrepresented in the South African epidemic, particularly in KwaZulu-Natal (7, 15). With these observations in mind, we hypothesized that the frequency of β7Hi cells before HIV infection would correlate with the V2 sequences of early-transmitting viruses encoding P/SDI/V motif. Sequences of acute/early HIV Envs were available for 32 CAPRISA 004 participants at a median of 5 weeks after HIV infection (IQR, 3 to 7). Participants infected by viruses with V2 loops containing the P/SDI/V motif had a higher frequency of pre-HIV β7Hi cells than those infected by viruses with LDI/V motifs (median, 11.5; IQR, 8.9 to 13.8; versus median, 9.1; IQR, 6.0 to 10.9; P = 0.0366; Fig. 1, F and G). These data suggest that the risk of HIV acquisition mediated by α4β7 might be particularly pronounced when exposure involves viruses containing certain V2 motifs associated with enhanced α4β7 binding.

Pre-HIV infection frequencies of β7Hi CD4+ T cells and HIV disease progression

To determine whether pre-HIV infection frequencies of β7Hi CD4+ T cells predicted the rate of HIV disease progression, we correlated the frequency of these cells with both peak and set-point VL, the rate of CD4+ T cell decline before ART initiation, and the median CD4/CD8 ratio after HIV infection (Fig. 2). A correlation was observed between β7Hi cell frequency and set-point VL (average of >180 day measurements; r = 0.345; P = 0.016; Fig. 2A) and a trend with peak VL (<180 days after HIV; r = 0.232, P = 0.112; Fig. 2B). In contrast, no correlations were observed for β7Int or β7Neg cells (fig. S4, A and B).

Fig. 2 Effect of preinfection β7Hi CD45RACD4+ T cell frequency on disease progression in patients that became infected in CAPRISA 004/002 study.

(A) Correlation between preinfection β7Hi frequency and peak viral load (VL) (n = 49). (B) Correlation between preinfection β7Hi frequency and set-point VL (n = 49). (C) Frequency of preinfection β7Hi cells as a predictor of CD4+ T cell decline of <500 cells/μl (n = 48), analyzed using Cox regression models. (D) Preinfection β7Hi cells as a predictor of CD4+ T cell decline of <500 cells/μl in a multivariable Cox regression model correcting for age, study site, study arm, set-point VL, depomedroxyprogesterone acetate (DMPA) use, and HSV-2 status at baseline. (E) Correlation between preinfection β7Hi frequency and mean CD4/CD8 ratio <180 days after infection (n = 48). (F) Correlation between preinfection β7Hi frequency and mean CD4/CD8 ratio >180 days after infection (n = 48). (G) Median postinfection plasma expression of lipopolysaccharide binding protein (LBP) expression in cases with preinfection β7Hi CD4+ T cell expression above (n = 22) and below (n = 22) the median. (H) Longitudinal plasma LBP expression at 6-month intervals in CAPRISA 002 cases. Linear mixed models were used to compare LBP expression over time. Spearman correlation was used to analyze associations between the two variables.

The frequency of β7Hi cells was a strong predictor of CD4+ T cell decline below 500 cells/μl; individuals with β7Hi cells above the median of β7Hi expression progressed to CD4+ T cell count of <500 at more than twice the rate of those below the β7Hi median (HR, 2.38; 95% CI, 1.25 to 4.51; P = 0.008; Fig. 2C). At day 500, about 80% of those above the β7Hi median had progressed, compared to about 50% of those below the β7Hi median. In multivariable Cox regression models (Table 3), inclusion of plasma VL as a covariate had an impact on the strength of association, suggesting that the β7Hi-associated rate of disease progression might be mediated, in part, by higher levels of HIV replication. However, in the full model, including VL and other important covariates (age, study site, study arm, DMPA use, and HSV-2 status at baseline), pre-HIV frequency of β7Hi cells remained a significant predictor of the rate of CD4+ T cell decline (aHR, 2.14; 95% CI, 1.04 to 4.39; P = 0.039; Fig. 2D).

Table 3 Multivariable analysis of CD4+ T cell decline and integrin β7Hi CD4+ T cells using Cox regression.
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Furthermore, we observed an inverse association between pre-HIV β7Hi cells and post-HIV CD4/CD8 ratio, another marker of disease progression (r = −0.322 and P = 0.026 for measurements <180 days after HIV; r = −0.347 and P = 0.016 for measurements >180 days after HIV; Fig. 2, E and F) (25). Again, neither β7Int nor β7Neg cell frequencies were associated with CD4+ T cell decline below 500 cells/μl or CD4/CD8 ratio (fig. S4, C to E). We did not find any associations between activation markers expressed on bulk preinfection CD4+ T cells and disease progression (fig. S5 and table S5).

To establish a link between human and NHP data, we characterized α4β7+ CD4+ T cell frequencies in 14 NHPs before intravenous injection with SIVmac239. Nine animals had low frequency (<30%), whereas the remaining five animals had higher frequency (>30%) of α4β7+ on CD4+ T cells; these patterns of expression were similar in both the blood and the gut tissue. RMs with higher α4β7 expression experienced higher set-point VL than animals with lower α4β7 expression (median from week 3 to 16, 331,680 versus 82,230 copies/ml), which was statistically significant in a linear mixed model analysis (P = 0.033; fig. S6A). As observed in humans, RMs with higher α4β7 expression had a faster rate of CD4+ T cell decline (P < 0.001; fig. S6B), demonstrating consistency between different primate species.

We hypothesized that the association between β7Hi cells and the rate of HIV disease progression might be mediated by more efficient transit of virus-infected cells into the GALT, leading to more extensive gut damage and its associated pathogenic effects. To test this hypothesis, we measured plasma expression of microbial translocation markers prospectively after acute HIV until ART initiation. We found that expression of lipopolysaccharide binding protein (LBP) was elevated in CAPRISA 004 participants with β7Hi cell frequencies above the median at all visits after HIV infection, whether compared as median values (Fig. 2G) or at 6-month intervals (β, 0.54; 95% CI, 0.06 to 1.03; P = 0.028; Fig. 2H). To determine whether this was simply a reflection of a more rapid progression, we used linear mixed models adjusting for VL and CD4/CD8 ratio, measured at the same time points as LBP. LBP remained associated with higher β7Hi frequency in the adjusted models (β, 0.59; 95% CI, 0.01 to 1.16; P = 0.045). In addition, we quantified plasma expression of another two commonly used markers, intestinal fatty acid–binding protein (I-FABP) and sCD14. We did not observe a statistically significant difference in I-FABP and sCD14 expression (table S6) in relation to β7Hi frequency.

Depletion of β7Hi CD4+ T cells in the blood and GI mucosa during acute HIV infection

To determine the impact of acute HIV infection on the β7Hi CD4+ T cell population early in HIV infection in both the blood and the GI tract, we compared frequencies of both CCR5+ and β7Hi cells at Fiebig (F) stages I, II, and III in participants enrolled in the RV254 early infection cohort to chronic HIV infected and uninfected participants (Fig. 3) (26). In the blood, β7Hi cells increased transiently in FI, followed by a modest drop in those recruited from FII onward (Fig. 3A). Similar kinetics were observed for blood CCR5 depletion, where frequency of CCR5+ cells remained comparable to HIV-uninfected expression levels in FI and decreased during FII and FIII (Fig. 3B). In contrast in the GI tract, β7Hi depletion was evident in all Fiebig stages, with major depletion occurring from FI (Fig. 3C). This occurred more rapidly than CCR5 depletion, where the major loss of CCR5+ cells was only evident during the transition from FII to FIII (Fig. 3D). These data confirm that α4β7+ CD4+ T cells are depleted very early in HIV infection, particularly in the gut, providing a potential explanation as to why these cells predicted higher rates of HIV acquisition and disease progression in CAPRISA 004 study.

Fig. 3 Depletion and post-ART recovery of β7Hi and CCR5+ CD4+ T cells in peripheral blood and cells isolated from the sigmoid colon during acute infection in RV254.

(A and B) Frequencies of β7Hi (A) and CCR5+ (B) CD4+ T cells in the peripheral blood at different Fiebig (F) stages [HIV-uninfected (HIV; n = 9), FI (n = 8), FII (n = 11), FIII (n = 20), and chronic HIV–infected (CHI; n = 5)]. (C) Frequencies of β7Hi CD4+ T cells in the colon [HIV (n = 9), FI (n = 8), FII (n = 6), FIII (n = 13), and CHI (n = 5)]. (D) Frequencies of CCR5+ CD4+ T cells in the colon [HIV (n = 9), FI (n = 8), FII (n = 10), FIII (n = 18), and CHI (n = 8)]. (E and F) Frequencies of β7Hi (E) and CCR5+ (F) CD4+ T cells in the peripheral blood after antiretroviral therapy (ART) initiation in either FI [purple data points; at baseline (n = 8), 6 months (n = 8), and 24 months (n = 7)] or FIII [black data points; at baseline (n = 18), 6 months (n = 18), and 24 months (n = 14)]. (G) Frequencies of β7Hi CD4+ T cells in the colon after ART initiation in either FI [purple data points; baseline (n = 8), 6 months (n = 5), and 24 months (n = 3)] or FIII [black data points; baseline (n = 13), 6 months (n = 15), and 24 months (n = 9)] (H) CCR5+ CD4+ T cells in the colon after ART initiation in either FI [purple data points; at baseline (n = 8), 6 months (n = 6), and 24 months (n = 4)] or FIII [black data points; at baseline (n = 18), 6 months (n = 17), and 24 months (n = 9)]. The dashed lines represent the median of cells in healthy control participants (green; n = 9) and in CHI patients (red; n = 5). For (A) to (D), Kruskal-Wallis test was used, followed by a Dunn’s multiple comparisons test, to look for differences between HIV group and groups at different Fiebig stages. For (E) to (H), Friedman test was used to test for significant differences within each ART initiation group (FI and FIII). *P < 0.05, **P < 0.01, and ***P < 0.001.

Because ART was initiated upon diagnosis in RV254, we were not able to assess disease progression in this cohort. However, we determined the impact of ART on β7Hi and CCR5+ CD4+ T cell frequencies in both colon biopsies and blood over 2 years after HIV treatment, which was initiated at the time of HIV diagnosis in very early infection (FI or FIII). In participants who initiated ART in either FI or FIII, 2 years of ART failed to restore blood β7Hi CD4+ T cells (Fig. 3E). The frequencies of β7Hi CD4+ T cells in peripheral blood did not increase during treatment. Similarly, ART initiation failed to restore blood CCR5+ CD4+ T cells (Fig. 3F). However, the impact of ART on β7Hi and CCR5+ CD4+ T cells in the colon was strikingly different. The frequency of colonic β7Hi CD4+ T cells in patients who initiated ART in either FI or FIII was already reduced at initial baseline measurement, and these expression levels showed no sign of recovery after 24 months of treatment (Fig. 3G). In contrast, in participants who initiated ART in FI, colonic CCR5+ CD4+ T cells were not depleted, and their frequency at 24 months of therapy was maintained at a level similar to healthy controls. Participants who initiated therapy in FIII showed an initial loss and a gradual, “near” recovery by month 24 (Fig. 3H). These data suggest that β7Hi CD4+ T cell depletion occurs very early during acute HIV infection, especially in the GI tract, compared to blood. It is also clear that ART is unable to restore the frequency of those CD4+ T cells in the GI tract, even when provided at the earliest time point, when gut damage is relatively minimal compared with chronic HIV.

DISCUSSION

The integrin α4β7 plays an important role in promoting immune cell trafficking to the inductive and effector sites of the GI tract, both of which are irreversibly damaged during acute HIV infection. The main aim of the present study was to evaluate the role of α4β7 integrin in humans at risk of HIV infection, an important step toward the translation of these promising preclinical studies. In line with our a priori hypotheses, expression of α4β7 on blood memory CD4+ T cells measured before HIV infection in South African women predicted both higher risk of HIV acquisition and a more rapid rate of HIV disease progression.

Although the association of α4β7 expression and HIV acquisition was relatively modest, results were consistent in independent cohorts in two different countries and in NHPs. Higher preinfection α4β7 frequency was previously associated with susceptibility to rectal SIV infection (14, 22). In addition, in a low-dose vaginal challenge, SIV infection was significantly delayed by blocking α4β7 using Act1 (18). Consistencies in ORs for HIV acquisition risk between CAPRISA 004 and the Kenyan FSW cohort demonstrate that α4β7 associates with HIV acquisition risk in women from different geographic locations. Reported findings demonstrate consistency in humans and show that results can be translated between human and NHPs.

Interactions between α4β7 and HIV Env may assist the virus in locating its ideal target cells (27). The findings herein show that higher frequency of α4β7 CD4+ T cells was associated with preferential infection by HIV-1 containing gp120 V2 motifs (P/SDV/I) that have been associated with higher α4β7 binding and are overrepresented in clade C sequences from KwaZulu-Natal, South Africa, the region where the CAPRISA 004 study was conducted (7, 15). The α4β7-binding motif has been implicated as an important epitope for HIV antibody responses, including both broadly neutralizing antibodies (bNAbs) (28, 29) and those that correlated with protection against HIV infection in the RV144 vaccine study (30). The role of preinfection α4β7 expression on HIV pathogenesis likely depends on the nature of the transmitting virus.

The frequency of α4β7 expression had a strong impact on the rate of HIV disease progression, in particular, as measured by the rate of CD4+ T cell decline. As observed with HIV acquisition, the progression effect was highly similar between RMs and humans. In addition, the data from RV254 suggest that α4β7+ CD4+ T cells are targeted very early in the blood and gut. In humans, a high proportion of initial HIV-target cells are likely α4β7+, and the rapid gut depletion of CD4+ T cells may be driven by the preferential depletion of cells expressing α4β7 (even earlier than CCR5). Therefore, in individuals with higher frequency of α4β7+ cells, one may expect increased viral replication and associated destruction of many CD4 compartments, including the GI mucosa, the latter of which has a major effect on disrupting immune homeostasis. Although we were not able to link rapid gut depletion with pre-HIV α4β7 due to lack of pre-HIV samples in RV254 and lack of gut sampling in CAPRISA 004, our finding of raised LBP expression at all stages of untreated HIV infection in individuals with higher α4β7 expression supports this concept, linking α4β7 expression with subsequent microbial translocation and gut damage. Although we did not observe similar associations with I-FABP and sCD14, this could be due to recent reports that have suggested that these markers may not be specific to microbial translocation and are influenced by other causes of GI disease (3133) and monocyte activation (34), respectively.

Initiation of ART, particularly at early stages of HIV infection (35), restores some immune cell populations but rarely to their preinfection frequency and/or function (36). Most of CD4+ T cell depletion occurs in the GALT during primary infection (3, 37), and ART administration at first detection of VL failed to prevent depletion or facilitate reconstitution of gut α4β7+ CD4+ T cells in RV254. The fact that ART alone does not lead to immune restoration, but ART, in combination with anti-α4β7, did so in NHPs (19), suggests that interventions in addition to ART may be needed to achieve functional CD4+ T cell restoration.

One of the limitations of our study is the lack of paired cervical and blood sampling, which is not available in CAPRISA 004. Nevertheless, data from two independent East African cohorts demonstrate that the frequency of α4β7+ cells correlated strongly between blood and cervical CD4+ T cells, suggesting that the correlation between increased frequencies of blood α4β7+ CD4+ T cells and HIV acquisition may be explained, at least in part, by a higher concentration of target cells at the site of HIV exposure (38). Although the results presented here are specific to heterosexual transmission of HIV, previous NHP studies support a similar role for α4β7 during other modes of exposure.

This study defines the importance of α4β7 in HIV acquisition and disease progression in a prospective natural history study of high-risk women. One model to explain these data is that preferential infection of α4β7+ CD4+ T cells at the time of HIV exposure leads to more pronounced local infection of these cells, which then migrate rapidly to the gut mucosal and lymphoid tissue, where rapid viral replication contributes to establishment of the latent HIV reservoir. Recent work by our group has suggested that the administration of a primatized analog of the anti-α4β7 mAb in SIV-infected macaques receiving early ART leads to sustained spontaneous control of SIV and repopulation of GI tract with CD4+ T cells in the absence of further treatment (19). Combined with the findings of the current study, these data and those from NHPs suggest that α4β7 integrin might be a useful target for HIV prevention and/or treatment in humans. Further evaluation of this concept is clinically feasible, given that a humanized version of the Act1 mAb clone (called vedolizumab) has been proven safe and effective and is U.S. Food and Drug Administration–approved for the treatment of adults with moderate to severe ulcerative colitis and Crohn’s disease (39, 40).

MATERIALS AND METHODS

Study design

We carried out a nested retrospective case-control analysis to correlate the expression of integrin β7Hi on CD4+ T cells to rates of HIV acquisition. Cases then followed prospectively to compare disease progression outcomes stratified by β7Hi CD4+ T cells at pre-HIV infection time points. The main outcomes for disease progression were set point, and peak HIV VLs measured after infection before the initiation of ART. Survival analyses were used to compare the time to CD4+ T cell decline below 500 cells/μl. In the RV254 study, different acute HIV stages were compared cross-sectionally at diagnosis and followed longitudinally after early ART initiation. All experiments were performed in a blinded fashion. Analogous studies were conducted in NHPs, as described further in Supplementary Materials and Methods. The detailed study cohorts, sample collection, and processing information are provided in Supplementary Materials and Methods. The sample size for each experiment is included in the figures and/or figure legends. Primary data are located in table S7.

Flow cytometry analysis

Peripheral blood mononuclear cells (PBMCs) were thawed, washed to remove the cryopreserving fluid, then rested for 3 hours (RPMI 1640 supplemented with 10% fetal bovine serum) at 37°C and 5% CO2, and stained with a panel of antibodies designed to profile β7 expression on different CD4+ T cell subsets in terms of their memory, activation, and target cell properties. Detailed methods can be found in Supplementary Materials and Methods.

Soluble biomarker analysis

Plasma LBP expression was measured using Human LBP DuoSet ELISA DY870-05 (R&D Systems Inc.). All assays were performed following the manufacturer’s instructions. Samples with values below the lower detection limit were assigned the value half the lower limit of quantification (LLOQ/2).

Viral sequencing

The sequence of transmitted/founder Envs were inferred as the consensus of acute/early sequences obtained from a median of 5 weeks after HIV infection (IQR, 3 to 7.25; range, 2 to 13 weeks). Viral Env sequences were generated by Sanger sequencing of amplicons generated by single genome amplication of viral RNA, performed as previously described (41, 42). Additional methods can be found in Supplementary Materials and Methods.

Statistical analysis

To compare HIV acquisition risk, we carried out conditional logistic regression with strata defined by matching criteria that was used to select cases and controls. The main explanatory variables in all models included three integrin β7–defined subsets, each modeled separately in bivariate and multivariable models adjusting for a number of potential confounding variables. Disease progression rates were evaluated using several readouts, including correlation analyses (Spearman rank correlation) with HIV VL and CD4/CD8 ratio, measured both as peak (highest value in the first 180 days of infection) and set point (average value in measurements made after 180 days of infection until ART initiation). Rates of CD4+ T cell decline were compared in bivariate and multivariable Cox regression models, with the end point defined as any two CD4+ T cell counts below 500/μl before ART initiation. Survival analyses excluded CD4+ T cell counts measured during the first 180 days of follow-up; these were censored to exclude transient CD4 drops during acute HIV infection, as previously described (43). D’Agostino and Pearson omnibus normality test was used for Gaussian distribution of the data. For data that did not follow normal distribution, nonparametric tests, including Kruskal-Wallis test and Spearman correlation, were performed. All statistics are two-tailed. Linear mixed models were used to compare LBP expression prospectively, with β7Hi above and below the median as the primary predictor, and adjustments were made for progression variables, including VL and CD4/CD8 ratio.

SUPPLEMENTARY MATERIALS

www.sciencetranslationalmedicine.org/cgi/content/full/10/425/eaam6354/DC1

Materials and Methods

Fig. S1. Effect of preinfection β7int CD45RA+CD4+ and β7Neg CD45RACD4+ T cell frequency on HIV acquisition.

Fig. S2. Phenotype of β7Hi CD45RACD4+, β7int CD45RA+CD4+, and β7Neg CD45RACD4+ T cells.

Fig. S3. Effect of preinfection α4β7+ CD4+ T cell frequency in the blood on SIV acquisition in NHPs exposed to weekly intravaginal challenges with SIVmac251.

Fig. S4. Effect of preinfection β7int CD45RA+CD4+ and β7Neg CD45RACD4+ T cell frequency on disease progression in patients that became infected in CAPRISA 004/002 study.

Fig. S5. Gating strategy used for the analysis of frozen PBMCs from the CAPRISA 004 study.

Fig. S6. Effect of preinfection α4β7+ CD4+ T cell frequency in the gut and the blood on disease progression in RMs after intravenous injection with SIVmac239.

Table S1. Characteristics of the Ugandan and Kenyan study populations.

Table S2. Cohort characteristics (RV254 study).

Table S3. Cohort characteristics (FSW cohort; Nairobi, Kenya).

Table S4. Analysis of HIV acquisition and integrin β7Hi CD4+ T cells using conditional logistic regression in CAPRISA 004 (n = 165), in FSW cohort from Nairobi (n = 41), and in the combined cohort analysis (n = 206).

Table S5. Correlation of other immunological markers on bulk CD4+ T cells and CD4+ T cell decline of <500 cells/μl in the CAPRISA 004 study.

Table S6. Effect of preinfection integrin β7Hi CD4+ T cell frequency on postinfection plasma I-FABP and sCD14 expression using linear mixed model analysis adjusting for VL and CD4/CD8 ratio.

Table S7. Primary data (provided as an Excel file).

References (4448)

REFERENCES AND NOTES

Acknowledgments: We thank all the study participants and the clinic and laboratory staff that participated in the CAPRISA 004 and 002 studies in Durban South Africa, RV254 study in Thailand, and Nairobi and Uganda studies. We also thank L. Morris and S. Krebs for the critical review of the manuscript. The views expressed are those of the authors and should not be construed to represent the positions of the U.S. Army or the U.S. Department of Defense or other institutions listed. Funding: The CAPRISA 004 part of this project was funded by NIH R21 AI115978-01. The original CAPRISA 004 tenofovir gel trial was funded principally by the U.S. Agency for International Development through FHI360 and CONRAD, with additional support provided by the South African Department of Science and Technology. RV254 is supported by cooperative agreements (W81XWH-07-2-0067 and W81XWH-11-2-0174) between the Henry M. Jackson Foundation for the Advancement of Military Medicine Inc. and the U.S. Department of the Army and by an intramural grant from the Thai Red Cross AIDS Research Center. The ART in RV254 was supported by the Government Pharmaceutical Organization (Thailand), Gilead, Merck, and ViiV Healthcare. The Majengo cohort in Nairobi has been funded by Gates Grand Challenges and the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR). Author contributions: A. Sivro, F.N., C.C., J. Arthos, A.A., and L.R.M. designed the study. A. Sivro, A. Schuetz, D.S., V.J., S.Y., L.J.L., A. Stalker, R.S.M., P.S., A.B., and F.N. performed the experiments. A. Sivro, A. Schuetz, D.S., V.J., A.B., N.Y.-Z., and L.R.M. analyzed the data. A. Sivro and L.R.M. wrote the manuscript. N.G., N.S., A.O.A., J.K., B.S.B., N.K., C.W., R.K., J.-A.S.P., N.P., J. Ananworanich, A.S.F., Q.A.K., S.S.A.K., and L.R.M. supervised the clinical and/or experimental aspects of the study. L.R.M. and A.A. obtained funding for the study. Competing interests: The authors declare that they have no competing interests.
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