Research ArticleHIV

Immune perturbations in HIV-1–infected individuals who make broadly neutralizing antibodies

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Science Immunology  29 Jul 2016:
Vol. 1, Issue 1, pp. aag0851
DOI: 10.1126/sciimmunol.aag0851

Setting the stage for HIV vaccines

Some HIV-infected individuals produce antibodies that can target multiple HIV strains—broadly neutralizing antibodies. Moody et al. now compare HIV-infected individuals who produce these antibodies with those who do not. They find that broadly neutralizing antibody production associates with particular immune traits, including a higher frequency of autoantibodies, fewer regulatory T cells, and more circulating memory T follicular helper cells. Vaccine protocols that can mimic these immune perturbations may therefore promote induction of broadly neutralizing antibodies and lead to a more successful immune response to HIV.

Abstract

Induction of broadly neutralizing antibodies (bnAbs) is a goal of HIV-1 vaccine development. bnAbs occur in some HIV-1–infected individuals and frequently have characteristics of autoantibodies. We have studied cohorts of HIV-1–infected individuals who made bnAbs and compared them with those who did not do so, and determined immune traits associated with the ability to produce bnAbs. HIV-1–infected individuals with bnAbs had a higher frequency of blood autoantibodies, a lower frequency of regulatory CD4+ T cells, a higher frequency of circulating memory T follicular helper CD4+ cells, and a higher T regulatory cell level of programmed cell death–1 expression compared with HIV-1–infected individuals without bnAbs. Thus, induction of HIV-1 bnAbs may require vaccination regimens that transiently mimic immunologic perturbations in HIV-1–infected individuals.

INTRODUCTION

Development of an HIV-1 vaccine is the cornerstone of a comprehensive global HIV-1 preventive strategy (1). A critical component of a successful strategy is design of immunogens to induce broadly neutralizing antibodies (bnAbs) (2, 3). However, to date, no candidate HIV-1 vaccines have induced plasma bnAb activity (46). Only rarely do HIV-1–infected individuals make high levels of bnAbs, but over 2 to 4 years of infection, ~50% of infected individuals develop cross-reactive antibodies that neutralize ~50% of difficult-to-neutralize (tier 2) HIV-1 isolates (711).

Clues to the dearth of vaccine-induced bnAbs come from analysis of the physical characteristics of bnAbs (2, 1214). All bnAbs isolated to date have very high frequencies of somatic mutations, long third heavy-chain complementarity-determining regions, and/or autoreactivity—traits of B cell antigen receptors that are negatively regulated by immune tolerance mechanisms (13, 1526). One hypothesis is that some or all bnAb development may be controlled by one or more immune tolerance mechanisms (2, 12, 13, 16).

About 50% of HIV-1–infected individuals will produce autoantibodies during untreated HIV-1 infection (2733). Here, we have profiled the immune perturbations associated with HIV-1 infection and bnAb induction. We studied a cohort of 239 chronically HIV-1–infected individuals for serum ability to broadly neutralize HIV-1 strains and selected 51 individuals with the highest blood bnAb activity versus 51 matched individuals with low neutralizing activity. We tested for the coincident presence of plasma autoantibodies and for peripheral blood CD4+ T cell subset frequencies in the HIV-1–infected individuals who had made bnAbs, in those who had not made bnAbs, and in HIV-1–seronegative controls (including those with and without autoantibodies). We quantified total CD4+ T cells and assessed the circulating frequency of resting memory T follicular helper (mTfh) cells, a population defined as the PD-1+ CXCR3 subset of CXCR5+ CD4+ T cells (34). We also determined the frequency of CD25+ Foxp3+ regulatory CD4+ T (Treg) cells—a population of cells that have been shown to suppress the development of autoantibody responses [reviewed in (35)]—as well as the proportion of circulating CD4+ T follicular-phenotype cells (i.e., CD4+ CXCR5+ T cells) composed of CD25+ Foxp3+ CD4+ T follicular regulatory (Tfr) cells, the subset of CD4+ Treg cells that mediates control of B cell responses within germinal centers (3642), and measured programmed cell death–1 (PD-1) expression on both Treg and Tfr cells.

RESULTS

Autoantibodies in HIV-1–infected individuals with high versus low HIV-1 neutralizing activity in plasma

Cohort A consisted of 239 HIV-1–infected individuals, of whom 214 (90%) were African (table S1). On the basis of serum neutralization data, we selected 51 individuals who had the highest level of bnAbs and matched them with 51 individuals who did not have bnAbs (Fig. 1A, figs. S1 and S2, and tables S1 to S9). Thirty-three of 51 (65%) HIV-1–infected individuals with bnAb activity had positive plasma reactivity in one or more autoantibody assays (Fig. 1C). In contrast, only 16 of 51 (31%) in the non-bnAb HIV-1–infected control group had plasma autoantibodies (χ2 = 11.4, P = 0.0008; Fig. 1C). Poisson regression results also showed that the bnAb individuals had a higher number of positive autoantibody tests than the non-bnAb HIV-1–infected control group (χ2 = 14.7, P = 0.0001; Fig. 1E). Cohort A was infected primarily with clade C viruses (A.bnAb, 33 of 51, 65%; A.Control, 37 of 51, 73%; P = 0.52, Fisher’s exact test; table S9), but we found that clade of infecting virus had no effect on the presence of either neutralization breadth or autoantibodies (tables S10 to S12).

Fig. 1 Neutralization and autoantibody testing of HIV-1–infected individuals.

HIV-1 neutralization data are shown as GMT for a panel of isolates for cohorts A (A) and B (B). Individuals with the highest (bnAb) and lowest (Control) HIV-1 neutralization for each cohort were tested in autoantibody assays. (C) and (D) compare the frequency of individuals in the bnAb and control groups with any positive result for cohorts A and B, respectively. The number of positive autoantibody results is shown for cohorts A (E) and B (F).

To determine the effect of geographic region of HIV-1 individual origin on autoantibody frequency in bnAb individuals, we studied a second confirmatory group (cohort B; tables S13 to S16) of HIV-1–infected individuals from the United States composed of individuals who produced bnAbs and those who had lower levels of plasma neutralizing antibodies (Fig. 1B). Confirming the data in cohort A, we found that 22 of 24 (92%) HIV-1–infected individuals in cohort B with bnAb activity had at least one positive test, whereas only 12 of 21 (57%) cohort B low-level neutralizing antibody individuals had plasma autoantibodies (χ2 = 7.2, P = 0.007; Fig. 1D). However, because of the lower number of individuals in cohort B, Poisson regression analysis was unable to show a difference in the total number of positive autoantibody tests in cohort B bnAb individuals compared with the non-bnAb controls (χ2 = 1.8, P = 0.2; Fig. 1F). Moreover, the cohort B HIV-1–infected non-bnAb control group was different from the non-bnAb control group of cohort A. The U.S. B.control group had a greater level of neutralizing antibodies than the primarily African A.control group [B.Control total isolate tested geometric mean titer (GMT) = 32.7; A.Control GMT = 12.2; P < 0.0001, t test; tables S4 and S14].

Because HIV-1 infection is associated with polyclonal B cell activation (43), we next asked whether overall levels of antibody production to HIV-1 and non–HIV-1 antigens were similar between the bnAb and control groups of both cohorts. Thus, we assayed for plasma antibody binding to HIV-1 Env gp120 and gp41, as well as to trivalent inactivated influenza vaccine for 2008 (TIV2008). Binding to HIV-1 Env gp120 (P < 0.0001, t test) and gp41 (P < 0.0001, t test) proteins was elevated in the cohort A bnAb group compared with the A.control group (Fig. 2, A and B, and table S17), whereas plasma antibodies to influenza were similar between the A.control group and the bnAb group (P = 0.19, t test; Fig. 2C). In both cohort B bnAb and control groups, antibodies to gp120, gp41, and TIV2008 were not statistically different (P = 0.35, 0.46, and 0.27, respectively, t test; Fig. 2, D to F, and table S17). Thus, the lack of increased antibodies to influenza in these cohorts suggests that the higher frequency of autoantibodies in HIV-1–infected individuals with bnAbs was not due to a general increase in antibody induction.

Fig. 2 Comparison of plasma antibody responses.

When compared with the A.Control group, the A.bnAb group had higher binding to HIV-1 Env gp120 (A) and gp41 (B) but similar binding (C) to TIV2008. Binding was similar between the B.bnAb and B.Control groups for the same three antigens (D to F). NS, not significant. Each symbol represents data from an individual participant; group medians, range, and quartiles are shown.

CD4+ T cell subsets in the A.bnAb group versus the A.control group

CD25+ Foxp3+ CD4+ Treg cells play an important role in the prevention of autoimmunity, and loss or impairment of Treg function leads to autoantibody induction (35, 44, 45). Conversely, increased frequencies of CD4+ T follicular helper (Tfh) cells, which play a crucial role in the germinal center B cell response, are often associated with autoantibody production (4648). Thus, we determined the frequency of CD4+ Tfh and Treg cells in the A.bnAb and A.Control groups from whom peripheral blood mononuclear cell samples were available, and matched HIV-1–seronegative controls. The A.bnAb group had a higher mean viral load than the A.Control group (table S7), although we found that the presence of autoantibodies was independent of viral load (tables S19 and S20). Total CD4+ T cells in both groups of HIV-1–infected individuals were reduced compared with HIV-1–seronegative controls, and they were significantly lower in the A.bnAb group than in the A.Control group (P = 0.0001, t test; Fig. 3A and table S18). Analysis of the circulating frequency of resting memory T follicular helper (mTfh) CD4+ T cells, defined as the PD-1+ CXCR3 subset of CXCR5+ CD4+ T cells (34), revealed that mTfh cells were present at significantly higher frequencies in the A.bnAb group than in the A.Control group or HIV-1–seronegative controls (P < 0.0001 for both, t test; Fig. 3B and table S18). The frequency of CD25+ Foxp3+ CD4+ Treg cells within lymphocytes was also significantly lower in the A.bnAb group than in the A.Control group (P = 0.004, t test; Fig. 3C and table S18), although the frequency of Treg cells within CD4+ T cells did not differ significantly between groups.

Fig. 3 T cell subsets in cohort A individuals with and without bnAbs and matched HIV-1–seronegative controls.

Total CD4+ T cell frequency within lymphocytes was lower in cohort A HIV-1–infected individuals than in HIV-1–seronegative controls and was lowest in the A.bnAb group (A). Resting mTfh cells were elevated in cohort A HIV-1–infected individuals compared with HIV-seronegative controls and were highest in the A.bnAb group (B). CD4+ Treg cell frequency was lowest in the A.bnAb group (C). PD-1 mean fluorescence intensity (MFI) on CD4+ Treg cells was highest in the A.bnAb group (D). The proportion of Tfr cells within circulating CD4+ follicular-phenotype T cells in the A.bnAb group did not differ significantly from that in the A.Control or seronegative groups (E). The Tfr/Tfh ratio, defined asEmbedded Imagein the A.bnAb group did not differ significantly from that in the A.Control or seronegative groups (F). The MFI of PD-1 staining on CD4+ Tfr cells was highest in the A.bnAb group (G). Each symbol represents data from an individual; group medians, range, and quartiles are shown.

The inhibitory receptor PD-1 has been associated with CD4+ and CD8+ T cell activation and/or dysfunction in HIV-1 infection [reviewed in (49)] and with the development of autoimmunity [reviewed in (50)]. Thus, we measured the level of PD-1 on circulating CD25+ Foxp3+ CD4+ Treg cells and found that, in the A.bnAb group, Treg cells expressed significantly higher levels of the inhibitory receptor PD-1 than did Treg cells in A.Control individuals (P < 0.0001, t test) or in HIV-1–seronegative controls (P < 0.0001, t test; Fig. 3D and table S18). The differences in mTfh and Treg frequencies and PD-1 expression on Treg cells in the A.bnAb and A.Control groups were independent of their differing viral loads (tables S21 and S22).

Recent studies have identified a subpopulation of CD25+ Foxp3+ CD4+ Treg cells that shares some of the phenotypic characteristics of CD4+ Tfh cells including expression of Bcl6, CXCR5, PD-1, and ICOS; these CD4+ Tfr cells can home into germinal centers and regulate the germinal center response by limiting Tfh numbers and function and via direct effects on B cells (35, 3742, 51, 52). Germinal center B cell responses are thought to be determined by the relative proportions of Tfr and Tfh cells, rather than the number of Tfr cells (41). Memory Tfr populations circulate in peripheral blood (41). We therefore measured the proportion of CD25+ Foxp3+ regulatory cells in the circulating CD4+ T follicular-phenotype cell population, defined as CXCR5+ CD4+ T cells. In both cohort A groups of HIV-1–infected individuals, the proportion of Tfr cells within the circulating CXCR5+ CD4+ T cell population (Fig. 3E and table S18) and the Tfr/Tfh ratio (i.e., ratio of CD25+ Foxp3+ to non–CD25+ Foxp3+ cells in the circulating CXCR5+ CD4+ T cell population) (Fig. 3F and table S18) did not differ significantly in the A.bnAb and the A.Control groups, although the level of PD-1 expression on Tfr cells was significantly higher in the former group (P = 0.004, t test; Fig. 3G and table S18). Given the current lack of consensus about the phenotypic definition of circulating CD4+ Tfr cells in humans (41, 5355), we also considered two other definitions for this population (CD25+ Foxp3+ cells within CXCR3 PD-1+ CXCR5+ CD4+ T cells and CD25+ Foxp3+ cells within ICOS+ PD-1+ CXCR5+ CD4+ T cells). Similar results were obtained regardless of the definition used, with no significant difference being observed in circulating Tfr frequencies or the Tfr/Tfh ratio in the A.bnAb and the A.Control groups, and PD-1 on Tfr being significantly higher or showing a trend toward higher expression in the A.bnAb group (fig. S6 and table S23). When we divided the cohort A individuals into groups on the basis of generation of autoantibodies rather than bnAbs, we found that autoantibody-positive individuals exhibited similar alterations in T cell subsets, including expression of higher levels of PD-1 on CD4+ Treg and Tfr populations, to those seen between the A.bnAb and A.Control groups, although this difference was less pronounced and did not reach statistical significance.

The higher levels of PD-1 expression on CD4+ Treg and Tfr cells in the A.bnAb group raised the hypothesis that Treg cell populations in the A.bnAb group are more activated and may be more dysfunctional than those in the A.Control group. We thus compared the expression of HLA-DR (another marker associated with CD4+ T cell activation) and CTLA-4 and LAG-3 [both of which are markers of CD4+ T cell exhaustion (56) but are also involved in CD4+ Treg cell effector function (57, 58)] on CD4+ Treg cells in the cohort A bnAb and non-bnAb groups and matched HIV-1–seronegative controls. The percentage of CD4+ Treg cells expressing HLA-DR was significantly higher in the A.bnAb group than in the A.Control group (P = 0.0003, t test; Fig. 4A and table S24), and the level of PD-1 expression on Treg cells was also significantly higher in the former group. Similar observations were also made for CTLA-4 (P = 0.01, t test; Fig. 4B and table S24). Although there was no difference between groups in the percentage of CD4+ Treg cells expressing LAG-3 (Fig. 4C and table S24), the level of LAG-3 expression on CD4+ Treg cells was again significantly higher in the A.bnAb group than in the A.Control group. HLA-DR, CTLA-4, and LAG-3 were all expressed on a significantly higher proportion of PD-1high CD4+ Treg cells than PD-1low or PD-1negative CD4+ Treg cells in both HIV-1–infected (data for the A.bnAb group are shown in Fig. 4, D to F, and table S25) and HIV-1–seronegative control individuals (Fig. 4, G to I, and table S26). To explore the functional capacity of the PD-1high subset of CD4+ Treg cells, we sorted CD25high CD127low CD4+ Treg cells from HIV-1–seronegative donors into PD-1high, PD-1low, and PD-1negative subpopulations, and we assessed their ability to suppress the proliferation of conventional (CD25low CD127high) CD4+ T cells. Whereas PD-1low and PD-1negative CD4+ Treg subpopulations mediated significant suppression of conventional CD4+ T (Tconv) cell proliferation (P = 0.01, sign test; Fig. 4J and table S27), this was not the case for PD-1high CD4+ Treg cells—the PD-1high CD4+ Treg subpopulation from some donors had a highly impaired suppressive capacity (Fig. 4J). Together, these results suggested that high PD-1 expression on Treg cells, as observed in the A.bnAb group, is indicative of activation and development of an impaired functional capacity.

Fig. 4 Phenotypic and functional analysis of CD4+ Treg cells.

CD4+ Treg cells expressing HLA-DR were higher in the A.bnAb group than in the A.Control or seronegative groups (A). Total CD4+ Treg cells expressing CTLA-4 were also higher in the A.bnAb group than in the A.Control or seronegative groups (B). No difference between groups was found for CD4+ Treg cells expressing LAG-3 (C). In the A.bnAb group, the PD-1high subset of CD4+ Treg cells expressed higher levels of HLA-DR (D), CTLA-4 (E), and LAG-3 (F) than did the PD-1low or PD-1negative subsets of CD4+ Treg cells. The results were similar for the HIV-1–seronegative control group (G to I). In (A) to (I), symbols represent individuals; group medians, range, and quartiles are shown. In experiments performed with samples from healthy HIV-1–seronegative UK donors, PD-1negative and PD-1low CD4+ Treg cells suppressed the proliferation of Tconv cells compared with that observed in the presence of other Tconv cells, whereas PD-1high CD4+ Treg cells did not do so (J). In (J), the symbols represent individuals; group medians, range, and quartiles are shown; and the horizontal dashed red line indicates the level of proliferation of Tconv cells in the presence of other Tconv cells to which other values were normalized.

The higher frequency of blood autoantibodies, higher frequency of circulating CD4+ mTfh cells, lower frequency of CD4+ Treg cells, and higher levels of PD-1 expression on CD4+ Treg and Tfr cells observed in the A.bnAb group compared with the A.Control group may have been present before HIV-1 infection and/or may have developed or been accentuated during the course of infection. The cohort A individuals had not been sampled before or during the early stages of HIV-1 infection, and we were unable to address the sequence of events preceding bnAb development during the course of infection. However, to gain insight into whether some healthy individuals have a preexisting immunological profile that could potentially predispose them to bnAb induction after HIV acquisition, we analyzed CD4+ T cell subsets in healthy HIV-1–seronegative individuals with and without plasma autoantibodies. None of the 48 HIV-1–seronegative control individuals studied in parallel to the HIV-1–infected groups had plasma autoantibodies. However, when we screened for the presence of autoantibodies in 118 predominantly African HIV-1–seronegative individuals, we identified 12 individuals who had plasma autoantibodies. Analysis of total and regulatory CD4+ T cell populations in these individuals and a control group of 23 age-, sex-, and location-matched HIV-1–seronegative individuals without plasma autoantibodies revealed that there was no difference between groups in the frequency of total CD4+ T cells within lymphocytes or circulating frequency of mTfh cells (Fig. 5, A and B, and table S28), but that the frequency of CD25+ Foxp3+ CD4+ Treg cells in the HIV-1–uninfected individuals with autoantibodies was lower than that in those without autoantibodies, although the difference was not statistically significant (P = 0.06, t test; Fig. 5C and table S28). The level of PD-1 expression on CD4+ Treg cells in some of the HIV-1–uninfected individuals with autoantibodies was also higher than that in those without autoantibodies, although there was no significant difference between groups in PD-1 expression on CD4+ Treg cells overall (P = 0.63, t test; Fig. 5D and table S28).

Fig. 5 T cell subsets in healthy, HIV-1–seronegative African individuals with and without autoantibodies.

HIV-1–seronegative individuals with and without autoantibodies had similar frequencies of total CD4+ T cells within lymphocytes (A). The circulating frequency of resting mTfh cells was similar in HIV-1–seronegative individuals with and without autoantibodies (B). CD4+ Treg cell frequency within lymphocytes in HIV-1–seronegative individuals with autoantibodies did not differ significantly from that in those without autoantibodies (C). PD-1 MFI on CD4+ Treg cells in HIV-1–seronegative individuals with autoantibodies did not differ significantly from that in those without autoantibodies (D). In all panels, each symbol represents data from an individual; group medians, range, and quartiles are shown.

Because HLA allotypes have been associated with the development of autoimmune disease (59), we performed HLA typing on all individuals in cohort A and found no significant differences in distribution between bnAb versus control groups for HLA class I (tables S29 and S30) or class II allotypes (Cochran-Mantel-Haenszel tests) (tables S31 and S32).

Last, to look for evidence of genes that predisposed HIV-1–infected individuals to make bnAbs, we performed full exome sequencing on the 51 bnAb individuals and on the 51 control HIV-1–infected individuals without bnAbs. We found no statistically significant genome-wide mutations in either group, although we did identify 20 single-nucleotide variants or small indels in the association study of HIV-1 broad neutralization before genome-wide statistical correction (table S33). To focus the analysis, we compared only those bnAb individuals who also expressed plasma autoantibody reactivity with individuals in the non-bnAb group who showed no autoantibody activity. Again, no statistically significant genome-wide associations were found; however, a number of candidate genes that are known to be relevant to controlling the immune system were identified (table S34).

DISCUSSION

A major conundrum in the HIV-1 vaccine development field is why 50% of HIV-1–infected individuals make bnAbs after years of infection, but vaccination of uninfected individuals with antigenic HIV-1 envelopes has, as yet, not induced bnAbs. Although structural integrity of the native envelope immunogen is a critical component for induction of bnAbs (3), multiple envelope trimer immunization studies have yet to induce bnAbs (6066). Here, we have defined the profile of immune perturbations found in those HIV-1–infected individuals with plasma bnAbs. HIV-1–infected individuals who make cross-reactive neutralizing antibodies have a higher viral load, lower total CD4+ T cells, a higher frequency of blood autoantibodies, higher levels of circulating mTfh cells, a lower frequency of Treg cells, and higher levels of PD-1 on Treg and Tfr cells compared with a group of HIV-1–infected individuals with no or low bnAb levels.

Early in the AIDS epidemic before antiretroviral treatment, it was noted that HIV-1 infection induced host immunoregulatory abnormalities leading to plasma autoantibody production (27, 29, 31, 43) and a high incidence of autoantibody seropositivity (2730, 32, 33). In an earlier pilot study of 16 HIV-1–infected individuals, we found that anti-cardiolipin antibodies were frequently present in those with plasma neutralization breadth but no observed elevation of other autoantibodies (67). The findings in our current study provide evidence for the hypothesis that one reason that bnAbs are induced in some HIV-1–infected individuals is that HIV-1 infection perturbs their immune system by loss, activation, and/or exhaustion of CD25+ Foxp3+ Treg cell populations in the setting of elevated CD4+ Tfh cells, thus facilitating the production of bnAbs. It would be of interest to prospectively recruit a new group of acutely HIV-1–infected individuals to determine the mechanism and timing of these events rather than use retrospective samples. However, with evidence supporting the early initiation of antiretroviral therapy at the time of diagnosis (68), it is no longer ethical to perform natural history studies of HIV-1 infection without offering antiretroviral therapy.

In HIV-1 infection, CD4+ T cells, including CD25+ Foxp3+ CD4+ Treg cells, are lost as a consequence of infection with HIV-1 and bystander apoptosis (69, 70). The cohort A HIV-1–infected individuals producing bnAbs had higher viral loads than those not producing bnAbs, and higher viral loads have also been associated with bnAb production in other HIV-1–infected cohorts [reviewed in (71)]. However, although the high viral loads in bnAb individuals may have been among the factors contributing to the greater depletion of both total CD4+ T cells and CD4+ Treg cells in the individuals producing bnAbs in our study, all the differences observed in CD4+ T cell subsets between the groups of individuals producing or not producing bnAbs were independent of viral load, indicating that they were primarily driven by other factors.

Tfh cell differentiation is a multistep process regulated by numerous signals; however, cytokines play an important role in regulation of early Tfh differentiation, with signaling via interleukin-6 (IL-6) promoting Tfh differentiation and signaling via IL-2 inhibiting Tfh differentiation (72). Tfh cells are thus expanded in a number of chronic viral infections, including HIV-1, where IL-6 is induced and IL-2 is limited (34, 7377). In a previous study of a HIV-1–infected cohort, chronically infected individuals generating bnAbs were found to have higher circulating frequencies of mTfh than matched individuals not generating bnAbs (34). Locci et al. further showed that mTfh frequencies during early HIV-1 infection were higher in individuals who subsequently developed bnAbs; likewise, Cohen et al. reported an association between early preservation of PD-1+ CXCR5+ CD4+ Tfh cells and bnAb development (78).

A recent study proposed that the expansion of germinal center Tfh cells during simian immunodeficiency virus (SIV) infection may be facilitated by a decline in the Tfr/Tfh ratio (79). However, others have reported an increase in the frequency of Tfr in lymph nodes and spleen during SIV and HIV infection, which suggests that the lymph node Tfr/Tfh ratio may not be perturbed (80, 81). Here, we studied circulating CD4+ Treg and Tfr cell subsets. We found that compared with individuals without bnAbs, individuals with bnAbs had a lower frequency of CD4+ Treg cells within lymphocytes, but although CD4+ Tfr cells largely differentiate from Treg cells (3739, 82), the circulating frequency of Tfr cells did not differ significantly between groups. Notably, PD-1 was expressed at significantly higher levels on both CD4+ Treg and CD4+ Tfr cells in individuals with bnAbs. Elevated PD-1 expression in the bnAb group likely reflects higher levels of immune activation in these individuals, consistent with which CD4+ Treg cells also expressed higher levels of the activation marker HLA-DR. PD-1 is an inhibitory receptor, the ligation of which has been shown to inhibit Tfr function in mice (41). PD-L1 expression on lymph node B cells is increased during HIV-1 infection (77); hence, the function of Tfr in individuals producing bnAbs may be inhibited as a consequence of their elevated expression of PD-1. PD-1 expression can also reflect T cell exhaustion as a consequence of sustained activation, and CD4+ Treg cells from individuals producing bnAbs expressed elevated levels of CTLA-4 and LAG-3, markers indicative of CD4+ T cell exhaustion (56). Although CTLA-4 and LAG-3 are also involved in Treg and Tfr function (40, 57, 58), we found that PD-1high CD4+ Treg cells exhibited an impaired ability to suppress the proliferation of Tconv cells in vitro, supporting the hypothesis that elevated PD-1 expression on Treg cell subsets may reflect cellular exhaustion and an impaired suppressive capacity.

Our data suggest that, by the time of chronic HIV-1 infection, most viremic individuals develop alterations in the CD4+ T cell subsets that mediate control of germinal center B cell responses. High viral loads, immune activation, dysregulation of cytokine production, and alterations in lymphoid tissue microenvironments may drive the development of particularly profound abnormalities in Treg cell subsets in some individuals, creating an environment permissive to generation of both autoantibodies and bnAbs that then emerge in a subset of these individuals. However, because some HIV-1–infected individuals with bnAbs did not have autoantibodies, the propensity to make autoantibodies may be a surrogate marker for an as-yet undiscovered perturbation induced by HIV-1 that leads to bnAb induction. Moreover, we cannot rule out that those HIV-1–infected individuals without plasma bnAbs but with autoantibodies may eventually go on to develop bnAbs, but had not done so at the time of study.

Some individuals may also be predisposed to generate bnAbs after infection with HIV-1 because of preexisting abnormalities in host tolerance controls. Increased Tfh frequencies and loss or functional impairment of Treg cell subsets have been associated with autoantibody production in individuals with autoimmune disease (35, 4448). There may be a spectrum of tolerance controls in healthy individuals, with individuals at the lower end being more likely to develop autoantibodies and potentially also to produce bnAbs in the context of HIV-1 infection.

We previously demonstrated that two bnAbs (2F5 and 4E10) directed at the HIV-1 Env gp41 neutralizing site near the viral membrane are autoreactive (13, 83), and in bnAb antibody heavy- and light-chain knock-in mice, both bnAbs were shown to be controlled by multiple immune tolerance mechanisms (21, 22, 24, 84, 85). The observations of bnAb autoreactivity prompted the hypothesis that patients with systemic lupus erythematosus (SLE) will be able to make bnAbs more readily than others during chronic HIV-1 infection (15). We recently described an individual with both HIV-1 infection and SLE who had serum anti–double-stranded DNA (dsDNA) and bnAb activity (86), and an isolated CD4 binding site bnAb (CH98) from this individual cross-reacted with dsDNA, thus providing direct evidence that bnAbs and SLE autoantibodies can be derived from similar autoreactive pools of B cells and may be similarly regulated (86). Regardless of the mechanisms involved, the presence of autoantibodies in plasma is an indication of HIV-1–associated breaks in immune tolerance, and our finding of decreased frequency of CD25+ Foxp3+ Treg cell subsets in HIV-1–infected individuals who make bnAbs, together with increased expression of PD-1 on regulatory T cell populations, suggests a mechanism of release of peripheral immune tolerance controls (35).

The studies presented here raise several hypotheses. First, our data suggest that immunization of animals and humans with HIV-1 envelopes in the absence of replication of HIV-1–induced immune perturbations will be unlikely to induce mature bnAbs. New vaccination strategies for amplifying antibody responses by transiently limiting immune tolerance controls of antibody responses to bnAb Env epitopes may be needed. Such vaccination strategies are already being tested in the setting of cancer vaccines to augment host anticancer T cell responses (87). Temporary breaks in peripheral tolerance may be mediated by strong adjuvants, because we have shown that anergy of bnAb-producing B cells can be broken in bnAb VHDJH/VLJL knock-in mice by immunization with an Env subunit with a Toll-like receptor 4 (TLR4) agonist (23). Furthermore, TLR9 agonists can boost Tfh differentiation while blocking Tfr, thereby skewing the Tfr/Tfh ratio in favor of Tfh (88, 89).

Second, on the basis of the continuum of bnAb responses made after HIV-1 infection [(7) and the present study], it is possible that a strategy that succeeds in transiently breaking immune tolerance in the setting of HIV-1 Env immunization may only induce bnAbs in some individuals. Some bnAbs are restricted during early B cell development at the first tolerance checkpoint in bone marrow because of germline B cell receptor (BCR) autoreactivity, resulting in fewer bnAb precursors before vaccination (21, 22, 24, 84, 85), whereas other bnAb germline BCRs are not autoreactive, and autoreactivity is only acquired in the periphery during affinity maturation (90). bnAbs with long third heavy-chain complementarity-determining regions that do emerge in HIV-1 infection appear to be rare by virtue of tolerance mechanisms that reduce their precursor frequency (12, 26, 91). Recent data have demonstrated that one form of immune tolerance is continued accumulation of somatic mutations in autoantibody (92) and bnAb B cell lineages (23) that can lead to reduction in BCR antibody autoreactivity and, in the case of bnAb development, can reduce bnAb activity (93). It is important to note that not all bnAbs that eventually are made in HIV-1–infected individuals are autoreactive (94, 95), and immunization strategies are being developed to select and drive such subdominant B cell lineages (12, 16, 96).

Last, low-affinity BCR autoreactivity can be a normal component of the human B cell response (97, 98). Thus, transient manipulation of the germinal center response to augment persistent responses of normal autoreactive pools of B cells without permanently breaking systemic immune tolerance to induce desired bnAb B cell clonal lineages is plausible.

SUPPLEMENTARY MATERIALS

immunology.sciencemag.org/cgi/content/full/1/1/aag0851/DC1

Methods

Fig. S1. Eigenvalues and amount of variance explained up to PC6.

Fig. S2. Cohort A PC1 scores in descending order.

Fig. S3. Plots of individual autoantibody assay results.

Fig. S4. Gating strategy for flow cytometric analysis of T cell subsets.

Fig. S5. Comparison of Helios expression in CD4+ Treg cells in cohort A individuals with and without bnAbs and matched HIV-1–seronegative controls.

Fig. S6. Comparison of Tfr subsets (as defined using alternative phenotyping strategies) in cohort A individuals with and without bnAbs and matched HIV-1–seronegative controls.

Table S1. Country of origin for cohort A individuals.

Table S2. Cohort A individuals included and excluded from principal components analysis and control group.

Table S3. Cohort A bnAb group reciprocal dilution ID50 neutralization results.

Table S4. Cohort A control group reciprocal dilution ID50 neutralization results.

Table S5. Cohort A differences between bnAb and control groups for biological sex.

Table S6. Cohort A differences between bnAb and control groups for country of origin.

Table S7. Cohort A differences between bnAb and control groups.

Table S8. Cohort A mean duration individuals were followed.

Table S9. Cohort A clade of HIV-1 infection.

Table S10. General linear model results for the effect of clade of HIV-1 infection in cohort A on PC1 score.

Table S11. Logistic model results for the effect of clade of HIV-1 infection in cohort A in the presence of autoantibodies.

Table S12. Poisson model results for the effect of clade of HIV-1 infection in cohort A in the presence of autoantibodies.

Table S13. Cohort B bnAb individuals reciprocal dilution ID50 neutralization results.

Table S14. Cohort B control individuals reciprocal dilution ID50 neutralization results.

Table S15. Cohort B differences between bnAb and control groups for biological sex.

Table S16. Cohort B differences between bnAb and control groups.

Table S17. General linear model results for the difference between bnAb and control groups of cohorts A and B for binding to additional antigens.

Table S18. General linear model results for the difference in T cell subsets between cohort A bnAb and control groups and African seronegative individuals.

Table S19. Logistic model results for the effect of viral load in cohort A in the presence of autoantibodies.

Table S20. Poisson model results for the effect of viral load in cohort A in the presence of autoantibodies.

Table S21. General linear model results for cohort A bnAb and control groups with covariates for group, for viral load, and as an interaction term.

Table S22. General linear model results for cohort A bnAb and control groups with viral load as a main effect.

Table S23. General linear model results for the difference in alternatively defined Tfr subsets between cohort A bnAb and control groups and African seronegative individuals.

Table S24. General linear model results for Treg activation/exhaustion marker expression between cohort A bnAb and control groups and African seronegative individuals.

Table S25. General linear model results for Treg marker expression levels on Treg subsets defined by PD-1 expression levels for the cohort A bnAb group.

Table S26. General linear model results for Treg marker expression levels on Treg subsets defined by PD-1 expression levels for the African seronegative individuals.

Table S27. Sign test results for suppression of T cell proliferation by subsets of Treg cells with differing levels of PD-1 expression, normalized to Tconv plus Tconv.

Table S28. General linear model results for the difference in T cell subsets within cohort A HIV-1–seronegative individuals who were autoantibody-positive and autoantibody-negative.

Table S29. Cohort A bnAb group two-digit HLA class I types.

Table S30. Cohort A control group two-digit HLA class I types.

Table S31. Cohort A bnAb group two-digit HLA class II types.

Table S32. Cohort A control group two-digit HLA class II types.

Table S33. Top 20 most highly associated functional variants in exome sequencing of bnAbs versus non-bnAbs (dominant genetic model).

Table S34. Top 20 most highly associated functional variants in exome sequencing of autoimmune bnAbs versus non-bnAbs (dominant genetic model).

References (99111)

REFERENCES AND NOTES

Acknowledgments: We acknowledge the contributions of the Center for HIV/AIDS Vaccine Immunology (CHAVI) Clinical Core Team for recruiting study participants and carrying out all aspects of the CHAVI001 and CHAVI008 protocols at the University of North Carolina at Chapel Hill, Chapel Hill, NC (J. Eron); Duke University, Durham, NC (C. Hicks); Blantyre, Malawi (J. Kumwenda and T. Taha); University of North Carolina Center at Lilongwe, Malawi (I. Hoffman and G. Kaminga); University of the Witwatersrand, Johannesburg, South Africa (H. Rees); University of KwaZulu-Natal, Durban, South Africa (S. A. Karim); Kilimanjaro Christian Medical Centre, Moshi, Tanzania (S. Noel, S. Kapiga, and J. Crump); and Imperial College, London, UK (S. Fidler). We thank the team at the Mortimer Market Center, London, UK (I. Williams and P. Pellegrino), who recruited additional HIV-1–infected individuals. We also thank F. Cai for expert technical support. Funding: Support for this work was provided by grants from the NIH, National Institute of Allergy and Infectious Diseases, Division of AIDS; UM-1 grant for the Duke Center for HIV/AIDS Vaccine Immunology-Immunogen Discovery AI100645; NIH grant R21-AI100696; CHAVI-AI0678501; and MRC Programme grant MR/K012037. Author contributions: B.F.H. conceived and designed the study, oversaw and directed autoreactivity and plasma protein binding assays, evaluated all data, and wrote the paper; I.P.-P. developed methods for and performed flow analysis of CD4+ T cell subsets and contributed to data analysis; N.A.V. performed all statistical analysis in the paper and edited the paper; C.C. developed methods for and performed flow analysis of CD4+ T cell subsets; K.E.L. performed autoreactivity and plasma protein binding assays; R.P. performed autoreactivity and plasma protein binding assays; K.A.S. managed programmatic aspects of the study, including sample annotation and cohort analysis; A.T.O. performed flow analysis of CD4+ T cell subsets; M.S.C. led the team that acquired the samples in cohort A; H.-X.L. provided recombinant protein reagents for plasma binding assays; F.G. performed clade typing of HIV-1; A.J.M. designed experiments and evaluated CD4+ T cell flow data; D.C.M. performed neutralization assays; L.V. designed experiments and evaluated data; G.K. designed experiments, evaluated data, and edited the paper; J.H. screened, recruited, and performed neutralization assays on cohort B; P.R.S. performed the exome sequencing study and association analysis; M.C. provided samples for cohort B and wrote and edited the paper; P.B. designed and directed the CD4+ T cell subset analyses, evaluated all data, and wrote and edited the paper; and M.A.M. designed the study, wrote and edited the paper, and analyzed all data. Competing interests: The authors declare that they have no competing interests.
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