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Immunologic and Virologic Events in Early HIV Infection Predict Subsequent Rate of Progression - MAJOR ARTICLE
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The Journal of Infectious Diseases Jan 15 2010;201:272-284
"Future efforts to identify markers of subsequent progression should focus on measures of activation and homeostasis during the earliest stages of infection."
Anuradha Ganesan,1,a Pratip K. Chattopadhyay,2,a Tess M. Brodie,2 Jing Qin,3 Wenjuan Gu,4 John R. Mascola,2 Nelson L. Michael,5 Dean A. Follmann,3 and Mario Roederer,2 for the Infectious Disease Clinical Research Program HIV Working Groupb
1National Naval Medical Center, Infectious Disease Clinical Research Program, Uniformed Services University, 2Vaccine Research Center, National Institute of Allergy and Infectious Diseases, and 3Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, 4Biostatistics Research Branch, Scientific Application International Corporation-Frederick, Frederick, and 5United States Military HIV Research Program, Walter Reed Army Institute of Research, Rockville, Maryland
ABSTRACT
Background. Variability in human immunodeficiency virus (HIV) disease progression cannot be fully predicted by CD4+ T cell counts or viral load (VL). Because central memory T (TCM) cells play a critical role in the pathogenesis of simian immunodeficiency virus disease, we hypothesized that quantifying these cells in early HIV infection could provide prognostic information.
Methods. We measured expression of CD45RO, chemokine (C-C motif) receptor (CCR) 5, CCR7, CD27, and CD28 to enumerate naive and memory subsets in samples from recently infected individuals. We also quantified proliferation, CD127 expression, and cell-associated VL. Disease progression was compared across subgroups defined by these measurements, using Kaplan-Meier survival curves and multivariate Cox proportional hazards regression.
Results. Four hundred sixty-six subjects contributed 101 events. The proportion or absolute count of TCM cells did not correlate with disease progression, defined as the time to AIDS or death. However, significant associations were observed for proliferation within CD4+ or CD8+ T cells, loss of naive or CD127+ memory CD8+ T cells, and CD4+ T cell-associated VL.
Conclusions. Our results demonstrate that the extent of the immunopathogenesis established early in HIV infection predicts the course of future disease. Because antiretroviral drug treatment reverses such defects in part, our study provides mechanistic clues to why early use of antiretrovirals may prove beneficial.
Infection by human immunodeficiency virus (HIV) type 1 has commonly been viewed as slow and progressive, characterized by a gradual decline in T helper (CD4+) cells; however, there is considerable variation in the rate of progression among individuals. This variability has been largely ascribed to differences in set-point plasma HIV RNA levels (plasma viral load [VL]) and CD4+ cell counts, although other parameters, such as CD8+ T cell activation, have also shown predictive power [1-3]. These measurements account for a relatively small fraction of the variation in CD4+ cell decline and progression to AIDS; still, plasma VL and CD4+ cell counts are currently the major criteria used for initiating treatment with highly active antiretroviral therapy (HAART). Recent publications [4-8] underscore the uncertainty as to when treatment should be initiated. To identify individuals most likely to benefit from early therapeutic intervention, it would be highly valuable to identify correlates of progression measured during early infection.
It remains difficult to identify and sample patients with acute or early HIV infection. Much of our current knowledge on early mucosal and systemic immune responses, as well as immunopathogenesis, is based on studies performed in nonhuman primate models of simian immunodeficiency virus (SIV) infection [9]. Although overt immunodeficiency during the first few weeks of SIV (or HIV) infection is rare, there is a dramatic depletion of the total body memory CD4+ T cell compartment during this time; typically more than half of all memory cells are destroyed [10]. Furthermore, data suggest that measuring the extent of this destruction during the first 4 weeks of infection predicts life span independently of set-point VL [11, 12].
The results of experiments in nonhuman primate models suggest that the dynamics of memory T cell subsets play a role in the pathogenesis of disease. Memory CD4+ T cells can be subdivided into phenotypically distinct subsets that are related by differentiation and have different functions. Central memory (TCM) T cells, which localize to blood and secondary lymphoid tissues, are capable of regeneration and long-term maintenance. These can differentiate to effector memory T (TEM) cells, which are more prevalent in peripheral tissues and provide immediate effector functions at sites of inflammation. Chemokine (C-C motif) receptor (CCR) 5, the obligate coreceptor of most transmitted HIV, is highly expressed on TEM cells, making them a principal target for destruction during acute HIV or SIV infection. After the major destruction of memory CD4+ T cells, a dramatic proliferation of TCM cells occurs, probably part of the homeostatic mechanisms to compensate for the loss [13]. The proliferative response in the memory T cell compartment appears essential, in that its failure predicts rapid disease progression [13]. Elegant studies in nonhuman primate models suggest that homeostasis within the TEM compartment is dependent on the continued differentiation of TCM cells, and failure of this delivery due to the declining numbers of TCM cells accelerates advancement to AIDS [14]. This association is further strengthened by the observation that among animals vaccinated against SIV, the absolute number of TCM cells predict survival better than either the absolute CD4+ cell count or plasma VL [11, 12].
On the basis of these observations and the critical role of CD4+ TCM cells in adaptive immune responses, we hypothesized that quantifying these cells early after HIV infection might provide additional prognostic value for defining subsequent rates of progression. To this end, we conducted a large cross-sectional analysis in a well-characterized, racially diverse cohort of 466 individuals sampled during acute or early HIV infection. The a priori defined primary goal of this study was to determine the association between progression to AIDS or death and the absolute number or fraction of CD4+ and CD8+ TCM cells. We also performed exploratory analyses to determine the prognostic value of (1) markers of immune proliferation (Ki-67 expression) and long-lived memory potential (CD127 expression [15]), (2) representation of naive and multiple memory T cell subsets, and (3) cell-associated VL within subsets of CD4+ cells.
Discussion
We performed a detailed evaluation of T cells and CAVL in a large, well-characterized cohort of individuals with long-term follow-up. The strength of this study is the comprehensive evaluation of T cells at early time points after seroconversion, with a large number of end points. Our primary objective was to evaluate whether TCM cell quantification predicts disease progression; secondary end points included evaluation of other T cell subsets, immune proliferation (activation), and CAVL.
TCM cells are a cornerstone of the adaptive immune response; the SIV model of infection points to the critical role played by these cells in the pathogenesis of disease [11, 14]. However, in our well-characterized cohort of recently infected subjects, we did not observe an association between the proportion of TCM cells and disease progression. Nonetheless, we identified other potential correlates of progression, including proportions of naive or CD127+ memory CD8+ T cells, Ki-67 expression in CD4+ or CD8+ T cells (correlating with IA), and the CD4+ CAVL.
We considered several possible explanations for the lack of an association between TCM cells and disease progression. Because the proportions of memory cells vary with time since infection [10, 22], it is possible that mixing subjects identified during acute and during early HIV infection might mask associations. Therefore, we analyzed the predictive value of the proportion of TCM cells in depending on the time from imputed seroconversion (within 3 months, 3-6 months, etc); no significant association was observed for any group. Although our study was powered to demonstrate differences overall, this subgrouping significantly limits statistical power. Longitudinal studies with repeated sampling are probably necessary to associate the dynamics of TCM cells with disease progression. Nonetheless, in humans, remodeling of the memory compartment is sufficiently variable during early infection that enumeration of memory cells may not provide a predictor for progression.
As part of our secondary objectives, we evaluated the predictive value of other T cell subset representation. After HIV infection, the naive T cell pool progressively declines throughout the course of the disease [20, 23-25]. In our cohort, subjects who best maintained naive CD8+ T cells showed significantly slower progression of disease. This suggests that, though destruction of naive T cells was thought to be a consequence of chronic disease, the loss of these cells starts early and may be related to the mechanisms accounting for progression throughout disease.
Within the CD8+ T cells, another marker predictive of progression is expression of the interleukin (IL) 7 receptor (CD127). IL-7 plays an integral role in the differentiation and survival of TCM and naive T cells [21, 26], and CD127 expression appears necessary for the generation of long-lived memory T cells, a hallmark of protective immunity [26]. Disturbances in the IL-7/IL-7 receptor axis have been reported during both acute and chronic HIV infection [27-29]; levels of CD127-CD8+ T cells correlate with VL and inversely with CD4+ cell counts [28, 30]. Here we show that decreased levels of CD127+CD8+ T cells during early disease are associated with faster disease progression. Thus, the early depletion of long-lived cells in general (eg, naive or memory CD127+ cells) (Figure 4) may predict subsequent progression to AIDS more accurately than the loss of TCM cells as defined by commonly used phenotypic markers.
IA plays a key role in the pathogenesis of both SIV and HIV infection [31] and correlates with loss of CD4+ T cells and progression to AIDS. IA has been studied extensively in the setting of chronic HIV infection [2, 32, 33]; these findings, together with those from some small studies of early infection [1, 34, 35], suggested that early levels of IA may set the stage for future disease. In our study, the proportion of proliferating (Ki-67+) CD8+ and CD4+ T cells, a measure of IA, varied among individuals but was low overall (mean, 1.7%). Nonetheless, higher levels of proliferation were strongly predictive of progression. Specifically, the median time to AIDS or death among subjects with the highest levels (top quartile) of proliferation in CD8+ T cells was 4 years, in contrast to 10 years for subjects with the lowest levels. Furthermore, although proliferation was correlated with plasma VL (data not shown), it still provides independent predictive power. The mechanisms by which IA exerts deleterious effects remain unclear, but they may be closely related to altered CD127 expression, because T cell activation is associated with reduced CD127 expression and altered T cell homeostasis [28, 36, 37].
In our study, Ki-67 expression in CD8+ cells identified subjects with faster progression to AIDS or death, even after adjustment for CD4+ cell count and VL. This argues for the inclusion of a marker of proliferation and activation to the markers used to assess vaccine efficacy and prognostic significance after HIV infection. Similarly, measures of immune proliferation and activation could be used to identify subjects most at risk for progression and likely to benefit from early therapeutic intervention.
The basic impetus for our study was the finding that acute SIV infection is accompanied by a massive destruction of memory T cells. As discussed above, cross-sectional enumeration of TCM cell subsets in early HIV disease did not provide a correlate of subsequent progression. However, because the early destruction of CD4+ T cells is mediated by viral infection, we hypothesized that the CAVL at early time points would still indicate the extent of acute-phase destruction. Indeed, we found that CAVL was predictive of disease progression, in that disease progressed more rapidly in individuals with higher rates of infection in CD4+ T cells. Remarkably, we found relatively high rates of infection of naive CD4+ T cells (albeit 10-fold less than for memory CD4+ T cells). Naive CD4+ T cells do not express CCR5, the obligate HIV coreceptor for nearly all transmitted viruses. In this early-stage cohort, we expect that most circulating virus is CCR5 dependent. Because naive CD4+ T cells can be infected with CCR5-dependent viruses in vitro, with T cell activation [38-40], the infection in vivo that we observed may be a direct consequence of IA.
In otherwise asymptomatic individuals, current practice guidelines recommend initiation of antiretroviral therapy at a CD4+ cell count <350 cells/µL [41, 42]. However, a growing body of literature supports the initiation of antiretroviral therapy at higher CD4+ cell counts, demonstrating reductions in both AIDS- and non-AIDS-related morbidity and mortality [4, 5, 7, 43-45]. Our studies provide some mechanistic clues explaining these beneficial effects of HAART. Specifically, we suggest that immunologic disturbances (altered homeostasis and increased proliferation or activation) are established early in HIV infection and are observed even among subjects with relatively preserved CD4+ cell counts. The magnitude of these disturbances correlate with progression. Because HAART has been shown to reduce IA, preserve naive T cell populations, and maintain CD127 expression [27, 46-49], our data indirectly support early initiation of such therapy.
In conclusion, we find that quantification of TCM cells in early infection does not provide predictive power for progression. However, measures of homeostasis and activation, including CD127 expression and Ki-67, do provide such information and should be studied further to determine their role in clinical monitoring of HIV-1 progression. In addition, CAVL provides predictive power but is not as easy to implement routinely. Future efforts to identify markers of subsequent progression should focus on measures of activation and homeostasis during the earliest stages of infection.
Results
T cell phenotypes during early HIV infection.To determine whether TCM cells or other subsets predict disease progression, we performed a comprehensive phenotypic analysis of T cell subsets in early HIV infection using 14-color flow cytometric analysis. Figure 1A-1D shows representative staining patterns of the markers studied and how different subsets were defined. To simplify the presentation of these complex data, we grouped subpopulations in a manner synthesized from a number of reports. Specifically, CD45RO-CCR7+CD27+CD28+CCR5-CD57- cells were termed naive (a strict definition that minimizes contamination with memory cells), and differential expression of CCR5, CCR7, CD27, and CD28 were used to identify TCM, transitional memory (TTM), and TEM cells.
Figure 1E shows the distribution of cells within these subpopulations for our cohort. At these early time points in HIV disease, naive cells still comprise a large proportion of the T cell compartments, similar to findings in healthy controls. When we grouped patients by the EDSC, we found no statistically significant differences in T cell composition between subjects identified 0-3 months, 3-6 months, 6-9 months, or >9 months after seroconversion (Figure 2). Thus, in this cross-sectional study, T cell composition was not influenced by the length of infection. However, there was substantial heterogeneity in the frequency of each cell type (Figure 1E) which allowed us to examine whether differential representations were associated with disease progression.
Memory T cell representation and progression.
Our primary hypothesis, based on nonhuman primate models, was that the preservation of TCM cells after acute infection would predict disease progression. We divided the cohort into 3 groups based on TCM cells levels: those with the highest (>75th percentile), intermediate (25th-75th percentiles), or lowest (<25th percentile) levels (Figure 3). Next, we compared the relative risk of disease progression across these groups. On the basis of our power calculations, 65 events would provide us with sufficient power to detect a significant difference (HR, >2.0) among subjects with differing proportions of CD4+ or CD8+ TCM cells. Although the analyses were adequately powered (101 events in total), neither the proportion (Figure 4A) nor the absolute cell count (data not shown) of TCM cells at early time points predicted disease progression in adjusted or unadjusted analyses. Similar results were obtained for the subgroup of patients (50%) sampled within 225 days of their EDSC (data not shown).
In secondary analyses, we examined a number of other phenotypic measurements, including absolute number and percentage of naive, TTM, and TEM cells, and we found a number of parameters that were associated with progression. Notably, the proportion of CD8+ T cells that were naive strongly predicted slower disease progression (unadjusted p=10 -3). This measurement remains significant after adjustment for CD4+ cell count (Table 2). These data are in agreement with findings in chronic infection [20] and suggest that individuals capable of maintaining naive cells after the earliest stages of infection have a lower risk of AIDS.
We also investigated the association between CD127 expression in total or memory T cells and disease progression. CD127 expression is elevated in TCM cells compared with TEM cells, has been associated with homeostatic maintenance of memory cells [21], and is a marker for long-lived memory T cells [15]. As shown in Figure 4C, low levels of CD127+CD8+ T cells were significantly associated with faster progression.
Cell-associated VL predicts progression.
The destruction of CD4+ T cells during acute infection is most likely due to infection of the cells by virus [10]; a fraction of infected cells survive and carry viral DNA. Quantification of the cell-associated VL (CAVL) in early disease may reflect the extent of the viral replication (and hence associated immune destruction) during acute infection.
Based on the phenotypic measurements, we sorted 4 subsets of CD4+ T cells by flow cytometry for every sample (Figure 2). We found HIV gag DNA in all cell types examined (surprisingly, including CCR5- naive cells); TEM cells contain significantly higher levels than other cell types (Figure 5A). There was no significant difference in the predictive power of CAVL for any subset of CD4+ T cells (data not shown); thus, we computed the total CD4+ CAVL by summing the CAVL in each subset weighted by its representation. Total CAVL is a strong predictor of disease-free survival in subjects sampled within the first 225 days after seroconversion (Figure 5B; Table 2). The effect of CAVL differed according to whether samples were obtained before or after the median EDSC of 225 days (interaction p=.04), with CAVL having a strong effect for subjects undergoing sampling in early infection (unadjusted p=10 -4; adjusted p=.03) (Table 2 and Figure 5B). For those who underwent sampling >225 days after EDSC, CAVL did not predict the rate of disease progression.
T cell proliferation predicts progression.
To determine the prognostic significance of immune proliferation, we measured the expression of Ki-67 (an antigen expressed during cellular proliferation). Ki-67 expression levels in both CD4+ and CD8+ T cells were predictors of progression (Table 2 and Figure 6). Specifically, subjects with the highest levels of Ki-67 expression exhibited faster progression to AIDS, for either CD4+ or CD8+ cells (Table 2). After adjustment for baseline CD4+ cell count, age, and VL, CD8+ Ki-67 levels continued to be independent predictors of disease progression (Table 2).
We repeated our analysis of the ability of Ki-67 to predict progression by treating HAART use as a time-varying covariate (rather than censoring at initiation of HAART). In this analysis, the results were similar: the CD8+ Ki-67 level was strongly associated with progression in a univariate analysis (HR, 2.5; p<.001) and showed a trend toward significance in the multivariate model (HR, 1.81; p=.07).
Methods
Subjects.The United States Military HIV Natural History Study is a prospective observational cohort that has followed HIV-infected Department of Defense beneficiaries since 1985. As part of this study, subjects undergo semiannual study visits and blood sampling for routine laboratory testing, including CD4+ cell counts and HIV RNA levels, and storage within the Natural History Study repository. Recruitment and follow-up procedures for this cohort have been described elsewhere [16]. In brief, during the study visits all interim medical history are captured, including medication use, AIDS events, and significant non-AIDS events. Approximately one-half of enrolled subjects are seroconverters with documented HIV-negative and HIV-positive dates. Subjects eligible for inclusion in our study were defined as seroconverters with cryopreserved peripheral blood mononuclear cells (PBMCs) stored within 18 months of their estimated date of seroconversion (EDSC). We estimated seroconversion as the midpoint between documented HIV-negative and HIV-positive dates. All subjects provided written informed consent to participate in the parent protocol. Both this substudy and the parent protocol were evaluated and approved by the institutional review boards of the participating sites.
Cryopreserved PBMCs from 466 subjects were assayed for this analysis. Table 1 shows the baseline virologic, immunologic, and demographic characteristics of the study group. Most subjects were male (94%), and the study population was racially diverse. The median time from the EDSC to cell sampling was 225 days (interquartile range, 162-296 days). Baseline was defined as the time of the cell sample used for our analyses. The median CD4+ cell count at baseline was 552 cells/µL, and the median HIV RNA level was 4.2 log10 copies/mL. Subjects were observed for a mean of 4 years after seroconversion. A total of 135 AIDS or death events occurred, 34 after initiation of HAART. Although all events met the 1993 definition of AIDS, 47 events also satisfied the more rigorous 1987 definition of AIDS [18, 19].
Statistical methods.AIDS was defined using the 1993 Centers for Disease Control definition, and disease progression was defined as either the occurrence of an AIDS-defining event or death [19]. For the time-to-event analysis, subjects were divided into 3 groups based on quartiles (lowest, <25%; intermediate, 25%-75%; upper, >75%) of measured variables. Both Kaplan-Meier curves and Cox proportional hazards regression models were used to evaluate the predictive value of immunophenotypic characteristics, immune activation (IA), and cell-associated VL. Time 0 (baseline) was defined as the time of the cell sample. For about 15% of the patients, HIV RNA measurements were missing or not within 30 days of baseline; consequently, 34% of the events are missing in analyses that adjust for HIV VL. For this reason we also report analyses adjusted only for CD4+ cell counts. There was no adjustment for multiple comparisons; P values should be interpreted with this in mind. Kaplan-Meier P values on graphs are based on the log-rank statistic.
To assess whether the relationship of the predictor variables varied with stage of infection, for selected variables, we used the median time from imputed seroconversion to procurement of cell samples to divide subjects into 2 groups. The first group included one-half of the subjects, sampled within 225 days (7.4 months) of their imputed seroconversion, and the second group included the other half, sampled after 225 days. If a test of interaction (comparing the effect of the predictor variable between the 2 groups) showed a significant difference (p=.05), we reported the results separately for the early and late subgroups.
For the primary analysis, all observations were censored either when HAART was initiated or at last follow-up. Although HAART is probably not an independent censoring mechanism, treating it as such probably results in slightly conservative estimates of hazard ratios (HRs). We also conducted additional sensitivity analyses in which HAART use was treated as a time-varying covariate and analyses were stratified by whether the baseline sample occurred before or after 1 January 1996, the year HAART became universally available in the United States. Results from these analyses were similar to those of the primary analysis. Statistical analysis was performed using SAS software, version 9.1 (SAS Institute), and S-PLUS software, version 6.2 (Tibco).
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