Relative control of HIV-1 infection has been linked to genetic and immune host factors. In this study, we analyzed 96 plasma proteome arrays from chronic untreated HIV-1–infected individuals using the classificatory random forest approach to discriminate between uncontrolled disease (plasma viral load [pVL] >50,000 RNA copies/ml; CD4 counts 283 cells/mm3, n = 47) and relatively controlled disease (pVL <10,000 RNA copies/ml; CD4 counts 657 cells/mm3, n = 49). Our analysis highlighted the TNF molecule’s relevance, in particular, TL1A (TNFSF15) and its cognate DR3 (TNFSRF25), both of which increased in the relative virus control phenotype. DR3 levels (in plasma and PBMCs) were validated in unrelated cohorts (including long-term nonprogressors), thus confirming their independence from CD4 counts and pVL. Further analysis in combined antiretroviral treatment (cART)–treated individuals with a wide range of CD4 counts (137–1835 cells/mm3) indicated that neither TL1A nor DR3 levels reflected recovery of CD4 counts with cART. Interestingly, in cART-treated individuals, plasma TL1A levels correlated with regulatory T cell frequencies, whereas soluble DR3 was strongly associated with the abundance of effector HLA-DR+CD8+ T cells. A positive correlation was also observed between plasma DR3 levels and the HIV-1–specific T cell responses. In vitro, costimulation of PBMC with DR3-specific mAb increased the magnitude of HIV-1–specific responses. Finally, in splenocytes of DNA.HTI-vaccinated mice, costimulation of HTI peptides and a DR3 agonist (4C12) intensified the magnitude of T cell responses by 27%. These data describe the role of the TL1A–DR3 axis in the natural control of HIV-1 infection and point to the use of DR3 agonists in HIV-1 vaccine regimens.

This article is featured in Top Reads, p.3235

Combined antiretroviral treatment (cART) administered to HIV-infected subjects suppresses viral replication, leads to recovery of CD4 T cell counts, and reduces T cell activation. Although cART improves the quality of life and life expectancy of people living with HIV (PLWH), it entails substantial lifelong side effects and does not fully restore immune function (1). In addition, access and adherence to treatment are sometimes limited, especially in low-income countries. Therefore, there is an urgent need for strategies to achieve a so-called functional cure and/or intervention that can eliminate the virus from the body (2, 3).

A small group of PLWH, known as long-term nonprogressors (LTNPs), do not experience disease progression, even in the absence of cART over long periods of time. Similarly, CD4 T cell depletion occurs at a slower pace in LTNP than with standard disease progression. This relative control of HIV has been associated with several host factors, including markers of the innate and adaptive immune responses (4). Also, LTNP produce more polyfunctional HIV-specific CTL responses (5, 6), which has served as the rationale for therapeutic CTL vaccines in HIV cure strategies.

Despite the considerable knowledge of the features of LTNPs, we do not fully understand the mechanisms associated with this natural control. In addition, new clinical guidelines recommend early initiation of treatment (7), thus limiting identification of these individuals and, consequently, the definition of new biomarkers to predict natural control.

Multiple mechanisms may contribute to the heterogeneous nature of LTNPs, and many of these processes can be studied in plasma, an accessible biological fluid. Proteomic arrays enable the identification of key processes in plasma. The “communicome” array, a protein array detecting the levels of dozens to hundreds of plasma proteins involved in cell-to-cell communication, has recently been used to identify plasma factors predictive of plasma viral load (pVL) in untreated HIV infection (8). In this study, we extend the analysis of this multiplexed proteomic array in plasma samples from untreated PLWH using classificatory random forest analysis for discrimination between HIV progressors and individuals with relative virus control. Our analysis identified TNF and TNFR as crucial factors associated with HIV control. Of these, TL1A (TNFSF15) and its cognate death receptor DR3 (TNFRSF25) were of particular interest, given that validation studies in unrelated cohorts including LTNPs confirmed higher levels of DR3 in plasma and PBMCs of individuals with relative virus control. Interestingly, neither pVL nor CD4 counts were associated with DR3 levels. Comprehensive immunological data collected from a cART-treated cohort with a wide range of CD4 T cell recovery (9) indicated that, whereas the TL1A ligand is associated with the frequency of regulatory T cells (Tregs) (CD4 and CD8), soluble DR3 (sDR3) is strongly associated with activated effector CD8 T cells. In addition, plasma DR3 levels are associated with HIV-specific T cell responses, and ex vivo costimulation with DR3-specific Ab boosts these responses in untreated PLWH. An intensification of the HIV response was also detected after ex vivo costimulation of plasmid DNA-vaccinated mice splenocytes with DR3 Ab agonist (4C12). Taken together, these data indicate for the first time that TL1A/DR3 may play an important role in the immune control of HIV and highlight the potential use of DR3 costimulation with specific agonists in T cell–boosting regimens in HIV vaccine interventions.

Antiretroviral-naive HIV-seropositive subjects in the chronic disease stage (n = 96) recruited at Germans Trias i Pujol University Hospital (Badalona, Spain) and the IMPACTA clinics in Lima, Peru were grouped in relation to their ability to control HIV disease, as previously reported (8). In brief, individuals with relative disease control were classed as “HIV-Low” (n = 49) and had pVL <10,000 HIV RNA copies/ml (range 25–9990; median 530 HIV RNA copies/ml). The median CD4 count was 657 cells/mm3 (range 289–1343 cells/mm3). Individuals with uncontrolled disease were classed as “HIV-High” (n = 47) and had pVL >50,000 HIV RNA copies/ml (range 50,295–1,200,000; median 105,520 HIV RNA copies/ml) and a median CD4 count of 283 cells/mm3 (range 11–726 cells/mm3) (Supplemental Table I).

Additional unrelated cohorts included seronegatives (n = 8), chronic untreated individuals (“untreated,” n = 15), participants with 1 y of cART (“treated,” n = 10), and LTNPs (n = 31, including viremic controllers [n = 13, pVL <2000 copies/ml] and elite controllers [n = 18, undetectable pVL, <50 copies/ml]) (Supplemental Table I and Ref. 8). cART-treated individuals with a wide range of CD4 counts, including immune-concordant (IC, n = 12) and immune-discordant subjects (ID, n = 12), were also included in the study (Table I and Ref. 9). Finally, an additional chronically untreated HIV-infected cohort, “PLWH” (n = 6, pVL range <50–16,041 HIV RNA copies/ml and CD4 counts range 281–1500 cells/mm3), was included for functional in vitro studies (Supplemental Table I). The study was approved by the Clinical Research Ethics Committee of the Germans Trias i Pujol University Hospital (Clinical Research Ethics Committee: EO-12-042), and all participants provided their written informed consent. Blood samples were processed using Lymphoprep (STEMCELL Technologies), and isolated PBMCs, PBMC dry pellets, and plasma samples were frozen until use.

Proteomic arrays were run using a custom-designed chip that enabled the detection and quantification of >600 individual proteins, as reported previously (8, 10). Raw data were background subtracted and normalized using cluster analysis and z-scored [z = (x − μ)/σ]. Multivariate analyses were then performed with Bioconductor in R software package (http://www.r-project.org) (11) using the CMA package R/Bioconductor with five cross-validations (12). This approach combines variable selection and model classification (random forest). The process was repeated 100 times (20 randomly repeated 5-fold cross-validation processes). Finally, the area under the curve was used to evaluate the model. The output of this multivariate analysis provides a ranking of variables according to the number of times that each variable is selected. For further analysis, we included the subset of the top 25 scoring variables with a frequency of ≥100. Gene ontology (GO) enrichment analysis was performed using the GOStats package R/Bioconductor (13), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted with Database for Annotation, Visualization and Integrated Discovery (14, 15). A hypergeometric test was applied in both cases.

PBMC dry cell pellet samples were used for RNA extraction (RNeasy Plus Mini Kit; QIAGEN) and retro-transcription (SuperScript III First-Strand Synthesis SuperMix, Invitrogen). The cDNA was used for quantitative real-time PCR based on TaqMan gene expression assays for detection of TL1A (Hs00270802_s1), DR3 (Hs00237054_m1), and TBP (Hs99999910_m1) in a 7500 real-time instrument (Applied Biosystems). Relative expression was calculated as 2−Δcycle threshold (mean of three replicates).

TL1A was determined using an ELISA kit (Human TL1A/TNFSF15 DuoSet ELISA; R&D Systems). DR3 protein in plasma was determined using an ELISA kit from CUSABIO and Booster Immunoleader, following the manufacturer’s instructions. Quantification of ligand and receptor (TL1A and DR3) was calculated using a four-parameter logistic nonlinear regression model.

Data were generated as described elsewhere (9, 1619). Spontaneous cell death was evaluated in fresh samples using 40 nM DIOC6 (Invitrogen), as described previously (16), combined with propidium iodide (Sigma-Aldrich, Madrid, Spain). For other staining panels, flow cytometry was performed using a series of different Ab combinations. In brief, T cell maturation and immunosenescence were evaluated using CD3-allophycocyanin-Cy7, CD4-PerCP-Cy5.5, CD8-V500, CD57-FITC, CD27-allophycocyanin, CD28-PE, CCR7-PE-Cy7, and CD45RA-V450 (BD Biosciences). Proliferation and Treg phenotype were assessed using an Ab panel comprising Ki67-FITC, FOXP3-PE, CD25- PE-Cy7, CD127-Alexa Fluor 647, CD3-allophycocyanin-Cy7, CD4-V450, and CD8-V500. The activation panel included CD95-FITC, CD38-PE, HLA-DR-PerCP, CD3-allophycocyanin-Cy7, CD4-allophycocyanin, and CD8-PE-Cy7. All the stained cells were collected in LSR II flow cytometer (Becton Dickinson) and analyzed with FlowJo Software (version 7.6.5).

T cell immunity to HIV was assessed in purified PBMCs using the ELISPOT assay (100,000 PBMCs/well), with an overlapping peptide (OLP) set comprising 410 OLPs, as described elsewhere (20). The breadth (number of reactive OLPs) and magnitude (spot forming cells per 106 PBMCs) were recorded.

We cultured thawed cryopreserved PBMCs from untreated PLWH and LTNPs (Supplemental Table I) (150,000 PBMCs/well) in duplicate in 96-well ELISPOT plates (MultiScreen HTS MSIPS4W10, Millipore) and stimulated them with a pool of selected reactive OLP peptides (each peptide, 2 μg/ml, Supplemental Table II). We also stimulated cells with a CMV, EBV, and influenza virus (CEF) peptide pool designed to stimulate T cells (CEF-MHC Class I Control Peptide Pool Plus; Cellular Technology, Shaker Heights, OH). Then, we costimulated the cells with 100 ng/ml of soluble TL1A (sTL1A) (Recombinant Human TL1A/TNFSF15; R&D Systems), 500 ng/ml of sDR3 (Recombinant Human DR3/TNFRSF25 Fc Chimera Protein; R&D Systems), and/or 100 ng/ml of mAb anti-DR3 (Purified anti-human DR3 [TRAMP] JD3; BioLegend). Concentrations were based on the manufacturers’ recommendations. Cells were incubated overnight at 37°C in 5% CO2 and processed for the ELISPOT (see above). For evaluation of DR3 expression on T cells, cells were recovered before the ELISPOT development procedure and stained for surface markers (CD3-allophycocyanin-Cy7, CD4-allophycocyanin, CD8-PercP, and DR3-PE [anti-human DR3 (TRAMP) JD3] from BioLegend) acquired on an LSR Fortessa cytometer (Becton Dickinson) and analyzed using FlowJo 7.6.5 software.

Two groups of cohoused C57BL/6 mice (Envigo) were immunized i.m. with 100 μg/animal of DNA.HTI (21) in the Animal Facility of Germans Trias i Pujol University Hospital. The first group (n = 3) received three doses of vaccine and the second group (n = 4) four. All vaccinations were separated by 3 wk, and mice were euthanized 2 wk after the last vaccination. Spleens were removed, and splenocytes isolated by mechanical disruption and passage through a 45-μm cell strainer (Falcon) using a 5-ml rubber syringe plunger. Following RBC lysis with red cell lysis buffer (17 mM Tris and 0.14 M NH4Cl; Sigma), splenocytes were washed twice with RPMI 1640 supplemented with 10% FCS and penicillin/streptomycin and cryopreserved in N2 until use in FBS with 10% DMSO. Procedures involving mice followed European Union legislation on animal experimentation and were approved by the Animal Experimentation Ethics Committee of Germans Trias i Pujol Research Institute and the Ministry of Agriculture, Livestock, Fishing, and Food of the Generalitat de Catalunya (order no. 6390 and 9183).

IFN-γ ELISPOT was used to determine vaccine-specific T cell responses in mice. Briefly, thawed splenocytes (200,000 cells/well in RPMI 1640 and 10% FCS) from the HTI-vaccinated mice were simultaneously stimulated overnight with a set of 15-mer OLPs covering the whole sequence of the HTI immunogen (Supplemental Table II) and increasing doses of the mouse DR3 agonist 4C12 (0.5, 1, and 2 μg/ml). The magnitude of the response (spot forming cells per 106 PBMCs) was recorded.

Univariate statistical analyses were performed using Prism Version 6 (GraphPad). For comparisons between patient groups, the Mann–Whitney and Wilcoxon signed rank tests were applied. The Spearman test was applied for the correlation analysis. For all analyses, p values <0.05 were considered statistically significant.

The communicome approach has served to identify plasma markers that predict pVL in HIV disease (8) and to define predictive biomarkers of other diseases (10). To explore the soluble factors involved in natural control of HIV infection, a classificatory multivariate approach was applied to discriminate between uncontrolled and relative infection control phenotypes. Multiplexed arrays of HIV-High (n = 47) and HIV-Low individuals (n = 49) (Ref. 8 and Supplemental Table I) were analyzed by applying a random forest model. These analyses revealed a total of 25 soluble molecules among 600 factors that consistently (frequency of >100 of 1000 iterations) distinguished between both groups of individuals (Fig. 1A). The molecules fell most noticeably into the GO categories of chemokines (CCL-8, -18, -22, and CXCL-1) and cytokines (including TGF-b family members), as well as apoptotic factors that belong to the TNF/TNFR family (TNFSF15, TNFRSF10D, and TNFRSF10C) and cell adhesion categories (including SIGLEC9, SELE, and ALCAM) (Fig. 1A, 1B). The important role of the cell death process in the pathology of HIV was further supported by KEGG analysis, which also indicated the relevance of the apoptosis pathway in the control of HIV infection (fold enrichment of 3.5, Fig. 1C). TNF/TNFR fall into this category and discriminate between chronic untreated HIV-infected individuals with controlled or uncontrolled disease.

FIGURE 1.

Plasma soluble factors in chronic untreated HIV groups. Communicome arrays performed in 96 HIV-infected individuals with HIV-High (n = 47) and HIV-Low (n = 49) (Ref. 8 and Supplemental Table I) were analyzed by applying a random forest model. (A) Frequency plot indicating the relevance of the top 25 scoring soluble factors with frequency ≥100 obtained after cART analysis. (B) Pie chart representing the GO biological processes gene enrichment analysis percentages for each category represented among the top 25 candidates. (C) KEGG enrichment analysis showing the fold enrichment value of each pathway among the top 25 selected factors.

FIGURE 1.

Plasma soluble factors in chronic untreated HIV groups. Communicome arrays performed in 96 HIV-infected individuals with HIV-High (n = 47) and HIV-Low (n = 49) (Ref. 8 and Supplemental Table I) were analyzed by applying a random forest model. (A) Frequency plot indicating the relevance of the top 25 scoring soluble factors with frequency ≥100 obtained after cART analysis. (B) Pie chart representing the GO biological processes gene enrichment analysis percentages for each category represented among the top 25 candidates. (C) KEGG enrichment analysis showing the fold enrichment value of each pathway among the top 25 selected factors.

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Classificatory analyses of plasma proteomic arrays indicate that TNF/TNFR are relevant for discriminating between the two groups of chronic untreated HIV individuals studied. Among the TNF/TNFR detected, the TNFSF15 (TL1A) molecule stands out as it is the first marker when considering only the apoptosis category (Fig. 1) and the fifth discriminatory factor obtained in the multivariate analyses (frequency of 531). TL1A and its cognate receptor TNFRSF25 (also known as DR3) act as T cell costimulatory signal with pleiotropic and broad functions that have been poorly studied (22, 23). In this study, higher relative plasma levels of TL1A and DR3 were detected in untreated HIV-infected subjects with lower viremia and normal CD4 counts than in those with chronic uncontrolled HIV infection (Mann–Whitney U test, TL1A p = 0.0003 and DR3 p = 0.0445, Fig. 2A, 2B). As the HIV-Low group includes individuals with a wide range of pVLs, we compared the relative plasma levels of TL1A and DR3 in HIV-Low individuals, separating those with pVL <50 from those with pVL ranging from 50 to 10,000 copies/ml. No differences were observed between these two groups for either molecule (Supplemental Fig. 1A, 1B). In addition, correlation analyses in chronic untreated HIV individuals with pVL or CD4 counts indicated that sTL1A was associated with these two parameters (pVL: ρ = −0.2475, p = 0.0151; CD4 counts: ρ: 0.2355 p = 0.0209; Spearman rank test, data not shown), and no significant correlation was found with sDR3 levels. In addition to DR3, TL1A ligand can also signal through the decoy receptor 3 (DcR3) (24), although the relative plasma levels of DcR3 do not differ between both groups of chronic untreated HIV-infected individuals. This observation holds when pVL differences are considered in the HIV-Low group (Supplemental Fig. 1C, 1D).

FIGURE 2.

sTL1A and sDR3 plasma levels and PBMC gene expression in chronic HIV-infected individuals. sTL1A (A) and sDR3 (B) relative plasma levels (z-score communicome values) in HIV-High (n = 47) and HIV-Low (n = 49) (Supplemental Table I). (C and D) Gene expression (Supplemental Table I) of TL1A (C) and DR3 (D) in HIV-High (n = 16) and HIV-Low (n = 30). (E and F) Unrelated validation cohorts for gene expression of TL1A (E) and DR3 (F) in dry pellet PBMC samples from seronegatives (SN, n = 6) and HIV-infected individuals 1 y before and after initiation of treatment (untreated [n = 11] and treated [n = 5]) and in LTNP (n = 23) (Supplemental Table I). (G) Absolute DR3 quantifications in plasma (ELISA) in a confirmatory cohort including SN (n = 8) and samples from time points 1 y before and after initiation of treatment (untreated [n = 15] and treated [n = 10]) and controllers (n = 31) (Supplemental Table I). The Mann–Whitney U test was applied for group comparisons, and p values <0.05 were considered significant.

FIGURE 2.

sTL1A and sDR3 plasma levels and PBMC gene expression in chronic HIV-infected individuals. sTL1A (A) and sDR3 (B) relative plasma levels (z-score communicome values) in HIV-High (n = 47) and HIV-Low (n = 49) (Supplemental Table I). (C and D) Gene expression (Supplemental Table I) of TL1A (C) and DR3 (D) in HIV-High (n = 16) and HIV-Low (n = 30). (E and F) Unrelated validation cohorts for gene expression of TL1A (E) and DR3 (F) in dry pellet PBMC samples from seronegatives (SN, n = 6) and HIV-infected individuals 1 y before and after initiation of treatment (untreated [n = 11] and treated [n = 5]) and in LTNP (n = 23) (Supplemental Table I). (G) Absolute DR3 quantifications in plasma (ELISA) in a confirmatory cohort including SN (n = 8) and samples from time points 1 y before and after initiation of treatment (untreated [n = 15] and treated [n = 10]) and controllers (n = 31) (Supplemental Table I). The Mann–Whitney U test was applied for group comparisons, and p values <0.05 were considered significant.

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Although plasma protein concentration is a reflection of multiple cell sources, not only PBMC, we decided to explore TL1A and DR3 gene expression in PBMCs from chronic untreated HIV-1–infected individuals with different levels of virus control. Although no differences between HIV-High and HIV-Low are observed for TL1A (Fig. 2C), its cognate receptor DR3 is significantly highly expressed in HIV-Low individuals (p = 0.0289, Mann–Whitney U test, Fig. 2D), suggesting that in PBMCs, the receptor DR3 plays a more important role in discriminating between the groups than the ligand. Additionally, the expression levels of ligand and receptor in PBMCs were validated in unrelated cohorts of chronic infection including individuals 1 y before cART treatment initiation (untreated, n = 11), 1 y after cART initiation (treated, n = 5), LTNPs (n = 23), and seronegative individuals (n = 6). Consistently, these analyses confirmed that TL1A expression was not significantly different between groups (Fig. 2E) and that only the DR3 receptor was significantly highly expressed in LTNPs than in untreated individuals (p = 0.0107, Mann–Whitney U test, Fig. 2F). Treated individuals tend to have higher levels of DR3 in PBMCs than untreated individuals (Fig. 2F), although the difference is not statistically significant (p > 0.05).

To validate the plasma levels in unrelated cohorts, absolute protein concentration of TL1A and DR3 was quantified. Absolute TL1A levels in plasma did not reach the levels of detection of the assay Human TL1A/TNFSF15 DuoSet ELISA (R&D Systems) in most of the samples measured. In contrast, findings for plasma sDR3 confirmed the higher levels associated with HIV control observed in the plasma proteomic arrays and PBMC gene expression tests (LTNPs versus untreated p = 0.0282; LTNPs versus treated p = 0.0030; Mann–Whitney U test, Fig. 2G). In addition, DR3 levels in the group of HIV-seronegative individuals tended to be lower compared with LTNP and more similar to chronic viremic individuals, suggesting that LTNP had particularly high levels of DR3. Interestingly, ligand and receptor gene expression did not correlate in HIV-infected patients (Supplemental Fig. 1E). Only the plasma levels of TL1A and DR3 correlated positively in untreated HIV individuals measured in the communicome array (ρ = 0.2705, p = 0.0077, Spearman rank test, Supplemental Fig. 1F).

These results indicate that higher sDR3 levels in plasma and DR3 expression by PBMCs are associated with control of HIV. Interestingly, plasma and PBMCs DR3 levels did not correlate with pVL or CD4 T cell counts, pointing to mechanisms in HIV controllers that are independent of those directly associated with viral replication or its cytopathic effects.

The TL1A/DR3 axis is a key pathway for the development of effective T cell immunity (25). Thus, we investigated whether absolute TL1A and DR3 plasma levels were reflections of differential T cell immunity and were associated with CD4 T cell repopulation upon cART in HIV infection. To do so, we studied cART-treated individuals from a cohort of IC and ID participants. These groups show a wide range of CD4 T cell counts, which differ significantly between the IC (median CD4 T cell counts = 829 cells/mm3) and the ID (median CD4 counts = 214 cells/mm3) (Table I and Ref. 9). No differences in TL1A and DR3 plasma levels were detected between the two groups (TL1A, IC, mean = 45.82 pg/ml versus ID, mean = 50.06 pg/ml, p = 0.064; DR3, IC, mean = 0.56 ng/ml versus ID, mean = 0.84 ng/ml, p = 0.42; unpaired t test, data not shown), suggesting that CD4 T cell repopulation mechanisms are independent of the TL1A/DR3 signaling axis.

Table I.
CD4 and CD8 cell markers of maturation, Tregs, and activation evaluated by flow cytometry
 
 

Table shows the percentage of CD4 and CD8 T cells expressing cell markers of maturation, Tregs, or activation evaluated by flow cytometry. Cells shaded in green indicate a significant Spearman correlation. Bold in the cell subsets indicates there is at least one significant correlation.

Conc, immune-concordant; Dis, immune-discordant; Info, information; M, male; ns, not significant; F, female; TEMRA, terminally differentiated effectory memory cells.

Because the TLA1–DR3 axis is involved in several T cell immune processes (25), the plasma levels of TL1A and DR3 in treated HIV-infected participants were correlated with immune-phenotypic T cell markers measured by flow cytometry (Table I). Whereas sTL1A levels positively correlated with transitional memory phenotype CD4 T cells (ρ = 0.488, p = 0.011, Spearman rank test, Table I), sDR3 levels were positively correlated with the frequency of effector CD8 T cells (ρ = 0.6616, p = 0.0002, Spearman rank test, Fig. 3A, Table I) and inversely correlated with the naive CD8 T cell subpopulation (ρ = −0.512, p = 0.0008, Spearman rank test, Table I). These data indicated that the TL1A and DR3 plasma levels are associated with different CD4 and CD8 T cell populations and their maturation status, suggesting that the ligand and its receptor may serve variable functions that have been reported for different cell types (23).

FIGURE 3.

DR3 correlates with effector CD8 T cells and TL1A, with regulatory CD4 and CD8 phenotypes. (A and B) Correlation between plasma DR3 protein levels and the percentage of effector CD8 T cells (A) and HLA-DR+CD45RO+CD8 T cells (B) in a cohort of treated individuals (n = 26, Table I). (C) Correlation between ELISA-determined plasma TL1A levels and the percentage of CD25highFOXP3+ T cells (circles, CD4 T cells; squares, CD8 T cells) in treated individuals, including IC and ID individuals (n = 26, Table I). The Spearman rank test was used for the correlations, and p values <0.05 were considered statistically significant.

FIGURE 3.

DR3 correlates with effector CD8 T cells and TL1A, with regulatory CD4 and CD8 phenotypes. (A and B) Correlation between plasma DR3 protein levels and the percentage of effector CD8 T cells (A) and HLA-DR+CD45RO+CD8 T cells (B) in a cohort of treated individuals (n = 26, Table I). (C) Correlation between ELISA-determined plasma TL1A levels and the percentage of CD25highFOXP3+ T cells (circles, CD4 T cells; squares, CD8 T cells) in treated individuals, including IC and ID individuals (n = 26, Table I). The Spearman rank test was used for the correlations, and p values <0.05 were considered statistically significant.

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Given that DR3 is a multifaceted receptor involved in cell death and proliferation processes (23, 26) and that IC- and ID-treated subjects clearly differ in terms of cell death, proliferation (Ki67+), and senescence processes (CD57+) (9), we performed an association analysis of these T cell markers and plasma levels of TL1A and DR3. Only TL1A plasma levels correlated with naive CD57+CD4 T cells (ρ = 0.407, p = 0.039, Spearman rank test, data not shown), suggesting a potential relationship between TL1A and the proportion of senescent naive CD4 T cells in peripheral blood.

As this ligand–receptor axis has been shown to play a key role in the activation of T cells and Tregs in several disorders (22, 27, 28), further studies of the association between TL1A and DR3 plasma levels and activation markers and Treg percentages were undertaken. Interestingly, although sDR3 was clearly associated with effector CD8 T cells with an activated cell phenotype (HLA-DR+CD45RO+CD8 T cells, ρ = 0.457, p = 0.019, Spearman rank test, Fig. 3B, Table I), sTL1A correlated with nonproliferating T cells (CD4 and CD8) with regulatory phenotypes (CD25HighFoxp3+CD4 T cells, ρ = 0.479, p = 0.013; CD25HighFoxp3+CD8 T cells, ρ = 0.545, p = 0.004, Spearman rank test, Fig. 3C, Table I).

As sTL1A is closely associated with CD4 and CD8 Treg subsets and sDR3 is strongly associated with CD8 T cells with an effector and activated phenotype, these data suggest a dichotomous mode of action for the TL1A ligand and sDR3 in HIV infection, as previously reported for other diseases (22, 28). Accordingly, the disruption of the TL1A/DR3 axis favors tolerance processes, although its stimulation might benefit anti-tumor and antiviral T cell–mediated responses (25, 29), in line with the associations between higher levels of DR3 and TLA1 and improved HIV control (see above).

Given that the TL1A/DR3 axis is a key pathway for the development of effective CD4 and CD8 T cell antiviral responses (25), we evaluated the association between plasma TL1A and DR3 levels in chronic untreated HIV-infected individuals and the magnitude and breadth of HIV-specific T cell responses. Although sTL1A did not correlate with the magnitude or the number of responses, plasma sDR3 levels were associated with broader and stronger HIV-specific T cell responses (breadth: ρ = 0.2589, p = 0.0155; and magnitude: ρ = 0.2214, p = 0.0393; Spearman rank test, Fig. 4A, 4B). These results reinforce the aforementioned association between DR3 and activated effector CD8 T cells (Fig. 3A, 3B, Table I). Interestingly, a stronger correlation between sDR3 and T cell breadth was observed in HIV-Low individuals (ρ: 0.3175, p = 0.0380; Spearman rank test, Fig. 4A), suggesting a potential role for this receptor in the generation of broad HIV T cell responses in the setting of more effective virus control.

FIGURE 4.

TL1A/DR3 axis role in HIV-specific T cell responses. (A and B) sDR3 relative plasma levels (z-score communicome) correlate with T cell breadth (A) and magnitude (B) in HIV-High (n = 46) and HIV-Low (n = 41) individuals (Supplemental Table I). (C) IFN-γ ELISPOT (percentage increase in the magnitude of T cell) after HIV-specific peptide pool stimulation in the presence of recombinant TL1A and DR3 and specific anti-DR3 mAb in PBMCs from untreated PLWH (Supplemental Table I). (D) Percentage increase in the magnitude of CEF-specific responses upon costimulation with anti-DR3 mAb. (E) Increase in magnitude of DNA.HTI-specific T cell responses in isolated splenocytes from HTI-vaccinated mice after stimulation with the mouse DR3-specific Ab 4C12 (agonist DR3). The Spearman rank test was used for correlation analysis, and the Wilcoxon signed rank test for group comparisons. The p values <0.05 were considered statistically significant.

FIGURE 4.

TL1A/DR3 axis role in HIV-specific T cell responses. (A and B) sDR3 relative plasma levels (z-score communicome) correlate with T cell breadth (A) and magnitude (B) in HIV-High (n = 46) and HIV-Low (n = 41) individuals (Supplemental Table I). (C) IFN-γ ELISPOT (percentage increase in the magnitude of T cell) after HIV-specific peptide pool stimulation in the presence of recombinant TL1A and DR3 and specific anti-DR3 mAb in PBMCs from untreated PLWH (Supplemental Table I). (D) Percentage increase in the magnitude of CEF-specific responses upon costimulation with anti-DR3 mAb. (E) Increase in magnitude of DNA.HTI-specific T cell responses in isolated splenocytes from HTI-vaccinated mice after stimulation with the mouse DR3-specific Ab 4C12 (agonist DR3). The Spearman rank test was used for correlation analysis, and the Wilcoxon signed rank test for group comparisons. The p values <0.05 were considered statistically significant.

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Although the TL1A ligand is produced mostly by endothelial and APCs, the DR3 receptor is expressed mainly in Ag-experienced T cells (22). To evaluate the protein levels of DR3 in CD4 and CD8 T cells from HIV-infected subjects with a controller (n = 3) or noncontroller phenotype (n = 3), we used flow cytometry. Supplemental Fig. 2 shows that upon in vitro HIV peptide stimulation, controllers upregulate DR3 expression in CD4 and CD8 T cells, whereas noncontrollers are unable to upregulate this receptor after 24 h of peptide stimulation.

As DR3 is a costimulator of CD8 T cell responses (25, 29) and has been proposed as a potential adjuvant for vaccination regimens (30), ex vivo intensification of HIV-specific T cell responses were evaluated in the presence of recombinant sTL1A, sDR3, and anti-DR3–specific Ab in untreated PLWH (Fig. 4C, Supplemental Table I). After 24 h, the stimulation of HIV-specific peptides combined with DR3-specific Ab significantly enhanced the HIV-specific T cell responses (12%, p = 0.0210, Wilcoxon-matched pairs test, Fig. 4C) compared with peptide stimulation alone. Similarly, the CEF-specific T cell response was also boosted upon costimulation with DR3 Ab (20% of increased responses, p = 0.0781, Wilcoxon-matched pairs test, Fig. 4D).

Because no data on agonistic or blocking capacity for human DR3-specific Abs has been reported, we further evaluated the use of DR3 Ab agonist (4C12) in vitro in splenocytes from DNA.HTI-vaccinated mice. In line with the effect of DR3-specific costimulation seen in human cells, when splenocytes from DNA.HTI-vaccinated mice were cultured and stimulated with HTI peptides and 4C12, the HTI-specific responses were boosted by 27% (p = 0.0156, Wilcoxon signed rank test, Fig. 4E). These data are in line with the effect of DR3-specific costimulation seen in human cells and further support the important role of the DR3 receptor in driving cellular immunity against HIV (Fig. 5).

FIGURE 5.

Model of TL1A–DR3 axis in HIV infection. (A) Failure of TL1A–DR3 axis during uncontrolled HIV infection. Upon HIV-specific activation, there is no upregulation of DR3 in the surface membrane of CD8 T cells (AI). The reduced levels of sTL1A do not allow the signaling through DR3 receptor (AII), which would weaken the IFN-γ production (AIII). (B) HIV control. Upon HIV-specific activation, DR3 protein is upregulated on the cell membrane (BI) which, together with higher plasma levels of sTL1A and/or the presence of a DR3 agonist, would ensure the signaling of the TL1A–DR3 axis (BII). This costimulatory effect would enhance the HIV-specific IFN-γ responses (BIII).

FIGURE 5.

Model of TL1A–DR3 axis in HIV infection. (A) Failure of TL1A–DR3 axis during uncontrolled HIV infection. Upon HIV-specific activation, there is no upregulation of DR3 in the surface membrane of CD8 T cells (AI). The reduced levels of sTL1A do not allow the signaling through DR3 receptor (AII), which would weaken the IFN-γ production (AIII). (B) HIV control. Upon HIV-specific activation, DR3 protein is upregulated on the cell membrane (BI) which, together with higher plasma levels of sTL1A and/or the presence of a DR3 agonist, would ensure the signaling of the TL1A–DR3 axis (BII). This costimulatory effect would enhance the HIV-specific IFN-γ responses (BIII).

Close modal

LTNPs maintain low levels of HIV virus for long periods of time without the need for cART, indicating that some host mechanisms are able to control viral infection without total eradication of the virus. This group of individuals with special features, including highly polyfunctional CTL responses against HIV (5), has been extensively studied with the aim of identifying key mechanisms involved in the relative control of HIV infection and guiding new therapeutic interventions.

In this study, we focused on the search for traits that could discriminate between phenotypes of controlled and uncontrolled HIV infection using a previously reported communicome approach (8, 10). The main plasma factors that distinguish between untreated HIV-infected individuals with relative control or absence of control fell into the GO and KEGG categories related to the cell death process. It is known that uncontrolled HIV infection causes direct CD4 cell death as well as indirect immune cell depletion and dysfunction. Thus, although the enrichment of cell death processes in these plasma samples may be expected, the mechanisms involved in CD4 T cell loss remain unclear and could involve cell death and proliferative pathways (31).

Among all the proteins in the cell death category, TL1A (TNFSF15) emerged as the most relevant factor for differentiating between individuals with controlled and uncontrolled HIV infection. In addition, high plasma levels of its cognate receptor DR3 (TNFRSF25) are associated with control of HIV infection. These elevated plasma levels are supported by higher gene expression levels of DR3 in PBMCs in individuals with superior control of HIV. No such association was observed for TL1A plasma protein levels and PBMC gene expression; this observation is consistent with the major source of TL1A being endothelial/epithelial cells and, to a lesser extent, lymphoid and myeloid immune cells, whereas its cognate receptor DR3 is expressed mainly in activated T cells (CD4 and CD8) present in PBMCs (22).

Twenty years ago, the DR3 receptor was classified as a death receptor because of its capacity to activate caspase-dependent and -independent apoptosis processes (32, 33). However, it was subsequently reported that in lymphocytes, DR3 signaling predominantly induces the MAPK and NF-κB pathways associated with inflammation, survival, and proliferation (22, 24). Although the specific trigger of the different functions of DR3 receptor remains unclear, the increase in DR3 expression in TCR-activated T cells and the enhancement of T cell proliferation as effector functions through the TL1A–DR3 axis are well documented (22, 25). Therefore, levels of DR3 in plasma or PBMCs are not necessarily expected to correlate with CD4 T cell counts or cell death processes in our study. Moreover, the higher plasma levels detected in elite controllers are not recovered with cART or CD4 T cell repopulation. Therefore, in this report, we point to a key role of the TL1A–DR3 axis in T cell function for the control of HIV infection.

TL1A–DR3 signaling is associated with several T cell–dependent autoimmune diseases as well as with the induction and maintenance of chronic inflammation (23, 24, 28, 34), although its involvement in human infectious disease is unknown. In this study, we found that TL1A was associated with regulatory and exhausted phenotypes in CD4 T cell populations from cART-treated individuals, whereas DR3 was strongly correlated with activated effector CD8 T cells, possibly because of the pleiotropic functions of the TL1A–DR3 axis. In this regard, DR3 is constitutively expressed in Tregs, whereas the TL1A–DR3 axis is involved in Treg expansion. In fact, evidence from murine models has shown that treatment with TL1A–Ig limits graft-versus-host disease (3537). In contrast, DR3 is only expressed in conventional CD4 and CD8 T cells, and after stimulation of TCRs with foreign cognate Ags, it enhances effector functions. It has been proposed that in infectious disease, TLA1–DR3 signaling in conventional T cells induces killing of infected cells, whereas its signaling in Treg might prevent exacerbated immune responses that damage host tissues (22). Therefore, although blocking of the TL1A–DR3 axis has been suggested when this system is disrupted, such as in autoimmune or chronic inflammatory diseases (24, 34, 38), its stimulation might benefit antitumor and antiviral T cell–mediated responses (25, 29).

Interestingly, we show that in individuals with uncontrolled HIV infection and reduced plasma levels of TL1A, in vitro stimulation of their PBMCs with HIV T cell epitopes is not sufficient to upregulate DR3 expression in CD8 T cells (Fig. 5A, Supplemental Fig. 2). In contrast, in a situation of HIV natural control, HIV-1 Ag presentation to CD8 T cells upregulates DR3 on the cell membrane of T cells and, together with high levels of sTL1A, favors TL1A–DR3 axis signaling (Fig. 5B). Actually, in the general untreated HIV population, stimulation of the HIV peptide pool combined with DR3 costimulation by a DR3-specific Ab increased HIV-specific T cell responses by 12%. Therefore, we propose that the agonistic stimulation of the TL1A/DR3 axis would allow a more effective killing of HIV-infected cells (Fig. 5B). This finding may also hold for other pathogens because the addition of DR3 Ab could increase CEF-induced responses by 20%. In the murine CMV model, the essential role of DR3 for an efficient antiviral T cell response has been documented, and the absence of DR3 been shown to result in dysregulated virus control (25). Although the increases observed upon CEF pool stimulation are modest, stimulation of the TL1A/DR3 axis at the time of induction of de novo responses in vivo may increase their magnitude.

Costimulation with the TL1A and DR3 axis is essential for effective CD4 and CD8 T cell responses against murine CMV infection (25). Accordingly, TL1A protein or DR3 agonistic Abs have been proposed as adjuvants in Ag-specific vaccinations (23, 39). We observed that the use of Ab agonists of DR3 in responder DNA.HTI-vaccinated mice intensified CD8-specific Ag responses by >25% in ex vivo stimulation experiments. These data clearly support the future use of DR3 stimulation in vivo together with vaccine candidates designed for the induction of cellular immunity, as proven in murine cancer models (29) and which could possibly be extended to cure HIV infection.

The TL1A–DR3 axis can be modulated by other host soluble factors such as the DcR3, which binds and neutralizes the signaling function of TL1A, as well as other ligands, such as FasL and light protein. However, although its blockade might be interesting in a cancer setting with increased DcR3 levels (40, 41), we did not detect any differences between HIV-infected controllers and noncontrollers. Inhibition of ADAM17 (a member of the ADAM metallopeptidase family, also known as TNF-α–converting enzyme) has also been proposed as a therapeutic target in inflammatory diseases because it increases levels of sTL1A (42). However, given the pleiotropic effects of this metalloprotease, including supporting HIV virus infection (4345), it may not offer a therapeutic target in the HIV antiviral response. However, in the communicome array, increased plasma levels of TIMP3, an ADAM17 inhibitor, were detected in HIV controllers, thus further highlighting the potential of targeting the TL1A–DR3 axis in strategies aimed at boosting specific CD8 T cell responses in HIV infection and, by inference, the immune response to other pathogens.

Overall, this study identifies the TL1A–DR3 axis in plasma as a new marker for HIV control and shows that this axis is associated with virus-specific T cell responses. Therefore, these results show that immune intensification involving stimulation of the TL1A–DR3 axis could be considered in future vaccination strategies, not only for HIV, but also for other viruses and emerging pathogens.

We thank all the participants involved in the study.

This work was supported by a grant from the Ministerio de Ciencia e Innovación (SAF2017_89726_R), the European Union Horizon 2020 Framework Programme for Research and Innovation under Grant 681137-EAVI2020, National Institutes of Health, National Institute of Allergy and Infectious Diseases Program Grant P01-AI131568, the Fondation Dormeur, Vaduz, (Liechtenstein), and a research agreement with Aelix Therapeutics. M.L.C. was partially supported by the Spanish Ministry of Economy, Industry and Competitiveness, Reference MTM2015-64465-C2-1-R. This work has been carried out within the framework of the Ph.D. in Advanced Immunology of the Universitat Autònoma de Barcelona for B.O.-T. and C.D.-C. This study has also received funding from “La Caixa” Foundation under Project HR17-00199.

The online version of this article contains supplemental material.

Abbreviations used in this article:

cART

combined antiretroviral treatment

CEF

CMV, EBV, and influenza virus

DcR3

decoy receptor 3

GO

gene ontology

IC

immune-concordant

ID

immune-discordant

KEGG

Kyoto Encyclopedia of Genes and Genomes

LTNP

long-term nonprogressor

OLP

overlapping peptide

PLWH

people living with HIV

pVL

plasma viral load

sDR3

soluble DR3

sTL1A

soluble TL1A

Treg

regulatory T cell.

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B.M. is a consultant for AELIX Therapeutics outside the submitted work. C.B. is founder, chief science officer, and shareholder of AELIX Therapeutics; J.B. is chief executive officer, founder, and shareholder of AlbaJuna Therapeutics. The other authors have no financial conflicts of interest.

This article is distributed under The American Association of Immunologists, Inc., Reuse Terms and Conditions for Author Choice articles.

Supplementary data