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CD4+ T-cell gene expression of healthy donors, HIV-1 and elite controllers: Immunological chaos
Cytokine 83 (2016) 127–135
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CD4+ T-cell gene expression of healthy donors, HIV-1 and elite controllers: Immunological chaos G. Nunnari a, P. Fagone b, F. Condorelli c, F. Nicoletti b, L. Malaguarnera b, M. Di Rosa b,⇑ a
Unit of Infectious Diseases, Department of Clinical and Molecular Biomedicine, University of Catania, Italy Department of Biomedical and Biotechnological Sciences, University of Catania, Italy c DiSCAFF & DFB Center, University of Piemonte Orientale A. Avogadro, Novara, Italy b
a r t i c l e
i n f o
Article history: Received 21 January 2016 Received in revised form 18 March 2016 Accepted 15 April 2016
Keywords: CD4+ HIV EC HLA
a b s t r a c t Objectives: T-cell repertoire dysfunction characterizes human immunodeficiency virus type 1 (HIV-1) infection, but the pathogenic mechanisms remain unclear. Disease progression is probably due to a profound dysregulation of Th1, Th2, Th17 and Treg patterns. The aim of this study was to analyze the features of CD4+ T cells in HIV-positive patients with different viroimmunological profile. Methods: we used a gene expression dataset of CD4+ T cells from healthy donors, HIV+ naive patients and Elite Controllers (EC), obtained from the NCBI Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/, accession number GSE18233). Results: Principal Component Analysis (PCA) showed an almost complete overlap between the HIVinfected and EC patients, which cannot easily explain the different responses to HIV infection of these two group of patients. We have found that HIV patients and the EC showed an upregulation of the Th1 pro-inflammatory cytokines and chemokines, compared to the controls. Also, we have surprisingly identified IL28B, which resulted downregulated in HIV and EC compared to healthy controls. We focused attention also on genes involved in the constitution of the immunological synapse and we showed that HLA class I and II genes resulted significantly upregulated in HIV and in EC compared to the control. In addition to it, we have found the upregulation of others syncytial molecules, including LAG3, CTLA4, CD28 and CD3, assisting the formation of syncytia with APC cells. Conclusions: Understanding the mechanisms of HIV-associated immunological chaos is critical to strategically plan focused interventions. Ó 2016 Elsevier Ltd. All rights reserved.
1. Introduction The pathogenesis of HIV infection results in the loss of CD4+ Tcells resolving in immunodeficiency. The patients infected with HIV experience a progressive decline in the CD4+ T-cells count that leads inexorably to the development of the syndrome of acquired immune deficiency (AIDS), with the consequent death of the patient due to minor infection processes [1–3]. The introduction of highly active antiretroviral therapy (HAART) in the clinical practice has determined a significant reduction in morbidity and mortality of people infected with human immunodeficiency virus (HIV) [4]. Despite this, there are in clinical cases where some individuals able to control the virus infection and replication. The Elite Controllers (EC) are a group of HIV-infected patients who are able Abbreviations: CD4, cluster of differentiation 4; EC, elite controller; HLA, human leukocyte antigen; HAART, highly active antiretroviral therapy. ⇑ Corresponding author. E-mail addresses: [email protected], [email protected] (M. Di Rosa). http://dx.doi.org/10.1016/j.cyto.2016.04.007 1043-4666/Ó 2016 Elsevier Ltd. All rights reserved.
to spontaneously control viral infection in the absence of antiretroviral therapy. To date, these patients have an immunological profile which remains totally unexplored. Based exclusively on the serological criteria, the EC have a low viral load, a higher number of CD4 compared to the HIV patient, and show increased survival. Since these patients have a higher survival and fail to control the virus, they represent the best candidates for comparative studies with HIV patients. With the progressive loss of CD4+ T cells during HIV infection, the dysfunction in the T cells compartment is reflected by cytokine expression levels [5,6]. HIV infection disrupts cytokine production and function of the CD4+ T helper and CD8+ cytotoxic T cells with disease progression mainly associated with a Th2 cytokine profile despite some contradictory references [7–9]. The cytokines mainly expressed during HIV infection are IL1b, IL6, Tumor necrosis factor alpha (TNF-a), interferon gamma (IFN-c) and IL-10. Measuring these cytokines gives an indication of the degree of immune activation (elevated levels of TNF-a, IL-6 and IL-1), the extent of the immune response and disease progression. Measuring cytokine alterations during HIV infection [10–15]
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and other pathological states [16–20] is increasingly being investigated for use in predicting disease progression. In an investigation by Roberts et al. [14], Cox proportional hazards regression was used to show that the plasma cytokine profile can predict disease progression in an acute model of HIV infection. Talat et al. [16] applied both uni- and multivariate approaches and identified a plasma cytokine signature capable of distinguishing samples collected from HIV patients (on treatment) from uninfected controls. Several recent publication have analyzed the transcription profile of HIV target cells, such as CD4 T cell, monocytes, macrophages and dendritic cells [21–25]. In these publications it was shown that the molecular profile changes as a function of viral load, replication and persistence to infection. However, despite suppressing viremia, HAART therapy cannot eradicate HIV: residual low level viremia (LLV) can indeed be detected in most patients with ultrasensitive assays, because of the persistency of viral reservoirs and ‘‘sanctuary sites” not fully eradicated by HAART and may interfere with the panel of cytokine expression in plasma of patients [26–28]. In this study, we have performed a comparative analysis of the immunological profile of CD4+ T cells from Healthy individuals, HIV patients with a high viral set point and EC. Understanding the immunological features associated to the different response to HIV infection is key to strategically plan focused interventions.
2. Methods 2.1. Selection of a microarray expression dataset The microarray dataset for the transcriptional profile of CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) was obtained from the NCBI Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/). The NCBI GEO accession number for the microarray data here analyzed is GSE18233. Preprocessed matrix included variance-stabilizing transformation and robust-spline normalization. Demographic characteristics of the patients are presented in the relative publication [29]. The viral setpoint was calculated for each participant by determining plasma HIV-1 RNA in the absence of antiretroviral treatment between 3 months and 3 years after seroconversion. For the microarray, total RNA was extracted from CD4+ T cells positively selected using magnetically labeled CD4 microbeads from cryopreserved PBMCs. 2.2. Selection of samples and differential expression analysis For the analysis, drug-naive patients were selected and stratified using the viral set point as parameter. HIV patients form the upper quartile were considered in this study as HIV group, which included 27 subjects. The EC group, defined in Rotger et al., 2010
Fig. 1. Gene expression of Cytokines and its receptors in HIV, EC and Healthy. Expression levels of Cytokine (A) and its receptor (B) in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC). Dataset accession number GSE18233. Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄p < 0.001; ⁄⁄⁄p < 0.0001).
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[29], corresponded to the subjects in the 25th percentile and included 16 patients. Eight samples from 3 healthy controls served as control population. CD4+ T cells were positively selected from frozen PBMCs using magnetically labeled CD4 microbeads and subsequent column purification according to the manufacturer’s protocol (Miltenyi Biotec). CD4+ T cell purity, verified by flow cytometry, was 95.6% (86.4–98.1%). For the details see Rotger et al., 2010 [29]. The MultiExperiment Viewer (MeV) software was used to identify differentially expressed genes and to generate expression heatmaps. Hierarchical clustering of genes was performed with Euclidean distance as similarity measurements. In cases where multiple microarray probes mapped to the same NCBI GeneID, we chose the probes which showed the maximum variance. Genes selected for the analysis included Transcription Factors, Chemokines and Chemokines Receptors, Cytokine and Cytokine Receptors, as well as genes involved in the Immunological Synapse and HLA genes. Bonferroni adjusted t statistics was used to identify differentially expressed genes among the three groups of subjects included. A value of p < 0.05 was chosen as threshold. Principal component analysis (PCA) was conducted on
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all genes in order to assign the general variability in the data to a reduced set of variables using the R based package, RCommander. Complete data provided as Supplementary Table 1.
2.3. Identification of commonly regulated genes and functional interconnections In order to identify genes commonly modulated in HIV patients and Elite Controllers, Venn Diagrams were drawn using the webbased utility Venn Diagram Generator (http://www.bioinformatics.lu). Weighted ‘‘Gene Constellation Networks” were built for selected genes using GeneMania Database (www.genemania.org). GeneMania allows to have a global view of interactions between genes, based on functional interconnection among genes derived from experimental data and text-mining predictions. For each node, weight is calculated to maximize the connectivity between input genes using linear regression. The more the genes are interconnected, the higher the weight they are linked by and the shorter the edge linking them.
Fig. 2. Gene expression of Chemokines and its receptors in HIV, EC and Healthy. Expression levels of Chemokines (A) and its receptor (B) in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC). Dataset accession number GSE18233. Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄p < 0.001; ⁄⁄⁄p < 0.0001).
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3. Results 3.1. CD4+ T cells cytokine and its receptor in Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) For this analysis we decided to focus our attention to transcription Factors, Chemokines and Chemokines Receptors, Cytokine, Cytokine Receptors, as well as genes involved in the Immunological Synapse and HLA genes to clarify the role played by immunological pathways in HIV-1 infection. The microarray dataset analysis for the transcriptional profile of CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) showed a characteristic expression pattern of cytokine and its receptors (Fig. 1). The typical Th1 cytokines, IL1b and IFNc and IL18, associated to the HIV-1 infection, were significantly upregulated in HIV and EC patient (p < 0.0001) as compared to healthy (Fig. 1A). No
significant differences were found between HIV and EC patients. The same trend was observed for the IL1BR, IFNcR1, IFNcR2 and IL18R1 receptors (p < 0.001) (Fig. 1B). As regard the Th1 receptors in HIV and EC, we observed a significant upregulation of IL12RB1 and CCR6 (p < 0.001), and a significant downregulation of CCR1, IL12RB1 and CCR5 (p < 0.001) compared to the healthy controls. For the Th2 cytokine pattern, only IL10 resulted significantly upregulated, whereas IL25, IL4, IL9, IL13 and IL5 were significantly downregulated (p < 0.001) (Supplementary Fig. 1A). The Th2 transcription factor GATA3 was significantly upregulated (p < 0.001). The Th2 cytokine receptors, IL4R, IL10RA, IL10RB were significantly upregulated in HIV and EC (Supplementary Fig. 1B). Conversely, CCR1 and CCR10 resulted downregulated, compared to the healthy group. The expression levels of Th17 related molecules showed a contrasting trend. Only IL8 resulted significantly upregulated (p < 0.001) in HIV and EC, contrarily to its receptor IL8R that was
Fig. 3. HLA Class I and II gene expression in HIV, EC and Healthy. (A) HLA CLASS I gene expressed in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC); (B) HLA CLASS II gene expressed in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC); (C) Schematic representation of chromosome 6 and HLA human family localization; (D) Hierarchical clustering of the repertoire of HLA family expressed in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC). Unsupervised hierarchical clustering and Euclidean distance were used for similarity measurement. Gene expression values are color coded from bright red (most upregulated) to dark blue (most downregulated). Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄p < 0.001; ⁄⁄⁄p < 0.0001). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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significantly downregulated compared to the healthy. As regard IL17A, IL17F, IL21, no significant variation was observed in HIV and EC. IL17B and IL22 were found significantly downregulated. The TGFBR1 and TGFBR2 receptors showed to be significantly upregulated in both HIV and ECs, compared to the healthy. The expression of TGFB2, mainly associated to Treg cell, was significantly downregulated in HIV and EC compared to the healthy. The IL2Ra, IL2Rb and IL2Rg receptors were significantly upregulated in HIV and EC compared to the healthy (Supplementary Fig. 1B). In addition, we observed that IL28B was downregulated in HIV and EC compared to the health group, while its receptor resulted significantly upregulated (p < 0.001) (Supplementary Fig. 1A). 3.2. Expression levels of chemokines and chemokines receptors in CD4 + T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) The analysis of chemokines expression showed a strong upregulation of CCL3, CCL5 and CXCL16 (p < 0.001) in both HIV and EC compared to the healthy group (Fig. 2A). The CCL1, CCL20, CCL27, CCL18, CXCL1, CCL15 chemokines resulted significantly downregulated in HIV and EC compared to the healthy. No significant mod-
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ulation was observed for CCL4 (Supplementary Fig. 2A). As regard chemokine receptors, we observed a significantly upregulation of CCR6, CCR7 and CXCR4 while CCR1, CCR5 and CCR10 were significantly downregulated compared to the healthy (Fig. 2B) (Supplementary Fig. 2B).
3.3. The immunological synapse gene expression in healthy, HIV and EC CD4+ T cells The analysis of the HLA gene family expression brought to interesting observations. The major antigens of the HLA Class I genes, HLA-A, HLA-B and HLA-C were significantly upregulated in HIV and EC compared to healthy group (Fig. 3A, C, and D). As regards the minor antigens of the HLA Class I gene family, HLA-E, HLA-F and HLA-G, they resulted to be significantly upregulated in HIV and EC compared to the healthy group (Fig. 3A, C, and D). Surprisingly, we observed a strong upregulation of the HLA Class II gene expression in CD4+ T cells. In particular, HLA-DPA1, HLA-DQB1, HLA-DRA and HLA-DRB1 were significantly upregulated in HIV and EC as compared to the healthy group (Fig. 3B, C, and D).
Fig. 4. Immunological synapse gene expression in HIV, EC and Healthy. The upregulation of synapse gene shows the strong interaction capacity of infected cells compared to healthy. Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄ p < 0.001; ⁄⁄⁄p < 0.0001).
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In addition, we considered in our analysis the principal genes taking part to the constitution of the immunological synapse. We observed that CTLA4, CD28, CD69, CD4, CD3 and LAG3 were upregulated in HIV and EC compared to controls (Fig. 4) (Supplementary Fig. 3).
3.4. Comparative analysis between HIV and EC The gene expression analysis showed that 104 and 96 genes were significantly upregulated in HIV and EC respectively, while 57 and 56 were significantly downregulated in HIV and EC respectively, as compared to healthy (Supplementary Fig. 4A and B). Among the upregulated genes, 93 were common between HIV and EC, 3 were characteristic of EC (CXCL6, IFNA16, and IFNB1) and 11 characteristic of HIV (CCL2, CCL8, CCR4, CXCR6, HLA-DOB, HLA-DRB1, IFNG, IL15RA, IL2RA, IL2RG, TGFA). Among the downregulated genes, 52 were common to HIV and EC, 4 were characteristic of EC (CXCL13, CXCL3, IL7 and TBX21), and 5 were characteristic of HIV (CCL24, IFNA1, IL11RA, IL5RA, TGFB1L1) (Fig. 5A and B). Principal Component Analysis revealed an almost complete overlap in the phenotypic characteristics of HIV and EC (Fig. 5C). The genes that differed significantly between the two groups were only three, LAG3, GATA3 and HLA-A. (Fig. 5D). GATA3 levels in EC were significantly higher than those in HIV, while reduced expression levels in EC vs. HIV were observed for both LAG3 and HLA-A. Gene Constellation Networks were constructed for LAG3, GATA3 and HLA-A in order to identify functionally correlate genes (Supplementary Fig. 5). 12 genes resulted correlated to LAG3
among those significantly modulated during HIV infection. These included ICOS, chemokines (CXCL11, CCL13, CCL8, CCL14), cytokine receptors and associated molecules (IL12RB1, IL21R, IL1RAPL2, IL18BP, IL2RA), and HLA genes (HLA-DOA, HLA-C). GATA3 was associated to 61 molecules, including cytokines (IL1RN, IL4, IL5, IL9, IL10, IL12A, IL13, IL17C, IL17D, IL18, IL32, TGFB2) and granzymes (GZMA, GZMB, GZMK, GZMM). HLA-A was associated to 70 genes, which included, besides molecules belonging to the Immunological Synapse, several chemokines (CCL2, CCL3, CCL5, CXCL9 and CXCL11).
4. Discussion In this study, we tried to define the immunological profile of high viremic HIV patients and EC in comparison to uninfected subjects. Surprisingly, analysis of the data showed an almost complete overlap between the HIV-infected and EC patients, which cannot easily explain the different responses to HIV infection of these two group of patients. We have found that HIV patients and the EC showed a upregulation of the Th1 pro-inflammatory cytokines IL1B, IL8, IFNc and IL18 but not IL6 and TNF-alpha, compared to the controls. Another cytokine highly expressed during HIV infection was IL10, which provides an effective autoregulatory mechanism that counteract the excessive inflammation in chronic infections (such as TB, HIV and malaria) [30]. It was recently observed that IL-10 contributes to a reversible T-cell dysfunction in HIV infected persons, and that blockade of the IL-10 pathway is able to increase HIV-specific CD4 and CD8 T-cell proliferation, and effector T-cell functions [31].
Fig. 5. Upregulated and downregulated gene expression in HIV, EC and Healthy. (A and B) Schematic representation of significantly upregulated and downregulated gene in HIV, EC and Healthy; (C) Scatter plot of the first three components of PCA of EC, HIV and Healthy; (D) GATA3 was significantly more expressed in EC compared to HIV and Healthy. HLA-A was significantly more expressed in HIV compared to EC and Healthy; LAG-3 was significantly more expressed in HIV compared to EC and Healthy.
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Among the other cytokines significantly modulated, we have surprisingly identified IL28B, which resulted downregulated in HIV and EC compared to healthy controls. IL28B (interferon IFN l3) produces an antiviral state by triggering a cascade through the JAK-STAT pathway that up-regulates the IFN-stimulated genes (ISGs). The effects of IL28B are similar to those of IFN-a and -b; however, IL28B binds to a distinct receptor that may up-regulate a different set of ISGs [32]. This cytokine has been identified as a key modulator of the immune response to hepatitis C virus (HCV), because a single-nucleotide polymorphism (SNP) (rs12979860) upstream of the IL28B gene was associated with spontaneous and treatment-induced HCV clearance [33,34]. Rallón NI et al. have shown that the IL28B CC genotype is a strong predictor of virological response to therapy in HIV/HCV-coinfected patients. Therefore, the IL28B downregulation in HIV and EC may be a control mechanism adopted by the virus to escape to the ISGs immune control. Interestingly, also the IL8R resulted downregulated in HIV and EC patients. There is a not large literature on IL8R and HIV and the few information are not exhaustive [35,36]. It can be assumed that the reduction of IL8R is a way to reduce the CD4+ T cell chemoattraction capacity in order to block recognition mechanisms from CD8+ T cells [37]. As regards chemokines, the complex pattern of modulation of these molecules gives an idea of the immunological tangle triggered by virus infection. CCL2 is a pro-inflammatory chemokine that is induced during several human acute and chronic viral infections. In HIV-1 infection [38] the significant increase in CCL2 has
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been associated to the effects of virus-derived proteins, such as gp120 [39], Nef [40], matrix protein p17 [41] and transactivator protein Tat [42,43], thus suggesting the immunomodulatory capacity of these molecules which promote HIV/AIDS pathogenesis. Other chemokines upregulated were CCL3 (MIP1a) and CCL4, that are natural ligands for the primary human immunodeficiency virus type 1 (HIV-1) co-receptor CCR5 and are also known to activate and enhance the cytotoxicity of natural killer cells [44]. The cognate ligands of CCR5 co-receptor, CCL3 (MIP-1a), CCL4 (MIP-1b) and CCL5 (RANTES) are typically produced by CD8+ T cells and have been shown to inhibit infection with R5 HIV-1 strains [45]. As regard chemokine receptors, we observed a significant upregulation of CCR6. Interestingly, CCR4(+)CCR6(+) and CXCR3(+)CCR6 (+) T cells exhibit gut- and lymph node-homing potential and are highly permissive to HIV replication, with the potential to infiltrate and recruit more CCR6(+) T cells into anatomic sites of viral replication [46]. In our study, we focused attention also on genes involved in the constitution of the immunological synapse. The HLA class I genes resulted significantly upregulated in HIV and in EC compared to the control. Interestingly, when comparing high viremic HIV patients and EC, only HLA-A appeared to be significantly downregulated in EC. The potential contribution of HLA-A alleles to viremic control in chronic HIV type 1 (HIV-1) infection has been relatively understudied compared with HLA-B. It has been demonstrate that HLAA⁄7401 is associated with lower viral loads and higher CD4+ T cell
Fig. 6. Graphical representation of CD4+ T cells in HIV. The synapsis representation of CD4+ T cell HIV infected and polarizing gene expression. Gene expression values are color coded from bright red (most upregulated) to dark blue (most downregulated). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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counts in several southern African cohorts [47]. Therefore, the significant downregulation observed in EC compared to HIV could be due to the different viral load. The ability of EC to control the HIV-1 virus replication in CD4 infected cells could explain the HLA-A reduction in the cells surface. The HLA-A molecules may be involved in restricting HIV replication and the reduction of these molecules could be explain the inhibition of CD4 killing by CD8 (cytotoxic) T lymphocyte. Unexpectedly, analysis of expression for HLA class II genes revealed that HLA-DP, HLA-DQ and HLA-DR were significantly upregulated in HIV and EC compared to the Healthy. In a recent publication, authors showed that certain HLA class II alleles are associated with HIV control, while others are associated with rather rapid disease progression In particular, they found that HLADRB1⁄15:02 is significantly associated with low viremia, while HLA-DRB1⁄03:01 is significantly associated with high viremia. Of note, a subgroup of HLA-DRB1 variants linked with low viremia showed the ability to present a larger breadth of peptides with lower functional avidity when compared to HLA-DRB1 variants linked with high viremia [48]. The action of HLA-class II expressed in CD4 + T cells could also explain the formation of cell syncytia resulting in infection of uninfected CD4+ T cell. In the past indeed, it has already been demonstrated the HLA-DR fundamental role in the formation of HIV syncytia cell [49]. Therefore, one might assume that a CD4+ T cell HIV infected could be recognized through HLA class I by CD8+ T cell and recognized trough HLA class II by CD4+ T cell not yet infected. In addition to it, the upregulation of syncytial molecules like LAG3, CTLA4, CD28 and CD3, assist the formation of syncytia with APC cells (Fig. 6). The significantly upregulation of LAG3 in HIV vs EC, could be then explained with the reduction of immunoactivation in EC patients. It has been shows that LAG3 expression is associated as an inhibitory marker and in immune suppression [50,51]. The EC ability to control the HIV-1 virus replication could be explain by the immuno-escape reduction. Exists an inverse correlation between LAG3 expression and HIV viral load [52]. This evidence is in accordance with our results. The LAG3 downregulation could be an effect of HIV viral load reduction and may results in an increase of infected cells recognition. As regard the significant upregulation of GATA3 in EC vs HIV patients, we hypothesized that the reduction of immunoactivation increase the TFs like GATA3 important for T cell development, homeostasis, activation, proliferation, and effector functions, all conditions needed in EC CD4 T cells. In conclusion, T-cell repertoire dysfunction characterizes HIV infection, but the pathogenic processes underlying it remain unclear. Disease progression is probably due to a profound dysregulation of Th1, Th2, Th17 and Treg patterns, however the superimposable features between high viremic individual and EC do not allow for the precise characterization of the mechanisms of viral replication, immune evasion and immune system viral control. Conflict of interest The authors declare that they have no conflict of interests. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.cyto.2016.04.007. References [1] M.S. Gottlieb, J.E. Groopman, W.M. Weinstein, J.L. Fahey, R. Detels, The acquired immunodeficiency syndrome, Ann. Int. Med. 99 (2) (1983) 208–220. [2] A.S. Fauci, Multifactorial nature of human immunodeficiency virus disease: implications for therapy, Science 262 (5136) (1993) 1011–1018.
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CD4+ T-cell gene expression of healthy donors, HIV-1 and elite controllers: Immunological chaos G. Nunnari a, P. Fagone b, F. Condorelli c, F. Nicoletti b, L. Malaguarnera b, M. Di Rosa b,⇑ a
Unit of Infectious Diseases, Department of Clinical and Molecular Biomedicine, University of Catania, Italy Department of Biomedical and Biotechnological Sciences, University of Catania, Italy c DiSCAFF & DFB Center, University of Piemonte Orientale A. Avogadro, Novara, Italy b
a r t i c l e
i n f o
Article history: Received 21 January 2016 Received in revised form 18 March 2016 Accepted 15 April 2016
Keywords: CD4+ HIV EC HLA
a b s t r a c t Objectives: T-cell repertoire dysfunction characterizes human immunodeficiency virus type 1 (HIV-1) infection, but the pathogenic mechanisms remain unclear. Disease progression is probably due to a profound dysregulation of Th1, Th2, Th17 and Treg patterns. The aim of this study was to analyze the features of CD4+ T cells in HIV-positive patients with different viroimmunological profile. Methods: we used a gene expression dataset of CD4+ T cells from healthy donors, HIV+ naive patients and Elite Controllers (EC), obtained from the NCBI Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/, accession number GSE18233). Results: Principal Component Analysis (PCA) showed an almost complete overlap between the HIVinfected and EC patients, which cannot easily explain the different responses to HIV infection of these two group of patients. We have found that HIV patients and the EC showed an upregulation of the Th1 pro-inflammatory cytokines and chemokines, compared to the controls. Also, we have surprisingly identified IL28B, which resulted downregulated in HIV and EC compared to healthy controls. We focused attention also on genes involved in the constitution of the immunological synapse and we showed that HLA class I and II genes resulted significantly upregulated in HIV and in EC compared to the control. In addition to it, we have found the upregulation of others syncytial molecules, including LAG3, CTLA4, CD28 and CD3, assisting the formation of syncytia with APC cells. Conclusions: Understanding the mechanisms of HIV-associated immunological chaos is critical to strategically plan focused interventions. Ó 2016 Elsevier Ltd. All rights reserved.
1. Introduction The pathogenesis of HIV infection results in the loss of CD4+ Tcells resolving in immunodeficiency. The patients infected with HIV experience a progressive decline in the CD4+ T-cells count that leads inexorably to the development of the syndrome of acquired immune deficiency (AIDS), with the consequent death of the patient due to minor infection processes [1–3]. The introduction of highly active antiretroviral therapy (HAART) in the clinical practice has determined a significant reduction in morbidity and mortality of people infected with human immunodeficiency virus (HIV) [4]. Despite this, there are in clinical cases where some individuals able to control the virus infection and replication. The Elite Controllers (EC) are a group of HIV-infected patients who are able Abbreviations: CD4, cluster of differentiation 4; EC, elite controller; HLA, human leukocyte antigen; HAART, highly active antiretroviral therapy. ⇑ Corresponding author. E-mail addresses: [email protected], [email protected] (M. Di Rosa). http://dx.doi.org/10.1016/j.cyto.2016.04.007 1043-4666/Ó 2016 Elsevier Ltd. All rights reserved.
to spontaneously control viral infection in the absence of antiretroviral therapy. To date, these patients have an immunological profile which remains totally unexplored. Based exclusively on the serological criteria, the EC have a low viral load, a higher number of CD4 compared to the HIV patient, and show increased survival. Since these patients have a higher survival and fail to control the virus, they represent the best candidates for comparative studies with HIV patients. With the progressive loss of CD4+ T cells during HIV infection, the dysfunction in the T cells compartment is reflected by cytokine expression levels [5,6]. HIV infection disrupts cytokine production and function of the CD4+ T helper and CD8+ cytotoxic T cells with disease progression mainly associated with a Th2 cytokine profile despite some contradictory references [7–9]. The cytokines mainly expressed during HIV infection are IL1b, IL6, Tumor necrosis factor alpha (TNF-a), interferon gamma (IFN-c) and IL-10. Measuring these cytokines gives an indication of the degree of immune activation (elevated levels of TNF-a, IL-6 and IL-1), the extent of the immune response and disease progression. Measuring cytokine alterations during HIV infection [10–15]
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and other pathological states [16–20] is increasingly being investigated for use in predicting disease progression. In an investigation by Roberts et al. [14], Cox proportional hazards regression was used to show that the plasma cytokine profile can predict disease progression in an acute model of HIV infection. Talat et al. [16] applied both uni- and multivariate approaches and identified a plasma cytokine signature capable of distinguishing samples collected from HIV patients (on treatment) from uninfected controls. Several recent publication have analyzed the transcription profile of HIV target cells, such as CD4 T cell, monocytes, macrophages and dendritic cells [21–25]. In these publications it was shown that the molecular profile changes as a function of viral load, replication and persistence to infection. However, despite suppressing viremia, HAART therapy cannot eradicate HIV: residual low level viremia (LLV) can indeed be detected in most patients with ultrasensitive assays, because of the persistency of viral reservoirs and ‘‘sanctuary sites” not fully eradicated by HAART and may interfere with the panel of cytokine expression in plasma of patients [26–28]. In this study, we have performed a comparative analysis of the immunological profile of CD4+ T cells from Healthy individuals, HIV patients with a high viral set point and EC. Understanding the immunological features associated to the different response to HIV infection is key to strategically plan focused interventions.
2. Methods 2.1. Selection of a microarray expression dataset The microarray dataset for the transcriptional profile of CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) was obtained from the NCBI Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/). The NCBI GEO accession number for the microarray data here analyzed is GSE18233. Preprocessed matrix included variance-stabilizing transformation and robust-spline normalization. Demographic characteristics of the patients are presented in the relative publication [29]. The viral setpoint was calculated for each participant by determining plasma HIV-1 RNA in the absence of antiretroviral treatment between 3 months and 3 years after seroconversion. For the microarray, total RNA was extracted from CD4+ T cells positively selected using magnetically labeled CD4 microbeads from cryopreserved PBMCs. 2.2. Selection of samples and differential expression analysis For the analysis, drug-naive patients were selected and stratified using the viral set point as parameter. HIV patients form the upper quartile were considered in this study as HIV group, which included 27 subjects. The EC group, defined in Rotger et al., 2010
Fig. 1. Gene expression of Cytokines and its receptors in HIV, EC and Healthy. Expression levels of Cytokine (A) and its receptor (B) in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC). Dataset accession number GSE18233. Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄p < 0.001; ⁄⁄⁄p < 0.0001).
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[29], corresponded to the subjects in the 25th percentile and included 16 patients. Eight samples from 3 healthy controls served as control population. CD4+ T cells were positively selected from frozen PBMCs using magnetically labeled CD4 microbeads and subsequent column purification according to the manufacturer’s protocol (Miltenyi Biotec). CD4+ T cell purity, verified by flow cytometry, was 95.6% (86.4–98.1%). For the details see Rotger et al., 2010 [29]. The MultiExperiment Viewer (MeV) software was used to identify differentially expressed genes and to generate expression heatmaps. Hierarchical clustering of genes was performed with Euclidean distance as similarity measurements. In cases where multiple microarray probes mapped to the same NCBI GeneID, we chose the probes which showed the maximum variance. Genes selected for the analysis included Transcription Factors, Chemokines and Chemokines Receptors, Cytokine and Cytokine Receptors, as well as genes involved in the Immunological Synapse and HLA genes. Bonferroni adjusted t statistics was used to identify differentially expressed genes among the three groups of subjects included. A value of p < 0.05 was chosen as threshold. Principal component analysis (PCA) was conducted on
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all genes in order to assign the general variability in the data to a reduced set of variables using the R based package, RCommander. Complete data provided as Supplementary Table 1.
2.3. Identification of commonly regulated genes and functional interconnections In order to identify genes commonly modulated in HIV patients and Elite Controllers, Venn Diagrams were drawn using the webbased utility Venn Diagram Generator (http://www.bioinformatics.lu). Weighted ‘‘Gene Constellation Networks” were built for selected genes using GeneMania Database (www.genemania.org). GeneMania allows to have a global view of interactions between genes, based on functional interconnection among genes derived from experimental data and text-mining predictions. For each node, weight is calculated to maximize the connectivity between input genes using linear regression. The more the genes are interconnected, the higher the weight they are linked by and the shorter the edge linking them.
Fig. 2. Gene expression of Chemokines and its receptors in HIV, EC and Healthy. Expression levels of Chemokines (A) and its receptor (B) in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC). Dataset accession number GSE18233. Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄p < 0.001; ⁄⁄⁄p < 0.0001).
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3. Results 3.1. CD4+ T cells cytokine and its receptor in Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) For this analysis we decided to focus our attention to transcription Factors, Chemokines and Chemokines Receptors, Cytokine, Cytokine Receptors, as well as genes involved in the Immunological Synapse and HLA genes to clarify the role played by immunological pathways in HIV-1 infection. The microarray dataset analysis for the transcriptional profile of CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) showed a characteristic expression pattern of cytokine and its receptors (Fig. 1). The typical Th1 cytokines, IL1b and IFNc and IL18, associated to the HIV-1 infection, were significantly upregulated in HIV and EC patient (p < 0.0001) as compared to healthy (Fig. 1A). No
significant differences were found between HIV and EC patients. The same trend was observed for the IL1BR, IFNcR1, IFNcR2 and IL18R1 receptors (p < 0.001) (Fig. 1B). As regard the Th1 receptors in HIV and EC, we observed a significant upregulation of IL12RB1 and CCR6 (p < 0.001), and a significant downregulation of CCR1, IL12RB1 and CCR5 (p < 0.001) compared to the healthy controls. For the Th2 cytokine pattern, only IL10 resulted significantly upregulated, whereas IL25, IL4, IL9, IL13 and IL5 were significantly downregulated (p < 0.001) (Supplementary Fig. 1A). The Th2 transcription factor GATA3 was significantly upregulated (p < 0.001). The Th2 cytokine receptors, IL4R, IL10RA, IL10RB were significantly upregulated in HIV and EC (Supplementary Fig. 1B). Conversely, CCR1 and CCR10 resulted downregulated, compared to the healthy group. The expression levels of Th17 related molecules showed a contrasting trend. Only IL8 resulted significantly upregulated (p < 0.001) in HIV and EC, contrarily to its receptor IL8R that was
Fig. 3. HLA Class I and II gene expression in HIV, EC and Healthy. (A) HLA CLASS I gene expressed in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC); (B) HLA CLASS II gene expressed in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC); (C) Schematic representation of chromosome 6 and HLA human family localization; (D) Hierarchical clustering of the repertoire of HLA family expressed in CD4+ T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC). Unsupervised hierarchical clustering and Euclidean distance were used for similarity measurement. Gene expression values are color coded from bright red (most upregulated) to dark blue (most downregulated). Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄p < 0.001; ⁄⁄⁄p < 0.0001). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
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significantly downregulated compared to the healthy. As regard IL17A, IL17F, IL21, no significant variation was observed in HIV and EC. IL17B and IL22 were found significantly downregulated. The TGFBR1 and TGFBR2 receptors showed to be significantly upregulated in both HIV and ECs, compared to the healthy. The expression of TGFB2, mainly associated to Treg cell, was significantly downregulated in HIV and EC compared to the healthy. The IL2Ra, IL2Rb and IL2Rg receptors were significantly upregulated in HIV and EC compared to the healthy (Supplementary Fig. 1B). In addition, we observed that IL28B was downregulated in HIV and EC compared to the health group, while its receptor resulted significantly upregulated (p < 0.001) (Supplementary Fig. 1A). 3.2. Expression levels of chemokines and chemokines receptors in CD4 + T cells from Healthy donors, HIV+ patients (HIV) and Elite Controllers (EC) The analysis of chemokines expression showed a strong upregulation of CCL3, CCL5 and CXCL16 (p < 0.001) in both HIV and EC compared to the healthy group (Fig. 2A). The CCL1, CCL20, CCL27, CCL18, CXCL1, CCL15 chemokines resulted significantly downregulated in HIV and EC compared to the healthy. No significant mod-
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ulation was observed for CCL4 (Supplementary Fig. 2A). As regard chemokine receptors, we observed a significantly upregulation of CCR6, CCR7 and CXCR4 while CCR1, CCR5 and CCR10 were significantly downregulated compared to the healthy (Fig. 2B) (Supplementary Fig. 2B).
3.3. The immunological synapse gene expression in healthy, HIV and EC CD4+ T cells The analysis of the HLA gene family expression brought to interesting observations. The major antigens of the HLA Class I genes, HLA-A, HLA-B and HLA-C were significantly upregulated in HIV and EC compared to healthy group (Fig. 3A, C, and D). As regards the minor antigens of the HLA Class I gene family, HLA-E, HLA-F and HLA-G, they resulted to be significantly upregulated in HIV and EC compared to the healthy group (Fig. 3A, C, and D). Surprisingly, we observed a strong upregulation of the HLA Class II gene expression in CD4+ T cells. In particular, HLA-DPA1, HLA-DQB1, HLA-DRA and HLA-DRB1 were significantly upregulated in HIV and EC as compared to the healthy group (Fig. 3B, C, and D).
Fig. 4. Immunological synapse gene expression in HIV, EC and Healthy. The upregulation of synapse gene shows the strong interaction capacity of infected cells compared to healthy. Data are expressed as intensity expression levels and presented as scatter dot plot. p values <0.01 were considered to be statistically significant (⁄p < 0.01; ⁄⁄ p < 0.001; ⁄⁄⁄p < 0.0001).
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In addition, we considered in our analysis the principal genes taking part to the constitution of the immunological synapse. We observed that CTLA4, CD28, CD69, CD4, CD3 and LAG3 were upregulated in HIV and EC compared to controls (Fig. 4) (Supplementary Fig. 3).
3.4. Comparative analysis between HIV and EC The gene expression analysis showed that 104 and 96 genes were significantly upregulated in HIV and EC respectively, while 57 and 56 were significantly downregulated in HIV and EC respectively, as compared to healthy (Supplementary Fig. 4A and B). Among the upregulated genes, 93 were common between HIV and EC, 3 were characteristic of EC (CXCL6, IFNA16, and IFNB1) and 11 characteristic of HIV (CCL2, CCL8, CCR4, CXCR6, HLA-DOB, HLA-DRB1, IFNG, IL15RA, IL2RA, IL2RG, TGFA). Among the downregulated genes, 52 were common to HIV and EC, 4 were characteristic of EC (CXCL13, CXCL3, IL7 and TBX21), and 5 were characteristic of HIV (CCL24, IFNA1, IL11RA, IL5RA, TGFB1L1) (Fig. 5A and B). Principal Component Analysis revealed an almost complete overlap in the phenotypic characteristics of HIV and EC (Fig. 5C). The genes that differed significantly between the two groups were only three, LAG3, GATA3 and HLA-A. (Fig. 5D). GATA3 levels in EC were significantly higher than those in HIV, while reduced expression levels in EC vs. HIV were observed for both LAG3 and HLA-A. Gene Constellation Networks were constructed for LAG3, GATA3 and HLA-A in order to identify functionally correlate genes (Supplementary Fig. 5). 12 genes resulted correlated to LAG3
among those significantly modulated during HIV infection. These included ICOS, chemokines (CXCL11, CCL13, CCL8, CCL14), cytokine receptors and associated molecules (IL12RB1, IL21R, IL1RAPL2, IL18BP, IL2RA), and HLA genes (HLA-DOA, HLA-C). GATA3 was associated to 61 molecules, including cytokines (IL1RN, IL4, IL5, IL9, IL10, IL12A, IL13, IL17C, IL17D, IL18, IL32, TGFB2) and granzymes (GZMA, GZMB, GZMK, GZMM). HLA-A was associated to 70 genes, which included, besides molecules belonging to the Immunological Synapse, several chemokines (CCL2, CCL3, CCL5, CXCL9 and CXCL11).
4. Discussion In this study, we tried to define the immunological profile of high viremic HIV patients and EC in comparison to uninfected subjects. Surprisingly, analysis of the data showed an almost complete overlap between the HIV-infected and EC patients, which cannot easily explain the different responses to HIV infection of these two group of patients. We have found that HIV patients and the EC showed a upregulation of the Th1 pro-inflammatory cytokines IL1B, IL8, IFNc and IL18 but not IL6 and TNF-alpha, compared to the controls. Another cytokine highly expressed during HIV infection was IL10, which provides an effective autoregulatory mechanism that counteract the excessive inflammation in chronic infections (such as TB, HIV and malaria) [30]. It was recently observed that IL-10 contributes to a reversible T-cell dysfunction in HIV infected persons, and that blockade of the IL-10 pathway is able to increase HIV-specific CD4 and CD8 T-cell proliferation, and effector T-cell functions [31].
Fig. 5. Upregulated and downregulated gene expression in HIV, EC and Healthy. (A and B) Schematic representation of significantly upregulated and downregulated gene in HIV, EC and Healthy; (C) Scatter plot of the first three components of PCA of EC, HIV and Healthy; (D) GATA3 was significantly more expressed in EC compared to HIV and Healthy. HLA-A was significantly more expressed in HIV compared to EC and Healthy; LAG-3 was significantly more expressed in HIV compared to EC and Healthy.
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Among the other cytokines significantly modulated, we have surprisingly identified IL28B, which resulted downregulated in HIV and EC compared to healthy controls. IL28B (interferon IFN l3) produces an antiviral state by triggering a cascade through the JAK-STAT pathway that up-regulates the IFN-stimulated genes (ISGs). The effects of IL28B are similar to those of IFN-a and -b; however, IL28B binds to a distinct receptor that may up-regulate a different set of ISGs [32]. This cytokine has been identified as a key modulator of the immune response to hepatitis C virus (HCV), because a single-nucleotide polymorphism (SNP) (rs12979860) upstream of the IL28B gene was associated with spontaneous and treatment-induced HCV clearance [33,34]. Rallón NI et al. have shown that the IL28B CC genotype is a strong predictor of virological response to therapy in HIV/HCV-coinfected patients. Therefore, the IL28B downregulation in HIV and EC may be a control mechanism adopted by the virus to escape to the ISGs immune control. Interestingly, also the IL8R resulted downregulated in HIV and EC patients. There is a not large literature on IL8R and HIV and the few information are not exhaustive [35,36]. It can be assumed that the reduction of IL8R is a way to reduce the CD4+ T cell chemoattraction capacity in order to block recognition mechanisms from CD8+ T cells [37]. As regards chemokines, the complex pattern of modulation of these molecules gives an idea of the immunological tangle triggered by virus infection. CCL2 is a pro-inflammatory chemokine that is induced during several human acute and chronic viral infections. In HIV-1 infection [38] the significant increase in CCL2 has
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been associated to the effects of virus-derived proteins, such as gp120 [39], Nef [40], matrix protein p17 [41] and transactivator protein Tat [42,43], thus suggesting the immunomodulatory capacity of these molecules which promote HIV/AIDS pathogenesis. Other chemokines upregulated were CCL3 (MIP1a) and CCL4, that are natural ligands for the primary human immunodeficiency virus type 1 (HIV-1) co-receptor CCR5 and are also known to activate and enhance the cytotoxicity of natural killer cells [44]. The cognate ligands of CCR5 co-receptor, CCL3 (MIP-1a), CCL4 (MIP-1b) and CCL5 (RANTES) are typically produced by CD8+ T cells and have been shown to inhibit infection with R5 HIV-1 strains [45]. As regard chemokine receptors, we observed a significant upregulation of CCR6. Interestingly, CCR4(+)CCR6(+) and CXCR3(+)CCR6 (+) T cells exhibit gut- and lymph node-homing potential and are highly permissive to HIV replication, with the potential to infiltrate and recruit more CCR6(+) T cells into anatomic sites of viral replication [46]. In our study, we focused attention also on genes involved in the constitution of the immunological synapse. The HLA class I genes resulted significantly upregulated in HIV and in EC compared to the control. Interestingly, when comparing high viremic HIV patients and EC, only HLA-A appeared to be significantly downregulated in EC. The potential contribution of HLA-A alleles to viremic control in chronic HIV type 1 (HIV-1) infection has been relatively understudied compared with HLA-B. It has been demonstrate that HLAA⁄7401 is associated with lower viral loads and higher CD4+ T cell
Fig. 6. Graphical representation of CD4+ T cells in HIV. The synapsis representation of CD4+ T cell HIV infected and polarizing gene expression. Gene expression values are color coded from bright red (most upregulated) to dark blue (most downregulated). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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counts in several southern African cohorts [47]. Therefore, the significant downregulation observed in EC compared to HIV could be due to the different viral load. The ability of EC to control the HIV-1 virus replication in CD4 infected cells could explain the HLA-A reduction in the cells surface. The HLA-A molecules may be involved in restricting HIV replication and the reduction of these molecules could be explain the inhibition of CD4 killing by CD8 (cytotoxic) T lymphocyte. Unexpectedly, analysis of expression for HLA class II genes revealed that HLA-DP, HLA-DQ and HLA-DR were significantly upregulated in HIV and EC compared to the Healthy. In a recent publication, authors showed that certain HLA class II alleles are associated with HIV control, while others are associated with rather rapid disease progression In particular, they found that HLADRB1⁄15:02 is significantly associated with low viremia, while HLA-DRB1⁄03:01 is significantly associated with high viremia. Of note, a subgroup of HLA-DRB1 variants linked with low viremia showed the ability to present a larger breadth of peptides with lower functional avidity when compared to HLA-DRB1 variants linked with high viremia [48]. The action of HLA-class II expressed in CD4 + T cells could also explain the formation of cell syncytia resulting in infection of uninfected CD4+ T cell. In the past indeed, it has already been demonstrated the HLA-DR fundamental role in the formation of HIV syncytia cell [49]. Therefore, one might assume that a CD4+ T cell HIV infected could be recognized through HLA class I by CD8+ T cell and recognized trough HLA class II by CD4+ T cell not yet infected. In addition to it, the upregulation of syncytial molecules like LAG3, CTLA4, CD28 and CD3, assist the formation of syncytia with APC cells (Fig. 6). The significantly upregulation of LAG3 in HIV vs EC, could be then explained with the reduction of immunoactivation in EC patients. It has been shows that LAG3 expression is associated as an inhibitory marker and in immune suppression [50,51]. The EC ability to control the HIV-1 virus replication could be explain by the immuno-escape reduction. Exists an inverse correlation between LAG3 expression and HIV viral load [52]. This evidence is in accordance with our results. The LAG3 downregulation could be an effect of HIV viral load reduction and may results in an increase of infected cells recognition. As regard the significant upregulation of GATA3 in EC vs HIV patients, we hypothesized that the reduction of immunoactivation increase the TFs like GATA3 important for T cell development, homeostasis, activation, proliferation, and effector functions, all conditions needed in EC CD4 T cells. In conclusion, T-cell repertoire dysfunction characterizes HIV infection, but the pathogenic processes underlying it remain unclear. Disease progression is probably due to a profound dysregulation of Th1, Th2, Th17 and Treg patterns, however the superimposable features between high viremic individual and EC do not allow for the precise characterization of the mechanisms of viral replication, immune evasion and immune system viral control. Conflict of interest The authors declare that they have no conflict of interests. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.cyto.2016.04.007. References [1] M.S. Gottlieb, J.E. Groopman, W.M. Weinstein, J.L. Fahey, R. Detels, The acquired immunodeficiency syndrome, Ann. Int. Med. 99 (2) (1983) 208–220. [2] A.S. Fauci, Multifactorial nature of human immunodeficiency virus disease: implications for therapy, Science 262 (5136) (1993) 1011–1018.
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