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Monocyte and CD4+ T-cell antiviral and innate responses associated with HIV-1 inflammation and cognitive impairment

Sharma, Vishakhaa,b; Bryant, Christopherc; Montero, Mariaa,b,∗; Creegan, Matthewa,b; Slike, Bonniea,b; Krebs, Shelly J.a,b; Ratto-Kim, Silviaa,b,†; Valcour, Victord; Sithinamsuwan, Pasirie; Chalermchai, Thepf; Eller, Michael A.a,b; Bolton, Diane L.a,b; on behalf of the SEARCH007/SEARCH011 Study Groupsf

Author Information
doi: 10.1097/QAD.0000000000002537



HIV-1 associated neurocognitive disorder (HAND) occurs in 40–70% of HIV-1 chronically infected individuals (16 million people), and can persist despite complete suppression of plasma HIV-1 viremia by combination antiretroviral therapy (cART) [1–4]. Currently, few therapies exist beyond cART to treat HAND [5]. Mechanisms that give rise to HAND and underlie its persistence even during suppressive cART are unclear. Although severe HIV-1 central nervous system (CNS) dysfunction is associated with extensive HIV-1 replication in the cerebrospinal fluid (CSF) [6–10], impairment has also been reported in the absence of CSF viremia [11–13]. Thus, additional processes are likely involved in the development and progression of HAND and may present opportunities for therapeutic intervention.

Many markers of systemic immune activation and inflammation commonly produced by monocytes persist during HIV-1 infection, despite effective therapy, including increased levels of CSF and serum neopterin, and plasma soluble (s)CD163, IP-10 (CXCL10), and MCP-1 (CCL2) [14–19]. Multiple lines of evidence suggest these and other inflammatory markers contribute to HAND [20–22], including an association between monocyte activation and CSF inflammation in cART-treated individuals [16]. Other cell types, however, are also impacted by infection and may play a role in neuropathogenesis. CD4+ and CD8+ T-cell activation is associated with HAND, CSF CD4+, and CD8+ T cells are activated during chronic infection, and T-cell tropic HIV-1 replicates in CSF [23–27]. Given the increased permeability of the blood--brain barrier during chronic infection [28–30], studies of these blood cell populations during untreated infection may reveal processes associated with cognitive dysfunction.

To better understand immune cell perturbations during HIV-1 infection and HAND that may play a role in pathogenesis, we assessed phenotypic and transcriptional changes in blood monocytes and CD4+ T cells in a cohort of infected and uninfected neurologically well characterized Thai individuals. Prior studies of this and a similar cohort found no association between cognitive status and standard clinical or virologic measures, including plasma viral load and CD4+ T-cell count but did identify associations with plasma and CSF neopterin [31–33]. We hypothesized that cellular activation, inflammatory gene responses, and infected cell burden contribute to HIV-1-associated inflammation and neurocognitive impairment during untreated infection.


Participant selection and specimen collection

Nineteen cART-naïve participants from the Thai Red Cross SEARCH011 cohort (NCT00782808) with chronic HIV-1 infection classified as either cognitively normal or with HAND [32] and prior HIV-1 DNA assessment were selected for analysis [34] (Table 1). All participants with confounding or contributing factors were excluded at entry as described in Supplementary Text S1, Peripheral blood mononuclear cells (PBMC) were isolated and cryopreserved spanning 2009–2011 as previously described [32]. Plasma and CSF levels of neopterin, IP-10, MCP1, sCD163 (n = 12), and sCD14 were measured by multiparameter or standard ELISA assays, as previously described [31]. Ten seronegative, healthy age-matched, and gender-matched Thai volunteers from the SEARCH007 cohort (NCT00777426) served as controls [35].

Table 1
Table 1:
Clinical characteristics of SEARCH011 (HIV+) and SEARCH007 (uninfected control) participants.

Flow cytometry and cell sorting

Cryopreserved PBMCs were thawed and directly stained with fluorescent conjugated antibodies specific for monocyte and lymphocytic lineage markers described in Supplemental Text, Briefly, 5–7 million cells were stained with LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific, Waltham, Massachusetts, USA), washed, and surface stained with antibodies. Viable monocytes and CD4+ T cells (Supplemental Figure 1, were sorted on a 5-laser FACS Aria II SORP (BD Biosciences, San Jose, California, USA: ∼98% purity) directly into a 96-well PCR plate at 1000 cells per well in six replicates and lysed immediately.

cDNA synthesis and quantitative gene expression

cDNA was prepared and quantitative PCR (qPCR) gene expression data was analyzed as described in Supplemental Text S1, Multiplex RT-qPCR was performed on a Fluidigm BioMark HD per manufacturer's instructions [36–38]. The 96-gene panel was selected based on prior reports of involvement in monocyte activation, adhesion, and transmigration as well as antiviral activity (Table S1, [39–44].

Statistical analysis

Statistical analysis of flow cytometry data was performed using JMP (v. 12, SAS Institute Inc., Cary, North Carolina, USA), and gene expression analysis was performed in R v3.2 (R Foundation, Vienna, Austria). Differential protein expression between study participants was determined by Student's t-test. Median host gene expression was computed for each diagnosis group, and gene expression distributions were compared between groups using nonparametric Mann--Whitney U tests. Concentrations of cells positive for HIV-1 transcripts, gag and env, were estimated using an adapted maximum likelihood approach described previously (Supplemental Text S1, [45]. Spearman rank-order correlations were estimated between gene expression and biomarkers of interest. Gene set enrichment was performed using DAVID ( [46]. Principal component analysis was performed as an exploratory approach to assess gene expression patterns that might be shared within a diagnosis group. P values were not adjusted for multiple comparisons in any of the analyses as this is a small-sample, hypothesis-generating analysis. Significance thresholds of P = 0.05 and P = 0.001 were considered as indicators of moderate and strong evidence of a true difference or association, respectively.


Monocyte frequency and phenotype in chronic HIV and HIV-associated neurocognitive disorders

The 19 HIV-1-infected participants were on average 38 years old, 42% women, with an average viral load of 1.8E5 copies/ml and average CD4+ cell count of 272 cells/μl (Table 1). Ten participants were classified as cognitively normal whereas nine exhibited HAND based on a battery of cognitive tests and applying 2007 Frascati criteria [47–50]. There was no significant difference between cognitively normal and HAND with regard to age, viral load, or CD4+ cell count (all P > 0.48 Mann—Whitney U test). There was a significant difference in the distribution of male and female participants between cognitively normal (20% women) and HAND (67% women) (P = 0.04, chi-square test).

To assess perturbations in mononuclear cells during HIV-1 infection and HAND, we examined monocyte and CD4+ T-cell frequency and phenotype in uninfected, cognitively normally infected, and HAND-infected individuals. As previously reported [51,52], the distribution of monocyte subsets differed between uninfected and infected individuals. The frequency of intermediate CD14+CD16+ monocytes was higher during infection, median 11 vs. 5% (P < 0.001), whereas classical CD14+CD16 monocytes were diminished (72 vs. 80%, P = 0.04) (Fig. 1a--c). The nonclassical subset (CD14CD16+) remained unchanged. These findings are in line with major shifts in the relative abundance of monocytes during chronic HIV-1 infection, purportedly because of ongoing immune activation and inflammation [53]. CD4+ T cells were dramatically reduced (P < 0.001) (Supplemental Figure 2a,

Fig. 1
Fig. 1:
Relative abundance and activation phenotype of monocytes during chronic HIV-1 infection and HIV-associated neurocognitive disorders.

As immune activation is a hallmark of disease progression in HIV-1 infection, we examined expression of several surface activation markers. CD169, a monocyte activation and adhesion marker, was markedly increased on monocytes of HIV-1-infected individuals (P < 0.001, Fig. 1d, Supplemental Figure 2b, [54,55]. Monocyte expression of CD86 (P = 0.03) and HLA-DR was also greater (P = 0.05, Fig. 1e--f, Supplemental Figure 2c and d,, whereas CD163 remained unchanged (Fig. 1g, Supplemental Figure 2e, The increase in CD169 was observed for all three subpopulations of monocytes: classical (P < 0.001), intermediate (P < 0.001) and nonclassical (P = 0.01) (Supplemental Figure 2f, CD86 and HLA-DR did not differ between subpopulations of monocytes (data not shown). CD4+ T-cell activation, as assessed by HLA-DR expression, was also increased (P = 0.001, Fig. 1h Supplemental Figure 2g,

To identify determinants of cognitive impairment, immunologic profiles from the HAND and cognitively normal HIV-1-infected individuals were compared. Distribution of the monocyte subsets did neither differ by cognitive status nor did monocyte expression of CD86 or HLA-DR (Fig. 1a--f). CD4+ T-cell frequency and activation was also similar (Fig. 1h, Supplemental Figure 2a, However, CD163, an anti-inflammatory scavenger receptor, and CD169, showed evidence of differing by cognitive status. Monocyte surface CD163 expression approached lower levels in HAND compared with cognitively normal (P = 0.06, Fig. 1g, Supplemental Figure 2e,; and expression among HAND, but not cognitively normal, patients was diminished relative to uninfected individuals (P = 0.02). Intermediate and classical monocytes exhibited the greatest difference in CD163 expression between HAND and cognitively normal (P = 0.04 and P = 0.07, respectively), as well as between HAND and uninfected (P = 0.15 and P = 0.04, respectively) (Fig. 1i). CD163 expression by nonclassical monocytes did not differ across study groups. No association between monocyte surface expression of CD163 was observed with plasma levels of sCD163 (n = 12). Monocyte CD169 surface expression was modestly increased in HAND versus cognitively normal (P = 0.10, Fig. 1d, Supplemental Figure 2b, This trend was also apparent in classical (P = 0.17) but not intermediate or nonclassical monocytes (Supplemental Figure 2f--h,

Gene expression profiles in monocytes and CD4+ T cells in chronic HIV

To identify transcriptional signatures associated with HIV-1 infection and HAND, expression of 96 genes involved in cellular activation, adhesion, transmigration, and antiviral activity was measured in monocytes and CD4+ T cells by multiplex qPCR [39–44]. Comparing monocytes from HIV-1-infected and uninfected individuals, 45 genes were differentially expressed (P < 0.05, uncorrected for multiple comparisons, unless otherwise noted): 41 upregulated and four downregulated (Fig. 2a). Among these, 17 genes, ANKRD22, CCL2, CMPK2, CXCL10, CXCL11, GBP1, IFI44, IFIT1, OAS1, OAS2, OASL, RSAD2, SLAMF7, USP18, VCAM1, XAF1, and ZBP1 exhibited at least four-fold difference between group medians (P < 0.001) (Fig. 2b). A similar analysis of CD4+ T cells yielded 49 differentially expressed genes (P < 0.05, Fig. 2c). As with monocytes, the vast majority were upregulated in infection. The nine genes that differed by at least four-fold (P < 0.001), CMPK2, IFI44, IFIT1, OAS1, OAS2, OASL, RSAD2, USP18, and XAF1 (Fig. 2d), overlapped with those observed in monocytes.

Fig. 2
Fig. 2:
Differential inflammatory gene expression in monocytes and CD4+ T cells during chronic HIV-1 infection.

Of the 45 genes differentially expressed in monocytes, 30 were shared with CD4+ T cells, whereas 15 were unique to monocytes (Fig. 2e). Functional annotation of the unique monocyte genes identified intercellular adhesion, malarial response, and cellular response to tumor necrosis factor (TNF) as upregulated processes. In CD4+ T cells, lymphocyte adhesion, monocytes surface markers, and leukocyte migration were uniquely upregulated. Pathways that were upregulated in both monocytes and CD4+ T cells included antiviral defense and IFNγ-mediated signaling pathways. Thus, both monocytes and CD4+ T cells undergo substantial changes in their transcriptional program during untreated chronic HIV-1 infection characterized by upregulation of many genes involved in immune response mobilization and antiviral activity.

Gene programs associated with cognitive impairment

Comparing the gene expression profile of HAND and cognitively normal HIV-1-infected individuals, two proinflammatory activation genes, STAT1 and EMR2, were modestly decreased in monocytes from individuals with cognitive impairment (both 1.4-fold, P = 0.02, and P = 0.04 respectively, Fig. 3a and b). Principle component analysis of the CD4+ T-cell gene expression data identified clusters of cognitively normal and HAND patients, barring two outliers (Fig. 3c and d). Principal component 1 (PC1) primarily described the difference between HAND and cognitively normal patients, albeit at a marginal significance level (P = 0.07) and reaching significance with outliers removed (P = 0.03) (Fig. 3c and d). The PC1 decrease was attributed largely to the proinflammatory genes RPL14 and FOS with the highest coefficients of 27.6 and 15.6, respectively. FOS trended mildly upregulated in HAND vs. cognitively normal (1.5-fold, P = 0.1, uncorrected FDR), while RPL14 did not differ by cognitive status. These data suggest that a diminished proinflammatory state of monocytes and CD4+ T cells is associated with cognitive impairment in chronic HIV-1.

Fig. 3
Fig. 3:
Gene expression differences associated with HIV-1-related cognitive impairment.

Gene programs associated with in-vivo inflammatory markers

To explore the relationship between leukocyte gene expression profiles and inflammation, transcript levels were compared with two common clinical markers of inflammation in HIV-1 pathogenesis, plasma neopterin, and soluble CD14 (sCD14), as well as inflammatory markers, IP-10, MCP-1, and sCD163, all produced primarily by monocytes. Monocyte expression of several genes was positively correlated with neopterin, sCD14, MCP-1, and IP-10 (Fig. 4a, P < 0.05). Many of these genes are involved in antiviral responses and TNF-signaling pathways (e.g. IFIT1, IL6, HS3ST3B1, NKG7, OAS1, OAS2, OASL, RSAD2, IFI16, GBP1, CXCL10, and XAF1). Few genes (e.g. ICAM1) were negatively correlated with the inflammatory markers. Surprisingly, CD4+ T-cell gene expression was also highly correlated with the monocyte inflammation markers and all correlations were positive (P < 0.05). Many correlations were shared between the markers. Antiviral defense and type I interferon signaling were common pathways represented among these genes, with strongest associations observed for ANKRD22, IFI44, IFIT1, and USP18 (P < 0.01). These data indicate that the transcriptional profiles of both monocytes and CD4+ T cells are associated with chronic infection inflammation.

Fig. 4
Fig. 4:
Monocyte and CD4+ T-cell transcriptional profiles associated with in-vivo inflammatory markers in HIV-1 infection and HAND.

Although levels of plasma sCD14 and neopterin did not differ by cognitive status in the participants selected for this study, we examined associations of these inflammation markers with gene expression in the HAND and cognitively normal subgroups to explore mechanisms of inflammation stratified by cognitive status. Gene correlates of inflammatory protein markers were more prominent among cognitively normal than HAND individuals (Fig. 4b). Combining monocyte and CD4+ T-cell data, 32 genes in our panel were correlated with the soluble markers in HAND; 16 of which were correlated with MCP-1. Among the cognitively normal, 43 genes were correlated with the inflammation markers, the majority of which were correlated with neopterin and sCD14. These data suggest that in general, innate gene programs exhibit different patterns of association with inflammation in HAND and cognitively normal individuals.

Some associations were unique to the HAND subgroup. Monocyte expression of PVRL2 and STAT1 was positively correlated with neopterin levels in HAND but not cognitively normal, whereas HBA2, IL6, and SELL were correlated with sCD14; unique associations were also observed for IP-10 and MCP-1 (Fig. 4b). Negative associations included multiple adhesion molecules in monocytes: CD13, ICAM1, OLR1, and SOD2 were negatively correlated with sCD14 in HAND only. CD4+ T-cell gene correlates of inflammatory markers unique to the HAND subgroup were limited primarily to MCP-1 levels. Twelve genes in CD4+ T cells and monocytes were correlated with MCP-1 in HAND but not cognitively normal. SPTLC2 and SELL expression were correlated with sCD14 in HAND; CXCL10 was negatively correlated with sCD163. Altogether, fewer genes were correlated with neopterin and sCD14 during HAND, more genes were correlated with MCP-1.

Infected cell frequency in HIV-associated neurocognitive disorders and cognitively normal infection

To determine whether HIV-1 infection of monocytes or CD4+ T cells is associated with neurocognitive impairment, we estimated the frequency of cells harboring viral nucleic acid. HIV-1 qPCR assays were employed to distinguish between: productive infection, as defined by the presence of spliced env viral RNA (vRNA); and genomic RNA-positive cells, which represent a broader class of infected cells that are not necessarily productive, as assessed by gag. The frequency of gag vRNA+ cells (CD4+ T cells or monocytes) did neither differ between HAND and cognitively normal participants (Fig. 5a), nor did env vRNA+ CD4+ T cells (Fig. 5b). env vRNA+ CD4+ T cells were detected in 86% of cognitively normal participants, but only in 38% of HAND participants, despite sampling a similar number of cells, suggesting fewer productively infected CD4+ T cells in HAND. No viral gene expression (env) was observed in monocytes. As expected, infected CD4+ T cells as assessed by both the gag and env assays were correlated with viral load (ρ = 0.68, P = 0.009 and ρ = 0.58, P = 0.02, respectively, Fig. 5c and d) and with each other (ρ = 0.58, P = 0.03, Fig. 5e). The positive correlations are consistent with circulating infected CD4+ T cells contributing to plasma viremia.

Fig. 5
Fig. 5:
Infected cell frequency and relationship to viral load, cognitive status, and host gene expression.

We explored the relationship between infected cell abundance and cellular activation. The frequency of gag vRNA+ CD4+ T cells was positively correlated with CD4+ T-cell expression of CASP1, CD13, and DIO3 (Fig. 5f), consistent with induction of a caspase-1-mediated proinflammatory process [56]. Protein surface markers of activation were not correlated with infected CD4+ T-cell frequency. Overall, we observed robust CD4+ T-cell infection, which associated with both plasma viremia and inflammation, but no evidence that peripheral infected cell frequency is associated with HAND within this cohort.


We describe transcriptional and phenotypic properties of monocytes and circulating CD4+ T cells in cognitively normal and impaired chronic HIV-1 infection and healthy uninfected individuals. As expected, several activation markers were upregulated during HIV-1 infection: CD169, CD86, and HLA-DR on monocytes and HLA-DR on CD4+ T cells. Genes involved in antiviral type I interferon responses, cell migration, and activation were also upregulated in both monocytes and CD4+ T cells. Plasma markers of inflammation, neopterin, and sCD14, were associated with expression of these genes in both monocytes and CD4+ T cells. In HAND, monocyte surface CD163 expression was diminished relative to healthy donors and cognitively normal infection, particularly among classical and intermediate monocytes, while CD169 trended higher relative to cognitively normal individuals. Host and viral gene expression profiling generally did not distinguish HAND from cognitively normal status. However, gene expression correlates of soluble markers of inflammation neopterin, sCD14, and MCP-1 differed between HAND and cognitively normal individuals, which may speak to dysregulated mechanisms that link innate gene programs and inflammation in cognitive impairment.

Our findings are consistent not only with monocyte activation in chronic HIV-1 infection contributing to inflammation and disease progression [57] but also highlight a previously unappreciated role for CD4+ T cells. In addition to the many proinflammatory factors upregulated in monocytes during HIV-1 infection described [58–63], we report increased expression of several additional genes functioning in interferon signaling and innate immunity, such as ANKRD22, CMPK2, GBP1, IFI44, IFIT1, USP18, XAF1, and ZBP1, several of which were also upregulated in CD4+ T cells. Clinical markers of inflammation (sCD14, neopterin, and MCP-1) were correlated with both monocyte and CD4+ T-cell transcriptional profiles. For monocytes, antiviral, and TNF signaling response genes were correlated with inflammation, whereas type I interferon signaling and antiviral defense genes were correlated for CD4+ T cells. In addition, infected CD4+ T cells were correlated with T-cell expression of two proinflammatory genes, CASP1 and CD13, suggesting that viral replication contributes to CD4+ T-cell proinflammatory responses.

HAND and cognitively normal infected individuals were distinguished by several novel features. Diminished surface CD163 on monocytes of HAND patients may result from increased CD163 shedding, giving rise to greater soluble CD163 as previously reported in HAND [64,65]. Inflammation in HAND may facilitate this process as proinflammatory factors promote surface CD163 cleavage [66]. The importance of CD163 in HAND is further supported by reduced neurological abnormalities following normalization of plasma sCD163 by ART [19,66,67]. The trend of increased monocyte surface CD169 expression, a proinflammatory adhesion molecule upregulated during HIV-1 infection [54,55,68,69], may implicate monocyte trafficking into the CNS across the blood--brain barrier in HAND. However, infected monocytes or CD4+ T cells, as assessed by cell-associated spliced or unspliced viral RNA, did not correlate with HAND status, despite prior evidence of monocyte HIV DNA varying with cognitive impairment [32]. Possible explanations for these discordant results include differences in monocyte isolation methods that vary in cell purity, analysis of RNA versus DNA, and consideration of HAND stratifications in the analysis.

Modest transcriptional downregulation of inflammatory response potentiators, STAT1 and EMR2, observed in monocytes of HAND patients, in conjunction with the heightened activation reflected by CD163 and CD169, indicates a potentially dysregulated monocyte status. Chronic type I interferon stimulation impairs monocyte function during high-level HIV-1 viremia [63], a phenomenon that may be exacerbated in HAND because of decreased STAT1 and EMR2. A possible mechanism for reduced STAT expression is a negative feedback loop involving CD169 upregulation in response to interferon signaling followed by CD169-mediated inhibition of STAT1 signaling [70]. EMR2, a myeloid-restricted member of the adhesion family of G protein-coupled receptors, mediates inflammatory cytokine production, whereas functional nucleotide polymorphisms in EMR2 have been associated with major depression, a condition prevalent in HAND [71,72]. Diminished EMR2 in HAND may thus impair inflammatory responses and contribute to neurological disorders. Furthermore, fewer proinflammatory genes were correlated with soluble markers of inflammation in HAND than among cognitively normal, suggesting a decoupling of monocyte gene and protein inflammatory responses in HAND. Of note, proinflammatory genes, such as STAT1 have been hypothesized to be neuroprotective [73,74], and thus, may directly or indirectly limit risk of HAND.

Overall, our data support a model wherein both monocytes and CD4+ T cells exhibit a highly activated profile in chronic HIV-1 infection and contribute to a persistent state of inflammation. We observed increased expression of many genes involved in type I interferon and antiviral responses as well as positive correlations between inflammatory gene expression and soluble markers of inflammation. However, mechanisms underlying HAND remain less clear. Elevated monocyte surface CD169 and diminished CD163, indicating greater activation in HAND, is contrasted with dampened monocyte expression of proinflammatory genes, suggesting monocyte activation may be dysregulated in HAND. The extent to which these findings, derived from therapy-naïve individuals, applies to cART-treated individuals with HAND is unknown and requires further investigation. Future studies assessing the entire cellular transcriptome and encompassing cells in the CNS in both cART-naïve and cART-treated individuals will extend these findings.


We thank the SEARCH007/11 study members, Yotin Chinvarun, James L.K. Fletcher, Somporn Tipsuk, and SEARCH nurses Duanghathai Suttichom and Somprartthana Rattanamanee. We thank Andrey Tokarev, Kier Om, and Ming Dong (USMHRP) for input and technical support. This work was supported by a cooperative agreement (W81XWH-07-2-0067) between the Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., and the US Department of Defense (DoD). The views expressed are those of the authors and should not be construed to represent the positions of the US Army, the DoD, or the Department of Health and Human Services.

Author contribution: V.S., S.J.K, S.R-K., V.V., and D.L.B. designed the study. P.S. and T.C. managed participant recruitment and clinical assessments. V.S., M.M., M.C., and B.S. executed experiments. V.S., S.J.K., M.A.E., C.B., and D.L.B. interpreted and analysed data. V.S. and D.L.B. wrote the manuscript.

Conflicts of interest

There are no conflicts of interest.


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Present address: PerkinElmer Spain, Ronda de Poniente 19, 28760 Tres Cantos, Spain.

Present address: International Vaccine Institute, Seoul, South Korea.


antiviral response; CD163; CD4+ T cells; cell-associated viral RNA; gene expression; HIV-1 associated neurocognitive disorder; HIV-1; monocytes; phenotype

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