Despite viral suppression and immune reconstitution with combination antiretroviral therapy (cART), neurocognitive impairment (NCI) remains a clinical concern in people living with HIV (PLWHIV).1 Mechanisms leading to NCI during HIV infection are probably multifactorial, but HIV-related factors, such as baseline HIV-RNA, years with HIV, and most prominently, lower nadir CD4+, have been identified as risk factors.2–6 Other important risk factors are advanced age, cardiovascular risk markers, and immune activation.4,7–11
Most PLWHIV are coinfected with cytomegalovirus (CMV), a β-herpes virus that establishes latent infection with frequent asymptomatic reactivations.12 CMV coinfection has been associated with inflammation, immune activation, and non-AIDS comorbidities such as cardiovascular and cerebrovascular diseases.13–26 Both CMV infection itself and increased immune response against CMV has been associated with cognitive impairment in elderly HIV-uninfected populations,27–30 and although the direct effect of CMV in the central nervous system remains controversial,31,32 some studies suggested a relationship between CMV and risk of Alzheimer disease.33–35 Furthermore, it has been found that CMV-IgG levels were associated with NCI in treated HIV infection21,36 suggesting that CMV coinfection may affect the risk of adverse neurocognitive outcomes in PLWHIV.37 However, studies are sparse, and no previous studies have investigated the relationship between cellular CMV-specific immune responses and NCI in PLWHIV.
Given the potential role of CMV on adverse neurocognitive outcomes in HIV infection, we hypothesized that CMV-specific humoral and cellular immune responses would be associated with NCI in treated HIV infection. To explore this hypothesis, we assessed NCI and CMV-specific immune responses in a cross-sectional cohort of PLWHIV on stable cART with low comorbidity and in a HIV-uninfected control group matched on age, sex, education, and comorbidity.
Sixty-one PLWHIV treated with cART ≥2 years before inclusion and with median HIV-RNA at 19 copies per milliliter [inter quartile range (IQR) 19–20] were included. All patients had HIV-RNA <500 copies per milliliter for ≥1 year before inclusion, and this cutoff was chosen to allow viral blips. Three patients had one measurement above 50 copies per milliliter. Patients were recruited from the Department of Infectious Diseases, University Hospital of Copenhagen, Rigshospitalet, in a study regarding cognitive function and cardiovascular risk profile.38–41 Thirty-one HIV-uninfected individuals matched for age, sex, education, and comorbidity were included as controls.38–41 Nineteen of those also participated in a study on diabetes.42 Exclusion criteria were acute illness, chronic infection with hepatitis B virus or hepatitis C virus, previous or current intravenous drug use, autoimmune disease, cancer, or pregnancy,38 and participants with a history of severe head injury, cerebral insult, opportunistic CNS infection, psychiatric disorders (apart from depression), diabetes, and any substance use disorder were excluded from the current study.
Detailed information of medical history, demographics, diagnosed depression, use of psychopharmacological drugs, and substance use disorder was obtained.38 High alcohol consumption was defined as >14/21 units/weeks for women/men according to Danish Health Authority guidelines. Comorbidity was graded by calculating the Charlson comorbidity index.43,44 Major depression inventory questionnaire was performed, and depression was defined as diagnosis of depression according to WHO/ICD-10 and/or treatment with antidepressants. HIV disease characteristics were recorded as preciously described.38
The study was approved by the National Committee on Biomedical Research Ethics for the Capital Region of Denmark (H-2-2010-089) and the Danish Data Protection Agency and conducted in accordance with the second declaration of Helsinki. Written informed consent was obtained from all participants.
Neurocognitive Functioning Assessments
All participants were tested with a neurocognitive test battery assessing 4 cognitive domains: executive functions, verbal generativity, verbal learning and memory, and speed of information processing.38,42 Verbal intelligence was assessed as a measurement of premorbid cognitive function as previously described (see Table 1, Supplemental Digital Content, http://links.lww.com/QAI/B177).38 All tests were performed by the same trained medical doctor.42 Test scores were transformed from raw scores to standard z-scores based on the mean and SD of the demographically comparable HIV-uninfected controls. Z-scores were then transformed into deficit scores ranging from no impairment (0) to severe impairment (5) (details in Table 1, Supplemental Digital Content, http://links.lww.com/QAI/B177) and averaged as a battery-wide summary score, the global deficit scale (GDS) score.45,46 After a conventional threshold and standard definition of NCI in PLWHIV, a GDS ≥0.5 was defined as NCI.45,47–49 Importantly, this cutoff is consistent with the international Frascati criteria for HAND.49,50 Neurocognitive domain-specific impairment was defined as a domain deficit score >0.5. GDS scores were used to provide additional information on the severity of NCI.
Blood was collected at the time of neurocognitive testing, peripheral blood mononuclear cells (PBMC) were isolated from heparinized blood samples and stored in liquid nitrogen, and serum and plasma were stored at −80°C until further analysis.38 As previously described in detail, plasma HIV-RNA was measured at inclusion, plasma concentrations of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) were measured using Meso-Scale Discovery MULTI-SPOT plate (MSD, Gaithersburg, MD), and T-lymphocyte subsets were determined using flow cytometry.38
Quantitative CMV-IgG Antibody Levels and Plasma CMV-DNA
As previously reported,51 serum CMV-IgG was measured using a commercial quantitative chemiluminescent immunoassay with a manufacturer-specified cutoff (negative <12.0 U/mL, positive >14.0 U/mL) (LIAISON CMV-IgG II; DiaSorin S.P.A., Saluggia, Italy),52 and concentration of CMV-DNA in plasma was measured with the Amplicor CMV Monitor test (Roche Diagnostics, Indianapolis, IN). To differentiate between primary and chronic CMV infection, CMV-IgG antibody avidity was measured with the LIAISON CMV Avidity II assay (DiaSorin S.P.A.).53,54
CMV-specific T-Cell Responses in PLWHIV
The method used for quantification of CMV-specific T-cell responses in PLWHIV has previously been described.51 In brief, PBMCs were stimulated with CMV-pp65 peptide pools [138 peptides, 65kDa-phosphoprotein (pp65)] (Swiss-Prot ID: P06725), CMV-gB peptide pools [224 peptides, Envelope-glycoprotein-B (gB)] (Swiss-Prot ID: P06473), or staphylococcal enterotoxin B (2.5 µg/mL; Sigma-Aldrich, St. Louis, MO) and incubated together with costimulatory anti-CD28/CD49d (1 µg/mL, BD Biosciences) for 6 hours at 37°C in 5% CO2 with addition of 1-µg/mL brefaldin A (BD Biosciences) after 2 hours. Background staining was determined by incubating unstimulated controls with dimethyl sulfoxide, anti-CD28/CD49d, and brefaldin A. After stimulation, PBMC were stained with BD Horizon Fixable Viability Stain 450 (FVS450), anti-CD4-FITC/anti-CD69-PE/anti-CD3-PerCP (clone-SK3/L78/SK7 BD fastimmune), anti-CD8-V500 (clone-SK1 BD Horizon), anti-IL-2-BV421 (clone-5344.111 BD Horizon), anti-TNF-α-APC (clone-6401.1111 BD FastImmune), and anti-IFN-γ-PE-Cy7 (clone-B27 BD Pharmingen). Fluorescence-minus-one controls were used in all staining. Cytokine responses were acquired immediately with BD FACSCanto II flow cytometer and analyzed using BD FACSDiva (v8.0.1) software (BD Biosciences). The gating strategy is depicted in Figure 1.A, Supplemental Digital Content, http://links.lww.com/QAI/B177; lymphocyte gate, a singlet gate, and a live/dead cell gate were applied before gating on CD3+CD4+ and CD3+CD8+ cells. Expression of IFN-γ, TNF-α, and IL-2 was then gated from activated (CD69+) CD4+ and CD8+ T cells. A combinational gating strategy was applied to obtain all functional subsets, and background staining was subtracted from all results. A positive response was defined as a background-subtracted response above 1/10,000 of CD4+ or CD8+ and at least 40 events. In each participant, at least 100,000 events were recorded. By summing up the frequency of CD4+ or CD8+ T cells within each unique function (IFN-γ, TNF-α, and IL-2), we analyzed the magnitude of total CMV-pp65– or CMV-gB–specific responses (%CD8+ and %CD4+), calculating each responding cell only once.
Differences in clinical characteristics and neurocognitive outcomes between PLWHIV and HIV-uninfected controls were assessed with Student t test or Mann–Whitney test for continuous variables and χ2 test or Fishers exact test were used for categorical variables where appropriate. Univariate and multivariable logistic models were used to test the association between CMV-specific immune responses and NCI in the total population and in PLWHIV alone. Unadjusted odds ratio (OR) and adjusted odds ratio (aOR) and 95% confidence intervals were reported. Covariates were selected based on clinical assumptions or known associations with NCI [HIV status (yes/no), age (per year), sex, education (per year decreasing), premorbid cognitive function (per 0.1 unit decreasing), depression (yes/no), smoking (yes/no), high alcohol consumption (yes/no), men who have sex with men (MSM) (yes/no), current use of Efavirenz (yes/no), comorbidity score ≥1 (yes/no), CMV seropositivity (yes/no), CMV-IgG (per 100 U/mL), IL-6 (per%), and TNF-α (per%)]. When analyzing PLWHIV alone, additional HIV-related factors (current CD4+ T cells, nadir CD4+, CD4+/CD8+ ratio, time living with HIV, time on cART, and CD8+ T-cell activation) and CMV-specific T-cell responses were included. Because of a small sample size and few events, a backward elimination selection approach was applied (selection criteria of covariates: P < 0.25 in univariate analysis and α = 0.2) to build basic multivariable models in the total population (including HIV, age, and premorbid cognitive function) and in PLWHIV alone (including CMV-specific CD4+ T cells, age, and premorbid cognitive function). Additional confounders were chosen based on associations in univariate analyses or study aims and were included one at a time in separate models or as interaction terms when appropriate. In addition, associations between CMV-IgG or CMV-specific T cells and the GDS score were investigated in multivariable linear regression models adjusted for age and premorbid cognitive function. False discovery rate (FDR, Benjamini–Hochberg method) adjusted P values were calculated to adjust for multiple testing when several cognitive domains were assessed. Otherwise, P values <0.05 were considered statistically significant. Analyses were performed using SAS (version 9.4 SAS Institute, Copenhagen, Denmark).
A total of 52 PLWHIV and 31 HIV-uninfected controls were included. PLWHIV had been on treatment with cART for a median of 7 years (IQR, 4–10) and had a median CD4+ T-cell count of 575 cells/µL (IQR, 420–720) (Table 1).38 As previously reported, PLWHIV and HIV-uninfected controls were demographically comparable (summarized in Table 1).38–40 However, 30.8% of PLWHIV had a depression on inclusion and/or were on antidepressive treatment compared with 3.2% of HIV-uninfected controls (P = 0.003). More PLWHIV were CMV-seropositive (90.4% vs. 64.3%, P = 0.004), and CMV-seropositive PLWHIV had higher CMV-IgG levels than CMV-seropositive HIV-uninfected controls [207 U/mL, IQR (119–528) vs. 111 U/mL, IQR (79–132), P = 0.003], whereas none of the participants had detectable CMV-DNA in plasma, and primary CMV infection was not detected.51
Factors Associated With NCI in PLWHIV
NCI was detected in 31% (n = 16) of PLWHIV as compared to 13% (n = 4) of HIV-uninfected controls (Table 1). Age (per year), education (per year less), premorbid cognitive function (per 0.1 unit decrease), IL-6 (per %), and comorbidity (score ≥ 1) were associated with NCI in univariate analysis, but HIV status was not (Table 2). However, after adjusting for age and premorbid cognitive function, PLWHIV had higher risk of NCI than HIV-uninfected controls [aOR 5.18 (1.15–23.41), P = 0.033] (Table 2), and the association remained significant when adjusting for comorbidity, IL-6, and CMV-IgG in separate multivariable models (Table 2).
Additional adjustment for MSM or current use of Efivarenz did not alter the results (data not shown). When including interaction terms, we found that higher IL-6 increased the association between HIV (p-interaction = 0.004) and NCI, whereas CMV-IgG (p-interaction = 0.146) did not (see Figure 2, Supplemental Digital Content, http://links.lww.com/QAI/B177).
The prevalence of depression was 25% in participants with NCI as compared to 19% in those without NCI (P = 0.542), and we did not find depression to be associated with NCI in univariate [OR 1.42 (0.40–4.52), P = 0.567] or multivariable analysis [aOR 0.73 (0.18–3.02), P = 0.668] after adjusting for HIV, age, and premorbid cognitive function. When analyzing the cognitive domains separately, PLWHIV had higher risk of impairment in speed of information processing [aOR 5.99 (1.13–31.60), P = 0.035], but after adjustment for multiple comparisons, the association was no longer significant (P = 0.088) (Fig. 1). No associations were found between CMV seropositivity and global or domain-specific impairment in the total population (data not shown).
In PLWHIV alone, we considered the same covariates in addition to current CD4+ T-cell count, nadir CD4+, CD4+/CD8+ ratio, time living with HIV, and CD8+ T-cell activation. Age, premorbid cognitive function, log IL-6, comorbidity, and lower CD4+ T cells (per 100 cells/μL) were associated with NCI in univariate analysis, but when adjusting for age and premorbid cognitive function, the association between log IL-6, comorbidity, and lower CD4+ T cells with NCI was no longer significant (Table 3).
Association Between CMV-IgG and Neurocognitive Function in PLWHIV
In the total study population, higher CMV-IgG was not associated with NCI, either in univariate analysis or when adjusting for HIV, age, and premorbid cognitive function [aOR 1.04 (0.78–1.39), P = 0.565] (Table 2). The same results were found in PLWHIV alone (Table 3). However, when considering severity of NCI in PLWHIV defined by the GDS score, lower premorbid cognitive function [β = −0.28 (−0.52 to −0.02), P = 0.038], lower education [β = −0.16 (−0.25 to −0.07), P = 0.001], lower CD4+ T cells [β = −0.15 (−0.31 to −0.01), P = 0.046], and higher CMV-IgG [β = 0.12 (0.01–0.22), P = 0.033] were associated with worse GDS scores in univariate analysis. In the multivariable linear model adjusting for age and premorbid cognitive function, higher CMV-IgG (per 100 U/mL) [β = 0.15 (0.06–0.23), P = 0.002] was still associated with worse GDS scores, also when adjusting for current CD4+ T cells or IL-6 in separate models (Table 4). Separate adjustments with other HIV-related factors including nadir CD4+ (P = 0.002), years living with HIV (P = 0.004), and years on cART (P = 0.002) did not alter the results. When individual domains were considered in univariate analysis, higher CMV-IgG (per 100 U/mL) was associated with worse deficit scores in speed of information processing [β = 0.20 (0.04–0.36), P = 0.019], whereas deficit scores in other domains were not associated with CMV-IgG, or could not be assessed because of a low number of individuals with scores indicating impairment (data not shown).
CMV-specific T cells and NCI in PLWHIV
In both univariate and multivariable analyses, higher CMV-specific CD4+ T-cell responses were associated with increased risk of NCI in PLWHIV [CMV-pp65: aOR 1.68 (1.10–2.57), P = 0.016], CMV-gB: aOR 3.73 (1.61–16.98, P = 0.022), also when adjusting for other potential confounders (comorbidity, CD4+ T cells, log IL-6, and activated CD8+ T cells) (Table 3). The associations were also stable when adjusting for HIV transmission mode (MSM). The association between CMV-specific CD4+ T-cell responses and NCI was modified by increasing age (p-interaction = 0.041), but not by lower CD4+ T-cell counts (p-interaction = 0.078) or higher IL-6 (p-interaction = 0.164). The same associations were not found for CMV-specific CD8+ T-cell responses (Table 3).When investigating severity of NCI, we found no associations between CMV-specific CD4+ T-cell responses and worse GDS scores (Table 4). When analyzing the cognitive domains separately, CMV-specific CD4+ T-cell responses were associated with impairment in speed of information processing [CMV-pp65: aOR 1.38 (1.00–1.90), P = 0.05], CMV-gB: aOR 1.75 (1.09–2.79, P = 0.020), but not with impairment in other domains (data not shown).
In this cross-sectional study, PLWHIV on stable cART had a higher risk of NCI than HIV-uninfected controls after adjustment for age and premorbid cognitive function. Higher CMV-specific CD4+ T-cell responses were associated with NCI in PLWHIV, whereas higher CMV-IgG was associated with worse neurocognitive performance overall.
Previous studies investigating the association between CMV and NCI in PLWHIV are sparse, despite evidence that CMV or CMV immunity are associated with cognitive impairment in elderly HIV-uninfected populations.27–30 The relationship between CMV-specific T-cell responses and NCI has not previously been investigated in PLWHIV, but in elderly HIV-uninfected individuals, higher CMV-specific CD4+ T-cell responses and CMV-IgG were associated with cognitive impairment.27 It has been demonstrated that CMV-specific CD4+ T cells are inflated in PLWHIV, have features of terminal differentiation (CD4+CD28−) and cytotoxic activity, and may play a role in endothelial dysfunction,55–58 but the mechanisms by which CMV-specific CD4+ T cells may affect neurocognitive performance is unknown. We previously found that CMV-specific CD4+ T cells were associated with CD8+ T-cell activation,51 and another study showed that anti-CMV treatment reduced CD8+ T-cell activation in PLWHIV.15 However, a role of CD8+ T-cell activation was not confirmed in this study.
The finding that CMV-IgG was associated with worse overall neurocognitive performance in PLWHIV has also been found in other recent studies.21,36 Interestingly, Letendre et al36 showed that the association was only present in PLWHIV on treatment. In our study, we did not find that duration of treatment had an impact on the association between CMV-IgG and neurocognitive performance. Associations between higher CMV-IgG and cognitive impairment has also been found in HIV-uninfected,27,30 but the mechanisms remain unknown.
Discordant results between humoral and cellular CMV-specific responses may be due to CMV-IgG and CMV-specific T-cell responses representing different pathways of adaptive immunity and being modulated by different factors. CMV-IgG has typically been interpreted as a marker of CMV reactivations, but recent studies have questioned this assumption.25,59,60 Higher CMV-specific immune responses may reflect a combination of CMV burden, host factors, HIV-related factors, and repeated exposures or cross-infections, in complex host-pathogen interactions that we are not able to address in this study. We sought to minimize confounding by selecting PLWHIV on stable cART with viral suppression, and by excluding PLWHIV with HCV/HBV coinfection, IDU, and other confounders.38 In previous observational studies, nadir CD4+ was a strong predictor of NCI,4,5,61 and CMV has been associated with nadir CD4+,20,26,62 systemic inflammation,25,63–65 lower CD4+/CD8+ ratios,13,14 and T-cell activation19,66 in PLWHIV. When adjusting for confounders, we generally found stable associations between CMV immunity and NCI, although a modifying effect of age and IL-6 on NCI was found. However, because of a small sample size, we had limited statistical power, and such relationships have to be confirmed in larger prospective studies. A high proportion of PLWHIV in our cohort had depressive symptoms or was on treatment with antidepressants. However, depression was not associated with NCI and did not mediate the association between HIV and NCI. This is in accordance with previous studies' finding that, despite a high prevalence of psychiatric symptoms in PLWHIV, these are often not associated with NCI.67–69
Important considerations when assessing NCI in PLWHIV are the cognitive test battery used, definition of NCI, and choice of normative standards. We used a reduced test battery of 6 neurocognitive tests investigating 4 recommended domains frequently affected in PLWHIV.50 NCI was detected in 31% of PLWHIV in our study, which is in accordance with results from the CHARTER study, finding that 30% in the subgroup of PLWHIV with minimal comorbidity, suppressed HIV-RNA, and normal CD4+ T-cell counts had NCI.4 The GDS method summarizes number and severity of impairments across all cognitive measures while performances in the normal range are not considered,48,49 and is consistent with international criteria for classification of HAND.50 The international criteria have been criticized for including PLWHIV with asymptomatic impairment in addition to false-positive results in the definition of NCI, and whether a more conservative cutoff should be applied is an ongoing discussion.70,71 We used a local normative reference group matched according to demographics instead of population-based normative standards. The use of a matched control group with correction for premorbid cognitive function is regarded as optimal if representative normative standards are not available.45,46 Importantly, the GDS method is validated for use with both demographically corrected normative standard and local normative standards using z-scores.45,47–49
Limitations in this study include the cross-sectional design, missing information about CMV-specific T-cell responses in HIV-uninfected, and a relatively small sample size. Because PLWHIV were on stable cART and strict exclusion criteria were used, results may not be applicable to the general population of PLWHIV. It is a limitation that information about HIV risk behavior other than transmission mode was not available. However, we sought to avoid confounding by excluding factors often associated with HIV risk behavior such as HBV/HCV, substance abuse disorders, or severe psychiatric illness, and adjustments for MSM was performed in multivariable analyses. However, the complex and probably reciprocal relationship between NCI and HIV risk behavior should be addressed in future studies. In addition, wide confidence intervals on the estimated ORs indicate that the sample size was small, and findings from this study need to be replicated with larger sample sizes. CMV-pp65 and CMV-gB are among the most immunodominant proteins,72 and despite only representative of a fraction of total CMV-specific T-cell responses,72,73 results may be representative of the overall CMV-specific immune response. However, future studies could benefit from inclusion of a wider range of immunogenic CMV proteins. The strength of the study is the well-characterized cohort with low comorbidity index and exclusion of important confounders in addition to assessment of both CMV-IgG and several functional outputs of CMV-specific T-cell responses, and the latter never previously been characterized in the context of NCI and treated HIV infection.
In summary, in this cohort of PLWHIV on stable cART and with low comorbidity index, PLWHIV had higher risk of NCI after adjustment for age and premorbid cognitive function, and the risk of NCI was increased in PLWHIV with higher CMV-specific CD4+ T-cell responses in addition to CMV-IgG levels being associated with worse GDS scores. It remains unclear how and if CMV immunity contributes to the pathogenesis behind NCI in PLWHIV on stable cART, and larger prospective studies are warranted.
The authors gratefully acknowledge the participants who made this study possible, and they thank the staff of our departments for their continuous support.
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