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. 2022 Aug 29;25:100498. doi: 10.1016/j.bbih.2022.100498

T-cell activation state differentially contributes to neuropsychiatric complications in women with HIV

Dionna W Williams a,b,1, Bianca R Flores a,1, Yanxun Xu c,d, Yuezhe Wang c, Danyang Yu c, Brandilyn A Peters e, Adebola Adedimeji e, Tracey E Wilson f, Daniel Merenstein g, Phyllis C Tien h, Mardge H Cohen i, Kathleen M Weber j, Adaora A Adimora l, Igho Ofotokun m, Margaret Fischl n, Janet Turan o, Bülent Turan p, Geoffroy Laumet q, Alan L Landay r, Raha M Dastgheyb s, Stephen J Gange k, Sheri D Weiser h,t, Leah H Rubin a,k,s,u,∗
PMCID: PMC9463560  PMID: 36097532

Abstract

Neuropsychiatric complications are common among women with HIV (WWH). The pathophysiological mechanisms underlying these complications are not fully known but likely driven in part by immune modulation. We examined associations between T-cell activation states which are required to mount an effective immune response (activation, co-stimulation/normal function, exhaustion, senescence) and neuropsychiatric complications in WWH. 369 WWH (78% HIV RNA undetectable/<20cp/mL) enrolled in the Women's Interagency HIV Study completed neuropsychological testing and measures of depression (Center for Epidemiological Studies Depression Scale-CES-D), self-reported stress levels (Perceived Stress Scale-10), and post-traumatic stress (PTSD Checklist-Civilian Scale). Multiparametric flow cytometry evaluated T-cell activation state. Partial least squares regressions were used to examine T-cell phenotypes and neuropsychiatric outcome associations after confounder adjustment. In the total sample and among virally suppressed (VS)-WWH, CD4+ T-cell exhaustion was associated with poorer learning and attention/working memory (P's < 0.05). In the total sample, CD4+ T-cell activation was associated with better attention/working memory and CD8+ T-cell co-stimulation and senescence was associated with poorer executive function (P's < 0.05). For mental health outcomes, in the total sample, CD4+ T-cell activation was associated with more perceived stress and CD4+ T-cell exhaustion was associated with less depressive symptoms (P's < 0.05). Among VS-WWH, CD4+ senescence was associated with less perceive stress and CD8+ T-cell co-stimulation and senescence was associated with higher depression (P's < 0.05). Together, results suggest the contribution of peripheral CD4+ and CD8+ T-cell activation status to neuropsychiatric complications in WWH.

Keywords: HIV, T-cell function, Cognition, Mental health, Women

Highlights

  • •

    T-cell activation states contribute to neuropsychiatric function in women with HIV.

  • •

    CD4+ T-cell activation improves, and exhaustion worsens, neuropsychiatric function.

  • •

    CD8+ T-cell activation states are associated with poorer neuropsychiatric function.

  • •

    Correlates of T-cell activation states and neuropsychiatric function vary by viremia.

1. Introduction

Neuropsychiatric complications, including cognitive impairment and mental health disorders (depression, anxiety disorders, post-traumatic stress disorder [PTSD]), are highly prevalent among people with HIV (PWH). Mild cognitive impairment without any changes in everyday function persists in 24% of PWH and mild cognitive impairment with some decline in everyday function persists in approximately 13% (Wang et al., 2020). The overall pooled prevalence of depression and depressive symptoms in two recent meta-analyses was 27% and 31% (95%CI 28–34) (Rezaei et al., 2019; Wang et al., 2017a) and for PTSD and PTSD symptoms was 33% (Ayano et al., 2020). These relatively high prevalence estimates alone demonstrate an urgent need to understand the pathophysiological mechanisms of neuropsychiatric complications in PWH, particularly among women with HIV (WWH) who appear to be more vulnerable to these conditions then men with HIV (Rubin et al., 2019a, 2019b, 2020a).

One likely contributor to neuropsychiatric complications in PWH is through immune system modulation, including the production of proinflammatory cytokines, trafficking of peripheral immune cells into the central nervous system (CNS), and chronic inflammation. Myeloid cells have been attributed as the predominate source of HIV-related neuroinflammation and the primary target of HIV infection in the brain (Joseph et al., 2015; Leon-Rivera et al., 2021; Rubin et al., 2020b; Veenhuis et al., 2021; Williams et al., 2014; Zhang and Gensel, 2014); however, T-cells are also involved in the neuropathogenesis of HIV. CD4+ T-cells are the predominate population of cells infected by HIV in the periphery and are responsible for stimulation of CD8+ T-cells, which mediate killing of virally infected cells. Like monocytes, T-cells can also migrate across the BBB into the brain (Nishihara et al., 2020), and can be associated with the severity of neuropsychiatric complications (Lynall et al., 2020; Wang et al., 2017b). While known to occur during homeostatic states, T-cell migration across the BBB occurs to a greater degree in inflammatory (Castro Dias et al., 2021; Qiu et al., 2021) and neurodegenerative conditions, including Parkinson's disease (Brochard et al., 2009), Alzheimer's disease, and Multiple Sclerosis (Oliveira-Giacomelli et al., 2021). Aberrant T-cells have also been mechanistically linked to neuropsychiatric complications (Kipnis et al., 2004; Woolley et al., 2011). T-cells are implicated in mental health disorders, including major depression (Beurel and Lowell, 2018; Woelfer et al., 2019). There is also a precedence for T-cells in promoting neuropsychiatric complications during HIV. In PWH, the presence of interferon gamma expressing T-cells in cerebrospinal fluid indicated a higher risk for cognitive impairment (Schrier et al., 2015). Furthermore, in vitro studies showed that leukotriene C4, an eicosanoid found in the CNS of PWH, promoted the migration of HIV-infected T-cells across a BBB model, implicating their role in the neuropathogenesis of HIV (Bertin et al., 2014). Additionally, T-cells from PWH migrated across an endothelial barrier to a greater extent than cells from controls (Birdsall et al., 1997). Together, these findings suggest that T-cells can enter the CNS during inflammatory, infectious, and neuropsychiatric disorders and contribute to the development of neurologic disease.

While the contribution of T cells to CNS disease is clear, the functional contribution of these cells to neuropsychiatric complications, including that which occurs in the context of HIV, is not completely understood. This is particularly true for the series of steps required to mount an effective and well-regulated immune response. T-cells are integral in inducing the adaptive immune response. To do this, they must first undergo a two-step process. Step one, termed activation, occurs when T cells receive extracellular signals mediated by T-cell receptor complexes (Hwang et al., 2020). Next, T-cells undergo co-stimulation (normal function) through interactions with antigen presenting cells. Both steps must occur to have an activated T-cell and these cells will not elicit an immune response if the steps occur in the wrong order, or if they receive only one signal (Hwang et al., 2020). Equally important are mechanisms to stop the immune response at the appropriate time (Bohineust et al., 2018). When these mechanisms fail, T-cells become exhausted and lose their functional responses, including efficient killing of infected cells, proliferative capacity, and cytokine responses (Fenwick et al., 2019). Chronic inflammatory states, like HIV, are hallmarked by T-cell exhaustion due to continual, repeated antigen stimulation. This continual stimulation results in T-cell dysfunction that results in reduced effector functions, changes to cytokine production, inhibitory receptors, proliferative capacity, transcriptional landscape, and epigenetic regulatory mechanisms (Blank et al., 2019; Im and Ha, 2020; Pawelec, 2019). Importantly, this occurs even in the context of viral suppression with antiretroviral therapy (Hunt et al., 2003).

The relationship between T-cell activation, co-stimulation, senescence, and exhaustion with neuropsychiatric complications is not well understood during HIV. However, T-cell functional states contribute to the development of neuropsychiatric complications through multiple mechanisms. An imbalance in the proportion of T-cell subsets occurs in people with obsessive-compulsive disorder (Rodriguez et al., 2019), and is implicated in promoting activation of inflammatory pathways that induce neuroinflammation, neuronal damage, and alterations in synaptic pruning. Further, alterations in T-cell subsets are implicated in abnormalities in white matter microstructure, reduced neurotransmitter levels, and reductions in immune tolerance (Poletti et al., 2017) that can occur as these cells acquire a senescence and exhaustion phenotype. Alterations in T-cell effector functions are implicated in mood disorders, including depression and anxiety (Vieira et al., 2010). Rodent models demonstrate that the loss of appropriate T-cell regulatory mechanisms contributes to depression-related behaviors (Cohen et al., 2006; Laumet et al., 2020; Shi et al., 2022; Westfall et al., 2021). Similar relationships occur for cognition, where impaired T-cell functional states contribute to decreases in spatial learning and memory (Ron-Harel et al., 2008; Ziv et al., 2006). The repeated antigen stimulation that occurs during autoimmune disorders is also associated with dysfunctional T-cell activation states that promote neuropsychiatric complications. This occurs in the context of systemic lupus erythematosus (SLE), where a loss of T-cell tolerance towards self-antigens occurs that is associated with alterations in neurotrophic factors, including brain-derived neurotrophic factor (Tian et al., 2019) and infiltration of activated CD4+ T cells into the choroid plexus that have functional effector phenotypes (Jain et al., 2018). Further, dysfunctional T-cell activation states also contribute to neuropsychiatric complications in additional autoimmune disorders, including multiple sclerosis (Brasanac et al., 2021; Kant et al., 2018). These findings highlight the importance of appropriate T-cell functional state in the development of neuropsychiatric disease and provide important pathways that contribute to cognitive and mental health disorders.

Due to the importance of T-cell activation states, as well as the relevance of T-cells in HIV CNS disease, our goal was to assess the association of T-cell dysregulation with neuropsychiatric complications in PWH. We were interested specifically in WWH due to the increased rates of neuropsychiatric complications in this population (Rubin et al., 2019a, 2019b, 2020a) as well as sex differences in the relationships between immune function and neuropsychiatric complications (Rubin et al., 2019a; Vecchio et al., 2020). Importantly, our analyses included an evaluation of a subset of WWH who were virally suppressed (VS) to provide mechanistic insight into how dysfunctional T-cell phenotypes (activation, co-stimulation/normal function, senescence, exhaustion status) contribute to neuropsychiatric complications in the absence of viral replication. We hypothesized that greater T-cell senescence and exhaustion would relate to poorer cognitive function and greater mental health symptoms.

2. Methods

2.1. Participants

Participants were enrolled in the Women's Interagency HIV study (WIHS), an ongoing, multisite prospective cohort study of the natural and treated history of WWH, that enrolled WWH and HIV-uninfected women in 1994–1995 at six sites (Bronx/Manhattan NY, Brooklyn NY, Chicago IL, Washington DC, Los Angeles CA, San Francisco CA). Additional enrollment occurred in 2001–2002, 2011–2012 and in 2014–2015, the WIHS added four southern sites (Atlanta GA, Chapel Hill NC, Miami FL, Birmingham AL) and closed its Los Angeles site. WIHS methods and study characteristics have been previously described (Adimora et al., 2018; Bacon et al., 2005; Barkan et al., 1998). In brief, biological specimens, physical exams, and extensive sociodemographic, behavioral, and clinical data (including the Center for Epidemiological Studies Depression scale [CES-D]) are collected semiannually. Participants complete neuropsychiatric assessments including neuropsychological (NP) testing, the Perceived Stress Scale (PSS-10), and the Post-Traumatic Stress Disorder (PTSD) Checklist-Civilian Scale (PCL-C) every two years starting in 2009.

For this study, we identified 430 WWH who were on ART, did not have a diagnosis of autoimmune diseases, cancer, or hepatitis B or C virus infection, had biospecimens in storage that were collected between 2013 and 2016, and had functional T-cell phenotypic characterization data measured in a previous study (Peters et al., 2021). Six participants did not have the covariate data needed for this analysis and were excluded. Of the remaining 424 individuals, 373 had complete data on the primary neuropsychiatric outcome measures concurrent or after the date biospecimens were available and constituted the study population for this study. For these individuals, NP, PCL-C, and PSS-10 data was available on average 1.22 years following the T-cell data (median = 1.01 years, interquartile [IQR] range = 0.19 years).

2.2. T-cell phenotypic characterization

T-cell phenotypic characterization was performed by multiparameter flow cytometry on frozen/thawed viable peripheral blood mononuclear cells (PBMCs) using BD Vacutainer ® CPT™ (BD Biosciences). A water bath was set to 37 °C and PBMCs were removed from LN2 storage before being thawed rapidly in the water bath. Once thawed, they were washed and stained with fluorochrome-conjugated monoclonal antibodies to CD3, CD4, CD8, CD57, CD28, PD-1, HLA-DR, and CD38 (BD Biosciences). To assess the viability of the cells, Aqua Live/Dead cell stain kit (Invitrogen) was utilized on the PBMCs prior to cell surface staining. After staining, the cells were washed, fixed in 2% formaldehyde, and analyzed within 24 h on a LSRII flow cytometer (BD) using FACS Diva software v6.11. FlowJo 9.9.3 (Tree Star Inc) was utilized to analyze the data. Analyses of immune activation (CD38+HLA-DR+), co-stimulation/normal function (CD57−CD28+) exhaustion (PD-1+), and senescence (CD57 + CD28−) were performed after stringent gating on singlet live (Aqua-) CD3+CD4+ or CD3+CD8+ T-cells (Fig. 1). FMO controls were stained and analyzed to define the gaiting strategies used to identify the phenotypic profiles of the T-cell subsets.

Fig. 1.

Fig. 1

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Representative flow cytometric analyses of frozen/thawed PBMC. Analyses of immune activation (CD38+HLA-DR+), co-stimulation (CD57−CD28+), exhaustion (PD-1+), and senescence (CD57 + CD28−) after stringent gating on lymphocytes > live (Aqua-) > singlet > CD3+CD4+ or CD3+CD8+ T-cells. Results are reported as the % of the parental CD3+CD4+ or CD3+CD8+ T-cell populations.

2.3. Cognitive outcomes

The following cognitive domains and related neuropsychological (NP) tests were used: learning and memory, Hopkins Verbal Learning Test-Revised (HVLT-R; learning outcomes: total learning; memory = delay free recall); attention/working memory, Letter-Number sequencing (outcomes = control and experimental conditions total correct); executive function, Trail Making Test Part B (mental flexibility) and Stroop Test color-word trial (behavioral inhibition) (outcomes = time to completion); psychomotor speed, Symbol Digit Modalities Test (outcome = total correct) and Stroop Test color-naming trial (outcome = time to completion); fluency, letter (outcome = total correct) and semantic (outcome = total correct); and motor function, Grooved Pegboard (outcome time to completion, dominant and nondominant hand). Timed outcomes were log transformed to normalize distributions and reverse scored so that better performance equaled higher values. Demographically adjusted (age, years of education, Wide Range Achievement Test-vocabulary subtest, race/ethnicity) T-scores were calculated for each outcome and T-scores were used to create domain scores consistent with previous large-scale WIHS-wide studies (Rubin et al., 2017, 2018). For each domain, a composite T-score was derived by averaging the T-scores for domains with ≥2 outcomes. If only one test in a domain was completed, the T-score for that test was used.

2.4. Self-report neuropsychiatric outcomes

Participants completed: the: 1) Center for Epidemiological Studies Depression scale (CES-D) which assesses depressive symptoms (Radloff, 1977); 2) Perceived Stress Scale (PSS)-10 which measures perceptions of stress; the degree of uncontrollability, unpredictability, and overload in the respondent's daily life (Cohen et al., 1983; Cohen and Williamson, 1988); and 3) PTSD Checklist-Civilian Scale (PCL-C) which assesses post-traumatic symptom burden anchored to stressful experiences rather than a specific event (Weathers et al., 1991). Primary outcome measures on each of the scales were the total scores (continuous). Additionally, subscale scores were computed on the CES-D (somatic, negative affect, positive affect, and interpersonal symptoms) and the PCL-C (avoidance, arousal, re-experiencing) to assess symptom subtypes. For those with multiple CES-D measurements, we selected the measurement that was concurrent with the other neuropsychiatric assessments.

2.5. Statistical Analyses

Prior to analyses, we examined the normality of our data. A series of partial least squares regressions (PLSR) were used to examine associations between T-cell phenotypes and neuropsychiatric outcomes in the total sample and stratified by viral suppression status (Geladi and Kowalski, 1986). PLSR is a method to model the relationship between multiple outcomes and predictors that accounts for the covariation amongst multiple outcome variables. This method also avoids the need for multiple comparison corrections for P-values which would be the case if we ran multiple parallel models. Here the predictor matrix for all analyses included the eight variables assessing T-cell phenotypes (surface markers of activation [%CD38+HLADR+], senescence [%CD57 + CD28−], exhaustion [%PD-1+], and co-stimulation/normal function [%CD57− CD28+] on CD4+ and CD8+ T cells). For NP function, the outcome matrix included the seven cognitive domain T-scores. For mental health, the outcome matrix included the total CES-D, PCL-C, and PSS-10 scores. When significant associations were seen between T-cell phenotypes and the total CES-D and/or PCL-C score, sub-analyses were conducted to examine T-cell phenotypes and subscale scores on the CES-D (e.g., somatic, negative affect) and PCL-C (e.g., arousal, avoidance). For each model, regression coefficients and P-values were obtained to determine the specific relationships between each T-cell phenotype-outcome association. The significance of each coefficient was determined by an approximate T-test based on jack-knife variance estimates, which computes the standard error of each coefficient by aggregating the coefficient estimates from resampling data (Martens and Martens, 2000).

As the resulting P-values from the jack-knife approach are not exact, we did not adjust for multiple testing. We examined all variables in Table 1 as potential confounders of the associations between T-cell phenotypes and neuropsychiatric outcomes. The only variables identified as confounders which were included in all models were: current smoking and heavy alcohol use (reflects >7 drinks/week or ≥4 drinks in one sitting) as well as body mass index. Analyses were conducted in R 3.6.2 with package ‘pls’ (Bjorn-Helge et al., 2019).

Table 1.

Sociodemographic, clinical, and behavioral characteristics of the overall sample of women with HIV (WWH) and by viral suppression (VS) status.

Total Sample (N = 373)
Mean (SD)		 VS only (n = 291)
Mean (SD)		 Viremic only (n = 82)
Mean (SD)
Age 44.5 (8.3) 45.0 (8.3) 42.8 (8.3)
Years of education 12.8 (3.1) 13.0 (3.1) 12.4 (2.8)
WRAT-3 reading subtest 91.0 (18.3) 91.4 (18.1) 89.5 (19.1)
Race/ethnicity, n (%)
 Black, non-Hispanic 300 (80) 235 (81) 65 (80)
 White, non-Hispanic 35 (9) 29 (10) 6 (7)
 Hispanic 26 (7) 18 (6) 8 (10)
 Other 12 (3) 9 (3) 3 (4)
Annual household income <$12,000/year, n (%) 165 (44) 130 (45) 35 (43)
Depressive symptoms (CES-D)† 11.2 (11.2) 10.9 (11.1) 12.4 (11.9)
Perceived stress symptoms (PSS-10)† 13.3 (7.8) 13.1 (7.8) 13.8 (7.9)
Reported use of the following non-ART medication types, n (%)
Antidepressants 45 (12) 36 (12) 9 (11)
Antipsychotics 13 (3) 11 (4) 2 (2)
Anticonvulsants 14 (4) 10 (3) 4 (5)
Antihistamines 18 (5) 14 (5) 4 (5)
Opioids 11 (3) 8 (3) 3 (4)
PTSD symptom burden (PCL-C)† 30.8 (13.7) 30.7 (13.8) 31.2 (13.6)
Current smoking status, n (%) 115 (31) 83 (29) 32 (39)
Recent heavy alcohol use, n (%) 42 (11) 33 (11) 9 (11)
Recent marijuana use, n (%) 64 (17) 53 (18) 11 (13)
Recent Crack, cocaine, and/or heroin use, n (%) 12 (3) 10 (3) 2 (2)
Body mass index 33.3 (9.6) 33.0 (9.4) 34.5 (10.2)
Efavirenz use at visit, n (%) 81 (22) 74 (25) 7 (9)
Integrase inhibitor use at visit, n (%) 115 (31) 83 (29) 32 (39)
Nadir CD4 count in WIHS, median (IQR) 293 (284) 298 (313) 267 (259)
Current CD4 count, median (IQR) 623 (410) 645 (418) 501 (408)
Undetectable HIV RNA, <20cp/mL, n (%) 291 (78) 291 (100) 0 (0)
Adherence (≥95%) to cART, n (%) 320 (86) 258 (89) 62 (76)
ART duration (years), M (SD) 9.1 (6.2) 8.9 (6.1) 9.8 (6.4)
cART duration (years), M (SD) 8.5 (5.5) 8.4 (5.5) 9.1 (5.5)
Prior AIDS diagnosis, n (%) 73 (20) 52 (18) 21 (26)
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Note. ART = antiretroviral therapy; cART = combination ART; CES-D = Center for Epidemiological Studies Depression scale (range of scores: 0–60); current refers to within the past week; heavy alcohol use reflects >7 drinks/week or ≥4 drinks in one sitting; IQR = interquartile range; recent, refers to within 6 months of the most recent WIHS visit; PTSD = post traumatic stress disorder; PCL-C=PTSD Civilian Checklist (range of scores: 17–85); PSS-10 = Perceived Stress Scale (range of scores: 10–50); SD = standard deviation; WIHS=Women's Interagency HIV Study; WRAT-3 = Wide Range Achievement Test standard score; UD = undetectable. † higher scores = more symptoms.

3. Results

3.1. Participants

The socio-demographic, behavioral, and clinical factors for the total sample and by VS status are depicted in Table 1. WWH had a mean age of 44.5 years (standard deviation [SD] = 8.3) and 80% identified as Black, non-Hispanic. The average years of education was 12.6 (SD = 2.8) and 44% had annual income ≤$12,000. Thirty percent reported current smoking, 11% current heavy alcohol use, and 17% recent (past six months) marijuana use. HIV RNA was <20 copies/mL for 78%, median CD4 count was 623 cells/mm3 (IQR = 410), and 19% of women had a prior diagnosis of AIDS. Thirty-one percent were on an integrase strand inhibitor-based regimen and 21% were on efavirenz.

The mean percentage of cell surface markers of CD4+ and CD8+ T-cell activation, co-stimulation/normal function, senescence, and exhaustion as well as cognitive performance are in the total sample and by VS status are depicted in Table 2. Viremic women had higher CD4+ T-cell activation (P = 0.003) and exhaustion (P = 0.003) levels as well as higher CD8+ T-cell activation (P < 0.001), co-stimulation/normal function (P = 0.01), senescence (P = 0.009), and exhaustion (P < 0.001) levels. Cognitive performance on each of the domains in the total sample as well as in VS-WWH and viremic women were in the normal range (T's ≥ 40).

Table 2.

T-cell activation states and domain-specific cognitive function in the overall sample of women with HIV (WWH) and by viral suppression (VS) status.

Total Sample (N = 373)
Mean (SD)		 VS only (n = 291)
Mean (SD)		 Viremic only (n = 82)
Mean (SD)
T-cell activation states
 %CD4+
 Activation 3.8 (3.6) 3.3 (2.6) 5.8 (5.5)
 Co-stimulation/normal function 75.1 (16.0) 75.5 (16.5) 73.6 (14.4)
 Senescence 4.9 (6.2) 4.9 (6.3) 5.0 (6.0)
 Exhaustion 14.5 (9.0) 13.2 (7.3) 19.0 (12.5)
 %CD8+
 Activation 7.8 (6.8) 6.3 (4.9) 13.2 (9.3)
 Co-stimulation/normal function 28.7 (17.9) 30.0 (18.5) 23.9 (14.6)
 Senescence 35.2 (15.5) 33.9 (15.8) 39.7 (13.6)
 Exhaustion 12.2 (7.7) 10.9 (6.8) 17.0 (8.9)
Cognitive function
 Learning 49.6 (9.9) 49.7 (9.5) 49.0 (11.2)
 Memory 49.6 (9.0) 49.3 (8.7) 50.8 (10.0)
 Executive function 48.1 (10.0) 48.1 (9.7) 48.3 (11.3)
 Fluency 49.6 (9.7) 49.6 (9.6) 49.8 (10.2)
 Attention/working memory 47.8 (10.2) 48.1 (10.1) 47.0 (10.7)
 Processing speed 49.9 (9.1) 50.2 (8.8) 48.7 (10.1)
 Motor function 49.7 (9.6) 49.8 (9.8) 49.4 (8.8)
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3.2. T-cell phenotypes and cognition

Among WWH, higher CD4+ T-cell activation was associated with better attention/working memory (P = 0.02), whereas higher CD4+ T-cell exhaustion was associated with poorer attention/working memory (P < 0.001) and verbal learning (P = 0.04 Fig. 2A). Higher CD8+ T-cell co-stimulation (P = 0.03) and senescence (P = 0.02) were associated with poorer executive function. Among the subset of VS-WWH, two associations remained significant (Fig. 2B). Specifically, higher CD4+ T-cell exhaustion was associated with poorer attention/working memory (P < 0.001) and verbal learning (P = 0.04). Among the subset of viremic women, there were no significant associations between T-cell phenotypes and cognition (Fig. 2C).

Fig. 2.

Fig. 2

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Associations between T-cell activation states and domain-specific cognitive function in the total sample (A), in virally suppressed (VS) (B), and in viremic (C) women with HIV. Markers used for determining activation status of the T-cells are as follows: CD4+ activation (CD3+CD4+CD38+HLA-DR+), CD4+ co-stimulation/normal function (CD3+CD4+CD57−CD28+), CD4+ senescence (CD3+CD4+CD57 + CD28−), CD4+ exhaustion (CD3+CD4+PD-1+), CD8+ activation (CD3+CD8+CD38+HLA-DR+), CD8+ co-stimulation/normal function (CD3+CD8+CD57−CD28+), CD8+ senescence (CD3+CD8+CD57 + CD28−), CD8+ exhaustion (CD3+CD4+PD-1+). The cognitive domains are described in further detail in Methods. The numbers in the figure reflect the magnitude of adjusted regression coefficients (see Statistical Analyses). Coeff = coefficient, (A) Total Sample, (B) VS only,(C) Viremic only.

3.3. T-cell phenotypes and mental health outcomes

Among WWH, higher CD4+ T-cell activation was associated with higher anxiety whereas higher CD4+ T-cell exhaustion (P = 0.04) was associated with lower depressive symptoms (P = 0.03) (Fig. 3A) particularly negative affect (β = −0.19, P = 0.02). CD8+ T-cell phenotypes were not significantly associated with any mental health outcomes. However, in the subset of VS-WWH, higher CD4+ T-cell senescence was associated with less perceived stress (P = 0.03) whereas higher CD8+ T-cell co-stimulation (P = 0.02) and CD8+ T-cell senescence (P = 0.03) was associated with higher depressive symptoms (Fig. 3B), particularly somatic symptoms (β = 0.41, P < 0.001 and β = 0.29, P < 0.001, respectively). Among viremic women, higher CD4+ T-cell activation was associated with greater perceived stress (P < 0.001), whereas higher CD4+ T-cell exhaustion was associated with less perceived stress (P = 0.01). Higher CD4+ T-cell co-stimulation was associated with greater depressive symptoms (P = 0.03), particularly negative affect (β = 0.46, P = 0.01), as well as higher CD4+ T-cell senescence was associated with greater PTSD symptom (P = 0.04) particularly avoidance symptoms (β = 0.27, P = 0.05).

Fig. 3.

Fig. 3

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Associations between T-cell activation states and mental health symptoms in the total sample and by viral suppression (VS) status. Markers used for determining activation status of the T-cells are as follows: CD4+ activation (CD3+CD4+CD38+HLA-DR+), CD4+ co-stimulation/normal function (CD3+CD4+CD57−CD28+), CD4+ senescence (CD3+CD4+CD57 + CD28−), CD4+ exhaustion (CD3+CD4+PD-1+), CD8+ activation (CD3+CD8+CD38+HLA-DR+), CD8+ co-stimulation/normal function (CD3+CD8+CD57−CD28+), CD8+ senescence (CD3+CD8+CD57 + CD28−), CD8+ exhaustion (CD3+CD4+PD-1+). Center for Epidemiological Studies Depression scale (CES-D); Post-Traumatic Stress Disorder (PTSD) Checklist-Civilian Scale (PCL-C); and Perceived Stress Scale (PSS)-10 are described in further detail in Methods. The numbers in the figure reflect the magnitude of adjusted regression coefficients (see Statistical Analyses). Coeff = coefficient, (A) Total Sample (B) VS only (C) Viremic only.

See Supplemental Material for all regression coefficients and P-values for all analyses conducted in the total sample, VS, and viremic women with HIV.

4. Discussion

To the best of our knowledge, we are among the first to examine an understudied contributor to neuropsychiatric complications in WWH: dysfunctional T-cell activation states. We not only examined associations in the total sample of WWH, but also identified associations among VS-WWH to mechanistically examine associations in the absence of viral replication which differed from the associations or lack of associations among viremic women. We found similar associations with dysfunctional T-cell activation states and cognition in WWH and among the subset of VS-WWH only. Strikingly, in contrast to the pattern of associations with cognition, associations with mental health outcomes differenced in VS-WWH and viremic women.

Our findings provide key insights into the mechanisms by which T-cell activation states may contribute to neuropsychiatric complications in PWH. We found that CD4+ T-cell activation was beneficial and were associated with better attention/working memory. This suggests that an initial antiviral response is protective, likely due to the T helper functions that occur following activation. CD4+ T-cell differentiation into T helper 1 effectors is essential for helping mount cytotoxic CD8+ T-cell responses that kill virally infected cells (Swain et al., 2012). CD4+ T-cells can also differentiate into T follicular helper cells that induce B cells to produce mature antibodies (Benova et al., 2020), including those with specificity to HIV proteins. CD4+ T-cells that have undergone activation can also serve as additional primers to boost innate immune responses to HIV, including macrophage (Martinez and Gordon, 2014) and NK cell functions (Jost et al., 2014) through cytokine production and the additional recruitment of effector cells to sites of viral replication through local chemokine production in infected tissues (Swain et al., 2012). Further, CD4+ T-cells may also have direct antiviral benefits by acquiring cytotoxic functions that promote the direct killing of infected cells through MHC II-dependent mechanisms (Juno et al., 2017). Together, these effector functions help mount an anti-HIV response that may have non-detrimental or protective neuropsychiatric implications. In addition to their immunologic benefits, CD4+ T-cell activation is required for the maintenance of neurogenesis during adulthood (Kipnis et al., 2012; Ron-Harel et al., 2008; Wolf et al., 2009), providing a direct mechanism by which they can be protective against neuropsychiatric complications during HIV. Unlike that which occurred for activation, CD4+ exhaustion was detrimental and was associated with poorer attention/working memory and verbal learning. T-cell exhaustion is an adaptive response to persistent antigen stimulation that helps limit tissue damage by decreasing antiviral functions through the upregulation of inhibitory receptors (Barnova et al., 2021; Budimir et al., 2021; Castelli et al., 2021). This suggests that, while aiming to have a beneficial impact, quelling the T-cell antiviral response or alterations in the integrity of the adaptive immune system (Kipnis et al., 2004) may be detrimental to neurologic function and can mechanistically contribute to the development of neuropsychiatric complications.

In contrast to CD4+ T-cells, CD8+ T-cell activation states were detrimental and were associated with poorer executive function and more depressive symptoms. While it may be surprising that the cytotoxic functions mediated by CD8+ T-cells are deleterious and contribute to neuropsychiatric complications in WWH, it is important to note that CD8+ T-cells remain only marginally functional during HIV, even in the context of fully viral suppressive ART. Due to the persistent exposure to viral antigens and chronic inflammation that occurs, CD8+ T-cells have increased expression of inhibitory receptors that suppress appropriate functional activation signaling. Further, aberrant CD8+ T-cells counts (Helleberg et al., 2015; Tanko et al., 2018), expression of activation and exhaustion markers (Perdomo-Celis et al., 2018; Trautmann et al., 2006), and their functional capacities remain impaired and are not fully restored by ART (Buggert et al., 2014; Migueles et al., 2009). Additionally, due to the decline in HIV antigens that occurs following exposure to ART, there is a decrease in the frequency of HIV-specific CD8+ T-cells (Casazza et al., 2001; Ogg et al., 1999; Rinaldo et al., 2000). It is evident that the loss of HIV-specific CD8+ T-cells is directly related to ART, as these cells significantly increased upon treatment interruption or failure (Altfeld et al., 2002; Casazza et al., 2001; Mollet et al., 2000). These aberrant CD8+ T-cell immune responses are not restricted to the periphery, and their presence in the CNS may also directly contribute to neurologic decline. CD8+ T-cells may enter the brain parenchyma and cerebrospinal fluid of PWH (Ganesh et al., 2016; Ho et al., 2013; Kessing et al., 2017). This may not be beneficial, as interferon-gamma expressing CD8+ T-cells in the cerebrospinal fluid was strongly correlated with cognitive status (Schrier et al., 2015). Despite their presence in the CNS, it remains unclear whether these cells maintain any functional capacity to kill infected cells (Ratto-Kim et al., 2018; Trautmann et al., 2012). This is particularly salient as CD8+ T-cells do not efficiently kill myeloid cells (Clayton et al., 2018; Rainho et al., 2015), the primary cell infected within the brain, suggesting that the presence of CD8+ T-cells may not necessarily eradicate the CNS viral burden. In fact, repeated challenge of CD8+ T-cells with HIV antigens promotes microglial activation and neurotoxicity (Prasad et al., 2021), as well as the development of CD8+ T-cell encephalitis (Cheema et al., 2019; Ishiguro et al., 2020; Lescure et al., 2013; Santana et al., 2020). In this context, it is not surprising that CD8+ T-cell activation states can contribute to neuropsychiatric complications during HIV.

There are a number of study limitations including lack of HIV-uninfected controls with T-cell activation data available, a small sample of viremic women, and the cross-sectional nature of the analysis. Not only are longitudinal assessments important for better addressing causality but would also be important to elucidate any potential mediating pathways (e.g., mental health – T-cell activation – NP impairment). In addition, we utilized self-report screeners of mental health symptoms (depressive, PTSD, non-specific anxiety) rather than a structured diagnostic interview. Current and lifetime psychiatric diagnostic data were not available in the cohort during the time frame that the T-cell markers were assessed. The World Health Organization's Composite International Diagnostic Interview Diagnoses (CIDI), which is a computer-assisted diagnostic interview for DSM-V criteria is now being administered and will be available for future studies. Another limitation is that T-cell markers are likely to change over time and they were not always measured concurrent with neuropsychiatric outcomes. Additionally, the T-cell markers used may not encompass all T-cell states. However, the markers selected were chosen to allow for a general assessment of cellular function and were used in previously published work in the WIHS (Peters et al., 2021). It is important to note that we evaluated T lymphocyte activation states in PBMCs obtained from peripheral blood. While our findings have implications for T-cell trafficking into the brain, we did not evaluate their migration across the BBB. Finally, the sample of WIHS women focused only on WWH on ART and those without cancer, hepatitis B/C, or autoimmune disorders. Thus, our findings are only generalizable to this subgroup of WWH and importantly cannot be generalized to men with HIV given known sex/gender differences in the immune system and neuro-immune interactions (Klein and Flanagan, 2016; Markle and Fish, 2014).

Importantly, our current study provides insight into the contribution of T-cell activation states to neuropsychiatric complications in WWH. Our findings indicate that CD4+ activation is beneficial for neuropsychiatric function, while exhaustion is detrimental. This is not surprising and suggests that an initial CD4+ T-cell response is protective, but due to the sustained stimulation that occurs in the context of a chronic viral infection, damage occurs once a senescent and exhaustive phenotype occurs. Conversely, all CD8+ activation states are associated with worsened neuropsychiatric function, indicating that targeting HIV-infected or cells expressing HIV antigens in the CNS is deleterious and disrupts the delicate balance of the CNS required for proper neuronal function.

Funding

Source of funding: This study was funded by a Women's Interagency HIV Study (WIHS) sub-study grant from NIMH (R01MH095683; Weiser) and K24AI134326 (Weiser). This work was also supported by the Johns Hopkins University NIMH Center for novel therapeutics for HIV-associated cognitive disorders (P30MH075773; Haughey, Rubin) and Central Nervous System Dysfunction Working Group (P30AI094189; Rubin). Dr. Williams effort was supported by R00DA044838 (Williams) and R01DA052859 (Williams). Data in this manuscript were collected by the Women's Interagency HIV Study, now the MACS/WIHS Combined Cohort Study (MWCCS). The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (Principal Investigators): Atlanta CRS (Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01-HL146241; Baltimore CRS (Todd Brown and Joseph Margolick), U01-HL146201; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01-HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01-HL146202; Data Analysis and Coordination Center (Gypsyamber D'Souza, Stephen Gange and Elizabeth Golub), U01-HL146193; Chicago-Cook County CRS (Mardge Cohen and Audrey French), U01-HL146245; Chicago-Northwestern CRS (Steven Wolinsky), U01-HL146240; Connie Wofsy Women's HIV Study, Northern California CRS (Bradley Aouizerat and Phyllis Tien), U01-HL146242; Los Angeles CRS (Roger Detels), U01-HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01-HL146203; Pittsburgh CRS (Jeremy Martinson and Charles Rinaldo), U01-HL146208; UAB-MS CRS (Mirjam-Colette Kempf and Deborah Konkle-Parker), U01-HL146192; UNC CRS (Adaora Adimora), U01-HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute (NHLBI), with additional co-funding from the Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), National Human Genome Research Institute (NHGRI), National Institute On Aging (NIA), National Institute Of Dental & Craniofacial Research (NIDCR), National Institute Of Allergy And Infectious Diseases (NIAID), National Institute Of Neurological Disorders And Stroke (NINDS), National Institute Of Mental Health (NIMH), National Institute On Drug Abuse (NIDA), National Institute Of Nursing Research (NINR), National Cancer Institute (NCI), National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute on Deafness and Other Communication Disorders (NIDCD), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). MWCCS data collection is also supported by UL1-TR000004 (UCSF CTSA), P30-AI-050409 (Atlanta CFAR), P30-AI-050410.

Declaration of competing interest

LHR is a consultant for Digital Artefacts, Inc. All coauthors have nothing to disclose.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbih.2022.100498.

Appendix A. Supplementary data

The following is the Supplementary data to this article:

Multimedia component 1
mmc1.docx (864.7KB, docx)

References

  1. Adimora A.A., Ramirez C., Benning L., Greenblatt R.M., Kempf M.C., Tien P.C., Kassaye S.G., Anastos K., Cohen M., Minkoff H., Wingood G., Ofotokun I., Fischl M.A., Gange S. Cohort profile: the women's interagency HIV study (WIHS) Int. J. Epidemiol. 2018;47:393–394i. doi: 10.1093/ije/dyy021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Altfeld M., van Lunzen J., Frahm N., Yu X.G., Schneider C., Eldridge R.L., Feeney M.E., Meyer-Olson D., Stellbrink H.J., Walker B.D. Expansion of pre-existing, lymph node-localized CD8+ T cells during supervised treatment interruptions in chronic HIV-1 infection. J. Clin. Invest. 2002;109:837–843. doi: 10.1172/JCI14789. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Ayano G., Duko B., Bedaso A. The prevalence of post-traumatic stress disorder among people living with HIV/AIDS: a systematic review and meta-analysis. Psychiatr. Q. 2020;91:1317–1332. doi: 10.1007/s11126-020-09849-9. [DOI] [PubMed] [Google Scholar]
  4. Bacon M.C., von Wyl V., Alden C., Sharp G., Robison E., Hessol N., Gange S., Barranday Y., Holman S., Weber K., Young M.A. The Women's Interagency HIV Study: an observational cohort brings clinical sciences to the bench. Clin. Diagn. Lab. Immunol. 2005;12:1013–1019. doi: 10.1128/CDLI.12.9.1013-1019.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Barkan S.E., Melnick S.L., Preston-Martin S., Weber K., Kalish L.A., Miotti P., Young M., Greenblatt R., Sacks H., Feldman J. The women's interagency HIV study. WIHS collaborative study Group. Epidemiology. 1998;9:117–125. [PubMed] [Google Scholar]
  6. Barnova M., Bobcakova A., Urdova V., Kosturiak R., Kapustova L., Dobrota D., Jesenak M. Inhibitory immune checkpoint molecules and exhaustion of T cells in COVID-19. Physiol. Res./Acad. Sci. Bohemoslov. 2021;70:S227–S247. doi: 10.33549/physiolres.934757. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Benova K., Hanckova M., Koci K., Kudelova M., Betakova T. T cells and their function in the immune response to viruses. Acta Virol. 2020;64:131–143. doi: 10.4149/av_2020_203. [DOI] [PubMed] [Google Scholar]
  8. Bertin J., Jalaguier P., Barat C., Roy M.A., Tremblay M.J. Exposure of human astrocytes to leukotriene C4 promotes a CX3CL1/fractalkine-mediated transmigration of HIV-1-infected CD4(+) T cells across an in vitro blood-brain barrier model. Virology. 2014;454–455:128–138. doi: 10.1016/j.virol.2014.02.007. [DOI] [PubMed] [Google Scholar]
  9. Beurel E., Lowell J.A. Th17 cells in depression. Brain Behav. Immun. 2018;69:28–34. doi: 10.1016/j.bbi.2017.08.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Birdsall H.H., Trial J., Lin H.J., Green D.M., Sorrentino G.W., Siwak E.B., de Jong A.L., Rossen R.D. Transendothelial migration of lymphocytes from HIV-1-infected donors: a mechanism for extravascular dissemination of HIV-1. J. Immunol. 1997;158:5968–5977. [PubMed] [Google Scholar]
  11. Bjorn-Helge M., Hovde K., Hiemstra P. 2019. Partial Least Squares and Principal Component Regression. [Google Scholar]
  12. Blank C.U., Haining W.N., Held W., Hogan P.G., Kallies A., Lugli E., Lynn R.C., Philip M., Rao A., Restifo N.P., Schietinger A., Schumacher T.N., Schwartzberg P.L., Sharpe A.H., Speiser D.E., Wherry E.J., Youngblood B.A., Zehn D. Defining 'T cell exhaustion. Nat. Rev. Immunol. 2019;19:665–674. doi: 10.1038/s41577-019-0221-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Bohineust A., Garcia Z., Beuneu H., Lemaitre F., Bousso P. Termination of T cell priming relies on a phase of unresponsiveness promoting disengagement from APCs and T cell division. J. Exp. Med. 2018;215:1481–1492. doi: 10.1084/jem.20171708. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Brasanac J., Ramien C., Gamradt S., Taenzer A., Glau L., Ritter K., Patas K., Agorastos A., Wiedemann K., Demiralay C., Fischer F., Otte C., Bellmann-Strobl J., Friese M.A., Tolosa E., Paul F., Heesen C., Weygandt M., Gold S.M. Immune signature of multiple sclerosis-associated depression. Brain Behav. Immun. 2021;100:174–182. doi: 10.1016/j.bbi.2021.11.022. [DOI] [PubMed] [Google Scholar]
  15. Brochard V., Combadiere B., Prigent A., Laouar Y., Perrin A., Beray-Berthat V., Bonduelle O., Alvarez-Fischer D., Callebert J., Launay J.M., Duyckaerts C., Flavell R.A., Hirsch E.C., Hunot S. Infiltration of CD4+ lymphocytes into the brain contributes to neurodegeneration in a mouse model of Parkinson disease. J. Clin. Invest. 2009;119:182–192. doi: 10.1172/JCI36470. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Budimir N., Thomas G.D., Dolina J.S., Salek-Ardakani S. Cancer Immunol Res; 2021. Reversing T-Cell Exhaustion in Cancer: Lessons Learned from PD-1/PD-L1 Immune Checkpoint Blockade. [DOI] [PubMed] [Google Scholar]
  17. Buggert M., Tauriainen J., Yamamoto T., Frederiksen J., Ivarsson M.A., Michaelsson J., Lund O., Hejdeman B., Jansson M., Sonnerborg A., Koup R.A., Betts M.R., Karlsson A.C. T-bet and Eomes are differentially linked to the exhausted phenotype of CD8+ T cells in HIV infection. PLoS Pathog. 2014;10 doi: 10.1371/journal.ppat.1004251. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Casazza J.P., Betts M.R., Picker L.J., Koup R.A. Decay kinetics of human immunodeficiency virus-specific CD8+ T cells in peripheral blood after initiation of highly active antiretroviral therapy. J. Virol. 2001;75:6508–6516. doi: 10.1128/JVI.75.14.6508-6516.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Castelli V., Lombardi A., Palomba E., Bozzi G., Ungaro R., Alagna L., Mangioni D., Muscatello A., Bandera A., Gori A. Immune checkpoint inhibitors in people living with HIV/AIDS: facts and controversies. Cells. 2021;10 doi: 10.3390/cells10092227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Castro Dias M., Odriozola Quesada A., Soldati S., Bosch F., Gruber I., Hildbrand T., Sonmez D., Khire T., Witz G., McGrath J.L., Piontek J., Kondoh M., Deutsch U., Zuber B., Engelhardt B. Brain endothelial tricellular junctions as novel sites for T cell diapedesis across the blood-brain barrier. J. Cell Sci. 2021;134 doi: 10.1242/jcs.253880. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Cheema A., Mathias K., Bui C., Dunham S.R., Goodman J.C., El Sahly H.M. CD8 encephalitis in a treatment-naive and a virologically suppressed patient with HIV. Can. J. Neurol. Sci. 2019;46:773–775. doi: 10.1017/cjn.2019.288. [DOI] [PubMed] [Google Scholar]
  22. Clayton K.L., Collins D.R., Lengieza J., Ghebremichael M., Dotiwala F., Lieberman J., Walker B.D. Resistance of HIV-infected macrophages to CD8(+) T lymphocyte-mediated killing drives activation of the immune system. Nat. Immunol. 2018;19:475–486. doi: 10.1038/s41590-018-0085-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Cohen H., Ziv Y., Cardon M., Kaplan Z., Matar M.A., Gidron Y., Schwartz M., Kipnis J. Maladaptation to mental stress mitigated by the adaptive immune system via depletion of naturally occurring regulatory CD4+CD25+ cells. J. Neurobiol. 2006;66:552–563. doi: 10.1002/neu.20249. [DOI] [PubMed] [Google Scholar]
  24. Cohen S., Kamarck T., Mermelstein R. A global measure of perceived stress. J. Health Soc. Behav. 1983;24:385–396. [PubMed] [Google Scholar]
  25. Cohen S., Williamson G. In: The Social Psychology of Health: Claremont Symposium on Applied Social Psychology. Spacapan S., Oskamp S., editors. Sage; Newbury Park, CA: 1988. Perceived stress in a probability sample of the United States. [Google Scholar]
  26. Fenwick C., Joo V., Jacquier P., Noto A., Banga R., Perreau M., Pantaleo G. T-cell exhaustion in HIV infection. Immunol. Rev. 2019;292:149–163. doi: 10.1111/imr.12823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Ganesh A., Lemongello D., Lee E., Peterson J., McLaughlin B.E., Ferre A.L., Gillespie G.M., Fuchs D., Deeks S.G., Hunt P.W., Price R.W., Spudich S.S., Shacklett B.L. Immune activation and HIV-specific CD8(+) T cells in cerebrospinal fluid of HIV controllers and noncontrollers. AIDS Res. Hum. Retrovir. 2016;32:791–800. doi: 10.1089/aid.2015.0313. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Geladi P., Kowalski B.R. Partial least-squares regression: a tutorial. Anal. Chim. Acta. Anal. Chim. Acta. 1986;185:1–17. [Google Scholar]
  29. Helleberg M., Kronborg G., Ullum H., Ryder L.P., Obel N., Gerstoft J. Course and clinical significance of CD8+ T-cell counts in a large cohort of HIV-infected individuals. J. Infect. Dis. 2015;211:1726–1734. doi: 10.1093/infdis/jiu669. [DOI] [PubMed] [Google Scholar]
  30. Ho E.L., Ronquillo R., Altmeppen H., Spudich S.S., Price R.W., Sinclair E. Cellular composition of cerebrospinal fluid in HIV-1 infected and uninfected subjects. PLoS One. 2013;8 doi: 10.1371/journal.pone.0066188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Hunt P.W., Martin J.N., Sinclair E., Bredt B., Hagos E., Lampiris H., Deeks S.G. T cell activation is associated with lower CD4+ T cell gains in human immunodeficiency virus-infected patients with sustained viral suppression during antiretroviral therapy. J. Infect. Dis. 2003;187:1534–1543. doi: 10.1086/374786. [DOI] [PubMed] [Google Scholar]
  32. Hwang J.R., Byeon Y., Kim D., Park S.G. Recent insights of T cell receptor-mediated signaling pathways for T cell activation and development. Exp. Mol. Med. 2020;52:750–761. doi: 10.1038/s12276-020-0435-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Im S.J., Ha S.J. Re-Defining T-cell exhaustion: subset, function, and regulation. Immune Netw. 2020;20 doi: 10.4110/in.2020.20.e2. e2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Ishiguro M., Ueno Y., Ishiguro Y., Takanashi M., Murai K., Taieb G., Daida K., Suda A., Yokoyama K., Naito T., Hattori N. CD8(+) T-cell encephalitis mimicking PRES in AIDS: a case report. BMC Neurol. 2020;20:179. doi: 10.1186/s12883-020-01756-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Jain S., Stock A., Macian F., Putterman C. A distinct T follicular helper cell subset infiltrates the brain in murine neuropsychiatric lupus. Front. Immunol. 2018;9:487. doi: 10.3389/fimmu.2018.00487. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Joseph S.B., Arrildt K.T., Sturdevant C.B., Swanstrom R. HIV-1 target cells in the CNS. J. Neurovirol. 2015;21:276–289. doi: 10.1007/s13365-014-0287-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Jost S., Tomezsko P.J., Rands K., Toth I., Lichterfeld M., Gandhi R.T., Altfeld M. CD4+ T-cell help enhances NK cell function following therapeutic HIV-1 vaccination. J. Virol. 2014;88:8349–8354. doi: 10.1128/JVI.00924-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Juno J.A., van Bockel D., Kent S.J., Kelleher A.D., Zaunders J.J., Munier C.M. Cytotoxic CD4 T cells-friend or foe during viral infection? Front. Immunol. 2017;8:19. doi: 10.3389/fimmu.2017.00019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Kant R., Pasi S., Surolia A. Auto-reactive Th17-cells trigger obsessive-compulsive-disorder like behavior in mice with experimental autoimmune encephalomyelitis. Front. Immunol. 2018;9:2508. doi: 10.3389/fimmu.2018.02508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Kessing C.F., Spudich S., Valcour V., Cartwright P., Chalermchai T., Fletcher J.L., Takata H., Nichols C., Josey B.J., Slike B., Krebs S.J., Sailsuta N., Lerdlum S., Jagodzinski L., Tipsuk S., Suttichom D., Rattanamanee S., Zetterberg H., Hellmuth J., Phanuphak N., Robb M.L., Michael N.L., Ananworanich J., Trautmann L. High number of activated CD8+ T cells targeting HIV antigens are present in cerebrospinal fluid in acute HIV infection. J. Acquir. Immune Defic. Syndr. 2017;75:108–117. doi: 10.1097/QAI.0000000000001301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Kipnis J., Cohen H., Cardon M., Ziv Y., Schwartz M. T cell deficiency leads to cognitive dysfunction: implications for therapeutic vaccination for schizophrenia and other psychiatric conditions. Proc. Natl. Acad. Sci. U. S. A. 2004;101:8180–8185. doi: 10.1073/pnas.0402268101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Kipnis J., Gadani S., Derecki N.C. Pro-cognitive properties of T cells. Nat. Rev. Immunol. 2012;12:663–669. doi: 10.1038/nri3280. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Klein S.L., Flanagan K.L. Sex differences in immune responses. Nat. Rev. Immunol. 2016;16:626–638. doi: 10.1038/nri.2016.90. [DOI] [PubMed] [Google Scholar]
  44. Laumet G., Edralin J.D., Dantzer R., Heijnen C.J., Kavelaars A. CD3(+) T cells are critical for the resolution of comorbid inflammatory pain and depression-like behavior. Neurobiol. Pain. 2020;7 doi: 10.1016/j.ynpai.2020.100043. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Leon-Rivera R., Veenstra M., Donoso M., Tell E., Eugenin E.A., Morgello S., Berman J.W. Central nervous system (CNS) viral seeding by mature monocytes and potential therapies to reduce CNS viral reservoirs in the cART era. mBio. 2021;12 doi: 10.1128/mBio.03633-20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Lescure F.X., Moulignier A., Savatovsky J., Amiel C., Carcelain G., Molina J.M., Gallien S., Pacanovski J., Pialoux G., Adle-Biassette H., Gray F. CD8 encephalitis in HIV-infected patients receiving cART: a treatable entity. Clin. Infect. Dis. 2013;57:101–108. doi: 10.1093/cid/cit175. [DOI] [PubMed] [Google Scholar]
  47. Lynall M.E., Turner L., Bhatti J., Cavanagh J., de Boer P., Mondelli V., Jones D., Drevets W.C., Cowen P., Harrison N.A., Pariante C.M., Pointon L., Clatworthy M.R., Bullmore E., Neuroimmunology of Mood D., Alzheimer's Disease C. Peripheral blood cell-stratified subgroups of inflamed depression. Biol. Psychiatr. 2020;88:185–196. doi: 10.1016/j.biopsych.2019.11.017. [DOI] [PubMed] [Google Scholar]
  48. Markle J.G., Fish E.N. SeXX matters in immunity. Trends Immunol. 2014;35:97–104. doi: 10.1016/j.it.2013.10.006. [DOI] [PubMed] [Google Scholar]
  49. Martens H., Martens M. Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR) Food Qual. Prefer. 2000;11:5–16. [Google Scholar]
  50. Martinez F.O., Gordon S. The M1 and M2 paradigm of macrophage activation: time for reassessment. F1000Prime Rep. 2014;6:13. doi: 10.12703/P6-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Migueles S.A., Weeks K.A., Nou E., Berkley A.M., Rood J.E., Osborne C.M., Hallahan C.W., Cogliano-Shutta N.A., Metcalf J.A., McLaughlin M., Kwan R., Mican J.M., Davey R.T., Jr., Connors M. Defective human immunodeficiency virus-specific CD8+ T-cell polyfunctionality, proliferation, and cytotoxicity are not restored by antiretroviral therapy. J. Virol. 2009;83:11876–11889. doi: 10.1128/JVI.01153-09. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Mollet L., Li T.S., Samri A., Tournay C., Tubiana R., Calvez V., Debre P., Katlama C., Autran B. Dynamics of HIV-specific CD8+ T lymphocytes with changes in viral load.The RESTIM and COMET Study Groups. J. Immunol. 2000;165:1692–1704. doi: 10.4049/jimmunol.165.3.1692. [DOI] [PubMed] [Google Scholar]
  53. Nishihara H., Soldati S., Mossu A., Rosito M., Rudolph H., Muller W.A., Latorre D., Sallusto F., Sospedra M., Martin R., Ishikawa H., Tenenbaum T., Schroten H., Gosselet F., Engelhardt B. Human CD4(+) T cell subsets differ in their abilities to cross endothelial and epithelial brain barriers in vitro. Fluids Barriers CNS. 2020;17:3. doi: 10.1186/s12987-019-0165-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Ogg G.S., Jin X., Bonhoeffer S., Moss P., Nowak M.A., Monard S., Segal J.P., Cao Y., Rowland-Jones S.L., Hurley A., Markowitz M., Ho D.D., McMichael A.J., Nixon D.F. Decay kinetics of human immunodeficiency virus-specific effector cytotoxic T lymphocytes after combination antiretroviral therapy. J. Virol. 1999;73:797–800. doi: 10.1128/jvi.73.1.797-800.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Oliveira-Giacomelli A., Petiz L.L., Andrejew R., Turrini N., Silva J.B., Sack U., Ulrich H. Role of P2X7 receptors in immune responses during neurodegeneration. Front. Cell. Neurosci. 2021;15 doi: 10.3389/fncel.2021.662935. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Pawelec G. Is there a positive side to T cell exhaustion? Front. Immunol. 2019;10:111. doi: 10.3389/fimmu.2019.00111. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Perdomo-Celis F., Feria M.G., Taborda N.A., Rugeles M.T. A low frequency of IL-17-producing CD8(+) T-cells is associated with persistent immune activation in people living with HIV despite HAART-induced viral suppression. Front. Immunol. 2018;9:2502. doi: 10.3389/fimmu.2018.02502. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Peters B.A., Sheira L.A., Hanna D.B., Qi Q., Sharma A., Adedimeji A., Wilson T., Merenstein D., Tien P.C., Cohen M., Wentz E.L., Kinslow J., Landay A.L., Weiser S.D. Food insecurity and T-cell dysregulation in women living with human immunodeficiency virus on antiretroviral therapy. Clin. Infect. Dis. 2021;72:e112–e119. doi: 10.1093/cid/ciaa1771. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Poletti S., de Wit H., Mazza E., Wijkhuijs A.J.M., Locatelli C., Aggio V., Colombo C., Benedetti F., Drexhage H.A. Th17 cells correlate positively to the structural and functional integrity of the brain in bipolar depression and healthy controls. Brain Behav. Immun. 2017;61:317–325. doi: 10.1016/j.bbi.2016.12.020. [DOI] [PubMed] [Google Scholar]
  60. Prasad S., Sheng W.S., Hu S., Chauhan P., Lokensgard J.R. Dysregulated microglial cell activation and proliferation following repeated antigen stimulation. Front. Cell. Neurosci. 2021;15 doi: 10.3389/fncel.2021.686340. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Qiu Y.M., Zhang C.L., Chen A.Q., Wang H.L., Zhou Y.F., Li Y.N., Hu B. Immune cells in the BBB disruption after acute ischemic Stroke: targets for immune therapy? Front. Immunol. 2021;12 doi: 10.3389/fimmu.2021.678744. [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Radloff L.S. The CES-D Scale: a self-report depression scale for research in the general population. Appl. Psychol. Meas. 1977;1:385–401. [Google Scholar]
  63. Rainho J.N., Martins M.A., Cunyat F., Watkins I.T., Watkins D.I., Stevenson M. Nef is dispensable for resistance of simian immunodeficiency virus-infected macrophages to CD8+ T cell killing. J. Virol. 2015;89:10625–10636. doi: 10.1128/JVI.01699-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Ratto-Kim S., Schuetz A., Sithinamsuwan P., Barber J., Hutchings N., Lerdlum S., Fletcher J.L.K., Phuang-Ngern Y., Chuenarom W., Tipsuk S., Pothisri M., Jadwattanakul T., Jirajariyavej S., Sajjaweerawan C., Akapirat S., Chalermchai T., Suttichom D., Kaewboon B., Prueksakaew P., Karnsomlap P., Clifford D., Paul R.H., de Souza M.S., Kim J.H., Ananworanich J., Valcour V. Characterization of cellular immune responses in Thai individuals with and without HIV-associated neurocognitive disorders. AIDS Res. Hum. Retrovir. 2018;34:685–689. doi: 10.1089/aid.2017.0237. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Rezaei S., Ahmadi S., Rahmati J., Hosseinifard H., Dehnad A., Aryankhesal A., Shabaninejad H., Ghasemyani S., Alihosseini S., Bragazzi N.L., Raoofi S., Kiaee Z.M., Ghashghaee A. Global prevalence of depression in HIV/AIDS: a systematic review and meta-analysis. BMJ Support. Palliat. Care. 2019;9:404–412. doi: 10.1136/bmjspcare-2019-001952. [DOI] [PubMed] [Google Scholar]
  66. Rinaldo C.R., Jr., Huang X.L., Fan Z., Margolick J.B., Borowski L., Hoji A., Kalinyak C., McMahon D.K., Riddler S.A., Hildebrand W.H., Day R.B., Mellors J.W. Anti-human immunodeficiency virus type 1 (HIV-1) CD8(+) T-lymphocyte reactivity during combination antiretroviral therapy in HIV-1-infected patients with advanced immunodeficiency. J. Virol. 2000;74:4127–4138. doi: 10.1128/jvi.74.9.4127-4138.2000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Rodriguez N., Morer A., Gonzalez-Navarro E.A., Serra-Pages C., Boloc D., Torres T., Martinez-Pinteno A., Mas S., Lafuente A., Gasso P., Lazaro L. Altered frequencies of Th17 and Treg cells in children and adolescents with obsessive-compulsive disorder. Brain Behav. Immun. 2019;81:608–616. doi: 10.1016/j.bbi.2019.07.022. [DOI] [PubMed] [Google Scholar]
  68. Ron-Harel N., Segev Y., Lewitus G.M., Cardon M., Ziv Y., Netanely D., Jacob-Hirsch J., Amariglio N., Rechavi G., Domany E., Schwartz M. Age-dependent spatial memory loss can be partially restored by immune activation. Rejuvenation Res. 2008;11:903–913. doi: 10.1089/rej.2008.0755. [DOI] [PubMed] [Google Scholar]
  69. Rubin L.H., Maki P.M., Springer G., Benning L., Anastos K., Gustafson D., Villacres M.C., Jiang X., Adimora A.A., Waldrop-Valverde D., Vance D.E., Bolivar H., Alden C., Martin E.M., Valcour V.G., Women's Interagency H.I.V.S. Cognitive trajectories over 4 years among HIV-infected women with optimal viral suppression. Neurology. 2017;89:1594–1603. doi: 10.1212/WNL.0000000000004491. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Rubin L.H., Neigh G.N., Sundermann E.E., Xu Y., Scully E.P., Maki P.M. Sex differences in neurocognitive function in adults with HIV: patterns, predictors, and mechanisms. Curr. Psychiatr. Rep. 2019;21:94. doi: 10.1007/s11920-019-1089-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Rubin L.H., Radtke K.K., Eum S., Tamraz B., Kumanan K.N., Springer G., Maki P.M., Anastos K., Merenstein D., Karim R., Weber K.M., Gustafson D., Greenblatt R.M., Bishop J.R. Cognitive burden of common non-antiretroviral medications in HIV-infected women. J. Acquir. Immune Defic. Syndr. 2018;79(1):83–91. doi: 10.1097/QAI.0000000000001755. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Rubin L.H., Springer G., Martin E.M., Seaberg E.C., Sacktor N.C., Levine A., Valcour V.G., Young M.A., Becker J.T., Maki P.M. Elevated depressive symptoms are a stronger predictor of executive dysfunction in HIV-infected women than in men. J. Acquir. Immune Defic. Syndr. 2019;81:274–283. doi: 10.1097/QAI.0000000000002029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Rubin L.H., Sundermann E.E., Dastgheyb R., Buchholz A.S., Pasipanodya E., Heaton R.K., Grant I., Ellis R., Moore D.J. Sex differences in the patterns and predictors of cognitive function in HIV. Front. Neurol. 2020;11 doi: 10.3389/fneur.2020.551921. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Rubin L.H., Xu Y., Norris P.J., Wang X., Dastgheyb R., Fitzgerald K.C., Keating S.M., Kaplan R.C., Maki P.M., Anastos K., Springer G., Benning L., Kassaye S., Gustafson D.R., Valcour V.G., Williams D.W. Early inflammatory signatures predict subsequent cognition in long-term virally suppressed women with HIV. Front. Integr. Neurosci. 2020;14:20. doi: 10.3389/fnint.2020.00020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Santana L.M., Valadares E.A., Ferreira-Junior C.U., Santos M.F., Albergaria B.H., Rosa-Junior M. CD8 + T-lymphocyte encephalitis: a systematic review. AIDS Rev. 2020;22:112–122. doi: 10.24875/AIDSRev.20000132. [DOI] [PubMed] [Google Scholar]
  76. Schrier R.D., Hong S., Crescini M., Ellis R., Perez-Santiago J., Spina C., Letendre S., Group H. Cerebrospinal fluid (CSF) CD8+ T-cells that express interferon-gamma contribute to HIV associated neurocognitive disorders (HAND) PLoS One. 2015;10 doi: 10.1371/journal.pone.0116526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Shi W., Zhang S., Lu Y., Wang Y., Zhao J., Li L. T cell responses in depressed mice induced by chronic unpredictable mild stress. J. Affect. Disord. 2022;296:150–156. doi: 10.1016/j.jad.2021.09.064. [DOI] [PubMed] [Google Scholar]
  78. Swain S.L., McKinstry K.K., Strutt T.M. Expanding roles for CD4(+) T cells in immunity to viruses. Nat. Rev. Immunol. 2012;12:136–148. doi: 10.1038/nri3152. [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Tanko R.F., Soares A.P., Masson L., Garrett N.J., Samsunder N., Abdool Karim Q., Abdool Karim S.S., Riou C., Burgers W.A. Residual T cell activation and skewed CD8+ T cell memory differentiation despite antiretroviral therapy-induced HIV suppression. Clin. Immunol. 2018;195:127–138. doi: 10.1016/j.clim.2018.06.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Tian B., Yang C., Wang J., Hou X., Zhao S., Li Y., Yang P. Peripheral blood brain-derived neurotrophic factor level and tyrosine kinase B expression on T lymphocytes in systemic lupus erythematosus: implications for systemic involvement. Cytokine. 2019;123 doi: 10.1016/j.cyto.2019.154764. [DOI] [PubMed] [Google Scholar]
  81. Trautmann L., Janbazian L., Chomont N., Said E.A., Gimmig S., Bessette B., Boulassel M.R., Delwart E., Sepulveda H., Balderas R.S., Routy J.P., Haddad E.K., Sekaly R.P. Upregulation of PD-1 expression on HIV-specific CD8+ T cells leads to reversible immune dysfunction. Nat. Med. 2006;12:1198–1202. doi: 10.1038/nm1482. [DOI] [PubMed] [Google Scholar]
  82. Trautmann L., Mbitikon-Kobo F.M., Goulet J.P., Peretz Y., Shi Y., Van Grevenynghe J., Procopio F.A., Boulassel M.R., Routy J.P., Chomont N., Haddad E.K., Sekaly R.P. Profound metabolic, functional, and cytolytic differences characterize HIV-specific CD8 T cells in primary and chronic HIV infection. Blood. 2012;120:3466–3477. doi: 10.1182/blood-2012-04-422550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Vecchio A.C., Williams D.W., Xu Y., Yu D., Saylor D., Lofgren S., O’Toole R., Boulware D.R., Nakasujja N., Nakigozi G., Kisakye A., Batte J., Mayanja R., Anok A., Reynolds S.J., Quinn T.C., Gray R.H., Wawer M.J., Sacktor N., Rubin L.H. Sex-specific associations between cerebrospinal fluid inflammatory marker levels and cognitive function in antiretroviral treated people living with HIV in rural Uganda. Brain Behav. Immun. 2020;93:111–118. doi: 10.1016/j.bbi.2020.12.021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  84. Veenhuis R.T., Williams D.W., Shirk E.N., Abreu C.M., Ferreira E.A., Coughlin J.M., Brown T.T., Maki P.M., Anastos K., Berman J.W., Clements J.E., Rubin L.H. Higher circulating intermediate monocytes are associated with cognitive function in women with HIV. JCI Insight. 2021;6 doi: 10.1172/jci.insight.146215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  85. Vieira M.M., Ferreira T.B., Pacheco P.A., Barros P.O., Almeida C.R., Araujo-Lima C.F., Silva-Filho R.G., Hygino J., Andrade R.M., Linhares U.C., Andrade A.F., Bento C.A. Enhanced Th17 phenotype in individuals with generalized anxiety disorder. J. Neuroimmunol. 2010;229:212–218. doi: 10.1016/j.jneuroim.2010.07.018. [DOI] [PubMed] [Google Scholar]
  86. Wang J., Wu X., Lai W., Long E., Zhang X., Li W., Zhu Y., Chen C., Zhong X., Liu Z., Wang D., Lin H. Prevalence of depression and depressive symptoms among outpatients: a systematic review and meta-analysis. BMJ Open. 2017;7 doi: 10.1136/bmjopen-2017-017173. [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Wang Y., Liu M., Lu Q., Farrell M., Lappin J.M., Shi J., Lu L., Bao Y. Global prevalence and burden of HIV-associated neurocognitive disorder: a meta-analysis. Neurology. 2020;95(19):e2610–e2621. doi: 10.1212/WNL.0000000000010752. [DOI] [PubMed] [Google Scholar]
  88. Wang Y.Q., Pan Y., Zhu S., Wang Y.G., Shen Z.H., Wang K. Selective impairments of alerting and executive control in HIV-infected patients: evidence from attention network test. Behav. Brain Funct. 2017;13:11. doi: 10.1186/s12993-017-0129-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  89. Weathers F.W., Huska J.A., Keane T.M. In: PCL-C for DSM-IV. Division N.C., editor. 1991. Boston. [Google Scholar]
  90. Westfall S., Caracci F., Zhao D., Wu Q.L., Frolinger T., Simon J., Pasinetti G.M. Microbiota metabolites modulate the T helper 17 to regulatory T cell (Th17/Treg) imbalance promoting resilience to stress-induced anxiety- and depressive-like behaviors. Brain Behav. Immun. 2021;91:350–368. doi: 10.1016/j.bbi.2020.10.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Williams D.W., Veenstra M., Gaskill P.J., Morgello S., Calderon T.M., Berman J.W. Monocytes mediate HIV neuropathogenesis: mechanisms that contribute to HIV associated neurocognitive disorders. Curr. HIV Res. 2014;12:85–96. doi: 10.2174/1570162x12666140526114526. [DOI] [PMC free article] [PubMed] [Google Scholar]
  92. Woelfer M., Kasties V., Kahlfuss S., Walter M. The role of depressive subtypes within the neuroinflammation hypothesis of major depressive disorder. Neuroscience. 2019;403:93–110. doi: 10.1016/j.neuroscience.2018.03.034. [DOI] [PubMed] [Google Scholar]
  93. Wolf S.A., Steiner B., Akpinarli A., Kammertoens T., Nassenstein C., Braun A., Blankenstein T., Kempermann G. CD4-positive T lymphocytes provide a neuroimmunological link in the control of adult hippocampal neurogenesis. J. Immunol. 2009;182:3979–3984. doi: 10.4049/jimmunol.0801218. [DOI] [PubMed] [Google Scholar]
  94. Woolley J.D., Khan B.K., Murthy N.K., Miller B.L., Rankin K.P. The diagnostic challenge of psychiatric symptoms in neurodegenerative disease: rates of and risk factors for prior psychiatric diagnosis in patients with early neurodegenerative disease. J. Clin. Psychiatr. 2011;72:126–133. doi: 10.4088/JCP.10m06382oli. [DOI] [PMC free article] [PubMed] [Google Scholar]
  95. Zhang B., Gensel J.C. Is neuroinflammation in the injured spinal cord different than in the brain? Examining intrinsic differences between the brain and spinal cord. Exp. Neurol. 2014;258:112–120. doi: 10.1016/j.expneurol.2014.04.007. [DOI] [PubMed] [Google Scholar]
  96. Ziv Y., Ron N., Butovsky O., Landa G., Sudai E., Greenberg N., Cohen H., Kipnis J., Schwartz M. Immune cells contribute to the maintenance of neurogenesis and spatial learning abilities in adulthood. Nat. Neurosci. 2006;9:268–275. doi: 10.1038/nn1629. [DOI] [PubMed] [Google Scholar]

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