Abstract
Background.
HIV-associated neurocognitive disorder persists in some people living with HIV despite optimal antiretroviral therapy. Latent tuberculosis infection (LTBI) may cause systemic inflammation and immune activation that may impair brain function. We assessed cognition and biomarkers of inflammation in both HIV+ and HIV− South Indians with and without LTBI.
Methods.
Adults (≥ 18 years old) with and without HIV infection were screened for LTBI by Interferon-Gamma Release Assays, completed comprehensive neurocognitive assessments, and underwent measurement of serum inflammatory biomarker levels.
Results.
The participants (n=119) were HIV+/LTBI+ (n=15), HIV+/LTBI− (n=50), HIV−/LTBI+ (n=26), and HIV−/LTBI− (n=28). HIV+ participants, regardless of LTBI status, had more impaired global deficit scores (GDS) than HIV− participants (OR=3.42, p=0.028, adjusted for sex and education differences). Neither GDS nor impairment rates differed in the LTBI+ compared with the LTBI− group (p=0.79 and p=0.41, respectively). The mean log10 IL-6 and MCP-1 values were significantly higher and hsCRP lower in the LTBI+ compared with the LTBI− group (p=0.044, 0.023, and 0.03 respectively, adjusting for HIV status and sex).
Conclusions.
In this cross-sectional study of South Indians, HIV infection, but not LTBI, was associated with increased neurocognitive impairment (NCI). Pro-inflammatory biomarkers (IL-6 and MCP-1, but not TNF-α) were elevated in the LTBI+ compared to the LTBI− groups. Biomarkers of immune activation (IFN-γ, MIP-1β, IL-2, IP-10, RANTES, and IL-22) did not differ between these groups. Larger longitudinal studies should be done to confirm our findings that the effect of LTBI on systemic inflammation or NCI is likely small.
Keywords: Latent tuberculosis infection (LTBI), HIV-1 infection, neurocognitive impairment (NCI), HIV-associated neurocognitive disorders (HAND), systemic inflammation
Introduction
Human Immunodeficiency Virus (HIV)-1 can cause HIV-associated neurocognitive disorder (HAND), a syndrome of neurocognitive impairment (NCI) resulting in varying degrees of impaired activities of daily living and reduced quality of life [1]. HAND persists in some people living with HIV (PLWH) despite optimal antiretroviral therapy (ART) that suppresses virus in the blood [1, 2]. Up to 44% of PLWH on ART meet the criteria for milder forms of HAND. The pathophysiology of HAND in patients with undetectable virus in blood due to ART is not well understood, but systemic and CSF inflammation have been implicated [3]. Chronic comorbidities such as diabetes, central obesity and subclinical co-infections with Hepatitis C virus, Cytomegalovirus, and Toxoplasma gondii have been linked to NCI and systemic inflammation [3-8]. Since comorbidities may be undetected and untreated, these are missed opportunities for interventions that could treat NCI.
The AIDS Clinical Trial Group recently found that active TB among HIV+ patients was associated with higher rate of NCI compared to those without active TB [9]. Similarly, global and domain-specific cognitive deficits were more prevalent in HIV+ Zambians with active pulmonary TB compared to those without TB and HIV−/TB− group [10]. This effect of active TB remained after correcting for CD4+ T-cell count and viral load. Both, active and latent TB have been associated with increased immune activation [11, 12]. Pro-Inflammatory cytokines (IL-12, IFN-γ, TNF-α) and CD4 T-cells are critical immune factors for controlling LTBI by maintaining granuloma formation [13]. However, soluble markers of systemic inflammation such as IL-8, IL-6, IP-10, CRP, sCD14, and hyaluronic acid are not elevated in HIV-uninfected persons with LTBI [11].
We hypothesized that LTBI might impair brain function by increasing systemic inflammation in PLWH. Thus, we assessed cognition and biomarkers of inflammation in both HIV+ and HIV− South Indians with and without LTBI.
Methods
Participants.
This study was conducted in Chennai, India, where HIV and TB co-infections are common [14]. Adults (≥ 18 years old) presenting to the Infectious Diseases Medical Centre at the Voluntary Health Services (VHS) Hospital in Chennai, India for HIV testing or treatment were approached for inclusion and studied before ART treatment was started. Thus, those with a current symptoms of pulmonary TB or a past history of active TB or treatment for possible or proven LTBI were excluded. Reinfection with a second strain of Mycobacterium tuberculosis can occur after treatment of LTBI with isoniazid in highly TB endemic areas like India.
Participants (n=119) without a confounding condition that could impact their performance on neurocognitive testing such as a history of CNS infections, strokes, active severe deression or psychosis, or organ system failure were recruited from April 2010 to September 2013. Although advised in the current national guidelines, treatment for LTBI was not offered as it was not the standard of care at the time of the study. Human data included in this manuscript was obtained and stored in compliance with regulations of the Indian Council of Medical Research and the Institutional Review Boards of the University of California, San Diego and VHS Hospital. All participants provided written informed consent.
Neurocognitive functioning assessments.
Cognition was assessed in Tamil using a comprehensive neurocognitive test battery described previously that assessed 7 cognitive domains: learning, delayed recall, attention/working memory, speed of information processing, verbal fluency, executive functions, and complex motor skills [15, 16]. Demographically corrected normative values for the neurocognitive tests adjusted for age, education, and sex were obtained using data from the HIV− participants [15-17]. Individual test scores were combined to create global deficit scores (GDS) and domain-specific deficit scores (DDS) that ranged from 0 (normal cognition) to 5 (severely impaired) [15]. The GDS detects impairment if performance is lower than expected for age and education in at least two domains and ignores higher than expected performance. Global NCI was defined as a GDS ≥ 0.5, and domain-specific NCI was defined as DDS > 0.5.
Laboratory assays.
LTBI, HIV, and serum biomarkers (IFN-γ, IL-6, TNF-α, MCP-1, MIP-1β, IL-2, IP-10, RANTES, IL-22, and high sensitivity C-reactive protein (hsCRP)) were measured at the same visit as cognition. QuantiFERON-TB Gold assay (Cellestis, Valencia, CA) was used to diagnose LTBI. HIV was diagnosed in accordance with India’s National AIDS Control Organisation HIV testing algorithm. HIV antibodies were qualitatively detected with the Alere Determine HIV-1/2 immunochromatographic test (Alere Medical Co. Ltd, Waltham, MA), the First Response HIV 1–2-0 Card Test (Premier Medical Corporation, Mumbai, India), and HIV TRI-DOT (Diagnostic Enterprises, New Delhi, India). HIV RNA RealTime HIV-1 assay (Abbott Laboratories, Lake Bluff, IL) was used to measure the plasma HIV RNA levels. CD4+ T-cells were quantified by the FlowCARE PLG CD4 assay (Beckman Coulter, Brea, CA). Serum levels of IFN-γ, IL-6, TNF-α, MCP-1, MIP-1β, IL-2, IP-10, RANTES, IL-22, and hsCRP were measured using commercial ELISA kits.
Statistical analysis.
For all testing, required parametric assumptions were verified, and data transformations or nonparametric methods were applied when needed. To achieve a normal distribution, deficit scores were square root transformed, and biomarkers (with the exception of RANTES, which already had a symmetric distribution) were modeled on log10 scale. Two-tailed tests and a 5% significance level were used for hypothesis testing unless indicated otherwise.
The associations of neurocognitive outcomes and biomarkers with HIV and LTBI were investigated with two approaches. One approach used original dichotomous variables for HIV and LTBI diagnoses and regressed cognitive outcomes or biomarkers on HIV status, LTBI status, and their interaction. The interaction was removed if it was not significant, and the effects of HIV and LTBI were assessed alone and controlled for each other. In the second approach, HIV and LTBI were combined into a single variable with four groups: HIV+/LTBI+, HIV+/LTBI, HIV−/LTBI+, and HIV−/LTBI−.
Linear regressions were used for analyzing T-scores, deficit scores, and biomarkers. Effect size for the mean difference in these values between groups was estimated with Cohen’s d. Logistic regression methods were used for cognitive impairment, where odds ratios (ORs) were used for the effect size. Differences in demographic and clinical characteristics between the four groups were compared using ANOVA or Kruskal-Wallis test for means and medians and Chi-square or Fisher’s exact test. Results of pair-wise comparisons were adjusted with false discovery rate (FDR) method. Important covariates that differed between the groups were included into multivariable models for primary outcomes as described in the Results section.
Results
Demographic and HIV and LTBI disease characteristics.
The 119 participants were divided into four groups based on HIV and LTBI status: HIV+/LTBI+ (n=15), HIV+/LTBI− (n=50), HIV−/LTBI+ (n=26), and HIV−/LTBI− (n=28). The 4 groups did not differ by age (p=0.31). HIV+/LTBI− participants had 2.8 fewer years of education than HIV−/LTBI− participants (mean 10 vs 12.8 years, respectively; p=0.002). A greater proportion of HIV+/LTBI+ participants compared with the HIV−/LTBI− group were male (73% vs 18%, p=0.01), therefore analyses were corrected for differences in sex and education between the 4 groups. Among HIV+ participants, the median CD4+ cell counts, and CD4+ T-cell counts < 200 cells/μL were similar in the LTBI+ and LTBI− groups. Only 4 participants had a CD4+ T-cell count < 200 cells/μL. Just over half of the HIV+ participants had an undetectable viral load, and the median viral load among those with detectable virus in blood was similar between HIV+/LTBI+ and HIV+/LTBI− groups. Twenty percent (13/65) of the HIV+ participants reported being on ART at the time of enrollment with higher rates among HIV+/LTBI+ compared with HIV+/LTBI− (43% versus 16%, p=0.06).
NCI by HIV and LTBI status.
The mean GDS for the 4 groups were HIV+/LTBI+ = 0.39, HIV+/LTBI− = 0.39, HIV−/LTBI+ = 0.24, and HIV−/LTBI− = 0.21 (Table 2). HIV+ participants, regardless of LTBI status, had more impaired global deficit scores than HIV− participants (OR=3.42, p=0.028, adjusted for sex and education differences). Neither GDS nor impairment rates differed in the LTBI+ or LTBI− groups (p=0.79 and p=0.41, respectively). There was no significant difference in global T scores in the 4 groups.
Table 2.
Mean deficit scores and percent impaired for each cognitive domain.
| Deficit Scores, mean (SD) | HIV+/LTBI+ N=15 |
HIV+/LTBI− N=50 |
HIV−/LTBI+ N=26 |
HIV−/LTBI− N=28 |
Group Comparisons with p<0.05 |
|---|---|---|---|---|---|
| Global Deficit Score | 0.39 (0.30) | 0.39 (0.37) | 0.24 (0.28) | 0.21 (0.22) | |
| N (%) impaired GDS | 5 (33%) | 14 (28%) | 4 (15%) | 3 (11%) | HIV+>HIV− |
| By Domain: | |||||
| Executive function | 0.37 (0.48) | 0.34 (0.41) | 0.25 (0.41) | 0.22 (0.43) | |
| N (%) impaired | 5 (33%) | 12 (24%) | 5 (19%) | 2 (7%) | |
| Verbal | 0.29 (0.42) | 0.29 (0.49) | 0.26 (0.49) | 0.25 (0.49) | |
| N (%) impaired | 3 (20%) | 13 (26%) | 4 (15%) | 7 (25%) | |
| Working Memory | 0.37 (0.55) | 0.48 (0.74) | 0.25 (0.51) | 0.16 (0.33) | |
| N (%) impaired | 3 (20%) | 14 (28%) | 4 (15%) | 3 (11%) | |
| Learning | 0.50 (0.57) | 0.37 (0.62) | 0.12 (0.21) | 0.29 (0.48) | |
| N (%) impaired | 5 (33%) | 10 (20%) | 0 | 5 (18%) | HIV+/LTBI+, HIV+/LTBI−> HIV−/LTBI+ |
| Memory | 0.30 (0.56) | 0.36 (0.69) | 0.16 (0.40) | 0.39 (0.70) | |
| N (%) impaired | 2 (13%) | 11 (22%) | 3 (12%) | 5 (18%) | |
| Motor | 0.60 (0.97) | 0.41 (0.71) | 0.33 (0.53) | 0.12 (0.26) | |
| N (%) impaired | 4 (27%) | 10 (20%) | 4 (15%) | 1 (4%) | |
| Speed Information Processing | 0.40 (0.47) | 0.46 (0.53) | 0.27 (0.38) | 0.17 (0.22) | |
| N (%) impaired | 5 (33%) | 17 (34%) | 4 (15%) | 1 (4%) | HIV+>HIV− |
SD = standard deviation. P-values for pairwise comparisons were by the analysis of covariance (ANCOVA) models, controlling for education.
We evaluated the combined effect of HIV and LTBI on global and domain-specific deficit scores and T scores in a linear model regressing the cognitive scores on HIV status, LTBI status, and their interaction controlling for sex and education (Tables 2 and 3). A significant interaction was found in a model predicting learning T score (p=0.048), showing that the HIV+/LTBI+ participants had significantly more learning impairment with lower T scores than the HIV−/LTBI+ participants (Cohen’s d=−0.81, p=0.018), but same was not true for HIV+/LTBI− and HIV−/LTBI− groups (p=0.99). Similarly, a logistic model showed a significant interaction of HIV and LTBI on learning impairment (p=0.015). The HIV+ status was associated with higher odds of learning impairment (OR=26.9, p=0.003) in LTBI+ participants. However, few LTBI+ participants (n=5) were learning impaired, resulting in a high uncertainty around the odds ratio of learning impairment in this group. This effect was not found in the LTBI− participants (OR=1.11, p=0.87).
Table 3.
Mean T scores by cognitive domain.
| T score, mean (SD) | HIV+/LTBI+ N=15 |
HIV+/LTBI− N=50 |
HIV−/LTBI+ N=26 |
HIV−/LTBI− N=28 |
P-value |
|---|---|---|---|---|---|
| Global | 48.3 (5.1) | 48.7 (6.2) | 49.7(6.1) | 49.9 (5.0) | 0.50 |
| By Domain: | |||||
| Executive function | 48.9 (8.2) | 49.4 (8.2) | 48.9 (7.6) | 50.3 (6.9) | 0.67 |
| Verbal | 47.4 (7.4) | 49.2 (9.9) | 50.5 (9.7) | 48.8 (8.2) | 0.44 |
| Working Memory | 47.6 (8.3) | 48.0 (9.8) | 49.8 (8.0) | 50.0 (7.3) | 0.88 |
| Learning | 45.1 (7.5) | 49.2 (9.7) | 51.4 (8.0) | 48.3 (8.9) | 0.13 |
| Memory | 47.5 (7.1) | 50.5 (9.5) | 50.5 (7.5) | 48.7 (9.0) | 0.50 |
| Motor | 46.7 (11.6) | 47.3 (10.2) | 49.4 (8.5) | 50.6 (8.4) | 0.82 |
| Speed of Information Processing | 50.0 (6.3) | 47.9 (7.3) | 48.8 (7.0) | 50.9 (5.6) | 0.26 |
SD = standard deviation. P-values were estimated by the analysis of covariance (ANCOVA) models, adjusting for education and sex.
In models controlling for LTBI, sex, and education levels, HIV+ participants were more impaired than HIV− in speed of information processing (SIP, OR=6.77, p=0.002). Pairwise comparisons between the 4 groups showed some marginal differences. Only 1 of 28 (3.6%) HIV-/LTBI− participants was impaired in SIP, whereas 17 of 50 (34%) HIV+/LTBI− participants (p=0.051) and 5 of 15 (33%) HIV+/LTBI+ participants (p=0.057) were impaired.
NCI by HIV subgroup analysis / CD4 T-cell counts and plasma HIV RNA.
HIV+ participants with low CD4+ T-cell counts and high viral loads tended to be more neurocognitively impaired. Although sample sizes are small, and results did not reach statistical significance (p=0.24), global impairment (GDS≥0.5) was more prevalent in HIV+/LTBI+ patients with a detectable viral load than those with an undetectable viral load (3/5 (60%) versus 2/10 (20%), respectively). In HIV+/LTBI− patients, global impairment was found in 8/24 (33%) participants with detectable HIV in blood compared to 6/26 (23%) participants with undetectable HIV, again not a statistically significant difference (p=0.94). The small number of participants in the study limited our power to detect the effects of viral load and CD4+ T-cell counts in the subgroups.
Association of NCI with biomarkers of inflammation.
Table 4 shows results of comparing biomarkers by HIV and LBTI status, adjusting for sex differences. Mean log10 hsCRP was higher (0.16, SD=0.15) in the LTBI− participants than in the LTBI+ participants (0.09, SD=0.21, p=0.03), adjusting for HIV status and sex). Controlling for LTBI status and sex, log10 TNF-α and log10 IL-22 were significantly lower in the HIV+ than the HIV− participants (p=0.015 and 0.017, respectively) (Table 4). Both of these findings were in directions opposite to those we had hypothesized and are unexplained.
Table 4.
Mean biomarker value concentration estimated via multivariable linear regression adjusted for sex.
| Biomarker (log10),mean (SD) |
HIV+/LTBI+ N=15 |
HIV+/LTBI− N=50 |
HIV−/LTBI+ N=26 |
HIV−/LTBI− N=28 |
Significant Group Comparisons (p<0.05) |
|---|---|---|---|---|---|
| hsCRP [mg/dL] | 0.06 (0.05) | 0.17 (0.03) | 0.10 (0.04) | 0.15 (0.04) | LTBI+ < LTBI− |
| IFN-γ [pg/mL] | 1.25 (0.12) | 1.09 (0.06) | 1.06 (0.06) | 1.20 (0.09) | |
| IL-2a [pg/mL] | −0.06 (0.20) | −0.0002 (0.11) | 0.46 (0.15) | 0.07 (0.15) | |
| IL-6 [pg/mL] | 0.65 (0.17) | 0.35 (0.09) | 0.61 (0.13) | 0.38 (0.13) | LTBI+ > LTBI− |
| IL-22 [pg/mL] | 0.35 (0.24) | 0.40 (0.13) | 0.92 (0.18) | 0.78 (0.18) | HIV+ < HIV− |
| TNF-αa [pg/mL] | −0.23 (0.15) | −0.07 (0.08) | 0.18 (0.11) | 0.14 (0.11) | HIV+ < HIV− |
| MCP-1 [pg/mL] | 2.06 (0.03) | 1.97 (0.02) | 1.99 (0.03) | 1.96 (0.03) | LTBI+ > LTBI− |
| MIP-1β [pg/mL] | 0.70 (0.08) | 0.64 (0.04) | 0.61 (0.06) | 0.62 (0.06) | |
| IP-10 [pg/mL] | 1.59 (0.05) | 1.50 (0.03) | 1.51 (0.04) | 1.52 (0.04) | |
| RANTESb [pg/mL] | 1389 (110) | 1241 (59) | 1053 (83) | 1082 (83) | HIV+ > HIV− |
Log10-transformed values are negative for biomarker levels between 0 and 1.
Not log10 transformed, because the original distribution for this biomarker was already approximately normal. None of the pairwise comparisons of the 4 groups (HIV+/LTBI+, HIV+/LTBI−, HIV−/LTBI+, HIV−/LTBI−) were significant after false discovery rate adjustment. Only direct effects of HIV and LTBI were statistically significant. SE = standard error.
Mean log10 IL-6 and log10 MCP-1 values were significantly higher in LTBI+ group compared to LTBI− group (p=0.044 and 0.023, respectively, adjusting for HIV status and sex). RANTES was significantly higher in HIV+ participants than in HIV− (p=0.01, adjusting for LTBI and sex). LTBI+ and LTBI− participants did not differ statistically in IFN-γ, TNF-α, MIP-1β, IL-2, IP-10, RANTES, or IL-22. (Table 4).
Comparisons of clinical laboratory tests of hematologic, hepatic, and renal function among the groups.
We found no differences between LTBI− and LTBI+ groups for any hematological, hepatic, or renal variables including: hemoglobin, hematocrit, total platelet count, mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), total white blood cell count (WBC), total lymphocyte count, percent neutrophils, percent lymphocytes, AST, ALT, ALP, total protein, and urea. Mean creatinine in HIV+/LTBI+ participants (0.89 mg/dL; SD=0.15) was higher than in the HIV+LTBI− group (0.80 mg/dL; SD=0.14; p= 0.024). However, this difference was not significant when controlled for sex (p=0.13). Thus, we found no effect of LTBI on bone marrow, liver, or kidney function.
An HIV effect was found for multiple erythrocyte and white blood cell indices in models adjusting for LTBI and sex. The HIV+ group had: a) lower total red blood cell (RBC) count (4.26 vs 4.57 × 106 cells/μL, p=0.002), but higher b) mean corpuscular volume (MCV) (93.0 vs 83.9 fL, p<0.001), c) MCHC (34.1 vs 33.4 g/dL, p=0.049), and d) MCH (31.5 and 28.1 pg, p<0.001). White cell indices were lower for a) WBC (7.03 vs, 8.54 × 106 cells/μL, p<0.002), b) percent neutrophils (50.7 vs 57.6, p<0.003), and higher for c) percent lymphocytes (34.9 vs 30.5, p=0.02). Thus, the HIV+ group tended toward macrocytic anemia and leukopenia.
Discussion
In this cross-sectional study of South Indians, HIV infection, but not LTBI, was associated with increased NCI. Prior studies have found a higher prevalence of NCI in HIV+ patients with active TB compared to those without active TB [9, 10]. Multiple studies suggest that increased systemic inflammation contributes to cognitive impairment in HIV+ and HIV− adults [3, 18, 19]. In contrast, LTBI did not increase NCI.
Our finding of increased rates of NCI in HIV+ compared to HIV− participants, is consistent with prior studies in other countries [1, 2]. This establishes the fact that our participants exhibit cognition functioning expected of typical HIV+ and HIV− cohorts in the era of effective ART. Some LTBI+ individuals may be in the process of developing active, but undetected asymptomaticTB, creating a possible bias toward finding an effect of LTBI on NCI and systemic inflammation in our study. Nevertheless, we found neither of these effects.
The percentage by men in each group varies very considerably, but we have no obvious explanation for this variation beyond the greater proportion of HIV + participants who are men. The effect of sex on prevalence of LTBI was examined in a study from Taiwan [20]. The higher prevalence of LTBI in men (32.6% for men > 25.2% for women, p<.01) appeared to be attributable to ~10-fold higher rates of smoking in men than women. Three-fold more men than women in India smoke, but we do not know the smoking habits of our participants.
Our HIV+ study participants had a tendency toward macrocytic anemia and leukopenia that has been well documented [21, 22]. Anemia is associated with increased mortality and cognitive impairment in HIV+ persons [23-25]. The mechanism of this association is unclear, but appears to involve both the effects of hepcidin on iron metabolism and systemic inflammation [26].
Inflammatory biomarker levels did not differ between HIV+/LTBI+, HIV+/LTBI−, HIV−/LTBI+, HIV−/LTBI− groups. We found that two of the three pro-inflammatory biomarkers we measured, IL-6 and MCP-1, but not TNF-α, were elevated in the LTBI+ compared to the LTBI− groups. Biomarkers of immune activation (IFN-γ, MIP-1β, IL-2, IP-10, RANTES, and IL-22) did not differ between these groups. Another biomarker of inflammation, hsCRP, was elevated in the LTBI− compared to the LTBI+ group, a finding in the opposite direction of the expected effect. HIV+ participants when compared to HIV− participants had lower levels of IL-22 and TNF-α, and higher levels of RANTES.
The meaning of these elevations and depressions in levels of serum biomarkers of systemic inflammation in our LTBI+ compared with LTBI− and HIV+ compared with HIV− participants is unclear. Other studies of patterns of cytokine in LTBI+ persons suggest that they have increased systemic inflammation. Higher IFN-γ levels in blood have been detected in LTBI+ than in LTBI− persons in both low and high TB transmission regions of the world [27, 28]. Studies of HIV− adults from the US (n=4,950; 430 LTBI+) and Lima, Peru (n=214; 120 LTBI+) found higher mean IFN-γ levels in blood in LTBI+ than LTBI− groups (3 vs. 2.5 pg/mL, p<0.001 and 14 vs. 6.5 pg/mL, p<0.01, respectively). Of note, IFN-γ levels in these two studies were measured in the nil (IGRA negative control) tubes after an incubation in whole blood for a period of 16–24 hours. In contrast, the current study directly measured all biomarker levels in blood without incubation with cells.
In another study, soluble markers of inflammation were not elevated, but LTBI+ compared with LTBI− had immune activation (higher T-cell activation) as measured by CD38 and HLA-DR expression on CD4+ and CD8+ T lymphocytes [11]. The LTBI+ group in that study also had significantly higher levels of CD127 - regulatory T-cells compared to LTBI−, whereas the LTBI+ and the active TB groups had levels that were similar to each other [12]. In addition, 3 months of LTBI treatment did not alter the expression of markers on T-cells of immune activation or apoptosis [12]. Thus, our findings in LTBI+ patients of no immune activation are inconsisitent with prior studies, but the only study that contradicts our finding of systemic inflammation in LTBI may be explained by differences in methods of measuring the state of systemic inflammation.
Whether LTBI contributes to HIV disease progression or has adverse impact on other organ systems is less clear. LTBI is associated with acute myocardial infarction [29]. Larger longitudinal studies are needed to further investigate: i) the possible contribution of LTBI to inflammation and immune activation that can drive atherosclerosis ; ii) long-term effect on other organ systems that are damaged by inflammation; and iii) improvement in inflammation and its consequences following LTBI treatment.
Biomarkers of inflammation (TNF-α) and immune activation (IFN- γ) were examined because both play a role in the control of M. tuberculosis infections [13, 30]. Neither TNF-α nor IFN-γ were elevated in the blood of our LTBI+ participants, but the small sample size limited our power to detect differences. Elevated levels of IFN-γ have been associated with clinical deterioration and progression to active TB disease in HIV− persons [27], but not with LTBI. Likewise, IFN-γ has been associated with maintenance of LTBI and restriction of bacillary growth and tissue destruction [30]. Nonetheless, IFN-γ was not associated with LTBI.
Limitations of this study are: a) its cross-sectional design, b) the small HIV+/LTBI+ group (n=15), and c) the inability to identify or exclude patients with LTBI who have been or are being treated. However, very few HIV+ patients and no HIV− patients were likely have received LTBI treatment for several reasons: a) priority given to treating active TB over LTBI in resources limited settings, b) concerns about selecting for drug resistance by treating patients with undiagnosed active TB with only one drug, and c) recurrent LTBI due to reinfection with M. tuberculosis after treatment.
Conclusions
In this cross-sectional analysis of HIV-infected persons predominately on ART and HIV− controls, LTBI was not significantly associated with increased prevalence or severity of NCI. As expected, HIV+ participants had lower global T scores and higher global deficit scores than HIV− regardless of LTBI status. Higher MCV, MCHC, and possibly lower total RBC count in the HIV+ group likely contributed to this observed cognitive impairment. Two pro-inflammatory biomarkers of inflammation, IL-6 and MCP-1,were elevated in LTBI+ compared to LTBI− persons. However, another marker of inflammation (hsCRP) was depressed in the LTBI+ groups. An interaction of LTBI with HIV+ was found in several cognitive domains, but the reason for this effect is unclear. Although larger longitudinal studies might be desirable, our study suggests that any effect of LTBI on systemic inflammation or NCI would likely be small.
Table 1.
Demographics and HIV characteristics.
| Variable | HIV+/LTBI+ N=15 |
HIV+/LTBI− N=50 |
HIV−/LTBI+ N=26 |
HIV−/LTBI− N=28 |
|---|---|---|---|---|
| Age (years), mean (SD) | 38.0 (7.8) | 34.5 (8.2) | 34.9(8.0) | 33.4(6.3) |
| % Male | 73% | 46% | 35% | 18% |
| Years of education, mean (SD) | 10.5 (3.1) | 10.0 (2.7) | 11.7 (3.7) | 12.8 (3.8) |
| CD4, median (IQR) [cells/μL] | 537 (395-616) | 552 (396-779) | n/a | n/a |
| N with CD4 <200 [cells/μL ] (%) | 1 (6.7%) | 3 (6.1%) | n/a | n/a |
| % with plasma viral load undetectable | 67% | 52% | n/a | n/a |
| Plasma viral load (log10) in detected (SD) | 5.6 (4.0) | 5.2 (3.9) | n/a | n/a |
| N (%) on ART | 11 (73%) | 27 (54%) | n/a | n/a |
| Serum creatinine, mg/dL, mean (SD) | 0.89 (0.15) | 0.80 (0.14) | DU | DU |
| Hemoglobin, g/dL, mean (SD) | 13.7 (1.3) | 13.3 (1.5) | 13.1 (1.7) | 12.5 (2.0) |
| MCV, fL, mean (SD) | 91.2 (7.4) | 93.5 (12.2) | 83.5 (4.3) | 84.3 (7.3) |
Numeric values are shown as mean (standard deviation, (SD)) or median (interquartile range, (IQR)).
DU= data unavailable. n/a= not applicable
Acknowledgments
We acknowledge and thank the participants of the study who generously shared their time for the purpose of research. We also thank the YRGCARE Infectious Diseases Laboratory and CART Clinical Research Site staff at the Voluntary Health Services, Chennai, India.
Funding Sources: ARB (K23 MH085512), RH (P30MH062512)
Footnotes
Conflict of Interest/Disclosures Statement: The authors disclose no conflict of interest related to the manuscript.
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