Abstract
Background:
HIV-positive patients on anti-retroviral therapy (ART) are at higher risk of developing many non-AIDS related chronic diseases, including chronic obstructive pulmonary disease (COPD), compared to HIV-negative individuals. While the mechanisms are not clear, a persistent pro-inflammatory state appears to be a key contributing factor. The aims of this study were to investigate whether HIV-positive patients without COPD present evidence of potentially predisposing abnormal pulmonary cytokine/chemokine environment and to explore the relationship between pulmonary and systemic cytokine levels.
Methods:
This study included 39 HIV-seropositive and 34 HIV-seronegative subjects without COPD. All were subjected to outpatient bronchoscopy with bronchoalveolar lavage fluid (BALF) aspiration and blood sample collection. The levels of 21 cytokines and chemokines were measured in plasma and BALF using a bead-based multi-analyte assay.
Results:
In plasma, HIV-infected patients showed significantly increased circulating levels of pro-inflammatory (TNFα) and Th1-associated cytokines (IL-12p70) as well as several chemokines (CXCL11 and CX3CL1). However, no statistically significant differences were found in the numbers of cells, the concentrations of protein and urea as well as cytokine levels in the BALFs of HIV-positive patients when compared to controls. Correlation analysis indicated a potential modulatory effect of the BMI in HIV-seropositive individuals.
Conclusions:
While our results are consistent with the existence of a systemic pro-inflammatory state in HIV-infected patients, they did not detect significant differences in cytokine levels and other inflammatory markers in the lungs of HIV-positive individuals when compared to HIV-negative controls.
Keywords: Chronic lung disease (CLD), chemokines, cytokines, HIV, inflammation
1. INTRODUCTION
Thanks to the emergence of ART, the survival of HIV-positive patients has been significantly extended and HIV infection has become a chronic and manageable disease [1–3]. However, when compared to uninfected individuals, HIV patients on ART manifest a higher prevalence of many non-AIDS related chronic diseases, including cardiovascular disease (CVD), diabetes, metabolic disorders, liver steatosis, osteoporosis, obstructive lung diseases, neurocognitive disorders and some types of cancer [4–8]. While the actual mechanisms responsible for these complications are not completely clear, the common denominator appears to be chronic inflammation [6,10]. In fact, while ART is able to suppress viral replication to below detection limits in blood, the immune system of patients with chronic HIV never truly achieves complete quiescence and rather appears to be in a persistently hyper-reactive state [7,11]. In addition, endothelial cells and the coagulation system, which interact closely with the immune system, appear to be chronically-activated as well [9,12,13].
The reasons for the enhanced immune activation in patients with HIV appear to be multifactorial. For example, even low level or even abortive HIV infection, through the presence of viral HIV-1 RNA or DNA, may induce immune activation via pattern recognition receptors (TLR-7 and TLR-9) and activation of caspase-1 [14,15]. Increased intestinal permeability and defects in intestinal immune homeostasis secondary to the loss of mucosal Th17 cells have been thought to lead to enhanced microbial translocation from the gut, resulting in immune activation [6,10,16,17]. In addition, secondary co-infections, CD4+ T cell lymphopenia, immunosenescence and immune dysregulation may also contribute to persistent immune activation [6,10]. Understanding of the mechanisms responsible for the persistent inflammation and immune activation should be key in identifying potential therapeutic targets and designing therapeutic strategies in order to reduce associated comorbidities in HIV patients.
In the ART era, obstructive lung disease has become a significant cause of morbidity and mortality in HIV-positive individuals. Moreover, several studies have suggested that HIV infection is an independent risk factor for chronic obstructive pulmonary disease (COPD) [18]. In acutely infected patients, HIV is known to promote pulmonary inflammation, particularly in the form of lymphocytic alveolitis, characterized by infiltration with virus-specific CD8+ T lymphocytes and activation of alveolar macrophages [8,19]; while decreasing CD4+ T cell numbers and immune function result in increased susceptibility to AIDS-defining pulmonary infections. Following ART, patients experience a significant reduction in viral titers, normalization of CD4+ T cell numbers and a return to a seemingly normal lung environment, albeit with reported persistent low-level production of IFNγ and induced chemokines, likely as a result of low-level viral persistence [19]. To what extent a systemic pro-inflammatory state contributes to pulmonary inflammation and the increased risk for chronic lung disease (CLD) in ART-treated HIV-patients is unclear. Nevertheless, it is important to point out that the mechanisms responsible for the association of chronic HIV infection and CLD are likely to be multiple, involving not only lung inflammation, but a combination of excess risk behaviors, increased susceptibility to pulmonary infections, lung epithelial cell injury, altered anti-oxidant/oxidant balance and direct effects of ART [8,18].
We undertook the present study in order to investigate whether HIV-positive patients on ART without CLD present evidence of abnormal pulmonary cytokine or chemokine environment and to explore the relationship between the pulmonary and systemic compartments, using a subgroup of subjects participating in a study of HIV-induced lung disease.
2. MATERIALS AND METHODS
2.1. Study Design
This was a cross-sectional study analyzing the data of a subgroup of subjects included in the study “The Impact of Oxidative Stress on HIV-Induced Lung Disease” performed at the University of Louisville in Louisville, Kentucky, USA [20]. The study enrolled a total of 132 subjects from February 2014 to October 2016, including both HIV-seropositive and seronegative patients with or without CLD (defined as FEV1/FVC ratio of less than 0.70 [21]). Only the subgroup of patients without COPD (n=73), including 39 HIV-seropositive and 34 HIV-seronegative subjects was included in the present study. HIV-seropositive individuals had been a median of eight years under ART and were stable from an immunological standpoint. Patients were excluded if they had a medical history of cardiovascular disease (other than controlled hypertension), acute infection, cancer, or other malignancy-related disorders. Subjects were seen in an outpatient basis and were stable from a respiratory standpoint. During their visit and after providing informed consent, the subjects underwent spirometry, blood sample collection and outpatient bronchoscopy with BALF aspiration. The study was approved by the University of Louisville’s Institutional Review Board (IRB), approval # 13.0442. All procedures were in accordance with ethical standards of the University of Louisville IRB and the Helsinki Declaration of 1975, as revised in 2000.
2.2. Samples
Plasma samples:
Venous blood (4 mL) was collected using Vacutainer EDTA tubes. Blood samples were transported within 30 minutes of collection to the laboratory for processing. Following centrifugation at 300 × g for 10 min, the plasma was separated by aspiration, aliquoted and stored frozen at −80°C until assayed.
Bronchoalveolar lavage fluid:
BALF collection was performed as previously described [20]. Briefly, following anesthesia (lidocaine 1% solution) of the vocal cords, a bronchoscope was wedged into a distal segment of a bronchus. Then, a total of 180 ml of sterile saline solution was instilled into a lobe of the lung. After gentle aspiration, the lavage was collected into three 50 mL and two 15 mL centrifuge tubes. The aspirates were then pooled, filtered through sterile gauze and centrifuged at 2,500 × g for 15 minutes. The cell pellets were resuspended in phosphate-buffered saline (PBS) and the total number of nucleated cells determined in a Bio-Rad TC20 automated cell counter (Bio-Rad Laboratories, Hercules, CA). The supernatants were aliquoted and stored at −80°C until assayed.
2.3. Cytokine measurements
Plasma and BALF samples were thawed and centrifuged at 10,000 × g for 5 minutes prior to use in the assays. The concentrations of twenty-one different cytokines and chemokines in serum and BAL samples were measured using Milliplex MAP High Sensitivity Human T cell panel kits (HSCYTMAG-28SK, EMD Millipore, Billerica, MA) according to the manufacturer’s instructions. The measured cytokines and chemokines included: IL-1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-17A, IL-21, IL-23, IFNγ, TNFα, GM-CSF, CCL3 (MIP-1α), CCL4 (MIP-1β), CCL20 (MIP-3α), CXCL11 (I-TAC) and CX3CL1 (Fractalkine). Cytokine/chemokine levels in plasma and BALF were reported in picogram per milliliter (pg/mL). Additionally, cytokine levels in BALF were expressed as pg/mg of protein or pg/ng urea after adjusting for protein or urea concentration, respectively. The minimum detectable concentrations of cytokines were (all in pg/mL): IL-1β (0.14), IL-2 (0.19), IL-4 (1.12), IL-5 (0.12), IL-6 (0.11), IL-7 (0.42), IL-8 (0.13), IL-10 (0.56), IL-12p70 (0.15), IL-13 (0.23), IL-17A (0.33), IL-21 (0.14), IL-23 (3.25), IFNγ (0.48), TNFα (0.16), GM-CSF (0.35), CCL3 (0.94), CCL4 (0.67), CCL20 (0.83), CXCL11 (1.25) and CX3CL1 (8.17).
2.4. Protein and Urea measurements
The concentration of total protein in BALF supernatants was measured colorimetrically using the Bio-Rad Protein Assay dye reagent and a bovine serum albumin protein standard according to the manufacturer’s instructions (Bio-Rad, Hercules, CA). The concentration of urea in BALF was measured using a colorimetric Urea Assay kit (Cat. No. MAK006, Sigma-Aldrich, St. Louis, MO) and reading at 570 nm in a Beckman Coulter AD340C Absorbance detector (Beckman Couler, Inidianapolis, IN).
2.5. Statistics.
Categorical variables summarized with frequencies and percentages and differences between groups were tested using Fisher’s exact test. Continuous variables (cytokine data) are summarized as means and standard deviations or as medians and intraquartile ranges. Data distribution was analyzed using the D’Agostino and Pearson omnibus normality test. Statistical comparisons between the groups were performed using the Mann Whitney U-test. Spearman’s correlations were calculated between plasma cytokines, BALF cytokines, viral load, CD4 count, and body mass index (BMI). The two-stage linear step-up procedure of Benjamini, Krieger and Yekutieli [22] was used to control the effect of multiple testing for plasma and BALF cytokines according to the false discovery rate (FDR, Q=5%). q-values (representing adjusted p-values based on the FDR) are indicated where appropriate. p- or q-values <0.05 were considered statistically significant. Statistical analyses were performed using GraphPad Prism 5.0 (GraphPad Software, La Jolla, CA) and R version 3.3.2 (www.r-project.org).
3. RESULTS
3.1. Patient Characteristics
The demographics and clinical characteristics of the subjects are shown in Table 1. HIV-seropositive subjects were overall older than HIV-seronegative ones (mean age 49.5±8.5 vs. 40.5±11.6 years old [p=0.004]; range 21.3–64.3 vs. 24.6–61.0 years old, respectively). Twenty-six (69%) subjects from the HIV-seropositive group and 16 (47%) from the HIV-seronegative group were male (p=0.103). Fourteen (41%) subjects from the HIV-seropositive group and eight (24%) from the HIV-seronegative group identified themselves as White; while 22 (59%) and 26 (74%) identified themselves as African American in the HIV- seropositive and seronegative groups, respectively. The two groups did not differ statistically in terms of BMI (average BMI of 28.1 vs. 30.0 for HIV-seropositive and seronegative patients, respectively; p=0.151). With the exception of a higher prevalence of hepatitis C in the HIV-seropositive group (n=13 vs. 1; p=0.001), the two groups did not differ statistically with respect to history of comorbidities nor in terms of smoking, alcohol or drug abuse history. The HIV-seropositive group had a median (IQR) of 8 (12.5) years on ART and 13 patients had previous history of AIDS-defining illness. The median CD4+ T cell count in the HIV-positive group was 550/mm3 (IQR: 362/mm3) and HIV viral loads ranged from undetectable to 35,500/mL (mean 2846/mL).
Table 1.
Demographic Characteristics
| Control Subjects | HIV+ patients | p-value | |
|---|---|---|---|
| n | 34 | 39 | |
| Age (years) | 40.5±11.6 | 49.5±8.5 | 0.004** |
| Sex (male) | 16 | 26 | >0.05 |
| (female) | 18 | 13 | |
| Ethnicity; | |||
| Caucasian | 8 | 14 | |
| African American | 26 | 22 | |
| Native American | 0 | 1 | |
| BMI | 30.0±8.5 | 28.1±9.5 | >0.05 |
| CD4 count [median (IQR)] | 550 (362) | ||
| CD4% [median (IQR)] | 26.3 (16.5) | ||
| HIV Viral load [median (IQR)] | 20 (280) | ||
| Years on ART [median (IQR)] | 8 (12.5) | ||
| Asthma history | 11 | 8 | >0.05 |
| Bacterial pneumonia history | 5 | 11 | >0.05 |
| Hypertryglyceridemia | 1 | 4 | >0.05 |
| Lipodystrophy | 0 | 1 | >0.05 |
| Hypercholesterolemia | 5 | 5 | >0.05 |
| Diabetes | 5 | 2 | >0.05 |
| Hypertension | 10 | 20 | >0.05 |
| Hepatitis C | 1 | 13 | 0.001** |
| Hepatitis B | 0 | 2 | >0.05 |
| Alcohol history | 1 | 5 | >0.05 |
| Drugs history | 11 | 21 | >0.05 |
p<0.01
3.2. Plasma cytokine profiles in chronic HIV-infected patients show significant differences with those of HIV-negative controls
The plasma cytokine profiles for both groups are shown in Table 2. With only a few exceptions, all cytokines and chemokines assayed were above the minimum detectable levels in most subjects. Generally, patients in the HIV-seropositive group showed a pattern consistent with enhanced systemic inflammation and/or immune activation. Even after controlling for the false discovery rate, the HIV-seropositive group had statistically significant higher levels of pro-inflammatory (TNFα), Th1-associated cytokines (IL-12p70) and two chemokines (CXCL11, an IFNγ-induced chemokine, and CX3CL1) compared with HIV-seronegative controls.
Table 2.
Plasma Cytokine Analysis
| Cytokine | Control (pg/mL) | HIV+ (pg/mL) | q-value |
|---|---|---|---|
| Innate | |||
| IL-1β | 1.1 (0.7) | 1.4 (1.7) | 0.086 |
| IL-6 | 0.9 (1.3) | 1.6 (1.7) | 0.105 |
| TNFα | 3.7 (2.7) | 5.8 (4.4) | 0.047* |
| IL-10 | 5.3 (3.9) | 7.9 (12.0) | 0.086 |
| Th1 | |||
| IL-12p70 | 0.9 (1.8) | 1.5 (3.5) | 0.038* |
| IFNγ | 9.5 (7.1) | 12.5 (18.4) | 0.086 |
| Th2 | |||
| IL-4 | 1.8 (4.1) | 10.0 (19.2) | 0.069 |
| IL-5 | 0.7 (1.8) | 1.4 (1.8) | 0.105 |
| IL-13 | 1.9 (2.9) | 1.7 (3.0) | 0.430 |
| Th17 | |||
| IL-17A | 2.5 (4.9) | 2.2 (7.9) | 0.313 |
| IL-23 | 16.7 (33.6) | 28.5 (133.9) | 0.105 |
| Other | |||
| IL-2 | 0.9 (0.9) | 0.8(1.6) | 0.705 |
| IL-7 | 4.3 (3.2) | 4.9 (8.2) | 0.313 |
| IL-21 | 0.5 (0.7) | 0.7 (1.8) | 0.105 |
| GM-CSF | 24.3 (47.0) | 35.1 (33.6) | 0.277 |
| Chemokines | |||
| CXCL8 (IL-8) | 2.9 (2.2) | 3.6 (3.5) | 0.311 |
| CXCL11 (ITAC) | 15.2 (27.2) | 35.1 (41.6) | 0.041* |
| CX3CL1 (Fractalkine) | 35.7 (47.9) | 71.9 (99.5) | 0.038* |
| CCL3 (MIP-1α) | 14.1 (7.4) | 14.6 (9.2) | 0.860 |
| CCL4 (MIP-1β) | 9.3 (6.1) | 11.5 (5.0) | 0.069 |
| CCL20 (MIP-3α) | 18.4 (17.8) | 22.9 (24.7) | 0.199 |
Cytokine concentration values represent medians (IQR).
q-values represent adjusted p-values based on FDR.
q <0.05
3.3. BALF cytokine profiles in chronic HIV-infected patients do not show significant differences with those of HIV-negative controls
As depicted in Table 3 (upper panel), the composition of the BALF recovered from the HIV-seropositive group did not differ significantly from that of the HIV-seronegative group in terms of total numbers of nucleated cells, protein and urea concentrations. The rate of detectability of the 21 measured cytokines in BALF samples varied widely. While some cytokines and chemokines were detectable in the majority of subjects, some were measurable in only a few. Table 3 shows the number of patients in which each of the measured cytokines/chemokines was detectable (above the minimum detectable concentration [MDC]) (lower left panel) as well as the median levels, expressed in pg/mL, for those cytokines with detectable levels in at least 5 or more patients (lower right panel). Overall, the two groups did not significantly differ from each other in terms of detectability nor in the levels of cytokines and chemokines measured after adjusting for FDR. Even after normalizing BALF cytokine and chemokine levels to the BALF protein or urea concentrations, no significant differences were observed between the two groups (Supplemmentary Tables 1 and 2, respectively).
Table 3.
BALF Composition
| Component | Control Subjects | HIV+ patients | p-value |
|---|---|---|---|
| Total cells (× 106) | 74.9 (55.1) | 56.8 (58.2) | 0.241 |
| Total protein (μg/mL) | 113.3 (78.3) | 101.9 (98.7) | 0.407 |
| Urea (ng/mL) | 3.1 (5.2) | 5.3 (3.9) | 0.160 |
Values represent medians (IQR).
3.4. Correlations of Systemic and BALF cytokine levels
An analysis of potential correlations among plasma and BALF cytokines as well as with other important variables was carried out. For all cytokines measured in both the HIV-seropositive and seronegative groups, no significant correlations were found between their levels in plasma and those in BALF. In addition, no significant correlations were found between cytokines levels in plasma or BALF of HIV-seropositive patients with infection parameters (CD4+ T cell count, total BALF cell count and viral load). Correlation analyses showed low to moderate but statistically significantly negative correlations between the total cell counts in BALF (r:-0.416, p=0.020) and the viral load (r:-0.434, p=0.013) with the BMI in the HIV-positive group. However, no significant correlations were found between the BMI and the levels of plasma or BALF cytokines. Interestingly, the Control group showed a moderate and statistically significant correlation between the BMI and the plasma levels of TNFα (r:0.635, q=0.004).
4. DISCUSSION
The aim of this study was to investigate the lung and systemic cytokine patterns, as measured in BALF and plasma respectively, in HIV-infected subjects without CLD and other chronic lung disorders participating in a larger study of HIV-induced lung disease. The HIV-positive group was compared to a control, HIV- negative group, also without chronic lung disease. HIV-positive patients had significantly increased circulating levels of several cytokines, including pro-inflammatory (TNFα), Th1-associated cytokines (IL-12p70) as well as several chemokines (CXCL11, and CX3CL1). In contrast, our study did not find statistically significant differences in BALF cytokine levels between HIV-positive and negative subjects, either when expessed as pg/mL or when normalized to both protein or urea concentrations. No significant correlations were found between the levels of cytokines in plasma and those in BALF and between plasma or BALF cytokines and the CD4+T cell count in HIV-positive patients.
The main contribution of our study to the literature was the finding that despite increased plasma levels of pro-inflammatory cytokines and chemokines, cytokine profiles in the lungs of HIV-positive patients without CLD do not differ substantially from HIV-seronegative controls. The higher systemic levels of cytokines in the HIV-infected group were consistent with the persistent inflammation and immune hyperreactivity that has been reported in chronically-infected HIV patients [6,7,11]. This immune activation is considered to multifactorial, including a low-level or abortive HIV infection, microbial translocation from the gut, co-infections by other microbes, immunosenescence and dysregulation of immunoregulatory pathways [6,7]. The elevated levels of TNFα and the chemokines, signs of chronic inflammation, may arise from macrophage activation due to bacterial translocation from the gut and/or to other causes including pyroptosis of CD4+ T cells [7,23]. The finding of increased levels of Th1-associated cytokines (IL-12p70) may be influenced by lingering viral infection and/or by the general hyper-responsive state of the immune system.
Notwithstanding our results demonstrating systemic inflammation in HIV-infected patients, we were unable to detect a significant inflammatory response in the lungs of HIV-positive patients. In fact, our study did not find statistically significant differences in BALF cytokine or chemokine levels between HIV-infected and control groups. Moreover, the lack of correlation between the levels of serum and BALF cytokines suggest that at least in HIV-positive subjects who do not present with pulmonary symptoms, the lung remains separate from the systemic compartment in terms of cytokines and is probably not the source of the increased systemic cytokine levels. Yet, it is still possible that while HIV-infected patients may not have an overt inflammatory response in the lung, persistent viremia, even if low-level, might subtly contribute along with other risk factors to the risk of obstructive lung disease.
The BMI seems to be an important factor, not only in HIV infection, but also the development of CLD. In fact, BMI has been reported to be negatively correlated with COPD in HIV-infected patients [24]. Moreover, the BMI has been indirectly correlated with both morbidity and mortality in COPD patients [25–27]. These observations have suggested that adiposity may have some moderating effects on the diseease. Our results showing a negative correlation between BMI and the total number of nucleated cells in the BALF as well as the viral load in the HIV-positive subjects suggest that the BMI may potentially have a “protective” or modulatory effect on the HIV infection and on the risk of lung complications, potentially by modulating inflammation. The mechanistic bases of such phenomenon remain to be better understood.
4.1. Limitations of the Study
There are several limitations to our study. First, there were significant differences in age between the two study groups, with HIV-seropositive patients being older (average age 49.5±8.5 vs. 40.5±11.6 years old) than the HIV-seronegative controls. Although not consistent, there is evidence that circulating levels of pro-inflammatory, T-cell derived cytokines and chemokines generally increase with age, albeit most studies have compared children to adults [28] or a wider age range than the difference in the two groups in our study (e.g, <30 to >60 years old) [29–31]. Nonetheless, it is still plausible that the age difference may have also contributed to the differences observed in our study. Second, although there were no significant differences in terms of smoking history between the two groups, the fact that most of the patients included in the study were smokers or ex-smokers, may have led to increased cytokine levels in the lung, preventing the detection of baseline differences. Thirdly, the Control and HIV-seropositive groups differed in terms of HCV-seropositivity, raising the possibility that HCV infection may have contributed to the higher levels of cytokines in plasma. While we cannot completely discard such possibility, none of the HIV-seropositive subjects had active liver disease or were undergoing treatment at the time of the study. In addition, comparison of the plasma cytokine levels in HCV-seronegative and -seropositive subjects failed to show any statistically significant differences. Finally, the relatively low umbers of subjects in this study is a limitation and further studies are necessary to establish the validity of these results.
4.2. Conclusions
In summary, while the results of this study are consistent with previous reports of the chronic systemic inflammation and immune hyperresponsiveness of HIV-positive patients, our results were unable to establish that these patients have significant levels of pulmonary inflammation.
Supplementary Material
Table 4.
BALF Cytokine Analysis
| Cytokine | Control (>MDC) n=34 | HIV+ (>MDC) n=39 | p-value | Control (pg/mL) | HIV+ (pg/mL) | q-value |
|---|---|---|---|---|---|---|
| Innate | ||||||
| IL-1β | 10 | 10 | 0.796 | 0.4 (0.8) | 0.3 (0.4) | 0.725 |
| IL-6 | 31 | 35 | 1.000 | 2.2 (3.3) | 2.2 (4.1) | 0.900 |
| TNFα | 32 | 34 | 0.438 | 0.7 (0.5) | 0. 8 (0.7) | 0.725 |
| IL-10 | 9 | 7 | 0.410 | 1.5 (4.1) | 2.1 (11.2) | 0.725 |
| Th1 | ||||||
| IL-12p70 | 4 | 1 | 0.177 | - | - | - |
| IFNγ | 7 | 6 | 0.760 | 1.0 (2.1) | 2.3 (4.1) | 0.725 |
| Th2 | ||||||
| IL-4 | 11 | 15 | 0.631 | 3.2 (1.4) | 2.8 (1.3) | 0.838 |
| IL-5 | 3 | 2 | 0.659 | - | - | - |
| IL-13 | 7 | 5 | 0.529 | 0.4 (0.3) | 0.3 (0.1) | 0.838 |
| Th17 | ||||||
| IL-17A | 3 | 1 | 0.333 | - | - | - |
| IL-23 | 3 | 1 | 0.333 | - | - | - |
| Other | ||||||
| IL-2 | 5 | 4 | 0.725 | 0.2 (2.4) | 0.4 (1.4) | 0.763 |
| IL-7 | 17 | 11 | 0.091 | 1.0 (5.2) | 4.6 (12.6) | 0.725 |
| IL-21 | 11 | 17 | 0.347 | 1.0 (4.5) | 0.3 (1.5) | 0.725 |
| GM-CSF | 28 | 26 | 0.182 | 0.7 (0.5) | 0.7 (0.4) | 0.763 |
| Chemokines | ||||||
| CXCL8 (IL-8) | 34 | 39 | 1.000 | 22.9 (33.6) | 30.2 (35.8) | 0.725 |
| CXCL11 (ITAC) | 18 | 22 | 0.817 | 2.3 (2.0) | 2.8 (2.9) | 0.725 |
| CX3CL1 (Fractalkine) | 15 | 16 | 0.816 | 17.7 (58.3) | 11.8 (67.2) | 0.725 |
| CCL3 (MIP-1α) | 27 | 26 | 0.295 | 2.9 (2.1) | 2.7 (3.2) | 0.725 |
| CCL4 (MIP-1β) | 19 | 23 | 0.816 | 1.9 (1.4) | 1.7 (2.0) | 0.838 |
| CCL20 (MIP-3α) | 21 | 29 | 0.315 | 5.3 (14.1) | 4.6 (12.4) | 0.725 |
MDC : Minimum detectable concentration
Cytokine concentration and other values represent medians (IQR). Results shown only for those cytokines with at least 5 values above the MDC.
q-values represent adjusted p values based on FDR.
HIGHLIGHTS:
Plasma levels of several cytokines and chemokines were elevated in HIV-seropositive subjects.
No significant differences in levels of cytokines, chemokines, total protein and cell numbers were observed in the bronchoalveolar lavage fluids (BALF) of HIV-positive vs. negative subjects.
Despite an elevated systemic cytokine response, the pulmonary cytokine environment of HIV-seropositive patients without COPD was not different to that of HIV-controls.
6. ACKNOWLEDGEMENTS:
This research was based on “The Impact of Oxidative Stress on HIV-induced Lung Disease” study RFA: RFA-HL-13.026, NHLBI # 1 U01 HL121807-01 submitted revised January 22nd, 2016. The funding source had no role in the design of the study, the collection, analysis and interpretation of the data and the writing of the manuscript. We acknowledge the following individuals, members of the Redox Clinical Trials team, for their role in these studies: Daniel Curran, MD; Carey Ackerman, MPH; Jenevieve Kincaid, MD; Joel Lanceta, MD; Ibrahim Elkhawas, MD; Veronica Corcino, MD; Kavitha Srinivasan, MD; Jyothi Chitekela, MD; Cynthia Maluf, MD; Cristian Rios, MD; Sabina Gautam, MD; Vladimir Pulgaron, MD; Daniya Sheikh, MD; Amar Sutrawe, MD; Nitish Nandu, MD; Alejandra Loban, MD; RaviTej Bommu, MD; Omar Jibril, MD; Dania Qaryouti, MD; Letty Probasco, MD; Kalifa Alexander, MPH; Sarah Abbas; Mohammad Tahboub, MD; Kimberley Buckner and Senen Pena, MD.
Sources of funding: National Institutes of Health (NIH) grant NHLBI # 1 U01 HL121807-01
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Conflicts of Interest: None of the authors have any to declare.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
5. REFERENCES
- 1.Antiretroviral Therapy Cohort C. (2008). Life expectancy of individuals on combination antiretroviral therapy in high-income countries: a collaborative analysis of 14 cohort studies. Lancet. 2008; 372:293–299. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Samji H, Cescon A, Hogg RS, et al. Closing the gap: increases in life expectancy among treated HIV-positive individuals in the United States and Canada. PLoS One. 2013; 8:e81355. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Legarth RA, Ahlstrom MG, Kronborg G, et al. Long-term mortality in HIV-infected individuals 50 years or older: a nationwide, population-based cohort study. J Acquir Immune Defic Syndr. 2016; 71:213–218. [DOI] [PubMed] [Google Scholar]
- 4.Bedimo RJ, McGinnis KA, Dunlap M, et al. Incidence of non-AIDS defining malignancies in HIV-infected versus noninfected patients in the HAART era: impact of immunosuppression. J Acquir Immune Defic Syndr. 2009; 52:203–208. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Brown TT, Tassiopoulos K, Bosch RJ, et al. Association between systemic inflammation and incident diabetes in HIV-infected patients after initiation of antiretroviral therapy. Diabetes Care. 2010; 33:2244–2249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Hunt PW. HIV and inflammation: mechanisms and consequences. Curr HIV/AIDS Rep. 2012; 9:139–47. [DOI] [PubMed] [Google Scholar]
- 7.Hunt PW, Lee SA, Siedner MJ. Immunologic biomarkers, morbidity, and mortality in treated HIV infection. J Infect Dis. 2016; 214(S2):S44–550. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Morris A, George MP, Crothers K, et al. HIV and chronic obstructive pulmonary disease. Is it worse and why? Proc Am Thorac Soc. 2011; 8:320–325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tenorio AR, Zheng Y, Bosch RJ, et al. Soluble markers of inflammation and coagulation but not T-cell activation predict non-AIDS-defining morbid events during suppressive antiretroviral therapy. J Infect Dis. 2014; 210:1248–1259. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Dinh DM, Volpe GE, Duffalo C, et al. Intestinal microbiota, microbial translocation, and systemic inflammation in chronic HIV infection. J Infect Dis. 2015; 211:19–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Younas M, Psomas C, Reynes J, et al. Immune activation in the course of HIV-1 infection: causes, phenotypes and persistence under therapy. HIV Medicine. 2016; 17:89–105. [DOI] [PubMed] [Google Scholar]
- 12.Baker JV. Chronic HIV disease and activation of the coagulation system. Thromb Res. 2013; 132:495–499. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Deeks SG, Tracy R, Douek DC. Systemic effects of inflammation on health during chronic HIV infection. Immunity. 2013; 39:633–645. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Beignon AS, McKenna K, Skoberne M, et al. Endocytosis of HIV-1 activates plasmacytoid dendritic cells via Toll-like receptor-viral RNA interactions. J Clin Invest. 2005; 115:3265–3275. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Doitsch G, Cavrois M, Lassen KG, et al. Abortive HIV infection mediates CD4 T ell depletion and inflammation in human lymphoid tissue. Cell. 2010; 143:789–801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Brenchley JM, Shacker TW, Ruff LE, et al. CD4+ T cell depletion during all stages of HIV disease occurs predominantly in the gastrointestinal tract. J Exp Med. 2004; 200:749–759. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Sankaran S, George MD, Reay E, et al. Rapid onset of intestinal epithelial barrier dysfunction in primary human immunodeficiency virus infection is driven by an imbalance between immune response and mucosal repair and regeneration. J Virol. 2008; 82:538–545. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Drummond MB, Kunisaki KM, Huang L. Obstructive lung diseases in HIV: a clinical review and identification of key future research needs. Semin Respir Crit Care Med. 2016; 37:277–288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Twigg HL III, Knox KS. HIV-related lung disorders. Drug Discov Today Dis Mech. 2007; 95–101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Morello Gearhardt A, Cavalazzi R, Peyrani P, et al. Lung cytokines and systemic inflammation in patients with COPD. Univ Louisville J Respir Infect. 2017; 1(4):1–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.GOLD, Global initiative for chronic obstructive lung disease (GOLD): Global strategy for the diagnosis, management and prevention of chronic obstructive pulmonary disease. 2016.
- 22.Benjamini Y, Krieger AM, Yekuteli D. adaptivelinear step-up procedures that control the false Discovery rate. Biometrika. 2006; 93:491–507. [Google Scholar]
- 23.Doitsch G, Galloway NLK, Geng X, et al. Cell death by pyroptosis drives CD4 T-cell depletion in HIV-1 infection. Nature. 2014; 505:509–516. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Risso K, Guillouet-de-Salvador F, Valerio L, et al. COPD in HIV-infected patients: CD4 cell count highly correlated. PLOS One. 2017; 12:e0169359. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wu Z, Yang D, Ge Z, et al. Body mass index of patients with chronic obstructive pulmonary disease is associated with pulmonary function and exacerbations: a retrospective real world research. J Thorac Dis. 2018; 10:5086–5099. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Guo Y, Zhang T, Wang Z, et al. Body mass index and mortality in chronic obstructive pulmonary disease. A dose-response meta-analysis. Medicine. 2016; 95:e4225. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Divo MJ, Cabrera C, Casanova C, et al. Comorbidity distribution, clinical expression and survival in COPD patients with differing body mass index. J COPD F. 2014; 1:229–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hoffmann F, Albert MH, Arenz S, et al. Intracellular T-cell cytokine levels are age-dependent in healthy children and adults. Eur Cyt Netw. 2005; 16:283–288. [PubMed] [Google Scholar]
- 29.Gardner EM, Murasko DM. Age-related changes in type 1 and type 2 cytokine production in humans. Biogerontology. 2002; 3:271–290. [DOI] [PubMed] [Google Scholar]
- 30.Alvarez-Rodriguez L, Lopez-Hoyos M, Muñoz-Cacho P et al. Aging is associated with circulating cytokine dysregulation. Cell Immunol. 2012; 273:124–132. [DOI] [PubMed] [Google Scholar]
- 31.Larsson A, Carlsson L, Gordh T, et al. The effects of age and gender on plasma levels of 63 cytokines. J Immunol Meth. 2015; 425:58–61. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.