Am J Physiol Lung Cell Mol Physiol 304: L873–L882, 2013.
First published April 19, 2013; doi:10.1152/ajplung.00385.2012.
Pulmonary cytokine composition differs in the setting of alcohol use disorders
and cigarette smoking
Ellen L. Burnham,1 Elizabeth J. Kovacs,2 and Christopher S. Davis2
1
Division of Pulmonary Sciences and Critical Care Medicine, Department of Medicine, University of Colorado School of
Medicine, Aurora, Colorado; 2Alcohol Research Program, Burn and Shock Trauma Institute, Department of Surgery, Loyola
University Chicago, Stritch School of Medicine, Chicago, Illinois
Submitted 21 November 2012; accepted in final form 14 April 2013
regulated and normal T cell expressed and secreted; interleukins;
pneumonia; pneumococcus
pneumonia is the most common
cause of death from infectious diseases in developed countries,
with Streptococcus pneumoniae (S. pneumoniae) being the
pathogen responsible for most cases of bacterial pneumonia
worldwide. S. pneumoniae is found routinely in the human
nasopharynx as a commensal bystander; however, compromised host immunity can precipitate invasion of the lower
airways with subsequent development of pneumonia and systemic spread of infection (reviewed in Refs. 6 and 64). Two
common factors that can compromise host immunity are alcohol misuse and cigarette smoking. Alcohol misuse is considSEVERE COMMUNITY-ACQUIRED
Address for reprint requests and other correspondence: E. L. Burnham,
Univ. of Colorado School of Medicine, Anschutz Medical Campus, 12700 E.
19th St., C272, Aurora, CO 80045 (e-mail: [email protected]).
http://www.ajplung.org
ered to be present when an individual consumes quantities of
alcohol in excess of recommended limits and occurs in a
spectrum of severity (51). Alcohol abuse or alcohol dependence are found at the most severe end of the alcohol misuse
spectrum and are associated with medical, legal, or social
consequences by criteria established in the Diagnostic and
Statistical Manual of Mental Disorders, 4th edition (DSM-IV)
(54). Together, they may be referred to as alcohol use disorders, or AUDs. AUDs may be identified using validated questionnaires in clinical settings (45, 50).
Recent epidemiological studies have specifically reported an
association between severe pneumococcal infections associated with bacteremia and septic shock among individuals
with AUDs in locations including Spain (22), Canada (43, 55),
and Australia (26), illustrating the global health implications of
this relationship. Similarly, associations between cigarette
smoking and the occurrence of pneumococcal pneumonia with
septic shock (22) and pneumococcal bacteremia (55) have also
been reported. Notably, the risk for developing pneumococcal
pneumonia has been reported to increase as the quantity of
alcohol consumption increases (52); similarly, the odds of
developing invasive pneumococcal disease increases with increasing pack-per-year cigarette-smoking history (38). The
majority of individuals with AUDs smoke cigarettes and in fact
would be categorized as having nicotine dependency (49),
making this association clinically relevant. However, the effect
of combined AUDs and cigarette smoking on the risk for
pneumococcal infection has been relatively unexplored. Published data containing information regarding alcohol use and
smoking history have been limited by their lack of basis on
validated questionnaires to classify the severity of alcohol use
and have been limited to patients who likely have good access
to health care (38, 55).
Reasons for observed associations between AUDs, cigarette
smoking, and the development of pulmonary pneumococcal
disease are likely complex, but probably involve direct effects
of these substances on the lung. Small clinical studies have
explored the influence of these environmental factors on pulmonary cytokines, chemokines, and growth factors that are
integral to proper communication between different cell types
involved in the immune response. These factors may be elaborated by resident myeloid lineage cells within the lung, such
as alveolar macrophages, as well as the alveolar epithelium. In
human subjects with AUDs and animal models, proinflammatory cytokine activation in the lung has been reported, including enhanced induction of tumor necrosis factor (TNF)-␣,
interleukin (IL)-1␤, and IL-6 (13, 33, 39, 57). Similarly,
cigarette smoke exposure has also been reported to alter alveolar macrophage release and bronchoalveolar lavage (BAL)
1040-0605/13 Copyright © 2013 the American Physiological Society
L873
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Burnham EL, Kovacs EJ, Davis CS. Pulmonary cytokine composition differs in the setting of alcohol use disorders and cigarette smoking.
Am J Physiol Lung Cell Mol Physiol 304: L873–L882, 2013. First
published April 19, 2013; doi:10.1152/ajplung.00385.2012.—Alcohol
use disorders (AUDs), including alcohol abuse and dependence, and
cigarette smoking are widely acknowledged and common risk factors
for pneumococcal pneumonia. Reasons for these associations are
likely complex but may involve an imbalance in pro- and antiinflammatory cytokines within the lung. Delineating the specific
effects of alcohol, smoking, and their combination on pulmonary
cytokines may help unravel mechanisms that predispose these individuals to pneumococcal pneumonia. We hypothesized that the combination of AUD and cigarette smoking would be associated with
increased bronchoalveolar lavage (BAL) proinflammatory cytokines
and diminished anti-inflammatory cytokines, compared with either
AUDs or cigarette smoking alone. Acellular BAL fluid was obtained
from 20 subjects with AUDs, who were identified using a validated
questionnaire, and 19 control subjects, matched on the basis of age,
sex, and smoking history. Half were current cigarette smokers; baseline pulmonary function tests and chest radiographs were normal. A
positive relationship between regulated and normal T cell expressed
and secreted (RANTES) with increasing severity of alcohol dependence was observed, independent of cigarette smoking (P ⫽ 0.0001).
Cigarette smoking duration was associated with higher IL-1␤ (P ⫽
0.0009) but lower VEGF (P ⫽ 0.0007); cigarette smoking intensity
was characterized by higher IL-1␤ and lower VEGF and diminished
IL-12 (P ⫽ 0.0004). No synergistic effects of AUDs and cigarette
smoking were observed. Collectively, our work suggests that AUDs
and cigarette smoking each contribute to a proinflammatory pulmonary milieu in human subjects through independent effects on BAL
RANTES and IL-1␤. Furthermore, cigarette smoking additionally
influences BAL IL-12 and VEGF that may be relevant to the pulmonary immune response.
L874
BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
MATERIALS AND METHODS
Subject screening, recruitment, and enrollment. Subjects with
AUDs were recruited between 2008 and 2010 at the Denver Comprehensive Addictions Rehabilitation and Evaluation Services (Denver
CARES) center, an inpatient detoxification facility affiliated with
Denver Health and Hospital System in Denver, CO. Control subjects
without AUDs were recruited from the Denver VA Medical Center’s
smoking cessation clinic and via approved flyers posted on the
University of Colorado’s Anschutz Medical Campus in Aurora, CO.
The institutional review boards at all participating sites approved this
study, and all subjects provided written informed consent before their
participation in this protocol.
Subjects with AUDs were eligible to participate if they met all of
the following criteria at study entry: 1) an Alcohol Use Disorders
Identification Test (AUDIT) score of ⱖ8 for men or ⱖ5 for women,
2) alcohol use within the 7 days before enrollment, and 3) age of ⱖ21
yr. The AUDIT questionnaire is a standardized set of 10 questions that
detect current and previous alcohol abuse, which has been validated in
a variety of clinical settings (45). Furthermore, to meet eligibility as a
control, control subjects’ AUDIT values were required to be ⬍8 for
men or ⬍5 for women. Screening of potential control subjects
centered on matching these control subjects to AUD subjects in terms
of age, sex, and smoking history. With the use of AUDIT data, both
subjects and controls were stratified into zones 1– 4, classifying the
severity of their alcohol consumption (37, 50). Zone stratification was
performed to enable comparisons between AUDs and abstinence, as
well as between AUDs and low-risk drinking. AUDIT scoring zones
clinically correlated to abstinence (zone 1), low-risk drinking (zone
2), mild to moderate alcohol misuse with a lower risk of alcohol
dependence (zone 3), and severe alcohol misuse (zone 4).
Cigarette-smoking history was assessed by self-report. In subjects
who were either actively smoking cigarettes, or who had previously
smoked, the number of packs per day smoked was collected, as well
as total number of years smoking, to calculate the pack-year history.
In previous (but not current) smokers, the number of years that had
elapsed since stopping smoking was also recorded. Current smokers
were also analyzed according to packs per day smoked. Nonsmokers
were characterized as subjects who did not smoke at all in the past
year, moderate smokers currently consumed ⬍1 pack of cigarettes per
day, whereas heavy smokers consumed 1 or more packs per day (31).
Analyzing subjects in larger groups according to smoking intensity
was performed to optimize the clinical applicability of the results,
given the variability of cigarette smoking reported in our cohort.
In an effort to minimize the effects of comorbidities on outcome
variables, AUD subjects and controls were ineligible to participate in
the study if they met any of the following criteria: 1) prior medical
history of liver disease (documented history of cirrhosis, total bilirubin ⱖ2.0 mg/dl, or serum albumin ⬍3.0), 2) prior medical history of
gastrointestinal bleeding (due to the concern for varices), 3) prior
medical history of heart disease (documentation of ejection fraction ⬍50%, myocardial infarction, or severe valvular dysfunction),
4) prior medical history of renal disease (end-stage renal disease
requiring dialysis, or a serum creatinine ⱖ2 mg/dl), 5) prior medical
history of lung disease defined as an abnormal chest radiograph or
spirometry (forced vital capacity or forced expiratory volume in 1 s
⬍75%), 6) concurrent illicit drug use defined as a toxicology screen
for cocaine, opiates, or methamphetamines, 7) prior history of diabetes mellitus, 8) prior history of human immunodeficiency virus,
9) failure of the patient to provide informed consent, 10) pregnancy,
or 11) abnormal nutritional status. The nutritional status was assessed
using the nutritional risk index (NRI) with the subject’s albumin, current
weight, and usual weight values in the following equation (17): NRI ⫽
1.519 (albumin in g/l) ⫹ (current weight/usual weight) * 100 ⫹ 0.417.
Subjects were considered to have a normal nutritional status if the NRI
was ⱖ90 and an abnormal NRI if it was ⬍90. Potential subjects ⬎55 yr
of age were also excluded to minimize the presence of concomitant but
asymptomatic comorbidities.
Study protocol. Eligible subjects with AUDs were admitted to the
University of Colorado Hospital Clinical and Translational Research
Center (CTRC) for bronchoscopy. All bronchoscopy procedures were
performed utilizing telemetry monitoring and standard conscious
sedation protocols as previously described (25). The bronchoscope
was wedged into a subsegment of either the right middle lobe or
the lingula. Three to four 50-ml aliquots of sterile, room temperature
0.9% saline were sequentially instilled and recovered with gentle
aspiration. The first aspirated aliquot was not utilized in experiments
for this investigation. The second and subsequent aliquots were
combined and used in experiments as representative of the distal
airspaces. AUD subjects were discharged ⬃24 h after completion of
bronchoscopy. Control subjects had bronchoscopy performed in a
similar fashion but were discharged the same day.
Laboratory processing. BAL samples were transported to the
laboratory in sterile 50-ml conical tubes. BAL fluid was immediately
centrifuged (900 g, 5 min) after collection to separate cellular and
acellular components. Specimens that were not assayed immediately
were aliquoted and stored at ⫺80°C.
Cytokine/growth factor assays. Acellular BAL fluid was used in
assays to assess differences in cytokine/chemokine/growth factors
within the alveolar space using a multiplex bead array (Bio-Rad
Laboratories, Hercules, CA) according to manufacturer instructions
and as previously described by our own laboratories (2, 16). Multiplex
bead array cytokines, chemokines, and growth factors included: IL1␤, IL-1RA, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12,
IL-13, IL-15, IL-17, eotaxin, fibroblast growth factor (FGF), granulocyte colony stimulating factor, granulocyte-monocyte colony stimulating factor, interferon (IFN)-␥, IFN-␥-induced protein 10 (IP-10,
also known as CXCL10), monocyte chemotactic protein-1 (also
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fluid values for TNF-␣ (34, 69), IL-1␤ (9), and IL-6 (34).
Delineating the combined effects of alcohol and cigarette
smoke exposure on TNF-␣ and IL-1␤ may be particularly
useful because these cytokines are known to be integral to
pneumococcal growth and dissemination (46, 63). Furthermore, a broader knowledge regarding combined alcohol and
smoking effects on additional pulmonary mediators could also
provide insight to the clinical relevance of more recently
proposed pathogenic mechanisms underlying pneumococcal
invasion, including the role for adaptive immunity (28, 36).
Our group has previously explored the effects of AUDs,
with and without concomitant cigarette smoking, on components of innate immunity that may influence predisposition for
pneumococcal infection (7, 10, 12). We have established a
cohort of subjects with AUDs with a carefully characterized
cigarette-smoking history and lung disease assessment, along
with a cohort of control subjects matched on age, smoking, and
sex. In these investigations, we sought to characterize the
cytokine, chemokine, and growth factor milieu within the lung
of those with AUDs who are either current smokers or nonsmokers. Our goals were to determine whether additive or
synergistic alterations related to AUDs and cigarette smoking
were present that could influence the development of pneumococcal pneumonia. We also sought to establish whether doseresponse relationships between the severity of alcohol misuse
and cigarette smoke exposure could be detected. We hypothesized that the combination of AUDs and cigarette smoking
would be associated with an increased quantity of proinflammatory mediators in BAL, including IL-1␤, IL-6, and TNF-␣,
compared with either factor alone. Conversely, we postulated
that the levels of anti-inflammatory mediators, including IL-10
and IL-1 receptor antagonist (IL-1RA), would be diminished.
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BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
Table 1. Demographics of subjects with AUDs and controls
Control Subjects,
n ⫽ 19
42.7 ⫾ 7.0
50%
13 ⫾ 12
41.4 ⫾ 6.7
47%
9 ⫾ 14
0.58
1.0
0.41
10 [0-24]
0.5 ⫾ 0.4
0.5 [0–0.5]
65%
0 [0-20]
0.4 ⫾ 0.5
0 [0–0.6]
47%
0.18
0.25
0.27
0.34
0.05
40% (8/20)
10% (2/20)
30% (6/20)
20% (4/20)
25.4 ⫾ 9.1
0/20
74% (14/19)
16% (3/19)
11% (2/19)
0% (0/19)
2.3 ⫾ 1.8
5/19
0/20
14/19
4/20
0/19
16/20
0/19
5.1 ⫾ 1.7
0.7 ⫾ 0.9
P Value
⬍0.0001
⬍0.0001*
⬍0.0001
AUD, alcohol use disorder; AUDIT, alcohol use disorders identification test;
WBC, white blood cell. *Comparison of AUDIT zones between alcohol use
disorder subjects and control subjects using Pearson’s test.
known as CCL2), macrophage inflammatory protein (MIP)-1␣ (also
known as CCL3), MIP-1␤ (also known as CCL4), platelet-derived
growth factor, regulated and normal T cell expressed and secreted
(RANTES, also known as CCL5), TNF-␣, and VEGF. All measurements were performed in duplicate.
Statistical analyses. Data were classified as parametrically or nonparametrically distributed based on testing of the variances. Parametrically distributed data were analyzed with a paired t-test for continuous outcome variables. Categorical data were compared using the
Fisher’s exact test. Nonparametrically distributed data involving ⬎2
groups were analyzed using the Kruskal-Wallis test. When significant
differences within groups were observed, post hoc comparisons between pairs were subsequently performed using the Wilcoxon method.
Univariate correlations between continuous variables were also assessed using the Spearman method to assess correlation (␳). A version
of the false discovery rate procedure that accounts for related comparisons was used to establish which responses remained significantly
different, controlling for multiple testing (4, 5). Statistical analyses
were performed using JMP 9.2 (Cary, NC).
RESULTS
Baseline demographics of enrolled subjects. Twenty subjects with AUDs were enrolled in these investigations, along
Table 2. Cell counts and differentials of subjects with alcohol use disorders, stratified by smoking
WBC count in BAL, million cells
%monocytes/macrophages
Total monocyte count, millions
%lymphocytes
lymphocyte count, millions
%neutrophils
neutrophil count, millions
(⫹)AUD/(⫹)Smoking
(⫹)AUD/(-)Smoking
(-)AUD/(⫹)Smoking
(-)AUD/(-)Smoking
P Value
20.1 ⫾ 8.6
92.7 ⫾ 1.8
18.6 ⫾ 8.0
5.1 ⫾ 2.3
1.0 ⫾ 0.6
2.2 ⫾ 1.5
0.5 ⫾ 0.1
12.2 ⫾ 6.5
88.9 ⫾ 6.3
10.8 ⫾ 6.2
9.5 ⫾ 6.2
1.1 ⫾ 0.9
1.5 ⫾ 1.3
0.1 ⫾ 0.1
29.8 ⫾ 19.8†
92.8 ⫾ 1.9
27.7 ⫾ 18.2*
5.2 ⫾ 2.9
1.7 ⫾ 1.7
1.9 ⫾ 1.2
0.5 ⫾ 0.1
10.3 ⫾ 4.2
90.1 ⫾ 8.6
9.4 ⫾ 4.4
7.0 ⫾ 5.5
0.6 ⫾ 0.4
2.9 ⫾ 4.0
0.2 ⫾ 0.1
0.002
0.36
0.002
0.14
0.17
0.59
0.09
Applicable values are means ⫾ SE. Comparisons assessed via ANOVA, with post hoc comparisons corrected for multiple comparisons. *P ⬍ 0.007 compared
with (⫹)AUD/(-)smoke and to (-)AUD/(-)smoke; †P ⬍ 0.008 compared with (⫹)AUD/(-)smoke and to (-)AUD/(-)smoke.
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Age
Current smokers, %
Pack-year smoking, mean
Pack-year smoking,
median
Packs per day, mean
Packs per day, median
Sex, % men
Race, %
White
African-American
Latino
Native American
AUDIT Score
Zone 1 (abstinence)
Zone 2 (low-risk
drinking)
Zone 3 (moderate alcohol
misuse)
Zone 4 (severe alcohol
misuse)
Days per week drinking
alcohol
AUD Subjects,
n ⫽ 20
with 19 healthy controls (Table 1). Ages between the two
groups were similar as were the percentage of current smokers.
There was a nonsignificant difference in the number of men
between groups. Racial differences were present between the
AUDs and control groups; more Caucasian subjects were
enrolled in the control group, whereas more Native Americans
were enrolled in the AUD group. Cigarette-smoking habits did
not vary significantly by age (P ⫽ 0.87), by sex (P ⫽ 1.0), or
by race (P ⫽ 0.08). The AUD group had significantly higher
AUDIT scores than did controls, with AUD subjects falling
exclusively in consumption zones 3 and 4, whereas control
subjects fell in zones 1 and 2.
Cell counts and differentials from BAL were similar between the AUD and non-AUD subjects although smokers in
each group had higher total cell counts (P ⫽ 0.002 for comparison across all AUD and non-AUD subjects, stratified by
smoking, Table 2). Similarly, smokers both with and without
AUDs had significantly higher total monocyte counts (P ⫽
0.002). The percentage of each cell type did not vary by
alcohol or smoking history.
BAL measurements for IL-2, IL-4, IL-5, IL-9, IL-17, eotaxin, FGF, and MIP-1␣ were below the detection limit of the
assay for the majority of subjects (⬎50%) assessed; therefore,
results for these factors were not analyzed further.
Dose-dependent association between BAL RANTES and alcohol use. Correlations in BAL cytokines were examined in
relation to the AUDIT scores from the 39 total subjects
collected at the time of bronchoscopy. A positive correlation
was observed between the quantity of BAL RANTES and
subjects’ AUDIT scores (␳ ⫽ 0.58, P ⫽ 0.0001, Fig. 1A).
Comparing RANTES across AUDIT zones confirmed that,
with increasing severity of alcohol dependence, RANTES was
increased (P ⫽ 0.001, Fig. 1B). Moreover, values for both zone
3 (P ⫽ 0.005) and zone 4 (P ⫽ 0.0004) were significantly
greater than those from subjects in zone 2 (low-risk drinkers),
accounting for multiple comparisons. No significant correlations were observed between AUDIT scores and any other
cytokine, chemokine, or growth factor in BAL, including
IL-1␤ (P ⫽ 0.83), IL-6 (P ⫽ 0.94), TNF-␣ (P ⫽ 0.25), IL-15
(P ⫽ 0.11), IP-10 (P ⫽ 0.31), IL-8 (P ⫽ 0.91), or IFN-␥ (P ⫽
0.35). Among all subjects with AUDs, BAL RANTES was
positively associated with IP-10 (␳ ⫽ 0.53, P ⫽ 0.02).
Dose-dependent association of cytokines in BAL and cigarette
smoking. Potential associations between cigarette-smoking history
and BAL cytokines were examined. Pack-year data were missing
from 4 of the 19 currently smoking AUD and control subjects.
Five current nonsmokers had smoked previously but had stopped
smoking more than 1 yr before bronchoscopy. In the cohort of
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BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
A
BAL RANTES, pg/mL
ρ=0.58,
p=0.0001
p=0.001
BAL RANTES, pg/mL
B
AUDIT Zone
Fig. 1. Regulated and normal T cell expressed and secreted (RANTES, also
known as CCL5) present in bronchoalveolar lavage (BAL) increased as the
severity of alcohol misuse increased in the 39 alcohol use disorder (AUD)
subjects and controls. Alcohol misuse was characterized in severity according
to the Alcohol Use Disorders Identification Test (AUDIT). A: AUDIT score vs.
BAL RANTES (Spearman’s correlation coefficient ⫽ ␳). B: subjects and
controls were stratified into 4 zones according to AUDIT scores. Controls were
contained in zone 1 (abstinence) and zone 2 (low-risk drinking), whereas AUD
subjects were contained in zone 3 (moderate alcohol misuse) and zone 4
(severe alcohol misuse). Kruskal-Wallis test used in analyses.
35 AUD subjects and controls (both current smokers and nonsmokers) who had complete smoking pack-year data, significantly
positive correlations were observed between pack-years smoked
and IL-1␤ (␳ ⫽ 0.53, P ⫽ 0.0009) (Fig. 2). Conversely, inverse
associations between VEGF and pack-year smoked were observed for (␳ ⫽ ⫺0.54, P ⫽ 0.0007). The direction and significance of these associations persisted when the five previously
smoking, but not currently smoking, individuals were excluded
from the analyses. No significant correlations were observed
between pack-years and IL-6 (␳ ⫽ 0.15), IL-8 (␳ ⫽ 0.40), IFN-␥
(␳ ⫽ ⫺0.31), IL-1RA (␳ ⫽ 0.34), IL-12 (␳ ⫽ ⫺0.48), or TNF-␣
(␳ ⫽ ⫺0.15).
Next, the relationship between packs per day smoking and
cytokines was examined in the 37 subjects with complete pack
per day smoking data. In univariate analyses, significant positive correlations were observed between packs per day smok-
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AUDIT Score
ing and IL-1␤ (␳ ⫽ 0.66, P ⬍ 0.0001) and IL-1RA (␳ ⫽ 0.46,
P ⫽ 0.005), whereas significant inverse correlations were
observed between packs per day smoking with IL-12 (␳ ⫽
⫺0.58, P ⫽ 0.0002) and VEGF (␳ ⫽ ⫺0.58, P ⫽ 0.0002),
correcting for multiple comparisons. After stratifying subjects
with complete pack per day smoking data into noncurrent
smokers (n ⫽ 20), moderate smokers (n ⫽ 10), and heavy
smokers (n ⫽ 7) (Fig. 3), we noticed that IL-1␤ values
increased with the intensity of cigarette smoking (P ⫽ 0.0002);
both moderate (P ⫽ 0.002) and heavy (P ⫽ 0.0008) cigarette
smokers had significantly higher IL-1␤ values than did nonsmokers in post hoc comparisons. Similar results were observed for IL-1RA (P ⫽ 0.004) although only the difference in
values between moderate smokers and nonsmokers remained
in post hoc comparisons (P ⫽ 0.002). In contrast, IL-12 (P ⫽
0.0004) and VEGF (P ⫽ 0.0004) also differed significantly
across the three levels of smoking. For each of these factors,
values in the nonsmoking group were significantly higher than
either the moderate or heavy smoking groups.
Effect of combined AUDs and cigarette smoking on BAL
cytokine, chemokine, and growth factor composition. The 39
subjects were stratified into four groups based on a history of
AUDs and current cigarette smoking. Ten subjects did not have
an AUD and did not smoke; nine did not have an AUD but did
smoke; ten had an AUD but did not smoke; and ten had an
AUD and smoked. Significant differences were noted to be
present across the four groups for BAL IL-1␤ (P ⫽ 0.001),
RANTES (P ⫽ 0.001), IL-12 (P ⫽ 0.0006), and VEGF (P ⫽
0.0003) (Fig. 4). After post hoc within-group comparisons
were performed, cigarette smoking, but not alcohol, appeared
to be driving both the higher values of BAL IL-1␤, as well as
the lower values of BAL IL-12 and VEGF. Examining the data
among AUD subjects only revealed that subjects with AUDs
who smoked cigarettes had significantly elevated BAL IL-1␤
compared with AUD subjects who did not smoke. However,
values for the AUD group who smoked were not significantly
different from non-AUD smoking controls. Similarly, for BAL
IL-12 and VEGF, among AUD subjects only, lower values
were observed in AUD subjects who smoked. However, as
with IL-1␤, values for the AUD group who smoked were not
significantly different from non-AUD subjects who smoked. In
contrast, BAL RANTES values among subjects with AUDs
were significantly higher compared with non-AUD subjects,
regardless of cigarette smoking. In the AUD subjects only,
RANTES values were not significantly more elevated among
cigarette smokers. Therefore, our data suggest that smoking
influences BAL IL-1␤, IL-12, and VEGF, independent of
AUDs, whereas an AUD history influences RANTES, independent of smoking.
Correlations between demographic factors and cytokine values.
To determine whether specific, unalterable demographic characteristics might have influenced our BAL data, we examined
the relationship of age, race, and sex with different cytokine
values. We observed that age was associated with decreased
IL-7 (␳ ⫽ ⫺0.40, P ⫽ 0.01). Although our cohort consisted
primarily of white subjects, we did examine a number of
African-American, Hispanic, and Native Americans as well.
However, of the 19 evaluable cytokines/growth factors within
BAL, we did not observe any significant differences referable
to race to persist after correcting for multiple comparisons.
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BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
A
B
ρ=0.53
p=0.0009
BAL IL-1β, pg/mL
BAL VEGF, pg/mL
ρ= -0.54
p=0.0007
Pack-year
Fig. 2. In current smokers (n ⫽ 35), significant associations were determined to be present when cigarette-smoking duration, assessed via pack-year history, was
assessed in relationship with BAL IL-1␤ (A), and VEGF (B). Spearman’s correlation coefficient ⫽ ␳.
Similarly, there were no remarkable cytokine differences between women in the cohort compared with men.
Correlations between resident lung cells and cytokine values.
To help establish the potential cells of origin responsible for
cytokine production, correlations between the absolute number
of different cell types obtained during BAL and cytokine
values were examined. The total white blood cell number per
milliliter of BAL fluid was positively associated with IL-1␤
(␳ ⫽ 0.61, P ⬍ 0.0001) but inversely associated with IL-12
(␳ ⫽ ⫺0.49, P ⫽ 0.002) and VEGF (␳ ⫽ ⫺0.48, P ⫽ 0.002).
Results were similar for the absolute monocyte count that was
positively associated with IL-1␤ (␳ ⫽ 0.58, P ⫽ 0.0001) and
negatively associated with IL-12 (␳ ⫽ ⫺0.52, P ⫽ 0.0006) and
VEGF (␳ ⫽ ⫺0.51, P ⫽ 0.0009). Finally, the absolute neutrophil count was most strongly associated with IL-1␤ (␳ ⫽ 0.48,
P ⫽ 0.002) and IL-1RA (␳ ⫽ 0.48, P ⫽ 0.002) but inversely
associated with IL-12 (␳ ⫽ ⫺0.42, P ⫽ 0.007). No correlation
between IL-10 or RANTES and the total white blood cell count
or any specific cell type was observed.
DISCUSSION
In these investigations, AUDs and cigarette smoking were
associated with alterations in pulmonary levels of specific
cytokines, chemokines, and growth factors. The relationship of
these two environmental mediators to measured BAL cytokines appeared related to different inflammatory pathways, and
no evidence of synergism between AUDs and smoking was
observed. Nevertheless, the elevation of BAL RANTES in
association with AUDs, along with elevated IL-1␤ in association with cigarette smoking, suggests that an independent but
potentially additive proinflammatory milieu may be present in
individuals who are coexposed to both alcohol and cigarettes.
To our knowledge, this is the first report in a sizable cohort of
well-characterized human subjects of elevated BAL RANTES
in association with AUD severity; alterations in BAL IL-12
and VEGF in the context of cigarette smoking and AUDs are
also novel. We confirmed previously reported positive relationships between cigarette smoking with BAL IL-1␤ expression
(31) and decreased VEGF expression (30, 60). Dose-response
relationships between cigarette smoking with IL-1␤, IL-1RA,
IL-12, and VEGF were also observed. Collectively, our work
suggests that cigarette smoking contributes to a proinflammatory milieu characterized via increasing IL-1␤, whereas increases in RANTES associated with AUDs may further accentuate this proinflammatory environment. Moreover, the association of tobacco with decreased IL-12 and VEGF suggests
potential influences on cellular immunity and alveolar epithelial permeability related to these substances, independent of
AUDs. Our observations provide new, clinically relevant insight regarding the relationship between AUDs, cigarette
smoking, and pneumococcal pulmonary disease. These data
may also help explain the severity of pneumococcal illness, as
several of these cytokines, chemokines, and growth factors
have been reported to have specific roles in colonization,
infection, and clearance of pneumococcus.
Alveolar macrophages produce type I interferons in response
to recognition of pneumococcal DNA. This recognition stimulates RANTES production in infected cells and neighboring
alveolar epithelial cells (28). RANTES is a CC chemokine that
serves as a chemoattractant for a variety of immune cell types
(53). In our subjects with AUDs, RANTES levels correlated
with levels of IP-10, a CXC chemokine secreted by cells in
response to IFN-␥. In the setting of experimental pneumococcal pneumonia, pulmonary levels of RANTES and IP-10 may
be increased (21, 40) and, along with other proinflammatory
cytokines, appear to play a role in the pneumococcal immune
response. In animal experiments using an EF3030 pneumococcal strain, RANTES also influenced the production of antibodies that limited the progression of nasopharyngeal pneumococcal carriage to frank pneumonia and influenced survival (40).
Our observation that BAL RANTES was increased in a dosedependent fashion among subjects with AUDs suggests a
potential protective role of alcohol in pneumococcal infection.
However, published investigations have alluded to a critical
effect of alcohol metabolism on RANTES expression (70) and
suggest that overexpression of RANTES may be pathological.
Moreover, RANTES overproduction has recently been reported to decrease T cell progeny and increase myeloid progenitors in a murine model. This could influence immune
responses to pathogens and may be important in aging-associ-
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Pack-year
L878
BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
*
*
BAL IL-1β, pg/mL
p=0.0002
B
p=0.004
BAL IL-1RA, pg/mL
A
D
p=0.0004
*
*
BAL VEGF, pg/mL
BAL IL-12, pg/mL
p=0.0004
*
*
Fig. 3. Correlations between cigarette-smoking intensity, assessed via packs smoked per day, were observed with BAL IL-1␤ (A), IL-1 receptor antagonist
(IL-1RA) (B), IL-12 (C), and VEGF (D). Nonsmokers are not currently smoking (n ⫽ 20); moderate smokers currently smoke ⬍1 pack per day (n ⫽ 10); heavy
smokers currently smoke ⱖ1 packs per day (n ⫽ 7). Boxes indicate intraquartile range of data, with medians (50th percentile); whiskers indicate 10th and 90th
percentiles of data. Kruskal-Wallis testing was used to compare medians across all 3 groups (P values provided). Post hoc within-group comparisons were also
performed. Both moderate and heavy smokers had significantly different median values than nonsmokers for BAL IL-1␤, IL-12, and VEGF; for IL-1RA, only
moderate smokers had significantly different median values than did nonsmokers (*P ⬍ 0.05 compared with nonsmokers).
ated immunodeficiency (20). As a final consideration, downregulation of RANTES receptor, CCR5, could also have affected our results; AUDs have previously been associated with
a decrease in CD4⫹ T cell CCR5 density (41) that potentially
influences the balance between cellular and humoral immunity.
Understanding the effect of alcohol use on RANTES expression in the lung and nasopharynx, as well as its effect on
CCR5, its receptor, will clarify the importance of this cytokine
on pneumococcal susceptibility among those with AUDs.
Although the association of serious pneumococcal infections
and cigarette smoking have been reported consistently in the
literature, reasons for this association are incompletely understood. A recent series examining BAL from a large cohort of
smokers with no pulmonary symptomatology, normal pulmonary function tests, and chest radiographs provides convincing
evidence that current smoking in and of itself leads to an
increased total number of recovered cells in BAL (27), suggesting that smoking without frank pulmonary disease can
contribute to a proinflammatory state within the lung. In our
series of smokers, IL-1␤ values were most strongly associated
with the absolute number of monocytes. The IL-1 family of
cytokines is important in early innate immune responses (58);
notably, a dose-dependent association between cigarette smoking with BAL IL-1␤ has previously been reported (31). In
animal models exposed to cigarette smoke extract, IL-1␤
production and signaling along with pulmonary neutrophilia
are believed to occur through Toll-like receptor (TLR)4 activation (18). TLRs are key initiators in recognizing pathogenassociated molecular peptides, including pneumolysin, produced by the pneumococcus (32). Pneumolysin binds directly
to TLR4, where it results in production of proinflammatory
mediators and induces epithelial cell apoptosis (56). In a
recently published investigation using an experimental model
of pneumococcal infection, chronic cigarette smoke exposure
followed by challenge with live S. pneumoniae was associated
with increased IL-1␤ in lung homogenates, BAL neutrophilia,
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C
*
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BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
A
B
*
*#
*+
p=0.001
*
BALANTES, pg/mL
BAL IL-1β, pg/mL
p=0.001
(-)AUD
(+)smoke
(+)AUD
(-)smoke
(+)AUD
(+)smoke
C
(-)AUD
(-)smoke
(-)AUD
(+)smoke
(+)AUD
(-)smoke
(+)AUD
(+)smoke
D
p=0.0003
*#
*
(-)AUD
(-)smoke
(-)AUD
(+)smoke
(+)AUD
(-)smoke
(+)AUD
(+)smoke
BAL VEGF, pg/mL
BAL IL-12, pg/mL
p=0.0006
*#
*
(-)AUD
(-)smoke
(-)AUD
(+)smoke
(+)AUD
(-)smoke
(+)AUD
(+)smoke
Fig. 4. The 39 subjects were stratified by AUDs and current tobacco use: (-)AUDs and (-)smoking, n ⫽ 10; (-)AUDs and (⫹)smoking, n ⫽ 9; (⫹)AUDs and
(-)smoking, n ⫽ 10; (⫹)AUDs and (⫹)smoking, n ⫽ 10. Boxes indicate intraquartile range of data, with medians (50th percentile); whiskers indicate 10th and
90th percentile of data. Significant differences between median values across the 4 groups were observed in BAL IL-1␤ (A), RANTES (B), IL-12 (C), and VEGF
(D), (P values provided, using Kruskal-Wallis testing). Subsequent post hoc comparisons between the 4 subgroups (using the Wilcoxon method) revealed that
smokers, either with or without AUDs, had significantly higher IL-1␤ than did non-AUD, nonsmokers. For RANTES, both AUD smokers and nonsmokers had
significantly higher values than did non-AUD, nonsmokers. Conversely, smokers, either with or without AUDs, had significantly lower IL-12 and VEGF
compared with non-AUD, nonsmokers. For these comparisons, *P ⬍ 0.01. Among AUD subjects only, comparing smokers to nonsmokers revealed significant
differences in IL-1␤, IL-12, and VEGF (#P ⬍ 0.02). Finally, among smoking subjects only, comparing AUD to non-AUD subjects revealed significant
differences in RANTES (⫹P ⬍ 0.008).
increased pulmonary bacterial burden, and worsened clinical
signs of pneumococcal pneumonia (42). Our investigations
suggest the possibility that cigarette smoke exposure results in
a baseline increase in the proinflammatory state of the lung.
Upon exposure to products of the pneumococcus (i.e., pneumolysin), additional inflammation may further overwhelm the
host response, resulting in an inability to clear the pathogen
with subsequent disease progression, perhaps due to slowed
resolution of neutrophilia in conjunction with damaged alveolar epithelium.
IL-12 is a regulatory cytokine that contributes to both innate
and acquired immunity, with a crucial role in host resistance to
pneumococcal infection (59). IL-12 is derived from lymphocytes and has the ability to stimulate the proliferation of T
cells, induce NK cell formation, and induce IFN-␥ production.
Chronic cigarette smoke exposure has been associated with a
significant increase in BAL IL-12 in a mouse model (8), but no
reports in the literature comment on the effect of either alcohol
or smoking on this cytokine in lung. Understanding the role of
IL-12 on pneumococcal immunity in humans may be important
in improving the efficacy of vaccines to combat this pathogen,
particularly in high-risk groups (26). IL-12 has been proposed
as an adjuvant with recombinant pneumococcal protein antigens in experimental mucosal vaccines (67). Ex vivo human
BAL cells that had been treated using this strategy were determined to have increased TNF-␣ production (and to a lesser extent,
IFN-␥ production) compared with exposure of cells with pneumococcal antigen alone (68). Nevertheless, progress in the use of
IL-12 as an adjuvant for human pneumococcal vaccines requires
further investigation to limit its toxicity and to optimize efficacious delivery to the mucosa (24).
Cigarette smoking has been associated with decreased BAL
VEGF and VEGF receptor-2 expression; levels become more
decreased as smoking-related lung disease progresses (30, 60).
These abnormalities may be related to the direct effect of
cigarette smoke on airway epithelial cells (61), where it can
induce cellular apoptosis and necrosis (29). In contrast, moderate doses of alcohol experimentally enhance VEGF expression, as well its interaction with the VEGFR-2 receptor (14 –
15, 23). Abnormal VEGF homeostasis in the lung elicited by
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(-)AUD
(-)smoke
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BRONCHOALVEOLAR LAVAGE CYTOKINES IN ALCOHOLISM AND SMOKING
Nevertheless, subjects with AUDs were recruited from a detoxification center that had a long-standing treatment relationship with
these individuals, enhancing the validity of their AUD characterization. Potential unmeasured confounders might have influenced
our results, such as occult liver disease. However, screening
laboratory work and pulmonary examination suggested no occult
illness in our subjects or controls. Finally, we acknowledge that
these investigations do not prove that alcohol or cigarettes are
directly causal to the cytokine differences we observed. Our work
does not explain the operative mechanisms underlying the reasons
that AUDs, cigarette smoking, or both may contribute to pulmonary infections, including pneumococcal pneumonia. It does,
however, provide a framework to understand the potential associations of AUDs and smoking on pulmonary cytokines, thereby
directing future investigations to help unravel mechanisms of
increased predisposition for pulmonary infections in this population.
In conclusion, we observed an association between the proinflammatory cytokine RANTES and AUDs that was independent
of cigarette smoking. We confirmed that cigarette smoking was
associated with an increase in the proinflammatory cytokine
IL-1␤, as well as decreases in IL-12 and VEGF. These abnormalities suggest an excessively proinflammatory state in the lung in
the setting of AUDs and cigarette smoking and also potential
influences on adaptive immunity (via IL-12) and alterations in
epithelial permeability (via VEGF). Collectively, these observations can help delineate the relationship of AUDs and cigarette
smoking on the predisposition for pneumococcal pulmonary infection and also provide insight regarding reasons for increased
disease severity among these individuals.
ACKNOWLEDGMENTS
The authors thank Luis Ramirez for assistance with laboratory assays, Dr.
Douglas Curran-Everett for biostatistical assistance, the staff at Denver
CARES to facilitate the performance of this research, and the support of Dr.
Robert House.
GRANTS
This study was supported in part by R24 AA019661 (E. Burnham),
NIH/NCATS Colorado CTSI Grant Number UL1 TR000154T32 (E. Burnham), T32 AA13527 (C. Davis), the Ralph and Marian C Falk Medical
Research Trust (E. Kovacs), and R01 AA012034 (E. Kovacs). Contents are the
authors’ sole responsibility and do not necessarily represent official NIH
views.
DISCLOSURES
No conflicts of interest, financial or otherwise, are declared by the authors.
AUTHOR CONTRIBUTIONS
Author contributions: E.L.B., E.J.K., and C.S.D. conception and design of
research; E.L.B. analyzed data; E.L.B., E.J.K., and C.S.D. interpreted results of
experiments; E.L.B. prepared figures; E.L.B. drafted manuscript; E.L.B.,
E.J.K., and C.S.D. edited and revised manuscript; E.L.B., E.J.K., and C.S.D.
approved final version of manuscript; C.S.D. performed experiments.
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