One airway: Biomarkers of protection from

upper and lower airway injury after World

Trade Center exposure

Soo Jung Cho a, Ghislaine C. Echevarria b,c, Sophia Kwon a,

Bushra Naveed a

, Edward J. Schenck a, Jun Tsukiji a,

William N. Rom a,d

, David J. Prezant e,f, Anna Nolan a,d,e,

Michael D. Weiden a,d,e,

*

a Division of Pulmonary, Critical Care and Sleep, New York University, School of Medicine New York,

NY, USA

b Divisio ́n de Anestesiologı ́a, Escuela de Medicina, Pontificia Universidad Cato ́lica de Chile,

Santiago, Chile

cNew York University, School of Medicine, Department of Medicine, New York, NY, USA

dNew York University, School of Medicine, Department of Environmental Medicine, Tuxedo Park,

NY, USA

e Bureau of Health Services and Office of Medical Affairs, Fire Department of New York, Brooklyn,

NY, USA

f

Pulmonary Medicine Division, Department of Medicine, Montefiore Medical Center and Albert Einstein

College of Medicine, Bronx, NY, USA

Received 17 September 2013; accepted 3 November 2013

Available online 13 November 2013

KEYWORDS

One airway;

Chronic

rhinosinusitis;

World Trade Center;

Innate immunity

Summary

Background: Firefighters exposed to World Trade Center (WTC) dust have developed chronic rhinosinusitis (CRS) and abnormal forced expiratory volume in 1 s (FEV1). Overlapping but distinct immune responses may be responsible for the clinical manifestations of upper and lower airway

injury. We investigated whether a panel of inflammatory cytokines, either associated or not associated with WTC-LI, can predict future chronic rhinosinusitis disease and its severity.

Methods: Serum obtained within six months of 9/11/2001 from 179 WTC exposed firefighters

presenting for subspecialty evaluation prior to 3/2008 was assayed for 39 cytokines. The

* Corresponding author. New York University School of Medicine, 550 1st Ave, New York, NY 10016, USA. Tel.: þ1 212 263 6479; fax: þ1 212

263 8442.

E-mail address: michael.weiden@med.nyu.edu (M.D. Weiden).

0954-6111 a 2013 The Authors. Published by Elsevier Ltd.

http://dx.doi.org/10.1016/j.rmed.2013.11.002

Available online at www.sciencedirect.com

ScienceDirect

journal homepage: www.elsevier.com/locate/rmed

Respiratory Medicine (2014) 108, 162e170

Open access under CC BY-NC-ND license.
main outcomes were medically managed CRS (N Z 62) and more severe CRS cases requiring

sinus surgery (N Z 14). We tested biomarker-CRS severity association using ordinal logistic

regression analysis.

Results: Increasing serum IL-6, IL-8, GRO and neutrophil concentration reduced the risk of

CRS progression. Conversely, increasing TNF-a increased the risk of progression. In a multivariable model adjusted for exposure intensity, increasing IL-6, TNF-a and neutrophil concentration remained significant predictors of progression. Elevated IL-6 levels and

neutrophil counts also reduced the risk of abnormal FEV1 but in contrast to CRS, increased

TNF-a did not increase the risk of abnormal FEV1.

Conclusions: Our study demonstrates both independent and overlapping biomarker associations with upper and lower respiratory injury, and suggests that the innate immune response

may play a protective role against CRS and abnormal lung function in those with WTC exposure.

a 2013 The Authors. Published by Elsevier Ltd.

Introduction

The World Trade Center (WTC) collapse produced vast

quantities of respirable dust affecting Fire Department of

New York (FDNY) rescue workers, other exposed workers,

lower Manhattan residents and children [1e6]. WTC dust

was alkaline (pH, 9.2e11.5) and was comprised of metals,

radionuclides, ionic species, asbestos, polycyclic aromatic

hydrocarbons, polychlorinated biphenyls, polychlorinated

dibenzodioxines and other potentially hazardous materials.

The bulk of WTC particulate matter (PM) was larger than

10 mm, which usually is filtered in the nasopharynx [7].

However, the body’s usual protective barriers were overwhelmed, producing intense dust exposure to both the

upper and lower airways [2].

A high incidence of upper and lower airway respiratory

disorders has persisted in WTC exposed firefighters years

after 9/11 [8]. Chronic rhinosinusitis (CRS) has been the

most common manifestation of upper airway injury in this

population. Prior to 9/11, only 4.4% of FDNY firefighters

reported rhinosinusitis symptoms. By one year after 9/11,

self-reported rhinosinusitis symptoms had increased 10-fold

(45.1%) and persisted above 30% well into the fifth year

after 9/11 [9,10]. Numerous disability claims arising from

respiratory disorders such as CRS have had substantial

financial ramifications [11].

Shared upper and lower airway immune response is well

established in the spectrum of atopic rhinosinusitis and

allergic asthma [12e14] and as a cause of chronic cough

syndrome [15]. CRS in the FDNY firefighter cohort exists

both in isolation and in accompaniment with WTC lower

airway injury (WTC-LI) [16], portending overlapping but

distinct immune pathogenesis of irritant-induced upper

and lower airway injury. The pathophysiology of CRS

after occupational irritant exposure has not been well

characterized.

We have previously reported inflammatory biomarkers

that are predictive of future abnormal lung function in the

FDNY firefighter cohort [17]. No biomarker studies have

been published that predict the long-term outcome of

upper airway disease in this population. We investigated

whether a panel of inflammatory cytokines, either associated or not associated with WTC-LI, can predict future

chronic rhinosinusitis disease and its severity.

Methods

Study design

All WTC exposed FDNY workers were enrolled in the

Medical Monitoring and Treatment Program. FDNY workers

(N Z 1720) who complained of any respiratory symptoms

between October 1, 2011 and March 10, 2008 were systematically sent for subspecialty pulmonary evaluation

(SPE). We performed a nested caseecohort study on firefighters using this baseline cohort of 1720 exposed, symptomatic workers. Study subgroups were derived from the

baseline cohort after excluding for patients with prior lung

or sinus disease. Fig. 1. Chronic rhinosinusitis (CRS) in our

study was defined as nasal and/or sinus inflammation, with

Abbreviations

CRS chronic rhinosinusitis

FDNY Fire Department City of New York

FEV1 forced expiratory volume in 1 s

GRO growth-regulated oncogene

IL-6 interleukin-6

IL-8 interleukin-8

LLN lower limit of normal

MME medical monitoring entry

NHANESNational Health and Nutrition

Examination Survey

PFT pulmonary function test

PM particulate matter

PMN polymorphonuclear neutrophil

SPE subspecialty pulmonary evaluation

TNF-a tumor necrosis factor-alpha

WTC World Trade Center

WTC-LI World Trade Center-related lower

airway injury

One airway, biomarkers of both upper and lower airway 163

Open access under CC BY-NC-ND license.
recurrence of symptoms after re-exposure to irritants [16].

The diagnosis of chronic rhinosinusitis was determined by

the evaluating physician and was confirmed by sinus CT

scan and treated medically with nasal saline lavage, nasal

steroids decongestant and proton pump inhibitor [18]. The

time of CRS diagnosis was abstracted from the FDNY electronic medical record (FDNY-eMR). Of the 179-study patients, whose serum were available for biomarker assay, 76

developed CRS; 62 were medically managed and 14 were

refractory to medical management and elected to have

sinus surgery. Refractory was defined as requiring at least 3

months of medical management with persistent symptoms,

despite reported medication adherence that substantially

interfered with the patient’s quality of life. Once medical

management failed, patients were referred to ENT subspecialty clinic. For our analysis of progression, we

confirmed in the FDNY-eMR an ordered progression from no

CRS prior to 9/11/01 to post-9/11/01 medically managed

sinusitis and, when refractory to medical management, to

surgically managed sinusitis. Subjects signed informed

consents approved by the institutional review boards of

Montefiore Medical Center (#07e09e320) and New York

University (#11e00439).

Demographics

Age, race and years of service at FDNY were obtained

from the FDNY-WTC-monitoring database. Body mass

indices (BMIs) were calculated from height and weight

measured at the time of serum draw. Degree of exposure

was self-reported at the first FDNY-WTC-monitoring and

was categorized using the FDNY-WTC Exposure Intensity

Index (Arrival Time): i. Presented on the morning of 9/11/

2001 and ii. Arrived between afternoon on 9/11/2001 and

9/12/2001 [17,19]. Those arrived after day-three were

excluded from analysis as a result of their low numbers in

this sample. Subjects underwent spirometry at the time of

serum collection as previously described [17,19,20].

Serum sampling and analysis

Blood drawn at the first post-9/11 FDNY-WTC-monitoring

exam was processed as described [17]. Serum was

thawed once at 4 C and assayed using a proinflammatory panel (39-Plex including EGF, Eotaxin,

FGF-2, Flt-3 ligand, Fractalkine, G-CSF, GM-CSF, GRO,

IFN-a2, IFN-g, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15,

IL-17, IL-1Ra, IL-1a, IL-1b, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7,

IL-8, IL-9, IP-10, MCP-1, MCP-3, MDC (CCL22), MIP-1a,

MIP-1b, TGF-a, TNF-a, TNF-b, VEGF, sCD40L, sIL-2Ra,

Millipore, Billerica, MA) and Metabolic Hormone Panel

(13-Plex including Amylin, C-Peptide, Ghrelin, GIP, GLP1, Glucagon, IL-6, Insulin, Leptin, MCP-1, PP, PYY, TNFa, Millipore, Billerica, MA) according to manufacturer’s

instructions (Millipore) and analyzed on a Luminex 200IS

(Luminex Corporation).

Statistical analysis

We tested normality using the ShapiroeWilk test and QeQ

plots. JonckheereeTerpstra or Wilcoxon rank-sum

tested for group comparisons. The Chi-squared or

Fisher’s exact tested for inferences on proportions.

Ordinal logistic regression analysis with the proportionalodds model tested association between inflammatory

biomarkers and progressive sinusitis severity. The

approximate likelihood-ratio test of proportionality of

odds and the Brant test of parallel lines assumption

assessed model appropriateness. Since biomarkers were

severely skewed, we log-transformed them before

including them as continuous covariates in the model.

Logistic regression was used to assess the association

between biomarkers and abnormal forced expiratory

volume in 1 s (FEV1 less than lower limit of normal). A

two-sided P-value less than 0.05 was considered significant. All analyses were performed with STATA/SE version

12.1 (StataCorp LP, College Station, TX).

Results

Study design and demographics

The derivation of medical CRS cases, surgical CRS cases and

controls with no sinusitis during the study period is

described in Fig. 1. Demographics of the baseline cohort

and all study subgroups are shown in Table 1. Serum obtained for biomarker analysis was drawn on average 2e3

months post-9/11. There was no significant difference in

the time to serum collection amongst these subgroups

(P Z 0.118). Cases and controls had similar age at 9/11,

years of firefighting service, body mass index, racial distribution and WTC exposure intensity. There were no significant differences in spirometric parameters including

FEV1 and FEV1/FVC in cases versus controls.

WTC Exposed FDNY workers Medical 

Monitoring and Treatment Program N=12,781 

Subspecialty Pulmonary Evaluation N=1,720

Inclusion Criteria:

i. Never smoking male FDNY rescue workers

ii. No pre-9/11 lung disease (FEV % predicted≥75)

iii. No prior sinus disease

iv. High or intermediate WTC exposure (arrival time 

before 9/13)

v. Accurate NHANES normative Data

vi. Serum from Medical Monitoring Entry with 

biomarkers assayed

Sinusitis Cases

N=76

Surgical 

Sinusitis

N=14

No Sinusitis

N=103

Medical 

Sinusitis

N=62

Study Cohort N=179

Figure 1 Study design. WTC Z World Trade Center;

FDNY Z Fire Department City of New York; FEV1 Z forced

expiratory volume in 1 s; NHANES Z National Health and

Nutrition Examination Survey.

164 S.J. Cho et al.
Sinusitis incidence and overlap with abnormal FEV1

KaplaneMeier estimator was used to assess the cumulative

proportion of CRS. The incidence of CRS steadily increased

over study period, Fig. 2 Panel A. We examined the proportion of the study cohort with sinusitis alone, abnormal

FEV1 alone or sinusitis with abnormal FEV1. Fourteen

percent (25/179) had both diagnoses, 28% (51/179) had only

sinusitis and 20% (35/179) had only abnormal FEV1, Fig. 2

panel B.

Characteristics of chronic rhinosinusitis

The median time from 9/11 to CRS diagnosis was between

39 and 40 months in medical and surgical cases. The subspecialty pulmonary evaluation (SPE) spirometry occurred 7

months before the diagnosis of CRS in the medically

managed cases and 4 months after the diagnosis of CRS in

surgical cases, Table 2. Eighty three percent of CRS cases

(63/76) had CT scans available for analysis including 50

medical and 13 surgical CRS cases. The median time from

9/11 to sinus CT scan was 77 months in both medical and

surgical cases, respectively (P Z 0.322). Polypoid pathology

on CT scan was more prevalent in surgical than medical

cases; 46% (6/13) of surgically and 10% (5/50) of medically

managed CRS patients had polypoid sinusitis (P Z 0.007).

Univariable ordinal logistic regression

Assuming an ordered progression of severity from no

sinusitis to medically managed sinusitis to sinusitis requiring

surgery, we modeled biomarker ability to predict sinus

disease status. We included a panel of 39 cytokines,

neutrophil concentration and potential confounders such as

age, BMI and exposure intensity in the initial analysis.

Interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis

factor-alpha (TNF-a), growth-regulated oncogene (GRO),

neutrophil counts and BMI had a P-value less than 0.2 and

were therefore included in the multivariable ordinal logistic model, Table 3.

Multivariable ordinal regression model

After adjustment for exposure intensity, IL-6, TNF-a and

neutrophil concentration made it into the final model,

Table 4. Increasing IL-6 and neutrophil counts increased the

Table 1 Demographics.

Control Medical cases Surgical cases P-valuee

Number of subjects 103 62 14

Age at 9/11a 41 (36e45) 41 (36e44) 42 (38e46) 0.880

Years of service at 9/11a 15 (8e18) 13 (6e17) 12 (9e16) 0.135

Raceb Caucasian 99 (96) 62 (98) 14 (100) 0.550

African American 4 (4) 1 (2) 0 (0)

Intensity of WTC Exposureb Highc 20 (19) 13 (21) 4 (29) 0.775

Intermediated 83 (81) 50 (79) 10 (71)

Time toa Serum Collection, months 2.6 (2.2e3.7) 2.6 (2.0e3.2) 2.3 (1.8e2.9) 0.118

Spirometry, months 35.7 (23e55) 31.7 (24e55) 43.8 (30e55) 0.550

Spirometrya FEV1, % Predicted 87 (74e99) 85 (73e95) 101 (88e107) 0.608

FEV1/FVC, % 76 (70e80) 76 (70e82) 77 (75e81) 0.263

Definition of abbreviations: WTC Z World Trade Center, FEV1 Z forced expiratory volume in 1 s; FVC Z forced vital capacity. a Values expressed as median (IQR). b Values expressed as N (%). c Arrival at WTC 9/11 morning. d Arrival at WTC between noon of 9/11 and midnight of 9/12. e Significance assessed by JonckheereeTerpstra test or Chi-squared test between medical cases, surgical cases and controls.

Abnormal 

FEV1

Sinusitis

51

(28%)

25

(14%) 35

(20%)

68 (38%)

A.

B.

Cumulative Proportion of CRS (%)

Time (months)

100

80

60

40

20

0

0 20 120 40 60 80 100

Figure 2 A. KaplaneMeier estimator was used to assess the

cumulative proportion of CRS. The incidence of CRS steadily

increased over study period. B. We examined the proportion of

the study cohort with sinusitis alone, abnormal FEV1 alone or

sinusitis with abnormal FEV1. Fourteen percent (25/179) had

both diagnoses, 28% (51/179) had only sinusitis and 20% (35/

179) had only abnormal FEV1.

One airway, biomarkers of both upper and lower airway 165
odds of being in the control, non-sinusitis group. With every

1 log10pg/mL increase in IL-6, the probability of being in the

control group increased by 10.6% while the probabilities of

being in the medical and surgical sinusitis groups decreased

by 7.8% and 2.8%, respectively. Similarly, with every

1000 cells/mL increase in neutrophil count, the probability

of being in the control group increased by 8.8% while the

probabilities of being in the medical and surgical sinusitis

groups decreased by 6.5% and 2.3%, respectively.

Conversely, elevated TNF-a levels increased the odds of

having surgically managed sinusitis. Every 1 log10pg/mL

increase in TNF-a level resulted in a 20.4% lower probability

of being in the control group, 15.1% higher probability of

being in the medical sinusitis group and 5.3% higher probability of being in the surgical group.

Biomarkers of chronic rhinosinusitis with polyps

Since surgical patients had a 7.7 fold (95% CI: 1.8e32)

increased odds of sinus polyps we investigated biomarkers

of polyps in this cohort. We observed that increasing serum

eotaxin, interferon-gamma (IFN-g), interleukin-4 (IL-4),

interleukin-13 (IL-13), vascular endothelial growth factor

(VEGF), and neutrophil concentration reduced the risk of

having CRS with polyps. Conversely, increasing eosinophil

concentration increased the risk of CRS with polyps, Table

5. In a multivariable model adjusted for exposure intensity, each 1 log10pg/mL increase in IFN-g and IL-4

decreased the odds of having sinus polyps by 96% (95% CI:

0.00e0.99) and 80% (95% CI: 0.06e0.75) respectively. Each

1000 cells/mL increase of neutrophil count was associated

with 96% (95% CI: 0.01e0.48) decrease the odds of sinus

polyps while each 10 cells/mL increase of eosinophil count

increased the risk of developing polyps by 15% (95%CI:

1.03e1.27), Table 6.

Biomarkers of sinus disease as predictors of

FEV1 < LLN

We have previously reported biomarkers of inflammation

that predict FEV1 below the lower limit of normal (LLN) in

WTC exposed firefighters, and previously reported that

macrophage derived chemokine (MDC) and granulocyte

macrophage colony stimulating factor (GM-CSF) increased

the risk of abnormal FEV1 years later. We therefore investigated if inflammatory biomarkers of sinus disease predicted abnormal FEV1 in this cohort. We observed that each

1 log10pg/mL increase in IL-6 decreased the odds of

abnormal FEV1 by 65% (95% CI: 0.19e0.62) and that each

1000 cells/mL increase of neutrophil count was associated

with 40% decrease in the risk of abnormal FEV1 (95% CI:

0.43e0.83) in a model adjusted for exposure, BMI, age, MDC

and GM-CSF. TNF-a levels didn’t have statistically significant association with lung function in this cohort.

Discussion

Years after 9/11, a high incidence of both upper and lower

airway respiratory disorders has persisted in WTC exposed

firefighters [8], with CRS representing both the most common manifestation of upper airway injury in this cohort and

a condition of substantial morbidity [11]. The FDNY has

reported that 80% of previously healthy firefighters complained of rhinosinusitis symptoms the first day after 9/11/

2001, 25% during the first year after exposure, and 32%

during the next 2e4 years [21]. In our study cohort who

presented to the subspecialty pulmonary evaluation, 42% of

WTC exposed firefighters were diagnosed with CRS, 4 times

higher than physician diagnosed sinusitis in the total cohort

(N Z 10,943) [22].

Table 2 Characteristics of chronic sinusitis in FDNY

cohort.

Medical cases Surgical cases P-valuec

Time to SPE,

monthsa

31.7 (24e55) 43.8 (30e55) 0.319

Time to sinusitis

diagnosis,

monthsa

39 (13e65) 40 (23e79) 0.634

Time to sinus

CT scan,

monthsa,d

77 (52e98) 77 (57e104) 0.616

Polypsb,d 5 (10) 6 (46) 0.007

Definition of abbreviations: SPE Z subspecialty pulmonary

evaluation; CT Z computed tomography. a Values expressed as median (IQR). b Values expressed as N (%). c Significance assessed by Wilcoxon rank-sum test and Fishers

exact test between medical cases and surgical cases.

d CT scans available: medical cases N Z 50; surgical cases

N Z 13.

Table 3 Predictive biomarkers and univariable ordinal logistic regression predicting sinus disease severity.

Predictor Controlsa Medical casesa Surgical casesa Crude OR (95%CI)b P-value

IL-6 (log10pg/mL) 5.7 (1.7e17.7) 2.6 (0.7e12.2) 4.8 (3.1e13.6) 0.72 (0.48e1.09) 0.118

IL-8 (log10pg/mL) 16.4 (11.7e35.0) 12.6 (9.4e22.7) 11.8 (9.0e21.8) 0.41 (0.19e0.90) 0.023

TNF-a (log10pg/mL) 4.0 (2.6e5.5) 4.3 (2.8e5.8) 5.0 (2.3e8.7) 1.93 (1.00e3.80) 0.044

GRO (log10pg/mL) 732 (487e973) 641 (474e871) 620 (506e952) 0.41 (0.11e1.50) 0.174

BMI, kg/m2 27.9 (26e31) 29.1 (26e31) 29.8 (28e32) 1.05 (1.03e1.14) 0.163

PMN count, 103 3.8 (3.0e4.5) 3.6 (2.8e4.2) 3.3 (2.6e3.9) 0.73 (0.57e0.94) 0.011

Definition of abbreviations: OR Z odds ratio; PMN Z polymorphonuclear neutrophils; 95%CI Z 95% confidence interval. a Values expressed as median (IQR). b Analysis was done between medical cases, surgical cases and controls.

166 S.J. Cho et al.
Whereas we have previously reported biomarkers of

inflammation predicting abnormal FEV1 in WTC exposed

firefighters, this is the first study to report a panel of inflammatory biomarkers that predict both future CRS disease and its progression or severity in this population.

Specifically, IL-6 and neutrophil concentration were found

to be protective against CRS, whereas TNF-a was a risk

factor for CRS progression or severity. Interestingly, in this

same group of patients using identical blood samples,

increased IL-6 levels and neutrophil counts were likewise

protective against an abnormal FEV1. In contrast, TNF-a

was not a risk factor for an abnormal FEV1 post-9/11 [17].

That we found both independent (TNF-a) and overlapping (IL-6, neutrophil counts) biomarker association with

irritant-induced upper and lower airway injury suggests

shared but distinct immune pathways. Indeed, there appears to be considerable clinical overlap between CRS and

lower airway injury as WTC-LI was a common comorbidity

of CRS in this cohort. Twenty-five out of 79 (32%) previously

healthy firefighters who developed CRS also developed

obstructive airway dysfunction post-9/11. This finding is

consistent with a prior report that 40% of WTC rescue

workers were diagnosed with both CRS and obstructive

airway disease post-9/11 [23].

The one-airway or unified airway concept linking the

upper and lower airways is already a well recognized and

accepted in asthma and allergic rhinitis [12,13] and in

chronic cough syndrome [15]. Numerous cross-sectional and

retrospective studies have demonstrated that allergic

rhinitis is a risk factor for the presence of asthma [24].

Potential mechanisms linking these upper and lower airway

disease states are the nasobronchial neural reflex (airway

hyperreactivity), drainage of pro-inflammatory material

from the nose to the lungs (common allergen), loss of

protective function of the nose, and inflammatory processes characterized by eosinophilia and local IgE production [14,25,26].

Several studies by Braunstahl [27,28] have shown that

stimulation with antigen at one respiratory site can result in

expression of inflammatory cytokines at a location distant

from the site of stimulation. The activation of Th2 lymphocytes in the nose can lead to the differentiation and

activation of immune cells from precursors in the nasal

mucosa and bone marrow, leading to recruitment of these

newly generated cells throughout the upper and lower

airways [14]. These findings suggest that there is “inflammatory crosstalk” occurring throughout a “unified” upper

and lower airway. However the pathophysiology of CRS and

WTC-LI after occupational irritant exposure has not been

previously described.

The biomarkers associated with CRS and/or WTC-LI

identified in this study are known to be important mediators of the innate immune system. This is consistent with

studies suggesting that the innate immune response plays

an important role in the pathogenesis of CRS as well as

Table 4 Multivariable ordinal logistic regression: final

model predicting sinus disease severity using stepwise

approach.

Predictor OR (95%CI)a P-value

IL-6 (log10pg/mL) 0.65 (0.42e1.00) 0.049

TNF-a (log10pg/mL) 2.31 (1.15e4.65) 0.018

PMN count, 103 0.69 (0.53e0.91) 0.008

Definition of abbreviations: OR Z odds ratio; IL6 Z interleukin-6; TNF-a Z tumor necrosis factor-alpha;

PMN Z polymorphonuclear neutrophils; 95%CI Z 95% confidence interval.

a Adjusted for exposure intensity. Omnibus test

c2(4) Z 15.30, P Z 0.004. Approximate likelihood-ratio test of

proportionality of odds P Z 0.424. Brant test of parallel lines

P Z 0.347.

Table 5 Predictive biomarkers and univariable logistic regression predicting CRS with polyps.

Predictor CRS without polypsa

N Z 52

CRS with polypsa

N Z 11

Crude OR (95%CI) P-value

Eotaxin (log10pg/mL) 125 (93e172) 79 (65e432) 0.04 (0.00e1.49) 0.082

IFN-g (log10pg/mL) 8.1 (4.8e20.1) 7.6 (3.3e9.3) 0.15 (0.02e1.32) 0.087

IL-4 (log10pg/mL) 3.2 (0.5e9.1) 0.5 (0.1e2.2) 0.52 (0.26e1.03) 0.062

IL-13 (log10pg/mL) 3.0 (0.5e18.7) 1.4 (0.5e6.9) 0.51 (0.21e1.27) 0.148

VEGF (log10pg/mL) 144 (88e247) 64 (48e94) 0.08 (0.01e0.70) 0.022

PMN count, 103 3.6 (2.9e4.2) 2.9 (2.5e3.4) 0.41 (0.18e0.94) 0.036

Eosinophil count, 10 16 (11e23) 25 (18e43) 1.04 (1e1.09) 0.058

Definition of abbreviations: OR Z odds ratio; IFN-g Z interferon-gamma; IL-4 Z interleukin-4; IL-13 Z interleukin-13; VEGF Z vascular

endothelial growth factor; PMN Z polymorphonuclear neutrophils; 95%CI Z 95% confidence interval. a Values expressed as median (IQR).

Table 6 Multivariable logistic regression: final model

predicting CRS with polyps.

Predictor OR (95%CI)a P-value

IFN-g (log10pg/mL) 0.04 (0.00e0.99) 0.050

IL-4 (log10pg/mL) 0.20 (0.06e0.75) 0.016

PMN count, 103 0.06 (0.01e0.48) 0.008

Eosinophil count, 10 1.15 (1.03e1.27) 0.009

Definition of abbreviations: OR Z odds ratio; IL4 Z interleukin-4; IFN-g Z interferon-gamma;

PMN Z polymorphonuclear neutrophils; 95%CI Z 95% confidence interval.

a Adjusted for exposure intensity. Omnibus test

c2(5) Z 26.87, P < 0.001. Approximate likelihood-ratio test of

proportionality of odds P Z 0.737.

One airway, biomarkers of both upper and lower airway 167
obstructive airway disease [29e31]. Interestingly, we found

neutrophil concentration to be protective of both CRS and

abnormal FEV1. A recent genome-wide association study

(GWAS) demonstrated an association between polymorphisms of the neutrophil’s acyloxyacyl hydrolase

(AOAH) gene with CRS in two independent populations

[32,33]. The AOAH gene, which is known to contribute to

the host defense against bacterial LPS, has also been linked

to asthma [34,35]. It may appear counter-intuitive that

neutrophils, which are conventionally agents of inflammation, were a protective biomarker for CRS and WTC-LI in our

study. However, recent investigations have indeed supported the concept that anti-inflammatory cascades can be

mediated by neutrophils early in the innate immune

response [36,37].

In our investigation, IL-6 was identified as a protective

biomarker for both sinusitis and abnormal FEV1 as well.

Although many IL-6 related gene variants have previously

been associated with conditions such as asthma and COPD

[38,39], studies demonstrating association between IL-6

polymorphisms and susceptibility to CRS have been rare.

Interestingly, causeeeffect studies using transgenic mice

have pointed to a dual role for IL-6 in lower airway diseases; 1) enhancing allergic airway inflammation and 2)

protecting against airway hyperreactivity/inflammation

[40e42].

TNF-a is a cytokine that is thought to play a central role

in pathogenesis in CRS [43,44]. In severe CRS, TNF-a synergizes with Th1 and Th2 to induce a chronic inflammatory

state [45,46]. Multiple studies showed that single nucleotide polymorphisms (SNPs) in TNF-a have been associated

with nasal polyps [47e49]. In our cohort, elevated TNF-a

levels were a risk factor for severe sinusitis (typically

polypoid on CT) but not WTC-LI. Further investigation is

required to assess if TNF-a directly contributes to the inflammatory cascade in WTC-related CRS.

The traditional classification of allergic CRS into CRS

with polyps versus without polyps is useful in the general

population in whom the presence of polyps is strongly

associated with sensitivity to aspirin or nonsteroidal antiinflammatory drugs. Our cohort is unique in that development of CRS was provoked by massive exposure to combustion byproducts, with pathophysiology that could

potentially be different from classical allergic CRS. There is

a suggestion that the cytokines that reduced the risk of

developing polyps are different from the cytokines that

reduced the risk of CRS progression even though increasing

blood PMN were protective biomarkers for both conditions.

Alternately, increasing eosinophil concentration was a

strong risk factor for polyps but not CRS progression. This

suggests overlapping but distinct pathways to CRS progression and sinus polyps.

This study has several limitations. This is an exploratory study using a panel of inflammatory cytokines in

this longitudinally followed cohort. The findings of this

investigation need to be validated in lager studies and

animal models. Our FDNY firefighters cohort is unique as

they had massive acute exposure to WTC dusts. This

limits the generalizability of these finding to other study

populations with lower level PM exposure produced by

ambient air pollution. However this is at the same time a

strength of our paper since we can make a safe

assumption that the etiology of sinusitis was WTC dust.

We did not have an unexposed control group to compare

and therefore we could not determine the direct effect

of WTC-PM exposure on serum biomarkers. In addition,

there is no good surrogate measure to estimate exposure

prior to 9/11 since all individual firefighters would have

had different rate of exposure even in each fire runs.

Replication of these findings in other longitudinally followed populations with and without PM exposure will be

important to demonstrate the generalizability of our

findings.

Our study demonstrates distinct but overlapping

biomarker association between upper and lower airway

injury, and suggests that a common inflammatory pathway

may be shared by CRS and lung disease caused by WTC

exposure. The potential relationship between irritantinduced CRS and lung injury may underlie preventive and

therapeutic strategies for these conditions by modulating

inflammation.

Funding

K23HL084191 (AN), K24A1080298 (MDW), RO1HL057879;

(MDW), HL090316, Al080298A, TL1RR029892; T32 ES007267

(BN, SJC); U01CA008617, RO1HL090316 (WNR), NIOSH/CDC

(U10- OH008243, U10-OH008242), and 1 UL1RR029893. This

work was also partially funded by the NYU-HHC Clinical and

Translational Science Institute, supported in part by grant

UL1TR000038 from the National Center for Advancing

Translational Sciences of the National Institutes of Health.

The funding agencies did not participate in the study

design; in the collection, analysis and interpretation of

data; in the writing of the report; and in the decision to

submit the article for publication.

Conflict of interest statement

The authors (SJC, GCE, SK, BN, ES, JT, WNR, DJP, AN, and

MDW) of this manuscript have no actual or potential conflicts of interest to disclose.

Acknowledgment

Author contributions: Drs Cho and Weiden had full access

to all of the data in the study and take responsibility for the

integrity of the data and the accuracy of the data analysis.

Dr. Cho: contributed to study design; data collection and

analysis; manuscript writing and preparation; and reviewing, editing, and approving the manuscript.

Dr. Echevarria: contributed to data analysis, reviewing,

editing, and approving the manuscript.

Ms. Kwon: contributed to data collection and reviewing,

editing, and approving the manuscript.

Dr. Naveed: contributed to data collection and reviewing, editing, and approving the manuscript.

Dr. Schenck: contributed to data collection and

reviewing, editing, and approving the manuscript.

Dr. Tsukiji: contributed to data collection and reviewing,

editing, and approving the manuscript.

168 S.J. Cho et al.
Dr Rom: contributed to manuscript writing and preparation; and reviewing, editing, and approving the

manuscript.

Dr Prezant: contributed to participant recruitment;

manuscript writing and preparation; and reviewing, editing, and approving the manuscript.

Dr Weiden: contributed to study design; participant

recruitment; data analysis; manuscript writing and preparation; and reviewing, editing, and approving the

manuscript.

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