Characterization of occupational endotoxin-related small airway disease with longitudinal paired inspiratory/expiratory CT scans

Yuming Sun; Jian Kang; Feng-ying Zhang; Hantao Wang; Peggy S Lai; George R Washko; Raul San Jose Estepar; David C Christiani; Yi Li

doi:10.1016/j.chest.2024.12.037

. Author manuscript; available in PMC: 2025 Jul 11.

Published in final edited form as: Chest. 2025 Jan 18;168(1):43–55. doi: 10.1016/j.chest.2024.12.037

Characterization of occupational endotoxin-related small airway disease with longitudinal paired inspiratory/expiratory CT scans

Yuming Sun ¹, Jian Kang ², Feng-ying Zhang ³, Hantao Wang ⁴, Peggy S Lai ⁵, George R Washko ⁶, Raul San Jose Estepar ⁷, David C Christiani ⁸, Yi Li ⁹

PMCID: PMC12245607 NIHMSID: NIHMS2044889 PMID: 39832623

Abstract

BACKGROUND:

Although small airway disease has been recognized as a major contributor to obstructive respiratory diseases, the association between occupational endotoxin exposure and small airway disease, as characterized by CT scans, requires further investigation.

RESEARCH QUESTION:

What is the association between occupational endotoxin exposure and small airway disease, and which CT imaging biomarkers effectively detect pre-clinical airway dysfunction?

STUDY DESIGN AND METHODS:

This study includes 404 subjects from the Shanghai Textile Worker Cohort. We collected longitudinal inspiratory/expiratory CT scans, spirometry data, and endotoxin levels in 2011 and 2016. We evaluated the marginal association among endotoxin, small airway measures, and spirometry by Pearson correlation coefficient. We applied linear mixed models and linear regression models to understand the adjusted association among endotoxin, small airway measures, and spirometry.

RESULTS:

We found significant association between endotoxin and small airway disease and airflow obstruction, as quantified by small airway measures and spirometry, respectively. All small airway measures were marginally correlated with endotoxin, among which RVC_{−856 to −950} and Residual₋₈₅₆ showed the strongest positive correlations. pp FEV₁ showed the strongest negative correlation with endotoxin. Adjusting for the confounders, E/I MLA, RVC_{−856 to −950}, Residual₋₈₅₆, FEV₁, and pp FEV₁ reported significant association with endotoxin. Workers who were exposed to 1,500 - 2,300 EU/m³ endotoxin showed a significantly higher RVC_{−856 to −950} by 0.071 (p = 0.006) and a 8.57% lower pp FEV₁ (p = 0.007) compared to workers exposed to less than 50 EU/m³ endotoxin.

INTERPRETATION:

We found that occupational endotoxin exposure was significantly associated with small airway disease and lower FEV₁. We identified Residual₋₈₅₆ and E/I MLA as the imaging biomarkers for early detection of small airway dysfunction in pre-clinical individuals (FEV₁/FVC ≥ 0.70). These findings have important implications for identifying early-stage SAD and airflow obstruction with CT imaging biomarkers.

Keywords: imaging biomarkers, occupational endotoxin exposure, paired CT scans, small airway disease

The textile and clothing industry is the most labor-intensive manufacturing sector in the world, employing more than 60 million people worldwide. ¹ The study on the global burden of chronic respiratory disease reported 519,000 deaths in 2016 due to occupational airborne exposures. ² Occupational exposure to textile dust is associated with increased risks of byssinosis, Chronic Obstructive Pulmonary Disease (COPD), and other respiratory diseases. ³ Endotoxin is generated from Gram-negative bacterial membranes in textile dust. ⁴ It is the major contributor to occupational respiratory diseases. ⁵ Furthermore, many studies have reported stronger correlations between chronic lung function loss and endotoxin exposure than dust exposure. ^6-8 However, whether occupational exposure to endotoxin can cause small airway disease (SAD) remains controversial. ^9,10

Small airways, usually defined as those with an internal diameter of ≤ 2mm, ¹¹ are the predominant sites of airflow resistance in obstructive pulmonary diseases, such as asthma ^12,13 and COPD. ^12,14 The airflow obstruction in small airways often occurs at an early stage of obstructive pulmonary diseases, making SAD an early indicator of lung damage. ^15,16 While spirometry has been the gold standard for diagnosing and assessing airflow obstruction in lung diseases, it is more sensitive to large airway dysfunction and therefore is not an effective biomarker for small airway disease (SAD) (Figure 1). ^17,18 Furthermore, the pathological changes in small airways can occur before the spirometric impairment of pulmonary functions, making the detection of SAD by spirometry even more challenging.^19,20

Figure 1. — Inspiratory (A, C) and expiratory (B, D) CT scans from two subjects of different occupations at GLOD stage 1 with similar spirometry but different small airway measures. Subject 1 (silk worker): 8-hour TWA endotoxin = 0 EU/m³ spirometry: pp FEV₁ = 0.808; small airway measures, Exp₋₈₅₆ = 0.057, E/I MLA = 0.759, RVC_{−856 to −950} = −0.477, Residual₋₈₅₆ = −0.164. Subject 2 (cotton worker): 8-hour TWA endotoxin = 4,890 EU/m³; spirometry: pp FEV₁ = 0.803; small airway measures, Exp₋₈₅₆ = 0.422, E/I MLA = 1.001, RVC_{−856 to −950} = 0.006, Residual₋₈₅₆ = 0.266. Abbreviations: pp FEV₁, percent predicted FEV₁; FVC, Forced Vital Capacity; Exp₋₈₅₆, percent gas trapping; E/I MLA, expiratory to inspiratory ratio of mean lung attenuation; RVC_{−856 to −950}, relative volume change of voxels with attenuation between −856 HU and −950 HU.

To overcome these challenges, researchers have used high-resolution computed tomography (CT) at inspiration and expiration to detect and evaluate damage to small airways. ^21-23 Specifically, researchers have assessed SAD using CT images by measuring the density of air trapping and quantifying voxels with attenuation less than −856 Hounsfield Units (HU) in expiratory CT scans. ^24,25 More recently, researchers have developed other quantitative measures based on paired inspiratory/expiratory CT scans, including the ratio of expiratory to inspiratory mean lung attenuation, ^26,27 relative volume change between inspiratory and expiratory CT scans, ²⁴ and other quantitative measures adjusting for the air trapping due to large airway damage. ²⁸ However, there is no consensus about the best quantitative measures of SAD, and further investigation is still required.²⁹

The Shanghai Textile Worker Study is a longitudinal cohort study for respiratory disease among textile workers established in 1981. ³⁰ The unique strength of this study lies in the measurement of endotoxin exposure throughout the subjects’ working lifetime and the longitudinal collection of paired inspiratory/expiratory CT scans for the cohort. In this study, our primary goal is to investigate the association between endotoxin exposure and SAD, characterized by quantitative small airway measures from CT scans and spirometry. Additionally, we aim to identify CT imaging biomarkers of small airway dysfunction for pre-clinical individuals who exhibit no airway obstruction (FEV₁/FVC ≥ 0.70). ^31,32

Study Design and Methods

Study population

Shanghai textile workers cohort, starting from 1981, includes cotton textile workers exposed to high levels of endotoxin and demographically similar, unexposed silk textile workers. In this study, we focused on the surveys conducted in 2011 and 2016 when the paired inspiratory/expiratory CT scans were collected. The initial population included 480 textile workers, of whom 76 were excluded due to the lack of paired CT scans. Thus, 404 textile workers were analyzed in this study, comprising 178 cotton workers and 226 silk workers (Figure 2). We calculated the Minimum Detectable Difference (MDD)³³ for the spirometry and quantitative small airway measures based on the current sample size, using a significance level of 0.05 and a power level of 80%. (e-Table 5).

Figure 2. — Flow diagram for the inclusion of textile workers in the analysis.

We collected data on demographics, work history, smoking status, and respiratory symptoms, including chronic bronchitis, chronic cough, and dyspnea. We performed prebronchodilator spirometry to collect Forced Expiratory Volume in the first second (FEV₁), percent predicted FEV₁ (pp FEV₁) and Forced Vital Capacity (FVC). FEV₁/FVC < 0.70 were used as the indicator of airway obstruction.^34,35 For workers with airway obstruction, we defined the Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 1 - 4 for airway obstruction by pp FEV₁. ³⁶ Among workers without airway obstruction, preserved ratio impaired spirometry (PRISm) was defined by pp FEV₁ < 80%. ³⁷

Exposure Assessment

Details of the exposure assessment were previously described. ³⁸ Briefly, the exposure of interest was the 8-hour time-weighted average (TWA) area endotoxin concentration. We collected the dust samples in six work areas of two cotton textile mills with a vertical elutriator (General Metalworks Corp., Mequon, Wisconsin, USA) following the NIOSH guidelines. We measured the endotoxin exposure from collected cotton dust sample filters using the Limulus amoebocyte lysate assay, chromogenic method (Kinetic-QCL; BioWhittaker, Walkersville, Maryland USA). ³⁹ The lower detection limit for endotoxin is 0.001 endotoxin unit (EU/m³). The samples collected from the silk mill provided non-detectable levels of endotoxin exposure (below 0.001 EU/m³), so silk workers were considered unexposed to endotoxin.

Paired Chest CT scans

Chest CT scans were obtained at full inspiration and expiration on subjects who consented to volumetric chest CT scans using a single Siemens Emotion-16 CT scanner. Images were reconstructed using a B65s kernel with slice thickness and intervals of 1 mm. The other parameters of CT scanner include: X-ray voltage, 130 kVp; tube current, 100 mAs for inspiratory CT scans and 50 mAs for expiratory CT scans; table speed, 13.2 mm/rotation; rotation time, 0.6 s; and pitch value, 1.1. The scanner and scanning protocol were the same in 2011 and 2016.

Quantitative Small Airway Measures

We used 3D Slicer to perform lung segmentation before extracting the quantitative small airway measures from paired CT scans. ⁴⁰ We used pyradiomics to extract the quantitative small airway measures, ⁴¹ including Expiratory₋₈₅₆ (Exp₋₈₅₆), Expiratory to Inspiratory Ratio of Mean Lung Attenuation (E/I MLA), Relative Volume Change_{−856 to −950} (RVC_{−856 to −950}) and Residual₋₈₅₆. Exp₋₈₅₆ is the percent of gas trapping, measured by the percentage of voxels with attenuation less than −856 HU on expiratory CT scans. ²⁶ E/I MLA is the ratio of mean voxel attenuation between expiratory and inspiratory CT scans. ^42,43 RVC_{−856 to −950} measures the difference in relative lung volume between the expiratory and inspiratory CT scans, where the relative lung volume is the volume of voxels with attenuation between −856 HU and −950 HU divided by that with attenuation greater than −950 HU. ²⁴ Residual₋₈₅₆ is the residuals from the linear regression of Expiratory₋₈₅₆ on Inspiratory-950, which is the percent of voxels with attenuation less than −950 HU. ²⁸

To evaluate the reproducibility of lung segmentation and feature extraction, we conducted internal validation for 30 subjects who were randomly selected from the 2011 and 2016 follow-ups, respectively. We performed the lung segmentation and feature extraction twice for the same CT scans of the selected subjects with a two-month interval. We used Intraclass correlation coefficient (ICC) to evaluate the agreement between the small airway measures collected in the two sessions.

Statistical Analysis

In the descriptive analysis, we used mean ± standard deviation (SD) to describe continuous variables and frequency (percentages, %) to display categorical variables. Missing data in spirometry were addressed by imputing values from the closest survey year available, thereby maintaining data continuity and minimizing the impact of missing data on the analysis. We evaluated the unadjusted correlation between 8-hour TWA endotoxin and small airway measures/spirometry in 2011 and 2016 using Pearson correlation coefficients. In the multivariate analysis, we classified 8-hour TWA endotoxin into quintiles. We replaced the reference group of the first quintile by 0 - 50 EU/m³. We used the linear mixed model with a random intercept to evaluate the effect of endotoxin exposure on small airway measures and spirometry, adjusting for age, gender, height, smoking intensity, survey time, and the interaction between 8-hour TWA endotoxin and survey year (8-hour TWA endotoxin × survey year). We also performed all the multivariate analysis restricted to cotton workers. We conducted similar analysis to investigate the relationships between small airway measures and spirometry. The statistical analysis was conducted using R version 4.3.2.

Results

There were a total of 404 subjects in the study population, including 178 cotton workers and 226 silk workers. Table 1 presents the baseline characteristics of the study population. The population consisted of more female workers (66%) than male workers. Fifty-five (13.6%) workers had airway obstruction (FEV₁/FVC < 0.70), among which 42 (76.4%) workers were in GOLD stage 1, 11 (20%) workers were in GOLD stage 2, 1 (1.8%) worker was in GOLD stage 3, and 1 (1.8%) worker was in GOLD stage 4. For the workers without airway obstruction, there were 10 (2.5%) individuals reported PRISm. BMI of silk workers (23.7 ± 3.1) was significantly lower than that of cotton workers (24.7 ± 3.6; p = 0.008). There was no significant difference between cotton workers and silk workers in terms of other demographic characteristics. Silk workers reported longer work history (26 years) than cotton workers (24 years). The 8-hour TWA endotoxin for cotton workers was 2,302 ± 1,678 EU/m³. Silk workers were unexposed to endotoxin. Specifically, all 226 silk workers and 11 cotton workers were exposed to endotoxin levels ≤ 50 EU/m³. Among the cotton workers, 61 were exposed to levels between 50 and 1,500 EU/m³, 35 to levels between 1,500 and 2,300 EU/m³, 37 to levels between 2,300 and 3,900 EU/m³, and 34 to levels exceeding 3,900 EU/m³. Silk workers reported slightly better lung function than cotton workers did. The mean FEV₁ was 2,321 ml for silk workers, which was higher than the FEV₁ of 2,305 ml for cotton workers. The pp FEV₁ for silk workers (109% ± 18%) was higher than that for cotton workers (105% ± 18%). The FEV₁ to FVC ratio of cotton worker was similar to that of silk worker with mean around 0.77. In the current sample, we did not find significant differences between cotton workers and silk workers regarding other spirometry, quantitative small airway measures, or symptom burden, including chronic bronchitis, chronic cough, and dyspnea, which aligns with the small MDDs reported in e-Table 5.

Table 1.

Baseline characteristics of study population

Characteristic	All^a N = 404	Cotton Worker^a N = 178	Silk Worker^a N = 226	p-value^b
8-hour TWA Endotoxin (EU/m³)^c				<0.001
≤ 50	237 (58.7%)	11 (6.2%)	226 (100%)
50 - 1,500	61 (15.1%)	61 (34.3%)	0 (0%)
1,500 - 2,300	35 (8.7%)	35 (19.7%)	0 (0%)
2,300 - 3,900	37 (9.2%)	37 (20.8%)	0 (0%)
> 3900	34 (8.4%)	34 (19.1%)	0 (0%)
Age (years)	64 ± 9	63 ± 9	64 ± 9	0.6
Gender				0.8
Female	267 (66.1%)	119 (66.9%)	148 (65.5%)
Male	137 (33.9%)	59 (33.1%)	78 (34.5%)
BMI	24.2 ± 3.4	24.7 ± 3.6	23.7 ± 3.1	0.008
Smoking status				0.7
Current	83 (20.5%)	40 (22.5%)	43 (19.0%)
Former	30 (7.4%)	12 (6.7%)	18 (8.0%)
Never	291 (72.0%)	126 (70.8%)	165 (73.0%)
Work history (years)	25 ± 8	24 ± 7	26 ± 9	0.086
Chronic bronchitis	35 (8.7%)	18 (10.1%)	17 (7.5%)	0.4
Chronic cough	11 (2.7%)	4 (2.2%)	7 (3.1%)	0.8
Dyspnea	94 (23.3%)	40 (22.5%)	54 (23.9%)	0.7
PRISm	10 (2.5%)	5 (2.8%)	5 (2.8%)	0.8
Airway obstruction	55 (13.6%)	23 (12.9%)	32 (14.2%)	0.7
GOLD stage^d				0.8
1	42 (76.4%)	17 (73.9%)	25 (78.1%)
2	11 (20.0%)	5 (21.7%)	6 (18.8%)
3	1 (1.8%)	0 (0%)	1 (3.1%)
4	1 (1.8%)	1 (4.3%)	0 (0%)
Spirometry
FEV₁ (ml)	2,314 ± 601	2,305 ± 639	2,321 ± 570	0.4
≤ 2756.88	323 (80.0%)	141 (79.2%)	182 (80.5%)	0.7
pp FEV₁, (%)	107 ± 18	105 ± 18	109 ± 18	0.066
≤ 1.22	323 (80.0%)	147 (82.6%)	176 (77.9%)	0.2
FEV₁/FVC	0.77 ± 0.07	0.77 ± 0.07	0.77 ± 0.08	0.5
Small airway measures
Exp₋₈₅₆	0.22 ± 0.13	0.21 ± 0.12	0.23 ± 0.14	0.5
≤ 0.31	323 (80.0%)	148 (83.1%)	178 (78.8%)	0.2
E/I MLA	0.86 ± 0.07	0.86 ± 0.06	0.86 ± 0.07	0.9
≤ 0.90	323 (80.0%)	145 (81.5%)	178 (78.8%)	0.5
RVC_{−856 to −950}	−0.36 ± 0.16	−0.36 ± 0.16	−0.36 ± 0.16	0.7
≤ −0.22	323 (80.0%)	144 (80.9%)	179 (79.2%)	0.7
Residual₋₈₅₆	0.00 ± 0.12	0.00 ± 0.11	0.00 ± 0.12	>0.9
≤ 0.08	323 (80.0%)	148 (83.1%)	175 (77.4%)	0.2

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Note: n (%) and Mean ± SD were reported for categorical variables and continuous variables, respectively. Abbreviations: TWA, Time-weighted Average; GOLD, Global Initiative for Chronic Obstructive Lung Disease; FEV₁, Forced Expiratory Volume in the first 1 second; pp FEV₁, percent predicted FEV₁; FVC, Forced Vital Capacity; Exp₋₈₅₆, percent gas trapping; E/I MLA, expiratory to inspiratory ratio of mean lung attenuation; RVC_{−856 to −950}, relative volume change of voxels with attenuation between −856 HU and −950 HU; Residual₋₈₅₆, residuals from the linear regression of Exp₋₈₅₆ on the percent of voxels with attenuation less than −950 HU.

Characteristics of 404 textile workers who had inspiratory/expiratory CT scans were collected in 2011 or 2016, including 178 cotton textile workers and 226 silk textile workers.

Wilcoxon rank sum test; Pearson’s Chi-square test; Fisher’s exact test

50 EU/m³ represents the reference level. 1500 EU/m³ is the 40th percentile, 2300 EU/m³ is the 60th percentile, and 3900 EU/m³ is the 80th percentile.

The GOLD stage is reported for the subset of 55 workers with COPD (FEV₁/FVC < 0.7).

Figure 3 shows the correlation network of small airway measures, spirometry and 8-hour TWA endotoxin. There are strong positive correlations within small airway measures and spirometry. Tables 2 and 3 report the correlation between small airway measures, spirometry, and endotoxin. At the significance level of 0.05, there only existed significant negative correlations between pp FEV₁ (correlation coefficient: −0.187, p < 0.001), FEV₁/FVC (correlation coefficient: −0.145, p = 0.004) and 8-hour TWA endotoxin in 2011. We found similar correlation between pp FEV₁ (correlation coefficient: −0.184, p < 0.001), FEV₁/FVC (correlation coefficient: −0.118 p = 0.017) and 8-hour TWA endotoxin in 2016. When it comes to the small airway measures, all the measures were significantly and positively correlated with 8-hour TWA endotoxin (p < 0.05) in 2016 with the strongest correlation of 0.135 for Residual₋₈₅₆. e-Table 2 shows the correlation between the quantitative small airway measures and spirometry.

Table 2.

Unadjusted correlations between quantitative small airways measures, spirometry and 8-hour TWA endotoxin

	2011, N = 404 8-hour TWA Endotoxin	p-Value	2016, N = 404 8-hour TWA Endotoxin	p-Value
Small airway measures
Exp₋₈₅₆	0.053	0.288	0.113	0.023
E/I MLA	0.060	0.229	0.117	0.019
RVC_{−856 to −950}	0.065	0.191	0.127	0.011
Residual₋₈₅₆	0.066	0.187	0.135	0.007
Spirometry
FEV₁	0.044	0.380	0.027	0.583
pp FEV₁	−0.187	<0.001	−0.184	<0.001
FEV₁/FVC	−0.145	0.004	−0.118	0.017

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Note: Pearson correlation coefficients were reported. p < 0.05 was considered significantly different from zero. Abbreviations: TWA, Time-weighted Average; FEV₁, Forced Expiratory Volume in the first 1 second; pp FEV₁, percent predicted FEV₁; FVC, Forced Vital Capacity; Exp₋₈₅₆, percent gas trapping; E/I MLA, expiratory to inspiratory ratio of mean lung attenuation; RVC_{−856 to −950}, relative volume change of voxels with attenuation between −856 HU and −950 HU; Residual₋₈₅₆, residuals from the linear regression of Exp₋₈₅₆ on the percent of voxels with attenuation less than −950 HU.

Table 3.

Unadjusted correlations between quantitative small airways measures and spirometry

	FEV₁	p-Value	pp FEV₁	p-Value	FEV₁/FVC	p-Value
2011, N = 404
Exp₋₈₅₆	0.011	0.831	−0.112	0.024	−0.446	<0.001
E/I MLA	−0.210	<0.001	−0.232	<0.001	−0.354	<0.001
RVC_{−856 to −950}	−0.292	<0.001	−0.240	<0.001	−0.232	<0.001
Residual₋₈₅₆	−0.149	0.003	−0.189	<0.001	−0.410	<0.001
2016, N = 404
Exp₋₈₅₆	−0.072	0.149	−0.126	0.011	−0.486	<0.001
E/I MLA	−0.292	<0.001	−0.233	<0.001	−0.385	<0.001
RVC_{−856 to −950}	−0.324	<0.001	−0.220	<0.001	−0.223	<0.001
Residual₋₈₅₆	−0.216	<0.001	−0.181	<0.001	−0.413	<0.001

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Note: Pearson correlation coefficients were reported. p < 0.05 was considered significantly different from zero. Abbreviations: FEV₁, Forced Expiratory Volume in the first 1 second; pp FEV₁, percent predicted FEV₁; FVC, Forced Vital Capacity; Exp₋₈₅₆, percent gas trapping; E/I MLA, expiratory to inspiratory ratio of mean lung attenuation; RVC_{−856 to −950}, relative volume change of voxels with attenuation between −856 HU and −950 HU; Residual₋₈₅₆, residuals from the linear regression of Exp₋₈₅₆ on the percent of voxels with attenuation less than −950 HU.

Table 4 and Table 5 report the effect of endotoxin on small airway dysfunction in 2011 and 2016, as well as the difference between two years. Specifically, Table 4 reports the association between SAD measured by quantitative small airway measures and 8-hour TWA endotoxin in the entire population and restricted to cotton workers. In the entire population, we found significant association between endotoxin exposure and E/I MLA, RVC_{−856 to −950} in both 2011 and 2016 at the significance level of 0.05. Comparing subjects who were exposed to 1,500 - 2,300 EU/m³ 8-hour TWA endotoxin to those exposed to less than or equal to 50 EU/m³ 8-hour TWA endotoxin, E/I MLA was 0.022 higher (p = 0.04) in 2011 and 0.023 higher (p = 0.035) in 2016 and RVC_{−856 to −950} was 0.066 higher (p = 0.011) in 2011 and 0.071 higher (p = 0.006) in 2016. The effect of endotoxin on small airway measures is generally larger in 2016 than in 2011, but the difference was not statistically significant. Restricted to cotton workers, we found that 8-hour TWA endotoxin was significantly associated with Residual₋₈₅₆, E/I MLA and RVC_{−856 to −950}. Table 5 reports effect of endotoxin on pulmonary function. In the entire population, we found significant association between pp FEV₁ and 8-hour TWA endotoxin. pp FEV₁ was 7.022% lower (p = 0.027) for workers exposed to 1,500 – 2,300 EU/m³ and 6.717% lower (p = 0.043) for workers exposed to more than 3,900 EU/m³ compared to those exposed to less than or equal to 50 EU/m³ endotoxin in 2011. In 2016, pp FEV1 8.570% lower for workers exposed to 1,500 – 2,300 EU/m³ endotoxin and 6.634% lower for workers exposed to more than 3,900 EU/m³. We found significant difference in the effects of endotoxin on FEV₁ between 2011 and 2016. Comparing workers exposed to 50 - 1,500 EU/m³ to those exposed to less than 50 EU/m³, FEV₁ was additional 72.093 ml lower in 2016 than in 2011. In the cotton workers, there was no significant association between endotoxin and spirometry. Similar results were found using occupation as the exposure variable (e-Tables 6, 7).

Table 4.

Multivariate analysis of the association between 8-hour TWA endotoxin and quantitative small airway measures

8-hour TWA Endotoxin^a (EU/m³)	Exp₋₈₅₆	p- Value	E/I MLA	p- Value	RVC_{−856 to −950}	p- Value	Residual₋₈₅₆	p- Value
All, N = 404
Survey year 2011
≤ 50	-	-	-	-	-	-	-	-
50 - 1,500	−0.014	0.431	0.002	0.787	0.006	0.778	−0.002	0.901
1,500 - 2,300	0.009	0.691	0.022	0.040	0.066	0.011	0.028	0.159
2,300 - 3,900	−0.013	0.535	−0.010	0.333	−0.010	0.693	−0.016	0.421
> 3,900	−0.007	0.765	0.009	0.411	0.024	0.380	0.013	0.538
Survey Year 2016
≤ 50	-	-	-	-	-	-	-	-
50 - 1,500	−0.001	0.972	0.008	0.354	0.023	0.255	0.010	0.547
1,500 - 2,300	0.019	0.390	0.023	0.035	0.071	0.006	0.033	0.100
2,300 - 3,900	0.014	0.525	−0.003	0.754	0.009	0.719	0.012	0.532
> 3,900	0.001	0.972	0.021	0.070	0.051	0.060	0.028	0.181
Difference
≤ 50	-	-	-	-	-	-	-	-
50 - 1,500	0.013	0.435	0.006	0.507	0.018	0.385	0.012	0.487
1,500 - 2,300	0.010	0.634	0.001	0.948	0.005	0.842	0.005	0.823
2,300 - 3,900	0.027	0.193	0.007	0.508	0.019	0.444	0.028	0.171
> 3,900	0.008	0.723	0.011	0.298	0.028	0.289	0.015	0.472
Cotton worker, N = 178
Survey year 2011
≤ 50	-	-	-	-	-	-	-	-
50 – 1,500	0.033	0.412	0.039	0.036	0.087	0.060	0.055	0.126
1,500 - 2,300	0.057	0.179	0.059	0.003	0.144	0.003	0.087	0.023
2,300 - 3,900	0.033	0.453	0.030	0.143	0.080	0.107	0.042	0.276
> 3,900	0.046	0.302	0.052	0.013	0.113	0.027	0.075	0.063
Survey year 2016
≤ 50	-	-	-	-	-	-	-	-
50 - 1,500	0.052	0.202	0.050	0.008	0.114	0.014	0.075	0.038
1,500 - 2,300	0.072	0.091	0.064	0.001	0.159	0.001	0.099	0.010
2,300 - 3,900	0.065	0.137	0.041	0.041	0.109	0.028	0.079	0.044
> 3,900	0.057	0.208	0.067	0.001	0.149	0.004	0.097	0.018
Difference
≤ 50	-	-	-	-	-	-	-	-
50 – 1,500	0.019	0.602	0.010	0.520	0.028	0.492	0.020	0.560
1,500 - 2,300	0.015	0.692	0.005	0.756	0.015	0.728	0.012	0.732
2,300 - 3,900	0.032	0.386	0.012	0.484	0.030	0.484	0.036	0.312
> 3,900	0.011	0.773	0.016	0.363	0.036	0.393	0.022	0.545

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Note: Coefficients and p-Values from the linear mixed model with a random intercept were reported. p < 0.05 was considered significantly different from zero. SAD quantified by small airway measures was outcome and 8-hour TWA endotoxin was the exposure variable in the model. The linear mixed models were adjusted for age, gender, height, smoking intensity, survey year, and the interaction between 8-hour TWA endotoxin and survey year (8-hour TWA endotoxin × survey year). Abbreviations: TWA, Time-weighted Average; FEV₁, Forced Expiratory Volume in the first 1 second; pp FEV₁, percent predicted FEV₁; FVC, Forced Vital Capacity; Exp₋₈₅₆, percent gas trapping; E/I MLA, expiratory to inspiratory ratio of mean lung attenuation; RVC_{−856 to 950}, relative volume change of voxels with attenuation between −856 HU and −950 HU; Residual₋₈₅₆, residuals from the linear regression of Exp₋₈₅₆ on the percent of voxels with attenuation less than −950 HU.

50 EU/m³ represents the reference level. 1500 EU/m³ is the 40th percentile, 2300 EU/m³ is the 60th percentile, and 3900 EU/m³ is the 80th percentile. There are 237 textile workers exposed to ≤ 50 EU/m³ endotoxin, 61 workers exposed to 50 - 1,500 EU/m³ endotoxin, 35 workers exposed to 1,500 - 2,300 EU/m³ endotoxin, 37 workers exposed to 2,300 - 3,900 EU/m³ endotoxin, and 34 workers exposed to more than 3,900 EU/m³.

Table 5.

Multivariate analysis of the association between 8-hour TWA endotoxin and spirometry

8-hour TWA Endotoxin^a EU/m³)	FEV₁	p-Value	pp FEV₁	p-Value	FEV₁/FVC	p-Value
All, N = 404
Survey year 2011
≤ 50	-	-	-	-	-	-
50 - 1,500	17.546	0.759	0.090	0.972	−0.003	0.717
1,500 - 2,300	−121.286	0.091	−7.022	0.027	0.008	0.484
2,300 - 3,900	−9.607	0.892	−0.553	0.859	−0.012	0.314
> 3,900	−135.806	0.071	−6.717	0.043	−0.014	0.274
Survey year 2016
≤ 50	-	-	-	-	-	-
50 – 1,500	−54.546	0.341	−2.386	0.345	−0.009	0.364
1,500 - 2,300	−164.020	0.023	−8.570	0.007	−0.003	0.774
2,300 - 3,900	−50.986	0.472	−1.253	0.688	−0.008	0.495
> 3,900	−155.622	0.041	−6.634	0.048	0.003	0.788
Difference
≤ 50	-	-	-	-	-	-
50 - 1,500	−72.093	0.013	−2.477	0.065	−0.005	0.455
1,500 - 2,300	−42.734	0.245	−1.549	0.361	−0.012	0.181
2,300 – 3,900	−41.379	0.248	−0.700	0.671	0.004	0.656
> 3,900	−19.816	0.598	0.083	0.962	0.017	0.058
Cotton worker, N = 178
Survey year 2011
≤ 50	-	-	-	-	-	-
50 - 1,500	−17.182	0.901	−0.922	0.871	−0.006	0.786
1,500 - 2,300	−148.325	0.303	−7.517	0.208	0.006	0.778
2,300 - 3,900	−51.750	0.728	−1.928	0.754	−0.015	0.508
> 3,900	−161.792	0.290	−7.134	0.260	−0.018	0.429
Survey year 2016
≤ 50	-	-	-	-	-	-
50 - 1,500	−71.708	0.603	−3.451	0.546	−0.028	0.185
1,500 - 2,300	−175.111	0.225	−9.170	0.126	−0.023	0.308
2,300 - 3,900	−76.496	0.608	−2.747	0.657	−0.028	0.213
> 3,900	−166.739	0.280	−7.070	0.268	−0.018	0.439
Difference
≤ 50	-	-	-	-	-	-
50 - 1,500	−54.526	0.408	−2.529	0.394	−0.022	0.150
1,500 - 2,300	−26.786	0.701	−1.653	0.598	−0.029	0.070
2,300 - 3,900	−24.745	0.720	−0.819	0.792	−0.013	0.407
> 3,900	−4.947	0.944	0.063	0.984	<0.001	0.990

Open in a new tab

Note: Coefficients and p-Values from the linear mixed model with a random intercept were reported. p < 0.05 was considered significantly different from zero. Spirometry was outcome and 8-hour TWA endotoxin was the exposure variable in the model. The linear mixed models were adjusted for age, gender, height, smoking intensity, survey year, and the interaction between 8-hour TWA endotoxin and survey year (8-hour TWA endotoxin × survey year). Abbreviations: TWA, Time-weighted Average; FEV₁, Forced Expiratory Volume in the first 1 second; pp FEV₁, percent predicted FEV₁; FVC, Forced Vital Capacity; Exp₋₈₅₆, percent gas trapping; E/I MLA, expiratory to inspiratory ratio of mean lung attenuation; RVC_{−856 to −950}, relative volume change of voxels with attenuation between −856 HU and −950 HU; Residual₋₈₅₆, residuals from the linear regression of Exp₋₈₅₆ on the percent of voxels with attenuation less than −950 HU.

The adjusted association between small airway measures and spirometry and the association between small airway measures in 2011 and spirometry in 2016 can be found in e-Table 3 and e-Table 4, respectively.

Discussion

In this longitudinal study of textile workers, we evaluated the impact of occupational exposure to endotoxin on SAD. Exposure to endotoxin was significantly associated with the higher quantitative small airway measures of SAD and lower pulmonary function. We also identified the imaging biomarkers for detecting pre-clinical small airway dysfunction. All the small airway measures were significantly associated with the decline in pulmonary function. Among all the small airway measures, E/I MLA and RVC_{−856 to −950} were the two CT imaging biomarkers that showed the strongest association with and were the most predictive of pulmonary function decline due to small airway damages. The quantitative measures showed high reproducibility in terms of lung segmentation and feature extraction (e-Table 1).

To our knowledge, this is the first study to examine the association between occupational exposure and SAD using longitudinal paired CT scans. The association between SAD and occupational exposure found in this study has also been reported by other studies. Paulin et al. reported a significant association between occupational exposure to vapors, gas, dust or fumes and SAD measured by air trapping. ⁴⁴ Marchetti et al. conducted a study on subjects from the COPDGene cohort and found similar association between occupational exposure to dust/fumes and air trapping. ⁴⁵ Mendelson et al. found significant association between dust exposure and CT-measured air trapping on workers exposed to World Trade Center disaster dust. ⁴⁶ These findings are consistent with the results of this study. However, this study provides more comprehensive evaluation of quantitative small airway measures other than air trapping.

We observed the largest effect at 8-hour TWA endotoxin exposure levels between 1,500 - 2,300 EU/m³. This could partly be due to the unequal sample sizes across exposure categories (Table 1). Alternatively, the observed effect may suggest a threshold effect rather than a linear dose-response relationship, a pattern that has also been reported in previous studies.^47,48 We also found differences in the correlation between spirometry and imaging-based small airway measures with endotoxin exposure. These may be due to nuances in the types of airway changes each biomarker detects. While the standard spirometry reflects broader airway involvement, it does not consistently capture small airway changes that are detectable on imaging.^17,18 This suggests that imaging biomarkers for small airways may be more sensitive indicators of small airway disease than standard spirometry. The comparison between imaging biomarkers and other spirometric biomarkers for SAD, such as residual volume (RV), total lung capacity (TLC), forced oscillation technique (FOT), lung clearance index, and Forced Expiratory Flow 25-75% (FEF_25-75) requires further investigation. Additionally, the absence of a significant correlation between imaging biomarkers and endotoxin exposure in the 2011 cohort could be related to sample size limitations. Future studies with larger samples and more comprehensive spirometry values are essential to clarify these findings.

In this study, we identified two imaging biomarkers, E/I MLA and RVC_{−856 to −950}, that are indicative of endotoxin-related small airway dysfunction. SAD has been difficult to diagnose using traditional spirometric definitions mainly because the small airway abnormalities could occur for years before significant pulmonary function decline. ⁴⁹ Mets et al. conducted a study on lung cancer screening subjects and identified E/I MLA as the most suitable quantitative measure from CT scans for early detection of SAD. ⁵⁰ Hersh et al. assessed the quantitative small airway measures using 8,517 subjects from the COPDGene study and found similar results as our findings that imaging biomarkers, such as E/I MLA and RVC_{−856 to −950}, were a better way to describe spirometry, exercise capacity, and quality of life.²⁸

This study has several advantages. First, this is the first study on the association between occupational endotoxin and SAD, measured by small airway measures from longitudinal CT scans. The longitudinal CT scans allow us to model the long-term effects of exposure to endotoxin on small airways. Second, most of the subjects (86.4%) in the study were at pre-clinical stage with no airway obstruction (FEV₁/FVC ≥ 0.70), which helps to identify the imaging biomarkers for early detection of small airway abnormalities. Third, detailed work history and exposure over the entire working lifetime were available in this study, providing a comprehensive evaluation of occupational exposure effects.

This study also has some limitations. The predominance of subjects in the pre-clinical stages may result from selection bias, as only subjects who were still alive in 2011 since 1981 were included. However, the sensitivity analysis in cotton workers yielded the similar results to those in the entire cohort, reinforcing the confidence in our conclusion. Measurement bias may arise from variations in spirometry and CT scan equipment calibration or operator technique, potentially affecting the reliability of spirometry and small airway measurements. The environmental exposure to endotoxin was not measured after retirement of textile workers which may be a confounder for the effect of occupational endotoxin on SAD. However, there has been research showing that prior occupational endotoxin has a long-term association with changes in the airways. ³⁰ Though we found significant association between endotoxin exposure and spirometry/quantitative small airway measures, the dose-response relationship between endotoxin and indices of small airway disease still requires further investigation in the future study. Additionally, as multiple metrics were analyzed in this study, there is a potential for chance associations between endotoxin exposure and spirometry or quantitative small airway measures due to multiple testing. Finally, other image-based measures, such as PRM^fSAD and DPM-fSAD, were not included in this study. However, our findings demonstrated significant associations between endotoxin exposure and small airway disease measured by E/I MLA, RVC_{−856 to −950}, and Residual₋₈₅₆. These findings indicate potential associations between endotoxin concentrations and other imaging-based measures which is an important direction for future research.

Interpretation

In this longitudinal study of textile workers, we found significant association between occupational endotoxin exposure and small airway disease, described by small airway measures from paired inspiratory/expiratory CT scans and pulmonary function decline. The results suggest that the quantitative small airway measures are important tools in the detection of small airway remodeling and lung function decline for pre-clinical individuals (FEV₁/FVC ≥ 0.70). Specifically, our study identifies E/I MLA and RVC_{−856 to −950} as potential imaging biomarkers for the detection of small airway disease in pre-clinical patients.

Supplementary Material

supplement

NIHMS2044889-supplement-supplement.pdf^{(93.8KB, pdf)}

FUNDING/SUPPORT:

This work was supported by the National Institute for Occupational Safety and Health (NIOSH) R01 OH002421 and T42OH008416.

ABBREVIATIONS:

COPD: Chronic Obstructive Pulmonary Disease
CT: Computed Tomography
E/I MLA: Expiratory to inspiratory ratio of mean lung attenuation
Exp₋₈₅₆: the Percentage of voxels with attenuation less than −856 HU on expiratory CT scans
FEV₁: Forced Expiratory Volume in the first 1 second
FVC: Forced Vital Capacity
HU: Hounsfield Units
PRISm: Preserved ratio impaired spirometry
pp FEV₁: Percent predicted FEV₁
RVC_{−856 to −950}: Relative volume change of voxels with attenuation between −856 HU and −950 HU
Residual₋₈₅₆: Residuals from the linear regression of Exp₋₈₅₆ on the percent of voxels with attenuation less than −950 HU
SAD: Small Airway Disease
TWA: Time-Weighted Average

Footnotes

INSTITUTIONAL REVIEW BOARD: The institutional review boards of the Harvard School of Public Health, the Putuo District People’s Hospital, and the Human Resources Administration of China approved the study protocols.

CONFLICT OF INTEREST: The authors declare they have no conflicts of interest related to this work to disclose.

Contributor Information

Yuming Sun, Department of Mathematics, College of William and Mary.

Jian Kang, Department of Biostatistics, University of Michigan.

Feng-ying Zhang, Shanghai Putuo District People’s Hospital.

Hantao Wang, Department of Environmental Health and Epidemiology, Harvard T.H. School of Public Health.

Peggy S. Lai, Department of Environmental Health and Epidemiology, Harvard T.H. School of Public Health; Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital/ Harvard Medical School.

George R. Washko, Department of Radiology, Brigham and Women’s Hospital.

Raul San Jose Estepar, Department of Radiology, Brigham and Women’s Hospital.

David C. Christiani, Department of Environmental Health and Epidemiology, Harvard T.H. School of Public Health; Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital/ Harvard Medical School.

Yi Li, Department of Biostatistics, University of Michigan.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

supplement

NIHMS2044889-supplement-supplement.pdf^{(93.8KB, pdf)}

[R1] 1.Nattrass N, Seekings J. Trajectories of development and the global clothing industry. Competition & Change. 2018;22(3):274–292. [Google Scholar]

[R2] 2.GBD 2016 Occupational Chronic Respiratory Risk Factors Collaborators et al. Global and regional burden of chronic respiratory disease in 2016 arising from non-infectious airborne occupational exposures: a systematic analysis for the global burden of disease study 2016. Occupational and Environmental Medicine. 2020;77(3):142–150. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R3] 3.Khan M, Muhmood K, Noureen S, et al. Epidemiology of respiratory diseases and associated factors among female textile workers in pakistan. International Journal of Occupational Safety and Ergonomics. 2022;28(1):184–198. [DOI] [PubMed] [Google Scholar]

[R4] 4.Lane SR, Nicholls PJ, Sewell RDE. The measurement and health impact of endotoxin contamination in organic dusts from multiple sources: focus on the cotton industry. Inhalation Toxicology. 2004;16(4):217–229. [DOI] [PubMed] [Google Scholar]

[R5] 5.Khan AW, Moshammer HM, Kundi M. Industrial hygiene, occupational safety and respiratory symptoms in the pakistani cotton industry. BMJ Open. 2015;5(4):e007266. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R6] 6.Castellan RM, Olenchock SA, Hankinson JL, et al. Acute bronchoconstriction induced by cotton dust: dose-related responses to endotoxin and other dust factors. Annals of Internal Medicine. 1984;101(2):157–163. [DOI] [PubMed] [Google Scholar]

[R7] 7.Haglind P, Rylander R. Exposure to cotton dust in an experimental cardroom. Occupational and Environmental Medicine. 1984;41(3):340–345. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R8] 8.Lai PS, Hang JQ, Zhang FY, et al. Imaging phenotype of occupational endotoxin-related lung function decline. Environmental Health Perspectives. 2016;124(9): 1436–1442. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R9] 9.Brass DM, Hollingsworth JW, Cinque M, et al. Chronic LPS inhalation causes emphysema-like changes in mouse lung that are associated with apoptosis. American Journal of Respiratory Cell and Molecular Biology. 2008;39(5):584–590. [DOI] [PMC free article] [PubMed] [Google Scholar]

[R10] 10.Brass DM, Savov JD, Gavett SH, et al. Subchronic endotoxin inhalation causes persistent airway disease. American Journal of Physiology-Lung Cellular and Molecular Physiology. 2003;285 (3):L755–L761. [DOI] [PubMed] [Google Scholar]

[R11] 11.Macklem PT, Mead J. Resistance of central and peripheral airways measured by a retrograde catheter. Journal of Applied Physiology. 1967;22(3):395–401. [DOI] [PubMed] [Google Scholar]

[R12] 12.Berge MVD, Hacken NHT, Cohen J, et al. Small airway disease in asthma and COPD: clinical implications. Chest. 2011;139(2):412–423. [DOI] [PubMed] [Google Scholar]

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PERMALINK

Characterization of occupational endotoxin-related small airway disease with longitudinal paired inspiratory/expiratory CT scans

Yuming Sun, PhD

Jian Kang, PhD

Feng-ying Zhang, MD

Hantao Wang, PhD

Peggy S Lai, MD

George R Washko, MD

Raul San Jose Estepar, PhD

David C Christiani, MD

Yi Li, PhD

Abstract

BACKGROUND:

RESEARCH QUESTION:

STUDY DESIGN AND METHODS:

RESULTS:

INTERPRETATION:

Figure 1.

Study Design and Methods

Study population

Figure 2.

Exposure Assessment

Paired Chest CT scans

Quantitative Small Airway Measures

Statistical Analysis

Results

Table 1.

Figure 3.

Table 2.

Table 3.

Table 4.

Table 5.

Discussion

Interpretation

Supplementary Material

FUNDING/SUPPORT:

ABBREVIATIONS:

Footnotes

Contributor Information

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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