Exhaled breath profiling for early silicosis detection in workers at risk: a pilot study

Our plain-English summary of Exhaled breath profiling for early silicosis detection in workers at risk: a pilot study, by N. Van Loon, D. Ruttens, M. Verbrugghe, et al (ERJ Open Research, 2026).

The study

• Authors: N. Van Loon, D. Ruttens, M. Verbrugghe, K. Zwijsen, P. Van Damme, T. Lapperre, K. Lamote
• Journal: ERJ Open Research
• Published: 2026;12(5)
• Read it: PubMed · Publisher · Free full text

Abstract

Background: Silicosis remains a major occupational health concern in respirable crystalline silica (RCS)-exposed workers. Exhaled breath analysis using volatile organic compound (VOC) profiling has emerged as a promising noninvasive approach for early disease detection. This feasibility study evaluated multicapillary column/ion mobility spectrometry (MCC/IMS)-based VOC profiling for differentiating silicosis from other respiratory conditions and healthy controls in an occupational health setting.

Methods: We conducted a multicentre, cross-sectional observational study employing MCC/IMS to identify VOC patterns. Breath data were reduced to principal components and used in logistic lasso regression to develop predictive models. Internal and external validation assessed model performance, and subgroup analyses explored the impact of comorbidities and spirometry abnormalities.

Results: A total of 185 participants were enrolled, including 24 COPD patients, 26 with benign asbestos-related diseases (BARD) and 32 with confirmed silicosis, alongside 25 healthy controls and 78 RCS-exposed controls. Silicosis was distinguished from BARD and COPD with 100% and 87.5% accuracy (area under the receiver operating characteristic curve (AUCROC) 1.00 and 0.89), respectively. Comparison with healthy RCS-exposed controls yielded 87.8% accuracy with 98.5% sensitivity (AUCROC 0.58), improving to 82.8% accuracy and AUCROC 0.90 when considering spirometry abnormalities. Eight VOCs, notably P13 and P14, were identified as key discriminators.

Conclusion: MCC/IMS-based breath analysis shows promise as a rapid, portable and noninvasive technique for early detection of silicosis in RCS-exposed workers. Future research should validate these findings in larger cohorts, integrate cross-validation of candidate biomarkers across analytical platforms and establish standardised protocols to enable routine implementation in occupational health surveillance.

Copyright ©The authors 2026.

In plain English

This Belgian pilot study tested whether breath analysis by multicapillary column/ion mobility spectrometry could detect silicosis. It enrolled 185 people: 32 with silicosis, 78 silica-exposed workers, 25 unexposed controls, 24 with COPD and 26 with benign asbestos-related diseases (BARD). BARD patients showed a distinct breath signature. After excluding people with other lung or autoimmune disease or illicit drug use, 17 silicosis patients were compared with 65 healthy exposed workers. Silicosis was distinguished from BARD with 100% accuracy (95% CI 93.3–100) and from COPD with 87.5% (74.5–95.3). Against healthy exposed workers, accuracy was 87.8% (79.4–93.6) and sensitivity 98.5% (92.7–99.9), but the area under the curve was 0.58 (0.36–0.78). Against 12 exposed workers with abnormal spirometry, accuracy was 82.8% (65.9–93.4) and the area under the curve 0.90 (95% CI 0.77–0.96 in the text, 76.5–98.5 in table 3). Two compounds, tentatively phenol and pentanal, were the key predictors. The authors concluded the model could serve to rule out silicosis among at-risk workers. They called the findings hypothesis-generating, citing small numbers, age and sex differences, and missing HRCT scans for most exposed workers.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Multicentre, cross-sectional observational pilot (feasibility) study of exhaled-breath VOC profiling by MCC/IMS, with lasso and logistic regression models
• Who was studied: 185 participants (165 males, 20 females, aged 25–81) were recruited at three Belgian centres: Ziekenhuis Oost-Limburg, Mensura Occupational Health Service and Antwerp University Hospital. They were 32 confirmed silicosis patients, 25 unexposed healthy controls, 78 RCS-exposed controls, 24 COPD patients and 26 BARD patients. People with prior lung diseases, autoimmune disorders or illicit drug use were excluded from the final analysis. This left 17 'pure' silicosis patients and 65 healthy RCS-exposed controls. Study dates are not given.
• Exposure: Occupational respirable crystalline silica (quartz). Exposure risk was graded as no, low or high by job task and material, and duration was grouped as none, under 15 years, or 15 years or more. 73% of RCS-exposed controls had high-risk jobs. A BARD group was included as a comparison; asbestos fiber types are not specified.
• Main results:
  • 182 of 185 participants gave a breath sample. Four chromatograms were excluded, and 103 VOC peaks were detected across valid samples.
  • The BARD group's breath profiles formed a distinct signature in principal component analysis.
  • A three-group model (silicosis, nonexposed and exposed controls) reached internal and external validation accuracies of 92.1% and 90.6% (AUCROC 0.98 and 0.87).
  • Silicosis patients (n=17) were distinguished from BARD patients (n=26) with 100% accuracy (95% CI 93.3–100; AUCROC 1.00). They were distinguished from COPD patients (n=24) with 87.5% accuracy (95% CI 74.5–95.3; AUCROC 0.89).
  • Silicosis patients (n=17) compared with unexposed healthy controls (n=25): 62% accuracy, 100% sensitivity and NPV, AUCROC 0.60.
  • Silicosis patients (n=17) compared with healthy RCS-exposed controls (n=65): accuracy 87.8% (95% CI 79.4–93.6), sensitivity 98.5% (92.7–99.9), specificity 47.1% (24.8–70.3), NPV 88.9%, and AUCROC 0.58 (95% CI 0.36–0.78).
  • Silicosis patients (n=17) compared with RCS-exposed controls who had abnormal spirometry (n=12): 82.8% accuracy (95% CI 65.9–93.4), 82.4% sensitivity, 83.3% specificity, 76.9% NPV, 87.5% PPV and AUCROC 0.90. The text gives the AUCROC 95% CI as 0.77–0.96, while table 3 gives 89.7 (76.5–98.5).
  • In the rule-out model (AUCROC 0.92), VOCs P14 and P13 were the key predictors. They were tentatively identified as pentanal and phenol.
• The authors' conclusion: The authors concluded that MCC/IMS breath profiling was feasible for distinguishing silicosis from BARD and COPD. They suggested the model could serve to rule out disease among at-risk workers, and called for validation in larger cohorts.
• Limitations the authors state:
  • Silicosis patients and controls differed significantly in age and sex, so residual confounding cannot be excluded.
  • Other factors such as medication use, cigarette smoke and ambient air contaminants may affect breath VOCs.
  • Few silicosis patients were in the final analysis, which may have reduced statistical power. The authors regard the findings as hypothesis-generating.
  • Most RCS-exposed workers had no HRCT, so early silicosis among controls cannot be ruled out and misclassification is possible.
  • MCC/IMS gives only tentative identification of compounds, without definitive chemical characterisation.

Topics

Medical terms in this study, explained in our Lexicon: Silicosis, Crystalline, Spirometry, COPD, Biomarker.

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