MSACL 2026 Abstract

Translating Asthma Breath Markers into an Actionable Clinical Tool for Personalized Medicine

Thibault Massenet (1), Delphine Zanella (1), Renaud Louis (2), Salman Siddiqui (3), Florence Schleich (4), Pierre-Hugues Stefanuto (1)
(1) Molecular System, Organic & Biological Analytical Chemistry group, University of Liège, Liège, Belgium. (2) Respiratory Medicine, University Hospital of Liège, GIGA I3 Research Group, Liège, Belgium. (3) National Heart and Lung Institute (NHLI), Imperial NIHR Respiratory Biomedical Research Cen-tre, Imperial College London, London, United Kingdom. (4) Respiratory Medicine, University Hospital of Liège, GIGA I3 Research Group, Exercise Physiolo-gy Lab, Department of Physical Activity and Rehabilitation Sciences, University of Liège, Liège, Belgium

Pierre-Hugues Stefanuto, PhD (Presenter) Liège University

Presenter Bio: Pierre-Hugues Stefanuto is lead scientist and lecturer at Liège University in Belgium. His main research interest is the development of analytical solutions based on chromatography and mass spectrometry technology. He is interested in the development of statistical models for method optimization and data handling. He is working on the development on multimodal solutions of untargeted screening of small molecules.
Driving Research Goal: Development of multi-omics screening to tackle biomedical challenges at the molecular level

Relevant Financial Disclosures (within past 24 months, reported on Apr 21, 2026) Consultant Fees Total Energies, L'Oréal Grant/Research Support FNRS, Fondation Leon Fredericq, University of Liège, MS Expertise, LECO Corp., Trajan Scientific Medical Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

INTRODUCTION:
Chronic lung inflammation is major challenge for healthcare professionals. Asthma and COPD are uncurable and represent a high burden on healthcare systems. According to WHO, asthma is the most common chronic disease among children. It affected around 262 million people in 2019 and caused 455 000 deaths. Proper asthma management requires efficient monitoring tools to define and adjust treatment using personalized approaches [1]. Exhaled breath analysis holds strong promise for non-invasive monitoring, especially for chronic lung inflammation. The best example is the use of FeNO measurement to access asthma phenotype in clinics [2]. In the past five years, we have demonstrated the capabilities of exhaled breath analysis to identify eosinophilic and neutrophilic asthma in large cohort (> 500 patients) [2,3]. We have also worked on in-vitro model development to identify metabolic pathways linked to our breath markers [3,4]. Asthma exhaled breath has yet to fully translate into clinical practice to reveal its full potential through large scale multicentric studies.

OBJECTIVES:
Building on this link between lung inflammation and breath composition, we aim to push further our exhaled breath platform by predicting treatment response in the context of biologic therapy. Following this goal, we are building routine breath screening capabilities, to support clinical translation.

METHODS:
In a longitudinal multicentric design (>130 patients), we have used our previously developed analytical workflow combining ready to use sampling kits with thermal desorption coupled comprehensive two-dimensional gas chromatography hyphenated with mass spectrometry (TD-GCxGC-MS). The breath samples were collected prior initiating treatment and at different time points over the course of treatment. The resulting data were analyzed following a targeted and a non-targeted screening workflow. All the samples and data collected are compliant with the ethical standards.

RESULTS:
We have established a robust QAQC compatible with exploratory Breathomics. To achieve this, we have performed extended investigations on sampling devices robustness and their implementability into clinical practice. We have also developed artificial breath samples for SST evaluation. Regarding the patient samples, in the targeted workflow, we have demonstrated the capabilities of transferring eosinophilic markers into treatment response prediction (AUC > 0.95). In addition, we have established a direct link with reactive aldehyde species in exhaled breath (AUC > 0.90). In the non-targeted workflow, we have also demonstrated the feasibility of multi-platform data combination for marker discovery.

CONCLUSION:
This study represents a major step forward regarding breath marker transferability across studies and research centers using different analytical workflows. It demonstrates the capacity to predict and monitor treatment in asthma patients, opening the door of personalized adjustments. This work consolidates the need to extend exhaled breath analysis as a major asset for lung inflammation monitoring.

References
[1] https://www.who.int/news-room/fact-sheets/detail/asthma
[2] Schleich, F. N., et al. (2019). Exhaled Volatile Organic Compounds Are Able to Discriminate between Neutrophilic and Eosinophilic Asthma. American Journal of Respiratory and Critical Care Medicine, 200, 444-453.
[3] Peltrini, R., et al. (2024). Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma. American Journal of Respiratory & Critical Care Medicine, 210(9).
[4] Zanella, D., et al. (2020). Comparison of the effect of chemically and biologically induced inflammation on the volatile metabolite production of lung epithelial cells by GC× GC-TOFMS. The Analyst, 145(15), 5148-5157.