The potential of volatile organic compound analysis for pathogen detection and disease monitoring in patients with cystic fibrosis

Barucha, Anton; Mauch, Renan Marrichi; Duckstein, Franziska; Zagoya, Carlos; Mainz, J.G.

doi:10.1080/17476348.2022.2104249

Cited by 5 publications

(2 citation statements)

References 74 publications

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“…This is the first study showing that ETI quickly impacts the breath composition and may contribute to normalise the level of abnormal VOCs in adults with CF. Disease-specific and lung pathogen-related breath signatures were previously reported in CF patients [23][24][25][26][27][28][29] but the effects of disease-modifying CFTR modulators have been little explored. Neerincx et al…”

Section: Discussionmentioning

confidence: 99%

Real-time breath metabolomics to assess early response to CFTR modulators in adults with cystic fibrosis: an open-label proof-of-concept study

Bardin,

Salvator,

Roquencourt

et al. 2024

Preprint

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BackgroundThe combination of CFTR modulators ivacaftor/tezacaftor/elexacaftor (ETI) achieves unprecedented improvements in clinical symptoms and respiratory function of people with cystic fibrosis. Yet, evaluation is difficult in people with high baseline lung function and the sweat test may vary depending on the type of CFTR mutation. Exhaled breath is a non-invasive sample, rich in personalised metabolic information and breathomics has emerged as a promising tool to monitor and assess therapeutic response. We hypothesised that ETI induces alterations in the breath composition and that these changes may correlate with clinical readouts.MethodsTen adults initiating ETI were enrolled in a prospective open-label study. Exhaled breath was analysed before, after one week and one month of treatment by real-time, proton transfer reaction-mass spectrometry. Clinical symptoms, lung function and sweat test results were recorded.ResultsA total of 29 breath samples were analysed; 108 volatile organic compounds (VOCs) were consistently detected. In responders (8/10), 21 VOCs were significantly modified, mostly hydrocarbons or small carbonyl compounds. At baseline, these VOCs exhibited significantly different concentrations compared to healthy young adults; throughout the first month of treatment, their level in CF breath evolved towards that of healthy volunteers. Eight of these also correlated with variations in lung function.ConclusionReal-time breath analysis identified alterations in the breath at the early stages of treatment that tended to normalise after one month. These changes exhibited correlations with clinical indicators, suggesting that breath VOCs may serve as early biomarkers useful for treatment monitoring.Trial registrationNCT05295524Key messagesWhat is already known on this topicAs efficient new generations of treatments are emerging for patients with CF, we are lacking early, non-invasive, personalised biomarkers associated with response to therapies. The previous generation of CFTR modulators modified the composition of breath within 3 months, yet nothing was known about the early impact of the newer combinations.What this study addsThe triple combination of CFTR modulators modifies the composition of breath in people with CF as soon as within one week of treatment and tends to normalise basal alterations in CF breath. These changes in breath composition may be captured with real-time mass spectrometry and correlate with clinical outcomes.How this study might affect research, practice or policyReal-time breath analysis may become useful in monitoring companion biomarkers associated with therapeutic response in patients with CF. Identification of related biological pathways could also help to elucidate the mode of action of these drugs.

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Section: Discussionmentioning

confidence: 99%

Real-time breath metabolomics to assess early response to CFTR modulators in adults with cystic fibrosis: an open-label proof-of-concept study

Bardin,

Salvator,

Roquencourt

et al. 2024

Preprint

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“…To enable accurate measurement of multiple gases, the combination of diverse gas-sensing films and an array design assisted by artificial intelligence algorithms shows great potential (Barucha et al 2022 ; Yang et al 2018 ). Capman et al (Capman et al 2022 ) demonstrated the selective and rapid detection of multiple VOCs using graphene-based variable capacitor arrays (Fig.…”

Section: Voc Detectionmentioning

confidence: 99%

Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform

Wang,

He,

Zhou

et al. 2023

Bioelectron Med

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The fourth industrial revolution has led to the development and application of health monitoring sensors that are characterized by digitalization and intelligence. These sensors have extensive applications in medical care, personal health management, elderly care, sports, and other fields, providing people with more convenient and real-time health services. However, these sensors face limitations such as noise and drift, difficulty in extracting useful information from large amounts of data, and lack of feedback or control signals. The development of artificial intelligence has provided powerful tools and algorithms for data processing and analysis, enabling intelligent health monitoring, and achieving high-precision predictions and decisions. By integrating the Internet of Things, artificial intelligence, and health monitoring sensors, it becomes possible to realize a closed-loop system with the functions of real-time monitoring, data collection, online analysis, diagnosis, and treatment recommendations. This review focuses on the development of healthcare artificial sensors enhanced by intelligent technologies from the aspects of materials, device structure, system integration, and application scenarios. Specifically, this review first introduces the great advances in wearable sensors for monitoring respiration rate, heart rate, pulse, sweat, and tears; implantable sensors for cardiovascular care, nerve signal acquisition, and neurotransmitter monitoring; soft wearable electronics for precise therapy. Then, the recent advances in volatile organic compound detection are highlighted. Next, the current developments of human-machine interfaces, AI-enhanced multimode sensors, and AI-enhanced self-sustainable systems are reviewed. Last, a perspective on future directions for further research development is also provided. In summary, the fusion of artificial intelligence and artificial sensors will provide more intelligent, convenient, and secure services for next-generation healthcare and biomedical applications.

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Volatile organic compounds analysis as promising biomarkers for Parkinson’s disease diagnosis: A systematic review and meta-analysis

Habibzadeh,

Ostovan,

Keshavarzian

et al. 2023

Clinical Neurology and Neurosurgery

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The potential of volatile organic compound analysis for pathogen detection and disease monitoring in patients with cystic fibrosis

Cited by 5 publications

References 74 publications

Real-time breath metabolomics to assess early response to CFTR modulators in adults with cystic fibrosis: an open-label proof-of-concept study

Real-time breath metabolomics to assess early response to CFTR modulators in adults with cystic fibrosis: an open-label proof-of-concept study

Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform

Volatile organic compounds analysis as promising biomarkers for Parkinson’s disease diagnosis: A systematic review and meta-analysis

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