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Systemic sclerosis is a rare autoimmune disease associated with rapidly evolving interstitial lung disease, responsible for the disease severity and mortality. Specific biomarkers enabling the early diagnosis and prognosis associated with the disease progression are highly needed. Volatile organic compounds in exhaled breath are widely available and non-invasive and have the potential to reflect metabolic processes occurring within the body. Comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry was used to investigate the potential of exhaled breath to diagnose systemic sclerosis. The exhaled breath of 32 patients and 30 healthy subjects was analyzed. The high resolving power of this approach enabled the detection of 356 compounds in the breath of systemic sclerosis patients, which was characterized by an increase of mainly terpenoids and hydrocarbons. In addition, the use of 4 complementary statistical approaches (two-tailed equal variance t-test, fold change, partial least squares discriminant analysis, and random forest) resulted in the identification of 16 compounds that can be used to discriminate systemic sclerosis patients from healthy subjects. Receiver operating curves were generated that provided an accuracy of 90%, a sensitivity of 92%, and a specificity of 89%. The chemical identification of eight compounds predictive of systemic sclerosis was validated using commercially available standards. The analytical variations together with the volatile composition of room air were carefully monitored during the timeframe of the study to ensure the robustness of the technique. This study represents the first reported evaluation of exhaled breath analysis for systemic sclerosis diagnosis and provides surrogate markers for such disease.

Despite the same basic ingredients used in brewing, there is a significant variation in beer styles. With the rapid increase in craft brewing, beer styles have become even more numerous and complex in the recent past. A GC-MS/VUV (post-column split for dual detection) instrument with headspace high capacity SPME was used to investigate 21 different beers which represent three beer styles - India pale ales, blondes, and hefeweizens. Since results from untargeted studies can be affected by the sorbent material used, the extraction performances of three high capacity SPME fibers, i.e., polydimethylsiloxane, polydimethylsiloxane/carbon wide range, and polydimethylsiloxane/carbon wide range/divinylbenzene, were evaluated. Good reproducibility (10% RSD) was obtained for each high capacity fiber using both detectors. The tandem MS/VUV detection coupled with GC separation proved to be particularly valuable for compound identification, especially for isomers and compounds with similar structures. The evaluation of VUV detection for untargeted analysis led to similar performances as MS detection. Both the VUV and the MS were able to effectively differentiate between beer styles using principal component analysis. In addition, the use of 3 different statistical approaches, one-way ANOVA (p-value 0.05), partial least square discriminant analysis, and random forest, universally identified 12 of the components most influential in distinguishing the three beer styles (e.g., β-myrcene, linalool, isopentyl acetate, 2,4-di-tert-butylphenol). This is the first reported evaluation of VUV detection and the first comparison of simultaneous VUV and MS detection for untargeted classification of complex mixtures using GC.

Rationale: Analysis of exhaled breath for asthma phenotyping using endogenously generated volatile organic compounds (VOCs) offers the possibility of noninvasive diagnosis and therapeutic monitoring. Induced sputum is indeed not widely available and markers of neutrophilic asthma are still lacking.Objectives: To determine whether analysis of exhaled breath using endogenously generated VOCs can be a surrogate marker for recognition of sputum inflammatory phenotypes.Methods: We conducted a prospective study on 521 patients with asthma recruited from the University Asthma Clinic of Liege. Patients underwent VOC measurement, fraction of exhaled nitric oxide (FENO) spirometry, sputum induction, and gave a blood sample. Subjects with asthma were classified in three inflammatory phenotypes according to their sputum granulocytic cell count.Measurements and Main Results: In the discovery study, seven potential biomarkers were highlighted by gas chromatography-mass spectrometry in a training cohort of 276 patients with asthma. In the replication study (n = 245), we confirmed four VOCs of interest to discriminate among asthma inflammatory phenotypes using comprehensive two-dimensional gas chromatography coupled to high-resolution time-of-flight mass spectrometry. Hexane and 2-hexanone were identified as compounds with the highest classification performance in eosinophilic asthma with accuracy comparable to that of blood eosinophils and FENO. Moreover, the combination of FENO, blood eosinophils, and VOCs gave a very good prediction of eosinophilic asthma (area under the receiver operating characteristic curve, 0.9). For neutrophilic asthma, the combination of nonanal, 1-propanol, and hexane had a classification performance similar to FENO or blood eosinophils in eosinophilic asthma. Those compounds were found in higher levels in neutrophilic asthma.Conclusions: Our study is the first attempt to characterize VOCs according to sputum granulocytic profile in a large population of patients with asthma and provide surrogate markers for neutrophilic asthma.

Sophie Graff,1 Delphine Zanella,2 Pierre-Hugues Stefanuto,2 Monique Henket,1 Virginie Paulus,1 Francoise Guissard,1 Catherine Moermans,1 Kristel Van Steen,3 Renaud Louis,1 Florence Schleich1 1Department of Respiratory Medicine, GIGA I3, CHU Sart-Tilman, Liege, Belgium; 2Organic and Biological Analytical Chemistry Group, University of Liege, Liege, Belgium; 3BIO3-Systems Genetics, GIGA-R, University of Liege, Liege, BelgiumCorrespondence: Sophie GraffDepartment of Respiratory Medicine, CHU Sart-Tilman, GIGA +4, CHU - B34, Avenue de l’Hôpital, 11, Liège 4000, BelgiumTel +32 4366 45 92Email sgraff@uliege.be

Exhaled breath analysis has become an important part of volatilomics, with high potential for health applications, particularly as a noninvasive diagnostic tool. Nevertheless, this approach faces numerous challenges, the first being the need to employ powerful analytical techniques to properly resolve the breath volatilome and to extract the relevant information, and the second consisting of establishing a high-quality and reliable data analysis workflow. This chapter highlights the capabilities of comprehensive two-dimensional gas chromatography (GC×GC) as the ideal analytical technique for the analysis of exhaled breath. The coupling of GC×GC with mass spectrometry (MS) and the enhanced identification power using high-resolution (HR) MS is also discussed. In addition, an emphasis is placed on the importance of the data processing workflow, as well as the need to produce high data quality in order to perform useful statistical analyses. Finally, some successful applications of GC×GC-(HR)MS in volatilomics are presented.

VOCs are surrogate markers for salbutamol and OCS use, which are part of the definition of poor asthma control. This suggests that VOCs are promising biomarkers that could possibly be used to detect poor adherence to inhaled therapy.http://bit.ly/2SgE44R