<figure><img src="image_1.png" /></figure>

HAL
open science

# Combination of real-time and hyphenated mass spectrometry for improved characterisation of exhaled breath biomarkers in clinical research

Elodie Lamy, Camille Roquencourt, Bingqing Zhou, Hélène Salvator, Pierre Moine, Djillali Annane, Philippe Devillier, Emmanuelle Bardin, Stanislas Grassin-Delyle

► To cite this version:

Elodie Lamy, Camille Roquencourt, Bingqing Zhou, Hélène Salvator, Pierre Moine, et al. Combina-
tion of real-time and hyphenated mass spectrometry for improved characterisation of exhaled breath
biomarkers in clinical research. Analytical and Bioanalytical Chemistry, 2024, 416 (22), pp.4929-4939.
10.1007/s00216-024-05421-7 . hal-04687384

HAL Id: hal-04687384

https://hal.science/hal-04687384v1

Submitted on 12 Dec 2024

**HAL** is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Combination of real-time and hyphenated mass spectrometry for improved characterisation of exhaled breath biomarkers in clinical research

Running head: VOCs in exhaled breath

4

5 Elodie LAMY,ª Camille ROQUENCOURT,ᶜ Bingqing ZHOU,ª Hélène SALVATOR,⁵ Pierre

6 MOINE,ª,b,f Djillali ANNANE,ª,b,f Philippe DEVILLIER,⁵,c,e Emmanuelle BARDIN,ª,g Stanislas

7 GRASSIN-DELYLE,ª,b,c

8

9 a Université Paris-Saclay, UVSQ, INSERM, Infection et Inflammation (2I), U1173, Département de
10 Biotechnologie de la Santé, Montigny le Bretonneux, France ; b FHU SEPSIS (Saclay and Paris
11 Seine Nord Endeavour to PerSonalize Interventions for Sepsis), Garches, France ; c Exhalomics®,
12 Hôpital Foch, Suresnes, France ; d Pneumologie, Hôpital Foch, Suresnes, France ; e Laboratoire de
13 recherche en Pharmacologie Respiratoire – VIM Suresnes, UMR 0892, Université Paris-Saclay,
14 UVSQ, Suresnes, France ; f Réanimation médicale, Hôpital Raymond Poincaré, Assistance
15 Publique-Hôpitaux de Paris, Garches, France ; g Institut Necker-Enfants Malades, Paris, France.

16

17 Corresponding author: Stanislas GRASSIN-DELYLE

18 Université Paris-Saclay, UVSQ, INSERM

19 Infection et inflammation (2I), U1173

20 Département de Biotechnologie de la Santé

21 UFR Simone Veil - Santé

22 2 avenue de la source de la Bièvre

23 78180 Montigny le Bretonneux, France

24 E-mail address: stanislas.grassin-delyle@uvsq.fr

25 Phone: + 33.1.70.42.94.22.

26
27 **ABSTRACT**

28 Exhaled breath volatilomics is a powerful non-invasive tool for biomarker discovery in medical
29 applications, but compound annotation is essential for pathophysiological insights and technology
30 transfer. This study was aimed at investigating the interest of a hybrid approach combining real-
31 time proton transfer reaction - time-of-flight mass spectrometry (PTR-TOF-MS) with
32 comprehensive thermal desorption - two-dimensional gas chromatography coupled to time-of-flight
33 mass spectrometry (TD-GCxGC-TOF-MS) to enhance the analysis and characterization of VOCs in
34 clinical research, using COVID-19 as a use case. VOC biomarker candidates were selected from
35 clinical research using PTR-TOF-MS fingerprinting in patients with COVID-19 and matched to the
36 Human Breathomic Database. Corresponding analytical standards were analysed using both a liquid
37 calibration unit coupled to PTR-TOF-MS and TD-GCxGC-TOF-MS, together with confirmation on
38 new clinical samples with TD-GCxGC-TOF-MS. From 26 potential VOC biomarkers, 23 were
39 successfully detected with PTR-TOF-MS. All VOCs were successfully detected using TD-GCxGC-
40 TOF-MS, providing effective separation of highly chemically-related compounds, including
41 isomers, and enabling high-confidence annotation based on two-dimensional chromatographic
42 separation and mass spectra. Four VOCs were identified with a level 1 annotation in the clinical
43 samples. For future applications, the combination of real-time PTR-TOF-MS and comprehensive
44 TD-GCxGC-TOF-MS, at least on a subset of samples from a whole study, would enhance the
45 performance of VOC annotation, offering potential advancements in biomarker discovery for
46 clinical research.

47

48 **Keywords:** volatile organic compounds; breath analysis; annotation; two-dimensional gas
49 chromatography; proton transfer reaction-mass spectrometry.

50
## 51 INTRODUCTION

Volatile organic compounds (VOCs) in exhaled breath were first described with the identification of acetone in the nineteenth century (1). Thousands of VOCs were since then reported in breath in a number of contexts (1, 2) and volatilomics, the science of breath analysis, is acknowledged as a powerful non-invasive tool for metabolomic screening and the discovery of biomarkers of pathologic states. VOCs in exhaled breath reflect a number of metabolic processes within the entire body and different factors such as age, weight, exposome and lifestyle can influence VOC profile in breath (3-8). Many studies have highlighted the potential of breath analysis for discovering biomarkers of asthma, lung cancer, COVID-19 or other infectious diseases (9-13). The analytical setups mainly consist in techniques relying on mass spectrometry (MS) such as gas chromatography – MS (GC-MS), proton transfer reaction – MS (PTR-MS), selected-ion flow-tube - MS (SIFT-MS)) or on sensors embedded in electronic noses (eNoses). Advantages are real-time analysis for techniques such as PTR-MS, SIFT-MS and eNoses, sensitive quantitative analysis (PTR-MS, SIFT-MS) and comprehensive analysis for GC-MS, while main disadvantages are time-consuming sample preparation and analysis (GC-MS), absence of separation of isomers (PTR-MS and SIFT-MS) and poor specificity (eNoses). For medical applications, the aim is not only to detect features (biomarker candidates) characterized by various reliable analytical metrics (m/z, retention time, fragmentation spectrum...) but also to have a strong capability for the chemical identification of these features (annotation). This enables the elucidation of the role of these metabolites in pathophysiology and facilitates technology transfers for developing detection methods that are easier, faster, or less costly. The level of confidence for the annotation of specific VOC differs greatly among techniques. Four levels of annotation applicable to MS techniques were described by the Metabolomics Standards Initiative, ranging from level 4, the level with the lowest confidence and defined only by the exact mass of the VOC, to level 1, the one with the highest confidence and defined by at least two orthogonal information such as retention time and exact mass or
fragmentation spectrum, found both in experimental samples and analytical standards. Achieving
the level 1 of annotation for a given compound entails its identification (14-16). Online methods are
one-dimensional techniques providing access to a single information, mainly consisting in the *m/z*
ratio of the protonated molecule consecutive to soft ionization. Electron ionisation and GC-MS
offer both fragmentation mass spectrum and retention time which can be matched to available
libraries for compound identification. However, challenging issues to address in the annotation step
are compounds co-eluting in chromatography, which is especially true for isomers, where each
molecule is highly chemically-related since it has the same molecular formula but different
arrangements in space, sometimes so similar that their fragmentation spectra can be identical. In
contrast to classical GC-MS, two-dimensional GC coupled to TOF-MS (GCxGC-TOF-MS)
provides increased sensitivity and superior separation capabilities thanks to the use of
chromatographic columns of different polarity, thereby enabling the detection and identification of
more VOCs. As suitable mass spectral libraries continue to be developed, GCxGC-TOF-MS is even
anticipated to surpass GC-MS as the gold-standard method for analysing clinical samples (17-19).
Real-time (online) and hyphenated chromatographic (offline) techniques can be associated for
certain purposes. For example, the complementarity of GC-MS and PTR-MS techniques for the
annotation of VOCs was summarized in a review article (17) and further corroborated recently (20,
21). However, PTR-MS and GCxGC-TOF-MS have never been associated for the characterization
of VOCs from human clinical breath specimen. Therefore, the aim of the present study was to take
advantage of the complementarity between online and offline MS methods to improve the analysis
and annotation of VOC biomarkers in clinical research, using COVID-19 as a use case. Hence,
candidate biomarkers discovered with real-time PTR-TOF-MS analysis were subjected to intensive
characterization by employing a comprehensive thermal desorption (TD)-GCxGC-TOF-MS
approach. The consecutive steps were the extraction of a list of features of interest from a previous
PTR-TOF-MS fingerprinting clinical study in COVID-19 patients; the generation of a list of
101 proposed annotations for each feature based on their *m/z* ratio; the list filtering to retain only a set of
102 VOCs reported in the Human Breathomic Database (HBDB) as expressed in human breath; analysis
103 of analytical standards of each VOCs with both PTR-TOF-MS and TD-GCxGC-TOF-MS, and
104 finally TD-GCxGC-TOF-MS confirmation with new clinical samples.
## 105 MATERIALS AND METHODS

### 107 Chemicals and reagents

108 LC-MS-grade methanol, hexane, water and 4-methyl-2-pentenal were supplied by Fisher Scientific

109 (Illkirch, France). Hexanoic acid was supplied by Cluzeau Info Labo (Sainte-Foy-la-Grande,

110 France). All other VOC analytical standards were supplied by Sigma Aldrich (Saint-Quentin-

111 Fallavier, France). The list of 26 VOC analytical standards is summarized in Table 1.

### 113 Analytical standard preparation

114 For liquid calibration unit (LCU)-PTR-TOF-MS analysis, standards were prepared separately at 250

115 ppb with dilutions in either water or hexane. For TD-GCxGC-TOF-MS analysis, each analytical

116 standard was prepared separately at 250 ppb in methanol and 1 microliter was spiked onto Tenax

117 TA tubes (Markes, Cardiff, United Kingdom).

### 119 Thermal desorption (TD)-GCxGC-TOF-MS system and analysis procedure

120 VOCs trapped onto the Tenax TA tubes were desorbed into a TD3.5+ thermodesorber (Gerstel,

121 Mulheim, Germany) with an initial temperature of 30°C, reaching 290°C in 4.5 min, then

122 maintained for 5.0 min. VOCs were transferred at a flow rate of 50 mL/min with helium (purity 5.0

123 provided by Messer, Suresnes, France) to a cold trap maintained at -30°C during the run of the

124 thermodesorber. Cold trap desorption was performed for 5.0 min at 290°C with a split ratio of 20

125 and finally purging the trap at 25 mL/min for 3.0 min. Two-dimensional gas chromatography was

126 performed according to a previously described method (9) with a 8890 GC system (Agilent

127 technologies, California, United States), using Rxi-624Sil MS (30 m x 0.25 mm x 1.4 µm) and

128 stabilwax (2 m x 0.25 mm x 0.5 µm) (Restek, Lisses, France) columns.
The GC oven temperature was initially set at 40°C for 1.0 min, reaching 240°C at a gradient of 129 5°C/min maintained during 5.0 min. The total run time was 46.0 min. The transfer line and 130 ionization source temperatures were set at 250°C. Modulation was performed with a cryogenic 131 module (American Magnetics, Tennessee, United States) and modulation period was 1.25 seconds. 132 Compounds were ionized with an electronic impact source operating at 70 eV and detected with a 133 time-of-flight BT4D mass spectrometer (Leco, Michigan, United States) in the scan range 29-450 134 Da with an acquisition rate of 32 Hz. Data acquisition and processing was performed using Maestro 135 (Gerstel) and ChromaTOF (Leco). 136

137

## LCU-PTR-TOF-MS system and analysis procedure

Solutions of analytical standards were nebulized with a liquid calibration unit (LCU-a, Ionicon, 139 Innsbruck, Austria). The nebulization chamber and the heated hose were set at 90°C and 70°C 140 respectively, the flow rate was 5 µL/min, nitrogen was used as a nebulizer gas with a flow rate of 141 1000 sccm. The acquisition time was 5.0 min per analytical standard. Compounds were ionized 142 with a proton-transfer-reaction source using H<sub>3</sub>O<sup>+</sup> as the primary ion and detected with a 143 quadrupole time-of-flight mass spectrometer (PTR-Qi-TOF, Ionicon), with instrument settings as 144 previously described (12). Data acquisition and processing was performed using TofDAQ Viewer 145 (Ionicon) and the ptairMS R package (22). 146

147

## Patient sampling for TD-GCxGC-TOF-MS analysis

Breath samples were obtained from 23 intensive care unit patients with COVID-19 enrolled in the 149 RECORDS trial (NCT04280497). The study was approved by an ethics committee (Comité de 150 Protection des Personnes EST I, Dijon, France; reference 20.03.10.51415). Whenever possible, 151 participants or their legally authorized next of kin provided written, informed consent before 152 inclusion. In the remaining cases, patients provided their deferred, written, informed consent. 153
Spontaneously breathing patients filled a 3-liter Tedlar® bag (SKC, PA, United States). Then the Tedlar® bag was immediately connected to a Tenax TA tube and gas was aspirated through the tube using the ACTI-VOC low-flow pump (Markes) at a flow rate of 200 mL/min for 5.0 min. For intubated and mechanically ventilated patients, exhaled breath was collected onto Tenax TA tube connected directly to the end of the endotracheal tube (i.e., without disconnection from the mechanical ventilator) using the same pumping parameters.
160 **RESULTS**

161 **Compound selection**

162 We previously reported a set of PTR-TOF-MS features to discriminate patients with or without
163 COVID-19 (12). These features, defined by their *m/z* ratio, were matched with the Human
164 Breathomics Database (HBDB) (tolerance set at 50 ppm), which allowed us to select a set of 26
165 candidate VOC biomarkers known to be expressed in the human breath (2, 23). Those compounds
166 mainly belong to the chemical families of alkanes, alkenes, ketones and aldehydes and correspond
167 to 10 distinct molecular formulas, with molecular masses in the range 70.09 – 142.28 Da. The list of
168 compounds is shown in Table 1.

169

170 **LCU-PTR-TOF-MS analysis**

171 The aqueous solutions of the different compounds were first analysed with LCU-PTR-TOF-MS,
172 and peaks at the expected *m/z* for [M+H]$^+$ ions were observed for 15 of the 26 VOCs (Table 1).
173 Solubilisation in hexane enabled the detection of 8 additional VOCs, but the three remaining
174 compounds (4-methylheptane, 1-chloroheptane, and 2,4,6-trimethylheptane) were not detected
175 under any condition. We then took advantage from the mass resolution offered by the TOF analyser
176 to perform an untargeted data analysis thanks to the ptairMS software (22), in addition to the
177 targeted search for the [M+H]$^+$ ions. All $^{13}$C isotopes of the [M+H]$^+$ ions for the 23 detected VOCs
178 were found with a relative abundance equivalent to 2-8% of their respective [M+H]$^+$ ion. Then, ions
179 with an abundance above 5% of the [M+H]$^+$ ion and highly correlated with the intensity of the
180 [M+H]$^+$ ion (*r* > 0.9) were considered. Additional correlated ions were thus observed for 20 of the
181 23 detected VOCs, but not for benzene, p-xylene and m-xylene. These ions were compared to those
182 described in the NIST database for the electron impact GC-MS analysis of the same compounds,
183 taking into account the mass difference related to the respective ionisation modes ([M+H]$^+$ for PTR-
184 MS *vs* M$^+$ for GC-MS). All results are reported in Table 2.
185 TD-GCxGC-TOF-MS analysis

186 All analytical standards (n = 26) were detected with TD-GCxGC-TOF-MS analysis. Retention 187 times ranged from 6.5 to 23.3 min in the first dimension and from 0.45 to 1.17 s in the second 188 dimension (Table 1). In the first chromatographic dimension, the retention time was related to the 189 number of carbons, with retention time globally increasing with the number of carbons. On the 190 other hand, the second chromatographic dimension was rather related to chemical families, with 191 mean retention times increasing between alkanes (0.498 s), alkenes (0.508 s), ketones (0.779 s) and 192 aldehydes (0.854 s). The identification scores obtained when matching the mass spectra to the NIST 193 database were all greater than 897/1000, demonstrating the high confidence of the identification. 194 We then stratified the data analysis to assess the ability of TD-GCxGC-TOF-MS to discriminate 195 between compounds co-eluting in the first chromatographic dimension or between isomers / closely 196 related compounds.

197 For example, benzene (C6H6) co-eluted in the first dimension with cyclohexene and 2,4-hexadiene 198 (retention times between 7.6 and 7.9 min). However, the retention times in the second dimension 199 were different, therefore enabling the individualisation of their respective mass spectra and 200 subsequent specific identification (Figure 1).

201 With respect to isomers or closely related compounds, there were 6 groups of compounds sharing 202 the same monoisotopic mass, which provided the same [M+H]⁺ ion during LCU-PTR-TOF-MS 203 analysis (Tables 1 and 2). One of these groups included 2,4-hexadiene, cyclohexene and 1- 204 methylcyclopentene, the three candidates for the molecular formula C6H10, with 2,4-hexadiene 205 analytical standard provided as a mixture of cis,cis, trans,trans, trans,cis and cis,trans stereoisomers. 206 The individual analysis of 2,4-hexadiene showed that the 4 stereoisomers were separated from each 207 other and correctly identified (NIST match factor > 948). Then, we observed that one 2,4-hexadiene 208 stereoisomer was co-eluted with cyclohexene, both compounds sharing the same mass spectra 209 (Figure 2). On the other hand, 1-methylcyclopentene was well separated from the two other VOCs
210 (Figures 1 and 2). Another group consisted in cyclohexanone, cis-3-hexenal, 4-hexen-3-one, 4-methyl-2-pentenal, trans-2-hexenal and 4-methyl-3-penten-2-one, the six VOC candidates for the molecular formula C<sub>6</sub>H<sub>10</sub>O. Dehydrated hexanoic acid (C<sub>6</sub>H<sub>12</sub>O<sub>2</sub> - H<sub>2</sub>O → C<sub>6</sub>H<sub>10</sub>O) was also considered as another potential candidate since a signal corresponding to C<sub>6</sub>H<sub>10</sub>O was detected during LCU-PTR-TOF-MS analysis of hexanoic acid. All these compounds separated well from each other, except for the two stereoisomers cis-3-hexenal and trans-2-hexenal (both reported as “hexenal” in Figure 1), which co-eluted in both dimensions and shared the same mass spectra.
211
212
213
214
215
216
217 One third group included ethylbenzene, p-xylene and m-xylene, the three VOC candidates for the molecular formula C<sub>8</sub>H<sub>10</sub>. The two xylene isomers (both reported as “xylene” in Figure 1) did not differ from each other neither by chromatography nor mass spectrometry, but their retention time in the first chromatographic dimension was distinct of that of ethylbenzene.
218
219
220

221 All the other VOCs corresponding to molecular formulas C<sub>6</sub>H<sub>8</sub>O (2,4-hexadienal and 2-ethylfuran), C<sub>7</sub>H<sub>14</sub>O (4-heptanone, 2-heptanone, heptanal), C<sub>8</sub>H<sub>18</sub> (4-methylheptane), C<sub>9</sub>H<sub>18</sub>O (2-nonanone and nonanal), C<sub>10</sub>H<sub>22</sub> (2,4,6-trimethylheptane), C<sub>4</sub>H<sub>6</sub>O (2-butenal), C<sub>8</sub>H<sub>14</sub> (1,7-octadiene) and C<sub>7</sub>H<sub>15</sub>Cl (1-chloroheptane) were individually separated from the other 25 VOCs (Figure 1).
222
223
224
225

226 **Clinical samples analysis**

227 New breath samples were obtained from 23 patients admitted in the intensive care unit for an acute respiratory distress syndrome related to COVID-19, as proven by PCR analysis on respiratory samples. The main patient characteristics were as follows: 14 males and 9 females, mean age 74 years (range 30-93), 9 intubated and mechanically ventilated, 10 and 4 with high- or low-flow nasal oxygen, respectively.
228
229
230
231

232 Breath TD-GCxGC-TOF-MS analysis was carried out and we successfully identified four of the 26 previously described VOCs (cyclohexanone, cyclohexene, ethylbenzene and xylene) in a minimum of 8/23 patient samples (Table 3). As these VOCs were detected and identified in both clinical
samples and analytical standards, a level 1 annotation was reached. Representative chromatograms
for ethylbenzene and xylene, both candidates for the molecular formula C8H10, are shown in Figures
3 and 4. Besides the identification of breath VOCs in patient samples with analytical standards, the
utility of TD-GCxGC-MS analysis of clinical samples has been demonstrated by observing the TIC
signal, highlighting the separation in the second chromatographic dimension of numerous
compounds co-eluted in the first dimension (Figure 5).
241 DISCUSSION

242 In this study, we demonstrate how to leverage the complementarity between online analysis
243 techniques and hyphenated techniques to improve the annotation of potential exhaled breath
244 biomarkers. The highest level of annotation can be achieved through the use of analytical standards
245 and comprehensive TD-GCxGC-MS analyses, enabling access to the best level of chromatographic
246 separation of highly chemically-related compounds, including isomers, in exhaled breath. The
247 nature of the information provided by the complementarity between the methods extended to the
248 identification of molecules whose physicochemical properties do not allow detection by PTR-TOF-
249 MS, and therefore their subsequent exclusion from the list of potential biomarkers by this method.
250 As for real-time analysis of patient's breath, the PTR-TOF-MS analysis of analytical standards was
251 simple, rapid and straightforward, allowing the detection of 23 out of 26 compounds. The 11 VOCs
252 which were not detected during the analysis of aqueous solutions were all lipophilic compounds
253 with a LogP between 1.8 and 4.8, forming visible droplets during the water solubilisation attempt,
254 thus confirming poor water solubility. These compounds were then all successfully solubilised in
255 hexane, a solvent weakly ionisable in the proton transfer reaction source, which allowed their
256 detection. The absence of signal for 4-methylheptane, 1-chloroheptane, and 2,4,6-trimethylheptane
257 may be attributed to their belonging to the class of alkanes or halogenated organic compounds with
258 a saturated structure, making them challenging to ionise. For successful PTR-TOF-MS detection,
259 the VOC proton affinity must indeed exceed that of water (166 kcal/mol), and alkanes/halogenated
260 alkanes are known to have low proton affinity (24-26), thus hindering the detection of these VOCs,
261 as observed with 4-methylheptane in a study conducted by another group (25).

262 Ions different than the expected [M+H]$^+$ or isotope ions were also observed for 2-butenal, 2,4-
263 hexadienal, cis-3-hexenal, 4-hexen-3-one, 4-methyl-2-pentenal, 4-methyl-3-penten-2-one, trans-2-
264 hexenal, ethylbenzene, 1,7-octadiene, 4-heptanone, 2-heptanone and 2-nonanone. The detected *m/z*
265 were consistent with fragmentation ions (lower *m/z*), and corresponded to M$^+$ ions reported in the
NIST database for GC-MS analysis after electron ionisation (taking into account the delta related to the proton adduct of PTR-MS analysis), suggesting similar processes in the molecular fragmentation pattern. For 1-methylcyclopentene, hexanoic acid, heptanal and nonanal, both protonated fragment ions, also equivalent to some EI-GC-MS ions, and PTR-TOF-MS-specific ions were observed. These PTR-TOF-MS specific ions may be adduct ions for those with higher *m/z*, as *m/z* 135.10 which was already reported as a water adduct of hexanoic acid (27). The detection of fragment and adduct ions was already described with PTR-TOF-MS analysis (27-30). More specifically, the mass spectra of hexanoic acid (27), heptanal and nonanal (30) with PTR-MS analysis were reported in two recent studies, which showed several features common with those from the present study. With respect to hydrocarbons benzene, p-xylene and m-xylene, only the protonated molecular ions were also reported in previous works (28), also in agreement with our findings.

Regarding the hyphenated method, more compounds could be detected with this technique, but at the cost of more complex sampling conditions and labour-intensive and time-consuming analytical steps. The two successive orthogonal chromatographic separations carried out in TD-GCxGC-TOF-MS assisted in the differentiation of closely related or isomeric compounds, therefore overcoming the analytical performance reached with classical GC-MS. Additionally, the electron impact ionisation method increases the generation of fragment ions from a single compound, thus enriching the level of information obtained when compared to soft ionisation methods. Altogether, improved chromatographic resolution and mass spectrum enhanced the identification of VOCs, as the co-elution of compounds in a single chromatographic dimension interferes with the queries in spectral databases, although some overlap may persist to some degree for certain isomers.

TD-GCxGC-TOF-MS analysis of both analytical standards and clinical samples allowed to reach a level 1 annotation for 4 candidate biomarkers, which expression in human breath was reported by several groups (2). Cyclohexanone was already been reported as a breath biomarker of interest for
291 the diagnosis of infectious diseases such as COVID-19, ventilator-associated pneumonia or malaria
292 (31-33), the diagnosis of chronic kidney disease (34, 35) and colorectal cancer (36, 37).

293 Cyclohexene was found interesting for the diagnosis of pneumonia (38); ethylbenzene for
294 pulmonary aspergillosis (39), childhood asthma (40), idiopathic pulmonary fibrosis (41), lung (42)
295 or colorectal (36) cancers, while xylene for the diagnosis of colorectal (36) and gastric (43) cancers.
296 Hence, cyclohexanone, xylene and ethylbenzene were all three differentially regulated in the breath
297 from patients with colorectal cancer (36).

298 The main strength of our study is the use of clinical samples from COVID-19 patients as specimen
299 for extensive investigations with both online and hyphenated mass spectrometry methods, further
300 strengthening the interest for combining both, as well as including two-dimensional gas
301 chromatography in the analytical setup, which outperforms in terms of analytical performance and
302 annotation what can be achieved when a single chromatographic dimension is employed. With
303 respect to the study limitations, we had to make a choice in the number of VOCs selected from the
304 data of the initial clinical study using PTR-TOF-MS for the acquisition of analytical standards. This
305 choice was based on previous knowledge regarding the expression of VOCs in breath, as
306 interpretation solely based on chemical data could have led to a much higher number of compounds.
307 The use of a greater number of isomeric compounds may have further documented the benefits of
308 two-dimensional chromatography. Then, a restricted number of VOCs was detected in the samples
309 from new patients, and not in all samples. This may be explained by various factors, including the
310 varying delays between admission in the ICU and breath sampling, as well as the variability in the
311 severity of the illness. Finally, new samples were exclusively collected from patients with COVID-
312 19, for reasons solely related to the patient population admitted to the clinical service during the
313 conduct of this study. Controls from COVID-19 negative patients are absent which limits the ability
314 to conclusively establish the role of candidate biomarkers for these VOCs.
315 CONCLUSION

316 The novel contributions of this study lie in its methodological innovations and practical applications
317 with clinical breath samples. Firstly, the manuscript pioneers the integration of proton transfer
318 reaction-time of flight-mass spectrometry with two-dimensional gas chromatography-time of flight-
319 mass spectrometry for analysing volatile organic compounds in human breath, combining real-time
320 analysis with enhanced separation capabilities. While PTR-TOF-MS analysis enables online
321 quantitative analysis, making it possible to measure very rapid changes in breath composition, TD-
322 GCxGC-TOF-MS provides undeniable power for compound annotation outperforming
323 unidimensional analysis. This dual approach allows for more accurate identification of VOCs
324 discovered during the online analysis, using only a small number of clinical samples for time-
325 consuming chromatographic characterization, overcoming the limitations of each method when
326 used alone on entire patient cohorts. Secondly, it achieves a level 1 annotation of VOCs, ensuring
327 high confidence in biomarker identification through comprehensive analytical standards and TD-
328 GCxGC-MS analyses, marking a significant improvement over prior studies that often fall short of
329 this annotation level. Thirdly, the use of GCxGC-TOF-MS effectively addresses the challenge of
330 isomer separation, significantly improving the identification of isomers compared to traditional GC-
331 MS. Additionally, the study demonstrates the practical application of these techniques by analysing
332 clinical samples, underscoring the method's relevance and offering a robust framework for future
333 clinical studies. While analysing several tens or hundreds of samples from a clinical study using
334 chromatographic methods could prove to be tedious, a practical application of this analytical
335 pipeline could involve analysing only a subset of samples with both methods to gain knowledge on
336 VOC annotation. The perspectives consist in robust biomarker identification and subsequent
337 technology transfer, including using techniques other than mass spectrometry, for the development
338 of large-scale tests and point-of-care devices, highlighting its significance in the field of
339 metabolomics.
340 **DECLARATIONS**

341

342 **Competing interests**

343 C.R., D.A. and S.G.D are named as inventors on a patent application covering breath analysis in

344 COVID-19 (WO 2022/058796, A method for analysing a breath sample for screening, diagnosis or
345 monitoring of SARS-CoV-2 carriage or infection (COVID-19) on humans). The authors declare no

346 other competing interest.

347

348 **Author contributions**

349 EL, HS, PM, SGD obtained clinical samples; EL, BZ and EB analyzed clinical samples and
350 analytical standards; SGD designed the study; HS, PM, DA were site investigators; EL, CR

351 analyzed the data; EL, PD, SGD interpreted the data; EL, SGD drafted the manuscript; CR, BZ, HS,
352 PM, DA, PD, EB revised the manuscript. All the authors have accepted responsibility for the entire

353 content of this submitted manuscript and approved submission.

354

355 **Ethics approval and source of biological materials**

356 Breath samples were obtained from patients with COVID-19 enrolled in the RECORDS trial
357 (NCT04280497). The study was approved by an ethics committee (Comite de Protection des

358 Personnes EST I, Dijon, France; reference 20.03.10.51415).

359

360 **Funding**

361 This work was supported by national programs and grants both under the supervision of Agence

362 Nationale de la Recherche (COVINOse, ANR-21-CO12-0004; RHU4 RECORDS, Programme

363 d'Investissements d'Avenir, ANR-18-RHUS-0004 and IHU PROMETHEUS, France 2030
364 program, ANR-23-IAHU-0004); Région Île de France (VolatolHom, SESAME 2016 and

365 MeLoMane, DIM 1HEALTH 2019) and Fondation Foch (VolatolHom and VOC-Info).
366

367 Acknowledgements

368 None
369 REFERENCES

370 1. Amann A, Costello Bde L, Miekisch W, Schubert J, Buszewski B, Pleil J, et al. The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. J Breath Res. 2014;8(3):034001.

373 2. Drabinska N, Flynn C, Ratcliffe N, Belluomo I, Myridakis A, Gould O, et al. A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome. J Breath Res. 2021;15(3).

376 3. Blanchet L, Smolinska A, Baranska A, Tigchelaar E, Swertz M, Zhernakova A, et al. Factors that influence the volatile organic compound content in human breath. J Breath Res. 2017;11(1):016013.

379 4. Longo V, Forleo A, Ferramosca A, Notari T, Pappalardo S, Siciliano P, et al. Blood, urine and semen Volatile Organic Compound (VOC) pattern analysis for assessing health environmental impact in highly polluted areas in Italy. Environ Pollut. 2021;286:117410.

382 5. Paciencia I, Madureira J, Rufo J, Moreira A, Fernandes Ede O. A systematic review of evidence and implications of spatial and seasonal variations of volatile organic compounds (VOC) in indoor human environments. J Toxicol Environ Health B Crit Rev. 2016;19(2):47-64.

385 6. Yang S, Li X, Song M, Liu Y, Yu X, Chen S, et al. Characteristics and sources of volatile organic compounds during pollution episodes and clean periods in the Beijing-Tianjin-Hebei region. Sci Total Environ. 2021;799:149491.

388 7. Weisel CP, Alimokhtari S, Sanders PF. Indoor air VOC concentrations in suburban and rural New Jersey. Environ Sci Technol. 2008;42(22):8231-8.

390 8. Salman D, Ibrahim W, Kanabar A, Joyce A, Zhao B, Singapuri A, et al. The variability of volatile organic compounds in the indoor air of clinical environments. J Breath Res. 2021;16(1).
392 9. Schleich FN, Zanella D, Stefanuto PH, Bessonov K, Smolinska A, Dallinga JW, et al.
393 Exhaled Volatile Organic Compounds Are Able to Discriminate between Neutrophilic and
394 Eosinophilic Asthma. Am J Respir Crit Care Med. 2019;200(4):444-53.

395 10. Ibrahim W, Carr L, Cordell R, Wilde MJ, Salman D, Monks PS, et al. Breathomics for the
396 clinician: the use of volatile organic compounds in respiratory diseases. Thorax. 2021;76(5):514-21.

397 11. Roquencourt C, Salvator H, Bardin E, Lamy E, Farfour E, Naline E, et al. Enhanced real-
398 time mass spectrometry breath analysis for the diagnosis of COVID-19. ERJ Open Res. 2023;9(5).

399 12. Grassin-Delyle S, Roquencourt C, Moine P, Saffroy G, Carn S, Heming N, et al.
400 Metabolomics of exhaled breath in critically ill COVID-19 patients: A pilot study. EBioMedicine.
401 2021;63:103154.

402 13. Belizario JE, Faintuch J, Malpartida MG. Breath Biopsy and Discovery of Exclusive
403 Volatile Organic Compounds for Diagnosis of Infectious Diseases. Front Cell Infect Microbiol.
404 2020;10:564194.

405 14. Salek RM, Steinbeck C, Viant MR, Goodacre R, Dunn WB. The role of reporting standards
406 for metabolite annotation and identification in metabolomic studies. Gigascience. 2013;2(1):13.

407 15. Schymanski EL, Jeon J, Gulde R, Fenner K, Ruff M, Singer HP, et al. Identifying small
408 molecules via high resolution mass spectrometry: communicating confidence. Environ Sci Technol.
409 2014;48(4):2097-8.

410 16. Sumner LW, Amberg A, Barrett D, Beale MH, Beger R, Daykin CA, et al. Proposed
411 minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG)
412 Metabolomics Standards Initiative (MSI). Metabolomics. 2007;3(3):211-21.

413 17. Majchrzak T, Wojnowski W, Lubinska-Szczygel M, Rozanska A, Namiesnik J, Dymerski T.
414 PTR-MS and GC-MS as complementary techniques for analysis of volatiles: A tutorial review.
415 Anal Chim Acta. 2018;1035:1-13.
416 18. Phillips M, Cataneo RN, Chaturvedi A, Kaplan PD, Libardoni M, Mundada M, et al.

417 Detection of an extended human volatome with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. PLoS One. 2013;8(9):e75274.

419 19. Gould O, Drabinska N, Ratcliffe N, de Lacy Costello B. Hyphenated Mass Spectrometry versus Real-Time Mass Spectrometry Techniques for the Detection of Volatile Compounds from the Human Body. Molecules. 2021;26(23).

420 20. Meurs J, Sakkoula E, Cristescu SM. Real-Time Non-Invasive Monitoring of Short-Chain Fatty Acids in Exhaled Breath. Front Chem. 2022;10:853541.

424 21. Roslund K, Lehto M, Pussinen P, Hartonen K, Groop PH, Halonen L, et al. Identifying volatile in vitro biomarkers for oral bacteria with proton-transfer-reaction mass spectrometry and gas chromatography-mass spectrometry. Sci Rep. 2021;11(1):16897.

427 22. Roquencourt C, Grassin-Delyle S, Thevenot EA. ptairMS: real-time processing and analysis of PTR-TOF-MS data for biomarker discovery in exhaled breath. Bioinformatics. 2022;38(7):1930-429 7.

430 23. Kuo TC, Tan CE, Wang SY, Lin OA, Su BH, Hsu MT, et al. Human Breathomics Database. Database (Oxford). 2020.

431 24. Blake RS, Monks PS, Ellis AM. Proton-transfer reaction mass spectrometry. Chem Rev. 2009;109(3):861-96.

434 25. Mallette ND, Knighton WB, Strobel GA, Carlson RP, Peyton BM. Resolution of volatile fuel compound profiles from Asrocoryne sarcoides: a comparison by proton transfer reaction-mass spectrometry and solid phase microextraction gas chromatography-mass spectrometry. AMB Express. 2012;2(1):23.

438 26. Lindinger W, Hansel A, Jordan A. On-line monitoring of volatile organic compounds at pptv levels by means of proton-transfer-reaction mass spectrometry (PTR-MS) - Medical
440 applications, food control and environmental research. International Journal of Mass Spectrometry.

441 1998;173(3):191-241.

442 27. Romano A, Hanna GB. Identification and quantification of VOCs by proton transfer

443 reaction time of flight mass spectrometry: An experimental workflow for the optimization of
444 specificity, sensitivity, and accuracy. J Mass Spectrom. 2018;53(4):287-95.

445 28. Gueneron M, Erickson MH, VanderSchelden GS, Jobson BT. PTR-MS fragmentation
446 patterns of gasoline hydrocarbons. International Journal of Mass Spectrometry. 2015;379:97-109.

447 29. Schwarz K, Filipiak W, Amann A. Determining concentration patterns of volatile
448 compounds in exhaled breath by PTR-MS. J Breath Res. 2009;3(2):027002.

449 30. Ernle L, Wang NJ, Bekö G, Morrison G, Wargocki P, Weschler CJ, et al. Assessment of
450 aldehyde contributions to PTR-MS m/z 69.07 in indoor air measurements. Environ Sci-Atmos.
451 2023;3(9):1286-95.

452 31. Felton TW, Ahmed W, White IR, van Oort P, Rattray NJW, Docherty C, et al. Analysis of
453 exhaled breath to identify critically ill patients with ventilator-associated pneumonia. Anaesthesia.
454 2023;78(6):712-21.

455 32. Xue C, Xu X, Liu Z, Zhang Y, Xu Y, Niu J, et al. Intelligent COVID-19 screening platform
456 based on breath analysis. J Breath Res. 2022;17(1).

457 33. Berna AZ, McCarthy JS, Wang RX, Saliba KJ, Bravo FG, Cassells J, et al. Analysis of
458 Breath Specimens for Biomarkers of Plasmodium falciparum Infection. J Infect Dis.
459 2015;212(7):1120-8.

460 34. Seong SH, Kim HS, Lee YM, Kim JS, Park S, Oh J. Exploration of Potential Breath
461 Biomarkers of Chronic Kidney Disease through Thermal Desorption-Gas Chromatography/Mass
462 Spectrometry. Metabolites. 2023;13(7).

463 35. Mochalski P, King J, Haas M, Unterkofler K, Amann A, Mayer G. Blood and breath profiles
464 of volatile organic compounds in patients with end-stage renal disease. BMC Nephrol. 2014;15:43.
465 36. Kononova E, Mezmale L, Polaka I, Veliks V, Anarkulova L, Vilkoite I, et al. Breath

466 Fingerprint of Colorectal Cancer Patients Based on the Gas Chromatography-Mass Spectrometry

467 Analysis. Int J Mol Sci. 2024;25(3).

468 37. Wang C, Ke C, Wang X, Chi C, Guo L, Luo S, et al. Noninvasive detection of colorectal
cancer by analysis of exhaled breath. Anal Bioanal Chem. 2014;406(19):4757-63.

470 38. van Oort PM, de Bruin S, Weda H, Knobel HH, Schultz MJ, Bos LD, et al. Exhaled Breath

471 Metabolomics for the Diagnosis of Pneumonia in Intubated and Mechanically-Ventilated Intensive
472 Care Unit (ICU)-Patients. Int J Mol Sci. 2017;18(2).

473 39. Li ZT, Zeng PY, Chen ZM, Guan WJ, Wang T, Lin Y, et al. Exhaled Volatile Organic

474 Compounds for Identifying Patients With Chronic Pulmonary Aspergillosis. Front Med (Lausanne).
475 2021;8:720119.

476 40. Gahleitner F, Guallar-Hoyas C, Beardsmore CS, Pandya HC, Thomas CP. Metabolomics
477 pilot study to identify volatile organic compound markers of childhood asthma in exhaled breath.
478 Bioanalysis. 2013;5(18):2239-47.

479 41. Yamada YI, Yamada G, Otsuka M, Nishikiori H, Ikeda K, Umeda Y, et al. Volatile Organic
480 Compounds in Exhaled Breath of Idiopathic Pulmonary Fibrosis for Discrimination from Healthy
481 Subjects. Lung. 2017;195(2):247-54.

482 42. Koureas M, Kirgou P, Amoutzias G, Hadjichristodoulou C, Gourgoulianis K, Tsakalof A.
483 Target Analysis of Volatile Organic Compounds in Exhaled Breath for Lung Cancer Discrimination
484 from Other Pulmonary Diseases and Healthy Persons. Metabolites. 2020;10(8).

485 43. Hong Y, Che X, Su H, Mai Z, Huang Z, Huang W, et al. Exhaled breath analysis using on-
486 line preconcentration mass spectrometry for gastric cancer diagnosis. J Mass Spectrom.
487 2021;56(4):e4588.

488
TABLES

<table><caption>**Table 1:** LCU-PTR-TOF-MS and TD-GCxGC-TOF-MS analytical standard (n=26) analysis.</caption><thead><tr><th rowspan="2">Compound</th><th rowspan="2">CAS number</th><th rowspan="2">Molecular formula</th><th rowspan="2">logP</th><th colspan="3">PTR-TOF-MS analysis</th><th colspan="3">TD-GCxGC-TOF-MS analysis</th></tr><tr><th>Calculated [M+H]<sup>+</sup></th><th>Detection in water solution</th><th>Detection in hexane solution</th><th>1D retention time (min)</th><th>2D retention time (s)</th><th>Identification score (NIST database)</th></tr></thead><tbody><tr><td>2-butenal</td><td>4170-30-3</td><td>C4H6O</td><td>0.5</td><td>71.05</td><td>✓</td><td>-</td><td>8.3</td><td>0.900</td><td>958</td></tr><tr><td>benzene</td><td>71-43-2</td><td>C6H6</td><td>2.1</td><td>79.06</td><td>✗</td><td>✓</td><td>7.8</td><td>0.675</td><td>967</td></tr><tr><td>1-methylcyclopentene</td><td>693-89-0</td><td>C6H10</td><td>1.8</td><td rowspan="3">83.09</td><td>✗</td><td>✓</td><td>7.1</td><td>0.480</td><td>937</td></tr><tr><td>2,4-hexadiene</td><td>592-46-1</td><td>C6H10</td><td>2.8</td><td>✗</td><td>✓</td><td>6.5-7.3-7.6-7.9</td><td>0.510</td><td>956</td></tr><tr><td>cyclohexene</td><td>110-83-8</td><td>C6H10</td><td>2.9</td><td>✓</td><td>-</td><td>7.9</td><td>0.500</td><td>942</td></tr><tr><td>2,4-hexadienal</td><td>142-83-6</td><td>C6H8O</td><td>1.2</td><td rowspan="2">97.07</td><td>✓</td><td>-</td><td>17.4</td><td>1.165</td><td>933</td></tr><tr><td>2-ethylfuran</td><td>3208-16-0</td><td>C6H8O</td><td>2.4</td><td>✗</td><td>✓</td><td>8.7</td><td>0.660</td><td>944</td></tr><tr><td>cyclohexanone</td><td>108-94-1</td><td>C6H10O</td><td>0.8</td><td rowspan="5">99.08</td><td>✓</td><td>-</td><td>16.8</td><td>0.945</td><td>943</td></tr><tr><td>cis-3-hexenal</td><td>6789-80-6</td><td>C6H10O</td><td>1.1</td><td>✓</td><td>-</td><td>15.1</td><td>0.855</td><td>952</td></tr><tr><td>4-hexen-3-one</td><td>2497-21-4</td><td>C6H10O</td><td>1.2</td><td>✓</td><td>-</td><td>14.2</td><td>0.855</td><td>897</td></tr><tr><td>4-methyl-2-pentenal</td><td>5362-56-1</td><td>C6H10O</td><td>1.3</td><td>✓</td><td>-</td><td>13.7</td><td>0.805</td><td>899</td></tr><tr><td>4-methyl-3-penten-2-one</td><td>141-79-7</td><td>C6H10O</td><td>1.4</td><td>✓</td><td>-</td><td>12.7</td><td>0.805</td><td>930</td></tr><tr><td>trans-2-hexenal</td><td>6728-26-3</td><td>C6H10O</td><td>1.5</td><td rowspan="2">117.09</td><td>✓</td><td>-</td><td>15.1</td><td>0.855</td><td>949</td></tr><tr><td>hexanoic acid</td><td>142-62-1</td><td>C6H12O2</td><td>1.9</td><td>✓</td><td>-</td><td>20.3</td><td>0.750</td><td>920</td></tr><tr><td>ethylbenzene</td><td>100-41-4</td><td>C8H10</td><td>3.1</td><td rowspan="3">107.09</td><td>✗</td><td>✓</td><td>14.4</td><td>0.710</td><td>950</td></tr><tr><td>p-xylene</td><td>106-42-3</td><td>C8H10</td><td>3.2</td><td>✓</td><td>-</td><td>14.7</td><td>0.725</td><td>946</td></tr><tr><td>m-xylene</td><td>108-38-3</td><td>C8H10</td><td>3.2</td><td>✓</td><td>-</td><td>14.7</td><td>0.725</td><td>952</td></tr><tr><td>1,7-octadiene</td><td>3710-30-3</td><td>C8H14</td><td>3.5</td><td>111.12</td><td>✗</td><td>✓</td><td>11.0</td><td>0.505</td><td>940</td></tr><tr><td>4-heptanone</td><td>123-19-3</td><td>C7H14O</td><td>1.6</td><td rowspan="3">115.11</td><td>✓</td><td>-</td><td>15.3</td><td>0.660</td><td>934</td></tr><tr><td>2-heptanone</td><td>110-43-0</td><td>C7H14O</td><td>1.6</td><td>✓</td><td>-</td><td>16.1</td><td>0.710</td><td>954</td></tr><tr><td>heptanal</td><td>111-71-7</td><td>C7H14O</td><td>2.3</td><td>✗</td><td>✓</td><td>16.4</td><td>0.700</td><td>953</td></tr><tr><td>4-methylheptane</td><td>589-53-7</td><td>C8H18</td><td>4.3</td><td rowspan="2">135.09</td><td>✗</td><td>✗</td><td>10.3</td><td>0.450</td><td>944</td></tr><tr><td>1-chloroheptane</td><td>629-06-1</td><td>C7H15Cl</td><td>4.2</td><td>✗</td><td>✗</td><td>17.8</td><td>0.600</td><td>950</td></tr><tr><td>2-nonanone</td><td>821-55-6</td><td>C9H18O</td><td>3.1</td><td rowspan="3">143.15</td><td>✓</td><td>-</td><td>22.9</td><td>0.700</td><td>957</td></tr><tr><td>nonanal</td><td>124-19-6</td><td>C9H18O</td><td>3.3</td><td>✗</td><td>✓</td><td>23.3</td><td>0.695</td><td>957</td></tr><tr><td>2,4,6-trimethylheptane</td><td>14720-74-2</td><td>C10H22</td><td>4.8</td><td>✗</td><td>✗</td><td>14.0</td><td>0.445</td><td>954</td></tr></tbody></table>
<table><caption>**Table 2:** Ion profiles from the untargeted VOC standards LCU-PTR-TOF-MS analysis.</caption><thead><tr><th>Compound</th><th>Monoisotopic mass (g/mol)</th><th>m/z of ions (relative abundance) detected with LCU-PTR-TOF-MS analysis (this study)</th><th>m/z reported in the NIST database with GC-MS analysis and corresponding to PTR-TOF-MS features</th></tr></thead><tbody><tr><td>2-butenal</td><td>70.04</td><td>31.02 (4%), 41.04 (10%), 43.05 (16%), 71.05 (68%), 72.05 (2%)</td><td>All ions</td></tr><tr><td>benzene</td><td>78.05</td><td>79.06 (98%), 80.06 (2%)</td><td>All ions</td></tr><tr><td>1-methylcyclopentene</td><td rowspan="3">82.08</td><td>58.07 (3%), 81.07 (0.3%), 83.09 (4%), 84.09 (0.2%), 85.10 (89%), 86.11 (4%)</td><td>57 - 80 - 82 - 83 - 84</td></tr><tr><td>2,4-hexadiene</td><td>83.09 (96%), 84.09 (4%)</td><td>All ions</td></tr><tr><td>cyclohexene</td><td>83.09 (94%), 84.09 (6%)</td><td>All ions</td></tr><tr><td>2,4-hexadienal</td><td rowspan="2">96.06</td><td>43.02 (11%), 97.07 (85%), 98.07 (4%)</td><td>All ions</td></tr><tr><td>2-ethylfuran</td><td>97.07 (98%), 98.07 (2%)</td><td>All ions</td></tr><tr><td>cyclohexanone</td><td rowspan="8">98.07</td><td>99.08 (96%), 100.08 (4%)</td><td>All ions</td></tr><tr><td>cis-3-hexenal</td><td>31.02 (2%), 41.04 (1%), 43.03 (2%), 51.04 (1%), 57.03 (78%), 58.04 (1%), 81.07 (8%), 99.08 (7%), 100.08 (0.3%)</td><td>All ions</td></tr><tr><td>4-hexen-3-one</td><td>43.02 (17%), 99.08 (79%), 100.08 (4%)</td><td>All ions</td></tr><tr><td>4-methyl-2-pentenal</td><td>41.04 (2%), 43.02 (41%), 81.07 (30%), 99.08 (27%), 100.08 (1%)</td><td>All ions</td></tr><tr><td>4-methyl-3-penten-2-one</td><td>43.02 (21%), 99.08 (75%), 100.08 (3%)</td><td>All ions</td></tr><tr><td>trans-2-hexen-1-al</td><td>31.02 (2%), 41.04 (1%), 43.03 (2%), 51.04 (1%), 57.03 (78%), 58.04 (1%), 81.07 (8%), 99.08 (7%), 100.08 (0.3%)</td><td>All ions</td></tr><tr><td>hexanoic acid</td><td>116.08</td><td>30.03 (63%), 82.10 (2%), 99.08 (1%), 101.09 (3%), 117.09 (28%), 118.09 (2%), 135.10 (1%)</td><td>29 - 81 - 98 - 100 - 116 - 117</td></tr><tr><td>ethylbenzene</td><td rowspan="3">106.08</td><td>79.05 (61%), 107.09 (37%), 108.09 (2%)</td><td>All ions</td></tr><tr><td>p-xylene</td><td>107.09 (93%), 108.09 (7%)</td><td>All ions</td></tr><tr><td>m-xylene</td><td>107.09 (94%), 108.09 (6%)</td><td>All ions</td></tr><tr><td>1,7-octadiene</td><td>110.11</td><td>95.09 (4%), 97.10 (7%), 111.12 (84%), 112.12 (5%)</td><td>All ions</td></tr><tr><td>4-heptanone</td><td rowspan="3">114.10</td><td>73.06 (6%), 115.11 (90%), 116.12 (4%)</td><td>All ions</td></tr><tr><td>2-heptanone</td><td>45.03 (18%), 71.09 (6%), 115.11 (72%), 116.12 (4%)</td><td>All ions</td></tr><tr><td>heptanal</td><td>95.09 (0.3%), 97.10 (92%), 98.11 (3%), 99.12 (1%), 115.11 (3%), 116.12 (0.2%), 129.09 (0.3%), 131.11 (0.4%)</td><td>96 - 97 - 114 - 115</td></tr><tr><td>4-methylheptane</td><td>114.14</td><td>x</td><td>NA</td></tr><tr><td>1-chloroheptane</td><td>134.09</td><td>x</td><td>NA</td></tr><tr><td>2-nonanone</td><td rowspan="2">142.14</td><td>57.07 (19%), 83.09 (14%), 143.14 (62%), 144.15 (4%)</td><td>All</td></tr><tr><td>nonanal</td><td>83.09 (53%), 125.13 (10%), 143.14 (28%), 144.18 (1%), 159.14 (7%)</td><td>82 - 124 - 142</td></tr><tr><td>2,4,6-trimethylheptane</td><td>142.17</td><td>x</td><td>NA</td></tr></tbody></table>

Abundances are expressed as percentages of the total signal. Ions detected during PTR-TOF-MS analysis are expected to be protonated molecules (for example [M+H]$^+$), whereas ions generated after electron ionisation for TD-GCxGC-TOF-MS analysis are obtained by removal of an electron (M$^+$), therefore any ion that would be detected by the 2 techniques would have a difference of about 1 m/z unit, related to the proton adduct.
<table><caption>**Table 3:** VOCs detected in new COVID-19 positive patient samples (n = 23) with TD-GCxGC-TOF-MS analysis.</caption><thead><tr><td>VOC</td><td>Monoisotopic mass (g/mol)</td><td>Number of patients with VOC detected (total n=23)</td><td>Identification score (NIST database) - average (min-max)</td></tr></thead><tbody><tr><td>cyclohexene</td><td>82.08</td><td>13</td><td>847 (667-942)</td></tr><tr><td>cyclohexanone</td><td>98.07</td><td>8</td><td>794 (693-835)</td></tr><tr><td>p- or m-xylene</td><td>106.08</td><td>23</td><td>922 (807-957)</td></tr><tr><td>ethylbenzene</td><td>106.08</td><td>23</td><td>935 (926-945)</td></tr></tbody></table>
FIGURE CAPTIONS

**Figure 1: Contour plot of TD-GCxGC-TOF-MS analysis of the 26 VOC analytical standards.**

Representative 2D contour plot of a mixture of the 26 analytical standards. The black frames correspond to 3 isomers of 2,4-hexadiene.

**Figure 2: Contour plots and mass spectra of 2,4-hexadiene and cyclohexene (m/z 67).**

Representative contour plot (2A) of 1-methylcyclopentene and cyclohexene (top) and the four isomers of 2,4-hexadiene (bottom). Representative mass spectra (2B) of cyclohexene and 2,4-hexadiene.

**Figure 3: Mass spectra from clinical breath samples compared to ethylbenzene and xylene standards.**

**Figure 4: Contour plots of xylene and ethylbenzene standards, patient breath and blank samples (m/z 91).**

**Figure 5: Surface 3D plots of TD-GCxGC-TOF-MS analysis of breath samples from two representative patients.** The z axis represents the logarithm of the total ion current.