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Metabolic effects of inhaled salbutamol determined by exhaled breath analysis


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We explore whether real-time breath analysis by high resolution mass spectrometry is suitable to monitor changes at the metabolic level due to inhaling bronchodilator medication. We compared the breath levels of metabolites in a group of patients (n = 50) at baseline and 10 and 30 min after inhalation of 200 μg salbutamol. The same procedure was performed with a group of controls (n = 48) inhaling a placebo spray. A total of 131 mass spectral features were significantly altered as a result of inhaling medication, but not after inhaling placebo. We found that homologous series of chemical classes correlated strongly with each other, strengthening the notion that certain biochemical processes can be monitored. For example, a series of fatty acids was found to be increased after salbutamol intake, suggesting lipolysis stimulation. Peaks corresponding to salbutamol, its main metabolite salbutamol-4-O-sulfate and formoterol were found to be generally increased in patients inhaling the drugs on an as-needed basis, as compared to non-medicated volunteers. Overall, these results suggest such real-time breath analysis is a useful tool for non-invasive therapeutic drug monitoring.
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Metabolic effects of inhaled salbutamol determined by exhaled breath
To cite this article: Martin T Gaugg et al 2017 J. Breath Res. 11 046004
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J. Breath Res. 11 (2017)046004
Metabolic effects of inhaled salbutamol determined by exhaled
breath analysis
Martin T Gaugg
, Anna Engler
, Yvonne Nussbaumer-Ochsner
, Lukas Bregy
, Anna S Stöberl
Thomas Gaisl
, Tobias Bruderer
, Renato Zenobi
, Malcolm Kohler
and Pablo Martinez-Lozano Sinues
Department of Chemistry and Applied Biosciences, Swiss Federal Institute of Technology, Zurich, Switzerland
Sleep Disorders Centre and Pulmonary Division, University Hospital of Zurich, Zurich, Switzerland
University Childrens Hospital Basel, University of Basel (Switzerland)
Equal contribution to this work.
Keywords: bronchodilator, metabolism, breath analysis
Supplementary material for this article is available online
We explore whether real-time breath analysis by high resolution mass spectrometry is suitable to
monitor changes at the metabolic level due to inhaling bronchodilator medication. We compared the
breath levels of metabolites in a group of patients (n=50)at baseline and 10 and 30 min after
inhalation of 200 μg salbutamol. The same procedure was performed with a group of controls
(n=48)inhaling a placebo spray. A total of 131 mass spectral features were signicantly altered as a
result of inhaling medication, but not after inhaling placebo. We found that homologous series of
chemical classes correlated strongly with each other, strengthening the notion that certain biochemical
processes can be monitored. For example, a series of fatty acids was found to be increased after
salbutamol intake, suggesting lipolysis stimulation. Peaks corresponding to salbutamol, its main
metabolite salbutamol-4-O-sulfate and formoterol were found to be generally increased in patients
inhaling the drugs on an as-needed basis, as compared to non-medicated volunteers. Overall, these
results suggest such real-time breath analysis is a useful tool for non-invasive therapeutic drug
Inhaling drugs is an attractive administration route
due to rapid absorption into the systemic circulation
and low concentrations of drug-metabolizing enzymes
in the lungs compared with the oral route [1].In
addition, it provides rapid local effects in the lung,
minimizing systemic drug effects. For these reasons,
inhaled medications have been used for many years for
the treatment of respiratory diseases (i.e. lungs are the
target organs), as well as more recently to treat
systemic diseases (e.g. diabetes)[1,2]. During drug
development programs, optimal aerosol particle size is
sought, to target the optimal site of deposition.
Typically, clinical response (e.g. forced expiratory
volume in 1 s (FEV
)) is assessed upon drug inhalation.
Parallel determination of drug response at a molecular
level is of course needed to fully understand mechan-
isms of action. Metabolic proling of body uids is a
possible approach to quantifying physiological
response to inhaled medication [3,4]. For example, a
recent nuclear magnetic resonance-based serum and
urine metabolomics study has mapped the overall
metabolic changes after inhalation of budesonide and
salbutamol in asthmatic children during acute exacer-
bation, concluding that seven metabolic pathways
were altered as a result [5]. However, inhaled drugs
tend to act quickly (e.g. hydrophobic molecules
absorbed within seconds)[1], posing some challenges
to the capture of highly dynamic responses to plasma-
or urine-based metabolomics. In addition, sample
collection [6]and manipulation [7,8], as well as
subjecting metabolites to harsh processes (e.g. heat
leading to thermal degradation [9])may lead to biased
results. To overcome these issues, we propose that
in vivo, real-time analysis of exhaled breath metabo-
lites provides an attractive means to track response to
inhaled medication rapidly and non-invasively.
22 April 2017
28 June 2017
30 June 2017
13 September 2017
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© 2017 IOP Publishing Ltd
Selected ion ow tube- and proton transfer reaction-
mass spectrometry (SIFT-MS and PTR-MS)are two
real-time techniques that have been widely used in a
clinical context [1012], although few examples can be
found in the literature for monitoring therapeutic
intervention [1316].
To prove this novel concept, we used secondary
electrospray ionization [17]-high resolution mass
spectrometry (SESI-HRMS)in this work to study
changes in endogenous metabolites in response to
inhaled medication, in contrast to a group inhaling
placebo. By using a placebo inhaler identical to the
medication inhaler except for the active ingredient, we
ruled out confounding factors such as contamination
of the oral cavity or changes due to the inhalation
maneuver. We chose to study the effect of salbutamol,
which is a short-acting bronchodilator widely used in
the treatment of obstructive lung diseases such as
asthma and chronic obstructive pulmonary disease
A total of 98 participants were included in this study:
48 inhaled placebo and 50 inhaled salbutamol. Of the
48 subjects inhaling placebo, eight suffered from
asthma and 40 did not have any lung disease. Of the 50
patients inhaling salbutamol, 13 suffered from asthma
and 37 suffered from moderate to severe COPD. The
anthropometric data is shown in table 1. Participants
were asked to refrain from eating, drinking (except
water), chewing gum, smoking and brushing their
teeth at least 1 h prior to measurement. The study was
approved by the local ethical committee (PB_2016-
00421, KEK-ZH-Nr. 2015-0148, KEK-ZH-Nr. 2014-
0088)and all subjects gave written, informed consent
to participate.
Real-time breath measurements
Exhaled breath analysis was performed at baseline, 10
and 30 min after the inhalation of 200 μg salbutamol
(n=50)or placebo (n=48). The placebo contained
only norurane. Figure 1(a)shows the timing used in
the study. Figure 1(b)displays a picture of the modied
mass spectrometer (Sciex Triple TOF 5600+)to allow
breath analysis by SESI-HRMS. The breath analysis
approach has been described in greater detail
elsewhere [19,20]. In brief, the atmospheric pressure
ion source of a quadrupole-time-of-ight mass
spectrometer was replaced by a lab-built SESI chamber
[21,22]. A nano-electrospray of 0.1% formic acid in
water was infused at 200 nl min
through a silica
capillary (PicoTip emitterO.D. 360 μmI.D.
20 μm). The electrospray was operated in the cone-jet
mode [23,24]and its current (100 nA)constantly
monitored. In addition, a lens was used sporadically to
visually inspect the Taylor cone [25]. The breath
sampling tube connected to the SESI chamber con-
sisted of stainless steel (6 mm I.D.), and was heated to
80 °C to prevent water condensation and adsorption
of low-volatility metabolites onto the walls. In order to
avoid confounding factors such as differences in
exhalation maneuvers [26], the sampling protocol was
standardized across all participants. The subjects
would typically provide vesix replicate exhalations.
Full exhalations were provided at a constant ow rate
by keeping the pressure in the sampling line at 12 mbar
(regulated by bio-feedback by the breathing subjects).
Measurements were recorded in positive and negative
ion mode, leading to mainly protonated and deproto-
nated species, respectively. The mass range in positive
ion mode was 40700 Da and in negative ion mode
40450 Da. Accumulation time was set to 1 s.
Compound identication
Identication of 10-hydroxydecanoic acid was per-
formed using on-line MS/MS experiments as well as
UHPLC-MS/MS experiments of exhaled breath con-
densate (EBC)and a standard. EBC was collected using
a sampling device constructed in-house following the
guidelines set by the ATS/ERS task force [27]. Two
healthy, non-smoking subjects were asked to exhale
into a glass cold trap. The collected EBC samples were
pooled (V
=32 ml), 0.5 ml were extracted and
stored at 4 °C and the remainder lyophilized to dryness
[28]. The residue was then reconstituted in a mixture
of 142.5 μl of the previously aliquoted EBC, 7.5 μl
methanol and acidied with 0.1% formic acid. This
up-concentrated sample was directly subjected to
UHPLC-HRMS/MS analysis. UHPLC separation was
done on an ACQUITY UPLC system (Waters, MA,
USA)with a C18 column (1.7 μm, 2.1×50 mm,
Waters)with pre-column lter. The ow rate was set
to 500 μl min
using a binary mixture of solvent A
(water with 0.1% formic acid)and solvent B (methanol
Table 1. Anthropometric data of the participants in this study.
Placebo (n=48)Salbutamol (n=50)
Mean age±SD (years)41.8±17.8 55.3±14.2
Male/Female 22/26 28/22
COPD(GOLD1-2/GOLD3-4)/Asthma/Healthy 0/8/40 37(8/29)/13/0
Mean FEV1 pre±SD (% pred)96.2±12.1 50.8±25.1
Mean FVC pre±SD (% pred)101.5±11.9 80.0±20.6
Smokers/Non-smokers/Ex-smokers 9/33/68/13/29
J. Breath Res. 11 (2017)046004 M T Gaugg et al
with 0.1% formic acid). The 10-hydroxydecanoic acid
standard (Apollo Scientic Ltd)was prepared at a
concentration of 100 ng ml
and analyzed with an
injection volume of 10 μl. A Triple TOF 5600+(AB
Sciex, Concord, ON, Canada)mass spectrometer was
used to measure a mass range of 40500 Da in negative
ion mode, with 15 ppm mass accuracy. Collision
energy was set at 40±30 eV.
Data analysis
.wiff (Sciexs proprietary format)data was
converted into
.mzXML format via MSConvert
(Proteowizard)[29]. Each sample le was interpolated
linearly and centroided, generating as a result a m/z
list of 1208 peaks present in at least 40% of the samples.
The mass spectra were normalized dividing by the sum
of a set of 904 signals found to be present in 90% of our
samples. We then computed the log
of the fold change
(i.e. ratio between measurements after 10 min over
baseline and after 30 min over baseline). Signicant
differences in exhaled metabolite levels in response to
salbutamol, but not to placebo inhalation were sought.
A paired two-tailed t-test followed by estimation of
false discovery rate (FDR)in multiple comparisons
was used for this purpose [30]. Statistical signicance
was set to FDR<0.05. We further considered only
the signals changing signicantly after 10 and 30 min
of salbutamol inhalation, but not changing signi-
cantly after placebo inhalation. Among the signicant
ones, we report here only those signals changing by at
least log
(fold change)>0.15 after 10 or 30 min of
inhaling salbutamol. The signals satisfying these con-
ditions were subjected to an agglomerative hierarchi-
cal cluster tree (Ward method; Euclidean distance).In
order to identify groups of signals showing similar
behavior, we constructed agglomerative clusters using
a cutoff Euclidean distance of 5. Finally, for the set of
molecules that were chemically identied, we com-
puted the correlation coefcients between pairs of
variables for the group inhaling salbutamol.
Results and discussion
Monitoring of exhaled compounds to adjust inhaled
medication dose to maximize efcacy and minimize
toxicity is an attractive approach. For example, this
concept has been implemented by measuring exhaled
NO in asthmatic patients to titrate treatment with
inhaled corticosteroids [31]. In the present work we
have explored whether comprehensive real-time
breath analysis can assist in a similar approach towards
a more personalized therapeutic regime.
Metabolites levels are altered after salbutamol
inhalation, but not after placebo
Subjectsbreath was analyzed, detecting as a result
1208 features (866 and 342 features in positive and
negative mode, respectively)present in at least 40% of
the samples. A total of 131 mass spectral features were
found to be signicantly altered in response to
salbutamol inhalation, but not to placebo inhalation.
Table S1, available online at
046004/mmedia lists all of these along with their mean
changes, 95% condence intervals, p-values and FDR.
Figure 2shows the histograms of the log
(fold change)
for the 131 signicantly altered ions after 10 and
30 min of inhalation of salbutamol. The distributions
for the placebo group are fairly symmetrical around 0
(i.e. mean 10 min after placebo=0.0254; mean
30 min after placebo=0.0220). In contrast, the
salbutamol distributions are atter, and their means
are displaced to the right (mean 10 min after salbuta-
mol=0.1458; mean 30 min after placebo=0.1963),
suggesting a general increase of these exhaled
Among 131 altered signals, 121 increased, while 10
signals were reduced after salbutamol inhalation, but
did not change signicantly in the placebo group.
Figure 3shows the breath-to-breath time trace for one
selected compound (m/z 259.1903; C
)for one
subject before and after inhalation of placebo (a)and
for a different subject inhaling salbutamol (b). The
vesix replicate measurements within each time
point show a satisfactory repeatability (4.8% average
Figure 1. (a)Study timing; (b)Modied high resolution mass spectrometer featuring a SESI ion source to allow for real-time analysis
of exhaled metabolites.
J. Breath Res. 11 (2017)046004 M T Gaugg et al
coefcient of variation). Clearly, the breath levels of
this compound for this particular patient increased
signicantly shortly after salbutamol inhalation, and
this change could be easily captured by on-line breath
analysis. In contrast, the levels for the subject inhaling
just placebo did not vary signicantly. The overall pic-
ture of the trends for this compound for the placebo
and medication groups is shown in gures 2(b)and
(c), respectively. Mean log
(fold change)for the pla-
cebo group after 10 and 30 min was 0.01 (95%
CI=0.06/0.07; FDR=0.93)and 0.02 (95%
CI=0.12/0.07; FDR=0.7), respectively. In con-
trast, mean log
(fold change)for the salbutamol group
after 10 and 30 min was 0.19 (95% CI=0.10/0.28;
)and 0.26 (95% CI=0.12/0.4;
), respectively. However, despite
the signicant changes for this particular molecule
(molecular formula C
)in the salbutamol
group, there is clear inter-individual variability, with
some subjects experiencing no changes at all. This
seems to be in line with the known lack of response to
medication for large parts of the population. For
example, it has been estimated that a daunting 75%
96% do not respond to the top-ten grossing drugs in
the market. Our data suggests that breath analysis has
potential to contribute to the identication of sub-
populations of responders and non-responders, at
least for certain drugs such as bronchodilators.
Metabolite associations and compound
We attempted the chemical identication of some of
the exhaled metabolites, to provide a biochemical
interpretation of our results. First, we computed an
agglomerative hierarchical cluster tree (Ward method;
Euclidean distance)and subsequently constructed
clusters from the hierarchical cluster tree using as
cutoff a distance of 5. This resulted in 26 clusters of
signals behaving similarly. The resulting clusters are
listed in table S1. As a result, it became apparent that
homologous series of closely related molecular for-
mulae (and most likely compounds)tend to cluster
together. This is a rst indication that this real-time
technique is capable of capturing metabolic cascades
in response to medication. For example, cluster
number 16 consisted of acetic, propionic and butyric
acids, which were in all cases found to be increased
after salbutamol inhalation. Similarly, heptanoic,
octanoic and nonanoic acids [21]clustered together
(number 22)and were found to increase after salbuta-
mol inhalation. Another interesting series of com-
pounds was cluster number 10. They all have similar
molecular formulae and were detected in negative ion
polarity. Compounds detected by SESI-MS operated
in negative ion mode are dominated by deprotonated
acids [21,32]; thus, we hypothesize that these com-
pounds are likely fatty acids. This was conrmed by
deploying a comprehensive analytical strategy.
Figure 4shows experimental evidence indicating that
the molecular formula C
corresponded to 10-
Hydroxydecanoic acid. Figure 4(a)shows the extracted
ion chromatograms at m/z187.1339 in negative ion
mode for EBC and the standard of 10-hydroxydeca-
noic acid. Figure 4(b)shows a head-to-tail MS/MS for
EBC and the standard. The perfect match in retention
time and fragmentation pattern provides strong evi-
dence for 10-hydroxydecanoic acid in exhaled breath
condensate. Figure 4(c)shows the fragmentation
spectrum at m/z 187.1339 during a real-time exhala-
tion. The diagnostic fragments of this compound were
indeed present, indicating that 10-hydroxydecanoic
acid is present in exhaled in real-time and detected by
Figure 2. Salbutamol leads to different distribution of some compounds in breath as compared to placebo. Histograms of the log
change)after 10 and 30 min for 131 breath signals found to be signicantly altered in the salbutamol group (n=50), but not in the
placebo group (n=48).
J. Breath Res. 11 (2017)046004 M T Gaugg et al
Figure 3. Detection of rapid response to medication by breath analysis; exemplary raw time traces for one compound (C
)for a
subject before and after inhaling placebo (a)and for another patient inhaling medication (b). Note that in 3 min several replicate
exhalations were performed. Note also the signicant increase of this molecule after inhalation of 200 μg of salbutamol, but not after
inhaling placebo; the same trend was observed for the whole population investigated. Relative changes for the same exhaled molecule
for the (c)placebo (n=48)and (d)salbutamol (n=50)groups.
Figure 4. Identication of 10-hydroxydecanoic acid. (a)Extracted ion chromatograms of 187.1340±0.002 Da of EBC and standard
(normalized to target peak apex);(b)head-to-tail plot of the MS
spectra (precursor selection: 187.1 Da)of EBC and standard; (c)on-
line MS
(precursor selection: 187.1 Da)breath spectrum. Due to the preselection window of 1 Da, multiple precursor ions are
selected, leading to a complex fragmentation spectrum. Nonetheless, thanks to the high mass resolution of the TOF-analyzer, it is
possible to identify the fragments corresponding to 10-hydroxydecanoic acid (indicated with inverted triangles).
J. Breath Res. 11 (2017)046004 M T Gaugg et al
SESI-MS. However, it is obvious that other fragments
are also present, because the isolation window of the
quadrupole is 1 Da, leading to the fragmentation of all
the species present at nominal mass 187 Da. It is also
interesting to note that different isomers of 10-
hydroxydecanoic acid were found in breath conden-
sate (gure 4(a)). For example, the most abundant
peak in the chromatogram at retention time
3.55 min, corresponds to 3-hydroxydecanoic acid
(Gaugg et al in preparation), which is an intermediate
in fatty acid biosynthesis. It is therefore very likely that
all different isomers are exhaled simultaneously.
To better understand the interactions of 10-
hydroxydecanoic acid with the rest of the compounds
in the same cluster we computed their correlations (r)
for the salbutamol group and plotted the correlation
network. Figure 5(a)shows the results (only r>0.65
are shown). Overall, we found strong positive correla-
tions among the different nodes (i.e. molecules). The
strongest correlation (r=0.86)was between
and C
. The former of these is
Figure 5. Exhaled compounds with similar molecular formulae correlate with each other after exposure to salbutamol. (a)Fatty acids
correlation network after salbutamol inhalation. Each node represents one breath compound (molecular formula shown), and the
value on each bond is the correlation coefcient. The connection width is proportional to the correlation coefcient (i.e. the thicker
the line, the stronger the correlation). Only signicant correlations are shown (p<0.001 and r>0.65). Note the association between
hydroxydecanoic acid and C
and C
.(b)Correlation between hydroxydecanoic acid and C
and C
in the group of salbutamol inhalers (to ease visualization, two outliers are not shown).
J. Breath Res. 11 (2017)046004 M T Gaugg et al
sebacic acid (Gaugg et al in preparation), and the latter
an unsaturated form of it. As to the identied hydro-
xydecanoic acid, the network shows a correlation with
sebacic acid (r=0.7),C
(r=0.69). The striking correlation
between these compounds is demonstrated in
gure 5(b), which shows the log
(fold change)of
hydroxydecanoic vs. log
(fold change)for C
and C
. While the complete network
remains to be fully characterized, overall, our breath
analysis data are consistent with previous studies that
describe signicant increase of non-esteried fatty
acids [33], and in general with the lipolytic effects of
beta-adrenergic agonists [34]. Moreover, these chan-
ges in fatty acid concentrations are known to happen
very rapidly, in the order of minutes [35,36], in line
with our own observations here. Additional correla-
tion networks are shown in gure S1.
Drug detection
We have just discussed that SESI-HRMS seems to be
sensitive and selective enough to capture signicant
changes of exhaled metabolites such as fatty acids
shortly after salbutamol inhalation, in contrast to a
placebo group. We argue that such information may
provide a more comprehensive understanding of the
mechanism of action of drugs allowing, for example,
responders and non-responders to medication to be
identied [37]. Obviously, monitoring of the adminis-
tered drug itself would complement such metabolic
information. In this regard, we have recently shown
the potential of SESI-HRMS as a rapid and non-
invasive platform to perform pharmacokinetic studies
of injected drugs by measuring them in vivo, in mouse
breath [38,39]. Initially, we did not observe obvious
changes in salbutamol levels above the background
levels. One explanation could be that the chemical
background in the m/zregion where the salbutamol is
expected (i.e. m/z240.1594; [C
Figure 6. Tentative detection of drugs in exhaled breath. Real-time traces for protonated salbutamol (a)and its main metabolite
salbutamol-4-O-sulfate (b)for 40 controls who had never inhaled salbutamol and 13 patients inhaling salbutamol on an as-needed
basis. The highest levels were found for four patients suffering from COPD, suggesting that they inhale salbutamol more frequently
than the asthma patients. The insets show the mass spectra in the region of interest. The theoretical mass for both ions is indicated with
a vertical bar. The spectra suggest that care should be taken with the interpretation, because the peaks are not fully resolved at this mass
resolution (20 000).
J. Breath Res. 11 (2017)046004 M T Gaugg et al
generally very crowded. Figure 6(a)shows representa-
tive mass spectral data at nominal mass 240 along with
the chemical structure of salbutamol. For reference,
the theoretical exact mass where protonated salbuta-
mol would be expected is indicated with a vertical line.
Clearly, even at mass resolution as high as 20 000, the
separation capability is insufcient to discriminate
salbutamol from other isobaric species [20,40].We
nevertheless inspected the time traces for protonated
salbutamol, as well as for its main metabolite, salbuta-
mol-4-O-sulfate (gure 6(b);m/z320.1162;
)[41]. Figure 6shows the time
traces for salbutamol (a)and salbutamol-4-O-sulfate
(b)for the 40 healthy controls that had never inhaled
salbutamol and 13 patients that according to their
medical records inhale salbutamol on an as-needed
basis. The rst four of the latter were COPD patients,
and nine suffered from asthma. Note that the traces
shown correspond to the baseline measurement, when
salbutamol was not yet inhaled. While we cannot give
denite proof that these two mass spectral peaks
indeed correspond to salbutamol and its main meta-
bolite, the high correlation between the two sets of
time traces suggests an association. Also, the intensity
of the time traces seems in general higher in the
patients, especially in the COPD group.
To further investigate whether common broncho-
dilators can be detected in breath by SESI-HRMS, we
expanded our data analysis. In particular, according to
their medical records, fourteen of the patients were
inhaling formoterol on an as-needed basis. For-
moterol is a long-acting beta2-agonist used in the
management of asthma and COPD. Its chemical
structure is shown in gure 7, along with a typical mass
spectrum in the region of m/z345. The exact mass at
which this molecule would be expected in protonated
form [C
is m/z345.1809, which is
indicated in the mass spectrum by a vertical bar. As in
the case of salbutamol, many isobaric species prevent
us from clearly resolving the expected peak. However,
similarly to salbutamol, the time traces tend to be
higher in the patients using the medication on an as-
needed basis as compared to the healthy controls who
did not inhale any medication. Further investigations
via UPLC-MS/MS analysis of EBC and higher resolu-
tion mass spectrometry are required to conrm that
salbutamol and formoterol can be detected in breath.
However, the evidence shown in previous studies
where drugs such as ketamine (MW 237 Da)were
unambiguously detected in breath and correlated with
plasma levels [38,39]and the data shown in gures 6
and 7strongly supports the idea that SESI-HRMS is
suitable to monitor drugs and their metabolites in
breath. If this hypothesis is conrmed, it additionally
opens attractive possibilities to screen for doping
agents in breath of athletes. Note in this regard that all
beta2-agonists are currently prohibited in and out of
competition by the World Anti-Doping Agency [42].
While this work suggests that breath analysis could
contribute to ongoing efforts to elucidate response
mechanisms to therapeutic intervention and possibly
drug monitoring, this study hasof courselimita-
tions. For example, the unambiguous identity of the
molecules signicantly altered, precludes gaining fur-
ther insights on reprogrammed metabolic pathways
associated with salbutamol. In this regard, we cannot
entirely exclude the possibility that some of the chan-
ges observed are actually due to bronchial dilation,
resulting in improved gas exchange at the lung level.
Figure 7. Detection of drugs in exhaled breath. Real-time traces of protonated formoterol for 40 controls who had never inhaled
salbutamol and 24 patients inhaling formoterol on an as-needed basis. The insets show the mass spectrum in the region of interest.
The theoretical mass for protonated formoterol is indicated with a vertical bar. The spectrum suggests that care should be taken with
the interpretation, as the peaks are not fully resolved at this mass resolution (20 000).
J. Breath Res. 11 (2017)046004 M T Gaugg et al
We aimed at exploring the concept of inhalational
drug monitoring via real-time breath analysis. We
demonstrated that analysis of exhaled breath by real-
time mass spectrometry allows one to capture rapid
metabolic changes induced by inhaled medication. We
conrmed that the use of high resolution and high
mass accuracy mass analyzers with MS/MS capabil-
ities is crucial to determining the identity of some of
these compounds. We noted that homologous series
of compounds tended to correlate, suggesting that
cascades of metabolic changes were monitored. For
example, observed intensity changes of families of fatty
acids are consistent with previous blood-based studies.
Uncovering altered metabolic routes is likely to
provide insights into the mechanisms by which activa-
tion of beta-adrenergic receptors lead to relaxation of
smooth muscles in the airways. We also conclude that
a mass resolution of 20 000 is clearly insufcient to
unambiguously detect the inhaled drugs investigated
in this study. Our data suggests that higher resolving
power may allow for the unambiguous detection of
salbutamol and formoterol in breath. Overall, this
study supports the notion that therapeutic drug
monitoring is plausible via real-time breath analysis.
This work was supported by grants from the Swiss
National Science Foundation (CR23I2_149617 and
32003B_143365/1)and a Marie-Curie European
Reintegration Grant (to PMLS)within the 7th Eur-
opean Community Framework Programme (276860).
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... Only a few studies have focused on this topic. The study by Gaugg et al. showed significantly altered breath prints in adults, as assessed by SESI-HRMS, 10 and 30 min after inhalation of salbutamol, which was not shown after inhalation of the placebo [17]. However, in most studies, subjects are instructed to not use their medication 2 to 4 h prior to breath sampling. ...
... In our study, we were fairly sure about medication use as we only included children in the final analysis when they were both steroid-naïve at inclusion and considered treatment-adherent after the trial. As mentioned before, exact medication intake was uncertain in the study by Brinkman et al. [18], and the effects of salbutamol were only investigated until 30 min after inhalation in the study by Gaugg et al. [17]. An extension of the latter study, including a longer follow-up duration and the use of various drugs, is of pivotal importance to improving the standardisation and reliability of exhaled breath analysis. ...
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Exhaled breath analysis has great potential in diagnosing various respiratory and non-respiratory diseases. In this study, we investigated the influence of inhaled corticosteroids (ICS) on exhaled volatile organic compounds (VOCs) of wheezing preschool children. Furthermore, we assessed whether exhaled VOCs could predict a clinical steroid response in wheezing preschool children. We performed a crossover 8-week ICS trial, in which 147 children were included. Complete data were available for 89 children, of which 46 children were defined as steroid-responsive. Exhaled VOCs were measured by GC-tof-MS. Statistical analysis by means of Random Forest was used to investigate the effect of ICS on exhaled VOCs. A set of 20 VOCs could best discriminate between measurements before and after ICS treatment, with a sensitivity of 73% and specificity of 67% (area under ROC curve = 0.72). Most discriminative VOCs were branched C11H24, butanal, octanal, acetic acid and methylated pentane. Other VOCs predominantly included alkanes. Regularised multivariate analysis of variance (rMANOVA) was used to determine treatment response, which showed a significant effect between responders and non-responders (p < 0.01). These results show that ICS significantly altered the exhaled breath profiles of wheezing preschool children, irrespective of clinical treatment response. Furthermore, exhaled VOCs were capable of determining corticosteroid responsiveness in wheezing preschool children.
... Furthermore, Bland-Altman analysis [31] was performed on m/z features corresponding to previously reported human metabolites in SESI-HRMS experiments. A list of 88 compounds (50 in positive and 38 in negative ionization mode) from various chemical families was used in order to cover the broad range of compounds that are typically detectable in human breath with SESI-HRMS [14][15][16][32][33][34][35][36][37][38][39][40]. More details can be found in the supplementary Table S1. ...
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Environmental volatile organic compounds (VOCs) from the ambient air potentially influence on-line breath analysis measurements by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). The aim of this study was to investigate how inhaling through a VOC filter affects the detected breath profiles and whether it is feasible to integrate such filters into routine measurements. A total of 24 adult participants performed paired breath analysis measurements with and without the use of an activated carbon filter for inspiration. Concordance correlation coefficients (CCCs) and the Bland–Altman analysis were used to assess the agreement between the two methods. Additionally, the effect on a selection of known metabolites and contaminants was analyzed. Out of all the detected features, 78.3% showed at least a moderate agreement before and after filter usage (CCC > 0.9). The decrease in agreement of the remaining m/z features was mostly associated with reduced signal intensities after filter usage. Although a moderate-to-substantial concordance was found for almost 80% of the m/z features, the filter still had an effect by decreasing signal intensities, not only for contaminants, but also for some of the studied metabolites. Operationally, the use of the filter complicated and slowed down the conductance of measurements, limiting its applicability in clinical studies.
... Inspired by the metabolic insights we may gain from breath by SESI-HRMS, diverse clinical trials were performed in the past years together with our collaboration partners at the University Hospital Zurich and University Children's Hospital Zurich. Exhaled breath of patients with various respiratory diseases has been investigated including chronic obstructive pulmonary disease (COPD) and asthma, [7,8] cystic fibrosis (CF), [9] idiopathic pulmonary fibrosis (IPF), [10] and obstructive sleep apnea (OSA). [11] In parallel to the growing number of exploratory studies, the instrumental setup has been installed on multiple clinical sites in Switzerland, namely the University Hospital Zurich, the Children's University Hospital Zurich and the Children's University Hospital Basel, which facilitates future recruiting and measurements of participants. ...
Full-text available
Exhaled breath reveals insights about the metabolic state of the human body through the endo- and exogenous compounds it contains. The extent of detectable compounds, however, was revolutionized by the application of mass spectrometry. More specifically, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) enables the detection of a broad range of breath-derived compounds simultaneously and with high sensitivity. Together with its rapid and non-invasive nature, direct breath analysis by SESI-HRMS gained particular interest for clinical applications. Over the past years, various clinical trials successfully demonstrated the technology’s capability for biomarker discovery in exhaled breath in adults and more recently in children. Current challenges lie within the potential translation of SESI-HRMS into clinical settings and the associated requirements, such as unambiguous biomarker identification and validation, which were objectives of more recent studies.
... Metabolomics studies of albuterol response have been conducted in airway and serum samples. In a study by Gaugg et al., metabolomics analysis of exhaled breath condensate (EBC) collected 10-30 min after albuterol administration revealed 131 mass spectral features that were altered as compared to placebo [39]. The changes in these features were strongly correlated within a given chemical class, suggesting that changes in biochemical processes in response to albuterol can be monitored using EBC. ...
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Purpose of Review Several genome-wide association studies (GWASs) of bronchodilator response (BDR) to albuterol have been published over the past decade. This review describes current knowledge gaps, including pharmacogenetic studies of albuterol response in minority populations, effect modification of pharmacogenetic associations by age, and relevance of BDR phenotype characterization to pharmacogenetic findings. New approaches, such as leveraging additional “omics” data to focus pharmacogenetic interrogation, as well as developing polygenic risk scores in asthma treatment responses, are also discussed. Recent Findings Recent pharmacogenetic studies of albuterol response in minority populations have identified genetic polymorphisms in loci (DNAH5, NFKB1, PLCB1, ADAMTS3, COX18, and PRKG1), that are associated with BDR. Additional studies are needed to replicate these findings. Modification of the pharmacogenetic associations for SPATS2L and ASB3 polymorphisms by age has also been published. Evidence from metabolomic and epigenomic studies of BDR may point to new pharmacogenetic targets. Lastly, a polygenic risk score for response to albuterol has been developed but requires validation in additional cohorts. Summary In order to expand our knowledge of pharmacogenetics of BDR, additional studies in minority populations are needed. Consideration of effect modification by age and leverage of other “omics” data beyond genomics may also help uncover novel pharmacogenetic loci for use in precision medicine for asthma treatment.
... For plausibility control, we investigated the volatility and polarity for the putatively identified compounds. SESI can detect compounds with very high boiling points such as fatty acids up to 15 carbon atoms (pentadecanoic acid, boiling point 330.4 ± 5°C, [25]); amino acids, e.g., l-pyroglutamic acid (453.1 ± 38.0°C, [61]); or even formoterol (603.2 ± 55.0°C [62]). The vapor pressure for these compounds with relatively low volatility will be close to 0, therefore we decided to rely on boiling points as volatility estimates. ...
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Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa, S. pneumoniae, S. aureus, H. influenzae, E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.
... Human volatiles, such as exhaled breath and skin gas, contain hundreds of volatile organic compounds (VOCs), which can be collected noninvasively and easily [1][2][3]. Since the concentration of VOCs changes with diseases and metabolic abnormalities, measurement and analysis of VOCs in humans may assist in non-invasive evaluations of metabolism and disease screening [4][5][6][7][8][9]. ...
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We constructed an imaging system to measure the concentration of acetone gas by acetone reduction using secondary alcohol dehydrogenase (S-ADH). Reduced nicotinamide adenine dinucleotide (NADH) was used as an electron donor, and acetone was imaged by fluorescence detection of the decrease in the autofluorescence of NADH. In this system, S-ADH–immobilized membranes wetted with buffer solution containing NADH were placed in a dark box, and UV-LED excitation sheets and a high-sensitivity camera were installed on both sides of the optical axis to enable loading of acetone gas. A hydrophilic polytetrafluoroethylene (H-PTFE) membrane with low autofluorescence was used as a substrate, and honeycomb-like through-hole structures were fabricated using a CO2 laser device. After loading the enzyme membrane with acetone gas standards, a decrease in fluorescence intensity was observed in accordance with the concentration of acetone gas. The degree of decrease in fluorescence intensity was calculated using image analysis software; it was possible to quantify acetone gas at concentrations of 50–2000 ppb, a range that includes the exhaled breath concentration of acetone in healthy subjects. We applied this imaging system to measure the acetone gas in the air exhaled by a healthy individual during fasting.
... Salbutamol is a short-acting ␤ 2 adrenergic receptor agonist that works by causing relaxation of airway smooth muscle, used for the treatment of asthma. A SESI-MS study reported the detection of peaks corresponding to salbutamol, its main metabolite salbutamol-4-O-sulfate and formoterol to be generally increased in patients inhaling the drugs on an as-needed basis, as compared to non-medicated volunteers [49]. Their results suggested that higher resolving power may allow for the unambiguous detection of salbutamol and formoterol in breath. ...
The advantages that on-line breath analysis has shown in different fields have already made it stand as an interesting tool for pharmacokinetic studies. This review summarizes recent progress in the field, diving into the different analytical methods and the different advantages and hurdles encountered. We conclude that there is a wealth of limitations in the application of this technique, and key aspects like standardization are still outstanding. Nevertheless, this is an experimental field that has not yet been fully explored; and the advantages it offers for animal welfare, decrease in the amount of drug needed in experimental studies, and complementary insights to current pharmacological studies, warrant further exploration. Further studies are needed to overcome current limitations and incorporate this technique into the toolbox of pharmacological studies, both at an industrial and academic level.
... Over the last decade, a number of efforts have lifted this technology to transition from an interesting analytical platform to a standardised technique with real potential in clinical settings [4][5][6][7] . Based on prior work suggesting that this technology is capable of detecting drugs as well as drug-modulated metabolites in exhaled breath [8][9][10][11] , we hypothesised that this would be the case in a clinical setting, whereby it might contribute to improved phenotyping of patients with chronic epilepsy requiring TDM. Here we show that such breath-metabolomics approach has potential to reliably predict blood levels of valproic acid (VPA, an ASM) and to offer an additional patient screening layer by providing scores for side effects and response to ASMs with minimal interference into routine clinical practice and patient invasiveness. ...
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Background Therapeutic management of epilepsy remains a challenge, since optimal systemic antiseizure medication (ASM) concentrations do not always correlate with improved clinical outcome and minimal side effects. We tested the feasibility of noninvasive real-time breath metabolomics as an extension of traditional therapeutic drug monitoring for patient stratification by simultaneously monitoring drug-related and drug-modulated metabolites. Methods This proof-of-principle observational study involved 93 breath measurements of 54 paediatric patients monitored over a period of 2.5 years, along with an adult’s cohort of 37 patients measured in two different hospitals. Exhaled breath metabolome of epileptic patients was measured in real time using secondary electrospray ionisation–high-resolution mass spectrometry (SESI–HRMS). Results We show that systemic ASM concentrations could be predicted by the breath test. Total and free valproic acid (VPA, an ASM) is predicted with concordance correlation coefficient (CCC) of 0.63 and 0.66, respectively. We also find (i) high between- and within-subject heterogeneity in VPA metabolism; (ii) several amino acid metabolic pathways are significantly enriched ( p < 0.01) in patients suffering from side effects; (iii) tyrosine metabolism is significantly enriched ( p < 0.001), with downregulated pathway compounds in non-responders. Conclusions These results show that real-time breath analysis of epileptic patients provides reliable estimations of systemic drug concentrations along with risk estimates for drug response and side effects.
... There must be transfer of VOCs throughout the body, from the original source(s) to the final bodily fluid destination. As to whether sufficient chemical transfer occurs for detection, or whether the VOC [193,196,197,202,250,252,256,258] [6,57,134,260,268,275,279,307,309,321,324,329,336,338,347,348,369,370,375,377,378,380,394,407] [ 183,186,190,191,411,412] [ 155,156,[162][163][164] [134] [111,114,115,117,421,422] [ [193,194,196,197,202 [193,194,196,202,250,255,256,258] [408] [155] 65 N/a [182] survives the journey through the human body is questionable. Almost certainly the gut microbiome is the source for many chemicals, and sometimes there is a change of chemistry on route from the gut to e.g. the bladder. ...
This paper comprises an updated version of the 2014 review which reported 1846 volatile organic compounds (VOCs) identified from healthy humans. In total over 900 additional VOCs have been reported since the 2014 review and the VOCs from semen have been added. The numbers of VOCs found in breath and the other bodily fluids are: blood 379, breath 1488, faeces 443, milk 290, saliva 549, semen 196, skin 623 and urine 444. Compounds were assigned CAS registry numbers and named according to a common convention where possible. The compounds have been included in a single table with the source reference(s) for each VOC, an update on our 2014 paper. VOCs have also been grouped into tables according to their chemical class or functionality to permit easy comparison. Careful use of the database is needed, as a number of the identified VOCs only have level 2 - putative assignment, and only a small fraction of the reported VOCs have been validated by standards. Some clear differences are observed, for instance, a lack of esters in urine with a high number in faeces and breath. However, the lack of compounds from matrices such a semen and milk compared to breath for example could be due to the techniques used or reflect the intensity of effort e.g. there are few publications on VOCs from milk and semen compared to a large number for breath. The large number of volatiles reported from skin is partly due to the methodologies used, e.g. by collecting skin sebum (with dissolved VOCs and semi VOCs) onto glass beads or cotton pads and then heating to a high temperature to desorb VOCs. All compounds have been included as reported (unless there was a clear discrepancy between name and chemical structure), but there may be some mistaken assignations arising from the original publications, particularly for isomers. It is the authors' intention that this work will not only be a useful database of VOCs listed in the literature but will stimulate further study of VOCs from healthy individuals; for example more work is required to confirm the identification of these VOCs adhering to the principles outlined in the metabolomics standards initiative. Establishing a list of volatiles emanating from healthy individuals and increased understanding of VOC metabolic pathways is an important step for differentiating between diseases using VOCs.
Exhaled breath (EB) may contain metabolites that are closely related to human health conditions. Real time analysis of EB is important to study its true composition, however, it has been difficult. A robust ambient ionization mass spectrometry method using a modified direct analysis in real time (DART) ion source was developed for the online analysis of breath volatiles. The modified DART ion source can provide a confined region for direct sampling, rapid transmission and efficient ionization of exhaled breath. With different sampling methods, offline analysis and near real-time evaluation of exhaled breath were also achieved, and their unique molecular features were characterized. High resolution MS data aided the putative metabolite identification in breath samples, resulting in hundreds of volatile organic compounds being identified in the exhalome. The method was sensitive enough to be used for monitoring the breath feature changes after taking different food and over-the-counter medicine. Quantification was performed for pyridine and valeric acid with fasting and after ingesting different food. The developed method is fast, simple, versatile, and potentially useful for evaluating the true state of human exhaled breath.
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Inhaled budesonide and salbutamol represent the most important and frequently used drugs in asthmatic children during acute exacerbation. However, there is still no consensus about their resulting metabolic derangements; thus, the present study was conducted to determine the distinct metabolic profiles of these two drugs. A total of 69 children with asthma during acute exacerbation were included, and their serum and urine were investigated using high-resolution nuclear magnetic resonance (NMR). A metabolomics analysis was performed using a principal component analysis and orthogonal signal correction-partial least squares using SIMCA-P. The different metabolites were identified, and the distinct metabolic profiles were analysed using MetPA. A high-resolution NMR-based serum and urine metabolomics approach was established to study the overall metabolic changes after inhaled budesonide and salbutamol in asthmatic children during acute exacerbation. The perturbed metabolites included 22 different metabolites in the serum and 21 metabolites in the urine. Based on an integrated analysis, the changed metabolites included the following: increased 4-hydroxybutyrate, lactate, cis-aconitate, 5-hydroxyindoleacetate, taurine, trans-4-hydroxy-l-proline, tiglylglycine, 3-hydroxybutyrate, 3-methylhistidine, glucose, cis-aconitate, 2-deoxyinosine, and 2-aminoadipate; and decreased alanine, glycerol, arginine, glycylproline, 2-hydroxy-3-methylvalerate, creatine, citrulline, glutamate, asparagine, 2-hydroxyvalerate, citrate, homoserine, histamine, sn-glycero-3-phosphocholine, sarcosine, ornithine, creatinine, glycine, isoleucine, and trimethylamine N-oxide. The MetPA analysis revealed 7 involved metabolic pathways: arginine and proline metabolism; taurine and hypotaurine metabolism; glycine, serine and threonine metabolism; glyoxylate and dicarboxylate metabolism; methane metabolism; citrate cycle; and pyruvate metabolism.
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Breath volatile organic compound (VOC) analysis can open a non-invasive window onto pathological and metabolic processes in the body. Decades of clinical breath-gas analysis have revealed that changes in exhaled VOC concentrations are important rather than disease specific biomarkers. As physiological parameters, such as respiratory rate or cardiac output, have profound effects on exhaled VOCs, here we investigated VOC exhalation under respiratory manoeuvres. Breath VOCs were monitored by means of real-time mass-spectrometry during conventional FEV manoeuvres in 50 healthy humans. Simultaneously, we measured respiratory and hemodynamic parameters noninvasively. Tidal volume and minute ventilation increased by 292 and 171% during the manoeuvre. FEV manoeuvre induced substance specific changes in VOC concentrations. pET-CO2 and alveolar isoprene increased by 6 and 21% during maximum exhalation. Then they decreased by 18 and 37% at forced expiration mirroring cardiac output. Acetone concentrations rose by 4.5% despite increasing minute ventilation. Blood-borne furan and dimethyl-sulphide mimicked isoprene profile. Exogenous acetonitrile, sulphides, and most aliphatic and aromatic VOCs changed minimally. Reliable breath tests must avoid forced breathing. As isoprene exhalations mirrored FEV performances, endogenous VOCs might assure quality of lung function tests. Analysis of exhaled VOC concentrations can provide additional information on physiology of respiration and gas exchange.
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Key points: The World Anti-Doping Code (the Code) does place some restrictions on prescribing inhaled β2-agonists, but these can be overcome without jeopardising the treatment of elite athletes with asthma.While the Code permits the use of inhaled glucocorticoids without restriction, oral and intravenous glucocorticoids are prohibited, although a mechanism exists that allows them to be administered for acute severe asthma.Although asthmatic athletes achieved outstanding sporting success during the 1950s and 1960s before any anti-doping rules existed, since introduction of the Code's policies on some drugs to manage asthma results at the Olympic Games have revealed that athletes with confirmed asthma/airway hyperresponsiveness (AHR) have outperformed their non-asthmatic rivals.It appears that years of intensive endurance training can provoke airway injury, AHR and asthma in athletes without any past history of asthma. Although further research is needed, it appears that these consequences of airway injury may abate in some athletes after they have ceased intensive training. The World Anti-Doping Code (the Code) has not prevented asthmatic individuals from becoming elite athletes. This review examines those sections of the Code that are relevant to respiratory physicians who manage elite and sub-elite athletes with asthma. The restrictions that the Code places or may place on the prescription of drugs to prevent and treat asthma in athletes are discussed. In addition, the means by which respiratory physicians are able to treat their elite asthmatic athlete patients with drugs that are prohibited in sport are outlined, along with some of the pitfalls in such management and how best to prevent or minimise them.
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Online breath analysis is an attractive approach to track exhaled compounds without sample preparation. Current commercially available real-time breath analysis platforms require the purchase of a full mass spectrometer. Here we present an ion source compatible with virtually any preexisting atmospheric pressure ionization mass spectrometer that allows real-time analysis of breath. We illustrate the capabilities of such technological development by upgrading an orbitrap mass spectrometer. As a result, we detected compounds in exhaled breath between 70 and 900 Da, with a mass accuracy of typically <1 ppm; resolutions between m /Δ m 22 000 and 70 000 and fragmentation capabilities. The setup was tested in a pilot study, comparing the breath of smokers ( n = 9) and non-smokers ( n = 10). Exogenous compounds associated to smoking, as well as endogenous metabolites suggesting increased oxidative stress in smokers, were detected and in some cases identified unambiguously. Most of these compounds correlated significantly with smoking frequency and allowed accurate discrimination of smokers and non-smokers.
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Aspartame, methyl-L-α-aspartyl-L-phenylalaninate, is used worldwide as a sweetener in foods and drinks and is considered to be safe at an acceptable daily intake (ADI) of 40 mg per kg of body weight. This compound is completely hydrolyzed in the gastrointestinal tract to aspartic acid, phenylalanine and methanol, each being toxic at high levels. The objective of the present study was to quantify the volatile methanol component in the exhaled breath of ten healthy volunteers following the ingestion of a single ADI dose of aspartame. Direct on-line measurements of methanol concentration were made in the mouth and nose breath exhalations using selected ion flow tube mass spectrometry, SIFT-MS, several times before aspartame ingestion in order to establish individual pre-dose (baseline) levels and then during two hours post-ingestion to track their initial increase and subsequent decrease. The results show that breath methanol concentrations increased in all volunteers by 1082 ± 205 parts-per-billion by volume (ppbv) from their pre-ingestion values, which ranged from 193 to 436 ppbv to peak values ranging from 981-1622 ppbv, from which they slowly decreased. These observations agree quantitatively with a predicted increase of 1030 ppbv estimated using a one-compartment model of uniform dilution of the methanol generated from a known amount of aspartame throughout the total body water (including blood). In summary, an ADI dose of aspartame leads to a 3-6 fold increase of blood methanol concentration above the individual baseline values.
The time-of-day of drug application is an important factor in maximizing efficacy and minimizing toxicity. Real-time in vivo mass spectrometric breath analysis of mice was deployed to investigate time-of-day variation in ketamine metabolism. Different production rates of ketamine metabolites, including the recently described anti-depressant hydroxynorketamine, were found in opposite circadian phases. Thus, breath analysis has potential as a rapid and 3Rs (Replacement, Reduction and Refinement) conforming screening method to estimate the time-dependence of drug metabolism.
Rationale: Direct mass spectrometry (MS)-based methods make it possible to monitor the molecular compositions of hundreds of volatile organic compounds (VOCs) in exhaled human breath in real time. Mass resolution and mass accuracy play important roles for direct MS analysis, especially for the low-concentration isobaric compounds in non-target research. Methods: Direct detection of VOCs in exhaled breath of four healthy subjects (3 males and 1 female aged between 25 to 35 years old) has been performed by using secondary nano-electrospray ionization mass spectrometry (Sec-nanoESI-UHRMS) at resolutions (R) of 15,000, 30,000, 60,000 and 120,000. Results: For some low-intensity isobaric ions, they could be distinguished only when R ≥ 60,000, e.g., signals at m/z 96.9591 (sulfate/sulfuric acid), m/z 96.9687 (phosphate/phosphoric acid) and m/z 96.9756 ([C4 H2 O7 S]- ), m/z 234.1161 ([C10 H20 O3 NS]+ ) and m/z 234.1338 ([C10 H20 O5 N]+ ), m/z 119.0686 (isotope of indole) and m/z 119.0705 (an interfering signal), respectively. At R 120,000, the mass errors were obtained from a set of reference ions, and the values were ≤0.6 mDa for ions detected in positive detection mode and in the range of -1.0-1.1 mDa for the negative mode. These mass errors were used to exclusively identify unknown compounds detected in the breath samples. By utilizing the present setup, besides the normal VOCs reported previously, we detected non-volatile species (sulfate/sulfuric acid, silicate/silicic acid, phosphate/phosphoric acid and nitrate/nitric acid), dichlorobenzene and an ammonium adduct ([(C2 H6 SiO)6 + NH4 ]+ ), which were ascribed to exhaled particles, indoor air pollution and an endogenous source, respectively. Conclusions: For direct breath analysis, high mass resolution of ≥60,000 and mass errors of 1.0 mDa (absolute value) covering the mass range of interests (e.g., m/z 50-500) are necessary for the exploration and accurate identification of low-intensity unknown isobaric compounds in non-target research. Copyright © 2017 John Wiley & Sons, Ltd.
A study has been carried out of the volatile organic compounds present in the exhaled breath of 58 cystic fibrosis (CF) patients. An important observation is that the acetic acid vapour concentration measured by selected ion flow tube mass spectrometry (SIFT-MS) is significantly elevated in the exhaled breath of CF patients, independent of the Pseudomonas aeruginosa (PA) infection status (PA-infected median 170 ppbv; PA-negative median 182 ppbv), compared to that of healthy controls (median 48 ppbv). The cause for this may be decreased pH of the mucus lining the CF airways. Thus, we speculate that non-invasive measurement of breath acetic acid concentration could serve as an indicator of the acidity of the CF airways mucosa.
Current anti-doping analytical methods are tailored mainly to the targeting of known drugs and endogenous molecules. This causes difficulties in rapidly reacting to emerging threats such as designer drugs, biological therapeutic agents and technologies. Biomarkers are considered as a promising approach for the fight against these threats to sport. The main purpose of this study was to find surrogate biomarkers induced by the intake of small amounts of the model compound salbutamol and explore a sensitive approach to help screen for possible drug misuse. Urine samples (91) from athletes with detectable salbutamol (30) and negative samples (61) were analyzed using a UHPLC-MS. A third group (30) was created by spiking salbutamol into negative samples to eliminate confounding effects. Data were then analysed in XCMS to extract metabolic features. Orthogonal Partial Least Squares - Discriminant Analysis was performed to select features correlated with detectable salbutamol (pcorr >0.5) and ROC analysis was performed to measure the predictive potential of the markers. Univariate analysis including Mann-Whitney U test and Spearman's correlation was conducted on selected markers. A total of 7,000 metabolic features were parsed, one feature identified as hypoxanthine increased with salbutamol (p <0.001). The ROC curve of hypoxanthine returned an AUC of 0.79 (p <0.001). Correlation with salbutamol (r=0.415, p <0.01, Spearman's correlation) showed hypoxanthine and purine metabolism have association to salbutamol administration. This surrogate discovery approach needs further PK studies but in the meantime can be used as an intelligence-based complementary approach for targeting of athletes to be further tested.
Background Obstructive sleep apnoea (OSA) is highly prevalent and associated with cardiovascular and metabolic changes. OSA is usually diagnosed by polysomnography which is time-consuming and provides little information on the patient's phenotype thus limiting a personalised treatment approach. Exhaled breath contains information on metabolism which can be analysed by mass spectrometry within minutes. The objective of this study was to identify a breath profile in OSA recurrence by use of secondary-electrospray-ionization-mass spectrometry (SESI-MS). Methods Patients with OSA effectively treated with CPAP were randomised to either withdraw treatment (subtherapeutic CPAP) or continue therapeutic CPAP for 2 weeks. Exhaled breath analysis by untargeted SESI-MS was performed at baseline and 2 weeks after randomisation. The primary outcome was the change in exhaled molecular breath pattern. Results 30 patients with OSA were randomised and 26 completed the trial according to the protocol. CPAP withdrawal led to a recurrence of OSA (mean difference in change of oxygen desaturation index between groups +30.3/h; 95% CI 19.8/h,40.7/h, p<0.001) which was accompanied by a significant change in 62 exhaled features (16 metabolites identified). The panel of discriminating mass-spectral features allowed differentiation between treated and untreated OSA with a sensitivity of 92.9% and a specificity of 84.6%. Conclusion Exhaled breath analysis by SESI-MS allows rapid and accurate detection of OSA recurrence. The technique has the potential to characterise an individual's metabolic response to OSA and thus makes a comprehensible phenotyping of OSA possible. Trial registration number NCT02050425 (registered at