Dataset Information

An interoperability framework for multicentric breath metabolomic studies

ABSTRACT: Exhaled breath contains valuable information at the molecular level and offers promising potential for precision medicine. However, few breath tests transition to routine clinical practice, partly because of the missing validation in multicenter trials. Therefore, we developed and applied an interoperability framework for standardized multicenter data acquisition and processing for breath analysis with secondary electrospray ionization-high resolution mass spectrometry. We aimed to determine the technical variability and metabolic coverage. Comparison of multicenter data revealed a technical variability of ∼20% and a core signature of the human exhaled metabolome consisting of ∼850 features, corresponding mainly to amino acid, xenobiotic, and carbohydrate metabolic pathways. In addition, we found high inter-subject variability for certain metabolic classes (e.g., amino acids and fatty acids), whereas other regions such as the TCA cycle were relatively stable across subjects. The interoperability framework and overview of metabolic coverage presented here will pave the way for future large-scale multicenter trials.

INSTRUMENT(S): Direct infusion MS - positive, Direct infusion MS - negative

SUBMITTER: Kapil Dev Singh

PROVIDER: MTBLS5657 | MetaboLights | 2022-10-27

REPOSITORIES: MetaboLights

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An interoperability framework for multicentric breath metabolomic studies.

Gisler Amanda A Singh Kapil Dev KD Zeng Jiafa J Osswald Martin M Awchi Mo M Decrue Fabienne F Schmidt Felix F Sievi Noriane A NA Chen Xing X Usemann Jakob J Frey Urs U Kohler Malcolm M Li Xue X Sinues Pablo P

iScience 20221115 12

Exhaled breath contains valuable information at the molecular level and offers promising potential for precision medicine. However, few breath tests transition to routine clinical practice, partly because of the missing validation in multicenter trials. Therefore, we developed and applied an interoperability framework for standardized multicenter data acquisition and processing for breath analysis with secondary electrospray ionization-high resolution mass spectrometry. We aimed to determine the ...[more]

PMID: 36479147

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Project description:Despite the attractiveness of breath analysis as a non-invasive means to retrieve relevant metabolic information, its introduction into routine clinical practice remains a challenge. Among all the different analytical techniques available to interrogate exhaled breath, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) offers a number of advantages (e.g., real-time, yet wide, metabolome coverage) that makes it ideal for untargeted and targeted studies. However, so far, SESI-HRMS has relied mostly on lab-built prototypes, making it difficult to standardize breath sampling and subsequent analysis, hence preventing further developments such as multi-center clinical studies. To address this issue, we present here a number of new developments. In particular, we have characterized a new SESI interface featuring real-time readout of critical exhalation parameters such as CO2, exhalation flow rate, and exhaled volume. Four healthy subjects provided breath specimens over a period of 1 month to characterize the stability of the SESI-HRMS system. A first assessment of the repeatability of the system using a gas standard revealed a coefficient of variation (CV) of 2.9%. Three classes of aldehydes, namely 4-hydroxy-2-alkenals, 2-alkenals and 4-hydroxy-2,6-alkedienals―hypothesized to be markers of oxidative stress―were chosen as representative metabolites of interest to evaluate the repeatability and reproducibility of this breath analysis analytical platform. Median and interquartile ranges (IQRs) of CVs for CO2, exhalation flow rate, and exhaled volume were 3.2% (1.5%), 3.1% (1.9%), and 5.0% (4.6%), respectively. Despite the high repeatability observed for these parameters, we observed a systematic decay in the signal during repeated measurements for the shorter fatty aldehydes, which eventually reached a steady state after three/four repeated exhalations. In contrast, longer fatty aldehydes showed a steady behavior, independent of the number of repeated exhalation maneuvers. We hypothesize that this highly molecule-specific and individual-independent behavior may be explained by the fact that shorter aldehydes (with higher estimated blood-to-air partition coefficients; approaching 100) mainly get exchanged in the airways of the respiratory system, whereas the longer aldehydes (with smaller estimated blood-to-air partition coefficients; approaching 10) are thought to exchange mostly in the alveoli. Exclusion of the first three exhalations from the analysis led to a median CV (IQR) of 6.7 % (5.5 %) for the said classes of aldehydes. We found that such intra-subject variability is in general much lower than inter-subject variability (median relative differences between subjects 48.2%), suggesting that the system is suitable to capture such differences. No batch effect due to sampling date was observed, overall suggesting that the intra-subject variability measured for these series of aldehydes was biological rather than technical. High correlations found among the series of aldehydes support this notion. Finally, recommendations for breath sampling and analysis for SESI-HRMS users are provided with the aim of harmonizing procedures and improving future inter-laboratory comparisons.

Project description:Background: RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences among samples are beginning to surface. Biological variation has been reported to be larger than technical variation. In addition, technical variation has been reported to be in line with expectations due to random sampling. However, strategies for dealing with technical variation will differ depending on the magnitude. The size of technical variance, and the role of sampling are examined in this manuscript. Results: Independent Solexa/Illumina experiments containing technical replicates are analyzed. When coverage is low, large disagreements between technical replicates are apparent. Exon detection between technical replicates is highly variable when the coverage is less than 5 reads per nucleotide and estimates of gene expression are more likely to disagree when coverage is low. Although large disagreements in the estimates of expression are observed at all levels of coverage. Conclusions: Technical variability is too high to ignore. Technical variability results in inconsistent detection of exons at low levels of coverage. Further, the estimate of the relative abundance of a transcript can substantially disagree, even when coverage levels are high. This may be due to the low sampling fraction and if so, it will persist as an issue needing to be addressed in experimental design even as the next wave of technology produces larger numbers of reads. We provide practical recommendations for dealing with the technical variability, without dramatic cost increases. Three independent samples of D. simulans male heads were collected with each sample representing a unique pool of biological material. Each sample was prepared according to manufacturer's instructions and then the same library was run on two lanes of a Solexa/Illumina flow cell, resulting in two technical replicates for each biological replicate, runs were 36 base-pair paired end.

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Dataset Information

An interoperability framework for multicentric breath metabolomic studies

Publications

An interoperability framework for multicentric breath metabolomic studies.

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